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dataio.py
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dataio.py
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import pandas as pd
import os
from collections import Counter
import re
import json
import math
import matplotlib.pyplot as plt
import time
import csv
def load_annotated_tie_pairs(meta_annotation_csv_path):
ret = []
used_dialog_ids = set()
with open(meta_annotation_csv_path, "r", encoding='utf-8') as csvfile:
csv_file = csv.reader(csvfile, delimiter=',')
for i, row in enumerate(csv_file):
if i == 0:
continue
new_row = dict()
new_row['annotation_pair_id'] = row[0]
new_row['dial1_id'] = row[1]
new_row['dial2_id'] = row[2]
ret.append(new_row)
used_dialog_ids.add(new_row['dial1_id'])
used_dialog_ids.add(new_row['dial2_id'])
return ret, used_dialog_ids
def load_annotated_pairs(meta_annotation_csv_path="./morepairs218.csv"):
ret = []
used_dialog_ids = set()
with open(meta_annotation_csv_path, "r", encoding='utf-8') as csvfile:
csv_file = csv.reader(csvfile, delimiter=',')
for i, row in enumerate(csv_file):
if i == 0:
continue
new_row = dict()
new_row['annotation_pair_id'] = row[0]
new_row['dial1_id'] = row[1]
new_row['dial2_id'] = row[2]
new_row['compare_res'] = int(row[3])
assert(new_row['compare_res'] == 1 or new_row['compare_res'] == 2)
ret.append(new_row)
used_dialog_ids.add(new_row['dial1_id'])
used_dialog_ids.add(new_row['dial2_id'])
return ret, used_dialog_ids
def load_dataset(data_set_csv_file_name, used_dialog_ids=set(), early_truncate=-1):
dataset = []
total_dial_count = 0
valid_dial_count = 0
begin_row_this_dialog = 0
end_row_this_dialog = 0
utters_this_dialog = []
def handle_dialog():
retFlag = True
each_dialog_data = dict()
dial_len = end_row_this_dialog - begin_row_this_dialog + 1
if dial_len == 0:
return False, None
if utters_this_dialog[0]['conversation_id'] in used_dialog_ids:
print("test data found! ignore:", utters_this_dialog[0]['conversation_id'])
return False, None
rating = utters_this_dialog[0]['rating']
each_dialog_data['rating'] = int(round(rating))
each_dialog_data['conversation_id'] = utters_this_dialog[0]['conversation_id']
each_dialog_data['response'] = []
each_dialog_data['text'] = []
for sub_cur_utter in utters_this_dialog:
response = sub_cur_utter['response']
if type(response) is str:
response = response.encode('ascii', 'ignore').decode('ascii')
try:
response_without_angle_brackets = re.sub(u'<.*?>', '', response)
except Exception as e:
print(response, utters_this_dialog)
print(e)
exit(0)
assert len(response_without_angle_brackets)>0, response_without_angle_brackets
each_dialog_data['response'].append(response_without_angle_brackets)
if type(sub_cur_utter['text']) is str:
assert len(sub_cur_utter['text'])>0, sub_cur_utter['text']
text = sub_cur_utter['text'].encode('ascii', 'ignore').decode('ascii')
each_dialog_data['text'].append(text)
return retFlag, each_dialog_data
start_time = time.time()
filepath = data_set_csv_file_name
print("reading data " + filepath)
df = pd.read_csv(filepath, low_memory=False)
for j, cur_utter in df.iterrows():
if early_truncate!=-1 and total_dial_count>early_truncate:
break
else:
pass
if j == 0:
prev_id = cur_utter['conversation_id']
prev_module = cur_utter['selected_modules']
prev_response = cur_utter['response']
if j%10000 == 9999:
print("current progress: ", j, "time elapsed:", time.time()-start_time, "valid_dial_count", valid_dial_count )
if prev_id != cur_utter['conversation_id']:
end_row_this_dialog = j -1
dial_valid_flag, each_dialog_data = handle_dialog()
if dial_valid_flag is True:
valid_dial_count += 1
dataset.append(each_dialog_data)
prev_id = cur_utter['conversation_id']
prev_module = cur_utter['selected_modules']
prev_response = cur_utter['response']
begin_row_this_dialog = j
total_dial_count += 1
utters_this_dialog = []
else:
pass
utters_this_dialog.append(cur_utter)
print("total sentences here: ", j, "total_dial_count: ", total_dial_count, "valid_dial_count", valid_dial_count)
end_time = time.time()
print(end_time - start_time)
return dataset
def balanced_dataset_load(data_set_csv_file_name, used_dialog_ids=set(), early_truncate=-1):
datasets = [ [] for _ in range(6) ]
total_dial_count = 0
valid_dial_count = 0
begin_row_this_dialog = 0
end_row_this_dialog = 0
utters_this_dialog = []
def handle_dialog():
retFlag = True
each_dialog_data = dict()
# dialog len in turns
dial_len = end_row_this_dialog - begin_row_this_dialog + 1
if dial_len == 0:
return False
if utters_this_dialog[0]['conversation_id'] in used_dialog_ids:
print("test data found! ignore:", utters_this_dialog[0]['conversation_id'])
return False, None
rating = utters_this_dialog[0]['rating']
each_dialog_data['rating'] = int(round(rating))
each_dialog_data['conversation_id'] = utters_this_dialog[0]['conversation_id']
each_dialog_data['response'] = []
each_dialog_data['text'] = []
for sub_cur_utter in utters_this_dialog:
response = sub_cur_utter['response']
if type(response) is str:
response = response.encode('ascii', 'ignore').decode('ascii')
try:
response_without_angle_brackets = re.sub(u'<.*?>', '', response)
except Exception as e:
print(response, utters_this_dialog)
print(e)
exit(0)
assert len(response_without_angle_brackets)>0, response_without_angle_brackets
each_dialog_data['response'].append(response_without_angle_brackets)
if type(sub_cur_utter['text']) is str:
assert len(sub_cur_utter['text'])>0, sub_cur_utter['text']
text = sub_cur_utter['text'].encode('ascii', 'ignore').decode('ascii')
each_dialog_data['text'].append(text)
return retFlag, each_dialog_data
start_time = time.time()
filepath = data_set_csv_file_name
print("reading data " + filepath)
df = pd.read_csv(filepath, low_memory=False)
for j, cur_utter in df.iterrows():
if early_truncate!=-1 and total_dial_count>early_truncate:
break
if j == 0:
prev_id = cur_utter['conversation_id']
prev_module = cur_utter['selected_modules']
prev_response = cur_utter['response']
if j%10000 == 9999:
print("current progress: ", j, "time elapsed:", time.time()-start_time, "valid_dial_count", valid_dial_count )
if prev_id != cur_utter['conversation_id']:
end_row_this_dialog = j -1
dial_valid_flag, each_dialog_data = handle_dialog()
if dial_valid_flag is True:
dial_rating = each_dialog_data['rating']
valid_dial_count += 1
datasets[dial_rating].append(each_dialog_data)
prev_id = cur_utter['conversation_id']
prev_module = cur_utter['selected_modules']
prev_response = cur_utter['response']
begin_row_this_dialog = j
total_dial_count += 1
utters_this_dialog = []
else:
pass
utters_this_dialog.append(cur_utter)
print("total sentences here: ", j, "total_dial_count: ", total_dial_count, "valid_dial_count", valid_dial_count)
end_time = time.time()
print(end_time - start_time)
print("1,2,3,4,5 len:", end=' ')
for dataset in datasets:
print(len(dataset))
return datasets
def get_all_data(datasets):
ret = []
for dataset in datasets:
ret += dataset
return ret
def balanced_split_dataset(datasets):
DEBUG_IO_FLAG = False
scores_wanted = {1,2,3,4,5}
train, dev, test = [], [], []
if DEBUG_IO_FLAG is False:
for s in scores_wanted:
test.extend(datasets[s][:125])
dev.extend(datasets[s][125:250])
train.extend(datasets[s][250:])
else:
for s in scores_wanted:
test.extend(datasets[s][:8])
dev.extend(datasets[s][8:16])
train.extend(datasets[s][16:32])
return train, dev, test