1.6.14

demos/aspect_polarity_classification/run_fast_lsa_deberta.py

@@ -39,7 +39,7 @@
 apc_config_english.hidden_dim = 768
 apc_config_english.embed_dim = 768
 apc_config_english.num_epoch = 25
-apc_config_english.log_step = 5
+apc_config_english.log_step = 10
 apc_config_english.learning_rate = 1e-5
 apc_config_english.batch_size = 16
 apc_config_english.evaluate_begin = 2
@@ -51,7 +51,7 @@
 Laptop14 = ABSADatasetList.Laptop14
 Trainer(config=apc_config_english,
         dataset=Laptop14,  # train set and test set will be automatically detected
-        checkpoint_save_mode=1,  # =None to avoid save model
+        checkpoint_save_mode=0,  # =None to avoid save model
         auto_device=True  # automatic choose CUDA or CPU
         )
 
@@ -104,7 +104,7 @@
 apc_config_english.seed = seeds
 
 apc_config_english.cross_validate_fold = -1  # disable cross_validate
-#
+
 Laptop14 = ABSADatasetList.Laptop14
 Trainer(config=apc_config_english,
         dataset=Laptop14,  # train set and test set will be automatically detected

demos/aspect_polarity_classification/sentiment_inference.py

@@ -13,33 +13,33 @@
 
 checkpoint_map = available_checkpoints(from_local=False)
 
-examples = [
-    'The [ASP]battery-life[ASP], and this [ASP]battery[ASP] is ok',
-    'The [ASP] battery-life [ASP] is bad',
-    'The [ASP] battery-life [ASP] is good',
-    'The [ASP] battery-life [ASP] ',
-    'Strong build though which really adds to its [ASP]durability[ASP] .',  # !sent! Positive
-    'Strong [ASP]build[ASP] though which really adds to its durability . !sent! Positive',
-    'The [ASP]battery life[ASP] is excellent - 6-7 hours without charging . !sent! Positive',
-    'I have had my computer for 2 weeks already and it [ASP]works[ASP] perfectly . !sent! Positive',
-    'And I may be the only one but I am really liking [ASP]Windows 8[ASP] . !sent! Positive',
-]
-sent_classifier = APCCheckpointManager.get_sentiment_classifier(checkpoint='fast_lsa_s_acc_84.9_f1_82.11.zip',
+# examples = [
+#     'The [ASP]battery-life[ASP], and this [ASP]battery[ASP] is ok',
+#     'The [ASP] battery-life [ASP] is bad',
+#     'The [ASP] battery-life [ASP] is good',
+#     'The [ASP] battery-life [ASP] ',
+#     'Strong build though which really adds to its [ASP]durability[ASP] .',  # !sent! Positive
+#     'Strong [ASP]build[ASP] though which really adds to its durability . !sent! Positive',
+#     'The [ASP]battery life[ASP] is excellent - 6-7 hours without charging . !sent! Positive',
+#     'I have had my computer for 2 weeks already and it [ASP]works[ASP] perfectly . !sent! Positive',
+#     'And I may be the only one but I am really liking [ASP]Windows 8[ASP] . !sent! Positive',
+# ]
+sent_classifier = APCCheckpointManager.get_sentiment_classifier(checkpoint='fast_lsa_s_acc_85',
                                                                 auto_device=True,  # Use CUDA if available
                                                                 )
 
 # text = 'everything is always cooked to perfection , the [ASP]service[ASP] is excellent , the [ASP]decor[ASP] cool and understated . !sent! 1 1'
 # sent_classifier.infer(text, print_result=True)
 
-inference_sets = examples
+# inference_sets = examples
+#
+# for ex in examples:
+#     result = sent_classifier.infer(ex, print_result=True)
 
-for ex in examples:
-    result = sent_classifier.infer(ex, print_result=True)
-
-inference_sets = ABSADatasetList.English
+inference_sets = ABSADatasetList.Laptop14
 results = sent_classifier.batch_infer(target_file=inference_sets,
                                       print_result=True,
                                       save_result=True,
                                       ignore_error=False,
                                       )
-print(results)
+# print(results)

pyabsa/__init__.py

@@ -6,7 +6,7 @@
 
 # Copyright (C) 2021. All Rights Reserved.
 
-__version__ = '1.6.13a0'
+__version__ = '1.6.14'
 __name__ = 'pyabsa'
 
 from termcolor import colored

pyabsa/core/apc/prediction/sentiment_classifier.py

@@ -204,6 +204,7 @@ def merge_results(self, results):
             if final_res and "".join(final_res[-1]['text'].split()) == "".join(result['text'].split()):
                 final_res[-1]['aspect'].append(result['aspect'])
                 final_res[-1]['sentiment'].append(result['sentiment'])
+                final_res[-1]['confidence'].append(result['confidence'])
                 final_res[-1]['ref_sentiment'].append(result['ref_sentiment'])
                 final_res[-1]['ref_check'].append(result['ref_check'])
             else:
@@ -212,6 +213,7 @@ def merge_results(self, results):
                         'text': result['text'].replace('  ', ' '),
                         'aspect': [result['aspect']],
                         'sentiment': [result['sentiment']],
+                        'confidence': [result['confidence']],
                         'ref_sentiment': [result['ref_sentiment']],
                         'ref_check': [result['ref_check']]
                     }
@@ -249,13 +251,16 @@ def _infer(self, save_path=None, print_result=True):
                         sent = int(i_probs.argmax(axis=-1))
                         real_sent = int(sample['polarity'][i])
 
+                    confidence = max(i_probs)
+
                     aspect = sample['aspect'][i]
                     text_raw = sample['text_raw'][i]
 
                     results.append({
                         'text': text_raw,
                         'aspect': aspect,
                         'sentiment': sent,
+                        'confidence': confidence,
                         'ref_sentiment': real_sent,
                         'ref_check': correct[sent == real_sent] if real_sent != '-999' else '',
                     })
@@ -269,11 +274,24 @@ def _infer(self, save_path=None, print_result=True):
                     for i in range(len(result['aspect'])):
                         if result['ref_sentiment'][i] != -999:
                             if result['sentiment'][i] == result['ref_sentiment'][i]:
-                                aspect_info = colored('{} -> {}(ref:{})'.format(result['aspect'][i], result['sentiment'][i], result['ref_sentiment'][i]), 'green')
+                                aspect_info = colored('{} -> {}(confidence:{}, ref:{})'.format(
+                                    result['aspect'][i],
+                                    result['sentiment'][i],
+                                    round(result['confidence'][i], 3),
+                                    result['ref_sentiment'][i]),
+                                    'green')
                             else:
-                                aspect_info = colored('{} -> {}(ref:{})'.format(result['aspect'][i], result['sentiment'][i], result['ref_sentiment'][i]), 'red')
+                                aspect_info = colored('{} -> {}(confidence:{}, ref:{})'.format(
+                                    result['aspect'][i],
+                                    result['sentiment'][i],
+                                    round(result['confidence'][i], 3),
+                                    result['ref_sentiment'][i]),
+                                    'red')
+
                         else:
-                            aspect_info = '{} -> {}'.format(result['aspect'][i], result['sentiment'][i])
+                            aspect_info = '{} -> {}(confidence:{})'.format(result['aspect'][i],
+                                                                           round(result['confidence'][i], 3),
+                                                                           result['sentiment'][i])
 
                         text_printing = text_printing.replace(result['aspect'][i], aspect_info)
                     print(text_printing)

pyabsa/utils/file_utils.py

@@ -274,14 +274,18 @@ def save_model(opt, model, tokenizer, save_path):
 
         torch.save(model_to_save.state_dict(), output_model_file)
         model_to_save.bert.config.to_json_file(output_config_file)
-        tokenizer.tokenizer.save_vocabulary(model_output_dir)
+        if hasattr(tokenizer, 'tokenizer'):
+            tokenizer.tokenizer.save_vocabulary(model_output_dir)
+        else:
+            tokenizer.save_vocabulary(model_output_dir)
+
     else:
         raise ValueError('Invalid save_mode: {}'.format(opt.save_mode))
     model.to(opt.device)
 
 
 def check_update_log():
-    print(colored('check update log at https://github.com/yangheng95/PyABSA/blob/release/release-note.json', 'red'))
+    print(colored('check release notes at https://github.com/yangheng95/PyABSA/blob/release/release-note.json', 'red'))
 
 
 def query_remote_version():

pyabsa/utils/pyabsa_utils.py

@@ -34,7 +34,10 @@ def save_args(config, save_path):
 def print_args(config, logger=None, mode=0):
     args = [key for key in sorted(config.args.keys())]
     for arg in args:
-        logger.info('{0}:{1}\t-->\tCalling Count:{2}'.format(arg, config.args[arg], config.args_call_count[arg]))
+        if logger:
+            logger.info('{0}:{1}\t-->\tCalling Count:{2}'.format(arg, config.args[arg], config.args_call_count[arg]))
+        else:
+            print('{0}:{1}\t-->\tCalling Count:{2}'.format(arg, config.args[arg], config.args_call_count[arg]))
 
     # activated_args = []
     # default_args = []

release-note.json

@@ -1,5 +1,5 @@
 {
-  "1.6.13a0": {
+  "1.6.13": {
     "1": "Some minor modifications"
   },
   "1.6.12": {

setup.py

@@ -25,5 +25,5 @@
     # Choose your license
     license='MIT',
     install_requires=['findfile>=1.5', 'autocuda>=0.8', 'spacy', 'networkx', 'seqeval', 'update_checker', 'typing_extensions',
-                      'tqdm', 'termcolor', 'gitpython', 'googledrivedownloader', 'transformers>4.5', 'torch>=1.0', 'sentencepiece', 'termcolor'],
+                      'tqdm', 'termcolor', 'gitpython', 'googledrivedownloader', 'transformers>4.5', 'torch>=1.0', 'sentencepiece'],
 )