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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- import numpy as np
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE,
- device_target="Ascend")
-
-
- class EditDistance(nn.Cell):
- def __init__(self, hypothesis_shape, truth_shape, normalize=True):
- super(EditDistance, self).__init__()
- self.edit_distance = P.EditDistance(normalize)
- self.hypothesis_shape = hypothesis_shape
- self.truth_shape = truth_shape
-
- def construct(self, hypothesis_indices, hypothesis_values, truth_indices, truth_values):
- return self.edit_distance(hypothesis_indices, hypothesis_values, self.hypothesis_shape,
- truth_indices, truth_values, self.truth_shape)
-
- def test_edit_distance():
- h1, h2, h3 = np.array([[0, 0, 0], [1, 0, 1], [1, 1, 1]]), np.array([1, 2, 3]), np.array([2, 2, 2])
- t1, t2, t3 = np.array([[0, 1, 0], [0, 0, 1], [1, 1, 0], [1, 0, 1]]), np.array([1, 2, 3, 1]), np.array([2, 2, 2])
- hypothesis_indices = Tensor(h1.astype(np.int64))
- hypothesis_values = Tensor(h2.astype(np.int64))
- hypothesis_shape = Tensor(h3.astype(np.int64))
- truth_indices = Tensor(t1.astype(np.int64))
- truth_values = Tensor(t2.astype(np.int64))
- truth_shape = Tensor(t3.astype(np.int64))
- edit_distance = EditDistance(hypothesis_shape, truth_shape)
- out = edit_distance(hypothesis_indices, hypothesis_values, truth_indices, truth_values)
- print(out)
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