




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__         =      {
    """configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__         =      [
					    """MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MegatronBertForCausalLM""",
					    """MegatronBertForMaskedLM""",
					    """MegatronBertForMultipleChoice""",
					    """MegatronBertForNextSentencePrediction""",
					    """MegatronBertForPreTraining""",
					    """MegatronBertForQuestionAnswering""",
					    """MegatronBertForSequenceClassification""",
					    """MegatronBertForTokenClassification""",
					    """MegatronBertModel""",
					    """MegatronBertPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_megatron_bert import (
										    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MegatronBertForCausalLM,
										    MegatronBertForMaskedLM,
										    MegatronBertForMultipleChoice,
										    MegatronBertForNextSentencePrediction,
										    MegatronBertForPreTraining,
										    MegatronBertForQuestionAnswering,
										    MegatronBertForSequenceClassification,
										    MegatronBertForTokenClassification,
										    MegatronBertModel,
										    MegatronBertPreTrainedModel,
										)

else:
					import sys

					UpperCamelCase__         =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










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


UpperCamelCase__         =      logging.get_logger(__name__)

UpperCamelCase__         =      {
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class       a__   ( snake_case__				):
						_a							:   Dict =   """mgp-str"""






						def __init__(       self		,      _A=[3_2, 1_2_8]		,      _A=4		,      _A=3		,      _A=2_7		,      _A=3_8		,      _A=5_0_2_5_7		,      _A=3_0_5_2_2		,      _A=7_6_8		,      _A=1_2		,      _A=1_2		,      _A=4.0		,      _A=True		,      _A=False		,      _A=1E-5		,      _A=0.0		,      _A=0.0		,      _A=0.0		,      _A=False		,      _A=0.02		,      **_A		,      ):




											"""simple docstring"""



											super().__init__(**_A      )

											__lowerCAmelCase           =	image_size
											__lowerCAmelCase           =	patch_size
											__lowerCAmelCase           =	num_channels
											__lowerCAmelCase           =	max_token_length
											__lowerCAmelCase           =	num_character_labels
											__lowerCAmelCase           =	num_bpe_labels
											__lowerCAmelCase           =	num_wordpiece_labels
											__lowerCAmelCase           =	hidden_size
											__lowerCAmelCase           =	num_hidden_layers
											__lowerCAmelCase           =	num_attention_heads
											__lowerCAmelCase           =	mlp_ratio
											__lowerCAmelCase           =	distilled
											__lowerCAmelCase           =	layer_norm_eps
											__lowerCAmelCase           =	drop_rate
											__lowerCAmelCase           =	qkv_bias
											__lowerCAmelCase           =	attn_drop_rate
											__lowerCAmelCase           =	drop_path_rate
											__lowerCAmelCase           =	output_aa_attentions
											__lowerCAmelCase           =	initializer_range




