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468 lines
17 KiB
468 lines
17 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "gtest/gtest.h"
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#include "paddle/fluid/operators/math/blas.h"
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#include "paddle/fluid/operators/math/math_function.h"
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#include "paddle/fluid/platform/device_context.h"
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void fill_fp16_data(paddle::platform::float16* in_ptr, size_t size,
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const std::vector<float>& data) {
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PADDLE_ENFORCE_EQ(size, data.size());
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for (size_t i = 0; i < data.size(); ++i) {
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in_ptr[i] = paddle::platform::float16(data[i]);
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}
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}
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template <typename T>
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inline paddle::operators::math::BlasT<paddle::platform::CUDADeviceContext, T>
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GetBlas(const paddle::platform::CUDADeviceContext& context) {
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return paddle::operators::math::GetBlas<paddle::platform::CUDADeviceContext,
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T>(context);
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}
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TEST(math_function, notrans_mul_trans_fp32) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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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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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input1, gpu_place, &input2_gpu);
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out_gpu.mutable_data<float>({2, 2}, gpu_place);
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GetBlas<float>(context).MatMul(input1_gpu, false, input2_gpu, true, 1,
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&out_gpu, 0);
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paddle::framework::TensorCopySync(out_gpu, cpu_place, &out);
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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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}
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TEST(math_function, notrans_mul_trans_fp16) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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// fp16 GEMM in cublas requires GPU compute capability >= 53
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if (context.GetComputeCapability() < 53) {
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return;
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}
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paddle::platform::float16* input1_ptr =
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input1.mutable_data<paddle::platform::float16>({2, 3}, cpu_place);
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fill_fp16_data(input1_ptr, input1.numel(), {0, 1, 2, 3, 4, 5});
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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input1, gpu_place, &input2_gpu);
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out_gpu.mutable_data<paddle::platform::float16>({2, 2}, gpu_place);
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GetBlas<paddle::platform::float16>(context).MatMul(
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input1_gpu, false, input2_gpu, true, paddle::platform::float16(1),
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&out_gpu, paddle::platform::float16(0));
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paddle::framework::TensorCopySync(out_gpu, cpu_place, &out);
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paddle::platform::float16* out_ptr = out.data<paddle::platform::float16>();
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context.Wait();
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EXPECT_EQ(static_cast<float>(out_ptr[0]), 5);
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EXPECT_EQ(static_cast<float>(out_ptr[1]), 14);
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EXPECT_EQ(static_cast<float>(out_ptr[2]), 14);
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EXPECT_EQ(static_cast<float>(out_ptr[3]), 50);
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}
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TEST(math_function, trans_mul_notrans_fp32) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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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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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input1, gpu_place, &input2_gpu);
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out_gpu.mutable_data<float>({3, 3}, gpu_place);
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GetBlas<float>(context).MatMul(input1_gpu, true, input2_gpu, false, 1,
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&out_gpu, 0);
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paddle::framework::TensorCopySync(out_gpu, cpu_place, &out);
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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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}
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TEST(math_function, trans_mul_notrans_fp16) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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// fp16 GEMM in cublas requires GPU compute capability >= 53
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if (context.GetComputeCapability() < 53) {
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return;
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}
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paddle::platform::float16* input1_ptr =
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input1.mutable_data<paddle::platform::float16>({2, 3}, cpu_place);
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fill_fp16_data(input1_ptr, input1.numel(), {0, 1, 2, 3, 4, 5});
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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input1, gpu_place, &input2_gpu);
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out_gpu.mutable_data<paddle::platform::float16>({3, 3}, gpu_place);
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GetBlas<paddle::platform::float16>(context).MatMul(
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input1_gpu, true, input2_gpu, false, paddle::platform::float16(1),
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&out_gpu, paddle::platform::float16(0));
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paddle::framework::TensorCopySync(out_gpu, cpu_place, &out);
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paddle::platform::float16* out_ptr = out.data<paddle::platform::float16>();
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context.Wait();
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EXPECT_EQ(static_cast<float>(out_ptr[0]), 9);
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EXPECT_EQ(static_cast<float>(out_ptr[1]), 12);
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EXPECT_EQ(static_cast<float>(out_ptr[2]), 15);
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EXPECT_EQ(static_cast<float>(out_ptr[3]), 12);
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EXPECT_EQ(static_cast<float>(out_ptr[4]), 17);
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EXPECT_EQ(static_cast<float>(out_ptr[5]), 22);
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EXPECT_EQ(static_cast<float>(out_ptr[6]), 15);
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EXPECT_EQ(static_cast<float>(out_ptr[7]), 22);
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EXPECT_EQ(static_cast<float>(out_ptr[8]), 29);
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}
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TEST(math_function, gemm_notrans_cublas_fp32) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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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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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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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input2, gpu_place, &input2_gpu);
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paddle::framework::TensorCopySync(input3, gpu_place, &input3_gpu);
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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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GetBlas<float>(context).GEMM(false, false, m, n, k, 1, a, 3, b + 1, 4, 1,
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c + 1, 4);
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paddle::framework::TensorCopySync(input3_gpu, cpu_place, &input3);
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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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}
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TEST(math_function, gemm_notrans_cublas_fp16) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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// fp16 GEMM in cublas requires GPU compute capability >= 53
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if (context.GetComputeCapability() < 53) {
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return;
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}
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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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paddle::platform::float16* input1_ptr =
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input1.mutable_data<paddle::platform::float16>({2, 3}, cpu_place);
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fill_fp16_data(input1_ptr, input1.numel(), {0, 1, 2, 3, 4, 5});
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paddle::platform::float16* input2_ptr =
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input2.mutable_data<paddle::platform::float16>({3, 4}, cpu_place);
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fill_fp16_data(input2_ptr, input2.numel(),
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{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11});
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paddle::platform::float16* input3_ptr =
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input3.mutable_data<paddle::platform::float16>({2, 4}, cpu_place);
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fill_fp16_data(input3_ptr, input3.numel(), {0, 1, 2, 3, 4, 5, 6, 7});
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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input2, gpu_place, &input2_gpu);
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paddle::framework::TensorCopySync(input3, gpu_place, &input3_gpu);
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paddle::platform::float16* a = input1_gpu.data<paddle::platform::float16>();
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paddle::platform::float16* b = input2_gpu.data<paddle::platform::float16>();
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paddle::platform::float16* c =
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input3_gpu.mutable_data<paddle::platform::float16>(gpu_place);
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GetBlas<paddle::platform::float16>(context).GEMM(
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false, false, m, n, k, static_cast<paddle::platform::float16>(1), a, 3,
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b + 1, 4, static_cast<paddle::platform::float16>(1), c + 1, 4);
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paddle::framework::TensorCopySync(input3_gpu, cpu_place, &input3);
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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(static_cast<float>(input3_ptr[0]), 0);
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EXPECT_EQ(static_cast<float>(input3_ptr[1]), 24);
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EXPECT_EQ(static_cast<float>(input3_ptr[2]), 28);
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EXPECT_EQ(static_cast<float>(input3_ptr[3]), 32);
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EXPECT_EQ(static_cast<float>(input3_ptr[4]), 4);
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EXPECT_EQ(static_cast<float>(input3_ptr[5]), 73);
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EXPECT_EQ(static_cast<float>(input3_ptr[6]), 86);
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EXPECT_EQ(static_cast<float>(input3_ptr[7]), 99);
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}
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TEST(math_function, gemm_trans_cublas_fp32) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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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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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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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input2, gpu_place, &input2_gpu);
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paddle::framework::TensorCopySync(input3, gpu_place, &input3_gpu);
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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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GetBlas<float>(context).GEMM(false, true, m, n, k, 1, a, 3, b + 3, 3, 1,
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c + 1, 4);
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paddle::framework::TensorCopySync(input3_gpu, cpu_place, &input3);
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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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}
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TEST(math_function, gemm_trans_cublas_fp16) {
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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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paddle::platform::CPUPlace cpu_place;
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paddle::platform::CUDAPlace gpu_place(0);
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paddle::platform::CUDADeviceContext context(gpu_place);
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// fp16 GEMM in cublas requires GPU compute capability >= 53
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if (context.GetComputeCapability() < 53) {
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return;
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}
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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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paddle::platform::float16* input1_ptr =
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input1.mutable_data<paddle::platform::float16>({2, 3}, cpu_place);
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fill_fp16_data(input1_ptr, input1.numel(), {0, 1, 2, 3, 4, 5});
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paddle::platform::float16* input2_ptr =
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input2.mutable_data<paddle::platform::float16>({4, 3}, cpu_place);
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fill_fp16_data(input2_ptr, input2.numel(),
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{0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11});
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paddle::platform::float16* input3_ptr =
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input3.mutable_data<paddle::platform::float16>({2, 4}, cpu_place);
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fill_fp16_data(input3_ptr, input3.numel(), {0, 1, 2, 3, 4, 5, 6, 7});
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paddle::framework::TensorCopySync(input1, gpu_place, &input1_gpu);
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paddle::framework::TensorCopySync(input2, gpu_place, &input2_gpu);
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paddle::framework::TensorCopySync(input3, gpu_place, &input3_gpu);
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paddle::platform::float16* a = input1_gpu.data<paddle::platform::float16>();
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paddle::platform::float16* b = input2_gpu.data<paddle::platform::float16>();
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paddle::platform::float16* c =
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input3_gpu.mutable_data<paddle::platform::float16>(gpu_place);
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GetBlas<paddle::platform::float16>(context).GEMM(
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false, true, m, n, k, static_cast<paddle::platform::float16>(1), a, 3,
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b + 3, 3, static_cast<paddle::platform::float16>(1), c + 1, 4);
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paddle::framework::TensorCopySync(input3_gpu, cpu_place, &input3);
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context.Wait();
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EXPECT_EQ(static_cast<float>(input3_ptr[0]), 0);
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EXPECT_EQ(static_cast<float>(input3_ptr[1]), 24);
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EXPECT_EQ(static_cast<float>(input3_ptr[2]), 28);
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EXPECT_EQ(static_cast<float>(input3_ptr[3]), 32);
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EXPECT_EQ(static_cast<float>(input3_ptr[4]), 4);
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EXPECT_EQ(static_cast<float>(input3_ptr[5]), 73);
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EXPECT_EQ(static_cast<float>(input3_ptr[6]), 86);
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|
EXPECT_EQ(static_cast<float>(input3_ptr[7]), 99);
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|
}
|
|
|
|
template <typename T>
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|
void GemvTest(int m, int n, bool trans) {
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paddle::framework::Tensor mat_a;
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|
paddle::framework::Tensor vec_b;
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|
paddle::framework::Tensor vec_c;
|
|
|
|
paddle::platform::CPUPlace cpu_place;
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|
paddle::platform::CUDAPlace gpu_place(0);
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|
paddle::platform::CUDADeviceContext context(gpu_place);
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|
|
|
T* data_a = mat_a.mutable_data<T>({m, n}, cpu_place);
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|
T* data_b = vec_b.mutable_data<T>({trans ? m : n}, cpu_place);
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|
T* data_c = vec_c.mutable_data<T>({trans ? n : m}, cpu_place);
|
|
|
|
paddle::framework::Tensor g_mat_a;
|
|
paddle::framework::Tensor g_vec_b;
|
|
paddle::framework::Tensor g_vec_c;
|
|
T* g_data_a = g_mat_a.mutable_data<T>(mat_a.dims(), gpu_place);
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|
T* g_data_b = g_vec_b.mutable_data<T>(vec_b.dims(), gpu_place);
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|
T* g_data_c = g_vec_c.mutable_data<T>(vec_c.dims(), gpu_place);
|
|
|
|
for (int i = 0; i < mat_a.numel(); ++i) {
|
|
data_a[i] = static_cast<T>(i);
|
|
}
|
|
for (int i = 0; i < vec_b.numel(); ++i) {
|
|
data_b[i] = static_cast<T>(i);
|
|
}
|
|
|
|
paddle::framework::TensorCopySync(mat_a, gpu_place, &g_mat_a);
|
|
paddle::framework::TensorCopySync(vec_b, gpu_place, &g_vec_b);
|
|
|
|
GetBlas<T>(context).GEMV(trans, static_cast<int>(m), static_cast<int>(n), 1.,
|
|
g_data_a, g_data_b, 0., g_data_c);
|
|
|
|
paddle::framework::TensorCopySync(g_vec_c, cpu_place, &vec_c);
|
|
|
|
if (!trans) {
|
|
for (int i = 0; i < m; ++i) {
|
|
T sum = 0.0;
|
|
for (int j = 0; j < n; ++j) {
|
|
sum += data_a[i * n + j] * data_b[j];
|
|
}
|
|
ASSERT_FLOAT_EQ(data_c[i], sum);
|
|
}
|
|
} else {
|
|
for (int i = 0; i < n; ++i) {
|
|
T sum = 0.0;
|
|
for (int j = 0; j < m; ++j) {
|
|
sum += data_a[j * n + i] * data_b[j];
|
|
}
|
|
ASSERT_FLOAT_EQ(data_c[i], sum);
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST(math_function, gemv) {
|
|
GemvTest<float>(3, 13, false);
|
|
GemvTest<double>(3, 13, false);
|
|
GemvTest<float>(3, 13, true);
|
|
GemvTest<double>(3, 13, true);
|
|
}
|