COMPMID-1979: Fuse Activation Function in CLGEMM - part 4
Fused activation function in CLGEMM
Change-Id: I644fdf09349325c0b3a2cd5fef2a3ea2c974149d
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1640
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index b4d94ec..2c17f27 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -1775,7 +1775,8 @@
_gemmlowp_output_stage(),
_fp_mixed_precision(false),
_broadcast_bias(false),
- _pretranpose_B(true)
+ _pretranpose_B(true),
+ _activation_info()
{
}
/** Constructor
@@ -1791,9 +1792,11 @@
* @param[in] gemmlowp_output_stage (Optional) GEMMLowp Output stage info
* @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy.
* @param[in] broadcast_bias (Optional) Broadcast the shape of the bias tensor from a vector to a matrix.
+ * @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
*/
GEMMInfo(bool is_a_reshaped, bool is_b_reshaped, bool reshape_b_only_on_first_run, int depth_output_gemm3d = 0, bool reinterpret_input_as_3d = false, bool retain_internal_weights = false,
- GEMMLowpOutputStageInfo gemmlowp_output_stage = GEMMLowpOutputStageInfo(), bool fp_mixed_precision = false, bool broadcast_bias = false) noexcept
+ GEMMLowpOutputStageInfo gemmlowp_output_stage = GEMMLowpOutputStageInfo(), bool fp_mixed_precision = false, bool broadcast_bias = false,
+ const ActivationLayerInfo &activation_info = ActivationLayerInfo()) noexcept
: _is_a_reshaped(is_a_reshaped),
_is_b_reshaped(is_b_reshaped),
_reshape_b_only_on_first_run(reshape_b_only_on_first_run),
@@ -1803,7 +1806,8 @@
_gemmlowp_output_stage(gemmlowp_output_stage),
_fp_mixed_precision(fp_mixed_precision),
_broadcast_bias(broadcast_bias),
- _pretranpose_B(reshape_b_only_on_first_run)
+ _pretranpose_B(reshape_b_only_on_first_run),
+ _activation_info(activation_info)
{
}
/** Flag which specifies if the matrix A has been reshaped
@@ -1896,6 +1900,14 @@
{
_pretranpose_B = flag;
}
+ /** Activation layer to apply after the matrix multiplication
+ *
+ * @return ActivationLayerInfo object
+ */
+ ActivationLayerInfo activation_info() const
+ {
+ return _activation_info;
+ }
private:
bool _is_a_reshaped;
@@ -1908,6 +1920,7 @@
bool _fp_mixed_precision;
bool _broadcast_bias;
bool _pretranpose_B;
+ ActivationLayerInfo _activation_info;
};
/** Winograd information */
diff --git a/arm_compute/runtime/CL/functions/CLGEMM.h b/arm_compute/runtime/CL/functions/CLGEMM.h
index 8c462fa..e2a92a8 100644
--- a/arm_compute/runtime/CL/functions/CLGEMM.h
+++ b/arm_compute/runtime/CL/functions/CLGEMM.h
@@ -127,7 +127,6 @@
CLMemoryGroup _memory_group;
CLGEMMMatrixMultiplyKernel _mm_kernel;
- CLGEMMMatrixAdditionKernel _ma_kernel;
CLGEMMReshapeLHSMatrixKernel _reshape_lhs_kernel;
CLGEMMReshapeRHSMatrixKernel _reshape_rhs_kernel;
CLGEMMMatrixMultiplyReshapedKernel _mm_reshaped_kernel;
@@ -135,7 +134,6 @@
CLTensor _tmp_a;
CLTensor _tmp_b;
const ICLTensor *_original_b;
- bool _run_addition;
bool _reshape_b_only_on_first_run;
bool _is_prepared;
GEMMType _gemm_type;
diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
index e9a3f9b..027727c 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
@@ -163,8 +163,10 @@
* except for input of QASYMM8 type where output should be of S32 type.
* @param[in] gemmlowp_output_stage GEMMLowp output stage info
* @param[in] gemm_3d_depth Depth of GEMM 3D
+ * @param[in] act_info Activation to apply after the matrix multiplication
*/
- void configure_mm(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, int gemm_3d_depth = 1);
+ void configure_mm(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, int gemm_3d_depth,
+ const ActivationLayerInfo &act_info);
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines
*
* @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32.
@@ -176,22 +178,21 @@
* @param[in] gemmlowp_output_stage GEMMLowp output stage info
* @param[in] gemm_3d_depth Depth of GEMM 3D
* @param[in] skip_im2col Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout.
- * @param[in] run_addition Flag which specifies if @ref CLGEMMMatrixMatrixMultiplyAddition to be run.
+ * @param[in] act_info Activation to apply after the matrix multiplication
*
* @return a status
*/
static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage,
- int gemm_3d_depth, bool skip_im2col, bool run_addition);
+ int gemm_3d_depth, bool skip_im2col, const ActivationLayerInfo &act_info);
private:
- CLMemoryGroup _memory_group;
- CLConvolutionLayerReshapeWeights _reshape_weights;
- CLIm2ColKernel _im2col_kernel;
- CLGEMM _mm_gemm;
- CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- CLCol2ImKernel _col2im_kernel;
- CLActivationLayer _activationlayer_function;
- CLSaturatedArithmeticOperationKernel _add_bias_kernel;
+ CLMemoryGroup _memory_group;
+ CLConvolutionLayerReshapeWeights _reshape_weights;
+ CLIm2ColKernel _im2col_kernel;
+ CLGEMM _mm_gemm;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLCol2ImKernel _col2im_kernel;
+ CLActivationLayer _activationlayer_function;
const ICLTensor *_original_weights;
@@ -199,15 +200,11 @@
CLTensor _weights_reshaped;
CLTensor _gemm_output;
- DataLayout _data_layout;
-
- bool _append_bias;
bool _skip_im2col;
bool _skip_col2im;
bool _is_quantized;
- bool _is_activationlayer_enabled;
+ bool _fuse_activation;
bool _is_prepared;
- bool _run_addition;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H__ */