
"""simple docstring"""

import argparse

import numpy as np
import torch

from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging


logging.set_verbosity_info()
SCREAMING_SNAKE_CASE_    					=						logging.get_logger('''transformers.models.speecht5''')




def     lowercase__						(					lowerCAmelCase				:					Any ,				lowerCAmelCase				:					int ,				lowerCAmelCase				:					Union[str, Any] ) ->      int:






    """simple docstring"""




    hf_model.apply_weight_norm()

    UpperCAmelCase									=					checkpoint['input_conv.weight_g']
    UpperCAmelCase									=					checkpoint['input_conv.weight_v']
    UpperCAmelCase									=					checkpoint['input_conv.bias']

    for i in range(len(config.upsample_rates ) ):
        UpperCAmelCase									=					checkpoint[F"upsamples.{i}.1.weight_g"]
        UpperCAmelCase									=					checkpoint[F"upsamples.{i}.1.weight_v"]
        UpperCAmelCase									=					checkpoint[F"upsamples.{i}.1.bias"]

    for i in range(len(config.upsample_rates ) * len(config.resblock_kernel_sizes ) ):
        for j in range(len(config.resblock_dilation_sizes ) ):
            UpperCAmelCase									=					checkpoint[F"blocks.{i}.convs1.{j}.1.weight_g"]
            UpperCAmelCase									=					checkpoint[F"blocks.{i}.convs1.{j}.1.weight_v"]
            UpperCAmelCase									=					checkpoint[F"blocks.{i}.convs1.{j}.1.bias"]

            UpperCAmelCase									=					checkpoint[F"blocks.{i}.convs2.{j}.1.weight_g"]
            UpperCAmelCase									=					checkpoint[F"blocks.{i}.convs2.{j}.1.weight_v"]
            UpperCAmelCase									=					checkpoint[F"blocks.{i}.convs2.{j}.1.bias"]

    UpperCAmelCase									=					checkpoint['output_conv.1.weight_g']
    UpperCAmelCase									=					checkpoint['output_conv.1.weight_v']
    UpperCAmelCase									=					checkpoint['output_conv.1.bias']

    hf_model.remove_weight_norm()




@torch.no_grad()
def     lowercase__						(					lowerCAmelCase				:					List[Any] ,				lowerCAmelCase				:					List[Any] ,				lowerCAmelCase				:					Dict ,				lowerCAmelCase				:					Optional[int]=None ,				lowerCAmelCase				:					Optional[int]=None ,				) ->      Optional[Any]:






    """simple docstring"""




    if config_path is not None:
        UpperCAmelCase									=					SpeechTaHifiGanConfig.from_pretrained(lowerCAmelCase )
    else:
        UpperCAmelCase									=					SpeechTaHifiGanConfig()

    UpperCAmelCase									=					SpeechTaHifiGan(lowerCAmelCase )

    UpperCAmelCase									=					torch.load(lowerCAmelCase )
    load_weights(orig_checkpoint['model']['generator'] ,				lowerCAmelCase ,				lowerCAmelCase )

    UpperCAmelCase									=					np.load(lowerCAmelCase )
    UpperCAmelCase									=					stats[0].reshape(-1 )
    UpperCAmelCase									=					stats[1].reshape(-1 )
    UpperCAmelCase									=					torch.from_numpy(lowerCAmelCase ).float()
    UpperCAmelCase									=					torch.from_numpy(lowerCAmelCase ).float()

    model.save_pretrained(lowerCAmelCase )

    if repo_id:
        print('Pushing to the hub...' )
        model.push_to_hub(lowerCAmelCase )


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE_    					=						argparse.ArgumentParser()
   parser.add_argument('''--checkpoint_path''', required=True, default=None, type=str, help='''Path to original checkpoint''')
   parser.add_argument('''--stats_path''', required=True, default=None, type=str, help='''Path to stats.npy file''')
   parser.add_argument('''--config_path''', default=None, type=str, help='''Path to hf config.json of model to convert''')
   parser.add_argument(
       '''--pytorch_dump_folder_path''', required=True, default=None, type=str, help='''Path to the output PyTorch model.'''
   )
   parser.add_argument(
       '''--push_to_hub''', default=None, type=str, help='''Where to upload the converted model on the 🤗 hub.'''
   )

   SCREAMING_SNAKE_CASE_    					=						parser.parse_args()
   convert_hifigan_checkpoint(
       args.checkpoint_path,
       args.stats_path,
       args.pytorch_dump_folder_path,
       args.config_path,
       args.push_to_hub,
   )





"""simple docstring"""

from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
SCREAMING_SNAKE_CASE_    					=						Lock()




def     lowercase__						(					lowerCAmelCase				:					Dict ,				lowerCAmelCase				:					Dict ,				lowerCAmelCase				:					Union[str, Any] ,				lowerCAmelCase				:					Optional[Any] ,				lowerCAmelCase				:					str ,				lowerCAmelCase				:					Optional[int] ,				lowerCAmelCase				:					Optional[Any] ) ->      Optional[int]:






    """simple docstring"""




    global process_lock

    # we perform n swaps since after n swaps we know we are sorted
    # we *could* stop early if we are sorted already, but it takes as long to
    # find out we are sorted as it does to sort the list with this algorithm
    for i in range(0 ,				10 ):
        if (i + position) % 2 == 0 and r_send is not None:
            # send your value to your right neighbor
            process_lock.acquire()
            r_send[1].send(lowerCAmelCase )
            process_lock.release()

            # receive your right neighbor's value
            process_lock.acquire()
            UpperCAmelCase									=					rr_cv[0].recv()
            process_lock.release()

            # take the lower value since you are on the left
            UpperCAmelCase									=					min(lowerCAmelCase ,				lowerCAmelCase )
        elif (i + position) % 2 != 0 and l_send is not None:
            # send your value to your left neighbor
            process_lock.acquire()
            l_send[1].send(lowerCAmelCase )
            process_lock.release()

            # receive your left neighbor's value
            process_lock.acquire()
            UpperCAmelCase									=					lr_cv[0].recv()
            process_lock.release()

            # take the higher value since you are on the right
            UpperCAmelCase									=					max(lowerCAmelCase ,				lowerCAmelCase )
    # after all swaps are performed, send the values back to main
    result_pipe[1].send(lowerCAmelCase )




def     lowercase__						(					lowerCAmelCase				:					Union[str, Any] ) ->      List[str]:






    """simple docstring"""




    UpperCAmelCase									=					[]
    UpperCAmelCase									=					[]
    # initialize the list of pipes where the values will be retrieved
    for _ in arr:
        result_pipe.append(Pipe() )
    # creates the processes
    # the first and last process only have one neighbor so they are made outside
    # of the loop
    UpperCAmelCase									=					Pipe()
    UpperCAmelCase									=					Pipe()
    process_array_.append(
        Process(
            target=lowerCAmelCase ,				args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0]) ,				) )
    UpperCAmelCase									=					temp_rs
    UpperCAmelCase									=					temp_rr

    for i in range(1 ,				len(lowerCAmelCase ) - 1 ):
        UpperCAmelCase									=					Pipe()
        UpperCAmelCase									=					Pipe()
        process_array_.append(
            Process(
                target=lowerCAmelCase ,				args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i]) ,				) )
        UpperCAmelCase									=					temp_rs
        UpperCAmelCase									=					temp_rr

    process_array_.append(
        Process(
            target=lowerCAmelCase ,				args=(
                len(lowerCAmelCase ) - 1,
                arr[len(lowerCAmelCase ) - 1],
                temp_ls,
                None,
                temp_lr,
                None,
                result_pipe[len(lowerCAmelCase ) - 1],
            ) ,				) )

    # start the processes
    for p in process_array_:
        p.start()

    # wait for the processes to end and write their values to the list
    for p in range(0 ,				len(lowerCAmelCase ) ):
        UpperCAmelCase									=					result_pipe[p][0].recv()
        process_array_[p].join()
    return arr




def     lowercase__						(					) ->      Union[str, Any]:






    """simple docstring"""




    UpperCAmelCase									=					list(range(10 ,				0 ,				-1 ) )
    print('Initial List' )
    print(*lowerCAmelCase )
    UpperCAmelCase									=					odd_even_transposition(lowerCAmelCase )
    print('Sorted List\n' )
    print(*lowerCAmelCase )


if __name__ == "__main__":
   main()



