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helper.py
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helper.py
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import os
import pickle
def load_data(path):
"""
Load Dataset from File
"""
input_file = os.path.join(path)
with open(input_file, "r", encoding='utf-8') as f:
data = f.read()
return data
def preprocess_and_save_data(dataset_path, token_lookup, create_lookup_tables):
"""
Preprocess Text Data
"""
text = load_data(dataset_path)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
token_dict = token_lookup()
for key, token in token_dict.items():
text = text.replace(key, ' {} '.format(token))
text = text.lower()
text = text.split()
vocab_to_int, int_to_vocab = create_lookup_tables(text)
int_text = [vocab_to_int[word] for word in text]
pickle.dump((int_text, vocab_to_int, int_to_vocab, token_dict), open('preprocess.p', 'wb'))
def load_preprocess():
"""
Load the Preprocessed Training data and return them in batches of <batch_size> or less
"""
return pickle.load(open('preprocess.p', mode='rb'))
def save_params(params):
"""
Save parameters to file
"""
pickle.dump(params, open('params.p', 'wb'))
def load_params():
"""
Load parameters from file
"""
return pickle.load(open('params.p', mode='rb'))