Struct MLCTensor

#[repr(C)]
pub struct MLCTensor { /* private fields */ }

👎Deprecated

Available on crate feature MLCTensor only.

A tensor object

See also Apple’s documentation

Implementations

impl MLCTensor

pub unsafe fn tensorID(&self) -> NSUInteger

👎Deprecated

The tensor ID

A unique number to identify each tensor. Assigned when the tensor is created.

pub unsafe fn descriptor(&self) -> Retained<MLCTensorDescriptor>

👎Deprecated

Available on crate feature MLCTensorDescriptor only.

The tensor descriptor

pub unsafe fn data(&self) -> Option<Retained<NSData>>

👎Deprecated

The tensor data

pub unsafe fn label(&self) -> Retained<NSString>

👎Deprecated

A string to help identify this object.

pub unsafe fn setLabel(&self, label: &NSString)

👎Deprecated

Setter for label.

pub unsafe fn device(&self) -> Option<Retained<MLCDevice>>

👎Deprecated

Available on crate feature MLCDevice only.

The device associated with this tensor.

pub unsafe fn optimizerData(&self) -> Retained<NSArray<MLCTensorData>>

👎Deprecated

Available on crate feature MLCTensorData only.

These are the host side optimizer (momentum and velocity) buffers which developers can query and initialize

When customizing optimizer data, the contents of these buffers must be initialized before executing optimizer update for a graph.

pub unsafe fn optimizerDeviceData( &self, ) -> Retained<NSArray<MLCTensorOptimizerDeviceData>>

👎Deprecated

Available on crate feature MLCTensorOptimizerDeviceData only.

These are the device side optimizer (momentum and velocity) buffers which developers can query

pub unsafe fn new() -> Retained<Self>

👎Deprecated

pub unsafe fn init(this: Allocated<Self>) -> Retained<Self>

👎Deprecated

pub unsafe fn tensorWithDescriptor( tensor_descriptor: &MLCTensorDescriptor, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTensorDescriptor only.

Create a MLCTensor object

Create a tensor object without any data

Returns: A new MLCTensor object

pub unsafe fn tensorWithDescriptor_randomInitializerType( tensor_descriptor: &MLCTensorDescriptor, random_initializer_type: MLCRandomInitializerType, ) -> Retained<Self>

👎Deprecated

Available on crate features MLCTensorDescriptor and MLCTypes only.

Create a MLCTensor object

Create a tensor object initialized with a random initializer such as Glorot Uniform.

Parameter tensorDescriptor: The tensor descriptor

Parameter randomInitializerType: The random initializer type

Returns: A new MLCTensor object

pub unsafe fn tensorWithDescriptor_fillWithData( tensor_descriptor: &MLCTensorDescriptor, fill_data: &NSNumber, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTensorDescriptor only.

Create a MLCTensor object

Create a tensor object with a MLCTensorData object that specifies the tensor data buffer

Parameter tensorDescriptor: The tensor descriptor

Parameter fillData: The scalar data to fill to tensor with

Returns: A new MLCTensor object

pub unsafe fn tensorWithDescriptor_data( tensor_descriptor: &MLCTensorDescriptor, data: &MLCTensorData, ) -> Retained<Self>

👎Deprecated

Available on crate features MLCTensorData and MLCTensorDescriptor only.

Create a MLCTensor object

Create a tensor object with a MLCTensorData object that specifies the tensor data buffer

Parameter tensorDescriptor: The tensor descriptor

Parameter data: The random initializer type

Returns: A new MLCTensor object

pub unsafe fn tensorWithShape(shape: &NSArray<NSNumber>) -> Retained<Self>

👎Deprecated

Create a MLCTensor object

Create a tensor object without any data. The tensor data type is MLCDataTypeFloat32.

Parameter shape: The tensor shape

Returns: A new MLCTensor object

pub unsafe fn tensorWithShape_randomInitializerType( shape: &NSArray<NSNumber>, random_initializer_type: MLCRandomInitializerType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a tensor object initialized with a random initializer such as Glorot Uniform. The tensor data type is MLCDataTypeFloat32

Parameter shape: The tensor shape

Parameter randomInitializerType: The random initializer type

Returns: A new MLCTensor object

pub unsafe fn tensorWithShape_randomInitializerType_dataType( shape: &NSArray<NSNumber>, random_initializer_type: MLCRandomInitializerType, data_type: MLCDataType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a tensor object initialized with a random initializer such as Glorot Uniform. The tensor data type is MLCDataTypeFloat32

Parameter shape: The tensor shape

Parameter randomInitializerType: The random initializer type

Parameter dataType: The tensor data type

Returns: A new MLCTensor object

pub unsafe fn tensorWithShape_dataType( shape: &NSArray<NSNumber>, data_type: MLCDataType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a tensor object without any data

Parameter shape: The tensor shape

Parameter dataType: The tensor data type

Returns: A new MLCTensor object

pub unsafe fn tensorWithShape_data_dataType( shape: &NSArray<NSNumber>, data: &MLCTensorData, data_type: MLCDataType, ) -> Retained<Self>

👎Deprecated

Available on crate features MLCTensorData and MLCTypes only.

Create a MLCTensor object

Create a tensor object with data

Parameter shape: The tensor shape

Parameter data: The tensor data

Parameter dataType: The tensor data type

Returns: A new MLCTensor object

pub unsafe fn tensorWithShape_fillWithData_dataType( shape: &NSArray<NSNumber>, fill_data: &NSNumber, data_type: MLCDataType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a tensor object with data

Parameter shape: The tensor shape

Parameter fillData: The scalar value to initialize the tensor data with

Parameter dataType: The tensor data type

Returns: A new MLCTensor object

pub unsafe fn tensorWithWidth_height_featureChannelCount_batchSize( width: NSUInteger, height: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, ) -> Retained<Self>

👎Deprecated

Create a MLCTensor object

Create a NCHW tensor object with tensor data type = MLCDataTypeFloat32

Parameter width: The tensor width

Parameter height: The tensor height

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Returns: A new MLCTensor object

pub unsafe fn tensorWithWidth_height_featureChannelCount_batchSize_fillWithData_dataType( width: NSUInteger, height: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, fill_data: c_float, data_type: MLCDataType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a NCHW tensor object initialized with a scalar value

Parameter width: The tensor width

Parameter height: The tensor height

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter fillData: The scalar value to initialize the tensor data with

Parameter dataType: The tensor data type

Returns: A new MLCTensorData object

pub unsafe fn tensorWithWidth_height_featureChannelCount_batchSize_randomInitializerType( width: NSUInteger, height: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, random_initializer_type: MLCRandomInitializerType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a NCHW tensor object initialized with a random initializer type. The tensor data type is MLCDataTypeFloat32

Parameter width: The tensor width

Parameter height: The tensor height

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter randomInitializerType: The random initializer type

Returns: A new MLCTensor object

pub unsafe fn tensorWithWidth_height_featureChannelCount_batchSize_data( width: NSUInteger, height: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, data: &MLCTensorData, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTensorData only.

Create a MLCTensor object

Create a NCHW tensor object with a tensor data object The tensor data type is MLCDataTypeFloat32.

Parameter width: The tensor width

Parameter height: The tensor height

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter data: The tensor data

Returns: A new MLCTensor object

pub unsafe fn tensorWithWidth_height_featureChannelCount_batchSize_data_dataType( width: NSUInteger, height: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, data: &MLCTensorData, data_type: MLCDataType, ) -> Retained<Self>

👎Deprecated

Available on crate features MLCTensorData and MLCTypes only.

Create a MLCTensor object

Create a NCHW tensor object with a tensor data object The tensor data type is MLCDataTypeFloat32.

Parameter width: The tensor width

Parameter height: The tensor height

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter data: The tensor data

Parameter dataType: The tensor data type

Returns: A new MLCTensor object

pub unsafe fn tensorWithSequenceLength_featureChannelCount_batchSize( sequence_length: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, ) -> Retained<Self>

👎Deprecated

Create a MLCTensor object

Create a tensor typically used by a recurrent layer The tensor data type is MLCDataTypeFloat32.

Parameter sequenceLength: The length of sequences stored in the tensor

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Returns: A new MLCTensor object

pub unsafe fn tensorWithSequenceLength_featureChannelCount_batchSize_randomInitializerType( sequence_length: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, random_initializer_type: MLCRandomInitializerType, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a tensor typically used by a recurrent layer The tensor data type is MLCDataTypeFloat32.

Parameter sequenceLength: The length of sequences stored in the tensor

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter randomInitializerType: The random initializer type

Returns: A new MLCTensor object

pub unsafe fn tensorWithSequenceLength_featureChannelCount_batchSize_data( sequence_length: NSUInteger, feature_channel_count: NSUInteger, batch_size: NSUInteger, data: Option<&MLCTensorData>, ) -> Retained<Self>

👎Deprecated

Available on crate feature MLCTensorData only.

Create a MLCTensor object

Create a tensor typically used by a recurrent layer The tensor data type is MLCDataTypeFloat32.

Parameter sequenceLength: The length of sequences stored in the tensor

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter data: The tensor data

Returns: A new MLCTensor object

pub unsafe fn tensorWithSequenceLengths_sortedSequences_featureChannelCount_batchSize_randomInitializerType( sequence_lengths: &NSArray<NSNumber>, sorted_sequences: bool, feature_channel_count: NSUInteger, batch_size: NSUInteger, random_initializer_type: MLCRandomInitializerType, ) -> Option<Retained<Self>>

👎Deprecated

Available on crate feature MLCTypes only.

Create a MLCTensor object

Create a tensor of variable length sequences typically used by a recurrent layer The tensor data type is MLCDataTypeFloat32.

Parameter sequenceLengths: An array of sequence lengths

Parameter sortedSequences: A flag to indicate if the sequence lengths are sorted. If yes, they must be sorted in descending order

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter randomInitializerType: The random initializer type

Returns: A new MLCTensor object

pub unsafe fn tensorWithSequenceLengths_sortedSequences_featureChannelCount_batchSize_data( sequence_lengths: &NSArray<NSNumber>, sorted_sequences: bool, feature_channel_count: NSUInteger, batch_size: NSUInteger, data: Option<&MLCTensorData>, ) -> Option<Retained<Self>>

👎Deprecated

Available on crate feature MLCTensorData only.

Create a MLCTensor object

Create a tensor of variable length sequences typically used by a recurrent layer The tensor data type is MLCDataTypeFloat32.

Parameter sequenceLengths: An array of sequence lengths

Parameter sortedSequences: A flag to indicate if the sequence lengths are sorted. If yes, they must be sorted in descending order

Parameter featureChannelCount: Number of feature channels

Parameter batchSize: The tensor batch size

Parameter data: The tensor data

Returns: A new MLCTensor object

pub unsafe fn hasValidNumerics(&self) -> bool

👎Deprecated

Returns a Boolean value indicating whether the underlying data has valid floating-point numerics, i.e. it does not contain NaN or INF floating-point values.

pub unsafe fn synchronizeData(&self) -> bool

👎Deprecated

Synchronize the data in host memory.

Synchronize the data in host memory i.e. tensor.data with latest contents in device memory This should only be called once the graph that this tensor is used with has finished execution; Otherwise the results in device memory may not be up to date. NOTE: This method should not be called from a completion callback when device is the GPU.

Returns: Returns YES if success, NO if there is a failure to synchronize

pub unsafe fn synchronizeOptimizerData(&self) -> bool

👎Deprecated

Synchronize the optimizer data in host memory.

Synchronize the optimizer data in host memory with latest contents in device memory This should only be called once the graph that this tensor is used with has finished execution; Otherwise the results in device memory may not be up to date. NOTE: This method should not be called from a completion callback when device is the GPU.

Returns: Returns YES if success, NO if there is a failure to synchronize

pub unsafe fn copyDataFromDeviceMemoryToBytes_length_synchronizeWithDevice( &self, bytes: NonNull<c_void>, length: NSUInteger, synchronize_with_device: bool, ) -> bool

👎Deprecated

Copy tensor data from device memory to user specified memory

Before copying tensor data from device memory, one may need to synchronize the device memory for example when device is the GPU. The synchronizeWithDevice argumet can be set appropraitely to indicate this. For CPU this is ignored. If the tensor has been specified in outputs of a graph using addOutputs, synchronizeWithDevice should be set to NO. NOTE: This method should only be called once the graph that this tensor is used with has finished execution; Otherwise the results in device memory may not be up to date. synchronizeWithDevice must be set to NO when this method is called from a completion callback for GPU.

Parameter bytes: The user specified data in which to copy

Parameter length: The size in bytes to copy

Parameter synchronizeWithDevice: Whether to synchronize device memory if device is GPU

Returns: Returns YES if success, NO if there is a failure to synchronize

pub unsafe fn bindAndWriteData_toDevice( &self, data: &MLCTensorData, device: &MLCDevice, ) -> bool

👎Deprecated

Available on crate features MLCDevice and MLCTensorData only.

Associates the given data to the tensor. If the device is GPU, also copies the data to the device memory. Returns true if the data is successfully associated with the tensor and copied to the device.

The caller must guarantee the lifetime of the underlying memory of datafor the entirety of the tensor’s lifetime. For input tensors, we recommend that the bindAndwriteData method provided by MLCTrainingGraph and MLCInferenceGraph be used. This method should only be used to allocate and copy data to device memory for tensors that are typically layer parameters such as weights, bias for convolution layers, beta, gamma for normalization layers.

Parameter data: The data to associated with the tensor

Parameter device: The compute device

Returns: A Boolean value indicating whether the data is successfully associated with the tensor and copied to the device.

pub unsafe fn bindOptimizerData_deviceData( &self, data: &NSArray<MLCTensorData>, device_data: Option<&NSArray<MLCTensorOptimizerDeviceData>>, ) -> bool

👎Deprecated

Available on crate features MLCTensorData and MLCTensorOptimizerDeviceData only.

Associates the given optimizer data and device data buffers to the tensor. Returns true if the data is successfully associated with the tensor and copied to the device.

The caller must guarantee the lifetime of the underlying memory of datafor the entirety of the tensor’s lifetime. The deviceDatabuffers are allocated by MLCompute. This method must be called before executeOptimizerUpdateWithOptions or executeWithInputsData is called for the training graph.

Parameter data: The optimizer data to be associated with the tensor

Parameter deviceData: The optimizer device data to be associated with the tensor

Returns: A Boolean value indicating whether the data is successfully associated with the tensor .

pub unsafe fn tensorByQuantizingToType_scale_bias( &self, type: MLCDataType, scale: c_float, bias: NSInteger, ) -> Option<Retained<MLCTensor>>

Available on crate feature MLCTypes only.

Converts a 32-bit floating-point tensor with given scale and a zero point Returns a quantized tensor

Parameter type: The quantized data type. Must be MLCDataTypeInt8, MLCDataTypeUInt8 or MLCDataTypeInt32

Parameter scale: The scale to apply in quantization

Parameter bias: The offset value that maps to float zero

Returns: A quantized tensor

pub unsafe fn tensorByQuantizingToType_scale_bias_axis( &self, type: MLCDataType, scale: &MLCTensor, bias: &MLCTensor, axis: NSInteger, ) -> Option<Retained<MLCTensor>>

Available on crate feature MLCTypes only.

Converts a 32-bit floating-point tensor with given scale and a zero point Returns a quantized tensor

Parameter type: The quantized data type. Must be MLCDataTypeInt8, MLCDataTypeUInt8 or MLCDataTypeInt32

Parameter scale: The scale to apply in quantization

Parameter bias: The offset value that maps to float zero

Parameter axis: The dimension on which to apply per-channel quantization

Returns: A quantized tensor

pub unsafe fn tensorByDequantizingToType_scale_bias_axis( &self, type: MLCDataType, scale: &MLCTensor, bias: &MLCTensor, axis: NSInteger, ) -> Option<Retained<MLCTensor>>

Available on crate feature MLCTypes only.

Converts a quantized tensor to a 32-bit floating-point tensor Returns a de-quantized tensor

Parameter type: The de-quantized data type. Must be MLCFloat32

Parameter scale: The scale thst was used for the quantized data

Parameter bias: The offset value that maps to float zero used for the quantized data

Parameter axis: The dimension on which to apply per-channel quantization

Returns: A quantized tensor

Methods from Deref<Target = NSObject>

pub fn doesNotRecognizeSelector(&self, sel: Sel) -> !

Handle messages the object doesn’t recognize.

See Apple’s documentation for details.

Methods from Deref<Target = AnyObject>

pub fn class(&self) -> &'static AnyClass

Dynamically find the class of this object.

Panics

May panic if the object is invalid (which may be the case for objects returned from unavailable init/new methods).

Example

Check that an instance of NSObject has the precise class NSObject.

use objc2::ClassType;
use objc2::runtime::NSObject;

let obj = NSObject::new();
assert_eq!(obj.class(), NSObject::class());

pub unsafe fn get_ivar<T>(&self, name: &str) -> &T

where T: Encode,

👎Deprecated: this is difficult to use correctly, use Ivar::load instead.

Use Ivar::load instead.

Safety

The object must have an instance variable with the given name, and it must be of type T.

See Ivar::load_ptr for details surrounding this.

pub fn downcast_ref<T>(&self) -> Option<&T>

where T: DowncastTarget,

Attempt to downcast the object to a class of type T.

This is the reference-variant. Use Retained::downcast if you want to convert a retained object to another type.

Mutable classes

Some classes have immutable and mutable variants, such as NSString and NSMutableString.

When some Objective-C API signature says it gives you an immutable class, it generally expects you to not mutate that, even though it may technically be mutable “under the hood”.

So using this method to convert a NSString to a NSMutableString, while not unsound, is generally frowned upon unless you created the string yourself, or the API explicitly documents the string to be mutable.

See Apple’s documentation on mutability and on isKindOfClass: for more details.

Generic classes

Objective-C generics are called “lightweight generics”, and that’s because they aren’t exposed in the runtime. This makes it impossible to safely downcast to generic collections, so this is disallowed by this method.

You can, however, safely downcast to generic collections where all the type-parameters are AnyObject.

Panics

This works internally by calling isKindOfClass:. That means that the object must have the instance method of that name, and an exception will be thrown (if CoreFoundation is linked) or the process will abort if that is not the case. In the vast majority of cases, you don’t need to worry about this, since both root objects NSObject and NSProxy implement this method.

Examples

Cast an NSString back and forth from NSObject.

use objc2::rc::Retained;
use objc2_foundation::{NSObject, NSString};

let obj: Retained<NSObject> = NSString::new().into_super();
let string = obj.downcast_ref::<NSString>().unwrap();
// Or with `downcast`, if we do not need the object afterwards
let string = obj.downcast::<NSString>().unwrap();

Try (and fail) to cast an NSObject to an NSString.

use objc2_foundation::{NSObject, NSString};

let obj = NSObject::new();
assert!(obj.downcast_ref::<NSString>().is_none());

Try to cast to an array of strings.

use objc2_foundation::{NSArray, NSObject, NSString};

let arr = NSArray::from_retained_slice(&[NSObject::new()]);
// This is invalid and doesn't type check.
let arr = arr.downcast_ref::<NSArray<NSString>>();

This fails to compile, since it would require enumerating over the array to ensure that each element is of the desired type, which is a performance pitfall.

Downcast when processing each element instead.

use objc2_foundation::{NSArray, NSObject, NSString};

let arr = NSArray::from_retained_slice(&[NSObject::new()]);

for elem in arr {
    if let Some(data) = elem.downcast_ref::<NSString>() {
        // handle `data`
    }
}

Trait Implementations

impl AsRef<AnyObject> for MLCTensor

fn as_ref(&self) -> &AnyObject

Converts this type into a shared reference of the (usually inferred) input type.

impl AsRef<MLCTensor> for MLCTensor

fn as_ref(&self) -> &Self

Converts this type into a shared reference of the (usually inferred) input type.

impl AsRef<NSObject> for MLCTensor

fn as_ref(&self) -> &NSObject

Converts this type into a shared reference of the (usually inferred) input type.

impl Borrow<AnyObject> for MLCTensor

fn borrow(&self) -> &AnyObject

Immutably borrows from an owned value.

impl Borrow<NSObject> for MLCTensor

fn borrow(&self) -> &NSObject

Immutably borrows from an owned value.

impl ClassType for MLCTensor

const NAME: &'static str = "MLCTensor"

The name of the Objective-C class that this type represents.

type Super = NSObject

The superclass of this class.

type ThreadKind = <<MLCTensor as ClassType>::Super as ClassType>::ThreadKind

Whether the type can be used from any thread, or from only the main thread.

fn class() -> &'static AnyClass

Get a reference to the Objective-C class that this type represents.

fn as_super(&self) -> &Self::Super

Get an immutable reference to the superclass.

impl CopyingHelper for MLCTensor

type Result = MLCTensor

The immutable counterpart of the type, or Self if the type has no immutable counterpart.

impl Debug for MLCTensor

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Deref for MLCTensor

type Target = NSObject

The resulting type after dereferencing.

fn deref(&self) -> &Self::Target

Dereferences the value.

impl Hash for MLCTensor

fn hash<H: Hasher>(&self, state: &mut H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl Message for MLCTensor

fn retain(&self) -> Retained<Self>

where Self: Sized,

Increment the reference count of the receiver.

impl NSCopying for MLCTensor

fn copy(&self) -> Retained<Self::Result>

where Self: Sized + Message + CopyingHelper,

Returns a new instance that’s a copy of the receiver.

unsafe fn copyWithZone(&self, zone: *mut NSZone) -> Retained<Self::Result>

where Self: Sized + Message + CopyingHelper,

Returns a new instance that’s a copy of the receiver.

impl NSObjectProtocol for MLCTensor

fn isEqual(&self, other: Option<&AnyObject>) -> bool

where Self: Sized + Message,

Check whether the object is equal to an arbitrary other object.

fn hash(&self) -> usize

where Self: Sized + Message,

An integer that can be used as a table address in a hash table structure.

fn isKindOfClass(&self, cls: &AnyClass) -> bool

where Self: Sized + Message,

Check if the object is an instance of the class, or one of its subclasses.

fn is_kind_of<T>(&self) -> bool

where T: ClassType, Self: Sized + Message,

👎Deprecated: use isKindOfClass directly, or cast your objects with AnyObject::downcast_ref

Check if the object is an instance of the class type, or one of its subclasses.

fn isMemberOfClass(&self, cls: &AnyClass) -> bool

where Self: Sized + Message,

Check if the object is an instance of a specific class, without checking subclasses.

fn respondsToSelector(&self, aSelector: Sel) -> bool

where Self: Sized + Message,

Check whether the object implements or inherits a method with the given selector.

fn conformsToProtocol(&self, aProtocol: &AnyProtocol) -> bool

where Self: Sized + Message,

Check whether the object conforms to a given protocol.

fn description(&self) -> Retained<NSObject>

where Self: Sized + Message,

A textual representation of the object.

fn debugDescription(&self) -> Retained<NSObject>

where Self: Sized + Message,

A textual representation of the object to use when debugging.

fn isProxy(&self) -> bool

where Self: Sized + Message,

Check whether the receiver is a subclass of the NSProxy root class instead of the usual NSObject.

fn retainCount(&self) -> usize

where Self: Sized + Message,

The reference count of the object.

impl PartialEq for MLCTensor

fn eq(&self, other: &Self) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl RefEncode for MLCTensor

const ENCODING_REF: Encoding = <NSObject as ::objc2::RefEncode>::ENCODING_REF

The Objective-C type-encoding for a reference of this type.

impl DowncastTarget for MLCTensor

impl Eq for MLCTensor