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Allow BatchEncoding to be initialized empty. (#4316)

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* Allow BatchEncoding to be initialized empty.

This is required by recent changes introduced in TF 2.2.

* Attempt to unpin Tensorflow to 2.2 with the previous commit.
This commit is contained in:
Funtowicz Morgan
2020-05-12 19:02:46 +00:00
committed by GitHub
parent 0a97f6312a
commit 7d7fe4997f
2 changed files with 7 additions and 3 deletions
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4
setup.py
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@@ -67,8 +67,8 @@ extras = {}
extras["mecab"] = ["mecab-python3"] extras["mecab"] = ["mecab-python3"]
extras["sklearn"] = ["scikit-learn"] extras["sklearn"] = ["scikit-learn"]
extras["tf"] = ["tensorflow <= 2.1"] extras["tf"] = ["tensorflow"]
extras["tf-cpu"] = ["tensorflow-cpu <= 2.1"] extras["tf-cpu"] = ["tensorflow-cpu"]
extras["torch"] = ["torch"] extras["torch"] = ["torch"]
extras["serving"] = ["pydantic", "uvicorn", "fastapi", "starlette"] extras["serving"] = ["pydantic", "uvicorn", "fastapi", "starlette"]

6
src/transformers/tokenization_utils.py
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@@ -173,7 +173,11 @@ class BatchEncoding(UserDict):
""" """
def __init__(self, data: Dict[str, Any], encoding: Optional[Union[EncodingFast, Sequence[EncodingFast]]] = None): def __init__(
self,
data: Optional[Dict[str, Any]] = None,
encoding: Optional[Union[EncodingFast, Sequence[EncodingFast]]] = None,
):
super().__init__(data) super().__init__(data)
if isinstance(encoding, EncodingFast): if isinstance(encoding, EncodingFast):