commit 553f6953fe3bdfad53c11c25f305a16d79d83b24
author Francesco Petrogalli <francesco.petrogalli@arm.com> Thu Jun 30 10:22:01 2022 +0000
committer Francesco Petrogalli <francesco.petrogalli@arm.com> Tue Jul 19 09:26:27 2022 +0000
tree 73642b948b79662096f593458c6138d2f7f48ec6
parent 99c46475daf277aa53e6747f9e41209f418fed33

[ONCPUML-951] Variable weight support for Convolution.

API changes for NEGEMMConvolutionLayer and CpuGemmConv2d

Built with:

    scons neon=1 opencl=0 os=linux arch=armv8.2-a multi_isa=1 \
        build=native -j32 Werror=false validation_tests=1 build_dir=opt \
        standalone=1 asserts=1 experimental_fixed_format_kernels=1 .

Tested with:

    ./build/opt/tests/arm_compute_validation

Hardware where the test executable was run:

Neoverse N1

Test coverage:

* NEGEMMConvolutionLayer, CpuGemmConv2d
* NHWC (the only one supported by the fixed-format kernels)
* F16, F32
* Shapes: RunSmall

Change-Id: I4fd3e495a7cbf61210ea02d37440ba9652934e99
Signed-off-by: Francesco Petrogalli <francesco.petrogalli@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7632
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

src/cpu/operators/CpuGemmConv2d.h

diff --git a/src/cpu/operators/CpuGemmConv2d.h b/src/cpu/operators/CpuGemmConv2d.h
index aec4a2f..f8f0bce 100644
--- a/src/cpu/operators/CpuGemmConv2d.h
+++ b/src/cpu/operators/CpuGemmConv2d.h
@@ -117,6 +117,17 @@
                            const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(),
                            bool enable_fast_math = false, unsigned int num_groups = 1);
 
+    /** Indicates whether or not there is an optimal assembly implementation that can be used to process the given parameters.
+     *
+     * The paramter list is the same as @ref NEGEMMConvolutionLayer::has_opt_impl
+     *
+     * @return a status.
+     */
+    static Status has_opt_impl(arm_gemm::WeightFormat &expected_weight_format, const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
+                               const PadStrideInfo &conv_info,
+                               const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(),
+                               const bool enable_fast_math = false);
+
     // Inherited methods overridden:
     void                             run(ITensorPack &tensors) override;
     void                             prepare(ITensorPack &tensors) override;
@@ -135,9 +146,11 @@
      * @param[in]  enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
      *                              available which may introduce a drop of accuracy as well. Default is false
      * @param[in]  gemm_3d_depth    (Optional) Depth of GEMM 3D (Defaults to 1)
+     * @param[in]  fixed_format     (Optional) Select GEMM execution with variable weights.
+     * @param[in]  weight_format    (Optional) The layout to be used for the weights tensor when running GEMM with variable weights.
      */
     void configure_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo(),
-                      bool enable_fast_math = false, int gemm_3d_depth = 1);
+                      bool enable_fast_math = false, int gemm_3d_depth = 1, bool fixed_format = false, arm_gemm::WeightFormat weight_format = arm_gemm::WeightFormat::UNSPECIFIED);
     /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer matrix multiply routines
      *
      * @param[in] src              Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32.
@@ -151,11 +164,13 @@
      *                             available which may introduce a drop of accuracy as well. Default is false
      * @param[in] gemm_3d_depth    (Optional) Depth of GEMM 3D (Defaults to 1)
      * @param[in] skip_im2col      (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false)
+     * @param[in] fixed_format     (Optional) Select GEMM execution with variable weights.
+     * @param[in] weight_format    (Optional) The layout to be used for the weights tensor when running GEMM with variable weights.
      *
      * @return a status
      */
     static Status validate_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo(),
-                              bool enable_fast_math = false, int gemm_3d_depth = 1, bool skip_im2col = false);
+                              bool enable_fast_math = false, int gemm_3d_depth = 1, bool skip_im2col = false, bool fixed_format = false, arm_gemm::WeightFormat weight_format = arm_gemm::WeightFormat::UNSPECIFIED);
     /** Static function to check if GEMM3D is supported in @ref NEGEMM or in @ref CpuGemmMLowpMatrixMultiplyCore
      *
      * @param[in] src           Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32.
@@ -187,6 +202,11 @@
     static SkipInfo skip_im_col_info(const ITensorInfo *src, const ITensorInfo *weights, const PadStrideInfo &conv_info,
                                      const Size2D &dilation, const ActivationLayerInfo &act_info);
 
+    /** Indicates if the convolution executes in variable weights mode.
+     *
+     * Similar to @ref CpuGemm::isVarWeightsKernel
+     */
+    bool isVarWeightsKernel() const;
     enum AuxTensorIdx
     {
         // CpuGemmLowpMatrixMultiplyCore has up to 8 internal tensors