Struct rcudnn::Cudnn

pub struct Cudnn { /* fields omitted */ }

Provides a the high-level interface to CUDA's cuDNN.

Methods

impl Cudnn

fn new() -> Result<Cudnn, Error>

Initializes a new CUDA cuDNN context.

Make sure your current CUDA device is cuDNN enabled.

fn from_c(id: cudnnHandle_t) -> Cudnn

Initializes a new CUDA cuDNN Context from its C type.

fn id_c(&self) -> &cudnnHandle_t

Returns the CUDA cuDNN Context as its C type.

fn version() -> usize

Returns the version of the CUDA cuDNN library.

fn init_convolution(
    &self,
    src_desc: &TensorDescriptor,
    conv_desc: ConvolutionDescriptor,
    filter_desc: FilterDescriptor,
    dest_desc: &TensorDescriptor
) -> Result<ConvolutionConfig, Error>

Initializes the parameters and configurations for running CUDA cuDNN convolution operations.

This includes finding the right convolution algorithm, workspace size and allocating that workspace.

fn init_normalization(
    &self,
    lrn_n: u32,
    lrn_alpha: f64,
    lrn_beta: f64,
    lrn_k: f64
) -> Result<NormalizationConfig, Error>

Initializes the parameters and configurations for running CUDA cuDNN LRN operations.

fn init_pooling(
    &self,
    window: &[i32],
    padding: &[i32],
    stride: &[i32]
) -> Result<PoolingConfig, Error>

Initializes the parameters and configurations for running CUDA cuDNN Pooling operations.

fn init_activation(&self) -> Result<ActivationConfig, Error>

Initializes the parameters and configurations for running CUDA cuDNN Activation operations.

fn init_dropout(
    &self,
    probability: f32,
    seed: u64
) -> Result<DropoutConfig, Error>

Initializes the parameters and configurations for running CUDA cuDNN dropout operation.

fn sigmoid_forward<T>(
    &self,
    activation_conf: &ActivationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward Sigmoid Activation function.

Writes the result of the computation to dest_data.

fn sigmoid_backward<T>(
    &self,
    activation_conf: &ActivationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward Sigmoid Activation function.

Writes the result of the computation to dest_diff_data.

fn relu_forward<T>(
    &self,
    activation_conf: &ActivationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward Rectified Linear Activation function.

Writes the result of the computation to dest_data.

fn relu_backward<T>(
    &self,
    activation_conf: &ActivationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward Rectified Linear Activation function.

Writes the result of the computation to dest_diff_data.

fn tanh_forward<T>(
    &self,
    activation_conf: &ActivationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward Hyperbolic Tangent Activation function.

Writes the result of the computation to dest_data.

fn tanh_backward<T>(
    &self,
    activation_conf: &ActivationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward Hyperbolic Tangent Activation function.

Writes the result of the computation to dest_diff_data.

fn convolution_forward<T>(
    &self,
    conv_config: &ConvolutionConfig,
    workspace: *mut c_void,
    filter_data: *const c_void,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward Convolution function.

Writes the result of the computation to dest_data.

fn convolution_backward_bias<T>(
    &self,
    dest_grad_desc: &TensorDescriptor,
    dest_grad_data: *const c_void,
    bias_grad_desc: &TensorDescriptor,
    bias_grad_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward Convolution function w.r.t the bias.

Writes the result of the computation to bias_grad_data.

fn convolution_backward_filter<T>(
    &self,
    conv_config: &ConvolutionConfig,
    workspace: *mut c_void,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_grad_desc: &TensorDescriptor,
    dest_grad_data: *const c_void,
    filter_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward Convolution function w.r.t the filter.

Writes the result of the computation to filter_data.

fn convolution_backward_data<T>(
    &self,
    conv_config: &ConvolutionConfig,
    workspace: *mut c_void,
    filter_data: *const c_void,
    dest_grad_desc: &TensorDescriptor,
    dest_grad_data: *const c_void,
    src_grad_desc: &TensorDescriptor,
    src_grad_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward Convolution function w.r.t the data.

Writes the result of the computation to src_grad_data.

fn softmax_forward<T>(
    &self,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward softmax function.

Writes the result of the computation to dest_data.

fn softmax_backward<T>(
    &self,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward softmax function.

Writes the result of the computation to dest_diff_data.

fn log_softmax_forward<T>(
    &self,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward logarithmic softmax function.

Writes the result of the computation to dest_data.

fn log_softmax_backward<T>(
    &self,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward logarithmic softmax function.

Writes the result of the computation to dest_diff_data.

fn lrn_forward<T>(
    &self,
    normalization_conf: &NormalizationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward local response normalization function.

Writes the result of the computation to dest_data.

fn lrn_backward<T>(
    &self,
    normalization_conf: &NormalizationConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward local response normalization function.

Writes the result of the computation to dest_diff_data.

fn pooling_avg_forward<T>(
    &self,
    pooling_conf: &PoolingConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward average pooling function.

Writes the result of the computation to dest_data.

fn pooling_avg_backward<T>(
    &self,
    pooling_conf: &PoolingConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward average pooling function.

Writes the result of the computation to dest_diff_data.

fn pooling_max_forward<T>(
    &self,
    pooling_conf: &PoolingConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the forward max pooling function.

Writes the result of the computation to dest_data.

fn pooling_max_backward<T>(
    &self,
    pooling_conf: &PoolingConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    src_diff_desc: &TensorDescriptor,
    src_diff_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *const c_void,
    dest_diff_desc: &TensorDescriptor,
    dest_diff_data: *mut c_void,
    scale: ScalParams<T>
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes the backward max pooling function.

Writes the result of the computation to dest_diff_data.

fn dropout_forward<T>(
    &self,
    dropout_conf: &DropoutConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes probability and applies it to Dropout

Writes the result of the computation to dest_data

fn dropout_backward<T>(
    &self,
    dropout_conf: &DropoutConfig,
    src_desc: &TensorDescriptor,
    src_data: *const c_void,
    dest_desc: &TensorDescriptor,
    dest_data: *mut c_void
) -> Result<(), Error> where
    T: Float + DataTypeInfo, 

Computes probability and applies it to Dropout

Writes the result of the computation to dest_data

Trait Implementations

impl Debug for Cudnn

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Clone for Cudnn

fn clone(&self) -> Cudnn

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Sync for Cudnn

impl Drop for Cudnn

fn drop(&mut self)

Executes the destructor for this type.