| import json |
|
|
| from torch import nn |
| from transformers import BertModel |
|
|
| with open("config.json") as json_file: |
| config = json.load(json_file) |
|
|
|
|
| class SentimentClassifier(nn.Module): |
| def __init__(self, n_classes): |
| super(SentimentClassifier, self).__init__() |
| self.bert = BertModel.from_pretrained(config["BERT_MODEL"]) |
| self.drop = nn.Dropout(p=0.3) |
| self.out = nn.Linear(self.bert.config.hidden_size, n_classes) |
|
|
| def forward(self, input_ids, attention_mask): |
| _, pooled_output = self.bert(input_ids=input_ids, attention_mask=attention_mask, return_dict=False) |
| output = self.drop(pooled_output) |
| return self.out(output) |
|
|
