feat: support custom onnx file and update model signatures #761
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## main #761 +/- ##
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+ Coverage 78.31% 79.03% +0.71%
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Files 17 17
Lines 1213 1240 +27
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+ Hits 950 980 +30
+ Misses 263 260 -3
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numb3r3
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server/clip_server/model/clip.py
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| @@ -335,6 +336,7 @@ def tokenize( | |||
| eot_token = _tokenizer.encoder['<|endoftext|>'] | |||
| all_tokens = [[sot_token] + _tokenizer.encode(text) + [eot_token] for text in texts] | |||
| result = torch.zeros(len(all_tokens), context_length, dtype=torch.long) | |||
| attention_masks = torch.zeros(len(all_tokens), context_length, dtype=torch.long) | |||
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I think we need to support variable input length here.
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This PR allows the user to set filepath for pretrained custom onnx model and unify the signature of tensorrt, onnx, and huggingface clip runtime.
We also add md5 verification to make sure users download the latest and correct models.
Since tensorrt models are extremely picky for many dependencies, we no longer support tensorrt model hosting, which means that it will first download the latest onnx model and convert to trt during runtime and save for it later use.
TODO: