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fix ci
This commit is contained in:
Peilin Wang 2021-02-17 17:21:19 -05:00
parent f9f24ca94d
commit 5f7fc5a0b1
3 changed files with 104 additions and 59 deletions
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14
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/cumsum_impl.cu
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@ -1,5 +1,5 @@
/**
* 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.
@ -137,6 +137,18 @@ void CumSum(const T *input, T *output, T *workspace, size_t dim0, size_t dim1, s
return;
}
template void CumSum<uint8_t>(const uint8_t *input, uint8_t *output, uint8_t *workspace, size_t dim0, size_t dim1,
size_t dim2, size_t stride, size_t stride2, bool exclusive_, bool reverse_,
cudaStream_t stream);
template void CumSum<int8_t>(const int8_t *input, int8_t *output, int8_t *workspace, size_t dim0, size_t dim1,
size_t dim2, size_t stride, size_t stride2, bool exclusive_, bool reverse_,
cudaStream_t stream);
template void CumSum<int32_t>(const int32_t *input, int32_t *output, int32_t *workspace, size_t dim0, size_t dim1,
size_t dim2, size_t stride, size_t stride2, bool exclusive_, bool reverse_,
cudaStream_t stream);
template void CumSum<double>(const double *input, double *output, double *workspace, size_t dim0, size_t dim1,
size_t dim2, size_t stride, size_t stride2, bool exclusive_, bool reverse_,
cudaStream_t stream);
template void CumSum<float>(const float *input, float *output, float *workspace, size_t dim0, size_t dim1, size_t dim2,
size_t stride, size_t stride2, bool exclusive_, bool reverse_, cudaStream_t stream);
template void CumSum<half>(const half *input, half *output, half *workspace, size_t dim0, size_t dim1, size_t dim2,

10
mindspore/ccsrc/backend/kernel_compiler/gpu/math/cumsum_gpu_kernel.cc
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@ -1,5 +1,5 @@
/**
* 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.
@ -18,6 +18,14 @@
namespace mindspore {
namespace kernel {
MS_REG_GPU_KERNEL_ONE(CumSum, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt8),
CumSumGpuKernel, uint8_t)
MS_REG_GPU_KERNEL_ONE(CumSum, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt8),
CumSumGpuKernel, int8_t)
MS_REG_GPU_KERNEL_ONE(CumSum, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
CumSumGpuKernel, int32_t)
MS_REG_GPU_KERNEL_ONE(CumSum, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64),
CumSumGpuKernel, double)
MS_REG_GPU_KERNEL_ONE(CumSum, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
CumSumGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(CumSum, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),

139
tests/st/ops/gpu/test_cumsum_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.
@ -22,71 +22,66 @@ from mindspore import Tensor
from mindspore.common.api import ms_function
from mindspore.ops import operations as P
x0 = np.random.rand(2, 3, 4, 4).astype(np.float32)
axis0 = 3
def cum_sum(nptype):
context.set_context(device_target='GPU')
x0 = np.random.rand(2, 3, 4, 4).astype(nptype)
axis0 = 3
x1 = np.random.rand(2, 3, 4, 4).astype(np.float32)
axis1 = 3
x1 = np.random.rand(2, 3, 4, 4).astype(nptype)
axis1 = 3
x2 = np.random.rand(2, 3, 1, 4).astype(np.float32)
axis2 = 2
x2 = np.random.rand(2, 3, 1, 4).astype(nptype)
axis2 = 2
x3 = np.random.rand(2, 3, 1, 4).astype(np.float32)
axis3 = 2
x3 = np.random.rand(2, 3, 1, 4).astype(nptype)
axis3 = 2
x4 = np.random.rand(2, 3, 4, 4).astype(np.float32)
axis4 = 1
x4 = np.random.rand(2, 3, 4, 4).astype(nptype)
axis4 = 1
x5 = np.random.rand(2, 3).astype(np.float32)
axis5 = 1
x5 = np.random.rand(2, 3).astype(nptype)
axis5 = 1
x6 = np.random.rand(1, 1, 1, 1).astype(np.float32)
axis6 = 0
x6 = np.random.rand(1, 1, 1, 1).astype(nptype)
axis6 = 0
context.set_context(device_target='GPU')
class CumSum(nn.Cell):
def __init__(self, nptype):
super(CumSum, self).__init__()
self.x0 = Tensor(x0)
self.axis0 = axis0
self.x1 = Tensor(x1)
self.axis1 = axis1
self.x2 = Tensor(x2)
self.axis2 = axis2
self.x3 = Tensor(x3)
self.axis3 = axis3
self.x4 = Tensor(x4)
self.axis4 = axis4
self.x5 = Tensor(x5)
self.axis5 = axis5
self.x6 = Tensor(x6)
self.axis6 = axis6
@ms_function
def construct(self):
return (P.CumSum()(self.x0, self.axis0),
P.CumSum()(self.x1, self.axis1),
P.CumSum()(self.x2, self.axis2),
P.CumSum()(self.x3, self.axis3),
P.CumSum()(self.x4, self.axis4),
P.CumSum()(self.x5, self.axis5),
P.CumSum()(self.x6, self.axis6))
class CumSum(nn.Cell):
def __init__(self):
super(CumSum, self).__init__()
self.x0 = Tensor(x0)
self.axis0 = axis0
self.x1 = Tensor(x1)
self.axis1 = axis1
self.x2 = Tensor(x2)
self.axis2 = axis2
self.x3 = Tensor(x3)
self.axis3 = axis3
self.x4 = Tensor(x4)
self.axis4 = axis4
self.x5 = Tensor(x5)
self.axis5 = axis5
self.x6 = Tensor(x6)
self.axis6 = axis6
@ms_function
def construct(self):
return (P.CumSum()(self.x0, self.axis0),
P.CumSum()(self.x1, self.axis1),
P.CumSum()(self.x2, self.axis2),
P.CumSum()(self.x3, self.axis3),
P.CumSum()(self.x4, self.axis4),
P.CumSum()(self.x5, self.axis5),
P.CumSum()(self.x6, self.axis6))
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_CumSum():
cumsum = CumSum()
cumsum = CumSum(nptype)
output = cumsum()
expect0 = np.cumsum(x0, axis=axis0)
@ -130,3 +125,33 @@ def test_CumSum():
error6 = np.ones(shape=expect6.shape) * 1.0e-5
assert np.all(diff6 < error6)
assert output[6].shape == expect6.shape
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_cum_sum_uint8():
cum_sum(np.uint8)
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_cum_sum_int8():
cum_sum(np.int8)
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_cum_sum_int32():
cum_sum(np.int32)
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_cum_sum_float16():
cum_sum(np.float16)
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_cum_sum_float32():
cum_sum(np.float32)