[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>

1 files changed, 9 insertions, 9 deletions

diff --git a/src/core/NEON/kernels/arm_gemm/gemm_fp32.cpp b/src/core/NEON/kernels/arm_gemm/gemm_fp32.cpp
index 4f7e191fb3..0fc9e8b912 100644
--- a/src/core/NEON/kernels/arm_gemm/gemm_fp32.cpp
+++ b/src/core/NEON/kernels/arm_gemm/gemm_fp32.cpp
@@ -31,12 +31,12 @@
 #include "gemv_pretransposed.hpp"
 
 #include "kernels/a32_sgemm_8x6.hpp"
-#ifdef ENABLE_FIXED_FORMAT_KERNELS
+#ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #include "kernels/a64_ffhybrid_fp32_mla_6x16.hpp"
 #include "kernels/a64_ffhybrid_fp32bf16fp32_mmla_4x24.hpp"
 #include "kernels/a64_ffinterleaved_bf16fp32_mmla_8x12.hpp"
 #include "kernels/a64_ffinterleaved_fp32_mla_8x12.hpp"
-#endif // ENABLE_FIXED_FORMAT_KERNELS
+#endif // ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #include "kernels/a64_hybrid_fp32bf16fp32_mmla_4x24.hpp"
 #include "kernels/a64_hybrid_fp32bf16fp32_mmla_6x16.hpp"
 #include "kernels/a64_hybrid_fp32_mla_4x24.hpp"
@@ -48,12 +48,12 @@
 #include "kernels/a64_smallK_hybrid_fp32_mla_6x4.hpp"
 #include "kernels/a64_smallK_hybrid_fp32_mla_8x4.hpp"
 
-#ifdef ENABLE_FIXED_FORMAT_KERNELS
+#ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #include "kernels/sve_ffhybrid_fp32_mla_6x4VL.hpp"
 #include "kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp"
 #include "kernels/sve_ffinterleaved_fp32_mla_8x3VL.hpp"
 #include "kernels/sve_ffinterleaved_bf16fp32_mmla_8x3VL.hpp"
-#endif // ENABLE_FIXED_FORMAT_KERNELS
+#endif // ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #include "kernels/sve_hybrid_fp32bf16fp32_mmla_4x6VL.hpp"
 #include "kernels/sve_hybrid_fp32bf16fp32_mmla_6x4VL.hpp"
 #include "kernels/sve_hybrid_fp32_mla_6x4VL.hpp"
@@ -165,7 +165,7 @@ GemmImplementation<float, float>::with_estimate(
     [](const GemmArgs &args) { return GemmInterleaved<cls_sve_interleaved_fp32_mla_8x3VL, float, float>::estimate_cycles<float>(args); },
     [](const GemmArgs &args) { return new GemmInterleaved<cls_sve_interleaved_fp32_mla_8x3VL, float, float>(args); }
 ),
- #ifdef ENABLE_FIXED_FORMAT_KERNELS
+ #ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #ifdef ARM_COMPUTE_ENABLE_BF16
 GemmImplementation<float, float>::with_estimate(
     GemmMethod::GEMM_INTERLEAVED,
@@ -200,7 +200,7 @@ GemmImplementation<float, float>::with_estimate(
     [](const GemmArgs &args) { return GemmHybridIndirectFixedFormat<cls_sve_ffhybrid_fp32_mla_6x4VL, float, float>::estimate_cycles<float>(args); },
     [](const GemmArgs &args) { return new GemmHybridIndirectFixedFormat<cls_sve_ffhybrid_fp32_mla_6x4VL, float, float>(args); }
 ),
-#endif // ENABLE_FIXED_FORMAT_KERNELS
+#endif // ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #endif // ARM_COMPUTE_ENABLE_SVE
 // Cortex-A35 specific kernel - use for any problem on A35, and never in any other cases.
 {
@@ -253,7 +253,7 @@ GemmImplementation<float, float>::with_estimate(
     [](const GemmArgs &args) { return GemmInterleaved<cls_a64_sgemm_8x12, float, float>::estimate_cycles<float>(args); },
     [](const GemmArgs &args) { return new GemmInterleaved<cls_a64_sgemm_8x12, float, float>(args); }
 ),
-#ifdef ENABLE_FIXED_FORMAT_KERNELS
+#ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #ifdef ARM_COMPUTE_ENABLE_BF16
 // "fast mode" (BF16) kernels
 GemmImplementation<float, float>::with_estimate(
@@ -289,7 +289,7 @@ GemmImplementation<float, float>::with_estimate(
     [](const GemmArgs &args) { return GemmHybridIndirectFixedFormat<cls_a64_ffhybrid_fp32_mla_6x16, float, float>::estimate_cycles<float>(args); },
     [](const GemmArgs &args) { return new GemmHybridIndirectFixedFormat<cls_a64_ffhybrid_fp32_mla_6x16, float, float>(args); }
 ),
-#endif // ENABLE_FIXED_FORMAT_KERNELS
+#endif // ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
 #endif // __aarch64__
 
 #ifdef __arm__
@@ -318,7 +318,7 @@ const GemmImplementation<float, float> *gemm_implementation_list<float, float>()
 
 /* Explicitly instantiate the external functions for these types. */
 template UniqueGemmCommon<float, float> gemm<float, float, Nothing>(const GemmArgs &args, const Nothing &);
-template bool has_opt_gemm<float, float, Nothing>(const GemmArgs &args, const Nothing &);
+template bool has_opt_gemm<float, float, Nothing>(WeightFormat &weight_format, const GemmArgs &args, const Nothing &);
 template KernelDescription get_gemm_method<float, float, Nothing>(const GemmArgs &args, const Nothing &);
 template std::vector<KernelDescription> get_compatible_kernels<float, float, Nothing> (const GemmArgs &args, const Nothing &);