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Added support for biomedical datasets with multiple entity types #2080

Added support for biomedical datasets with multiple entity types

Added support for biomedical datasets with multiple entity types #2080

Triggered via pull request January 26, 2024 14:36
Status Failure
Total duration 21m 26s
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10 errors and 1 warning
test: flair/__init__.py#L1
mypy-status mypy exited with status 1.
test: flair/data.py#L1
flair/data.py 1730: error: Argument 1 to "len" has incompatible type "Dataset[Any]"; expected "Sized" [arg-type]
test: flair/data.py#L1
Black format check --- /home/runner/work/flair/flair/flair/data.py 2024-01-26 14:36:36.326452+00:00 +++ /home/runner/work/flair/flair/flair/data.py 2024-01-26 14:38:48.068685+00:00 @@ -985,16 +985,14 @@ def get_span(self, start: int, stop: int): span_slice = slice(start, stop) return self[span_slice] @typing.overload - def __getitem__(self, idx: int) -> Token: - ... + def __getitem__(self, idx: int) -> Token: ... @typing.overload - def __getitem__(self, s: slice) -> Span: - ... + def __getitem__(self, s: slice) -> Span: ... def __getitem__(self, subscript): if isinstance(subscript, slice): return Span(self.tokens[subscript]) else:
test: flair/file_utils.py#L1
Black format check --- /home/runner/work/flair/flair/flair/file_utils.py 2024-01-26 14:36:36.330452+00:00 +++ /home/runner/work/flair/flair/flair/file_utils.py 2024-01-26 14:38:48.555897+00:00 @@ -1,6 +1,7 @@ """Utilities for working with the local dataset cache. Copied from AllenNLP.""" + import base64 import functools import io import logging import mmap
test: flair/models/entity_linker_model.py#L1
Black format check --- /home/runner/work/flair/flair/flair/models/entity_linker_model.py 2024-01-26 14:36:36.330452+00:00 +++ /home/runner/work/flair/flair/flair/models/entity_linker_model.py 2024-01-26 14:38:57.948881+00:00 @@ -106,13 +106,13 @@ **classifierargs: The arguments propagated to :meth:`flair.nn.DefaultClassifier.__init__` """ super().__init__( embeddings=embeddings, label_dictionary=label_dictionary, - final_embedding_size=embeddings.embedding_length * 2 - if pooling_operation == "first_last" - else embeddings.embedding_length, + final_embedding_size=( + embeddings.embedding_length * 2 if pooling_operation == "first_last" else embeddings.embedding_length + ), **classifierargs, ) self.pooling_operation = pooling_operation self._label_type = label_type
test: flair/nn/model.py#L1
Black format check --- /home/runner/work/flair/flair/flair/nn/model.py 2024-01-26 14:36:36.330452+00:00 +++ /home/runner/work/flair/flair/flair/nn/model.py 2024-01-26 14:39:03.450959+00:00 @@ -698,13 +698,15 @@ device=flair.device, ) else: return torch.tensor( [ - self.label_dictionary.get_idx_for_item(label[0]) - if len(label) > 0 - else self.label_dictionary.get_idx_for_item("O") + ( + self.label_dictionary.get_idx_for_item(label[0]) + if len(label) > 0 + else self.label_dictionary.get_idx_for_item("O") + ) for label in labels ], dtype=torch.long, device=flair.device, )
test: flair/nn/distance/euclidean.py#L1
Black format check --- /home/runner/work/flair/flair/flair/nn/distance/euclidean.py 2024-01-26 14:36:36.330452+00:00 +++ /home/runner/work/flair/flair/flair/nn/distance/euclidean.py 2024-01-26 14:39:04.602118+00:00 @@ -14,11 +14,10 @@ It was published under MIT License: https://github.com/asappresearch/dynamic-classification/blob/master/LICENSE.md Source: https://github.com/asappresearch/dynamic-classification/blob/55beb5a48406c187674bea40487c011e8fa45aab/distance/euclidean.py """ - import torch from torch import Tensor, nn
test: tests/test_tars.py#L51
test_train_tars[False] OSError: Unable to load weights from pytorch checkpoint file for './cache/transformers/hub/models--sshleifer--tiny-distilroberta-base/snapshots/d305c58110158c865cb6746c62d4511d4148a934/pytorch_model.bin' at './cache/transformers/hub/models--sshleifer--tiny-distilroberta-base/snapshots/d305c58110158c865cb6746c62d4511d4148a934/pytorch_model.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
test: tests/embeddings/test_transformer_word_embeddings.py#L149
TestTransformerWordEmbeddings.test_layoutlm_embeddings[False] OSError: Unable to load weights from pytorch checkpoint file for './cache/transformers/hub/models--microsoft--layoutlm-base-uncased/snapshots/8290fe08a848303616911d513e66ec192840ffbd/pytorch_model.bin' at './cache/transformers/hub/models--microsoft--layoutlm-base-uncased/snapshots/8290fe08a848303616911d513e66ec192840ffbd/pytorch_model.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
test: tests/embeddings/test_transformer_word_embeddings.py#L182
TestTransformerWordEmbeddings.test_layoutlmv3_embeddings[False] OSError: Unable to load weights from pytorch checkpoint file for './cache/transformers/hub/models--microsoft--layoutlmv3-base/snapshots/ba7716c277fb9b49bba6c3c4cad84123b689acf2/pytorch_model.bin' at './cache/transformers/hub/models--microsoft--layoutlmv3-base/snapshots/ba7716c277fb9b49bba6c3c4cad84123b689acf2/pytorch_model.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
test
Node.js 16 actions are deprecated. Please update the following actions to use Node.js 20: actions/checkout@v3, actions/setup-python@v4, actions/cache@v3. For more information see: https://github.blog/changelog/2023-09-22-github-actions-transitioning-from-node-16-to-node-20/.