forked from mindspore-Ecosystem/mindspore
100 lines
3.2 KiB
Python
100 lines
3.2 KiB
Python
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# 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.common.dtype as mstype
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import mindspore.context as context
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from mindspore.common.tensor import Tensor
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from mindspore.nn import Cell
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from mindspore.ops import operations as P
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class LinSpaceNet(Cell):
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def __init__(self, num):
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super(LinSpaceNet, self).__init__()
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self.ls_op = P.LinSpace()
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self.num = num
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def construct(self, start, stop):
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output = self.ls_op(start, stop, self.num)
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return output
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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_lin_space_1():
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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start_np = 5
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stop_np = 150
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num_np = 12
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start = Tensor(start_np, dtype=mstype.float32)
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stop = Tensor(stop_np, dtype=mstype.float32)
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num = num_np
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ls_op = P.LinSpace()
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result_ms = ls_op(start, stop, num).asnumpy()
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result_np = np.linspace(start_np, stop_np, num_np)
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assert np.allclose(result_ms, result_np)
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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_lin_shape_2():
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context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
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start_np = -25
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stop_np = 147
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num_np = 10
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start = Tensor(start_np, dtype=mstype.float32)
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stop = Tensor(stop_np, dtype=mstype.float32)
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num = num_np
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ls_op = P.LinSpace()
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result_ms = ls_op(start, stop, num).asnumpy()
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result_np = np.linspace(start_np, stop_np, num_np)
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assert np.allclose(result_ms, result_np)
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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_lin_shape_3():
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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start_np = 25
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stop_np = -147
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num_np = 20
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start = Tensor(start_np, dtype=mstype.float32)
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stop = Tensor(stop_np, dtype=mstype.float32)
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net = LinSpaceNet(num_np)
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result_ms = net(start, stop).asnumpy()
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result_np = np.linspace(start_np, stop_np, num_np)
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assert np.allclose(result_ms, result_np)
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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_lin_shape_4():
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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start_np = -25.3
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stop_np = -147
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num_np = 36
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start = Tensor(start_np, dtype=mstype.float32)
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stop = Tensor(stop_np, dtype=mstype.float32)
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net = LinSpaceNet(num_np)
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result_ms = net(start, stop).asnumpy()
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result_np = np.linspace(start_np, stop_np, num_np)
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assert np.allclose(result_ms, result_np)
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