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69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
8 months ago
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# 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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import paddle
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from paddle import nn
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from .rec_ctc_loss import CTCLoss
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from .rec_sar_loss import SARLoss
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from .rec_nrtr_loss import NRTRLoss
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class MultiLoss(nn.Layer):
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def __init__(self, **kwargs):
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super().__init__()
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self.loss_funcs = {}
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self.loss_list = kwargs.pop("loss_config_list")
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self.weight_1 = kwargs.get("weight_1", 1.0)
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self.weight_2 = kwargs.get("weight_2", 1.0)
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for loss_info in self.loss_list:
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for name, param in loss_info.items():
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if param is not None:
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kwargs.update(param)
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loss = eval(name)(**kwargs)
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self.loss_funcs[name] = loss
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def forward(self, predicts, batch):
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self.total_loss = {}
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total_loss = 0.0
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# batch [image, label_ctc, label_sar, length, valid_ratio]
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for name, loss_func in self.loss_funcs.items():
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if name == "CTCLoss":
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loss = (
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loss_func(predicts["ctc"], batch[:2] + batch[3:])["loss"]
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* self.weight_1
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)
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elif name == "SARLoss":
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loss = (
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loss_func(predicts["sar"], batch[:1] + batch[2:])["loss"]
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* self.weight_2
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)
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elif name == "NRTRLoss":
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loss = (
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loss_func(predicts["gtc"], batch[:1] + batch[2:])["loss"]
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* self.weight_2
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)
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else:
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raise NotImplementedError(
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"{} is not supported in MultiLoss yet".format(name)
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)
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self.total_loss[name] = loss
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total_loss += loss
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self.total_loss["loss"] = total_loss
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return self.total_loss
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