Use print() function in both Python 2 and Python 3

convlab/env/movie.py

@@ -1069,7 +1069,7 @@ def initialize_episode(self):
 
  def action_decode(self, action):
  """ DQN: Input state, output action """
- if type(action) == np.ndarray:
+ if isinstance(action, np.ndarray):
  action = action[0]
  act_slot_response = deepcopy(self.feasible_actions[action])
  return {'act_slot_response': act_slot_response, 'act_slot_value_response': None}

convlab/lib/util.py

@@ -14,6 +14,7 @@
 from importlib import reload
 from pprint import pformat
 
+import cv2
 import numpy as np
 import pandas as pd
 import pydash as ps

convlab/modules/dst/multiwoz/evaluate.py

@@ -168,7 +168,7 @@ def _is_empty(slot, domain_state):
  return False
 
 def _is_match(value1, value2):
- if type(value1) is not str or type(value2) is not str:
+ if not isinstance(value1, str) or not isinstance(value2, str):
  return value1 == value2
  value1 = value1.lower()
  value2 = value2.lower()
@@ -179,7 +179,7 @@ def _is_match(value1, value2):
  return False
 
 def _fuzzy_match(value1, value2):
- if type(value1) is not str or type(value2) is not str:
+ if not isinstance(value1, str) or not isinstance(value2, str):
  return value1 == value2
  value1 = value1.lower()
  value2 = value2.lower()

convlab/modules/dst/multiwoz/rule_dst.py

@@ -22,7 +22,7 @@ def __init__(self):
 
  def update(self, user_act=None):
  # print('------------------{}'.format(user_act))
- if type(user_act) is not dict:
+ if not isinstance(user_act, dict):
  raise Exception('Expect user_act to be <class \'dict\'> type but get {}.'.format(type(user_act)))
  previous_state = self.state
  new_belief_state = copy.deepcopy(previous_state['belief_state'])

convlab/modules/e2e/multiwoz/Sequicity/metric.py

@@ -402,13 +402,13 @@ def constraint_same(self, truth_cons, gen_cons):
  def _get_entity_dict(self, entity_data):
  entity_dict = {}
  for k in entity_data:
- if type(entity_data[k][0]) is str:
+ if isinstance(entity_data[k][0], str):
  for entity in entity_data[k]:
  entity = self._lemmatize(self._tokenize(entity))
  entity_dict[entity] = k
  if k in ['event','poi_type']:
  entity_dict[entity.split()[0]] = k
- elif type(entity_data[k][0]) is dict:
+ elif isinstance(entity_data[k][0], dict):
  for entity_entry in entity_data[k]:
  for entity_type, entity in entity_entry.items():
  entity_type = 'poi_type' if entity_type == 'type' else entity_type

convlab/modules/e2e/multiwoz/Sequicity/model.py

@@ -478,7 +478,7 @@ def main(arg_mode=None, arg_model=None):
  for pair in args.cfg:
  k, v = tuple(pair.split('='))
  dtype = type(getattr(cfg, k))
- if dtype == type(None):
+ if isinstance(None, dtype):
  raise ValueError()
  if dtype is bool:
  v = False if v == 'False' else True

convlab/modules/e2e/multiwoz/Sequicity/reader.py

@@ -288,7 +288,7 @@ def db_degree_handler(self, z_samples, *args, **kwargs):
  for cons_idx_list in z_samples:
  constraints = set()
  for cons in cons_idx_list:
- if type(cons) is not str:
+ if not isinstance(cons, str):
  cons = self.vocab.decode(cons)
  if cons == 'EOS_Z1':
  break
@@ -715,14 +715,14 @@ def _get_encoded_data(self, tokenized_data):
  def _get_entity_dict(self, entity_data):
  entity_dict = {}
  for k in entity_data:
- if type(entity_data[k][0]) is str:
+ if isinstance(entity_data[k][0], str):
  for entity in entity_data[k]:
  entity = self._lemmatize(self._tokenize(entity))
  entity_dict[entity] = k
  if k in ['event', 'poi_type']:
  entity_dict[entity.split()[0]] = k
  self.abbr_dict[entity.split()[0]] = entity
- elif type(entity_data[k][0]) is dict:
+ elif isinstance(entity_data[k][0], dict):
  for entity_entry in entity_data[k]:
  for entity_type, entity in entity_entry.items():
  entity_type = 'poi_type' if entity_type == 'type' else entity_type
@@ -753,7 +753,7 @@ def db_degree_handler(self, z_samples, idx=None, *args, **kwargs):
  for i,cons_idx_list in enumerate(z_samples):
  constraints = set()
  for cons in cons_idx_list:
- if type(cons) is not str:
+ if not isinstance(cons, str):
  cons = self.vocab.decode(cons)
  if cons == 'EOS_Z1':
  break
@@ -902,7 +902,7 @@ def _get_encoded_data(self, tokenized_data):
  def _get_clean_db(self, raw_db_data):
  for entry in raw_db_data:
  for k, v in list(entry.items()):
- if type(v) != str or v == '?':
+ if not isinstance(v, str) or v == '?':
  entry.pop(k)
 
  def _construct(self, train_json_path, dev_json_path, test_json_path, db_json_path):

convlab/modules/e2e/multiwoz/Sequicity/tsd_net.py

@@ -25,7 +25,7 @@ def toss_(p):
 
 
 def nan(v):
- if type(v) is float:
+ if isinstance(v, float):
  return v == float('nan')
  return np.isnan(np.sum(v.data.cpu().numpy()))
 

convlab/modules/nlg/multiwoz/sc_lstm/nlg_sc_lstm.py

@@ -90,13 +90,13 @@ def generate_delex(self, meta):
  domain, intent = k.split('-')
  if intent == "Request":
  for pair in v:
- if type(pair[1]) != str:
+ if not isinstance(pair[1], str):
  pair[1] = str(pair[1])
  pair.insert(1, '?')
  else:
  counter = {}
  for pair in v:
- if type(pair[1]) != str:
+ if not isinstance(pair[1], str):
  pair[1] = str(pair[1])
  if pair[0] == 'Internet' or pair[0] == 'Parking':
  pair.insert(1, 'yes')

convlab/modules/nlu/multiwoz/svm/Features.py

@@ -156,8 +156,7 @@ def get_ngrams(sentence, max_length, skip_ngrams=False, add_tags = True):
  for n in range(1, max_length+1):
  subsets = set(itertools.combinations(range(len(words)), n))
  for subset in subsets:
- subset = list(subset)
- subset.sort()
+ subset = sorted(subset)
  dists = [(subset[i]-subset[i-1]) for i in range(1, len(subset))]
  out.append((" ".join([words[j] for j in subset]), dists))
 
@@ -267,7 +266,7 @@ def get_cnngrams(cnet, max_ngrams, max_length):
 class cnNgram(object):
 
  def __init__(self, words, logp, delta=0):
- if type(words) != type([]) :
+ if not isinstance(words, type([])) :
  words = words.split()
  self.words = words
  self.logp = logp

convlab/modules/nlu/multiwoz/svm/corpora/scripts/baseline.py

@@ -356,7 +356,7 @@ def main() :
  elif args.focus.lower() == "false":
  tracker = Tracker()
  else:
- raise RuntimeError,'Dont recognize focus=%s (must be True or False)' % (args.focus) 
+ raise RuntimeError('Dont recognize focus=%s (must be True or False)' % (args.focus)) 
  for call in dataset :
  this_session = {"session-id":call.log["session-id"], "turns":[]}
  tracker.reset()

convlab/modules/nlu/multiwoz/svm/corpora/scripts/check_track.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
@@ -81,7 +82,7 @@ def check(self):
  self.add_error(("top level","wall-time should be included"))
  else:
  wall_time = self.tracker_output["wall-time"]
- if type(wall_time) != type(0.0):
+ if not isinstance(wall_time, type(0.0)):
  self.add_error(("top level","wall-time must be a float"))
  elif wall_time <= 0.0 :
  self.add_error(("top level","wall-time must be positive"))
@@ -192,11 +193,11 @@ def add_error(self, context, error_str):
 
  def print_errors(self):
  if len(self.errors) == 0 :
- print "Found no errors, trackfile is valid"
+ print("Found no errors, trackfile is valid")
  else :
- print "Found",len(self.errors),"errors:"
+ print("Found",len(self.errors),"errors:")
  for context, error in self.errors:
- print " ".join(map(str, context)), "-", error
+ print(" ".join(map(str, context)), "-", error)
 
 
 

convlab/modules/nlu/multiwoz/svm/corpora/scripts/dataset_walker.py

@@ -31,7 +31,7 @@ class dataset_walker(object):
  def __init__(self,dataset,labels=False,dataroot=None):
  if "[" in dataset :
  self.datasets = json.loads(dataset)
- elif type(dataset) == type([]) :
+ elif isinstance(dataset, type([])) :
  self.datasets= dataset
  else:
  self.datasets = [dataset]

convlab/modules/nlu/multiwoz/svm/corpora/scripts/prettyPrint.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
@@ -12,7 +13,7 @@
 
 def jsonItemToCued(i):
  if len(i) > 2:
- print "Unsure what to do about " + str(i)
+ print("Unsure what to do about " + str(i))
  if len(i) > 1:
  return i[0] + "=" + i[1]
  elif len(i) == 1:
@@ -34,28 +35,28 @@ def prettyPrint(fname):
  log = json.load(open(os.path.join(fname, "log.json")))
  label = json.load(open(os.path.join(fname, "label.json")))
  for turn, labelturn in zip(log["turns"], label["turns"]) :
- print "SYS > " + turn['output']['transcript']
+ print("SYS > " + turn['output']['transcript'])
  dact = turn['output']['dialog-acts']
  slulist = turn['input']['live']['slu-hyps']
- print "DAct > " + jsonToCued(dact)
+ print("DAct > " + jsonToCued(dact))
  if len(slulist) > 0:
  for s in slulist:
  slu = s
  #prob = slulist[0]['prob']
- print "SLU > %-20s [%.2f]" % (jsonToCued(slu['slu-hyp']),slu['score'])
+ print("SLU > %-20s [%.2f]" % (jsonToCued(slu['slu-hyp']),slu['score']))
 
  asrlist = turn['input']['live']['asr-hyps']
- print "ASR > " + asrlist[0]['asr-hyp']
- print "Tran > " +str(labelturn['transcription'])
- print " "
+ print("ASR > " + asrlist[0]['asr-hyp'])
+ print("Tran > " +str(labelturn['transcription']))
+ print(" ")
 
 
 
 
 if __name__ == "__main__":
 
  if len(sys.argv) < 2:
- print "Usage: python prettyPrint.py [dialogfolder]"
+ print("Usage: python prettyPrint.py [dialogfolder]")
  else:
  fname = sys.argv[1]
  prettyPrint(fname)

convlab/modules/nlu/multiwoz/svm/corpora/scripts/report.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 # Modified by Microsoft Corporation.
 # Licensed under the MIT license.
 
@@ -78,35 +79,34 @@ def main(argv):
  tables[state_component][EVALUATION_SCHEMES[(schedule, label_scheme)]][stat] = result
 
  for state_component in ["goal.joint","method","requested.all"]:
- print state_component.center(50)
- evaluation_schemes = [key for key in tables[state_component].keys() if len(tables[state_component][key])>0]
- evaluation_schemes.sort()
+ print(state_component.center(50))
+ evaluation_schemes = sorted([key for key in tables[state_component].keys() if len(tables[state_component][key])>0])
  stats = tables[state_component][evaluation_schemes[0]].keys()
  stats.sort()
  print_row(['']+evaluation_schemes, header=True)
  for stat in stats:
  print_row([stat] + [tables[state_component][evaluation_scheme][stat] for evaluation_scheme in evaluation_schemes])
 
- print "\n\n"
+ print("\n\n")
 
 
 
 
- print ' featured metrics'
+ print(' featured metrics')
  print_row(["","Joint Goals","Requested","Method"],header=True)
  print_row(["Accuracy",tables["goal.joint"]["eval_2a"]["acc"],tables["requested.all"]["eval_2a"]["acc"],tables["method"]["eval_2a"]["acc"] ])
  print_row(["l2",tables["goal.joint"]["eval_2a"]["l2"],tables["requested.all"]["eval_2a"]["l2"],tables["method"]["eval_2a"]["l2"] ])
  print_row(["roc.v2_ca05",tables["goal.joint"]["eval_2a"]["roc.v2_ca05"],tables["requested.all"]["eval_2a"]["roc.v2_ca05"],tables["method"]["eval_2a"]["roc.v2_ca05"] ])
 
 
- print "\n\n"
+ print("\n\n")
 
 
- print ' basic stats'
- print '-----------------------------------------------------------------------------------'
+ print(' basic stats')
+ print('-----------------------------------------------------------------------------------')
  for k in sorted(basic_stats.keys()):
  v = basic_stats[k]
- print '%20s : %s' % (k,v)
+ print('%20s : %s' % (k,v))
 
 def print_row(row, header=False):
  out = [str(x) for x in row]
@@ -119,11 +119,11 @@ def print_row(row, header=False):
  out = ("|".join(out))[:-1]+"|"
 
  if header:
- print "-"*len(out)
- print out
- print "-"*len(out)
+ print("-"*len(out))
+ print(out)
+ print("-"*len(out))
  else:
- print out
+ print(out)
 
 
 if (__name__ == '__main__'):