[Styling] stylify using ruff (#27144)
* try to stylify using ruff * might need to remove these changes? * use ruf format andruff check * use isinstance instead of type comparision * use # fmt: skip * use # fmt: skip * nits * soem styling changes * update ci job * nits isinstance * more files update * nits * more nits * small nits * check and format * revert wrong changes * actually use formatter instead of checker * nits * well docbuilder is overwriting this commit * revert notebook changes * try to nuke docbuilder * style * fix feature exrtaction test * remve `indent-width = 4` * fixup * more nits * update the ruff version that we use * style * nuke docbuilder styling * leve the print for detected changes * nits * Remove file I/O Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com> * style * nits * revert notebook changes * Add # fmt skip when possible * Add # fmt skip when possible * Fix * More ` # fmt: skip` usage * More ` # fmt: skip` usage * More ` # fmt: skip` usage * NIts * more fixes * fix tapas * Another way to skip * Recommended way * Fix two more fiels * Remove asynch Remove asynch --------- Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com>
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@@ -362,11 +362,15 @@ class TokenizerTesterMixin:
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model_main_input_name: str = "input_ids",
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):
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for i_r in input_r.values():
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self.assertEqual(len(i_r), 2), self.assertEqual(len(i_r[0]), max_length), self.assertEqual(
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len(i_r[1]), max_length
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(
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self.assertEqual(len(i_r), 2),
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self.assertEqual(len(i_r[0]), max_length),
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self.assertEqual(len(i_r[1]), max_length),
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)
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self.assertEqual(len(i_r), 2), self.assertEqual(len(i_r[0]), max_length), self.assertEqual(
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len(i_r[1]), max_length
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(
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self.assertEqual(len(i_r), 2),
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self.assertEqual(len(i_r[0]), max_length),
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self.assertEqual(len(i_r[1]), max_length),
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)
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for i_r, i_p in zip(input_r[model_main_input_name], input_p[model_main_input_name]):
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@@ -1565,7 +1569,9 @@ class TokenizerTesterMixin:
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# Testing single inputs
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encoded_sequence = tokenizer.encode(sequence_0, add_special_tokens=False)
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encoded_sequence_dict = tokenizer.encode_plus(
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sequence_0, add_special_tokens=True, return_special_tokens_mask=True # , add_prefix_space=False
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sequence_0,
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add_special_tokens=True,
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return_special_tokens_mask=True, # , add_prefix_space=False
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)
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encoded_sequence_w_special = encoded_sequence_dict["input_ids"]
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special_tokens_mask = encoded_sequence_dict["special_tokens_mask"]
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