35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
# copyright (c) 2022 PaddlePaddle Authors. All Rights Reserve.
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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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from paddle import nn
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from paddle.nn import functional as F
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class PRENHead(nn.Layer):
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def __init__(self, in_channels, out_channels, **kwargs):
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super(PRENHead, self).__init__()
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self.linear = nn.Linear(in_channels, out_channels)
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def forward(self, x, targets=None):
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predicts = self.linear(x)
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if not self.training:
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predicts = F.softmax(predicts, axis=2)
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return predicts
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