





"""simple docstring"""






# Copyright 2023 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 typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A			      =	{'''configuration_mra''': ['''MRA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MraConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A			      =	[
		    '''MRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MraForMaskedLM''',
		    '''MraForMultipleChoice''',
		    '''MraForQuestionAnswering''',
		    '''MraForSequenceClassification''',
		    '''MraForTokenClassification''',
		    '''MraLayer''',
		    '''MraModel''',
		    '''MraPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mra import (
				    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MraForMaskedLM,
				    MraForMultipleChoice,
				    MraForQuestionAnswering,
				    MraForSequenceClassification,
				    MraForTokenClassification,
				    MraLayer,
				    MraModel,
				    MraPreTrainedModel,
				)
else:
		import sys

		A			      =	_LazyModule(__name__, globals()['''__file__'''], _import_structure)






from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__           =			logging.get_logger(__name__)

UpperCamelCase__           =			{
    "tanreinama/GPTSAN-2.8B-spout_is_uniform": (
        "https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json"
    ),
}

class 							__SCREAMING_SNAKE_CASE       (  _a							):
							snake_case  :   Optional[Any]      =							"""gptsan-japanese"""
							snake_case  :   Any      =							[
							    """past_key_values""",
							]
							snake_case  :   str      =							{
							    """hidden_size""": """d_model""",
							    """num_attention_heads""": """num_heads""",
							    """num_hidden_layers""": """num_layers""",
							}






							def __init__(    self	,			__lowerCAmelCase=36000	,			__lowerCAmelCase=1280	,			__lowerCAmelCase=1024	,			__lowerCAmelCase=8192	,			__lowerCAmelCase=4096	,			__lowerCAmelCase=128	,			__lowerCAmelCase=10	,			__lowerCAmelCase=0	,			__lowerCAmelCase=16	,			__lowerCAmelCase=16	,			__lowerCAmelCase=128	,			__lowerCAmelCase=0.0	,			__lowerCAmelCase=1E-5	,			__lowerCAmelCase=False	,			__lowerCAmelCase=0.0	,			__lowerCAmelCase="float32"	,			__lowerCAmelCase=False	,			__lowerCAmelCase=False	,			__lowerCAmelCase=False	,			__lowerCAmelCase=0.002	,			__lowerCAmelCase=False	,			__lowerCAmelCase=True	,			__lowerCAmelCase=35998	,			__lowerCAmelCase=35995	,			__lowerCAmelCase=35999	,			**__lowerCAmelCase	,			):
														UpperCamelCase__					  =      vocab_size
														UpperCamelCase__					  =      max_position_embeddings
														UpperCamelCase__					  =      d_model
														UpperCamelCase__					  =      d_ff
														UpperCamelCase__					  =      d_ext
														UpperCamelCase__					  =      d_spout
														UpperCamelCase__					  =      num_switch_layers
														UpperCamelCase__					  =      num_ext_layers
														UpperCamelCase__					  =      num_switch_layers + num_ext_layers
														UpperCamelCase__					  =      num_heads
														UpperCamelCase__					  =      num_experts
														UpperCamelCase__					  =      expert_capacity
														UpperCamelCase__					  =      dropout_rate
														UpperCamelCase__					  =      layer_norm_epsilon
														UpperCamelCase__					  =      router_bias
														UpperCamelCase__					  =      router_jitter_noise
														UpperCamelCase__					  =      router_dtype
														UpperCamelCase__					  =      router_ignore_padding_tokens
														UpperCamelCase__					  =      output_hidden_states
														UpperCamelCase__					  =      output_attentions
														UpperCamelCase__					  =      initializer_factor
														UpperCamelCase__					  =      output_router_logits
														UpperCamelCase__					  =      use_cache

														super().__init__(
														    separator_token_id=__lowerCAmelCase	,			pad_token_id=__lowerCAmelCase	,			eos_token_id=__lowerCAmelCase	,			**__lowerCAmelCase	,			)




