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ZDisket
26 lines
974 B
Python
26 lines
974 B
Python
# imports
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import json
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import torch
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from moji.sentence_tokenizer import SentenceTokenizer
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from moji.model_def import torchmoji_feature_encoding
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from moji.global_variables import PRETRAINED_PATH, VOCAB_PATH
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class TorchMoji():
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def __init__(self, verbose=False):
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if verbose:
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print(f'Tokenizing using dictionary from {VOCAB_PATH}')
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with open(VOCAB_PATH, 'r') as f:
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vocabulary = json.load(f)
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self.torchmoji_tokenizer = SentenceTokenizer(vocabulary, fixed_length=120)
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if verbose:
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print(f'Loading model from {PRETRAINED_PATH}.')
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self.torchmoji_model = torchmoji_feature_encoding(PRETRAINED_PATH)
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def __call__(self, text):# str[txt_T]
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with torch.no_grad():
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tokenized, _, _ = self.torchmoji_tokenizer.tokenize_sentences([text,])
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embed = self.torchmoji_model(tokenized)
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return torch.from_numpy(embed).unsqueeze(0).float()# [1, 1, embed] |