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# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
util tools
"""
from __future__ import print_function
import os
import sys
import numpy as np
import paddle.fluid as fluid
import io
def str2bool(v):
"""
argparse does not support True or False in python
"""
return v.lower() in ("true", "t", "1")
def parse_result(words, crf_decode, dataset):
""" parse result """
offset_list = (crf_decode.lod())[0]
words = np.array(words)
crf_decode = np.array(crf_decode)
batch_size = len(offset_list) - 1
for sent_index in range(batch_size):
begin, end = offset_list[sent_index], offset_list[sent_index + 1]
sent=[]
for id in words[begin:end]:
if dataset.id2word_dict[str(id[0])]=='OOV':
sent.append(' ')
else:
sent.append(dataset.id2word_dict[str(id[0])])
tags = [
dataset.id2label_dict[str(id[0])] for id in crf_decode[begin:end]
]
sent_out = []
tags_out = []
parital_word = ""
for ind, tag in enumerate(tags):
# for the first word
if parital_word == "":
parital_word = sent[ind]
tags_out.append(tag.split('-')[0])
continue
# for the beginning of word
if tag.endswith("-B") or (tag == "O" and tags[ind - 1] != "O"):
sent_out.append(parital_word)
tags_out.append(tag.split('-')[0])
parital_word = sent[ind]
continue
parital_word += sent[ind]
# append the last word, except for len(tags)=0
if len(sent_out) < len(tags_out):
sent_out.append(parital_word)
return sent_out,tags_out
def parse_padding_result(words, crf_decode, seq_lens, dataset):
""" parse padding result """
words = np.squeeze(words)
batch_size = len(seq_lens)
batch_out = []
for sent_index in range(batch_size):
sent=[]
for id in words[begin:end]:
if dataset.id2word_dict[str(id[0])]=='OOV':
sent.append(' ')
else:
sent.append(dataset.id2word_dict[str(id[0])])
tags = [
dataset.id2label_dict[str(id)]
for id in crf_decode[sent_index][1:seq_lens[sent_index] - 1]
]
sent_out = []
tags_out = []
parital_word = ""
for ind, tag in enumerate(tags):
# for the first word
if parital_word == "":
parital_word = sent[ind]
tags_out.append(tag.split('-')[0])
continue
# for the beginning of word
if tag.endswith("-B") or (tag == "O" and tags[ind - 1] != "O"):
sent_out.append(parital_word)
tags_out.append(tag.split('-')[0])
parital_word = sent[ind]
continue
parital_word += sent[ind]
# append the last word, except for len(tags)=0
if len(sent_out) < len(tags_out):
sent_out.append(parital_word)
batch_out.append([sent_out, tags_out])
return batch_out
def init_checkpoint(exe, init_checkpoint_path, main_program):
"""
Init CheckPoint
"""
assert os.path.exists(
init_checkpoint_path), "[%s] cann't be found." % init_checkpoint_path
def existed_persitables(var):
"""
If existed presitabels
"""
if not fluid.io.is_persistable(var):
return False
return os.path.exists(os.path.join(init_checkpoint_path, var.name))
fluid.io.load_vars(
exe,
init_checkpoint_path,
main_program=main_program,
predicate=existed_persitables)
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