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utils.py
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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.
"""
EmoTect utilities.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import io
import os
import sys
import six
import random
import paddle
import paddle.fluid as fluid
import numpy as np
def init_checkpoint(exe, init_checkpoint_path, main_program):
"""
Init CheckPoint
"""
fluid.load(main_program, init_checkpoint_path, exe)
def word2id(word_dict, query):
"""
Convert word sequence into id list
"""
unk_id = len(word_dict)
wids = [
word_dict[w] if w in word_dict else unk_id
for w in query.strip().split(" ")
]
return wids
def pad_wid(wids, max_seq_len=128, pad_id=0):
"""
Padding data to max_seq_len
"""
seq_len = len(wids)
if seq_len < max_seq_len:
for i in range(max_seq_len - seq_len):
wids.append(pad_id)
else:
wids = wids[:max_seq_len]
seq_len = max_seq_len
return wids, seq_len
def data_reader(file_path, word_dict, num_examples, phrase, epoch, max_seq_len):
"""
Data reader, which convert word sequence into id list
"""
all_data = []
with io.open(file_path, "r", encoding='utf8') as fin:
for line in fin:
if line.startswith("label"):
continue
if phrase == "infer":
cols = line.strip().split("\t")
query = cols[-1] if len(cols) != -1 else cols[0]
wids = word2id(word_dict, query)
wids, seq_len = pad_wid(wids, max_seq_len)
all_data.append((wids, seq_len))
else:
cols = line.strip().split("\t")
if len(cols) != 2:
sys.stderr.write("[NOTICE] Error Format Line!")
continue
label = int(cols[0])
query = cols[1].strip()
wids = word2id(word_dict, query)
wids, seq_len = pad_wid(wids, max_seq_len)
all_data.append((wids, label, seq_len))
num_examples[phrase] = len(all_data)
if phrase == "infer":
def reader():
"""
Infer reader function
"""
for wids, seq_len in all_data:
yield wids, seq_len
return reader
def reader():
"""
Reader function
"""
for idx in range(epoch):
if phrase == "train" and 'ce_mode' not in os.environ:
random.shuffle(all_data)
for wids, label, seq_len in all_data:
yield wids, label, seq_len
return reader
def load_vocab(file_path):
"""
load the given vocabulary
"""
vocab = {}
with io.open(file_path, 'r', encoding='utf8') as fin:
wid = 0
for line in fin:
if line.strip() not in vocab:
vocab[line.strip()] = wid
wid += 1
vocab["<unk>"] = len(vocab)
return vocab
def print_arguments(args):
"""
print arguments
"""
print('----------- Configuration Arguments -----------')
for arg, value in sorted(six.iteritems(vars(args))):
print('%s: %s' % (arg, value))
print('------------------------------------------------')
def query2ids(vocab_path, query):
"""
Convert query to id list according to the given vocab
"""
vocab = load_vocab(vocab_path)
wids = word2id(vocab, query)
return wids