From 9382ab366997cbf6fdb0d4a6312bce113ea74a51 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Mon, 17 Dec 2018 15:12:07 +0000 Subject: COMPMID-1710: Improve test coverage for CLGEMMMatrixMultiplyReshapedKernel Added test for: 1) Fp16 2) GEMM3D Change-Id: I17c03fe04fe49fba71685d33a6fd8572c91e1a56 Reviewed-on: https://review.mlplatform.org/416 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio --- tests/validation/fixtures/GEMMFixture.h | 149 ++++++++++++++++++++++++++++---- 1 file changed, 133 insertions(+), 16 deletions(-) (limited to 'tests/validation/fixtures/GEMMFixture.h') diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h index ce2b177ce9..24c9d96611 100644 --- a/tests/validation/fixtures/GEMMFixture.h +++ b/tests/validation/fixtures/GEMMFixture.h @@ -151,13 +151,13 @@ protected: SimpleTensor _reference{}; }; -template +template class GEMMMatrixMultiplyReshapedValidationFixture : public framework::Fixture { public: template 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) + bool interleave_rhs, DataType data_type, float alpha) { GEMMLHSMatrixInfo lhs_info; lhs_info.m0 = m0; @@ -177,8 +177,8 @@ public: 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); + _target = compute_target(lhs_shape, rhs_shape, lhs_info, rhs_info, data_type, alpha); + _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha); } protected: @@ -189,11 +189,11 @@ protected: library->fill(tensor, distribution, i); } - TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info) + TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, DataType data_type, float alpha) { // Create tensors - TensorType lhs = create_tensor(lhs_shape, DataType::F32, 1); - TensorType rhs = create_tensor(rhs_shape, DataType::F32, 1); + TensorType lhs = create_tensor(lhs_shape, data_type, 1); + TensorType rhs = create_tensor(rhs_shape, data_type, 1); TensorType lhs_reshaped; TensorType rhs_reshaped; TensorType dst; @@ -210,7 +210,7 @@ protected: 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)); + gemm.configure(&lhs_reshaped, &rhs_reshaped, &dst, alpha, 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); @@ -240,27 +240,144 @@ protected: return dst; } - SimpleTensor compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape) + SimpleTensor compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha) { TensorShape dst_shape = lhs_shape; dst_shape[0] = rhs_shape[0]; dst_shape[1] = lhs_shape[1]; // Create reference - SimpleTensor lhs{ lhs_shape, DataType::F32, 1 }; - SimpleTensor rhs{ rhs_shape, DataType::F32, 1 }; - SimpleTensor c{ dst_shape, DataType::F32, 1 }; + SimpleTensor lhs{ lhs_shape, data_type, 1 }; + SimpleTensor rhs{ rhs_shape, data_type, 1 }; + SimpleTensor c{ dst_shape, data_type, 1 }; // Fill reference fill(lhs, 0); fill(rhs, 1); - fill(c, 2); - return reference::gemm(lhs, rhs, c, 1.0f, 0.0f); + return reference::gemm(lhs, rhs, c, alpha, 0.0f); } - TensorType _target{}; - SimpleTensor _reference{}; + TensorType _target{}; + SimpleTensor _reference{}; +}; + +template +class GEMMMatrixMultiplyReshaped3DValidationFixture : public framework::Fixture +{ +public: + template + void setup(unsigned int m_w, unsigned int m_h, 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, DataType data_type, float alpha) + { + 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; + + // In case of GEMM3D, m is the product between m_w and m_h + const unsigned int m = m_w * m_h; + + // 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, data_type, alpha, m_h); + _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, m_h); + } + +protected: + template + 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, DataType data_type, float alpha, + unsigned int m_h) + { + // Create tensors + TensorType lhs = create_tensor(lhs_shape, data_type, 1); + TensorType rhs = create_tensor(rhs_shape, data_type, 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, alpha, lhs_info, rhs_info, GEMMReshapeInfo(M, N, K, 1, 1, m_h)); + + 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 compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, unsigned int m_h) + { + TensorShape dst_shape = lhs_shape; + dst_shape.set(0, rhs_shape[0]); + dst_shape.set(1, lhs_shape[1] / m_h); + dst_shape.set(2, m_h); + dst_shape.set(3, lhs_shape[2]); + + // Create reference + SimpleTensor lhs{ lhs_shape, data_type, 1 }; + SimpleTensor rhs{ rhs_shape, data_type, 1 }; + SimpleTensor c{ dst_shape, data_type, 1 }; + + // Fill reference + fill(lhs, 0); + fill(rhs, 1); + + return reference::gemm(lhs, rhs, c, alpha, 0.0f); + } + + TensorType _target{}; + SimpleTensor _reference{}; }; } // namespace validation } // namespace test -- cgit v1.2.1