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update matmul implementation for GPU

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pull/11862/head
Corleone 4 years ago
parent 8a61767f32
commit 82de371987
2 changed files with 22 additions and 12 deletions
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26
mindspore/ccsrc/backend/kernel_compiler/gpu/math/matmul_gpu_kernel.h
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@ -1,5 +1,5 @@
/**
* Copyright 2019 Huawei Technologies Co., Ltd
* Copyright 2019-2021 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@ -58,14 +58,24 @@ class MatMulGpuKernel : public GpuKernel {
auto stride_c = SizeToInt(m_ * n_);
try {
CHECK_CUBLAS_RET_WITH_EXCEPT(
kernel_node_,
cublasGemmStridedBatchedEx(handle_, transpose_x2_, transpose_x1_, SizeToInt(n_), SizeToInt(m_), SizeToInt(k_),
&alpha, input2_addr, dtype_b_, ldb, stride_b, input1_addr, dtype_a_, lda, stride_a,
&beta, output_addr, dtype_c_, ldc, stride_c, batch_, CUDA_R_32F, algo_),
"cublasSgemm Call Fail");
// Use cublasGemmEx to get high performance when batch_ is 1
if (batch_ == 1) {
CHECK_CUBLAS_RET_WITH_EXCEPT(kernel_node_,
cublasGemmEx(handle_, transpose_x2_, transpose_x1_, SizeToInt(n_), SizeToInt(m_),
SizeToInt(k_), &alpha, input2_addr, dtype_b_, ldb, input1_addr,
dtype_a_, lda, &beta, output_addr, dtype_c_, ldc, CUDA_R_32F, algo_),
"cublasSgemm Call Fail");
} else {
CHECK_CUBLAS_RET_WITH_EXCEPT(
kernel_node_,
cublasGemmStridedBatchedEx(handle_, transpose_x2_, transpose_x1_, SizeToInt(n_), SizeToInt(m_), SizeToInt(k_),
&alpha, input2_addr, dtype_b_, ldb, stride_b, input1_addr, dtype_a_, lda, stride_a,
&beta, output_addr, dtype_c_, ldc, stride_c, batch_, CUDA_R_32F, algo_),
"cublasGemmStridedBatchedEx Call Fail");
}
} catch (const std::exception &e) {
MS_LOG(EXCEPTION) << "Encountered an exception: " << e.what() << " when invoke cublas cublasGemmStridedBatchedEx";
MS_LOG(EXCEPTION) << "Encountered an exception: " << e.what() << " when invoke cublas "
<< (batch_ == 1 ? "cublasGemmEx" : "cublasGemmStridedBatchedEx");
}
return true;
}

8
tests/st/ops/gpu/test_tensordot_op.py
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@ -1,4 +1,4 @@
# Copyright 2020 Huawei Technologies Co., Ltd
# Copyright 2020-2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@ -150,7 +150,7 @@ def test_tensor_dot_fp16():
network = NetTensorDot(axes)
ms_result_np = network(x1_tensor, x2_tensor).asnumpy()
np_result = np.tensordot(x1, x2, axes)
np.testing.assert_array_almost_equal(ms_result_np, np_result)
assert np.allclose(ms_result_np, np_result, rtol=1e-3, atol=1e-3)
# 3D
shape_x1 = (60, 30, 450)
@ -164,7 +164,7 @@ def test_tensor_dot_fp16():
network = NetTensorDot(axes)
ms_result_np = network(x1_tensor, x2_tensor).asnumpy()
np_result = np.tensordot(x1, x2, axes)
np.testing.assert_array_almost_equal(ms_result_np, np_result)
assert np.allclose(ms_result_np, np_result, rtol=1e-3, atol=6e0)
@pytest.mark.level0
@ -173,7 +173,7 @@ def test_tensor_dot_fp16():
def test_tensor_dot_outer():
context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
np.random.seed(2746)
shape_x1 = (1, 2, 3) # incompatable dims for x1 and x2
shape_x1 = (1, 2, 3) # incompatible dims for x1 and x2
shape_x2 = (4, 5, 6)
axes = 0 # outer product does not require multiplicable dims
x1 = np.random.random(shape_x1).astype(np.float32)

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