


import argparse

import numpy as np
import torch

from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging


logging.set_verbosity_info()
__UpperCamelCase				:  str      					=							logging.get_logger('transformers.models.speecht5')
def      snake_case_						( __lowercase			,       __lowercase			,       __lowercase       ):
   hf_model.apply_weight_norm()

   UpperCAmelCase_							:      str						=   checkpoint['''input_conv.weight_g''']
   UpperCAmelCase_							:      Tuple						=   checkpoint['''input_conv.weight_v''']
   UpperCAmelCase_							:      Union[str, Any]						=   checkpoint['''input_conv.bias''']

   for i in range(len(config.upsample_rates       )       ):
      UpperCAmelCase_							:      Union[str, Any]						=   checkpoint[F'''upsamples.{i}.1.weight_g''']
      UpperCAmelCase_							:      Any						=   checkpoint[F'''upsamples.{i}.1.weight_v''']
      UpperCAmelCase_							:      int						=   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_							:      Optional[Any]						=   checkpoint[F'''blocks.{i}.convs1.{j}.1.weight_g''']
         UpperCAmelCase_							:      Any						=   checkpoint[F'''blocks.{i}.convs1.{j}.1.weight_v''']
         UpperCAmelCase_							:      List[Any]						=   checkpoint[F'''blocks.{i}.convs1.{j}.1.bias''']

         UpperCAmelCase_							:      str						=   checkpoint[F'''blocks.{i}.convs2.{j}.1.weight_g''']
         UpperCAmelCase_							:      Optional[Any]						=   checkpoint[F'''blocks.{i}.convs2.{j}.1.weight_v''']
         UpperCAmelCase_							:      Tuple						=   checkpoint[F'''blocks.{i}.convs2.{j}.1.bias''']

   UpperCAmelCase_							:      Optional[int]						=   checkpoint['''output_conv.1.weight_g''']
   UpperCAmelCase_							:      Dict						=   checkpoint['''output_conv.1.weight_v''']
   UpperCAmelCase_							:      Any						=   checkpoint['''output_conv.1.bias''']

   hf_model.remove_weight_norm()
@torch.no_grad()
def      snake_case_						( __lowercase			,       __lowercase			,       __lowercase			,       __lowercase=None			,       __lowercase=None			,       ):
   if config_path is not None:
      UpperCAmelCase_							:      Any						=   SpeechTaHifiGanConfig.from_pretrained(__lowercase       )
   else:
      UpperCAmelCase_							:      Optional[int]						=   SpeechTaHifiGanConfig()

   UpperCAmelCase_							:      str						=   SpeechTaHifiGan(__lowercase       )

   UpperCAmelCase_							:      List[Any]						=   torch.load(__lowercase       )
   load_weights(orig_checkpoint['''model''']['''generator''']			,       __lowercase			,       __lowercase       )

   UpperCAmelCase_							:      Optional[Any]						=   np.load(__lowercase       )
   UpperCAmelCase_							:      Any						=   stats[0].reshape(-1       )
   UpperCAmelCase_							:      Dict						=   stats[1].reshape(-1       )
   UpperCAmelCase_							:      Optional[Any]						=   torch.from_numpy(__lowercase       ).float()
   UpperCAmelCase_							:      int						=   torch.from_numpy(__lowercase       ).float()

   model.save_pretrained(__lowercase       )

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


if __name__ == "__main__":
       __UpperCamelCase				:  List[str]      					=							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.'
       )

       __UpperCamelCase				:  Optional[Any]      					=							parser.parse_args()
       convert_hifigan_checkpoint(
           args.checkpoint_path,
           args.stats_path,
           args.pytorch_dump_folder_path,
           args.config_path,
           args.push_to_hub,
       )



# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py

import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def      snake_case_						( __lowercase			,       __lowercase			,       __lowercase			,       __lowercase       ):
   UpperCAmelCase_							:      int						=   multiprocessing.Manager()
   UpperCAmelCase_							:      Union[str, Any]						=   manager.list()

   UpperCAmelCase_							:      int						=   multiprocessing.Process(target=__lowercase			,       args=(check_program, result, timeout)       )
   p.start()
   p.join(timeout=timeout + 1       )
   if p.is_alive():
      p.kill()

   if not result:
      result.append('''timed out'''       )

   return {
       "task_id": task_id,
       "passed": result[0] == "passed",
       "result": result[0],
       "completion_id": completion_id,
   }
def      snake_case_						( __lowercase			,       __lowercase			,       __lowercase       ):
   with create_tempdir():
      # These system calls are needed when cleaning up tempdir.
      import os
      import shutil

      UpperCAmelCase_							:      str						=   shutil.rmtree
      UpperCAmelCase_							:      Tuple						=   os.rmdir
      UpperCAmelCase_							:      Dict						=   os.chdir

      # Disable functionalities that can make destructive changes to the test.
      reliability_guard()

      # Run program.
      try:
         UpperCAmelCase_							:      Optional[int]						=   {}
         with swallow_io():
            with time_limit(__lowercase       ):
               exec(__lowercase			,       __lowercase       )
         result.append('''passed'''       )
      except TimeoutException:
         result.append('''timed out'''       )
      except BaseException as e:
         result.append(F'''failed: {e}'''       )

      # Needed for cleaning up.
      UpperCAmelCase_							:      Optional[int]						=   rmtree
      UpperCAmelCase_							:      Optional[Any]						=   rmdir
      UpperCAmelCase_							:      Optional[Any]						=   chdir
@contextlib.contextmanager
def      snake_case_						( __lowercase       ):
   def signal_handler(__lowercase			,       __lowercase       ):
      raise TimeoutException('''Timed out!'''       )

   signal.setitimer(signal.ITIMER_REAL			,       __lowercase       )
   signal.signal(signal.SIGALRM			,       __lowercase       )
   try:
      yield
   finally:
      signal.setitimer(signal.ITIMER_REAL			,       0       )
@contextlib.contextmanager
def      snake_case_						( ):
   UpperCAmelCase_							:      Optional[Any]						=   WriteOnlyStringIO()
   with contextlib.redirect_stdout(__lowercase       ):
      with contextlib.redirect_stderr(__lowercase       ):
         with redirect_stdin(__lowercase       ):
            yield
@contextlib.contextmanager
def      snake_case_						( ):
   with tempfile.TemporaryDirectory() as dirname:
      with chdir(__lowercase       ):
         yield dirname





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    pass





class  lowerCAmelCase__(    io.StringIO						):






    '''simple docstring'''





    def 					_lowerCamelCase (	self				:   Dict       ,   *__snake_case				:   List[Any]       ,   **__snake_case				:   int	):





       '''simple docstring'''
       raise OSError





    def 					_lowerCamelCase (	self				:   Dict       ,   *__snake_case				:   int       ,   **__snake_case				:   Any	):





       '''simple docstring'''
       raise OSError





    def 					_lowerCamelCase (	self				:   int       ,   *__snake_case				:   List[str]       ,   **__snake_case				:   Optional[Any]	):





       '''simple docstring'''
       raise OSError





    def 					_lowerCamelCase (	self				:   Union[str, Any]       ,   *__snake_case				:   Optional[Any]       ,   **__snake_case				:   List[Any]	):





       '''simple docstring'''
       return False





class  lowerCAmelCase__(    contextlib._RedirectStream						):  # type: ignore






    '''simple docstring'''





    A_  :     Optional[Any]			= 'stdin'





@contextlib.contextmanager
def      snake_case_						( __lowercase       ):
   if root == ".":
      yield
      return
   UpperCAmelCase_							:      Tuple						=   os.getcwd()
   os.chdir(__lowercase       )
   try:
      yield
   except BaseException as exc:
      raise exc
   finally:
      os.chdir(__lowercase       )


def      snake_case_						( __lowercase=None       ):

   if maximum_memory_bytes is not None:
      import resource

      resource.setrlimit(resource.RLIMIT_AS			,       (maximum_memory_bytes, maximum_memory_bytes)       )
      resource.setrlimit(resource.RLIMIT_DATA			,       (maximum_memory_bytes, maximum_memory_bytes)       )
      if not platform.uname().system == "Darwin":
         resource.setrlimit(resource.RLIMIT_STACK			,       (maximum_memory_bytes, maximum_memory_bytes)       )

   faulthandler.disable()

   import builtins

   UpperCAmelCase_							:      Any						=   None
   UpperCAmelCase_							:      Any						=   None

   import os

   UpperCAmelCase_							:      Union[str, Any]						=   '''1'''

   UpperCAmelCase_							:      List[str]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Any						=   None
   UpperCAmelCase_							:      Optional[int]						=   None
   UpperCAmelCase_							:      List[str]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      str						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      int						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      int						=   None
   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Any						=   None

   import shutil

   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Tuple						=   None

   import subprocess

   UpperCAmelCase_							:      Dict						=   None  # type: ignore

   UpperCAmelCase_							:      Union[str, Any]						=   None

   import sys

   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      List[str]						=   None
   UpperCAmelCase_							:      Dict						=   None