53 lines
2.0 KiB
Python
Executable File
53 lines
2.0 KiB
Python
Executable File
#copyright (c) 2019 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 math
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import paddle
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import paddle.fluid as fluid
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from paddle.fluid.param_attr import ParamAttr
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from .rec_seq_encoder import SequenceEncoder
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from ..common_functions import get_para_bias_attr
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import numpy as np
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class CTCPredict(object):
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def __init__(self, params):
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super(CTCPredict, self).__init__()
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self.char_num = params['char_num']
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self.encoder = SequenceEncoder(params)
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self.encoder_type = params['encoder_type']
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self.fc_decay = params.get("fc_decay", 0.0004)
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def __call__(self, inputs, labels=None, mode=None):
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encoder_features = self.encoder(inputs)
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if self.encoder_type != "reshape":
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encoder_features = fluid.layers.concat(encoder_features, axis=1)
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name = "ctc_fc"
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para_attr, bias_attr = get_para_bias_attr(
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l2_decay=self.fc_decay, k=encoder_features.shape[1], name=name)
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predict = fluid.layers.fc(input=encoder_features,
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size=self.char_num + 1,
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param_attr=para_attr,
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bias_attr=bias_attr,
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name=name)
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decoded_out = fluid.layers.ctc_greedy_decoder(
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input=predict, blank=self.char_num)
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predicts = {'predict': predict, 'decoded_out': decoded_out}
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return predicts
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