

"""simple docstring"""




from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


A_				:      Union[str, Any]           =			{
    "susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json",
    "susnato/ernie-m-large_pytorch": "https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json",
}





class  lowerCamelCase    (A__      ):
			lowerCamelCase__ :		int       		=				'ernie_m'
			lowerCamelCase__ :		Dict[str, str]       		=				{"dropout": "classifier_dropout", "num_classes": "num_labels"}

			def __init__(       self					:    List[str]     ,					__UpperCAmelCase					:    int = 2_5_0_0_0_2     ,					__UpperCAmelCase					:    int = 7_6_8     ,					__UpperCAmelCase					:    int = 1_2     ,					__UpperCAmelCase					:    int = 1_2     ,					__UpperCAmelCase					:    int = 3_0_7_2     ,					__UpperCAmelCase					:    str = "gelu"     ,					__UpperCAmelCase					:    float = 0.1     ,					__UpperCAmelCase					:    float = 0.1     ,					__UpperCAmelCase					:    int = 5_1_4     ,					__UpperCAmelCase					:    float = 0.02     ,					__UpperCAmelCase					:    int = 1     ,					__UpperCAmelCase					:    float = 1e-05     ,					__UpperCAmelCase					:    Union[str, Any]=None     ,					__UpperCAmelCase					:    List[Any]=False     ,					__UpperCAmelCase					:    Union[str, Any]=0.0     ,					**__UpperCAmelCase					:    Any     ,					) ->     Optional[Any]:
						super().__init__(pad_token_id=__UpperCAmelCase     ,					**__UpperCAmelCase							)
						SCREAMING_SNAKE_CASE__										=   vocab_size
						SCREAMING_SNAKE_CASE__										=   hidden_size
						SCREAMING_SNAKE_CASE__										=   num_hidden_layers
						SCREAMING_SNAKE_CASE__										=   num_attention_heads
						SCREAMING_SNAKE_CASE__										=   intermediate_size
						SCREAMING_SNAKE_CASE__										=   hidden_act
						SCREAMING_SNAKE_CASE__										=   hidden_dropout_prob
						SCREAMING_SNAKE_CASE__										=   attention_probs_dropout_prob
						SCREAMING_SNAKE_CASE__										=   max_position_embeddings
						SCREAMING_SNAKE_CASE__										=   initializer_range
						SCREAMING_SNAKE_CASE__										=   layer_norm_eps
						SCREAMING_SNAKE_CASE__										=   classifier_dropout
						SCREAMING_SNAKE_CASE__										=   is_decoder
						SCREAMING_SNAKE_CASE__										=   act_dropout





"""simple docstring"""




A_				:      Any           =			"0.21.0"

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
						from .utils import rich


