71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
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# copyright (c) 2021 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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import paddle
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from paddle import nn
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from .ace_loss import ACELoss
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from .center_loss import CenterLoss
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from .rec_ctc_loss import CTCLoss
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class EnhancedCTCLoss(nn.Layer):
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def __init__(self,
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use_focal_loss=False,
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use_ace_loss=False,
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ace_loss_weight=0.1,
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use_center_loss=False,
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center_loss_weight=0.05,
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num_classes=6625,
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feat_dim=96,
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init_center=False,
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center_file_path=None,
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**kwargs):
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super(EnhancedCTCLoss, self).__init__()
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self.ctc_loss_func = CTCLoss(use_focal_loss=use_focal_loss)
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self.use_ace_loss = False
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if use_ace_loss:
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self.use_ace_loss = use_ace_loss
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self.ace_loss_func = ACELoss()
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self.ace_loss_weight = ace_loss_weight
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self.use_center_loss = False
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if use_center_loss:
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self.use_center_loss = use_center_loss
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self.center_loss_func = CenterLoss(
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num_classes=num_classes,
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feat_dim=feat_dim,
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init_center=init_center,
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center_file_path=center_file_path)
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self.center_loss_weight = center_loss_weight
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def __call__(self, predicts, batch):
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loss = self.ctc_loss_func(predicts, batch)["loss"]
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if self.use_center_loss:
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center_loss = self.center_loss_func(
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predicts, batch)["loss_center"] * self.center_loss_weight
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loss = loss + center_loss
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if self.use_ace_loss:
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ace_loss = self.ace_loss_func(
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predicts, batch)["loss_ace"] * self.ace_loss_weight
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loss = loss + ace_loss
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return {'enhanced_ctc_loss': loss}
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