COMPMID-661: Convolution quantized (#32)
Change-Id: Id69df4ce98d1d89bdf9c9aa5c4d909659909b30f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110456
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
index cd1ea70..74c1244 100644
--- a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
@@ -36,6 +36,8 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLMemoryGroup.h"
#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include <memory>
@@ -55,7 +57,8 @@
CLConvolutionLayerReshapeWeights(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input and output tensors.
*
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QS8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
+ * Data type supported: QS8/QASYMM8/QS16/F16/F32.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
* @param[out] output Destination tensor. Data types supported: Same as @p weights.
* @param[in] transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise.
@@ -79,7 +82,8 @@
* -# @ref CLGEMMTranspose1xWKernel (executed only once for each configuration)
* -# @ref CLIm2ColKernel
* -# @ref CLGEMMInterleave4x4Kernel
- * -# @ref CLGEMMMatrixMultiplyKernel
+ * -# @ref CLGEMMMatrixMultiplyKernel or @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
+ * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale (if quantized asymmetric)
* -# @ref CLCol2ImKernel
*/
class CLConvolutionLayer : public IFunction
@@ -91,9 +95,10 @@
*
* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs.
- * Data types supported: QS8/QS16/F16/F32.
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as @p input.
+ * Data types supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+ * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
@@ -106,20 +111,37 @@
void run() override;
private:
- CLMemoryGroup _memory_group;
- CLConvolutionLayerReshapeWeights _reshape_weights;
- CLIm2ColKernel _input_im2col_kernel;
- CLGEMMInterleave4x4Kernel _input_interleave_kernel;
- CLGEMMMatrixMultiplyKernel _mm_kernel;
- CLCol2ImKernel _output_col2im_kernel;
- CLTensor _input_im2col_reshaped;
- CLTensor _input_interleaved_reshaped;
- CLTensor _weights_reshaped;
- CLTensor _weights_transposed;
- CLTensor _gemm_output;
- bool _has_bias;
- bool _is_fully_connected_convolution;
- bool _are_weights_reshaped;
+ /** Configures the appropriate matrix multiply routine
+ *
+ * @param input Input tensor. Data types supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param weights Weights tensor. Data type supported: Same as @p input.
+ * @param output Output tensor. Data types supported: Same as @p input,
+ * except for input of QASYMM8 type where output should be of S32 type.
+ * @param is_interleaved_transposed Flag that signals if matrix is interleaved transposed
+ */
+ void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, bool is_interleaved_transposed = true);
+
+private:
+ CLMemoryGroup _memory_group;
+ CLConvolutionLayerReshapeWeights _reshape_weights;
+ CLIm2ColKernel _input_im2col_kernel;
+ CLGEMMInterleave4x4Kernel _input_interleave_kernel;
+ CLGEMMMatrixMultiplyKernel _mm_kernel;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
+ CLCol2ImKernel _output_col2im_kernel;
+
+ CLTensor _input_im2col_reshaped;
+ CLTensor _input_interleaved_reshaped;
+ CLTensor _weights_reshaped;
+ CLTensor _weights_transposed;
+ CLTensor _gemm_output;
+ CLTensor _tmp_output;
+
+ bool _append_bias;
+ bool _is_fully_connected_convolution;
+ bool _are_weights_reshaped;
+ bool _is_quantized;
};
}
#endif /* __ARM_COMPUTE_CLCONVOLUTIONLAYER_H__ */