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author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-12-12 10:18:04 +0000 |
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committer | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-12-14 14:57:48 +0000 |
commit | bf9731edfa0439cad4d70efc3065e71e199c62b8 (patch) | |
tree | 71340a3d04a6294744c642ed6e4a56c0e8a77592 /tests/validation/fixtures/GEMMFixture.h | |
parent | 92e278d5f462c930af1947883a5f48c10586ae9c (diff) | |
download | ComputeLibrary-bf9731edfa0439cad4d70efc3065e71e199c62b8.tar.gz |
COMPMID-1687: Optimize CLGEMMMatrixMultiplyKernel for Mali-G76 - Part1
The current implementation is limited just to FP32
Change-Id: I185ab57e483e879d7c301e9cc3033efc8b41e244
Reviewed-on: https://review.mlplatform.org/389
Reviewed-by: Anthony Barbier <Anthony.barbier@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Diffstat (limited to 'tests/validation/fixtures/GEMMFixture.h')
-rw-r--r-- | tests/validation/fixtures/GEMMFixture.h | 111 |
1 files changed, 111 insertions, 0 deletions
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h index 0083abffb5..ce2b177ce9 100644 --- a/tests/validation/fixtures/GEMMFixture.h +++ b/tests/validation/fixtures/GEMMFixture.h @@ -151,6 +151,117 @@ protected: SimpleTensor<T> _reference{}; }; +template <typename TensorType, typename AccessorType, typename ReshapeLHSFunctionType, typename ReshapeRHSFunctionType, typename GEMMFunctionType> +class GEMMMatrixMultiplyReshapedValidationFixture : public framework::Fixture +{ +public: + template <typename...> + void setup(unsigned int m, unsigned int n, unsigned int k, unsigned int batch_size, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int v0, unsigned int h0, bool interleave_lhs, + bool interleave_rhs) + { + GEMMLHSMatrixInfo lhs_info; + lhs_info.m0 = m0; + lhs_info.k0 = k0; + lhs_info.v0 = v0; + lhs_info.interleave = interleave_lhs; + lhs_info.transpose = false; + + GEMMRHSMatrixInfo rhs_info; + rhs_info.n0 = n0; + rhs_info.k0 = k0; + rhs_info.h0 = h0; + rhs_info.interleave = interleave_rhs; + rhs_info.transpose = true; + + // Set the tensor shapes for LHS and RHS matrices + const TensorShape lhs_shape(k, m, batch_size); + const TensorShape rhs_shape(n, k, batch_size); + + _target = compute_target(lhs_shape, rhs_shape, lhs_info, rhs_info); + _reference = compute_reference(lhs_shape, rhs_shape); + } + +protected: + template <typename U> + void fill(U &&tensor, int i) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + } + + TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info) + { + // Create tensors + TensorType lhs = create_tensor<TensorType>(lhs_shape, DataType::F32, 1); + TensorType rhs = create_tensor<TensorType>(rhs_shape, DataType::F32, 1); + TensorType lhs_reshaped; + TensorType rhs_reshaped; + TensorType dst; + + const unsigned int M = lhs_shape[1]; + const unsigned int N = rhs_shape[0]; + const unsigned int K = lhs_shape[0]; + + // The output tensor will be auto-initialized within the function + + // Create and configure function + ReshapeLHSFunctionType reshape_lhs; + ReshapeRHSFunctionType reshape_rhs; + GEMMFunctionType gemm; + reshape_lhs.configure(&lhs, &lhs_reshaped, lhs_info); + reshape_rhs.configure(&rhs, &rhs_reshaped, rhs_info); + gemm.configure(&lhs_reshaped, &rhs_reshaped, &dst, 1.0f, lhs_info, rhs_info, GEMMReshapeInfo(M, N, K)); + + ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(rhs.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + lhs.allocator()->allocate(); + rhs.allocator()->allocate(); + lhs_reshaped.allocator()->allocate(); + rhs_reshaped.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!rhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!lhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(lhs), 0); + fill(AccessorType(rhs), 1); + + // Compute GEMM + reshape_lhs.run(); + reshape_rhs.run(); + gemm.run(); + + return dst; + } + + SimpleTensor<float> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape) + { + TensorShape dst_shape = lhs_shape; + dst_shape[0] = rhs_shape[0]; + dst_shape[1] = lhs_shape[1]; + + // Create reference + SimpleTensor<float> lhs{ lhs_shape, DataType::F32, 1 }; + SimpleTensor<float> rhs{ rhs_shape, DataType::F32, 1 }; + SimpleTensor<float> c{ dst_shape, DataType::F32, 1 }; + + // Fill reference + fill(lhs, 0); + fill(rhs, 1); + fill(c, 2); + + return reference::gemm<float>(lhs, rhs, c, 1.0f, 0.0f); + } + + TensorType _target{}; + SimpleTensor<float> _reference{}; +}; } // namespace validation } // namespace test } // namespace arm_compute |