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180 lines
6.0 KiB
180 lines
6.0 KiB
#include "gtest/gtest.h"
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#include "paddle/operators/math/math_function.h"
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TEST(math_function, notrans_mul_trans) {
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paddle::framework::Tensor input1;
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paddle::framework::Tensor input1_gpu;
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paddle::framework::Tensor input2_gpu;
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paddle::framework::Tensor out_gpu;
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paddle::framework::Tensor out;
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auto* cpu_place = new paddle::platform::CPUPlace();
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float* input1_ptr = input1.mutable_data<float>({2, 3}, *cpu_place);
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float arr[6] = {0, 1, 2, 3, 4, 5};
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memcpy(input1_ptr, arr, 6 * sizeof(float));
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auto* gpu_place = new paddle::platform::GPUPlace(0);
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paddle::platform::CUDADeviceContext context(*gpu_place);
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input1_gpu.CopyFrom(input1, *gpu_place, context);
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input2_gpu.CopyFrom(input1, *gpu_place, context);
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out_gpu.mutable_data<float>({2, 2}, *gpu_place);
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paddle::operators::math::matmul<paddle::platform::GPUPlace, float>(
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context, input1_gpu, false, input2_gpu, true, 1, &out_gpu, 0);
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out.CopyFrom(out_gpu, *cpu_place, context);
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float* out_ptr = out.data<float>();
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context.Wait();
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EXPECT_EQ(out_ptr[0], 5);
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EXPECT_EQ(out_ptr[1], 14);
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EXPECT_EQ(out_ptr[2], 14);
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EXPECT_EQ(out_ptr[3], 50);
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delete gpu_place;
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}
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TEST(math_function, trans_mul_notrans) {
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paddle::framework::Tensor input1;
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paddle::framework::Tensor input1_gpu;
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paddle::framework::Tensor input2_gpu;
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paddle::framework::Tensor out_gpu;
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paddle::framework::Tensor out;
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auto* cpu_place = new paddle::platform::CPUPlace();
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float* input1_ptr = input1.mutable_data<float>({2, 3}, *cpu_place);
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float arr[6] = {0, 1, 2, 3, 4, 5};
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memcpy(input1_ptr, arr, 6 * sizeof(float));
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auto* gpu_place = new paddle::platform::GPUPlace(0);
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paddle::platform::CUDADeviceContext context(*gpu_place);
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input1_gpu.CopyFrom(input1, *gpu_place, context);
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input2_gpu.CopyFrom(input1, *gpu_place, context);
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out_gpu.mutable_data<float>({3, 3}, *gpu_place);
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paddle::operators::math::matmul<paddle::platform::GPUPlace, float>(
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context, input1_gpu, true, input2_gpu, false, 1, &out_gpu, 0);
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out.CopyFrom(out_gpu, *cpu_place, context);
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float* out_ptr = out.data<float>();
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context.Wait();
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EXPECT_EQ(out_ptr[0], 9);
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EXPECT_EQ(out_ptr[1], 12);
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EXPECT_EQ(out_ptr[2], 15);
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EXPECT_EQ(out_ptr[3], 12);
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EXPECT_EQ(out_ptr[4], 17);
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EXPECT_EQ(out_ptr[5], 22);
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EXPECT_EQ(out_ptr[6], 15);
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EXPECT_EQ(out_ptr[7], 22);
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EXPECT_EQ(out_ptr[8], 29);
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delete gpu_place;
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}
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TEST(math_function, gemm_notrans_cublas) {
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paddle::framework::Tensor input1;
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paddle::framework::Tensor input2;
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paddle::framework::Tensor input3;
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paddle::framework::Tensor input1_gpu;
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paddle::framework::Tensor input2_gpu;
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paddle::framework::Tensor input3_gpu;
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int m = 2;
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int n = 3;
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int k = 3;
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auto* cpu_place = new paddle::platform::CPUPlace();
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float* input1_ptr = input1.mutable_data<float>({2, 3}, *cpu_place);
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float arr1[6] = {0, 1, 2, 3, 4, 5};
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memcpy(input1_ptr, arr1, 6 * sizeof(float));
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float* input2_ptr = input2.mutable_data<float>({3, 4}, *cpu_place);
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float arr2[12] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11};
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memcpy(input2_ptr, arr2, 12 * sizeof(float));
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float* input3_ptr = input3.mutable_data<float>({2, 4}, *cpu_place);
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float arr3[8] = {0, 1, 2, 3, 4, 5, 6, 7};
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memcpy(input3_ptr, arr3, 8 * sizeof(float));
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auto* gpu_place = new paddle::platform::GPUPlace(0);
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paddle::platform::CUDADeviceContext context(*gpu_place);
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input1_gpu.CopyFrom(input1, *gpu_place, context);
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input2_gpu.CopyFrom(input2, *gpu_place, context);
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input3_gpu.CopyFrom(input3, *gpu_place, context);
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float* a = input1_gpu.data<float>();
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float* b = input2_gpu.data<float>();
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float* c = input3_gpu.mutable_data<float>(*gpu_place);
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paddle::operators::math::gemm<paddle::platform::GPUPlace, float>(
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context, false, false, m, n, k, 1, a, 3, b + 1, 4, 1, c + 1, 4);
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input3.CopyFrom(input3_gpu, *cpu_place, context);
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// numpy code:
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// a = np.arange(6).reshape(2, 3)
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// b = np.arange(12).reshape(3, 4)[:, 1:]
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// c = np.arange(8).reshape(2, 4)[:, 1:]
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// out = np.arange(8).reshape(2, 4)
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// out[:, 1:] = np.dot(a, b) + c
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context.Wait();
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EXPECT_EQ(input3_ptr[0], 0);
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EXPECT_EQ(input3_ptr[1], 24);
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EXPECT_EQ(input3_ptr[2], 28);
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EXPECT_EQ(input3_ptr[3], 32);
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EXPECT_EQ(input3_ptr[4], 4);
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EXPECT_EQ(input3_ptr[5], 73);
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EXPECT_EQ(input3_ptr[6], 86);
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EXPECT_EQ(input3_ptr[7], 99);
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delete gpu_place;
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}
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TEST(math_function, gemm_trans_cublas) {
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paddle::framework::Tensor input1;
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paddle::framework::Tensor input2;
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paddle::framework::Tensor input3;
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paddle::framework::Tensor input1_gpu;
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paddle::framework::Tensor input2_gpu;
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paddle::framework::Tensor input3_gpu;
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int m = 2;
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int n = 3;
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int k = 3;
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auto* cpu_place = new paddle::platform::CPUPlace();
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float* input1_ptr = input1.mutable_data<float>({2, 3}, *cpu_place);
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float arr1[6] = {0, 1, 2, 3, 4, 5};
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memcpy(input1_ptr, arr1, 6 * sizeof(float));
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float* input2_ptr = input2.mutable_data<float>({4, 3}, *cpu_place);
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float arr2[12] = {0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11};
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memcpy(input2_ptr, arr2, 12 * sizeof(float));
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float* input3_ptr = input3.mutable_data<float>({2, 4}, *cpu_place);
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float arr3[8] = {0, 1, 2, 3, 4, 5, 6, 7};
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memcpy(input3_ptr, arr3, 8 * sizeof(float));
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auto* gpu_place = new paddle::platform::GPUPlace(0);
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paddle::platform::CUDADeviceContext context(*gpu_place);
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input1_gpu.CopyFrom(input1, *gpu_place, context);
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input2_gpu.CopyFrom(input2, *gpu_place, context);
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input3_gpu.CopyFrom(input3, *gpu_place, context);
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float* a = input1_gpu.data<float>();
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float* b = input2_gpu.data<float>();
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float* c = input3_gpu.mutable_data<float>(*gpu_place);
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paddle::operators::math::gemm<paddle::platform::GPUPlace, float>(
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context, false, true, m, n, k, 1, a, 3, b + 3, 3, 1, c + 1, 4);
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input3.CopyFrom(input3_gpu, *cpu_place, context);
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context.Wait();
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EXPECT_EQ(input3_ptr[0], 0);
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EXPECT_EQ(input3_ptr[1], 24);
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EXPECT_EQ(input3_ptr[2], 28);
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EXPECT_EQ(input3_ptr[3], 32);
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EXPECT_EQ(input3_ptr[4], 4);
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EXPECT_EQ(input3_ptr[5], 73);
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EXPECT_EQ(input3_ptr[6], 86);
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EXPECT_EQ(input3_ptr[7], 99);
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delete gpu_place;
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}
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