Rework OpenCL Depthwise Convolution
- Remove dedicated kernels for NCHW. Now we only use NHWC with permute
- Remove specialized kernels for 3x3 NHWC
- Simplify CLDepthwiseConvolutionLayer.cpp to call just the native
implementation for both floating-point and quantized data types
- Develop two parametric opencl kernels for depthwise convolution layer NHWC
(floating-point and quantized)
- Add support to export the weights to cl_image
- Extend test for depthwise convolution on opencl
Resolves COMPMID-4417
Change-Id: Ibe533f79c2860f9cac8e921895d5a8f947753a5c
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5893
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h
index bbb00a1..01ddae1 100644
--- a/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h
@@ -33,13 +33,14 @@
namespace arm_compute
{
class CLCompileContext;
-class CLFillBorderKernel;
class CLDepthwiseConvolutionLayerNativeKernel;
-class CLDepthwiseConvolutionLayer3x3NCHWKernel;
-class CLDepthwiseConvolutionLayer3x3NHWCKernel;
class ICLTensor;
/** Function to execute a depthwise convolution
+ *
+ * -# @ref CLDepthwiseConvolutionLayerNativeKernel
+ * -# @ref CLPermute (if the data layout is NCHW)
+ *
*/
class CLDepthwiseConvolutionLayer : public IFunction
{
@@ -102,239 +103,38 @@
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
- ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
+ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
+ unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
// Inherited methods overriden:
void run() override;
void prepare() override;
+ void set_memory_group(std::shared_ptr<IMemoryManager> memory_manager)
+ {
+ _memory_group = MemoryGroup(std::move(memory_manager));
+ };
+
private:
- /** Static function to choose the best depthwise convolution function for @ref CLDepthwiseConvolutionLayer
- *
- * @param[in] input Source tensor info. Data type supported: QASYMM8/FP16/FP32. Data layout supported: NHWC, NCHW
- * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
- * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input, S32 when input is QASYMM8.
- * @param[in] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- *
- * @return a Depthwise Convolution Function
- */
- static DepthwiseConvolutionFunction get_depthwiseconvolution_function(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
- ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
+ MemoryGroup _memory_group;
- /** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels:
- *
- * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW)
- * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC)
- * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0)
- *
- */
- class CLDepthwiseConvolutionLayerInternal3x3 : public IFunction
- {
- public:
- /** Default constructor */
- CLDepthwiseConvolutionLayerInternal3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLDepthwiseConvolutionLayerInternal3x3(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete;
- /** Default move constructor */
- CLDepthwiseConvolutionLayerInternal3x3(CLDepthwiseConvolutionLayerInternal3x3 &&) = default;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLDepthwiseConvolutionLayerInternal3x3 &operator=(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete;
- /** Default move assignment operator */
- CLDepthwiseConvolutionLayerInternal3x3 &operator=(CLDepthwiseConvolutionLayerInternal3x3 &&) = default;
- /** Initialize the function's source, destination, conv and border_size.
- *
- * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
- * @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM].
- * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input.
- * @param[out] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- */
- void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
- ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
- /** Initialize the function's source, destination, conv and border_size.
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
- * @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM].
- * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input.
- * @param[out] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- */
- void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
+ std::unique_ptr<CLDepthwiseConvolutionLayerNativeKernel> _dwc_native_kernel;
+ CLPermute _permute_input_to_nhwc;
+ CLPermute _permute_weights_to_nhwc;
+ CLPermute _permute_output_to_nchw;
- /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3
- *
- * @param[in] input Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW.
- * @param[in] weights Weights tensor info. A 3D tensor with shape [3, 3, IFM].
- * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input, S32 when input is QASYMM8.
- * @param[in] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
- ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
+ CLTensor _permuted_input;
+ CLTensor _permuted_weights;
+ CLTensor _permuted_output;
+ CLTensor _output_multipliers;
+ CLTensor _output_shifts;
+ const ITensor *_original_weights;
+ const ITensor *_input;
+ const ITensor *_output;
- // Inherited methods overriden:
- void run() override;
- void prepare() override;
-
- void set_memory_group(std::shared_ptr<IMemoryManager> memory_manager)
- {
- _memory_group = MemoryGroup(std::move(memory_manager));
- };
-
- private:
- MemoryGroup _memory_group;
- std::unique_ptr<CLDepthwiseConvolutionLayer3x3NCHWKernel> _kernel_nchw;
- std::unique_ptr<CLDepthwiseConvolutionLayer3x3NHWCKernel> _kernel_nhwc;
- std::unique_ptr<CLFillBorderKernel> _border_handler;
- CLPermute _permute_input_to_nchw;
- CLPermute _permute_weights_to_nchw;
- CLPermute _permute_output_to_nhwc;
- CLTensor _permuted_input;
- CLTensor _permuted_weights;
- CLTensor _permuted_output;
- CLTensor _output_multipliers;
- CLTensor _output_shifts;
- const ITensor *_original_weights;
- const ITensor *_input;
- const ITensor *_output;
- bool _needs_permute;
- bool _is_prepared;
- bool _is_quantized;
- bool _is_nhwc;
- };
-
- /** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels:
- *
- * -# @ref CLDepthwiseConvolutionLayerNativeKernel
- * -# @ref CLPermute (x 3) if the data layout is NCHW
- *
- */
- class CLDepthwiseConvolutionLayerGeneric : public IFunction
- {
- public:
- /** Default constructor */
- CLDepthwiseConvolutionLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLDepthwiseConvolutionLayerGeneric(const CLDepthwiseConvolutionLayerGeneric &) = delete;
- /** Default move constructor */
- CLDepthwiseConvolutionLayerGeneric(CLDepthwiseConvolutionLayerGeneric &&) = default;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CLDepthwiseConvolutionLayerGeneric &operator=(const CLDepthwiseConvolutionLayerGeneric &) = delete;
- /** Default move assignment operator */
- CLDepthwiseConvolutionLayerGeneric &operator=(CLDepthwiseConvolutionLayerGeneric &&) = default;
- /** Initialize the function's source, destination, weights and convolution information.
- *
- * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F32. (Written to only for border filling).
- * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
- * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
- * @param[out] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- */
- void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
- /** Initialize the function's source, destination, weights and convolution information.
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F32. (Written to only for border filling).
- * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
- * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
- * @param[out] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- */
- void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
-
- /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayerGeneric
- *
- * @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/F32.
- * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
- * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
- * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
- * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
- * @param[in] output Destination tensor. Data type supported: same as @p input.
- * @param[in] conv_info Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
-
- // Inherited methods overriden:
- void run() override;
- void prepare() override;
-
- void set_memory_group(std::shared_ptr<IMemoryManager> memory_manager)
- {
- _memory_group = MemoryGroup(std::move(memory_manager));
- };
-
- private:
- MemoryGroup _memory_group;
-
- std::unique_ptr<CLDepthwiseConvolutionLayerNativeKernel> _dwc_native_kernel;
- CLPermute _permute_input_to_nhwc;
- CLPermute _permute_weights_to_nhwc;
- CLPermute _permute_output_to_nchw;
-
- CLTensor _permuted_input;
- CLTensor _permuted_weights;
- CLTensor _permuted_output;
- CLTensor _output_multipliers;
- CLTensor _output_shifts;
- const ITensor *_original_weights;
- const ITensor *_input;
- const ITensor *_output;
-
- bool _needs_permute;
- bool _is_prepared;
- bool _is_quantized;
- };
-
- std::shared_ptr<IMemoryManager> _memory_manager;
-
- DepthwiseConvolutionFunction _depth_conv_func;
- CLDepthwiseConvolutionLayerInternal3x3 _func_3x3;
- CLDepthwiseConvolutionLayerGeneric _func_generic;
+ bool _needs_permute;
+ bool _is_prepared;
+ bool _is_quantized;
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H */