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| import gradio as gr | |
| import os | |
| import torch | |
| import transformers | |
| import shutil | |
| stat = shutil.disk_usage('.') | |
| print('Disk usage:') | |
| print(stat) | |
| device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu') | |
| class Interactive: | |
| def __init__(self): | |
| self.tokenizer = transformers.AutoTokenizer.from_pretrained('liujch1998/cd-pi', use_auth_token=os.environ['HF_TOKEN_DOWNLOAD']) | |
| self.model = transformers.T5EncoderModel.from_pretrained('liujch1998/cd-pi', use_auth_token=os.environ['HF_TOKEN_DOWNLOAD']).to(device) | |
| self.linear = torch.nn.Linear(self.model.shared.embedding_dim, 1).to(device) | |
| self.linear.weight = torch.nn.Parameter(self.model.shared.weight[32099, :].unsqueeze(0)) # (1, D) | |
| self.linear.bias = torch.nn.Parameter(self.model.shared.weight[32098, 0].unsqueeze(0)) # (1) | |
| self.model.eval() | |
| self.t = self.model.shared.weight[32097, 0].item() | |
| def run(self, statement): | |
| input_ids = self.tokenizer.batch_encode_plus([statement], return_tensors='pt', padding='longest').input_ids.to(device) | |
| with torch.no_grad(): | |
| output = self.model(input_ids) | |
| last_hidden_state = output.last_hidden_state.to(device) # (B=1, L, D) | |
| hidden = last_hidden_state[0, -1, :] # (D) | |
| logit = self.linear(hidden).squeeze(-1) # () | |
| logit_calibrated = logit / self.t | |
| score = logit.sigmoid() | |
| score_calibrated = logit_calibrated.sigmoid() | |
| return { | |
| 'logit': logit.item(), | |
| 'logit_calibrated': logit_calibrated.item(), | |
| 'score': score.item(), | |
| 'score_calibrated': score_calibrated.item(), | |
| } | |
| interactive = Interactive() | |
| def predict(statement, model): | |
| result = interactive.run(statement) | |
| return { | |
| 'True': result['score_calibrated'], | |
| 'False': 1 - result['score_calibrated'], | |
| } | |
| examples = [ | |
| # openbookqa | |
| 'If a person walks in the opposite direction of a compass arrow they are walking south.', | |
| 'If a person walks in the opposite direction of a compass arrow they are walking north.', | |
| # arc_easy | |
| 'A pond is different from a lake because ponds are smaller and shallower.', | |
| 'A pond is different from a lake because ponds have moving water.', | |
| # arc_hard | |
| 'Hunting strategies are more likely to be learned rather than inherited.', | |
| 'A spotted coat is more likely to be learned rather than inherited.', | |
| # ai2_science_elementary | |
| 'Photosynthesis uses carbon from the air to make food for plants.', | |
| 'Respiration uses carbon from the air to make food for plants.', | |
| # ai2_science_middle | |
| 'The barometer measures atmospheric pressure.', | |
| 'The thermometer measures atmospheric pressure.', | |
| # commonsenseqa | |
| 'People aim to complete a job at work.', | |
| 'People aim to kill animals at work.', | |
| # qasc | |
| 'Climate is generally described in terms of local weather conditions.', | |
| 'Climate is generally described in terms of forests.', | |
| # physical_iqa | |
| 'ice box will turn into a cooler if you add water to it.', | |
| 'ice box will turn into a cooler if you add soda to it.', | |
| # social_iqa | |
| 'Kendall opened their mouth to speak and what came out shocked everyone. Kendall is a very aggressive and talkative person.', | |
| 'Kendall opened their mouth to speak and what came out shocked everyone. Kendall is a very quiet person.', | |
| # winogrande_xl | |
| 'Sarah was a much better surgeon than Maria so Maria always got the easier cases.', | |
| 'Sarah was a much better surgeon than Maria so Sarah always got the easier cases.', | |
| # com2sense_paired | |
| 'If you want a quick snack, getting one banana would be a good choice generally.', | |
| 'If you want a snack, getting twenty bananas would be a good choice generally.', | |
| # sciq | |
| 'Each specific polypeptide has a unique linear sequence of amino acids.', | |
| 'Each specific polypeptide has a unique linear sequence of fatty acids.', | |
| # quarel | |
| 'Tommy glided across the marble floor with ease, but slipped and fell on the wet floor because wet floor has more resistance.', | |
| 'Tommy glided across the marble floor with ease, but slipped and fell on the wet floor because marble floor has more resistance.', | |
| # quartz | |
| 'If less waters falls on an area of land it will cause less plants to grow in that area.', | |
| 'If less waters falls on an area of land it will cause more plants to grow in that area.', | |
| # cycic_mc | |
| 'In U.S. spring, Rob visits the financial district every day. In U.S. winter, Rob visits the park every day. Rob will go to the park on January 20.', | |
| 'In U.S. spring, Rob visits the financial district every day. In U.S. winter, Rob visits the park every day. Rob will go to the financial district on January 20.', | |
| # comve_a | |
| 'Summer in North America is great for swimming, boating, and fishing.', | |
| 'Summer in North America is great for skiing, snowshoeing, and making a snowman.', | |
| # csqa2 | |
| 'Gas is always capable of turning into liquid under high pressure.', | |
| 'Cotton candy is sometimes made out of cotton.', | |
| # symkd_anno | |
| 'James visits a famous landmark. As a result, James learns about the world.', | |
| 'Cliff and Andrew enter the castle. But before, Cliff needed to have been a student at the school.', | |
| # gengen_anno | |
| 'Generally, bar patrons are capable of taking care of their own drinks.', | |
| 'Generally, ocean currents have little influence over storm intensity.', | |
| # 'If A sits next to B and B sits next to C, then A must sit next to C.', | |
| # 'If A sits next to B and B sits next to C, then A might not sit next to C.', | |
| ] | |
| input_statement = gr.Dropdown(choices=examples, label='Statement:') | |
| input_model = gr.Textbox(label='Commonsense statement verification model:', value='liujch1998/cd-pi', interactive=False) | |
| output = gr.outputs.Label(num_top_classes=2) | |
| description = '''This is a demo for a commonsense statement verification model. Under development.''' | |
| gr.Interface( | |
| fn=predict, | |
| inputs=[input_statement, input_model], | |
| outputs=output, | |
| title="cd-pi Demo", | |
| description=description, | |
| ).launch() | |