objc2-metal-performance-shaders 0.3.2

//! This file has been automatically generated by `objc2`'s `header-translator`.
//! DO NOT EDIT
use core::ffi::*;
use core::ptr::NonNull;
use objc2::__framework_prelude::*;
use objc2_foundation::*;
use objc2_metal::*;

use crate::*;

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNConvolutionDescriptor specifies a convolution descriptor
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiondescriptor?language=objc)
    #[unsafe(super(NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    pub struct MPSCNNConvolutionDescriptor;
);

extern_conformance!(
    unsafe impl NSCoding for MPSCNNConvolutionDescriptor {}
);

extern_conformance!(
    unsafe impl NSCopying for MPSCNNConvolutionDescriptor {}
);

unsafe impl CopyingHelper for MPSCNNConvolutionDescriptor {
    type Result = Self;
}

extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionDescriptor {}
);

extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNConvolutionDescriptor {}
);

impl MPSCNNConvolutionDescriptor {
    extern_methods!(
        /// The width of the filter window.  The default value is 3.
        /// Any positive non-zero value is valid, including even values.
        /// The position of the left edge of the filter window is given
        /// by offset.x - (kernelWidth>>1)
        #[unsafe(method(kernelWidth))]
        #[unsafe(method_family = none)]
        pub unsafe fn kernelWidth(&self) -> NSUInteger;

        /// Setter for [`kernelWidth`][Self::kernelWidth].
        #[unsafe(method(setKernelWidth:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setKernelWidth(&self, kernel_width: NSUInteger);

        /// The height of the filter window.  The default value is 3.
        /// Any positive non-zero value is valid, including even values.
        /// The position of the top edge of the filter window is given
        /// by offset.y - (kernelHeight>>1)
        #[unsafe(method(kernelHeight))]
        #[unsafe(method_family = none)]
        pub unsafe fn kernelHeight(&self) -> NSUInteger;

        /// Setter for [`kernelHeight`][Self::kernelHeight].
        #[unsafe(method(setKernelHeight:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setKernelHeight(&self, kernel_height: NSUInteger);

        /// The number of feature channels per pixel in the input image.
        #[unsafe(method(inputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn inputFeatureChannels(&self) -> NSUInteger;

        /// Setter for [`inputFeatureChannels`][Self::inputFeatureChannels].
        #[unsafe(method(setInputFeatureChannels:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setInputFeatureChannels(&self, input_feature_channels: NSUInteger);

        /// The number of feature channels per pixel in the output image.
        #[unsafe(method(outputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn outputFeatureChannels(&self) -> NSUInteger;

        /// Setter for [`outputFeatureChannels`][Self::outputFeatureChannels].
        #[unsafe(method(setOutputFeatureChannels:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setOutputFeatureChannels(&self, output_feature_channels: NSUInteger);

        /// The output stride (downsampling factor) in the x dimension. The default value is 1.
        #[unsafe(method(strideInPixelsX))]
        #[unsafe(method_family = none)]
        pub unsafe fn strideInPixelsX(&self) -> NSUInteger;

        /// Setter for [`strideInPixelsX`][Self::strideInPixelsX].
        #[unsafe(method(setStrideInPixelsX:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setStrideInPixelsX(&self, stride_in_pixels_x: NSUInteger);

        /// The output stride (downsampling factor) in the y dimension. The default value is 1.
        #[unsafe(method(strideInPixelsY))]
        #[unsafe(method_family = none)]
        pub unsafe fn strideInPixelsY(&self) -> NSUInteger;

        /// Setter for [`strideInPixelsY`][Self::strideInPixelsY].
        #[unsafe(method(setStrideInPixelsY:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setStrideInPixelsY(&self, stride_in_pixels_y: NSUInteger);

        /// Number of groups input and output channels are divided into. The default value is 1.
        /// Groups lets you reduce the parameterization. If groups is set to n, input is divided into n
        /// groups with inputFeatureChannels/n channels in each group. Similarly output is divided into
        /// n groups with outputFeatureChannels/n channels in each group. ith group in input is only
        /// connected to ith group in output so number of weights (parameters) needed is reduced by factor
        /// of n. Both inputFeatureChannels and outputFeatureChannels must be divisible by n and number of
        /// channels in each group must be multiple of 4.
        #[unsafe(method(groups))]
        #[unsafe(method_family = none)]
        pub unsafe fn groups(&self) -> NSUInteger;

        /// Setter for [`groups`][Self::groups].
        #[unsafe(method(setGroups:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setGroups(&self, groups: NSUInteger);

        /// dilationRateX property can be used to implement dilated convolution as described in
        /// https://arxiv.org/pdf/1511.07122v3.pdf
        /// to aggregate global information in dense prediction problems.
        /// Default value is 1. When set to value > 1, original kernel width, kW is dilated to
        ///
        /// kW_Dilated = (kW-1)*dilationRateX + 1
        ///
        /// by inserting d-1 zeros between consecutive entries in each row of the original kernel.
        /// The kernel is centered based on kW_Dilated.
        #[unsafe(method(dilationRateX))]
        #[unsafe(method_family = none)]
        pub unsafe fn dilationRateX(&self) -> NSUInteger;

        /// Setter for [`dilationRateX`][Self::dilationRateX].
        #[unsafe(method(setDilationRateX:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setDilationRateX(&self, dilation_rate_x: NSUInteger);

        /// dilationRateY property can be used to implement dilated convolution as described in
        /// https://arxiv.org/pdf/1511.07122v3.pdf
        /// to aggregate global information in dense prediction problems.
        /// Default value is 1. When set to value > 1, original kernel height, kH is dilated to
        ///
        /// kH_Dilated = (kH-1)*dilationRateY + 1
        ///
        /// by inserting d-1 rows of zeros between consecutive row of the original kernel.
        /// The kernel is centered based on kH_Dilated.
        #[unsafe(method(dilationRateY))]
        #[unsafe(method_family = none)]
        pub unsafe fn dilationRateY(&self) -> NSUInteger;

        /// Setter for [`dilationRateY`][Self::dilationRateY].
        #[unsafe(method(setDilationRateY:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setDilationRateY(&self, dilation_rate_y: NSUInteger);

        #[cfg(feature = "MPSCNNNeuron")]
        /// This mathod can be used to add a neuron activation funtion of given type with
        /// associated scalar parameters A and B that are shared across all output channels.
        /// Neuron activation fucntion is applied to output of convolution. This is a per-pixel
        /// operation that is fused with convolution kernel itself for best performance.
        /// Note that this method can only be used to fuse neuron of kind for which parameters
        /// A and B are shared across all channels of convoution output. It is an error to call
        /// this method for neuron activation functions like MPSCNNNeuronTypePReLU,
        /// which require per-channel parameter values. For those kind of neuron activation functions,
        /// use appropriate setter functions. Default is descriptor with neuronType MPSCNNNeuronTypeNone.
        ///
        /// Note: in certain cases the neuron descriptor will be cached by the MPSNNGraph or the
        /// MPSCNNConvolution. If the neuron type changes after either is made, behavior is undefined.
        #[unsafe(method(fusedNeuronDescriptor))]
        #[unsafe(method_family = none)]
        pub unsafe fn fusedNeuronDescriptor(&self) -> Retained<MPSNNNeuronDescriptor>;

        #[cfg(feature = "MPSCNNNeuron")]
        /// Setter for [`fusedNeuronDescriptor`][Self::fusedNeuronDescriptor].
        #[unsafe(method(setFusedNeuronDescriptor:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setFusedNeuronDescriptor(
            &self,
            fused_neuron_descriptor: &MPSNNNeuronDescriptor,
        );

        #[cfg(all(
            feature = "MPSCNNKernel",
            feature = "MPSCNNNeuron",
            feature = "MPSCore",
            feature = "MPSKernel"
        ))]
        /// MPSCNNNeuron filter to be applied as part of convolution. This is applied after BatchNormalization in the end.
        /// Default is nil.
        /// This is deprecated. You dont need to create MPSCNNNeuron object to fuse with convolution. Use neuron properties
        /// in this descriptor.
        #[deprecated]
        #[unsafe(method(neuron))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuron(&self) -> Option<Retained<MPSCNNNeuron>>;

        #[cfg(all(
            feature = "MPSCNNKernel",
            feature = "MPSCNNNeuron",
            feature = "MPSCore",
            feature = "MPSKernel"
        ))]
        /// Setter for [`neuron`][Self::neuron].
        #[deprecated]
        #[unsafe(method(setNeuron:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setNeuron(&self, neuron: Option<&MPSCNNNeuron>);

        /// <NSSecureCoding
        /// > support
        #[unsafe(method(supportsSecureCoding))]
        #[unsafe(method_family = none)]
        pub unsafe fn supportsSecureCoding() -> bool;

        /// <NSSecureCoding
        /// > support
        ///
        /// # Safety
        ///
        /// `a_coder` possibly has further requirements.
        #[unsafe(method(encodeWithCoder:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeWithCoder(&self, a_coder: &NSCoder);

        /// <NSSecureCoding
        /// > support
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;

        #[cfg(all(
            feature = "MPSCNNKernel",
            feature = "MPSCNNNeuron",
            feature = "MPSCore",
            feature = "MPSKernel"
        ))]
        /// This method is deprecated. Please use neuronType, neuronParameterA and neuronParameterB properites to fuse
        /// neuron with convolution.
        ///
        /// Parameter `kernelWidth`: The width of the filter window.  Must be > 0. Large values will take a long time.
        ///
        /// Parameter `kernelHeight`: The height of the filter window.   Must be > 0. Large values will take a long time.
        ///
        /// Parameter `inputFeatureChannels`: The number of feature channels in the input image. Must be >= 1.
        ///
        /// Parameter `outputFeatureChannels`: The number of feature channels in the output image. Must be >= 1.
        ///
        /// Parameter `neuronFilter`: An optional neuron filter that can be applied to the output of convolution.
        ///
        /// Returns: A valid MPSCNNConvolutionDescriptor object or nil, if failure.
        #[deprecated]
        #[unsafe(method(cnnConvolutionDescriptorWithKernelWidth:kernelHeight:inputFeatureChannels:outputFeatureChannels:neuronFilter:))]
        #[unsafe(method_family = none)]
        pub unsafe fn cnnConvolutionDescriptorWithKernelWidth_kernelHeight_inputFeatureChannels_outputFeatureChannels_neuronFilter(
            kernel_width: NSUInteger,
            kernel_height: NSUInteger,
            input_feature_channels: NSUInteger,
            output_feature_channels: NSUInteger,
            neuron_filter: Option<&MPSCNNNeuron>,
        ) -> Retained<Self>;

        /// Creates a convolution descriptor.
        ///
        /// Parameter `kernelWidth`: The width of the filter window.  Must be > 0. Large values will take a long time.
        ///
        /// Parameter `kernelHeight`: The height of the filter window.   Must be > 0. Large values will take a long time.
        ///
        /// Parameter `inputFeatureChannels`: The number of feature channels in the input image. Must be >= 1.
        ///
        /// Parameter `outputFeatureChannels`: The number of feature channels in the output image. Must be >= 1.
        ///
        /// Returns: A valid MPSCNNConvolutionDescriptor object or nil, if failure.
        #[unsafe(method(cnnConvolutionDescriptorWithKernelWidth:kernelHeight:inputFeatureChannels:outputFeatureChannels:))]
        #[unsafe(method_family = none)]
        pub unsafe fn cnnConvolutionDescriptorWithKernelWidth_kernelHeight_inputFeatureChannels_outputFeatureChannels(
            kernel_width: NSUInteger,
            kernel_height: NSUInteger,
            input_feature_channels: NSUInteger,
            output_feature_channels: NSUInteger,
        ) -> Retained<Self>;

        /// Adds batch normalization for inference, it copies all the float arrays provided, expecting
        /// outputFeatureChannels elements in each.
        ///
        ///
        /// This method will be used to pass in batch normalization parameters to the convolution during the
        /// init call. For inference we modify weights and bias going in convolution or Fully Connected layer to combine
        /// and optimize the layers.
        ///
        /// w: weights for a corresponding output feature channel
        /// b: bias for a corresponding output feature channel
        /// W: batch normalized weights for a corresponding output feature channel
        /// B: batch normalized bias for a corresponding output feature channel
        ///
        /// I = gamma / sqrt(variance + epsilon), J = beta - ( I * mean )
        ///
        /// W = w * I
        /// B = b * I + J
        ///
        /// Every convolution has (OutputFeatureChannel * kernelWidth * kernelHeight * InputFeatureChannel) weights
        ///
        /// I, J are calculated, for every output feature channel separately to get the corresponding weights and bias
        /// Thus, I, J are calculated and then used for every (kernelWidth * kernelHeight * InputFeatureChannel)
        /// weights, and this is done OutputFeatureChannel number of times for each output channel.
        ///
        /// thus, internally, batch normalized weights are computed as:
        ///
        /// W[no][i][j][ni] = w[no][i][j][ni] * I[no]
        ///
        /// no: index into outputFeatureChannel
        /// i : index into kernel Height
        /// j : index into kernel Width
        /// ni: index into inputFeatureChannel
        ///
        /// One usually doesn't see a bias term and batch normalization together as batch normalization potentially cancels
        /// out the bias term after training, but in MPS if the user provides it, batch normalization will use the above
        /// formula to incorporate it, if user does not have bias terms then put a float array of zeroes in the convolution
        /// init for bias terms of each output feature channel.
        ///
        /// this comes from:
        /// https://arxiv.org/pdf/1502.03167v3.pdf
        ///
        /// Note: in certain cases the batch normalization parameters will be cached by the MPSNNGraph
        /// or the MPSCNNConvolution. If the batch normalization parameters change after either is made,
        /// behavior is undefined.
        ///
        ///
        /// Parameter `mean`: Pointer to an array of floats of mean for each output feature channel
        ///
        /// Parameter `variance`: Pointer to an array of floats of variance for each output feature channel
        ///
        /// Parameter `gamma`: Pointer to an array of floats of gamma for each output feature channel
        ///
        /// Parameter `beta`: Pointer to an array of floats of beta for each output feature channel
        ///
        /// Parameter `epsilon`: A small float value used to have numerical stability in the code
        ///
        /// # Safety
        ///
        /// - `mean` must be a valid pointer or null.
        /// - `variance` must be a valid pointer or null.
        /// - `gamma` must be a valid pointer or null.
        /// - `beta` must be a valid pointer or null.
        #[unsafe(method(setBatchNormalizationParametersForInferenceWithMean:variance:gamma:beta:epsilon:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setBatchNormalizationParametersForInferenceWithMean_variance_gamma_beta_epsilon(
            &self,
            mean: *const c_float,
            variance: *const c_float,
            gamma: *const c_float,
            beta: *const c_float,
            epsilon: c_float,
        );

        #[cfg(feature = "MPSCNNNeuronType")]
        /// Adds a neuron activation function to convolution descriptor.
        ///
        ///
        /// This mathod can be used to add a neuron activation funtion of given type with
        /// associated scalar parameters A and B that are shared across all output channels.
        /// Neuron activation fucntion is applied to output of convolution. This is a per-pixel
        /// operation that is fused with convolution kernel itself for best performance.
        /// Note that this method can only be used to fuse neuron of kind for which parameters
        /// A and B are shared across all channels of convoution output. It is an error to call
        /// this method for neuron activation functions like MPSCNNNeuronTypePReLU,
        /// which require per-channel parameter values. For those kind of neuron activation functions,
        /// use appropriate setter functions.
        ///
        /// Note: in certain cases, the neuron descriptor will be cached by the MPSNNGraph or the
        /// MPSCNNConvolution. If the neuron type changes after either is made, behavior is undefined.
        ///
        ///
        /// Parameter `neuronType`: type of neuron activation function. For full list see MPSCNNNeuronType.h
        ///
        /// Parameter `parameterA`: parameterA of neuron activation that is shared across all channels of convolution output.
        ///
        /// Parameter `parameterB`: parameterB of neuron activation that is shared across all channels of convolution output.
        #[deprecated]
        #[unsafe(method(setNeuronType:parameterA:parameterB:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setNeuronType_parameterA_parameterB(
            &self,
            neuron_type: MPSCNNNeuronType,
            parameter_a: c_float,
            parameter_b: c_float,
        );

        #[cfg(feature = "MPSCNNNeuronType")]
        /// Getter funtion for neuronType set using setNeuronType:parameterA:parameterB method
        #[deprecated]
        #[unsafe(method(neuronType))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronType(&self) -> MPSCNNNeuronType;

        /// Getter funtion for neuronType set using setNeuronType:parameterA:parameterB method
        #[deprecated]
        #[unsafe(method(neuronParameterA))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronParameterA(&self) -> c_float;

        /// Getter funtion for neuronType set using setNeuronType:parameterA:parameterB method
        #[deprecated]
        #[unsafe(method(neuronParameterB))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronParameterB(&self) -> c_float;

        /// Add per-channel neuron parameters A for PReLu neuron activation functions.
        ///
        ///
        /// This method sets the neuron to PReLU, zeros parameters A and B and sets the per-channel
        /// neuron parameters A to an array containing a unique value of A for each output feature
        /// channel.
        ///
        /// If the neuron function is f(v,a,b), it will apply
        ///
        /// OutputImage(x,y,i) = f( ConvolutionResult(x,y,i), A[i], B[i] ) where i in [0,outputFeatureChannels-1]
        ///
        /// See https://arxiv.org/pdf/1502.01852.pdf for details.
        ///
        /// All other neuron types, where parameter A
        /// and parameter B are shared across channels must be set using
        /// -setNeuronOfType:parameterA:parameterB:
        ///
        /// If batch normalization parameters are set, batch normalization will occur before
        /// neuron application i.e. output of convolution is first batch normalized followed
        /// by neuron activation. This function automatically sets neuronType to MPSCNNNeuronTypePReLU.
        ///
        /// Note: in certain cases the neuron descriptor will be cached by the MPSNNGraph or the
        /// MPSCNNConvolution. If the neuron type changes after either is made, behavior is undefined.
        ///
        ///
        /// Parameter `A`: An array containing per-channel float values for neuron parameter A.
        /// Number of entries must be equal to outputFeatureChannels.
        #[deprecated]
        #[unsafe(method(setNeuronToPReLUWithParametersA:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setNeuronToPReLUWithParametersA(&self, a: &NSData);
    );
}

/// Methods declared on superclass `NSObject`.
impl MPSCNNConvolutionDescriptor {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// MPSCNNSubPixelConvolutionDescriptor can be used to create MPSCNNConvolution object that does sub pixel upsamling
    /// and reshaping opeartion as described in
    /// http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Shi_Real-Time_Single_Image_CVPR_2016_paper.pdf
    ///
    /// Conceptually MPSCNNConvolution with subPixelScaleFactor > 1 can be thought of as filter performing regular CNN convolution producing N output feature channels at each pixel of
    /// an intermediate MPSImage followed by a kernel that rearranges/reshapes these N channels at each pixel of intermediate MPSImage into a pixel block of
    /// size subPixelScaleFactor x subPixelScaleFactor with N/(subPixelScaleFactor * subPixelScaleFactor) featureChannels at each pixel of this pixel block. Thus each pixel in intermedaite
    /// MPSImage with N channels map to subPixelScaleFactor x subPixelScaleFactor pixel block in final destination MPSImage with N/(subPixelScaleFactor * subPixelScaleFactor) featureChannels.
    /// MPSCNNConvolution with subPixelScaleFactor > 1 fuses the convolution and reshaping operation into single compute kernel thus not only saving DRAM roundtrip but also memory
    /// needed for intermediate MPSImage had these operation done separately.
    /// Let N be the value of outputFeatureChannels property and let r = subPixelScaleFactor.
    /// Conceptually Convolution will produce intermedaite image Io of dimensions (treated as 3D tensor) width x height x N where
    /// width = (clipRect.size.width + r - 1) / r
    /// height = (clipRect.size.height + r -1) / r
    /// Reshaping happens as follows
    ///
    /// ```text
    ///                    Destination[clipRect.origin.x+x][clipRect.origin.y+y][c] = Io[ floor(x/r) ][ floor(y/r) ][ (N/r^2) * ( r * mod(y,r) + mod(x,r) ) + c ]
    ///                    where x in [0,clipRect.size.width-1], y in [0,clipRect.size.height-1], c in [0,N/r^2 - 1]
    /// ```
    ///
    /// The following conditions must be met:
    /// 1) N (outputFeatureChannels) must be multiple of r^2 (subPixelScaleFactor * subPixelScaleFactor).
    /// 2) The destination MPSImage to encode call must have at least N/r^2 + destinationFeatureChannelOffset channels.
    /// 3) Number of feature channels in reshaped output image (N/r^2) can be any value when groups = 1 but must be multiple of 4 when groups > 1.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnsubpixelconvolutiondescriptor?language=objc)
    #[unsafe(super(MPSCNNConvolutionDescriptor, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    pub struct MPSCNNSubPixelConvolutionDescriptor;
);

extern_conformance!(
    unsafe impl NSCoding for MPSCNNSubPixelConvolutionDescriptor {}
);

extern_conformance!(
    unsafe impl NSCopying for MPSCNNSubPixelConvolutionDescriptor {}
);

unsafe impl CopyingHelper for MPSCNNSubPixelConvolutionDescriptor {
    type Result = Self;
}

extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNSubPixelConvolutionDescriptor {}
);

extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNSubPixelConvolutionDescriptor {}
);

impl MPSCNNSubPixelConvolutionDescriptor {
    extern_methods!(
        /// Upsampling scale factor. Each pixel in input is upsampled into a subPixelScaleFactor x subPixelScaleFactor pixel block by rearranging
        /// the outputFeatureChannels as described above. Default value is 1.
        #[unsafe(method(subPixelScaleFactor))]
        #[unsafe(method_family = none)]
        pub unsafe fn subPixelScaleFactor(&self) -> NSUInteger;

        /// Setter for [`subPixelScaleFactor`][Self::subPixelScaleFactor].
        #[unsafe(method(setSubPixelScaleFactor:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setSubPixelScaleFactor(&self, sub_pixel_scale_factor: NSUInteger);
    );
}

/// Methods declared on superclass `MPSCNNConvolutionDescriptor`.
impl MPSCNNSubPixelConvolutionDescriptor {
    extern_methods!(
        /// <NSSecureCoding
        /// > support
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;

        #[cfg(all(
            feature = "MPSCNNKernel",
            feature = "MPSCNNNeuron",
            feature = "MPSCore",
            feature = "MPSKernel"
        ))]
        /// This method is deprecated. Please use neuronType, neuronParameterA and neuronParameterB properites to fuse
        /// neuron with convolution.
        ///
        /// Parameter `kernelWidth`: The width of the filter window.  Must be > 0. Large values will take a long time.
        ///
        /// Parameter `kernelHeight`: The height of the filter window.   Must be > 0. Large values will take a long time.
        ///
        /// Parameter `inputFeatureChannels`: The number of feature channels in the input image. Must be >= 1.
        ///
        /// Parameter `outputFeatureChannels`: The number of feature channels in the output image. Must be >= 1.
        ///
        /// Parameter `neuronFilter`: An optional neuron filter that can be applied to the output of convolution.
        ///
        /// Returns: A valid MPSCNNConvolutionDescriptor object or nil, if failure.
        #[deprecated]
        #[unsafe(method(cnnConvolutionDescriptorWithKernelWidth:kernelHeight:inputFeatureChannels:outputFeatureChannels:neuronFilter:))]
        #[unsafe(method_family = none)]
        pub unsafe fn cnnConvolutionDescriptorWithKernelWidth_kernelHeight_inputFeatureChannels_outputFeatureChannels_neuronFilter(
            kernel_width: NSUInteger,
            kernel_height: NSUInteger,
            input_feature_channels: NSUInteger,
            output_feature_channels: NSUInteger,
            neuron_filter: Option<&MPSCNNNeuron>,
        ) -> Retained<Self>;

        /// Creates a convolution descriptor.
        ///
        /// Parameter `kernelWidth`: The width of the filter window.  Must be > 0. Large values will take a long time.
        ///
        /// Parameter `kernelHeight`: The height of the filter window.   Must be > 0. Large values will take a long time.
        ///
        /// Parameter `inputFeatureChannels`: The number of feature channels in the input image. Must be >= 1.
        ///
        /// Parameter `outputFeatureChannels`: The number of feature channels in the output image. Must be >= 1.
        ///
        /// Returns: A valid MPSCNNConvolutionDescriptor object or nil, if failure.
        #[unsafe(method(cnnConvolutionDescriptorWithKernelWidth:kernelHeight:inputFeatureChannels:outputFeatureChannels:))]
        #[unsafe(method_family = none)]
        pub unsafe fn cnnConvolutionDescriptorWithKernelWidth_kernelHeight_inputFeatureChannels_outputFeatureChannels(
            kernel_width: NSUInteger,
            kernel_height: NSUInteger,
            input_feature_channels: NSUInteger,
            output_feature_channels: NSUInteger,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `NSObject`.
impl MPSCNNSubPixelConvolutionDescriptor {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// MPSCNNDepthWiseConvolutionDescriptor can be used to create MPSCNNConvolution object that does depthwise convolution
    ///
    /// Depthwise convolution applies different filter to each input feature channel i.e. no cross channel mixing.
    /// Number of outputFeatureChannels can be greater than number of inputFeatureChannels, in which case convolution
    /// expects channelMultipler = outputFeactureChannels/inputFeatureChannels number of filters for each input channel.
    /// This means channelMultipler filters are applied to each input feature channel producing channelMultipler output feature channels.
    /// All channelMultipler output feature channels produced by single input feature channel are stored togather in output image i.e.
    /// output[x,y,k*channelMultiplier + q] = input[x,y,k] * filter[k,q]
    /// where * here denotes convolution.
    /// group must be 1.
    /// Weights array returned by MPSCNNConvolutionDataProvier is interpreted as
    /// Weights [inputFeatureChannels] [channelMultiplier] [kH] [kW]
    /// = Weights [ inputFeatureChannels * channelMultiplier ] [kH] [kW]
    /// = Weights [ outputFeatureChannels ] [kH] [kW]
    ///
    /// Currently only channel multipler of 1 is supported i.e. inputFeatureChannels == outputFeatureChannels
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnndepthwiseconvolutiondescriptor?language=objc)
    #[unsafe(super(MPSCNNConvolutionDescriptor, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    pub struct MPSCNNDepthWiseConvolutionDescriptor;
);

extern_conformance!(
    unsafe impl NSCoding for MPSCNNDepthWiseConvolutionDescriptor {}
);

extern_conformance!(
    unsafe impl NSCopying for MPSCNNDepthWiseConvolutionDescriptor {}
);

unsafe impl CopyingHelper for MPSCNNDepthWiseConvolutionDescriptor {
    type Result = Self;
}

extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNDepthWiseConvolutionDescriptor {}
);

extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNDepthWiseConvolutionDescriptor {}
);

impl MPSCNNDepthWiseConvolutionDescriptor {
    extern_methods!(
        /// Ratio of outputFeactureChannel to inputFeatureChannels for depthwise convolution i.e. how many output feature channels are
        /// produced by each input channel.
        #[unsafe(method(channelMultiplier))]
        #[unsafe(method_family = none)]
        pub unsafe fn channelMultiplier(&self) -> NSUInteger;
    );
}

/// Methods declared on superclass `MPSCNNConvolutionDescriptor`.
impl MPSCNNDepthWiseConvolutionDescriptor {
    extern_methods!(
        /// <NSSecureCoding
        /// > support
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;

        #[cfg(all(
            feature = "MPSCNNKernel",
            feature = "MPSCNNNeuron",
            feature = "MPSCore",
            feature = "MPSKernel"
        ))]
        /// This method is deprecated. Please use neuronType, neuronParameterA and neuronParameterB properites to fuse
        /// neuron with convolution.
        ///
        /// Parameter `kernelWidth`: The width of the filter window.  Must be > 0. Large values will take a long time.
        ///
        /// Parameter `kernelHeight`: The height of the filter window.   Must be > 0. Large values will take a long time.
        ///
        /// Parameter `inputFeatureChannels`: The number of feature channels in the input image. Must be >= 1.
        ///
        /// Parameter `outputFeatureChannels`: The number of feature channels in the output image. Must be >= 1.
        ///
        /// Parameter `neuronFilter`: An optional neuron filter that can be applied to the output of convolution.
        ///
        /// Returns: A valid MPSCNNConvolutionDescriptor object or nil, if failure.
        #[deprecated]
        #[unsafe(method(cnnConvolutionDescriptorWithKernelWidth:kernelHeight:inputFeatureChannels:outputFeatureChannels:neuronFilter:))]
        #[unsafe(method_family = none)]
        pub unsafe fn cnnConvolutionDescriptorWithKernelWidth_kernelHeight_inputFeatureChannels_outputFeatureChannels_neuronFilter(
            kernel_width: NSUInteger,
            kernel_height: NSUInteger,
            input_feature_channels: NSUInteger,
            output_feature_channels: NSUInteger,
            neuron_filter: Option<&MPSCNNNeuron>,
        ) -> Retained<Self>;

        /// Creates a convolution descriptor.
        ///
        /// Parameter `kernelWidth`: The width of the filter window.  Must be > 0. Large values will take a long time.
        ///
        /// Parameter `kernelHeight`: The height of the filter window.   Must be > 0. Large values will take a long time.
        ///
        /// Parameter `inputFeatureChannels`: The number of feature channels in the input image. Must be >= 1.
        ///
        /// Parameter `outputFeatureChannels`: The number of feature channels in the output image. Must be >= 1.
        ///
        /// Returns: A valid MPSCNNConvolutionDescriptor object or nil, if failure.
        #[unsafe(method(cnnConvolutionDescriptorWithKernelWidth:kernelHeight:inputFeatureChannels:outputFeatureChannels:))]
        #[unsafe(method_family = none)]
        pub unsafe fn cnnConvolutionDescriptorWithKernelWidth_kernelHeight_inputFeatureChannels_outputFeatureChannels(
            kernel_width: NSUInteger,
            kernel_height: NSUInteger,
            input_feature_channels: NSUInteger,
            output_feature_channels: NSUInteger,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `NSObject`.
impl MPSCNNDepthWiseConvolutionDescriptor {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

/// [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutionweightslayout?language=objc)
// NS_ENUM
#[repr(transparent)]
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord)]
pub struct MPSCNNConvolutionWeightsLayout(pub u32);
impl MPSCNNConvolutionWeightsLayout {
    #[doc(alias = "MPSCNNConvolutionWeightsLayoutOHWI")]
    pub const OHWI: Self = Self(0);
}

unsafe impl Encode for MPSCNNConvolutionWeightsLayout {
    const ENCODING: Encoding = u32::ENCODING;
}

unsafe impl RefEncode for MPSCNNConvolutionWeightsLayout {
    const ENCODING_REF: Encoding = Encoding::Pointer(&Self::ENCODING);
}

/// [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnweightsquantizationtype?language=objc)
// NS_ENUM
#[repr(transparent)]
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord)]
pub struct MPSCNNWeightsQuantizationType(pub u32);
impl MPSCNNWeightsQuantizationType {
    #[doc(alias = "MPSCNNWeightsQuantizationTypeNone")]
    pub const None: Self = Self(0);
    #[doc(alias = "MPSCNNWeightsQuantizationTypeLinear")]
    pub const Linear: Self = Self(1);
    #[doc(alias = "MPSCNNWeightsQuantizationTypeLookupTable")]
    pub const LookupTable: Self = Self(2);
}

unsafe impl Encode for MPSCNNWeightsQuantizationType {
    const ENCODING: Encoding = u32::ENCODING;
}

unsafe impl RefEncode for MPSCNNWeightsQuantizationType {
    const ENCODING_REF: Encoding = Encoding::Pointer(&Self::ENCODING);
}

extern_class!(
    /// The MPSCNNConvolutionGradientState is returned by resultStateForSourceImage:sourceStates method on MPSCNNConvolution object.
    /// Note that resultStateForSourceImage:sourceStates:destinationImage creates the object on autoreleasepool.
    /// It will be consumed by MPSCNNConvolutionGradient. This is also used by MPSCNNConvolutionTranspose encode call
    /// that returns MPSImage on left hand side to correctly size the destination.
    /// Note that state objects are not usable across batches i.e. when batch is done you should nuke the state object and create
    /// new one for next batch.
    ///
    /// This state exposes the gradient with respect to weights and biases, as computed by the MPSCNNConvolutionGradient kernel, as a metal buffer to be used
    /// during weights and biases update. The standard weights and biases update formula is:
    ///
    /// weights(t+1) = f(weights(t), gradientForWeights(t)) and
    /// biases(t+1) = f(biases(t), gradientForBiases(t)),
    ///
    /// where the weights(t)/biases(t) are the wegihts and the biases at step t that are provided by data source provider used to create MPSCNNConvolution and
    /// MPSCNNConvoltuionGradient objects. There are multiple ways user can update weights and biases as described below:
    ///
    /// 1) For check pointing, i.e. updating weights/biases and storing:
    /// once the command buffer on which MPSCNNConvolutionGradient is enqueued is done (e.g. in command
    /// buffer completion callback), the application can simply use
    /// float* delta_w = (float*)((char*)[gradientForWeights contents]);
    /// float* delta_b = (float*)((char*)[gradientForBiases contents]);
    /// to update the weights and biases in the data provider directly.
    /// The application can instead provide a metal kernel that reads from gradientForWeights and gradientForBiases buffer and the buffer created using data provided by the data source
    /// to do any kind of update it will like to do, then read back the updated weights/biases and store to the data source. Note that lifetime of the
    /// gradientForWeights and gradientForBiases buffer is the same as the MPSCNNConvolutionGradientState. So it's the applications's responsibility to make sure the buffer is alive
    /// (retained) when the update kernel is running if the command buffer doesn't retain the buffer. Also, in order to gaurantee that the buffer is correctly
    /// synchronized for CPU side access, it is the application's responsibility to call
    /// [gradientState synchronizeOnCommandBuffer:]
    /// before accessing data from the buffer.
    ///
    /// 2) For a CPU side update, once the weights and biases in the data source provider are updated as above, the original MPSCNNConvolution and
    /// MPSCNNConvolutionGradient objects need to be updated with the new weigths and biases by calling the
    /// -(void) reloadWeightsAndBiasesFromDataSource
    /// method. Again application needs to call [gradientState synchronizeOnCommandBuffer:] before touching data on CPU side.
    ///
    /// 3) The above CPU side update requires command buffer to be done. If the application doesn't want to update its data source provider object and would prefer to directly
    /// enqueue an update of the internal MPSCNNConvolution and MPSCNNConvolutionGradient weights/biases buffers on the GPU without CPU side involvement, it needs to do
    /// following:
    /// i) get gradientForWeights and gradientForBiases buffers from this gradient state object and set it as source of update kernel
    /// ii) create a temporary buffer, dest, of same size and set it as destination of update kernel
    /// iii) enqueue update kernel on command buffer
    /// iv) call reloadWeightsAndBiasesWithCommandBuffer:dest:weightsOffset:biasesOffset on MPSCNNConvolution and MPSCNNConvolutionGradient objects. This
    /// will reload the weights from application's update kernel in dest on GPU without CPU side involvement.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiongradientstate?language=objc)
    #[unsafe(super(MPSNNGradientState, MPSState, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(
        feature = "MPSCore",
        feature = "MPSNNGradientState",
        feature = "MPSState"
    ))]
    pub struct MPSCNNConvolutionGradientState;
);

#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSNeuralNetworkTypes",
    feature = "MPSState"
))]
extern_conformance!(
    unsafe impl MPSImageSizeEncodingState for MPSCNNConvolutionGradientState {}
);

#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionGradientState {}
);

#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
impl MPSCNNConvolutionGradientState {
    extern_methods!(
        /// A buffer that contains the loss function gradients with respect to weights.
        /// Each value in the buffer is a float. The layout of the gradients with respect to the weights is the same as
        /// the weights layout provided by data source i.e. it can be interpreted as 4D array
        ///
        /// gradientForWeights[outputFeatureChannels][kernelHeight][kernelWidth][inputFeatureChannels/groups]
        /// For depthwise convolution it will be (since we only support channel multiplier of 1 currently)
        /// gradientForWeights[outputFeatureChannels][kernelHeight][kernelWidth]
        #[unsafe(method(gradientForWeights))]
        #[unsafe(method_family = none)]
        pub unsafe fn gradientForWeights(&self) -> Retained<ProtocolObject<dyn MTLBuffer>>;

        /// A buffer that contains the loss function gradients with respect to biases.
        #[unsafe(method(gradientForBiases))]
        #[unsafe(method_family = none)]
        pub unsafe fn gradientForBiases(&self) -> Retained<ProtocolObject<dyn MTLBuffer>>;

        #[cfg(all(feature = "MPSCNNKernel", feature = "MPSKernel"))]
        /// The convolution filter that produced the state.
        /// For child MPSCNNConvolutionTrasposeGradientState object, convolution
        /// below refers to MPSCNNConvolution object that produced MPSCNNConvolutionGradientState object
        /// which was used to create MPSCNNConvolutionTransposeGradientState object. See resultStateForSourceImage:sourceStates
        /// method of MPSCNNConvolutionTranspose below.
        #[unsafe(method(convolution))]
        #[unsafe(method_family = none)]
        pub unsafe fn convolution(&self) -> Retained<MPSCNNConvolution>;

        /// Layout of gradient with respect to weights in gradientForWeights buffer.
        /// Currently only MPSCNNConvolutionWeightsLayoutOHWI is supported.
        #[unsafe(method(gradientForWeightsLayout))]
        #[unsafe(method_family = none)]
        pub unsafe fn gradientForWeightsLayout(&self) -> MPSCNNConvolutionWeightsLayout;
    );
}

/// Methods declared on superclass `MPSState`.
#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
impl MPSCNNConvolutionGradientState {
    extern_methods!(
        /// Create a MPSState holding a temporary MTLBuffer
        ///
        /// Parameter `cmdBuf`: The command buffer against which the temporary resource is allocated
        ///
        /// Parameter `bufferSize`: The size of the buffer in bytes
        #[unsafe(method(temporaryStateWithCommandBuffer:bufferSize:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_bufferSize(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
            buffer_size: usize,
        ) -> Retained<Self>;

        /// Create a MPSState holding a temporary MTLTexture
        ///
        /// Parameter `cmdBuf`: The command buffer against which the temporary resource is allocated
        ///
        /// Parameter `descriptor`: A descriptor for the new temporary texture
        #[unsafe(method(temporaryStateWithCommandBuffer:textureDescriptor:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_textureDescriptor(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
            descriptor: &MTLTextureDescriptor,
        ) -> Retained<Self>;

        /// Create a new autoreleased temporary state object without underlying resource
        ///
        /// Parameter `cmdBuf`: The command buffer with which the temporary resource is associated
        #[unsafe(method(temporaryStateWithCommandBuffer:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:bufferSize:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_bufferSize(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            buffer_size: usize,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:textureDescriptor:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_textureDescriptor(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            descriptor: &MTLTextureDescriptor,
        ) -> Retained<Self>;

        /// Create a MPSState with a non-temporary MTLResource
        ///
        /// Parameter `resource`: A MTLBuffer or MTLTexture. May be nil.
        ///
        /// # Safety
        ///
        /// - `resource` may need to be synchronized.
        /// - `resource` may be unretained, you must ensure it is kept alive while in use.
        #[unsafe(method(initWithResource:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithResource(
            this: Allocated<Self>,
            resource: Option<&ProtocolObject<dyn MTLResource>>,
        ) -> Retained<Self>;

        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Option<Retained<Self>>;

        /// Initialize a non-temporary state to hold a number of textures and buffers
        ///
        /// The allocation of each resource will be deferred  until it is needed.
        /// This occurs when -resource or -resourceAtIndex: is called.
        ///
        /// Parameter `resourceList`: The list of resources to create.
        #[unsafe(method(initWithDevice:resourceList:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_resourceList(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            resource_list: &MPSStateResourceList,
        ) -> Retained<Self>;

        /// Initialize a temporary state to hold a number of textures and buffers
        ///
        /// The textures occur first in sequence
        #[unsafe(method(temporaryStateWithCommandBuffer:resourceList:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_resourceList(
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            resource_list: &MPSStateResourceList,
        ) -> Retained<Self>;

        /// Create a state object with a list of MTLResources
        ///
        /// Because MPS prefers deferred allocation of resources
        /// your application should use -initWithTextures:bufferSizes:bufferCount:
        /// whenever possible. This method is useful for cases when the
        /// MTLResources must be initialized by the CPU.
        ///
        /// # Safety
        ///
        /// - `resources` generic may need to be synchronized.
        /// - `resources` generic may be unretained, you must ensure it is kept alive while in use.
        #[unsafe(method(initWithResources:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithResources(
            this: Allocated<Self>,
            resources: Option<&NSArray<ProtocolObject<dyn MTLResource>>>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
impl MPSCNNConvolutionGradientState {
    extern_methods!(
        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

/// [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiongradientstatebatch?language=objc)
#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
pub type MPSCNNConvolutionGradientStateBatch = NSArray<MPSCNNConvolutionGradientState>;

extern_class!(
    /// The MPSCNNConvolutionTransposeGradientState is returned by resultStateForSourceImage:sourceStates method on MPSCNNConvolutionTranspose object.
    /// Note that resultStateForSourceImage:sourceStates:destinationImage creates the object on autoreleasepool.
    /// It will be consumed by MPSCNNConvolutionTransposeGradient. It contains reference to MPSCNNConvolutionGradientState object that connects
    /// MPSCNNConvolution and its corresponding MPSCNNConvolutionTranspose in forward pass of autoencoder. In an autoencoder forward pass, MPSCNNConvolutionGradientState is produced
    /// by MPSCNNConvolution object and is used by corresponding MPSCNNConvolutionTraspose of forward pass that "undo" the corresponding MPSCNNConvolution. It is used to correctly size
    /// destination image that is returned on left hand side by encode call MPSCNNConvolutionTranspose as well as automatically set kernelOffsetX/Y on MPSCNNConvolutionTranspose using
    /// the offset and other properties of corresponding MPSCNNConvolution object. During training, same MPSCNNConvolutionGradientState object will be consumed by MPSCNNConvolutionGradient
    /// object and the MPSCNNConvolutionTransposeGradientState produced by MPSCNNConvolutionTranspose's resultStateForSourceImage:sourceStates:destinationImage will be consumed by
    /// MPSCNNConvolutionTransposeGradient object
    ///
    /// Note that state objects are not usable across batches i.e. when batch is done you should nuke the state object and create
    /// new one for next batch.
    /// Weights update process for MPSCNNConvolutionTranspose is same as explained above for MPSCNNConvolution. See comments for MPSCNNConvolutionGradientState.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiontransposegradientstate?language=objc)
    #[unsafe(super(MPSCNNConvolutionGradientState, MPSNNGradientState, MPSState, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(
        feature = "MPSCore",
        feature = "MPSNNGradientState",
        feature = "MPSState"
    ))]
    pub struct MPSCNNConvolutionTransposeGradientState;
);

#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSNeuralNetworkTypes",
    feature = "MPSState"
))]
extern_conformance!(
    unsafe impl MPSImageSizeEncodingState for MPSCNNConvolutionTransposeGradientState {}
);

#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionTransposeGradientState {}
);

#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
impl MPSCNNConvolutionTransposeGradientState {
    extern_methods!(
        #[cfg(all(feature = "MPSCNNKernel", feature = "MPSKernel"))]
        /// The convolutionTranspose filter that produced the state.
        #[unsafe(method(convolutionTranspose))]
        #[unsafe(method_family = none)]
        pub unsafe fn convolutionTranspose(&self) -> Retained<MPSCNNConvolutionTranspose>;
    );
}

/// Methods declared on superclass `MPSState`.
#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
impl MPSCNNConvolutionTransposeGradientState {
    extern_methods!(
        /// Create a MPSState holding a temporary MTLBuffer
        ///
        /// Parameter `cmdBuf`: The command buffer against which the temporary resource is allocated
        ///
        /// Parameter `bufferSize`: The size of the buffer in bytes
        #[unsafe(method(temporaryStateWithCommandBuffer:bufferSize:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_bufferSize(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
            buffer_size: usize,
        ) -> Retained<Self>;

        /// Create a MPSState holding a temporary MTLTexture
        ///
        /// Parameter `cmdBuf`: The command buffer against which the temporary resource is allocated
        ///
        /// Parameter `descriptor`: A descriptor for the new temporary texture
        #[unsafe(method(temporaryStateWithCommandBuffer:textureDescriptor:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_textureDescriptor(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
            descriptor: &MTLTextureDescriptor,
        ) -> Retained<Self>;

        /// Create a new autoreleased temporary state object without underlying resource
        ///
        /// Parameter `cmdBuf`: The command buffer with which the temporary resource is associated
        #[unsafe(method(temporaryStateWithCommandBuffer:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:bufferSize:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_bufferSize(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            buffer_size: usize,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:textureDescriptor:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_textureDescriptor(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            descriptor: &MTLTextureDescriptor,
        ) -> Retained<Self>;

        /// Create a MPSState with a non-temporary MTLResource
        ///
        /// Parameter `resource`: A MTLBuffer or MTLTexture. May be nil.
        ///
        /// # Safety
        ///
        /// - `resource` may need to be synchronized.
        /// - `resource` may be unretained, you must ensure it is kept alive while in use.
        #[unsafe(method(initWithResource:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithResource(
            this: Allocated<Self>,
            resource: Option<&ProtocolObject<dyn MTLResource>>,
        ) -> Retained<Self>;

        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Option<Retained<Self>>;

        /// Initialize a non-temporary state to hold a number of textures and buffers
        ///
        /// The allocation of each resource will be deferred  until it is needed.
        /// This occurs when -resource or -resourceAtIndex: is called.
        ///
        /// Parameter `resourceList`: The list of resources to create.
        #[unsafe(method(initWithDevice:resourceList:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_resourceList(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            resource_list: &MPSStateResourceList,
        ) -> Retained<Self>;

        /// Initialize a temporary state to hold a number of textures and buffers
        ///
        /// The textures occur first in sequence
        #[unsafe(method(temporaryStateWithCommandBuffer:resourceList:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_resourceList(
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            resource_list: &MPSStateResourceList,
        ) -> Retained<Self>;

        /// Create a state object with a list of MTLResources
        ///
        /// Because MPS prefers deferred allocation of resources
        /// your application should use -initWithTextures:bufferSizes:bufferCount:
        /// whenever possible. This method is useful for cases when the
        /// MTLResources must be initialized by the CPU.
        ///
        /// # Safety
        ///
        /// - `resources` generic may need to be synchronized.
        /// - `resources` generic may be unretained, you must ensure it is kept alive while in use.
        #[unsafe(method(initWithResources:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithResources(
            this: Allocated<Self>,
            resources: Option<&NSArray<ProtocolObject<dyn MTLResource>>>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
impl MPSCNNConvolutionTransposeGradientState {
    extern_methods!(
        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

/// [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiontransposegradientstatebatch?language=objc)
#[cfg(all(
    feature = "MPSCore",
    feature = "MPSNNGradientState",
    feature = "MPSState"
))]
pub type MPSCNNConvolutionTransposeGradientStateBatch =
    NSArray<MPSCNNConvolutionTransposeGradientState>;

extern_class!(
    /// The MPSCNNConvolutionWeightsAndBiasesState is returned by exportWeightsAndBiasesWithCommandBuffer: method on MPSCNNConvolution object.
    /// This is mainly used for GPU side weights/biases update process.
    /// During training, application can keep a copy of weights, velocity, momentum MTLBuffers in its data source, update the weights (in-place or out of place)
    /// with gradients obtained from MPSCNNConvolutionGradientState and call [MPSCNNConvolution reloadWeightsAndBiasesWithCommandBuffer] with resulting updated
    /// MTLBuffer. If application does not want to keep a copy of weights/biases, it can call [MPSCNNConvolution exportWeightsAndBiasesWithCommandBuffer:] to get
    /// the current weights from convolution itself, do the updated and call reloadWithCommandBuffer.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutionweightsandbiasesstate?language=objc)
    #[unsafe(super(MPSState, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCore", feature = "MPSState"))]
    pub struct MPSCNNConvolutionWeightsAndBiasesState;
);

#[cfg(all(feature = "MPSCore", feature = "MPSState"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionWeightsAndBiasesState {}
);

#[cfg(all(feature = "MPSCore", feature = "MPSState"))]
impl MPSCNNConvolutionWeightsAndBiasesState {
    extern_methods!(
        /// A buffer that contains the weights.
        /// Each value in the buffer is a float. The layout of the weights with respect to the weights is the same as
        /// the weights layout provided by data source i.e. it can be interpreted as 4D array
        ///
        /// weights[outputFeatureChannels][kernelHeight][kernelWidth][inputFeatureChannels/groups]
        /// for regular convolution. For depthwise convolution
        /// weights[outputFeatureChannels][kernelHeight][kernelWidth] as we currently only support channel multiplier of 1.
        #[unsafe(method(weights))]
        #[unsafe(method_family = none)]
        pub unsafe fn weights(&self) -> Retained<ProtocolObject<dyn MTLBuffer>>;

        /// A buffer that contains the biases. Each value is float and there are ouputFeatureChannels values.
        #[unsafe(method(biases))]
        #[unsafe(method_family = none)]
        pub unsafe fn biases(&self) -> Option<Retained<ProtocolObject<dyn MTLBuffer>>>;

        /// Offset at which weights start in weights buffer
        /// Default value is 0.
        #[unsafe(method(weightsOffset))]
        #[unsafe(method_family = none)]
        pub unsafe fn weightsOffset(&self) -> NSUInteger;

        /// Offset at which weights start in biases buffer
        /// Default value is 0.
        #[unsafe(method(biasesOffset))]
        #[unsafe(method_family = none)]
        pub unsafe fn biasesOffset(&self) -> NSUInteger;

        /// Create and initialize MPSCNNConvolutionWeightsAndBiasesState with application
        /// provided weights and biases buffers.
        ///
        /// This is the convinience API when buffers of exact size i.e.
        /// [weights length] =  inputFeatureChannels*kernelWidth*kernelHeight*channelMultiplier*sizeof(float)                   // for depthwise convolution
        /// outputFeatureChannels*kernelWidth*kernelHeight*(inputChannels/groups)*sizeof(float)      // for regular otherwise
        /// and [biases length]  =  outputFeatureChannels*sizeof(float)
        ///
        /// # Safety
        ///
        /// - `weights` may need to be synchronized.
        /// - `weights` may be unretained, you must ensure it is kept alive while in use.
        /// - `weights` contents should be of the correct type.
        /// - `biases` may need to be synchronized.
        /// - `biases` may be unretained, you must ensure it is kept alive while in use.
        /// - `biases` contents should be of the correct type.
        #[unsafe(method(initWithWeights:biases:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithWeights_biases(
            this: Allocated<Self>,
            weights: &ProtocolObject<dyn MTLBuffer>,
            biases: Option<&ProtocolObject<dyn MTLBuffer>>,
        ) -> Retained<Self>;

        /// Create and initialize MPSCNNConvolutionWeightsAndBiasesState with application provided convolution descriptor
        ///
        /// Create weights and biases buffers of appropriate size
        #[unsafe(method(initWithDevice:cnnConvolutionDescriptor:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_cnnConvolutionDescriptor(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            descriptor: &MPSCNNConvolutionDescriptor,
        ) -> Retained<Self>;

        /// Create and initialize temporary MPSCNNConvolutionWeightsAndBiasesState with application provided convolution descriptor
        ///
        /// Create weights and biases buffers of appropriate size from command buffer cache.
        #[unsafe(method(temporaryCNNConvolutionWeightsAndBiasesStateWithCommandBuffer:cnnConvolutionDescriptor:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryCNNConvolutionWeightsAndBiasesStateWithCommandBuffer_cnnConvolutionDescriptor(
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            descriptor: &MPSCNNConvolutionDescriptor,
        ) -> Retained<Self>;

        /// Create and initialize MPSCNNConvolutionWeightsAndBiasesState with application
        /// provided weights and biases buffers.
        ///
        /// It gives finer allocation control to application e.g. application can pass same buffer for weights and biases with
        /// appropriate offsets. Or offset into some larger buffer from application managed heap etc. Number of weights
        /// and biases or the length of weights and biases buffer this object owns (will read or write to), starting at offset is
        /// determined by MPSCNNConvolutionDescriptor passed in.
        /// weightsLength =  inputFeatureChannels*kernelWidth*kernelHeight*channelMultiplier*sizeof(float)                   // for depthwise convolution
        /// outputFeatureChannels*kernelWidth*kernelHeight*(inputChannels/groups)*sizeof(float)      // for regular otherwise
        /// biasesLength  =  outputFeatureChannels*sizeof(float)
        /// Thus filters operating on this object will read or write to NSRange(weightsOffset, weightsLength) of weights buffer
        /// and NSRange(biasesOffset, biasesLength) of biases buffer. Thus sizes of buffers provided must be such that
        /// weightsOffset + weightsLength
        /// <
        /// = [weights length]
        /// and     biasesOffset + biasesLength
        /// <
        /// = [biases length]
        /// Offsets must of sizeof(float) aligned i.e. multiple of 4.
        ///
        /// # Safety
        ///
        /// - `weights` may need to be synchronized.
        /// - `weights` may be unretained, you must ensure it is kept alive while in use.
        /// - `weights` contents should be of the correct type.
        /// - `biases` may need to be synchronized.
        /// - `biases` may be unretained, you must ensure it is kept alive while in use.
        /// - `biases` contents should be of the correct type.
        #[unsafe(method(initWithWeights:weightsOffset:biases:biasesOffset:cnnConvolutionDescriptor:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithWeights_weightsOffset_biases_biasesOffset_cnnConvolutionDescriptor(
            this: Allocated<Self>,
            weights: &ProtocolObject<dyn MTLBuffer>,
            weights_offset: NSUInteger,
            biases: Option<&ProtocolObject<dyn MTLBuffer>>,
            biases_offset: NSUInteger,
            descriptor: &MPSCNNConvolutionDescriptor,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSState`.
#[cfg(all(feature = "MPSCore", feature = "MPSState"))]
impl MPSCNNConvolutionWeightsAndBiasesState {
    extern_methods!(
        /// Create a MPSState holding a temporary MTLBuffer
        ///
        /// Parameter `cmdBuf`: The command buffer against which the temporary resource is allocated
        ///
        /// Parameter `bufferSize`: The size of the buffer in bytes
        #[unsafe(method(temporaryStateWithCommandBuffer:bufferSize:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_bufferSize(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
            buffer_size: usize,
        ) -> Retained<Self>;

        /// Create a MPSState holding a temporary MTLTexture
        ///
        /// Parameter `cmdBuf`: The command buffer against which the temporary resource is allocated
        ///
        /// Parameter `descriptor`: A descriptor for the new temporary texture
        #[unsafe(method(temporaryStateWithCommandBuffer:textureDescriptor:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_textureDescriptor(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
            descriptor: &MTLTextureDescriptor,
        ) -> Retained<Self>;

        /// Create a new autoreleased temporary state object without underlying resource
        ///
        /// Parameter `cmdBuf`: The command buffer with which the temporary resource is associated
        #[unsafe(method(temporaryStateWithCommandBuffer:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer(
            cmd_buf: &ProtocolObject<dyn MTLCommandBuffer>,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:bufferSize:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_bufferSize(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            buffer_size: usize,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:textureDescriptor:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_textureDescriptor(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            descriptor: &MTLTextureDescriptor,
        ) -> Retained<Self>;

        /// Create a MPSState with a non-temporary MTLResource
        ///
        /// Parameter `resource`: A MTLBuffer or MTLTexture. May be nil.
        ///
        /// # Safety
        ///
        /// - `resource` may need to be synchronized.
        /// - `resource` may be unretained, you must ensure it is kept alive while in use.
        #[unsafe(method(initWithResource:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithResource(
            this: Allocated<Self>,
            resource: Option<&ProtocolObject<dyn MTLResource>>,
        ) -> Retained<Self>;

        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Option<Retained<Self>>;

        /// Initialize a non-temporary state to hold a number of textures and buffers
        ///
        /// The allocation of each resource will be deferred  until it is needed.
        /// This occurs when -resource or -resourceAtIndex: is called.
        ///
        /// Parameter `resourceList`: The list of resources to create.
        #[unsafe(method(initWithDevice:resourceList:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_resourceList(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            resource_list: &MPSStateResourceList,
        ) -> Retained<Self>;

        /// Initialize a temporary state to hold a number of textures and buffers
        ///
        /// The textures occur first in sequence
        #[unsafe(method(temporaryStateWithCommandBuffer:resourceList:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryStateWithCommandBuffer_resourceList(
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            resource_list: &MPSStateResourceList,
        ) -> Retained<Self>;

        /// Create a state object with a list of MTLResources
        ///
        /// Because MPS prefers deferred allocation of resources
        /// your application should use -initWithTextures:bufferSizes:bufferCount:
        /// whenever possible. This method is useful for cases when the
        /// MTLResources must be initialized by the CPU.
        ///
        /// # Safety
        ///
        /// - `resources` generic may need to be synchronized.
        /// - `resources` generic may be unretained, you must ensure it is kept alive while in use.
        #[unsafe(method(initWithResources:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithResources(
            this: Allocated<Self>,
            resources: Option<&NSArray<ProtocolObject<dyn MTLResource>>>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCore", feature = "MPSState"))]
impl MPSCNNConvolutionWeightsAndBiasesState {
    extern_methods!(
        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_protocol!(
    /// Provides convolution filter weights and bias terms
    ///
    /// The MPSCNNConvolutionDataSource protocol declares the methods that an
    /// instance of MPSCNNConvolution uses to obtain the weights and bias terms
    /// for the CNN convolution filter.
    ///
    /// Why? CNN weights can be large. If multiple copies of all the weights
    /// for all the convolutions are available unpacked in memory at the same
    /// time, some devices can run out of memory. The MPSCNNConvolutionDataSource
    /// is used to encapsulate a reference to the weights such as a file path,
    /// so that unpacking can be deferred until needed, then purged soon thereafter
    /// so that not all of the data must be in memory at the same time.
    /// MPS does not provide a class that conforms to this protocol. It is up to
    /// the developer to craft his own to encapsulate his data.
    ///
    /// Batch normalization and the neuron activation function are handled using the
    /// -descriptor method.
    ///
    /// Thread safety: The MPSCNNConvolutionDataSource object can be called by
    /// threads that are not the main thread. If you will be creating multiple
    /// MPSNNGraph objects concurrently in multiple threads and these share
    /// MPSCNNConvolutionDataSources, then the data source objects may be called
    /// reentrantly.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiondatasource?language=objc)
    pub unsafe trait MPSCNNConvolutionDataSource: NSCopying + NSObjectProtocol {
        #[cfg(all(feature = "MPSCore", feature = "MPSCoreTypes"))]
        /// Alerts MPS what sort of weights are provided by the object
        ///
        /// For MPSCNNConvolution, MPSDataTypeUInt8, MPSDataTypeFloat16
        /// and MPSDataTypeFloat32 are supported for normal convolutions
        /// using MPSCNNConvolution. MPSCNNBinaryConvolution assumes weights to be
        /// of type MPSDataTypeUInt32 always.
        #[unsafe(method(dataType))]
        #[unsafe(method_family = none)]
        unsafe fn dataType(&self) -> MPSDataType;

        /// Return a MPSCNNConvolutionDescriptor as needed
        ///
        /// MPS will not modify this object other than perhaps to retain it.
        /// User should set the appropriate neuron in the creation of convolution descriptor
        /// and for batch normalization use:
        ///
        /// ```text
        ///        
        ///               -setBatchNormalizationParametersForInferenceWithMean:variance:gamma:beta:epsilon:
        /// ```
        ///
        ///
        /// Returns: A MPSCNNConvolutionDescriptor that describes the kernel housed by this object.
        #[unsafe(method(descriptor))]
        #[unsafe(method_family = none)]
        unsafe fn descriptor(&self) -> Retained<MPSCNNConvolutionDescriptor>;

        /// Returns a pointer to the weights for the convolution.
        ///
        /// The type of each entry in array is given by -dataType. The number
        /// of entries is equal to:
        ///
        /// ```text
        ///                   inputFeatureChannels * outputFeatureChannels * kernelHeight * kernelWidth
        /// ```
        ///
        /// The layout of filter weight is as a 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ inputChannels / groups ]
        ///
        /// Frequently, this function is a single line of code to return
        /// a pointer to memory allocated in -load.
        ///
        /// Batch normalization parameters are set using -descriptor.
        ///
        /// Note: For binary-convolutions the layout of the weights are:
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ floor((inputChannels/groups)+31) / 32 ]
        /// with each 32 sub input feature channel index specified in machine byte order, so that for example
        /// the 13th feature channel bit can be extracted using bitmask = (1U
        /// <
        /// <
        /// 13).
        #[unsafe(method(weights))]
        #[unsafe(method_family = none)]
        unsafe fn weights(&self) -> NonNull<c_void>;

        /// Returns a pointer to the bias terms for the convolution.
        ///
        /// Each entry in the array is a single precision IEEE-754 float
        /// and represents one bias. The number of entries is equal
        /// to outputFeatureChannels.
        ///
        /// Frequently, this function is a single line of code to return
        /// a pointer to memory allocated in -load. It may also just
        /// return nil.
        ///
        /// Note: bias terms are always float, even when the weights are not.
        #[unsafe(method(biasTerms))]
        #[unsafe(method_family = none)]
        unsafe fn biasTerms(&self) -> *mut c_float;

        /// Alerts the data source that the data will be needed soon
        ///
        /// Each load alert will be balanced by a purge later, when MPS
        /// no longer needs the data from this object.
        /// Load will always be called atleast once after initial construction
        /// or each purge of the object before anything else is called.
        /// Note: load may be called to merely inspect the descriptor.
        /// In some circumstances, it may be worthwhile to postpone
        /// weight and bias construction until they are actually needed
        /// to save touching memory and keep the working set small.
        /// The load function is intended to be an opportunity to open
        /// files or mark memory no longer purgeable.
        ///
        /// Returns: Returns YES on success.  If NO is returned, expect MPS
        /// object construction to fail.
        #[unsafe(method(load))]
        #[unsafe(method_family = none)]
        unsafe fn load(&self) -> bool;

        /// Alerts the data source that the data is no longer needed
        ///
        /// Each load alert will be balanced by a purge later, when MPS
        /// no longer needs the data from this object.
        #[unsafe(method(purge))]
        #[unsafe(method_family = none)]
        unsafe fn purge(&self);

        /// A label that is transferred to the convolution at init time
        ///
        /// Overridden by a MPSCNNConvolutionNode.label if it is non-nil.
        #[unsafe(method(label))]
        #[unsafe(method_family = none)]
        unsafe fn label(&self) -> Option<Retained<NSString>>;

        /// A pointer to a 256 entry lookup table containing the values to use for the weight range [0,255]
        #[optional]
        #[unsafe(method(lookupTableForUInt8Kernel))]
        #[unsafe(method_family = none)]
        unsafe fn lookupTableForUInt8Kernel(&self) -> NonNull<c_float>;

        /// Quantizaiton type of weights. If it returns MPSCNNWeightsQuantizationTypeLookupTable,
        /// lookupTableForUInt8Kernel method must be implmented. if it returns MPSCNNWeightsQuantizationTypeLookupLinear,
        /// rangesForUInt8Kernel method must be implemented.
        #[optional]
        #[unsafe(method(weightsQuantizationType))]
        #[unsafe(method_family = none)]
        unsafe fn weightsQuantizationType(&self) -> MPSCNNWeightsQuantizationType;

        #[cfg(all(
            feature = "MPSCore",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        /// Callback for the MPSNNGraph to update the convolution weights on GPU.
        ///
        /// It is the resposibility of this method to decrement the read count of both the gradientState
        /// and the sourceState before returning.  BUG: prior to macOS 10.14, ios/tvos 12.0, the MPSNNGraph
        /// incorrectly decrements the readcount of the gradientState after this method is called.
        ///
        ///
        /// Parameter `commandBuffer`: The command buffer on which to do the update.
        /// MPSCNNConvolutionGradientNode.MPSNNTrainingStyle controls where you want your update
        /// to happen. Provide implementation of this function for GPU side update.
        ///
        /// Parameter `gradientState`: A state object produced by the MPSCNNConvolution and updated by MPSCNNConvolutionGradient
        /// containing weight gradients.
        ///
        /// Parameter `sourceState`: A state object containing the convolution weights
        ///
        /// Returns: If NULL, no update occurs. If nonnull, the result will be used to update the
        /// weights in the MPSNNGraph
        #[optional]
        #[unsafe(method(updateWithCommandBuffer:gradientState:sourceState:))]
        #[unsafe(method_family = none)]
        unsafe fn updateWithCommandBuffer_gradientState_sourceState(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            gradient_state: &MPSCNNConvolutionGradientState,
            source_state: &MPSCNNConvolutionWeightsAndBiasesState,
        ) -> Option<Retained<MPSCNNConvolutionWeightsAndBiasesState>>;

        #[cfg(all(
            feature = "MPSCore",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        /// Callback for the MPSNNGraph to update the convolution weights on CPU.
        /// MPSCNNConvolutionGradientNode.MPSNNTrainingStyle controls where you want your update
        /// to happen. Provide implementation of this function for CPU side update.
        ///
        /// Parameter `gradientState`: A state object produced by the MPSCNNConvolution and updated by MPSCNNConvolutionGradient
        /// containing weight gradients. MPSNNGraph is responsible for calling [gradientState synchronizeOnCommandBuffer:]
        /// so that application get correct gradients for CPU side update.
        ///
        /// Parameter `sourceState`: A state object containing the convolution weights used. MPSCNNConvolution and MPSCNNConvolutionGradient reloadWeightsWithDataSource
        /// will be called right after this method is called. Note that the weights returned here may not match the weights
        /// in your data source due to conversion loss. These are the weights actually used, and should
        /// be what you use to calculate the new weights. Your copy may be incorrect. Write the new weights
        /// to your copy and return them out the left hand side.
        ///
        /// Returns: TRUE if success/no error, FALSE in case of failure.
        #[optional]
        #[unsafe(method(updateWithGradientState:sourceState:))]
        #[unsafe(method_family = none)]
        unsafe fn updateWithGradientState_sourceState(
            &self,
            gradient_state: &MPSCNNConvolutionGradientState,
            source_state: &MPSCNNConvolutionWeightsAndBiasesState,
        ) -> bool;

        /// When copyWithZone:device on convolution is called, data source copyWithZone:device
        /// will be called if data source object responds to this selector. If not, copyWithZone:
        /// will be called if data source responds to it. Otherwise, it is simply retained.
        /// This is to allow application to make a separate copy of data source in convolution
        /// when convolution itself is coplied, for example when copying training graph for running
        /// on second GPU so that weights update on two different GPUs dont end up stomping same
        /// data source.
        ///
        /// # Safety
        ///
        /// `zone` must be a valid pointer or null.
        #[optional]
        #[unsafe(method(copyWithZone:device:))]
        #[unsafe(method_family = copy)]
        unsafe fn copyWithZone_device(
            &self,
            zone: *mut NSZone,
            device: Option<&ProtocolObject<dyn MTLDevice>>,
        ) -> Retained<Self>;

        /// Layout of weights returned by data source. Currently only OHWI layout is supported which is default.
        /// See MPSCNNConvolutionWeightsLayout above.
        #[optional]
        #[unsafe(method(weightsLayout))]
        #[unsafe(method_family = none)]
        unsafe fn weightsLayout(&self) -> MPSCNNConvolutionWeightsLayout;

        #[cfg(all(feature = "MPSCore", feature = "MPSCoreTypes"))]
        /// Alerts MPS what weight precision to use in the CNNConvolution kernel
        ///
        /// If precision of weights returned by dataType does not match precision returned by
        /// kernelWeightsDataType, weights are converted to precision specified by kernelWeightsDataType
        /// before being passed to kernel.
        /// For MPSCNNConvolution, dataType precisions of MPSDataTypeUInt8 or MPSDataTypeFloat16
        /// must return a kernelWeightsDataType of MPSDataTypeFloat16. dataType precisions of
        /// MPSDataTypeFloat32 may return kernelWeightsDataType of MPSDataTypeFloat16 or
        /// MPSDataTypeFloat32. When kernelWeightsDataType returns MPSDataTypeFloat32 the
        /// accumulatorPrecisionOption on the CNNConvolution object must be set to
        /// MPSNNConvolutionAccumulatorPrecisionOptionFloat.
        /// When kernelWeightsDataType is unimplemented the kernel will use float16 precision.
        /// MPSCNNBinaryConvolution assumes weights to be of type MPSDataTypeUInt32 always,
        /// and the kernelWeightsDataType is unused.
        #[optional]
        #[unsafe(method(kernelWeightsDataType))]
        #[unsafe(method_family = none)]
        unsafe fn kernelWeightsDataType(&self) -> MPSDataType;
    }
);

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNConvolution specifies a convolution.
    /// The MPSCNNConvolution convolves the input image with a set of filters, each producing one feature map in the output image.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolution?language=objc)
    #[unsafe(super(MPSCNNKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNConvolution;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNConvolution {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolution {
    extern_methods!(
        /// The number of feature channels per pixel in the input image.
        #[unsafe(method(inputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn inputFeatureChannels(&self) -> NSUInteger;

        /// The number of feature channels per pixel in the output image.
        #[unsafe(method(outputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn outputFeatureChannels(&self) -> NSUInteger;

        /// Number of groups input and output channels are divided into.
        #[unsafe(method(groups))]
        #[unsafe(method_family = none)]
        pub unsafe fn groups(&self) -> NSUInteger;

        /// dataSource with which convolution object was created
        #[unsafe(method(dataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn dataSource(
            &self,
        ) -> Retained<ProtocolObject<dyn MPSCNNConvolutionDataSource>>;

        /// Sub pixel scale factor which was passed in as part of MPSCNNConvolutionDescriptor when creating this MPSCNNConvolution object.
        #[unsafe(method(subPixelScaleFactor))]
        #[unsafe(method_family = none)]
        pub unsafe fn subPixelScaleFactor(&self) -> NSUInteger;

        #[cfg(feature = "MPSCNNNeuron")]
        /// MPSCNNNeuron filter to be applied as part of convolution.
        /// Can be nil in wich case no neuron activation fuction is applied.
        #[deprecated]
        #[unsafe(method(neuron))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuron(&self) -> Option<Retained<MPSCNNNeuron>>;

        #[cfg(feature = "MPSCNNNeuronType")]
        /// The type of neuron to append to the convolution
        ///
        /// Please see class description for a full list. Default is MPSCNNNeuronTypeNone.
        #[deprecated]
        #[unsafe(method(neuronType))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronType(&self) -> MPSCNNNeuronType;

        /// Parameter "a" for the neuron.  Default: 1.0f
        ///
        /// Please see class description for interpretation of a.
        #[deprecated]
        #[unsafe(method(neuronParameterA))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronParameterA(&self) -> c_float;

        /// Parameter "b" for the neuron.  Default: 1.0f
        ///
        /// Please see class description for interpretation of b.
        #[deprecated]
        #[unsafe(method(neuronParameterB))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronParameterB(&self) -> c_float;

        /// Parameter "c" for the neuron.  Default: 1.0f
        ///
        /// Please see class description for interpretation of c.
        #[deprecated]
        #[unsafe(method(neuronParameterC))]
        #[unsafe(method_family = none)]
        pub unsafe fn neuronParameterC(&self) -> c_float;

        #[cfg(feature = "MPSCNNNeuron")]
        /// Fused neuron descritor passed in convolution descriptor for fusion with convolution.
        ///
        /// Please see class description for interpretation of c.
        #[unsafe(method(fusedNeuronDescriptor))]
        #[unsafe(method_family = none)]
        pub unsafe fn fusedNeuronDescriptor(&self) -> Option<Retained<MPSNNNeuronDescriptor>>;

        /// Channel multiplier.
        ///
        /// For convolution created with MPSCNNDepthWiseConvolutionDescriptor, it is the number of
        /// output feature channels for each input channel. See MPSCNNDepthWiseConvolutionDescriptor for more details.
        /// Default is 0 which means regular CNN convolution.
        #[unsafe(method(channelMultiplier))]
        #[unsafe(method_family = none)]
        pub unsafe fn channelMultiplier(&self) -> NSUInteger;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Precision of accumulator used in convolution.
        ///
        /// See MPSNeuralNetworkTypes.h for discussion. Default is MPSNNConvolutionAccumulatorPrecisionOptionFloat.
        #[unsafe(method(accumulatorPrecisionOption))]
        #[unsafe(method_family = none)]
        pub unsafe fn accumulatorPrecisionOption(
            &self,
        ) -> MPSNNConvolutionAccumulatorPrecisionOption;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Setter for [`accumulatorPrecisionOption`][Self::accumulatorPrecisionOption].
        #[unsafe(method(setAccumulatorPrecisionOption:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setAccumulatorPrecisionOption(
            &self,
            accumulator_precision_option: MPSNNConvolutionAccumulatorPrecisionOption,
        );

        /// Initializes a convolution kernel
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolution filter will be used
        ///
        /// Parameter `weights`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource
        /// protocol. The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNConvolution uses to obtain the weights and bias terms
        /// for the CNN convolution filter.
        ///
        ///
        /// Returns: A valid MPSCNNConvolution object or nil, if failure.
        #[unsafe(method(initWithDevice:weights:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_weights(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            weights: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        ) -> Retained<Self>;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Initializes a convolution kernel
        /// WARNING:                        This API is depreated and will be removed in the future. It cannot be used
        /// when training. Also serialization/unserialization wont work for MPSCNNConvolution
        /// objects created with this init. Please move onto using initWithDevice:weights:.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolution filter will be used
        ///
        /// Parameter `convolutionDescriptor`: A pointer to a MPSCNNConvolutionDescriptor.
        ///
        /// Parameter `kernelWeights`: A pointer to a weights array.  Each entry is a float value. The number of entries is =
        /// inputFeatureChannels * outputFeatureChannels * kernelHeight * kernelWidth
        /// The layout of filter weight is so that it can be reinterpreted as 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ inputChannels / groups ]
        /// Weights are converted to half float (fp16) internally for best performance.
        ///
        /// Parameter `biasTerms`: A pointer to bias terms to be applied to the convolution output.  Each entry is a float value.
        /// The number of entries is = numberOfOutputFeatureMaps
        ///
        /// Parameter `flags`: Currently unused. Pass MPSCNNConvolutionFlagsNone
        ///
        ///
        /// Returns: A valid MPSCNNConvolution object or nil, if failure.
        ///
        /// # Safety
        ///
        /// - `kernel_weights` must be a valid pointer.
        /// - `bias_terms` must be a valid pointer or null.
        #[deprecated]
        #[unsafe(method(initWithDevice:convolutionDescriptor:kernelWeights:biasTerms:flags:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_convolutionDescriptor_kernelWeights_biasTerms_flags(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            convolution_descriptor: &MPSCNNConvolutionDescriptor,
            kernel_weights: NonNull<c_float>,
            bias_terms: *const c_float,
            flags: MPSCNNConvolutionFlags,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        /// Allocate a MPCNNConvolutionGradientSState to hold the results from a -encodeBatchToCommandBuffer... operation
        ///
        ///
        /// Parameter `sourceImage`: The MPSImage consumed by the associated -encode call.
        ///
        /// Parameter `sourceStates`: The list of MPSStates consumed by the associated -encode call,
        /// for a batch size of 1.
        ///
        /// Returns: The list of states produced by the -encode call for batch size of 1.
        /// -isResultStateReusedAcrossBatch returns YES for MPSCNNConvolution so same
        /// state is used across entire batch. State object is not reusasable across batches.
        #[unsafe(method(resultStateForSourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn resultStateForSourceImage_sourceStates_destinationImage(
            &self,
            source_image: &MPSImage,
            source_states: Option<&NSArray<MPSState>>,
            destination_image: &MPSImage,
        ) -> Option<Retained<MPSCNNConvolutionGradientState>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(resultStateBatchForSourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn resultStateBatchForSourceImage_sourceStates_destinationImage(
            &self,
            source_image: &MPSImageBatch,
            source_states: Option<&NSArray<MPSStateBatch>>,
            destination_image: &MPSImageBatch,
        ) -> Option<Retained<MPSCNNConvolutionGradientStateBatch>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(temporaryResultStateForCommandBuffer:sourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryResultStateForCommandBuffer_sourceImage_sourceStates_destinationImage(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImage,
            source_states: Option<&NSArray<MPSState>>,
            destination_image: &MPSImage,
        ) -> Option<Retained<MPSCNNConvolutionGradientState>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(temporaryResultStateBatchForCommandBuffer:sourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryResultStateBatchForCommandBuffer_sourceImage_sourceStates_destinationImage(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImageBatch,
            source_states: Option<&NSArray<MPSStateBatch>>,
            destination_image: &MPSImageBatch,
        ) -> Option<Retained<MPSCNNConvolutionGradientStateBatch>>;

        /// CPU side reload. Reload the updated weights and biases from data provider into internal weights and bias buffers. Weights and biases
        /// gradients needed for update are obtained from MPSCNNConvolutionGradientState object. Data provider passed in init call is used for this purpose.
        #[unsafe(method(reloadWeightsAndBiasesFromDataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesFromDataSource(&self);

        /// Deprecated. dataSource will be ignored.
        #[deprecated]
        #[unsafe(method(reloadWeightsAndBiasesWithDataSource:))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesWithDataSource(
            &self,
            data_source: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        );

        #[cfg(feature = "MPSState")]
        /// GPU side reload. Reload the updated weights and biases from update buffer produced by application enqueued metal kernel into internal weights
        /// and biases buffer. Weights and biases gradients needed for update are obtained from MPSCNNConvolutionGradientState object's gradientForWeights and gradientForBiases metal buffer.
        ///
        ///
        /// Parameter `commandBuffer`: Metal command buffer on which application update kernel was enqueued consuming MPSCNNConvolutionGradientState's gradientForWeights and gradientForBiases buffers
        /// and producing updateBuffer metal buffer.
        ///
        /// Parameter `state`: MPSCNNConvolutionWeightsAndBiasesState containing weights and biases buffers which have updated weights produced by application's update kernel.
        /// The state readcount will be decremented.
        #[unsafe(method(reloadWeightsAndBiasesWithCommandBuffer:state:))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesWithCommandBuffer_state(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            state: &MPSCNNConvolutionWeightsAndBiasesState,
        );

        #[cfg(feature = "MPSState")]
        /// GPU side export. Enqueue a kernel to export current weights and biases stored in MPSCNNConvoltion's internal buffers into weights and biases MTLBuffer
        /// returned in MPSCNNConvolutionWeightsAndBiasesState.
        ///
        ///
        /// Parameter `commandBuffer`: Metal command buffer on which export kernel is enqueued.
        ///
        /// Parameter `resultStateCanBeTemporary`: If FALSE, state returned will be non-temporary. If TRUE, returned state may or may not be temporary.
        ///
        /// Returns: MPSCNNConvolutionWeightsAndBiasesState containing weights and biases buffer to which weights got exported. This state and be
        /// temporary or non-temporary depending on the flag resultStateCanBeTemporary
        #[unsafe(method(exportWeightsAndBiasesWithCommandBuffer:resultStateCanBeTemporary:))]
        #[unsafe(method_family = none)]
        pub unsafe fn exportWeightsAndBiasesWithCommandBuffer_resultStateCanBeTemporary(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            result_state_can_be_temporary: bool,
        ) -> Retained<MPSCNNConvolutionWeightsAndBiasesState>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolution {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolution {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

/// [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiongradientoption?language=objc)
// NS_OPTIONS
#[repr(transparent)]
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord)]
pub struct MPSCNNConvolutionGradientOption(pub NSUInteger);
bitflags::bitflags! {
    impl MPSCNNConvolutionGradientOption: NSUInteger {
        #[doc(alias = "MPSCNNConvolutionGradientOptionGradientWithData")]
        const GradientWithData = 1;
        #[doc(alias = "MPSCNNConvolutionGradientOptionGradientWithWeightsAndBias")]
        const GradientWithWeightsAndBias = 2;
        #[doc(alias = "MPSCNNConvolutionGradientOptionAll")]
        const All = MPSCNNConvolutionGradientOption::GradientWithData.0|MPSCNNConvolutionGradientOption::GradientWithWeightsAndBias.0;
    }
}

unsafe impl Encode for MPSCNNConvolutionGradientOption {
    const ENCODING: Encoding = NSUInteger::ENCODING;
}

unsafe impl RefEncode for MPSCNNConvolutionGradientOption {
    const ENCODING_REF: Encoding = Encoding::Pointer(&Self::ENCODING);
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNConvolutionGradient implementents backward propagation of gradient i.e. it computes the gradient of loss function
    /// with respect input data of corresonding forward convolution and gradient of loss function with respect to weights and bias
    /// of corresponding convolution in forward pass.
    ///
    /// Gradient with respect to data
    /// ==============================
    /// Gradient with respect to input data of corresponding forward convolution will be written in destination image passed to
    /// encode call of MPSCNNConvolutionGradient.
    /// This step is similar to convolution transpose in that the strided convolution in forward pass become zero filled convolution in
    /// backward propagation of gradients. The difference between MPSCNNConvolutionTranspose and gradient wrt data is how the
    /// weights, that are provided by data source, are interpreted. MPSCNNConvolution and MPSCNNConvolutionTranspose interpret weights
    /// provided by data source as
    /// weights[outputFeatureChannels][kernelWidth][kernelHeight][inputFeatureChannels]
    /// whereas convoution gradient with respect to data interpret the weights as
    /// weights[inputFeatureChannels][kernelWidth][kernelHeight][outputFeatureChannels]
    /// i.e. weights are transposed in inputFeatureChannels/outputFeatureChannels dimension and also rotated 180 degress in spatial dimension
    ///
    /// User should use the same data source provider to initialize MPSCNNConvolutionGradient as is used to initialize corresponding
    /// forward MPSCNNConvolution. Implementation will do the transposition/shuffling needed.
    /// Thus, while the forward MPSCNNConvolution takes sourceImage of inputFeatureChannels and convolves it with
    /// Wt[outputFeatureChannels][kernelHeight][kernelWidth][inputFeatureChannels] to produce destinationImage of outputFeatureChannels,
    /// MPSConvolutionGradient takes sourceGradient of outputFeatureChannels which is out of previous layer (nomally neuron backward layer),
    /// convolves it with transposed and rotated weights and produces destinationGradient of inputFeatureChannels.
    /// If the user decide to double buffer data source provider i.e. different data source providers are passed to forward MPSCNNConvolution object and
    /// corresponding MPSCNNConvolutionGradient object, it is user responsibility to make sure both data source providers provide same weights/bias data
    /// and have same properties in convolution descriptor else behavior is undefined.
    ///
    /// Gradient with respect to weights and bias
    /// =========================================
    /// Gradient with respect to weights and bias are returned in MPSCNNConvolutionGradientState object to be used in weights update functions.
    /// If I denotes the input image to corresponding MPSCNNConvolution in forward pass and E denoates the loss gradient from previous layer
    /// (normally neuron backward layer) in backward pass, gradient of E with respect to weights is
    ///
    /// delta_E/delta_Wkpqc = sum_i sum_j [ E(i, j, k) * I( secondaryStrideInPixelX*i + secondaryOffset.x + secondaryDilationRateX*p,
    /// secondaryStrideinPixelY*i + secondaryOffset.y + secondaryDilationRateY*q, c) ]
    ///
    /// where i goes over 0..W-1 and j goes over 0..H-1, (W,H) being width and height of E.
    /// p in [0, secondaryKernelWidth-1]
    /// q in [0, secondaryKernelHeight-1]
    /// c in [0, inputeFeatureChannels/groups - 1]
    /// k in [0, outputFeatureChannels]
    ///
    /// and gradient with respect to bias
    ///
    /// delta_E/delta_bk = sum_i sum_j [ E(i, j, k) ]
    ///
    /// These gradients with respect to weights and bias are returned as buffers in MPSCNNConvolutionGradientState object passed in the encode call.
    /// These are consumed by MPSCNNConvolution object's -updateWeightsAndBias:MPSCNNConvolutionGradientState* method for CPU side update and
    /// encodeWeightsAndBiasUpdate:commandBuffer:MPSCNNConvolutionGradientState* method of MPSCNNConvolution object for GPU side update.
    /// UPdated weights and biases are computed as
    ///
    /// Wkpqc_new = Wkpqc_old + delta_E/delta_Wkpqc
    /// bk_new = bk_old + delta_E/delta_bk
    ///
    /// Note that MPSCNNConvolutionGradientState objects's buffers that contain gradients, for CPU side update, will only contain
    /// valid data after command buffer is complete so
    /// its only makes sense to call -updateWeightsAndBias method on MPSCNNConvolution objects after command bufer is
    /// complete. One can achieve this by enqueueing a command buffer completion handler block that make this call.
    /// Since MPSCNNConvolutionGradientState is used across command buffers i.e. its created in forward pass, consumed by  MPSCNNConvolutionGradient in backward pass in same command buffer and passed onto MPSCNNConvolution updateWeightsAndBias method
    /// after completion of command buffer, it cannot be a temporary state.
    ///
    /// In order to gaurantee consistency between forward pass (MPSCNNConvolution) and weights gradient computation in this filter, certain requirements
    /// must be met.
    /// 1) Dimensions of loss gradient E from previous layer in backward pass must be equal to clipRect.size of corresponding MPSCNNConvolution in forward pass.
    /// This is to gaurantee that only those pixels for which weights/bias contributed in destination of forward pass end up contributing to weights/bias gradient update.
    /// If the dimension of loss gradient E from previous layer is not equal to clipRect.size of corresponding forward MPSCNNConvolution,
    /// i) one can insert a slice operation to extract out the region of size clipRect.size from appropriate offset in E and set primaryOffset = 0 Or
    /// ii) set primatryOffset to offset in E at which valid data starts and make sure data outside is zeroed.
    /// 2) secondaryOffset should be set to what offset property of MPSCNNConvolution was set to in forward pass.
    ///
    /// Currently back propagation for gradients is only supported for regualar convolution and depthwise convolution. Back propagation
    /// sub-pixel convolution are not supported. So channelMultiplier and subPixelScaleFactor must be one.
    ///
    /// Note on setting correct offsets
    /// ===============================
    /// If the forward convolution is called with
    /// offset = _offset; kernelWidth = kW; kernelHeight = kH; strideInPixelsX = sX; strideInPixelsY = sY;
    /// dilationRateX = dX; dilationRateY = dY;
    /// thus dilated filter parameters are
    /// kW_Dilated = (kW - 1)*dX + 1; kH_Dilated = (kH - 1)*dY + 1;
    /// Then the correct offset can be computed as follows.
    /// Convoluton Gradient with Data
    /// =============================
    /// Convolution gradient with data of forward convolution with stride > 1 is essentially normal convoution with unit stride,
    /// on an image that is formed by inserting strideInPixelsX-1 zeros in between each column and strideInPixelsY-1 zeros in between each
    /// row of input gradient (output gradient of last layer) with kernel weights that are rotated by 180 degrees in spatial dimension (MPSCNNConvolutionGradient
    /// does this rotation internally). primaryOffset property defines offset in original input gradient coordinate system. In order to
    /// translate it in zero filled intermediate image coordinate system, kernelOffsetX and kernelOffsetY properties can be used as follows
    /// offsetInZeroFilledImageX = primaryOffset.x * primaryStrideInPixelsX + kernelOffsetX;
    /// offsetInZeroFilledImageY = primaryOffset.y * primaryStrideInPixelsY + kernelOffsetY;
    /// This is what internally MPSCNNConvolutionGradient do. In order to correctly match forward convolution offset setting (so that padding policy is
    /// consistent), application should set
    /// primaryOffset.x = 0; primaryOffset.y = 0;
    /// kernelOffset.x = -_offset.x + (~(NSInteger) kW_Dilated
    /// &
    /// 1L);
    /// kernelOffset.y = -_offset.y + (~(NSInteger) kH_Dilated
    /// &
    /// 1L);
    /// Convolution gradient with data does not use secondaryOffset.
    ///
    /// Convolution Gradient with Weights and Biases
    /// ============================================
    /// For consistent padding policy with respect to forward convolution,
    /// secondaryOffset.x = _offset.x - kW_Dilated/2
    /// secondaryOffset.y = _offset.y - kH_Dilated/2
    /// Convolution gradient with weights and biases does not use primaryOffset (or it is assumed to be zero) as summation is over entire
    /// gradient image and only gradient image without any padding is currently accepted. If previous layer produces gradient image with
    /// padding, slice operation should be used to extract out the gradient which will be input to MPSCNNConvolutionGradient.
    ///
    /// Note that if application uses encode method that return destination gradient on left hand side and consumes MPSCNNConvolutionGradientState
    /// object produced by forward MPSCNNConvolution, all these parameters are set automatically for the application i.e. applicaiton does not
    /// need to worry about setting these.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiongradient?language=objc)
    #[unsafe(super(MPSCNNGradientKernel, MPSCNNBinaryKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNConvolutionGradient;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNConvolutionGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNConvolutionGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNConvolutionGradient {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNConvolutionGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionGradient {
    extern_methods!(
        /// The number of feature channels per pixel in the gradient image (primarySource) of encode call. This is same is outputFeatureChannels
        /// or the feature channels of destination image in forward convolution i.e. dataSource.descriptor.outputFeatureChannels
        #[unsafe(method(sourceGradientFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn sourceGradientFeatureChannels(&self) -> NSUInteger;

        /// The number of feature channels per pixel in the input image to forward convolution which is used here as secondarySource.
        /// This is same as dataSource.descriptor.inputFeatureChannels. This is also the number of feature channels in destinatin image
        /// here i.e. gradient with respect to data.
        #[unsafe(method(sourceImageFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn sourceImageFeatureChannels(&self) -> NSUInteger;

        /// Number of groups input and output channels are divided into.
        #[unsafe(method(groups))]
        #[unsafe(method_family = none)]
        pub unsafe fn groups(&self) -> NSUInteger;

        /// Channel multiplier.
        ///
        /// For convolution created with MPSCNNDepthWiseConvolutionDescriptor, it is the number of
        /// output feature channels for each input channel. See MPSCNNDepthWiseConvolutionDescriptor for more details.
        /// Default is 0 which means regular CNN convolution. Currently only channelMultiplier of 1 is supported i.e. inputChannels == outputChannels
        #[unsafe(method(channelMultiplier))]
        #[unsafe(method_family = none)]
        pub unsafe fn channelMultiplier(&self) -> NSUInteger;

        /// dataSource with which gradient object was created
        #[unsafe(method(dataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn dataSource(
            &self,
        ) -> Retained<ProtocolObject<dyn MPSCNNConvolutionDataSource>>;

        /// Option to control which gradient to compute. Default is MPSCNNConvolutionGradientOptionAll
        /// which means both gradient with respect to data and gradient with respect to weight and bias are computed.
        #[unsafe(method(gradientOption))]
        #[unsafe(method_family = none)]
        pub unsafe fn gradientOption(&self) -> MPSCNNConvolutionGradientOption;

        /// Setter for [`gradientOption`][Self::gradientOption].
        #[unsafe(method(setGradientOption:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setGradientOption(&self, gradient_option: MPSCNNConvolutionGradientOption);

        /// Property to control serialization of weights and bias.
        ///
        /// During serialization of convolution object in -encodeWithCoder call, weights and biases are saved so that convolution
        /// object can be properly unserialized/restored in -initWithCoder call. If data source provied is NSSecureCoding compliant,
        /// data source is serialized else weights and biases are serialized.
        /// As weights/biases data may be several MB and these are same for both gradient and forward convolution object,
        /// application may already have weights/biases on disk through convolution, it can
        /// save disk space by setting this property false so convolution gradient object does not end up storing another copy of weights/biases.
        /// Default is NO. When application decides to set it to NO, it MUST call
        /// -(void) reloadWeightsAndBiasesFromDataSource
        /// after initWithCoder has initialized convolution object.
        #[deprecated]
        #[unsafe(method(serializeWeightsAndBiases))]
        #[unsafe(method_family = none)]
        pub unsafe fn serializeWeightsAndBiases(&self) -> bool;

        /// Setter for [`serializeWeightsAndBiases`][Self::serializeWeightsAndBiases].
        #[deprecated]
        #[unsafe(method(setSerializeWeightsAndBiases:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setSerializeWeightsAndBiases(&self, serialize_weights_and_biases: bool);

        /// Initializes a convolution gradient (with respect to weights and bias) object.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolutionGradient filter will be used
        ///
        /// Parameter `weights`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource
        /// protocol. Note that same data source as provided to forward convolution should be used.
        ///
        ///
        /// Returns: A valid MPSCNNConvolutionGradient object or nil, if failure.
        #[unsafe(method(initWithDevice:weights:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_weights(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            weights: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;

        /// CPU side reload. Reload the updated weights and biases from data provider into internal weights and bias buffers. Weights and biases
        /// gradients needed for update are obtained from MPSCNNConvolutionGradientState object. Data provider passed in init call is used for this purpose.
        #[unsafe(method(reloadWeightsAndBiasesFromDataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesFromDataSource(&self);

        #[cfg(feature = "MPSState")]
        /// GPU side reload. Reload the updated weights and biases from update buffer produced by application enqueued metal kernel into internal weights
        /// and biases buffer. Weights and biases gradients needed for update are obtained from MPSCNNConvolutionGradientState object's gradientForWeights and gradientForBiases metal buffer.
        ///
        ///
        /// Parameter `commandBuffer`: Metal command buffer on which application update kernel was enqueued consuming MPSCNNConvolutionGradientState's gradientForWeights and gradientForBiases buffer
        /// and producing updateBuffer metal buffer.
        ///
        /// Parameter `state`: MPSCNNConvolutionWeightsAndBiasesState containing weights and biases buffers which have updated weights produced by application's update kernel.
        #[unsafe(method(reloadWeightsAndBiasesWithCommandBuffer:state:))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesWithCommandBuffer_state(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            state: &MPSCNNConvolutionWeightsAndBiasesState,
        );
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionGradient {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionGradient {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNFullyConnected specifies a fully connected convolution layer a.k.a. Inner product
    /// layer. A fully connected CNN layer is one where every input channel is connected
    /// to every output channel. The kernel width is equal to width of source image
    /// and the kernel height is equal to the height of source image. Width and height of the output
    /// is 1x1. Thus, it takes a srcW x srcH x Ni MPSCNNImage, convolves it with Weights[No][SrcW][srcH][Ni]
    /// and produces a 1 x 1 x No output. The following must be true:
    ///
    /// ```text
    ///                          kernelWidth  == source.width
    ///                          kernelHeight == source.height
    ///                          clipRect.size.width == 1
    ///                          clipRect.size.height == 1
    /// ```
    ///
    /// One can think of a fully connected layer as a matrix multiplication that flattens an image into a vector of length
    /// srcW*srcH*Ni. The weights are arragned in a matrix of dimension No x (srcW*srcH*Ni) for product output vectors
    /// of length No. The strideInPixelsX, strideInPixelsY, and group must be 1. Offset is not applicable and is ignored.
    /// Since clipRect is clamped to the destination image bounds, if the destination is 1x1, one doesn't need to set the
    /// clipRect.
    ///
    /// Note that one can implement an inner product using MPSCNNConvolution by setting
    ///
    /// ```text
    ///                      offset = (kernelWidth/2,kernelHeight/2)
    ///                      clipRect.origin = (ox,oy), clipRect.size = (1,1)
    ///                      strideX = strideY = group = 1
    /// ```
    ///
    /// However, using the MPSCNNFullyConnected for this is better for performance as it lets us choose the most
    /// performant method which may not be possible when using a general convolution. For example,
    /// we may internally use matrix multiplication or special reduction kernels for a specific platform.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnfullyconnected?language=objc)
    #[unsafe(super(MPSCNNConvolution, MPSCNNKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNFullyConnected;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNFullyConnected {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNFullyConnected {
    extern_methods!(
        /// Initializes a fully connected kernel
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNFullyConnected filter will be used
        ///
        /// Parameter `weights`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource
        /// protocol. The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNFullyConnected uses to obtain the weights and bias terms
        /// for the CNN fully connected filter.
        ///
        ///
        /// Returns: A valid MPSCNNFullyConnected object or nil, if failure.
        #[unsafe(method(initWithDevice:weights:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_weights(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            weights: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        ) -> Retained<Self>;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Initializes a convolution kernel
        /// WARNING:                        This API is depreated and will be removed in the future. It cannot be used
        /// when training. Also serialization/unserialization wont work for MPSCNNConvolution
        /// objects created with this init. Please move onto using initWithDevice:weights:.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolution filter will be used
        ///
        /// Parameter `convolutionDescriptor`: A pointer to a MPSCNNConvolutionDescriptor.
        ///
        /// Parameter `kernelWeights`: A pointer to a weights array.  Each entry is a float value. The number of entries is =
        /// inputFeatureChannels * outputFeatureChannels * kernelHeight * kernelWidth
        /// The layout of filter weight is so that it can be reinterpreted as 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ inputChannels / groups ]
        /// Weights are converted to half float (fp16) internally for best performance.
        ///
        /// Parameter `biasTerms`: A pointer to bias terms to be applied to the convolution output.  Each entry is a float value.
        /// The number of entries is = numberOfOutputFeatureMaps
        ///
        /// Parameter `flags`: Currently unused. Pass MPSCNNConvolutionFlagsNone
        ///
        ///
        /// Returns: A valid MPSCNNConvolution object or nil, if failure.
        ///
        /// # Safety
        ///
        /// - `kernel_weights` must be a valid pointer.
        /// - `bias_terms` must be a valid pointer or null.
        #[deprecated]
        #[unsafe(method(initWithDevice:convolutionDescriptor:kernelWeights:biasTerms:flags:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_convolutionDescriptor_kernelWeights_biasTerms_flags(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            convolution_descriptor: &MPSCNNConvolutionDescriptor,
            kernel_weights: NonNull<c_float>,
            bias_terms: *const c_float,
            flags: MPSCNNConvolutionFlags,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNFullyConnected {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNFullyConnected {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// Compute the gradient for fully connected layer.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnfullyconnectedgradient?language=objc)
    #[unsafe(super(
        MPSCNNConvolutionGradient,
        MPSCNNGradientKernel,
        MPSCNNBinaryKernel,
        MPSKernel,
        NSObject
    ))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNFullyConnectedGradient;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNFullyConnectedGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNFullyConnectedGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNFullyConnectedGradient {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNFullyConnectedGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNFullyConnectedGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNFullyConnectedGradient {
    extern_methods!(
        /// Initializes a convolution gradient (with respect to weights and bias) object.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolutionGradient filter will be used
        ///
        /// Parameter `weights`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource
        /// protocol. Note that same data source as provided to forward convolution should be used.
        ///
        ///
        /// Returns: A valid MPSCNNConvolutionGradient object or nil, if failure.
        #[unsafe(method(initWithDevice:weights:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_weights(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            weights: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNFullyConnectedGradient {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNFullyConnectedGradient {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNConvolutionTranspose specifies a transposed convolution.
    /// The MPSCNNConvolutionTranspose convolves the input image with a set of filters, each producing one feature map in the output image.
    ///
    /// Some third-party frameworks may rotate the weights spatially by 180 degrees for Convolution Transpose. MPS uses the weights
    /// specified by the developer as-is and does not perform any rotation. The developer may need to rotate the weights appropriately
    /// in case this rotation is needed before the convolution transpose is applied.
    ///
    /// When the stride in any dimension is greater than 1, the convolution transpose puts (stride - 1) zeroes in-between the source
    /// image pixels to create an expanded image. Then a convolution is done over the expanded image to generate the output of the
    /// convolution transpose.
    ///
    /// Intermediate image size = (srcSize - 1) * Stride + 1
    ///
    /// Examples:
    ///
    ///
    /// ```text
    ///               So in case of sride == 2 (this behaves same in both dimensions)
    ///
    ///               Source image:
    ///                _______________
    ///               |   |   |   |   |
    ///               | 1 | 2 | 3 | 4 |
    ///               |   |   |   |   |
    ///                ---------------
    ///
    ///               Intermediate Image:
    ///                ___________________________
    ///               |   |   |   |   |   |   |   |
    ///               | 1 | 0 | 2 | 0 | 3 | 0 | 4 |
    ///               |   |   |   |   |   |   |   |
    ///                ---------------------------
    ///
    ///
    ///               NOTE on Offset:
    ///               There are 2 types of offsets defined:
    ///               1) The Offset defined in MPSCNNKernel from which MPSCNNConvolutionTranspose inherits. This offset is applied to from where
    ///                  the kernel will be applied on the source.
    ///               2) The kernelOffsetX and kernelOffsetY which is the offset applied to the kernel when it is finally applied on the intermediate
    ///                  image.
    ///
    ///               So totalOffset = Offset * stride + kernelOffset
    ///
    ///               The offset defined by user refers to the coordinate frame of the expanded image
    ///               (we are showing only 1 dimension X it can be extended to Y dimension as well) :
    ///
    ///               X indicates where the convolution transpose begins:
    ///
    ///               Intermediate Image:  Offset = 0, kernelOffset = 0
    ///                ___________________________
    ///               |   |   |   |   |   |   |   |
    ///               | 1 | 0 | 2 | 0 | 3 | 0 | 4 |
    ///               | X |   |   |   |   |   |   |
    ///                ---------------------------
    ///
    ///
    ///               X indicates where the convolution transpose begins:
    ///
    ///               Intermediate Image:  Offset = 0, kernelOffset = 1
    ///                ___________________________
    ///               |   |   |   |   |   |   |   |
    ///               | 1 | 0 | 2 | 0 | 3 | 0 | 4 |
    ///               |   | X |   |   |   |   |   |
    ///                ---------------------------
    ///
    ///
    ///               X indicates where the convolution transpose begins:
    ///
    ///               Intermediate Image:  Offset = 0, kernelOffset = -1
    ///                  ___________________________
    ///                 |   |   |   |   |   |   |   |
    ///               X | 1 | 0 | 2 | 0 | 3 | 0 | 4 |
    ///                 |   |   |   |   |   |   |   |
    ///                  ---------------------------
    ///
    ///
    ///
    ///
    ///               So if the user wanted to apply an offset of 2 on the source image of convolution transpose:
    ///
    ///               Source image:
    ///                _______________
    ///               |   |   |   |   |
    ///               | 1 | 2 | 3 | 4 |
    ///               |   |   | X |   |
    ///                ---------------
    ///
    ///               offset = 2, kernelOffset = 0
    ///
    ///               Intermediate Image:
    ///                ___________________________
    ///               |   |   |   |   |   |   |   |
    ///               | 1 | 0 | 2 | 0 | 3 | 0 | 4 |
    ///               |   |   |   |   | X |   |   |
    ///                ---------------------------
    ///
    /// ```
    ///
    /// Note that if your application is not using MPSCNNConvolutionGradientState to configure the convolution transpose with respect to convolution,
    /// your application may do this using padding policy. In such case if convolution uses valid padding policy, than convolution transpose should use
    /// full padding policy and vice vera. Full padding remains full.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiontranspose?language=objc)
    #[unsafe(super(MPSCNNKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNConvolutionTranspose;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNConvolutionTranspose {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNConvolutionTranspose {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNConvolutionTranspose {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionTranspose {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNConvolutionTranspose {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionTranspose {
    extern_methods!(
        /// The number of feature channels per pixel in the input image.
        #[unsafe(method(inputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn inputFeatureChannels(&self) -> NSUInteger;

        /// The number of feature channels per pixel in the output image.
        #[unsafe(method(outputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn outputFeatureChannels(&self) -> NSUInteger;

        /// Offset in X from which the kernel starts sliding
        #[unsafe(method(kernelOffsetX))]
        #[unsafe(method_family = none)]
        pub unsafe fn kernelOffsetX(&self) -> NSInteger;

        /// Setter for [`kernelOffsetX`][Self::kernelOffsetX].
        #[unsafe(method(setKernelOffsetX:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setKernelOffsetX(&self, kernel_offset_x: NSInteger);

        /// Offset in Y from which the kernel starts sliding
        #[unsafe(method(kernelOffsetY))]
        #[unsafe(method_family = none)]
        pub unsafe fn kernelOffsetY(&self) -> NSInteger;

        /// Setter for [`kernelOffsetY`][Self::kernelOffsetY].
        #[unsafe(method(setKernelOffsetY:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setKernelOffsetY(&self, kernel_offset_y: NSInteger);

        /// Number of groups input and output channels are divided into.
        #[unsafe(method(groups))]
        #[unsafe(method_family = none)]
        pub unsafe fn groups(&self) -> NSUInteger;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Precision of accumulator used in convolution.
        ///
        /// See MPSNeuralNetworkTypes.h for discussion. Default is MPSNNConvolutionAccumulatorPrecisionOptionFloat.
        #[unsafe(method(accumulatorPrecisionOption))]
        #[unsafe(method_family = none)]
        pub unsafe fn accumulatorPrecisionOption(
            &self,
        ) -> MPSNNConvolutionAccumulatorPrecisionOption;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Setter for [`accumulatorPrecisionOption`][Self::accumulatorPrecisionOption].
        #[unsafe(method(setAccumulatorPrecisionOption:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setAccumulatorPrecisionOption(
            &self,
            accumulator_precision_option: MPSNNConvolutionAccumulatorPrecisionOption,
        );

        /// dataSource with which convolution transpose object was created
        #[unsafe(method(dataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn dataSource(
            &self,
        ) -> Retained<ProtocolObject<dyn MPSCNNConvolutionDataSource>>;

        /// Initializes a convolution transpose kernel
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolutionTranspose filter will be used
        ///
        /// Parameter `weights`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource
        /// protocol. The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNConvolutionTranspose uses to obtain the weights and bias terms
        /// for the CNN convolutionTranspose filter. Currently we support only Float32 weights.
        ///
        ///
        /// Returns: A valid MPSCNNConvolutionTranspose object.
        #[unsafe(method(initWithDevice:weights:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_weights(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            weights: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        ) -> Retained<Self>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;

        /// <NSSecureCoding
        /// > support
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        /// Encode a MPSCNNKernel into a command Buffer. Create a texture to hold the result and return it.
        ///
        /// In the first iteration on this method, encodeToCommandBuffer:sourceImage:destinationImage:
        /// some work was left for the developer to do in the form of correctly setting the offset property
        /// and sizing the result buffer. With the introduction of the padding policy (see padding property)
        /// the filter can do this work itself. If you would like to have some input into what sort of MPSImage
        /// (e.g. temporary vs. regular) or what size it is or where it is allocated, you may set the
        /// destinationImageAllocator to allocate the image yourself.
        ///
        /// This method uses the MPSNNPadding padding property to figure out how to size
        /// the result image and to set the offset property. See discussion in MPSNeuralNetworkTypes.h.
        ///
        /// Note: the regular encodeToCommandBuffer:sourceImage: method may be used when no state is needed,
        /// such as when the convolution transpose operation is not balanced by a matching convolution object upstream.
        /// These encode methods are for auto encoders where each convolution in inference pass is coupled with convolution
        /// transpose. In order for convolution transpose to correctly undo the convolution downsampling, MPSCNNConvolutionGradientState
        /// produced by convolution is needed by convolution transpose to correctly size destination image.
        /// These methods are only useful for inference only network. For training, use encode methods that take MPSCNNConvolutionTransposeGradientState below.
        ///
        ///
        /// Parameter `commandBuffer`: The command buffer
        ///
        /// Parameter `sourceImage`: A MPSImage to use as the source images for the filter.
        ///
        /// Parameter `convolutionGradientState`: A valid MPSCNNConvolutionGradientState from the MPSCNNConvoluton counterpart to this MPSCNNConvolutionTranspose.
        /// If there is no forward convolution counterpart, pass NULL here. This state affects the sizing
        /// the result.
        ///
        /// Returns: A MPSImage or MPSTemporaryImage allocated per the destinationImageAllocator containing the output of the graph.
        /// The offset property will be adjusted to reflect the offset used during the encode.
        /// The returned image will be automatically released when the command buffer completes. If you want to
        /// keep it around for longer, retain the image. (ARC will do this for you if you use it later.)
        #[unsafe(method(encodeToCommandBuffer:sourceImage:convolutionGradientState:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeToCommandBuffer_sourceImage_convolutionGradientState(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImage,
            convolution_gradient_state: Option<&MPSCNNConvolutionGradientState>,
        ) -> Retained<MPSImage>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(encodeBatchToCommandBuffer:sourceImages:convolutionGradientStates:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeBatchToCommandBuffer_sourceImages_convolutionGradientStates(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImageBatch,
            convolution_gradient_state: Option<&MPSCNNConvolutionGradientStateBatch>,
        ) -> Retained<MPSImageBatch>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(encodeToCommandBuffer:sourceImage:convolutionGradientState:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeToCommandBuffer_sourceImage_convolutionGradientState_destinationImage(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImage,
            convolution_gradient_state: Option<&MPSCNNConvolutionGradientState>,
            destination_image: &MPSImage,
        );

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(encodeBatchToCommandBuffer:sourceImages:convolutionGradientStates:destinationImages:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeBatchToCommandBuffer_sourceImages_convolutionGradientStates_destinationImages(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImageBatch,
            convolution_gradient_state: Option<&MPSCNNConvolutionGradientStateBatch>,
            destination_image: &MPSImageBatch,
        );

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        /// Allocate a MPCNNConvolutionTransposeGradientState to hold the results from a -encodeBatchToCommandBuffer... operation
        ///
        ///
        /// Parameter `sourceImage`: The MPSImage consumed by the associated -encode call.
        ///
        /// Parameter `sourceStates`: The list of MPSCNNConvolutionGradientState consumed by the associated -encode call,
        /// for a batch size of 1. In auto encoders, this state is produced by corresponding MPSCNNConvolution.
        ///
        ///
        /// Returns: The list of states produced by the -encode call for batch size of 1.
        /// -isResultStateReusedAcrossBatch returns YES for MPSCNNConvolutionTranspose so same
        /// state is used across entire batch. State object is not reusasable across batches.
        #[unsafe(method(resultStateForSourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn resultStateForSourceImage_sourceStates_destinationImage(
            &self,
            source_image: &MPSImage,
            source_states: Option<&NSArray<MPSCNNConvolutionGradientState>>,
            destination_image: &MPSImage,
        ) -> Option<Retained<MPSCNNConvolutionTransposeGradientState>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(resultStateBatchForSourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn resultStateBatchForSourceImage_sourceStates_destinationImage(
            &self,
            source_image: &MPSImageBatch,
            source_states: Option<&NSArray<MPSCNNConvolutionGradientStateBatch>>,
            destination_image: &MPSImageBatch,
        ) -> Option<Retained<MPSCNNConvolutionTransposeGradientStateBatch>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(temporaryResultStateForCommandBuffer:sourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryResultStateForCommandBuffer_sourceImage_sourceStates_destinationImage(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImage,
            source_states: Option<&NSArray<MPSCNNConvolutionGradientState>>,
            destination_image: &MPSImage,
        ) -> Option<Retained<MPSCNNConvolutionTransposeGradientState>>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(temporaryResultStateBatchForCommandBuffer:sourceImage:sourceStates:destinationImage:))]
        #[unsafe(method_family = none)]
        pub unsafe fn temporaryResultStateBatchForCommandBuffer_sourceImage_sourceStates_destinationImage(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImageBatch,
            source_states: Option<&NSArray<MPSCNNConvolutionGradientStateBatch>>,
            destination_image: &MPSImageBatch,
        ) -> Option<Retained<MPSCNNConvolutionTransposeGradientStateBatch>>;

        /// CPU side reload. Reload the updated weights and biases from data provider into internal weights and bias buffers. Weights and biases
        /// gradients needed for update are obtained from MPSCNNConvolutionTransposeGradientState object. Data provider passed in init call is used for this purpose.
        #[unsafe(method(reloadWeightsAndBiasesFromDataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesFromDataSource(&self);

        #[cfg(feature = "MPSState")]
        /// GPU side reload. Reload the updated weights and biases from update buffer produced by application enqueued metal kernel into internal weights
        /// and biases buffer. Weights and biases gradients needed for update are obtained from MPSCNNConvolutionTransposeGradientState object's gradientForWeights and gradientForBiases metal buffer.
        ///
        ///
        /// Parameter `commandBuffer`: Metal command buffer on which application update kernel was enqueued consuming MPSCNNConvolutionGradientState's gradientForWeights and gradientForBiases buffers
        /// and producing updateBuffer metal buffer.
        ///
        /// Parameter `state`: MPSCNNConvolutionWeightsAndBiasesState containing weights and biases buffers which have updated weights produced by application's update kernel.
        /// The state readcount will be decremented.
        #[unsafe(method(reloadWeightsAndBiasesWithCommandBuffer:state:))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesWithCommandBuffer_state(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            state: &MPSCNNConvolutionWeightsAndBiasesState,
        );

        #[cfg(feature = "MPSState")]
        /// GPU side export. Enqueue a kernel to export current weights and biases stored in MPSCNNConvoltionTranspose's internal buffers into weights and biases MTLBuffer
        /// returned in MPSCNNConvolutionWeightsAndBiasesState.
        ///
        ///
        /// Parameter `commandBuffer`: Metal command buffer on which export kernel is enqueued.
        ///
        /// Parameter `resultStateCanBeTemporary`: If FALSE, state returned will be non-temporary. If TRUE, returned state may or may not be temporary.
        ///
        /// Returns: MPSCNNConvolutionWeightsAndBiasesState containing weights and biases buffer to which weights got exported. This state and be
        /// temporary or non-temporary depending on the flag resultStateCanBeTemporary
        #[unsafe(method(exportWeightsAndBiasesWithCommandBuffer:resultStateCanBeTemporary:))]
        #[unsafe(method_family = none)]
        pub unsafe fn exportWeightsAndBiasesWithCommandBuffer_resultStateCanBeTemporary(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            result_state_can_be_temporary: bool,
        ) -> Retained<MPSCNNConvolutionWeightsAndBiasesState>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        /// These low level encode functions should be used during training. The first two encode functions, which return
        /// destination image on left hand side, takes in MPSCNNConvolutionGradientState that was produced by corresponding
        /// MPSCNNConvolution when there is one e.g. auto encoders. This state is used to correctly size destination being returned.
        /// These encode methods return MPSCNNConvoltionTransposeGradientState object on auto release pool to be consumed by MPSCNNConvolutionTransposeGradient.
        #[unsafe(method(encodeToCommandBuffer:sourceImage:convolutionGradientState:destinationState:destinationStateIsTemporary:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeToCommandBuffer_sourceImage_convolutionGradientState_destinationState_destinationStateIsTemporary(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_image: &MPSImage,
            convolution_gradient_state: Option<&MPSCNNConvolutionGradientState>,
            out_state: &mut Option<Retained<MPSCNNConvolutionTransposeGradientState>>,
            is_temporary: bool,
        ) -> Retained<MPSImage>;

        #[cfg(all(
            feature = "MPSImage",
            feature = "MPSNDArray",
            feature = "MPSNNGradientState",
            feature = "MPSState"
        ))]
        #[unsafe(method(encodeBatchToCommandBuffer:sourceImages:convolutionGradientStates:destinationStates:destinationStateIsTemporary:))]
        #[unsafe(method_family = none)]
        pub unsafe fn encodeBatchToCommandBuffer_sourceImages_convolutionGradientStates_destinationStates_destinationStateIsTemporary(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            source_images: &MPSImageBatch,
            convolution_gradient_states: Option<&MPSCNNConvolutionGradientStateBatch>,
            out_states: &mut Option<Retained<MPSCNNConvolutionTransposeGradientStateBatch>>,
            is_temporary: bool,
        ) -> Retained<MPSImageBatch>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionTranspose {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionTranspose {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNConvolutionTransposeGradient implementents backward propagation of gradient for MPSCNNConvolutionTranspose forward filter
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnconvolutiontransposegradient?language=objc)
    #[unsafe(super(MPSCNNGradientKernel, MPSCNNBinaryKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNConvolutionTransposeGradient;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNConvolutionTransposeGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNConvolutionTransposeGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNConvolutionTransposeGradient {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNConvolutionTransposeGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNConvolutionTransposeGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionTransposeGradient {
    extern_methods!(
        /// The number of feature channels per pixel in the gradient image (primarySource) of encode call. This is same is outputFeatureChannels
        /// or the feature channels of destination image in forward convolution i.e. dataSource.descriptor.outputFeatureChannels
        #[unsafe(method(sourceGradientFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn sourceGradientFeatureChannels(&self) -> NSUInteger;

        /// The number of feature channels per pixel in the input image to forward convolution which is used here as secondarySource.
        /// This is same as dataSource.descriptor.inputFeatureChannels. This is also the number of feature channels in destinatin image
        /// here i.e. gradient with respect to data.
        #[unsafe(method(sourceImageFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn sourceImageFeatureChannels(&self) -> NSUInteger;

        /// Number of groups input and output channels are divided into.
        #[unsafe(method(groups))]
        #[unsafe(method_family = none)]
        pub unsafe fn groups(&self) -> NSUInteger;

        /// dataSource with which gradient object was created
        #[unsafe(method(dataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn dataSource(
            &self,
        ) -> Retained<ProtocolObject<dyn MPSCNNConvolutionDataSource>>;

        /// Option to control which gradient to compute. Default is MPSCNNConvolutionGradientOptionAll
        /// which means both gradient with respect to data and gradient with respect to weight and bias are computed.
        #[unsafe(method(gradientOption))]
        #[unsafe(method_family = none)]
        pub unsafe fn gradientOption(&self) -> MPSCNNConvolutionGradientOption;

        /// Setter for [`gradientOption`][Self::gradientOption].
        #[unsafe(method(setGradientOption:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setGradientOption(&self, gradient_option: MPSCNNConvolutionGradientOption);

        /// Initializes a convolution transpose gradient (with respect to weights and bias) object.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNConvolutionGradient filter will be used
        ///
        /// Parameter `weights`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource
        /// protocol. Note that same data source as provided to forward convolution should be used.
        ///
        ///
        /// Returns: A valid MPSCNNConvolutionTransposeGradient object or nil, if failure.
        #[unsafe(method(initWithDevice:weights:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_weights(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            weights: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;

        /// CPU side reload. Reload the updated weights and biases from data provider into internal weights and bias buffers. Weights and biases
        /// gradients needed for update are obtained from MPSCNNConvolutionGradientState object. Data provider passed in init call is used for this purpose.
        #[unsafe(method(reloadWeightsAndBiasesFromDataSource))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesFromDataSource(&self);

        #[cfg(feature = "MPSState")]
        /// GPU side reload. Reload the updated weights and biases from update buffer produced by application enqueued metal kernel into internal weights
        /// and biases buffer. Weights and biases gradients needed for update are obtained from MPSCNNConvolutionGradientState object's gradientForWeights and gradientForBiases metal buffer.
        ///
        ///
        /// Parameter `commandBuffer`: Metal command buffer on which application update kernel was enqueued consuming MPSCNNConvolutionGradientState's gradientForWeights and gradientForBiases buffer
        /// and producing updateBuffer metal buffer.
        ///
        /// Parameter `state`: MPSCNNConvolutionWeightsAndBiasesState containing weights and biases buffers which have updated weights produced by application's update kernel.
        #[unsafe(method(reloadWeightsAndBiasesWithCommandBuffer:state:))]
        #[unsafe(method_family = none)]
        pub unsafe fn reloadWeightsAndBiasesWithCommandBuffer_state(
            &self,
            command_buffer: &ProtocolObject<dyn MTLCommandBuffer>,
            state: &MPSCNNConvolutionWeightsAndBiasesState,
        );
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionTransposeGradient {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNConvolutionTransposeGradient {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNBinaryConvolution specifies a convolution with binary weights and an input image using binary approximations.
    /// The MPSCNNBinaryConvolution optionally first binarizes the input image and then convolves the result with a set of
    /// binary-valued filters, each producing one feature map in the output image (which is a normal image)
    ///
    /// The output is computed as follows:
    ///
    /// out[i, x, y, c] = ( sum_{dx,dy,f} in[i,x+dx, y+dy, f] x B[c,dx,dy,f] )
    /// * scale[c] * beta[i,x,y] + bias[c], where
    ///
    /// the sum over dx,dy is over the spatial filter kernel window defined by 'kernelWidth' and 'KernelHeight',
    /// sum over 'f' is over the input feature channel indices within group, 'B' contains the binary weights, interpreted as
    /// {-1,1} or { 0, 1 } and scale[c] is the 'outputScaleTerms' array and bias is the 'outputBiasTerms' array. Above 'i' is
    /// the image index in batch the sum over input channels 'f' runs through the group indices.
    ///
    /// The convolution operator 'x' is defined by MPSCNNBinaryConvolutionType passed in at initialization time of the filter
    /// (
    ///
    /// See: initWithDevice).
    /// In case 'type' = MPSCNNBinaryConvolutionTypeBinaryWeights, the input image is not binarized at all
    /// and the convolution is computed interpreting the weights as [ 0, 1 ] -> { -1, 1 } with the given scaling terms.
    /// In case 'type' = MPSCNNBinaryConvolutionTypeXNOR the convolution is computed by first binarizing the input image
    /// using the sign function 'bin(x) = x
    /// <
    /// 0 ? -1 : 1' and the convolution multiplication is done with the
    /// XNOR-operator !(x ^ y) = delta_xy = { (x==y) ? 1 : 0 },
    /// and scaled according to the optional scaling operations. Note that we output the values of the bitwise convolutions
    /// to interval { -1, 1 }, which means that the output of the XNOR-operator is scaled implicitly as follows:
    /// r = 2 * ( !(x ^ y) ) - 1 = { -1, 1 }.
    /// This means that for a dot-product of two 32-bit words the result is:
    /// r = 2 * popcount(!(x ^ y) ) - 32 = 32 - 2 * popcount( x ^ y ) = { -32, -30, ..., 30, 32 }.
    /// In case 'type' = MPSCNNBinaryConvolutionTypeAND the convolution is computed by first binarizing the input image
    /// using the sign function 'bin(x) = x
    /// <
    /// 0 ? -1 : 1' and the convolution multiplication is done with the
    /// AND-operator (x
    /// &
    /// y) = delta_xy * delta_x1 = { (x==y==1) ? 1 : 0 }.
    /// and scaled according to the optional scaling operations. Note that we output the values of the AND-operation is
    /// assumed to lie in { 0, 1 } interval and hence no more implicit scaling takes place.
    /// This means that for a dot-product of two 32-bit words the result is:
    /// r = popcount(x
    /// &
    /// y) = { 0, ..., 31, 32 }.
    ///
    /// The input data can be pre-offset and scaled by providing the 'inputBiasTerms' and 'inputScaleTerms' parameters for the
    /// initialization functions and this can be used for example to accomplish batch normalization of the data. The scaling of
    /// input values happens before possible beta-image computation.
    ///
    /// The parameter 'beta' above is an optional image which is used to compute scaling factors for each spatial position and image index.
    /// For the XNOR-Net based networks this is computed as follows: beta[i,x,y] = sum_{dx,dy} A[i, x+dx, y+dy] / (kx * ky), where
    /// (dx,dy) are summed over the convolution filter window [ -kx/2, (kx-1)/2], [ -ky/2, (ky-1)/2 ] and
    /// A[i,x,y] = sum_{c} abs( in[i,x,y,c] ) / Nc, where 'in' is the original input image (in full precision) and Nc is the
    /// number of input channels in the input image. Parameter 'beta' is not passed as input and to enable beta-scaling the user can
    /// provide 'MPSCNNBinaryConvolutionFlagsUseBetaScaling' in the flags parameter in the initialization functions.
    ///
    /// Finally the normal activation neuron is applied and the result is written to the output image.
    ///
    /// NOTE: MPSCNNBinaryConvolution does not currently support groups > 1.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnbinaryconvolution?language=objc)
    #[unsafe(super(MPSCNNKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNBinaryConvolution;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNBinaryConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNBinaryConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNBinaryConvolution {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNBinaryConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNBinaryConvolution {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNBinaryConvolution {
    extern_methods!(
        #[unsafe(method(inputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn inputFeatureChannels(&self) -> NSUInteger;

        /// The number of feature channels per pixel in the output image.
        #[unsafe(method(outputFeatureChannels))]
        #[unsafe(method_family = none)]
        pub unsafe fn outputFeatureChannels(&self) -> NSUInteger;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Initializes a binary convolution kernel with binary weights and a single scaling term.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNBinaryConvolution filter will be used
        ///
        /// Parameter `convolutionData`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol.
        /// The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNBinaryConvolution uses to obtain the weights and bias terms as
        /// well as the convolution descriptor.
        /// Each entry in the convolutionData:weights array is a 32-bit unsigned integer value
        /// and each bit represents one filter weight (given in machine byte order).
        /// The featurechannel indices increase from the least significant bit within the 32-bits.
        /// The number of entries is =
        /// ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth
        /// The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ]
        /// (The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on
        /// inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally
        /// outputChannels varies least rapidly.)
        ///
        /// Parameter `scaleValue`: A floating point value used to scale the entire convolution.
        ///
        /// Parameter `type`: What kind of binarization strategy is to be used.
        ///
        /// Parameter `flags`: See documentation above and documentation of MPSCNNBinaryConvolutionFlags.
        ///
        ///
        /// Returns: A valid MPSCNNBinaryConvolution object or nil, if failure.
        #[unsafe(method(initWithDevice:convolutionData:scaleValue:type:flags:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_convolutionData_scaleValue_type_flags(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            convolution_data: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
            scale_value: c_float,
            r#type: MPSCNNBinaryConvolutionType,
            flags: MPSCNNBinaryConvolutionFlags,
        ) -> Retained<Self>;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Initializes a binary convolution kernel with binary weights as well as both pre and post scaling terms.
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNBinaryConvolution filter will be used
        ///
        /// Parameter `convolutionData`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol.
        /// The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNBinaryConvolution uses to obtain the weights and the convolution descriptor.
        /// Each entry in the convolutionData:weights array is a 32-bit unsigned integer value
        /// and each bit represents one filter weight (given in machine byte order).
        /// The featurechannel indices increase from the least significant bit within the 32-bits.
        /// The number of entries is =
        /// ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth
        /// The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ]
        /// (The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on
        /// inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally
        /// outputChannels varies least rapidly.)
        ///
        /// Parameter `outputBiasTerms`: A pointer to bias terms to be applied to the convolution output.  Each entry is a float value.
        /// The number of entries is = numberOfOutputFeatureMaps. If nil then 0.0 is used for bias.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `outputScaleTerms`: A pointer to scale terms to be applied to binary convolution results per output feature channel.
        /// Each entry is a float value. The number of entries is = numberOfOutputFeatureMaps. If nil then 1.0 is used.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `inputBiasTerms`: A pointer to offset terms to be applied to the input before convolution and before input scaling.
        /// Each entry is a float value. The number of entries is 'inputFeatureChannels'. If NULL then 0.0 is used for bias.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `inputScaleTerms`: A pointer to scale terms to be applied to the input before convolution, but after input biasing.
        /// Each entry is a float value. The number of entries is 'inputFeatureChannels'. If nil then 1.0 is used.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `type`: What kind of binarization strategy is to be used.
        ///
        /// Parameter `flags`: See documentation above and documentation of MPSCNNBinaryConvolutionFlags.
        ///
        ///
        /// Returns: A valid MPSCNNBinaryConvolution object or nil, if failure.
        ///
        /// # Safety
        ///
        /// - `output_bias_terms` must be a valid pointer or null.
        /// - `output_scale_terms` must be a valid pointer or null.
        /// - `input_bias_terms` must be a valid pointer or null.
        /// - `input_scale_terms` must be a valid pointer or null.
        #[unsafe(method(initWithDevice:convolutionData:outputBiasTerms:outputScaleTerms:inputBiasTerms:inputScaleTerms:type:flags:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_convolutionData_outputBiasTerms_outputScaleTerms_inputBiasTerms_inputScaleTerms_type_flags(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            convolution_data: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
            output_bias_terms: *const c_float,
            output_scale_terms: *const c_float,
            input_bias_terms: *const c_float,
            input_scale_terms: *const c_float,
            r#type: MPSCNNBinaryConvolutionType,
            flags: MPSCNNBinaryConvolutionFlags,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNBinaryConvolution {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNBinaryConvolution {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSCNNBinaryFullyConnected specifies a fully connected convolution layer with binary weights
    /// and optionally binarized input image.
    /// See
    /// MPSCNNFullyConnectedfor details on the fully connected layer and
    /// MPSCNNBinaryConvolution for binary convolutions.
    ///
    /// The default padding policy for MPSCNNBinaryConvolution is different from most
    /// filters. It uses MPSNNPaddingMethodSizeValidOnly instead of MPSNNPaddingMethodSizeSame.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpscnnbinaryfullyconnected?language=objc)
    #[unsafe(super(MPSCNNBinaryConvolution, MPSCNNKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSCNNBinaryFullyConnected;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSCNNBinaryFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSCNNBinaryFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSCNNBinaryFullyConnected {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSCNNBinaryFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSCNNBinaryFullyConnected {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNBinaryFullyConnected {
    extern_methods!(
        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Initializes a binary fully connected kernel with binary weights and a single scaling term.
        ///
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNBinaryFullyConnected filter will be used
        ///
        /// Parameter `convolutionData`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol.
        /// The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNBinaryFullyConnected uses to obtain the weights and bias terms as
        /// well as the convolution descriptor.
        /// Each entry in the convolutionData:weights array is a 32-bit unsigned integer value
        /// and each bit represents one filter weight (given in machine byte order).
        /// The featurechannel indices increase from the least significant bit within the 32-bits.
        /// The number of entries is =
        /// ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth
        /// The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ]
        /// (The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on
        /// inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally
        /// outputChannels varies least rapidly.)
        ///
        /// Parameter `scaleValue`: A single floating point value used to scale the entire convolution.
        /// Each entry is a float value. The number of entries is 'inputFeatureChannels'. If nil then 1.0 is used.
        ///
        /// Parameter `type`: What kind of binarization strategy is to be used.
        ///
        /// Parameter `flags`: See documentation above and documentation of MPSCNNBinaryConvolutionFlags.
        ///
        ///
        /// Returns: A valid MPSCNNBinaryFullyConnected object or nil, if failure.
        #[unsafe(method(initWithDevice:convolutionData:scaleValue:type:flags:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_convolutionData_scaleValue_type_flags(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            convolution_data: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
            scale_value: c_float,
            r#type: MPSCNNBinaryConvolutionType,
            flags: MPSCNNBinaryConvolutionFlags,
        ) -> Retained<Self>;

        #[cfg(feature = "MPSNeuralNetworkTypes")]
        /// Initializes a binary fully connected kernel with binary weights as well as both pre and post scaling terms.
        ///
        ///
        /// Parameter `device`: The MTLDevice on which this MPSCNNBinaryFullyConnected filter will be used
        ///
        /// Parameter `convolutionData`: A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol.
        /// The MPSCNNConvolutionDataSource protocol declares the methods that an
        /// instance of MPSCNNBinaryFullyConnected uses to obtain the weights and the convolution descriptor.
        /// Each entry in the convolutionData:weights array is a 32-bit unsigned integer value
        /// and each bit represents one filter weight (given in machine byte order).
        /// The featurechannel indices increase from the least significant bit within the 32-bits.
        /// The number of entries is =
        /// ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth
        /// The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array)
        /// weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ]
        /// (The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on
        /// inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally
        /// outputChannels varies least rapidly.)
        ///
        ///
        /// Parameter `outputBiasTerms`: A pointer to bias terms to be applied to the convolution output.  Each entry is a float value.
        /// The number of entries is = numberOfOutputFeatureMaps. If nil then 0.0 is used for bias.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `outputScaleTerms`: A pointer to scale terms to be applied to binary convolution results per output feature channel.
        /// Each entry is a float value. The number of entries is = numberOfOutputFeatureMaps. If nil then 1.0 is used.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `inputBiasTerms`: A pointer to offset terms to be applied to the input before convolution and before input scaling.
        /// Each entry is a float value. The number of entries is 'inputFeatureChannels'. If NULL then 0.0 is used for bias.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `inputScaleTerms`: A pointer to scale terms to be applied to the input before convolution, but after input biasing.
        /// Each entry is a float value. The number of entries is 'inputFeatureChannels'. If nil then 1.0 is used.
        /// The values stored in the pointer are copied in and the array can be freed after this function returns.
        ///
        /// Parameter `type`: What kind of binarization strategy is to be used.
        ///
        /// Parameter `flags`: See documentation above and documentation of MPSCNNBinaryConvolutionFlags.
        ///
        ///
        /// Returns: A valid MPSCNNBinaryFullyConnected object or nil, if failure.
        ///
        /// # Safety
        ///
        /// - `output_bias_terms` must be a valid pointer or null.
        /// - `output_scale_terms` must be a valid pointer or null.
        /// - `input_bias_terms` must be a valid pointer or null.
        /// - `input_scale_terms` must be a valid pointer or null.
        #[unsafe(method(initWithDevice:convolutionData:outputBiasTerms:outputScaleTerms:inputBiasTerms:inputScaleTerms:type:flags:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_convolutionData_outputBiasTerms_outputScaleTerms_inputBiasTerms_inputScaleTerms_type_flags(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            convolution_data: &ProtocolObject<dyn MPSCNNConvolutionDataSource>,
            output_bias_terms: *const c_float,
            output_scale_terms: *const c_float,
            input_bias_terms: *const c_float,
            input_scale_terms: *const c_float,
            r#type: MPSCNNBinaryConvolutionType,
            flags: MPSCNNBinaryConvolutionFlags,
        ) -> Retained<Self>;

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNBinaryFullyConnected {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSCNNBinaryFullyConnected {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSNNGramMatrixCalculation filter specifies a layer which computes the uncentered cross-correlation
    /// values between the image planes of each feature channel of an image. If the input image batch is
    /// x = x[b, y, x, c], where 'b' is batch index, 'y' and 'x' are the image coordinate and
    /// 'c' is the feature channel index then this filter computes the values:
    ///
    /// y = y[b, 1, f, c] = alpha * sum_{x,y} x[b,y,x,f] * x[b,y,x,c], where
    ///
    /// 'alpha' is a scaling factor. This operation can be interpreted to be computing all combinations
    /// of fully connected layers between the different image planes of the input image. The results
    /// are stored in the feature channel and 'x'-coordinate indices of the output batch.
    /// The operation is performed independently on different images in the batch.
    ///
    /// NOTE: Due to the nature of the operation this filter specifies a special padding policy
    /// and hence does not support non-default offset or cliprect properties.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpsnngrammatrixcalculation?language=objc)
    #[unsafe(super(MPSCNNKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSNNGramMatrixCalculation;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSNNGramMatrixCalculation {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSNNGramMatrixCalculation {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSNNGramMatrixCalculation {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSNNGramMatrixCalculation {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSNNGramMatrixCalculation {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSNNGramMatrixCalculation {
    extern_methods!(
        /// Scaling factor for the output. Default: 1.0f.
        #[unsafe(method(alpha))]
        #[unsafe(method_family = none)]
        pub unsafe fn alpha(&self) -> c_float;

        /// Setter for [`alpha`][Self::alpha].
        #[unsafe(method(setAlpha:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setAlpha(&self, alpha: c_float);

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        /// Initializes a MPSNNGramMatrixCalculation kernel.
        ///
        ///
        /// Parameter `device`: The MTLDevice on which this MPSNNGramMatrixCalculation filter will be used.
        ///
        /// Parameter `alpha`: Scaling factor for the output.
        ///
        /// Returns: A valid MPSNNGramMatrixCalculation object or nil, if failure.
        #[unsafe(method(initWithDevice:alpha:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_alpha(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            alpha: c_float,
        ) -> Retained<Self>;

        /// Initializes a MPSNNGramMatrixCalculation kernel with scaling factor alpha = 1.0f.
        ///
        ///
        /// Parameter `device`: The MTLDevice on which this MPSNNGramMatrixCalculation filter will be used.
        ///
        /// Returns: A valid MPSNNGramMatrixCalculation object or nil, if failure.
        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSNNGramMatrixCalculation {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSNNGramMatrixCalculation {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}

extern_class!(
    /// Dependencies: This depends on Metal.framework
    ///
    /// The MPSNNGramMatrixCalculationGradient defines the gradient filter for MPSNNGramMatrixCalculation.
    ///
    /// See also [Apple's documentation](https://developer.apple.com/documentation/metalperformanceshaders/mpsnngrammatrixcalculationgradient?language=objc)
    #[unsafe(super(MPSCNNGradientKernel, MPSCNNBinaryKernel, MPSKernel, NSObject))]
    #[derive(Debug, PartialEq, Eq, Hash)]
    #[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
    pub struct MPSNNGramMatrixCalculationGradient;
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCoding for MPSNNGramMatrixCalculationGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSCopying for MPSNNGramMatrixCalculationGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
unsafe impl CopyingHelper for MPSNNGramMatrixCalculationGradient {
    type Result = Self;
}

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSObjectProtocol for MPSNNGramMatrixCalculationGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
extern_conformance!(
    unsafe impl NSSecureCoding for MPSNNGramMatrixCalculationGradient {}
);

#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSNNGramMatrixCalculationGradient {
    extern_methods!(
        /// Scaling factor for the output. Default: 1.0f. NOTE: the value for alpha is automatically adjusted by
        /// the
        /// MPSNNGradientStatewhen it is provided in the encode call.
        #[unsafe(method(alpha))]
        #[unsafe(method_family = none)]
        pub unsafe fn alpha(&self) -> c_float;

        /// Setter for [`alpha`][Self::alpha].
        #[unsafe(method(setAlpha:))]
        #[unsafe(method_family = none)]
        pub unsafe fn setAlpha(&self, alpha: c_float);

        /// NSSecureCoding compatability
        ///
        /// While the standard NSSecureCoding/NSCoding method
        /// -initWithCoder: should work, since the file can't
        /// know which device your data is allocated on, we
        /// have to guess and may guess incorrectly.  To avoid
        /// that problem, use initWithCoder:device instead.
        ///
        /// Parameter `aDecoder`: The NSCoder subclass with your serialized MPSKernel
        ///
        /// Parameter `device`: The MTLDevice on which to make the MPSKernel
        ///
        /// Returns: A new MPSKernel object, or nil if failure.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:device:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder_device(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Option<Retained<Self>>;

        /// Initializes a MPSNNGramMatrixCalculationGradient kernel.
        ///
        ///
        /// Parameter `device`: The MTLDevice on which this MPSNNGramMatrixCalculationGradient filter will be used.
        ///
        /// Parameter `alpha`: Scaling factor for the output. NOTE: the value for alpha is automatically adjusted by
        /// the
        /// MPSNNGradientStatewhen it is provided in the encode call.
        ///
        /// Returns: A valid MPSNNGramMatrixCalculationGradient object or nil, if failure.
        #[unsafe(method(initWithDevice:alpha:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice_alpha(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
            alpha: c_float,
        ) -> Retained<Self>;

        /// Initializes a MPSNNGramMatrixCalculationGradient kernel with scaling factor alpha = 1.0f.
        ///
        ///
        /// Parameter `device`: The MTLDevice on which this MPSNNGramMatrixCalculationGradient filter will be used.
        ///
        /// Returns: A valid MPSNNGramMatrixCalculationGradient object or nil, if failure.
        #[unsafe(method(initWithDevice:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithDevice(
            this: Allocated<Self>,
            device: &ProtocolObject<dyn MTLDevice>,
        ) -> Retained<Self>;
    );
}

/// Methods declared on superclass `MPSKernel`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSNNGramMatrixCalculationGradient {
    extern_methods!(
        /// Called by NSCoder to decode MPSKernels
        ///
        /// This isn't the right interface to decode a MPSKernel, but
        /// it is the one that NSCoder uses. To enable your NSCoder
        /// (e.g. NSKeyedUnarchiver) to set which device to use
        /// extend the object to adopt the MPSDeviceProvider
        /// protocol. Otherwise, the Metal system default device
        /// will be used.
        ///
        /// # Safety
        ///
        /// `a_decoder` possibly has further requirements.
        #[unsafe(method(initWithCoder:))]
        #[unsafe(method_family = init)]
        pub unsafe fn initWithCoder(
            this: Allocated<Self>,
            a_decoder: &NSCoder,
        ) -> Option<Retained<Self>>;
    );
}

/// Methods declared on superclass `NSObject`.
#[cfg(all(feature = "MPSCNNKernel", feature = "MPSCore", feature = "MPSKernel"))]
impl MPSNNGramMatrixCalculationGradient {
    extern_methods!(
        #[unsafe(method(init))]
        #[unsafe(method_family = init)]
        pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>;

        #[unsafe(method(new))]
        #[unsafe(method_family = new)]
        pub unsafe fn new() -> Retained<Self>;
    );
}