forked from huawei/mindspore2022
59 lines
2.0 KiB
Python
59 lines
2.0 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.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 EqualCount(nn.Cell):
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def __init__(self):
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super(EqualCount, self).__init__()
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self.op = P.EqualCount()
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def construct(self, *inp):
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return self.op(*inp)
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def get_output(*inp, enable_graph_kernel=False):
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context.set_context(enable_graph_kernel=enable_graph_kernel)
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output = EqualCount()(*inp)
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return output
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def basic_test(datatype):
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x = Tensor(np.array([[1, 1, 1, 1], [3, 3, 3, 3]]).astype(datatype))
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y = Tensor(np.array([[1, 2, 1, 2], [1, 1, 3, 3]]).astype(datatype))
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expect = get_output(x, y, enable_graph_kernel=False)
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output = get_output(x, y, enable_graph_kernel=True)
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expect_np = expect.asnumpy().copy()
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output_np = output.asnumpy().copy()
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assert np.allclose(expect_np, output_np, 1.e-4, 1.e-7)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_gpu_fp16():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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basic_test(np.float16)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_gpu_fp32():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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basic_test(np.float32)
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