Unify the style of type annotations#64
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| ): | ||
| input_tensor: torch.Tensor, | ||
| output_tensor: torch.Tensor, | ||
| comm: hcclComm_t, |
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Can the hcclComm_t pass the syntax check?
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Yes, because hcclComm_t equal to ctypes.c_void_p.
| ) | ||
| self._client = KVClient(host=host, port=port) | ||
| self.local_tensors = [] | ||
| self.local_tensors: List["torch.Tensor"] = [] |
| ).remote() | ||
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| backend_info: dict = ray.get( | ||
| backend_info: Dict[str, Any] = ray.get( |
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Whether local variables should be annotated or not, establish a unified standard.
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I think we need to annotate local vars while using some uncommon types
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and uncommon returned values
| meta_bytes = pickle.dumps(meta_tuple, protocol=pickle.HIGHEST_PROTOCOL) | ||
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| bufs: list[bytestr] = [meta_bytes, raw_data] | ||
| bufs = [meta_bytes, raw_data] |
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Whether local variables should be annotated or not, establish a unified standard.
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consider introducing tools like |
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| # don't want a baseline the size of the codebase) | ||
| --arg-type-hints-in-docstring=False, | ||
| --skip-checking-raises=True, | ||
| --check-return-types=False, |
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looks like return/arg type check are not enabled?
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I referred to RAY's set about pydoclint there. Should we enable it?
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get it. now only arg name is checked. types are not cheked. let's follow the ray setting :)
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Description
pydoclintto .pre-commit-config.yaml