*/
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-
#ifndef __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__
#define __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__
-#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
-#include "arm_compute/runtime/CL/functions/CLTransposeConvLayerUpsample.h"
-
-#include "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h"
-
-#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLDirectTransposeConvLayer.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
namespace arm_compute
{
-class ICLTensor;
-/** Function to run the transpose convolution layer.
- *
- * @note This layer was copied in order to fix a bug computing to wrong output dimensions.
- *
- * TransposeConv Layer is the backward pass of Convolution Layer. First we transform the input
- * depending on the stride and pad info and then perform a 1x1
- * convolution pass. Input stride defines how many zeroes we should put between each element of the
- * input, pad is the amount of padding and finally a is a user
- * specified value where a < stride - 1, that increases the padding top and right of the input
- * image.
- *
- * The relation between input to output is as follows:
- * \f[
- * width\_output = (width\_input - 1) \cdot stride\_x - \cdot padding\_x + kernel\_x
- * \f]
- * \f[
- * height\_output = (height\_input - 1) \cdot stride\_y - \cdot padding\_y + kernel\_y
- * \f]
- *
- * where:
- * width_input is the size of the first input dimension.
- * height_input is the size of the second input dimension.
- * width_output is the size of the first output dimension.
- * height_output is the size of the second output dimension.
- * kernel_x and kernel_y are the convolution sizes in x and y.
- * stride_x and stride_y is the input stride of the first and second dimension.
- *
- * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution.
- * Therefore, it will be necessary to use the weights in the
- * reverse order to perform an actual convolution. This is achieved by using the @ref
- * CPPFlipWeightsKernel.
- *
- * This function calls the following OpenCL kernels/functions:
- *
- * -# @ref CLTransposeConvLayerUpsample
- * -# @ref CLConvolutionLayer
+/** Basic function to compute the deconvolution layer. This function calls the following OpenCL
+ * kernels/functions:
*
+ * -# @ref CLGEMMDeconvolutionLayer
+ * -# @ref CLDirectTransposeConvLayer
*/
class CLTransposeConvLayer : public IFunction
{
public:
- /** Constructor */
+ /** Default constructor */
CLTransposeConvLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLTransposeConvLayer(const CLTransposeConvLayer &) = delete;
- /** Default move constructor */
- CLTransposeConvLayer(CLTransposeConvLayer &&) = default;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLTransposeConvLayer &operator=(const CLTransposeConvLayer &) = delete;
- /** Default move assignment operator */
- CLTransposeConvLayer &operator=(CLTransposeConvLayer &&) = default;
+
/** Set the input, weights, biases and output tensors.
*
- * @param[in,out] input Input tensor. 3 lower dimensions represent a single input,
- * and an optional 4th dimension for batch of inputs.
- * Data types supported: QASYMM8/F16/F32.
- * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM].
- * Data type supported: Same as @p input.
- * @param[in] bias (Optional) The biases have one dimension. Data type supported:
- * Same as @p input.
- * @param[out] output Output tensor. The output has the same number of dimensions
- * as the @p input.
- * @param[in] info Contains padding and policies to be used in the
- * transpose convolution, this is decribed in @ref PadStrideInfo.
- * @param[in] invalid_right The number of zeros added to right edge of the output.
- * @param[in] invalid_bottom The number of zeros added to top edge of the output.
- * @param[in] weights_info (Optional) Weights information needed for @ref
- * CLConvolutionLayer, specifies if the weights tensor has been
- * reshaped with @ref CLWeightsReshapeKernel.
+ * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an
+ * optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
+ * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type
+ * supported: Same as @p input.
+ * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same
+ * as @p input.
+ * @param[out] output Output tensor. The output has the same number of dimensions as the
+ * @p input.
+ * @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this
+ * is described in @ref PadStrideInfo.
+ * @param[in] invalid_right The number of zeros added to right edge of the output.
+ * @param[in] invalid_bottom The number of zeros added to bottom edge of the output.
+ * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer,
+ * specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
+ *
*/
void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output,
- const PadStrideInfo &info, unsigned int invalid_right, unsigned int invalid_bottom,
+ const PadStrideInfo &deconv_info, unsigned int invalid_right,
+ unsigned int invalid_bottom, const WeightsInfo &weights_info = WeightsInfo());
+ /** Set the input, weights, biases and output tensors.
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and
+ * an optional 4th dimension for batch of inputs. Data types supported:
+ * QASYMM8_SIGNED/QASYMM8/F16/F32.
+ * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data
+ * type supported: Same as @p input.
+ * @param[in] bias (Optional) The biases have one dimension. Data type supported:
+ * Same as @p input.
+ * @param[out] output Output tensor. The output has the same number of dimensions as
+ * the @p input.
+ * @param[in] deconv_info Contains padding and policies to be used in the deconvolution,
+ * this is described in @ref PadStrideInfo.
+ * @param[in] invalid_right The number of zeros added to right edge of the output.
+ * @param[in] invalid_bottom The number of zeros added to bottom edge of the output.
+ * @param[in] weights_info (Optional) Weights information needed for @ref
+ * CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref
+ * CLWeightsReshapeKernel.
+ *
+ */
+ void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *weights,
+ const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &deconv_info,
+ unsigned int invalid_right, unsigned int invalid_bottom,
const WeightsInfo &weights_info = WeightsInfo());
/** Static function to check if given info will lead to a valid configuration of @ref
- * CLTransposeConvLayer
+ * CLTransposeConvLayer
+ *
+ * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an
+ * optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
+ * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data
+ * type supported: Same as @p input.
+ * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as
+ * @p input.
+ * @param[in] output Output tensor info. The output has the same number of dimensions as the
+ * @p input.
+ * @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is
+ * described in @ref PadStrideInfo.
+ * @param[in] invalid_right The number of zeros added to right edge of the output.
+ * @param[in] invalid_bottom The number of zeros added to bottom edge of the output.
+ * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer,
+ * specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
*
- * @param[in] input Input tensor info. 3 lower dimensions represent a single input,
- * and an optional 4th dimension for batch of inputs.
- * Data types supported: QASYMM8/F16/F32.
- * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM].
- * Data type supported: Same as @p input.
- * @param[in] bias (Optional) The biases have one dimension. Data type supported:
- * Same as @p input.
- * @param[in] output Output tensor info. The output has the same number of dimensions
- * as the @p input.
- * @param[in] info Contains padding and policies to be used in the
- * transpose convolution, this is decribed in @ref PadStrideInfo.
- * @param[in] innvalid_right The number of zeros added to right edge of the output.
- * @param[in] invalid_bottom The number of zeros added to top edge of the output.
- * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer,
- * specifies if the weights tensor has been reshaped with @ref
- * CLWeightsReshapeKernel.
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *weights,
- const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info,
- unsigned int innvalid_right, unsigned int invalid_bottom,
+ const ITensorInfo *bias, ITensorInfo *output,
+ const PadStrideInfo &deconv_info, unsigned int invalid_right,
+ unsigned int invalid_bottom,
const WeightsInfo &weights_info = WeightsInfo());
+ static DeconvolutionMethod
+ get_deconvolution_method(const ITensorInfo *input, const ITensorInfo *weights,
+ const ITensorInfo *bias, ITensorInfo *output,
+ const PadStrideInfo &deconv_info, unsigned int invalid_right,
+ unsigned int invalid_bottom, const WeightsInfo &weights_info);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
- MemoryGroup _memory_group;
- CLTransposeConvLayerUpsample _scale_f;
- CLConvolutionLayer _conv_f;
- CPPFlipWeightsKernel _flip_weights;
- CLTensor _scaled_output;
- ICLTensor *_original_weights;
- CLTensor _weights_flipped;
- bool _is_prepared;
+ std::shared_ptr<IMemoryManager> _memory_manager;
+ std::unique_ptr<IFunction> _function;
};
-}
+} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__ */
projects / platform / core / ml / nnfw.git / blobdiff