





"""simple docstring"""




from typing import TYPE_CHECKING

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


lowerCamelCase_     :						Tuple						=					{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_     :						str						=					['OwlViTFeatureExtractor']
   lowerCamelCase_     :						Union[str, Any]						=					['OwlViTImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_     :						Any						=					[
       'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'OwlViTModel',
       'OwlViTPreTrainedModel',
       'OwlViTTextModel',
       'OwlViTVisionModel',
       'OwlViTForObjectDetection',
   ]

if TYPE_CHECKING:
   from .configuration_owlvit import (
       OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       OwlViTConfig,
       OwlViTOnnxConfig,
       OwlViTTextConfig,
       OwlViTVisionConfig,
   )
   from .processing_owlvit import OwlViTProcessor

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_owlvit import OwlViTFeatureExtractor
      from .image_processing_owlvit import OwlViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_owlvit import (
          OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          OwlViTForObjectDetection,
          OwlViTModel,
          OwlViTPreTrainedModel,
          OwlViTTextModel,
          OwlViTVisionModel,
      )

else:
   import sys

   lowerCamelCase_     :						Tuple						=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






"""simple docstring"""




from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
lowerCamelCase_     :						Any						=					HfArgumentParser(InitializationArguments)
lowerCamelCase_     :						Union[str, Any]						=					parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
lowerCamelCase_     :						List[Any]						=					AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
lowerCamelCase_     :						Tuple						=					{
    '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)
lowerCamelCase_     :						int						=					AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
lowerCamelCase_     :						Any						=					AutoModelForCausalLM.from_config(config)

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