wehub-resource-sync
81 lines
2.4 KiB
Python
81 lines
2.4 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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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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import unittest
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import numpy as np
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import paddle
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from paddle.nn.functional.input import embedding_renorm_
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def ref_embedding_renorm_(x, weight, max_norm, norm_type=2.0):
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weight = weight.copy()
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x = np.reshape(x, (-1,))
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x = np.unique(x)
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x = np.sort(x)
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for i in range(len(x)):
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norm = np.linalg.norm(
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weight[int(x[i])], ord=norm_type, axis=0, keepdims=False
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)
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if norm > max_norm:
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weight[int(x[i])] *= max_norm / (norm + 1e-7)
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return weight
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class TestEmbeddingRenormOp(unittest.TestCase):
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def setUp(self):
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self._init_attr()
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self.dtype = self._init_dtype()
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x = np.array([[2, 1, 3], [4, 5, 6]]).astype("int64")
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weight = np.random.random((10, 4)).astype(self.dtype) * 10
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y_ref = ref_embedding_renorm_(x, weight, self.max_norm, self.norm_type)
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self.inputs = {'X': x, 'Weight': weight}
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self.outputs = {'Out': y_ref}
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self.attrs = {'max_norm': self.max_norm, 'norm_type': self.norm_type}
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def _init_dtype(self):
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return "float32"
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def _init_attr(self):
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self.max_norm = 1.0
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self.norm_type = 2.0
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def test_check_output(self):
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paddle_result = embedding_renorm_(
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paddle.to_tensor(self.inputs['X']),
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paddle.to_tensor(self.inputs['Weight']),
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self.max_norm,
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self.norm_type,
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)
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np.testing.assert_allclose(
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paddle_result.numpy(), self.outputs['Out'], atol=1e-5
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)
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class TestEmbeddingRenormOp1(TestEmbeddingRenormOp):
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def _init_attr(self):
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self.max_norm = 1.0
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self.norm_type = 1.0
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class TestEmbeddingRenormOp2(TestEmbeddingRenormOp):
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def _init_attr(self):
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self.max_norm = 1.0
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self.norm_type = 3.0
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if __name__ == '__main__':
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unittest.main()
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