




import unicodedata
from dataclasses import dataclass
from typing import Optional, Union

import numpy as np

from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A     ,	_A							):







	'''simple docstring'''





	if isinstance(_A     ,	_A							):
		snake_case_		    =     np.full((len(_A							), sequence_length, 2)     ,	_A							)
	else:
		snake_case_		    =     np.full((len(_A							), sequence_length)     ,	_A							)

	for i, tensor in enumerate(_A							):
		if padding_side == "right":
			if isinstance(_A     ,	_A							):
				snake_case_		    =     tensor[:sequence_length]
			else:
				snake_case_		    =     tensor[:sequence_length]
		else:
			if isinstance(_A     ,	_A							):
				snake_case_		    =     tensor[:sequence_length]
			else:
				snake_case_		    =     tensor[:sequence_length]

	return out_tensor.tolist()


def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     ord(_A							)
	if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126):
		return True
	snake_case_		    =     unicodedata.category(_A							)
	if cat.startswith("P"							):
		return True
	return False






@dataclass
class 		UpperCAmelCase   (				UpperCAmelCase__			):







						'''simple docstring'''





						lowerCAmelCase_     		=   42
						lowerCAmelCase_     		=   True
						lowerCAmelCase_     		=   None
						lowerCAmelCase_     		=   None
						lowerCAmelCase_     		=   -100
						lowerCAmelCase_     		=   "pt"






						def        snake_case__						(						self							:     Dict       ,	__lowercase							:     Optional[int]						):






							"""simple docstring"""






							import torch

							snake_case_		    =     "label" if "label" in features[0].keys() else "labels"
							snake_case_		    =     [feature[label_name] for feature in features] if label_name in features[0].keys() else None
							snake_case_		    =     self.tokenizer.pad(
							    __lowercase       ,	padding=self.padding       ,	max_length=self.max_length       ,	pad_to_multiple_of=self.pad_to_multiple_of       ,	return_tensors="pt" if labels is None else None       ,	)

							if labels is None:
								return batch

							snake_case_		    =     torch.tensor(batch["entity_ids"]						).shape[1]
							snake_case_		    =     self.tokenizer.padding_side
							if padding_side == "right":
								snake_case_		    =     [
								    list(__lowercase						) + [self.label_pad_token_id] * (sequence_length - len(__lowercase						)) for label in labels
								]
							else:
								snake_case_		    =     [
								    [self.label_pad_token_id] * (sequence_length - len(__lowercase						)) + list(__lowercase						) for label in labels
								]

							snake_case_		    =     [feature["ner_tags"] for feature in features]
							snake_case_		    =     padding_tensor(__lowercase       ,	-1       ,	__lowercase       ,	__lowercase						)
							snake_case_		    =     [feature["original_entity_spans"] for feature in features]
							snake_case_		    =     padding_tensor(__lowercase       ,	(-1, -1)       ,	__lowercase       ,	__lowercase						)
							snake_case_		    =     {k: torch.tensor(__lowercase       ,	dtype=torch.intaa						) for k, v in batch.items()}

							return batch






# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser


def 						lowerCamelCase__    (		):







	'''simple docstring'''





	snake_case_		    =     ArgumentParser("Accelerate CLI tool"     ,	usage="accelerate <command> [<args>]"     ,	allow_abbrev=_A							)
	snake_case_		    =     parser.add_subparsers(help="accelerate command helpers"							)

	# Register commands
	get_config_parser(subparsers=_A							)
	env_command_parser(subparsers=_A							)
	launch_command_parser(subparsers=_A							)
	tpu_command_parser(subparsers=_A							)
	test_command_parser(subparsers=_A							)

	# Let's go
	snake_case_		    =     parser.parse_args()

	if not hasattr(_A     ,	"func"							):
		parser.print_help()
		exit(1							)

	# Run
	args.func(_A							)


if __name__ == "__main__":
		main()
