Trait collenchyma_nn::Convolution [−] [src]

pub trait Convolution<F>: NN<F> {
    fn new_convolution_config(
        &self, 
        src: &SharedTensor<F>, 
        dest: &SharedTensor<F>, 
        filter: &mut SharedTensor<F>, 
        algo_fwd: ConvForwardAlgo, 
        algo_bwd_filter: ConvBackwardFilterAlgo, 
        algo_bwd_data: ConvBackwardDataAlgo, 
        stride: &[i32], 
        zero_padding: &[i32]
    ) -> Result<Self::CC, Error>;
    fn convolution(
        &self, 
        filter: &mut SharedTensor<F>, 
        x: &mut SharedTensor<F>, 
        result: &mut SharedTensor<F>, 
        workspace: &mut SharedTensor<u8>, 
        config: &Self::CC
    ) -> Result<(), Error>;
    fn convolution_plain(
        &self, 
        filter: &SharedTensor<F>, 
        x: &SharedTensor<F>, 
        result: &mut SharedTensor<F>, 
        workspace: &mut SharedTensor<u8>, 
        config: &Self::CC
    ) -> Result<(), Error>;
    fn convolution_grad_filter(
        &self, 
        src_data: &mut SharedTensor<F>, 
        dest_diff: &mut SharedTensor<F>, 
        filter_diff: &mut SharedTensor<F>, 
        workspace: &mut SharedTensor<u8>, 
        config: &Self::CC
    ) -> Result<(), Error>;
    fn convolution_grad_filter_plain(
        &self, 
        src_data: &SharedTensor<F>, 
        dest_diff: &SharedTensor<F>, 
        filter_diff: &mut SharedTensor<F>, 
        workspace: &mut SharedTensor<u8>, 
        config: &Self::CC
    ) -> Result<(), Error>;
    fn convolution_grad_data(
        &self, 
        filter: &mut SharedTensor<F>, 
        x_diff: &mut SharedTensor<F>, 
        result_diff: &mut SharedTensor<F>, 
        workspace: &mut SharedTensor<u8>, 
        config: &Self::CC
    ) -> Result<(), Error>;
    fn convolution_grad_data_plain(
        &self, 
        filter: &SharedTensor<F>, 
        x_diff: &SharedTensor<F>, 
        result_diff: &mut SharedTensor<F>, 
        workspace: &mut SharedTensor<u8>, 
        config: &Self::CC
    ) -> Result<(), Error>;
}

Provides the functionality for a Backend to support Convolution operations.

Required Methods

Creates a new ConvolutionConfig, which needs to be passed to further convolution Operations.

Computes a CNN convolution over the input Tensor x with complete memory management.

Saves the result to result.

For a no-memory managed version see convolution_plain.

Computes the convolution over the input Tensor x without any memory management.

Saves the result to result.

Attention:
For a correct computation result, you need to manage the memory allocation and synchronization yourself.
For a memory managed version see convolution.

Computes the gradient of a CNN convolution with respect to the filter and complete memory management.

Saves the result to filter_diff.

For a no-memory managed version see convolution_grad_filter_plain.

Computes the gradient of a convolution with respect to the filter and without any memory management.

Saves the result to filter_diff.

Attention:
For a correct computation result, you need to manage the memory allocation and synchronization yourself.
For a memory managed version see convolution_grad_filter.

Computes the gradient of a CNN convolution over the input Tensor x with respect to the data and complete memory management.

Saves the result to result_diff.

For a no-memory managed version see convolution_grad_data_plain.

Computes the gradient of a convolution over the input Tensor x with respect to the data and without any memory management.

Saves the result to result_diff.

Attention:
For a correct computation result, you need to manage the memory allocation and synchronization yourself.
For a memory managed version see convolution_grad_data.

Implementors