




from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase__            =     logging.get_logger(__name__)

UpperCamelCase__            =     {
    """squeezebert/squeezebert-uncased""": (
        """https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"""
    ),
    """squeezebert/squeezebert-mnli""": """https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json""",
    """squeezebert/squeezebert-mnli-headless""": (
        """https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"""
    ),
}
class      a__       (   snake_case__ ):
						_a				:       int   =       SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
						_a				:       List[str]   =       """squeezebert"""






						def __init__(  self						,     _A=3_0_5_2_2						,     _A=7_6_8						,     _A=1_2						,     _A=1_2						,     _A=3_0_7_2						,     _A="gelu"						,     _A=0.1						,     _A=0.1						,     _A=5_1_2						,     _A=2						,     _A=0.02						,     _A=1E-1_2						,     _A=0						,     _A=7_6_8						,     _A=4						,     _A=4						,     _A=4						,     _A=1						,     _A=4						,     _A=4						,     **_A						,     ):




											"""simple docstring"""



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

											__lowerCAmelCase							  =			vocab_size
											__lowerCAmelCase							  =			hidden_size
											__lowerCAmelCase							  =			num_hidden_layers
											__lowerCAmelCase							  =			num_attention_heads
											__lowerCAmelCase							  =			hidden_act
											__lowerCAmelCase							  =			intermediate_size
											__lowerCAmelCase							  =			hidden_dropout_prob
											__lowerCAmelCase							  =			attention_probs_dropout_prob
											__lowerCAmelCase							  =			max_position_embeddings
											__lowerCAmelCase							  =			type_vocab_size
											__lowerCAmelCase							  =			initializer_range
											__lowerCAmelCase							  =			layer_norm_eps
											__lowerCAmelCase							  =			embedding_size
											__lowerCAmelCase							  =			q_groups
											__lowerCAmelCase							  =			k_groups
											__lowerCAmelCase							  =			v_groups
											__lowerCAmelCase							  =			post_attention_groups
											__lowerCAmelCase							  =			intermediate_groups
											__lowerCAmelCase							  =			output_groups






class      a__       (   snake_case__ ):






						@property
						def 							__SCREAMING_SNAKE_CASE(  self     ):




											"""simple docstring"""



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










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__            =     {
    """configuration_marian""": ["""MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarianConfig""", """MarianOnnxConfig"""],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""MarianTokenizer"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     [
					    """MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MarianForCausalLM""",
					    """MarianModel""",
					    """MarianMTModel""",
					    """MarianPreTrainedModel""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""TFMarianModel""", """TFMarianMTModel""", """TFMarianPreTrainedModel"""]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""FlaxMarianModel""", """FlaxMarianMTModel""", """FlaxMarianPreTrainedModel"""]

if TYPE_CHECKING:
					from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_marian import MarianTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_marian import (
										    MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MarianForCausalLM,
										    MarianModel,
										    MarianMTModel,
										    MarianPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
					import sys

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




