

'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging


_UpperCAmelCase  :		List[str]  =		logging.get_logger(__name__)

_UpperCAmelCase  :		int  =		{
    '''speechbrain/m-ctc-t-large''': '''https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json''',
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}

class 						__magic_name__   (							__SCREAMING_SNAKE_CASE ):
 UpperCamelCase__     =       'mctct'







 def __init__(       self  , snake_case_=80_65  , snake_case_=15_36  , snake_case_=36  , snake_case_=61_44  , snake_case_=4  , snake_case_=3_84  , snake_case_=9_20  , snake_case_=1E-5  , snake_case_=0.3  , snake_case_="relu"  , snake_case_=0.02  , snake_case_=0.3  , snake_case_=0.3  , snake_case_=1  , snake_case_=0  , snake_case_=2  , snake_case_=1  , snake_case_=0.3  , snake_case_=1  , snake_case_=(7,)  , snake_case_=(3,)  , snake_case_=80  , snake_case_=1  , snake_case_=None  , snake_case_="sum"  , snake_case_=False  , **snake_case_  , ):
   super().__init__(**snake_case_  , pad_token_id=snake_case_  , bos_token_id=snake_case_  , eos_token_id=snake_case_   )
   lowercase									=vocab_size
   lowercase									=hidden_size
   lowercase									=num_hidden_layers
   lowercase									=intermediate_size
   lowercase									=num_attention_heads
   lowercase									=attention_head_dim
   lowercase									=max_position_embeddings
   lowercase									=layer_norm_eps
   lowercase									=layerdrop
   lowercase									=hidden_act
   lowercase									=initializer_range
   lowercase									=hidden_dropout_prob
   lowercase									=attention_probs_dropout_prob
   lowercase									=pad_token_id
   lowercase									=bos_token_id
   lowercase									=eos_token_id
   lowercase									=conv_glu_dim
   lowercase									=conv_dropout
   lowercase									=num_conv_layers
   lowercase									=input_feat_per_channel
   lowercase									=input_channels
   lowercase									=conv_channels
   lowercase									=ctc_loss_reduction
   lowercase									=ctc_zero_infinity

   # prevents config testing fail with exporting to json
   lowercase									=list(snake_case_   )
   lowercase									=list(snake_case_   )

   if len(self.conv_kernel   ) != self.num_conv_layers:
     raise ValueError(
         '''Configuration for convolutional module is incorrect. '''
         '''It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '''
         f'but is `len(config.conv_kernel) = {len(self.conv_kernel   )}`, '
         f'`config.num_conv_layers = {self.num_conv_layers}`.'   )



from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
lowercase_   							=  HfArgumentParser(InitializationArguments)
lowercase_   							=  parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
lowercase_   							=  AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
lowercase_   							=  {
    'vocab_size': len(tokenizer),
    'scale_attn_by_inverse_layer_idx': True,
    'reorder_and_upcast_attn': True,
}

# Load model config (GPT-2 large in this case)
lowercase_   							=  AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
lowercase_   							=  AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)


