



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase				:							int								=logging.get_logger(__name__)

UpperCAmelCase				:							Optional[Any]								={
    """nghuyong/ernie-1.0-base-zh""": """https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json""",
    """nghuyong/ernie-2.0-base-en""": """https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json""",
    """nghuyong/ernie-2.0-large-en""": """https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json""",
    """nghuyong/ernie-3.0-base-zh""": """https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-medium-zh""": """https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-mini-zh""": """https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-micro-zh""": """https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-nano-zh""": """https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json""",
    """nghuyong/ernie-gram-zh""": """https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json""",
    """nghuyong/ernie-health-zh""": """https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json""",
}


class  _lowercase				(snake_case__ ):
				'''simple docstring'''







				lowercase__				  =  'ernie'

				def __init__(	self       ,	snake_case__=3_0522       ,	snake_case__=768       ,	snake_case__=12       ,	snake_case__=12       ,	snake_case__=3072       ,	snake_case__="gelu"       ,	snake_case__=0.1       ,	snake_case__=0.1       ,	snake_case__=512       ,	snake_case__=2       ,	snake_case__=3       ,	snake_case__=False       ,	snake_case__=0.02       ,	snake_case__=1e-12       ,	snake_case__=0       ,	snake_case__="absolute"       ,	snake_case__=True       ,	snake_case__=None       ,	**snake_case__       ,	):

									'''simple docstring'''


									super().__init__(pad_token_id=snake_case__       ,	**snake_case__      )

									UpperCamelCase_											=				vocab_size
									UpperCamelCase_											=				hidden_size
									UpperCamelCase_											=				num_hidden_layers
									UpperCamelCase_											=				num_attention_heads
									UpperCamelCase_											=				hidden_act
									UpperCamelCase_											=				intermediate_size
									UpperCamelCase_											=				hidden_dropout_prob
									UpperCamelCase_											=				attention_probs_dropout_prob
									UpperCamelCase_											=				max_position_embeddings
									UpperCamelCase_											=				type_vocab_size
									UpperCamelCase_											=				task_type_vocab_size
									UpperCamelCase_											=				use_task_id
									UpperCamelCase_											=				initializer_range
									UpperCamelCase_											=				layer_norm_eps
									UpperCamelCase_											=				position_embedding_type
									UpperCamelCase_											=				use_cache
									UpperCamelCase_											=				classifier_dropout




class  _lowercase				(snake_case__ ):
				'''simple docstring'''







				@property
				def  _lowerCamelCase   (	self      ):

									'''simple docstring'''


									if self.task == "multiple-choice":
														UpperCamelCase_											=				{0: 'batch', 1: 'choice', 2: 'sequence'}
									else:
														UpperCamelCase_											=				{0: 'batch', 1: 'sequence'}
									return OrderedDict(
									    [
									        ("input_ids", dynamic_axis),
									        ("attention_mask", dynamic_axis),
									        ("token_type_ids", dynamic_axis),
									        ("task_type_ids", dynamic_axis),
									    ]      )







from __future__ import annotations



def 				_lowerCAmelCase      (_lowerCAmelCase):
					UpperCamelCase_											=				{1}
					UpperCamelCase_											=				[1]
					for _ in range(2				,		depth + 1):
										UpperCamelCase_											=				[*previous_coefficients, 0]
										UpperCamelCase_											=				[0, *previous_coefficients]
										UpperCamelCase_											=				[]
										for x, y in zip(_lowerCAmelCase				,		_lowerCAmelCase):
															coefficients.add(x + y)
															previous_coefficients.append(x + y)
					return coefficients



def 				_lowerCAmelCase      (_lowerCAmelCase):
					UpperCamelCase_											=				set()
					for number in unique_coefficients:
										UpperCamelCase_											=				2
										UpperCamelCase_											=				number
										while divisor**2 <= copy_number:
															UpperCamelCase_											=				0
															while copy_number % divisor == 0:
																				copy_number //= divisor
																				multiplicity += 1
															if multiplicity >= 2:
																				non_squarefrees.add(_lowerCAmelCase)
																				break
															divisor += 1

					return unique_coefficients.difference(_lowerCAmelCase)



def 				_lowerCAmelCase      (_lowerCAmelCase = 51):
					UpperCamelCase_											=				get_pascal_triangle_unique_coefficients(_lowerCAmelCase)
					UpperCamelCase_											=				get_squarefrees(_lowerCAmelCase)
					return sum(_lowerCAmelCase)


if __name__ == "__main__":
	print(F"{solution() = }")
