forked from mindspore-Ecosystem/mindspore
109 lines
3.1 KiB
Python
109 lines
3.1 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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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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# ============================================================================
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import numpy as np
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import pytest
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import mindspore
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.ops import operations as P
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class RandpermNet(nn.Cell):
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def __init__(self, max_length, pad, dtype):
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super(RandpermNet, self).__init__()
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self.randperm = P.Randperm(max_length, pad, dtype)
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def construct(self, x):
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return self.randperm(x)
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def randperm(max_length, pad, dtype, n):
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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x = Tensor(np.array([n]).astype(np.int32))
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randperm_net = RandpermNet(max_length, pad, dtype)
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output = randperm_net(x).asnumpy()
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# verify permutation
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output_perm_sorted = np.sort(output[0:n])
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expected = np.arange(n)
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np.testing.assert_array_equal(expected, output_perm_sorted)
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# verify pad
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output_pad = output[n:]
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for e in output_pad:
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assert e == pad
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print(output)
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print(output.dtype)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_int8():
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randperm(8, -1, mindspore.int8, 5)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_int16():
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randperm(3, 0, mindspore.int16, 3)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_int32():
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randperm(4, -6, mindspore.int32, 2)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_int64():
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randperm(12, 128, mindspore.int64, 4)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_uint8():
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randperm(8, 1, mindspore.uint8, 5)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_uint16():
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randperm(8, 0, mindspore.uint16, 8)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_uint32():
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randperm(4, 8, mindspore.uint32, 3)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_uint64():
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randperm(5, 4, mindspore.uint64, 5)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_randperm_n_too_large():
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with pytest.raises(RuntimeError) as info:
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randperm(1, 0, mindspore.int32, 2)
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assert "n (2) cannot exceed max_length_ (1)" in str(info.value)
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