forked from mindspore-Ecosystem/mindspore
154 lines
4.5 KiB
Python
154 lines
4.5 KiB
Python
# Copyright 2020 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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import mindspore as ms
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class OpNetWrapper(nn.Cell):
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def __init__(self, op):
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super(OpNetWrapper, self).__init__()
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self.op = op
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def construct(self, *inputs):
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return self.op(*inputs)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_int():
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op = nn.Range(0, 100, 10)
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op_wrapper = OpNetWrapper(op)
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outputs = op_wrapper()
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print(outputs)
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assert outputs.shape == (10,)
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assert np.allclose(outputs.asnumpy(), range(0, 100, 10))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_float():
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op = nn.Range(10., 100., 20.)
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op_wrapper = OpNetWrapper(op)
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outputs = op_wrapper()
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print(outputs)
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assert outputs.shape == (5,)
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assert np.allclose(outputs.asnumpy(), [10., 30., 50., 70., 90.])
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_range_op_int():
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"""
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Feature: test Range op on CPU.
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Description: test the Range when input is int.
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Expectation: result is right.
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"""
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range_op = ms.ops.Range()
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result = range_op(ms.Tensor(2, ms.int32), ms.Tensor(5, ms.int32), ms.Tensor(2, ms.int32))
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expect = np.array([2, 4], np.int32)
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assert np.array_equal(result.asnumpy(), expect)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_range_op_float():
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"""
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Feature: test Range op on CPU.
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Description: test the Range when input is float.
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Expectation: result is right.
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"""
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range_op = ms.ops.Range()
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result = range_op(ms.Tensor(2, ms.float32), ms.Tensor(5, ms.float32), ms.Tensor(1, ms.float32))
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expect = np.array([2, 3, 4], np.float32)
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assert np.array_equal(result.asnumpy(), expect)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_range_op_int64():
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"""
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Feature: test Range op on CPU.
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Description: test the Range when input is int64.
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Expectation: result is right.
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"""
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range_op = ms.ops.Range()
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result = range_op(ms.Tensor(2, ms.int64), ms.Tensor(5, ms.int64), ms.Tensor(2, ms.int64))
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expect = np.array([2, 4], np.int64)
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assert np.array_equal(result.asnumpy(), expect)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_range_op_float64():
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"""
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Feature: test Range op on CPU.
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Description: test the Range when input is float64.
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Expectation: result is right.
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"""
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range_op = ms.ops.Range()
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result = range_op(ms.Tensor(2, ms.float64), ms.Tensor(5, ms.float64), ms.Tensor(1, ms.float64))
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expect = np.array([2, 3, 4], np.float64)
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assert np.array_equal(result.asnumpy(), expect)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_range_op_int_reserve():
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"""
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Feature: test Range op on CPU.
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Description: test the Range when input is int and delta is negative.
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Expectation: result is right.
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"""
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range_op = ms.ops.Range()
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result = range_op(ms.Tensor(8, ms.int32), ms.Tensor(1, ms.int32), ms.Tensor(-1, ms.int32))
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expect = np.array([8, 7, 6, 5, 4, 3, 2], np.int32)
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assert np.array_equal(result.asnumpy(), expect)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_range_op_float_reserve():
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"""
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Feature: test Range op on CPU.
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Description: test the Range when input is float and delta is negative.
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Expectation: result is right.
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"""
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range_op = ms.ops.Range()
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result = range_op(ms.Tensor(8, ms.float32), ms.Tensor(1, ms.float32), ms.Tensor(-1, ms.float32))
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expect = np.array([8, 7, 6, 5, 4, 3, 2], np.float32)
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assert np.array_equal(result.asnumpy(), expect)
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if __name__ == '__main__':
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test_int()
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test_float()
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