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fix(ml): handle missing context_length field (#6695)

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* handle missing `context_length` field

* specify list type
This commit is contained in:
Mert
2024-01-27 19:50:50 -05:00
committed by GitHub
parent e2ac019f51
commit 2249f7d42a
3 changed files with 12 additions and 9 deletions
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10
machine-learning/app/models/clip.py
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@@ -144,11 +144,11 @@ class OpenCLIPEncoder(BaseCLIPEncoder):
def _load(self) -> None:
super()._load()
text_cfg: dict[str, Any] = self.model_cfg["text_cfg"]
context_length: int = text_cfg.get("context_length", 77)
pad_token: int = self.tokenizer_cfg["pad_token"]
context_length = self.model_cfg["text_cfg"]["context_length"]
pad_token = self.tokenizer_cfg["pad_token"]
size = self.preprocess_cfg["size"]
size: list[int] | int = self.preprocess_cfg["size"]
self.size = size[0] if isinstance(size, list) else size
self.resampling = get_pil_resampling(self.preprocess_cfg["interpolation"])
@@ -157,7 +157,7 @@ class OpenCLIPEncoder(BaseCLIPEncoder):
log.debug(f"Loading tokenizer for CLIP model '{self.model_name}'")
self.tokenizer: Tokenizer = Tokenizer.from_file(self.tokenizer_file_path.as_posix())
pad_id = self.tokenizer.token_to_id(pad_token)
pad_id: int = self.tokenizer.token_to_id(pad_token)
self.tokenizer.enable_padding(length=context_length, pad_token=pad_token, pad_id=pad_id)
self.tokenizer.enable_truncation(max_length=context_length)
log.debug(f"Loaded tokenizer for CLIP model '{self.model_name}'")