forked from mindspore-Ecosystem/mindspore
64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
# Copyright 2020-2022 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 pytest
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import numpy as np
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import mindspore as ms
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from mindspore import context
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from mindspore import ops, Tensor, dtype, ms_function
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def test_cast():
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"""
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Feature: test cast operator
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Description: Cast original data type to target data type
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Expectation: success
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"""
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context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
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input_np = np.random.randn(2, 3, 4, 5).astype(np.float32)
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input_x = Tensor(input_np)
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type_dst = ms.float32
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cast = ops.Cast()
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result = cast(input_x, type_dst)
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assert result.dtype == type_dst
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@ms_function
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def expand_tensor(a, b):
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out = ops.tile(a, b)
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return out
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_tile_eliminate():
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"""
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Feature: tile_eliminate
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Description: All value of multiplier is '1' but length of multiplier is greater than tensor dims, can't do eliminate
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Expectation: success
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"""
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context.set_context(mode=context.PYNATIVE_MODE)
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tensor_ = Tensor(np.ndarray([1, 448, 448]), dtype=dtype.float32)
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out = ops.tile(tensor_, (1, 1, 1))
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assert out.shape == (1, 448, 448)
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out = ops.tile(tensor_, (1, 1, 1, 1))
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assert out.shape == (1, 1, 448, 448)
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out = expand_tensor(tensor_, (1, 1, 1))
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assert out.shape == (1, 448, 448)
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out = expand_tensor(tensor_, (1, 1, 1, 1))
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assert out.shape == (1, 1, 448, 448)
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