
import argparse
import logging

import numpy as np
import torch

from transformers import AutoModelForCausalLM, AutoTokenizer


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''',
    datefmt='''%m/%d/%Y %H:%M:%S''',
    level=logging.INFO,
)
_A							=       logging.getLogger(__name__)




def 					lowerCamelCase__					(    a__	:	List[str]  )		->						Dict:
       np.random.seed(args.seed  )
       torch.manual_seed(args.seed  )
       if args.n_gpu > 0:
              torch.cuda.manual_seed_all(args.seed  )




def 					lowerCamelCase__					(    )		->						Any:
       UpperCamelCase_											=							argparse.ArgumentParser()
       parser.add_argument(
           """--model_name_or_path"""						,   default=a__						,   type=a__						,   required=a__						,   )
       parser.add_argument("""--prompt"""						,   type=a__						,   default=""""""  )
       parser.add_argument("""--length"""						,   type=a__						,   default=20  )
       parser.add_argument("""--stop_token"""						,   type=a__						,   default=a__						,   help="""Token at which text generation is stopped"""  )
       parser.add_argument(
           """--temperature"""						,   type=a__						,   default=1.0						,   help="""temperature of 1.0 has no effect, lower tend toward greedy sampling"""						,   )
       parser.add_argument(
           """--repetition_penalty"""						,   type=a__						,   default=1.0						,   help="""primarily useful for CTRL model; in that case, use 1.2"""  )
       parser.add_argument("""--k"""						,   type=a__						,   default=0  )
       parser.add_argument("""--penalty_alpha"""						,   type=a__						,   default=0.0  )
       parser.add_argument("""--p"""						,   type=a__						,   default=0.9  )

       parser.add_argument("""--prefix"""						,   type=a__						,   default=""""""						,   help="""Text added prior to input."""  )
       parser.add_argument("""--padding_text"""						,   type=a__						,   default=""""""						,   help="""Deprecated, the use of `--prefix` is preferred."""  )
       parser.add_argument("""--xlm_language"""						,   type=a__						,   default=""""""						,   help="""Optional language when used with the XLM model."""  )

       parser.add_argument("""--seed"""						,   type=a__						,   default=42						,   help="""random seed for initialization"""  )
       parser.add_argument("""--no_cuda"""						,   action="""store_true"""						,   help="""Avoid using CUDA when available"""  )
       parser.add_argument(
           """--fp16"""						,   action="""store_true"""						,   help="""Whether to use 16-bit (mixed) precision (through NVIDIA apex) instead of 32-bit"""						,   )
       UpperCamelCase_											=							parser.parse_args()

       UpperCamelCase_											=							torch.device("""cuda""" if torch.cuda.is_available() and not args.no_cuda else """cpu"""  )
       UpperCamelCase_											=							0 if args.no_cuda else torch.cuda.device_count()

       logger.warning(f'''device: {args.device}, n_gpu: {args.n_gpu}, 16-bits training: {args.fpaa}'''  )

       set_seed(a__  )

       # Initialize the model and tokenizer
       UpperCamelCase_											=							AutoTokenizer.from_pretrained(args.model_name_or_path  )
       UpperCamelCase_											=							AutoModelForCausalLM.from_pretrained(args.model_name_or_path  )

       # tokenizer = GPT2Tokenizer.from_pretrained(args.model_name_or_path)
       # model = OPTForCausalLM.from_pretrained(args.model_name_or_path)
       model.to(args.device  )

       if args.fpaa:
              model.half()

       logger.info(a__  )
       UpperCamelCase_											=							args.prompt if args.prompt else input("""Model prompt >>> """  )

       UpperCamelCase_											=							tokenizer(a__						,   return_tensors="""pt"""						,   add_special_tokens=a__  )
       UpperCamelCase_											=							{key: value.to(args.device  ) for key, value in inputs.items()}

       UpperCamelCase_											=							model.generate(
           **a__						,   max_length=args.length + len(inputs["""input_ids"""][0]  )						,   penalty_alpha=args.penalty_alpha						,   top_k=args.k						,   )

       UpperCamelCase_											=							[]
       for generated_sequence_idx, generated_sequence in enumerate(a__  ):
              print(f'''=== GENERATED SEQUENCE {generated_sequence_idx + 1} ==='''  )
              UpperCamelCase_											=							generated_sequence.tolist()

              # Decode text
              UpperCamelCase_											=							tokenizer.decode(a__						,   clean_up_tokenization_spaces=a__						,   add_special_tokens=a__  )

              # Remove all text after the stop token
              UpperCamelCase_											=							text[: text.find(args.stop_token  ) if args.stop_token else None]

              # Add the prompt at the beginning of the sequence. Remove the excess text that was used for pre-processing
              UpperCamelCase_											=							(
                  prompt_text + text[len(tokenizer.decode(inputs["""input_ids"""][0]						,   clean_up_tokenization_spaces=a__  )  ) :]
              )

              generated_sequences.append(a__  )
              print(a__  )

       return generated_sequences


if __name__ == "__main__":
      main()





import argparse
import os


_A							=       {
    '''pytorch''': {
        '''1.13''': {
            '''torch''': '''1.13.1''',
            '''torchvision''': '''0.14.1''',
            '''torchaudio''': '''0.13.1''',
            '''python''': 3.9,
            '''cuda''': '''cu116''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu116'''
            ),
            '''base_image''': '''nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.12''': {
            '''torch''': '''1.12.1''',
            '''torchvision''': '''0.13.1''',
            '''torchaudio''': '''0.12.1''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.11''': {
            '''torch''': '''1.11.0''',
            '''torchvision''': '''0.12.0''',
            '''torchaudio''': '''0.11.0''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''1.10''': {
            '''torch''': '''1.10.2''',
            '''torchvision''': '''0.11.3''',
            '''torchaudio''': '''0.10.2''',
            '''python''': 3.9,
            '''cuda''': '''cu113''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu113'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        '''1.9''': {
            '''torch''': '''1.9.1''',
            '''torchvision''': '''0.10.1''',
            '''torchaudio''': '''0.9.1''',
            '''python''': 3.9,
            '''cuda''': '''cu111''',
            '''install''': (
                '''python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1'''
                ''' --extra-index-url https://download.pytorch.org/whl/cu111'''
            ),
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
    },
    '''tensorflow''': {
        '''2.11''': {
            '''tensorflow''': '''2.11.1''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.11.1''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.10''': {
            '''tensorflow''': '''2.10.1''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.10.1''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.9''': {
            '''tensorflow''': '''2.9.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.9.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.8''': {
            '''tensorflow''': '''2.8.2''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.8.2''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.7''': {
            '''tensorflow''': '''2.7.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.7.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.6''': {
            '''tensorflow''': '''2.6.5''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.6.5''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
        '''2.5''': {
            '''tensorflow''': '''2.5.3''',
            '''install''': '''python3 -m pip install --no-cache-dir -U tensorflow==2.5.3''',
            '''base_image''': '''nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04''',
        },
    },
}


if __name__ == "__main__":
      _A							=       argparse.ArgumentParser('''Choose the framework and version to install''')
      parser.add_argument(
          '''--framework''', help='''The framework to install. Should be `torch` or `tensorflow`''', type=str, required=True
      )
      parser.add_argument('''--version''', help='''The version of the framework to install.''', type=str, required=True)
      _A							=       parser.parse_args()

      _A							=       past_versions_testing[args.framework][args.version]

      os.system(F'''echo "export INSTALL_CMD=\'{info['install']}\'" >> ~/.profile''')
      print(F'''echo "export INSTALL_CMD=\'{info['install']}\'" >> ~/.profile''')

      _A							=       ''''''
      if args.framework == "pytorch":
            _A							=       info['''cuda''']
      os.system(F'''echo \"export CUDA=\'{cuda}\'\" >> ~/.profile''')
      print(F'''echo \"export CUDA=\'{cuda}\'\" >> ~/.profile''')



