

import inspect
import os
import unittest
from pathlib import Path

import torch

import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command




class      UpperCamelCase (     unittest.TestCase   ):
    __UpperCamelCase         =inspect.getfile(accelerate.test_utils   )
    __UpperCamelCase         =os.path.sep.join(mod_file.split(os.path.sep   )[:-1] + ["scripts", "test_cli.py"]   )

    __UpperCamelCase         =["accelerate", "launch"]
    __UpperCamelCase         =Path.home() / ".cache/huggingface/accelerate"
    __UpperCamelCase         ="default_config.yaml"
    __UpperCamelCase         =config_folder / config_file
    __UpperCamelCase         =config_folder / "_default_config.yaml"

    __UpperCamelCase         =Path("tests/test_configs"   )

    @classmethod
    def UpperCamelCase			(			cls :      str    ):

     """simple docstring"""






     if cls.config_path.is_file():
      cls.config_path.rename(cls.changed_path    )

    @classmethod
    def UpperCamelCase			(			cls :      Optional[int]    ):

     """simple docstring"""






     if cls.changed_path.is_file():
      cls.changed_path.rename(cls.config_path    )

    def UpperCamelCase			(			self :      List[Any]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			self.base_cmd
     if torch.cuda.is_available() and (torch.cuda.device_count() > 1):
      cmd += ["--multi_gpu"]
     execute_subprocess_async(cmd + [self.test_file_path]							,    env=os.environ.copy()    )

    def UpperCamelCase			(			self :      Tuple    ):

     """simple docstring"""






     for config in sorted(self.test_config_path.glob('**/*.yaml'    )    ):
      with self.subTest(config_file=snake_case__    ):
       execute_subprocess_async(
           self.base_cmd + ['--config_file', str(snake_case__    ), self.test_file_path]							,    env=os.environ.copy()    )




    def UpperCamelCase			(			self :      str    ):

     """simple docstring"""






     execute_subprocess_async(['accelerate', 'test']							,    env=os.environ.copy()    )




class      UpperCamelCase (     unittest.TestCase   ):
    __UpperCamelCase         ="test-tpu"
    __UpperCamelCase         ="us-central1-a"
    __UpperCamelCase         ="ls"
    __UpperCamelCase         =["accelerate", "tpu-config"]
    __UpperCamelCase         ="cd /usr/share"
    __UpperCamelCase         ="tests/test_samples/test_command_file.sh"
    __UpperCamelCase         ="Running gcloud compute tpus tpu-vm ssh"

    def UpperCamelCase			(			self :      Any    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd
         + ['--command', self.command, '--tpu_zone', self.tpu_zone, '--tpu_name', self.tpu_name, '--debug']							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      Tuple    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd
         + [
             '--config_file',
             'tests/test_configs/0_12_0.yaml',
             '--command',
             self.command,
             '--tpu_zone',
             self.tpu_zone,
             '--tpu_name',
             self.tpu_name,
             '--debug',
         ]							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      List[str]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--debug']							,    return_stdout=snake_case__    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      List[str]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--command', self.command, '--debug']							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      Tuple    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd
         + [
             '--config_file',
             'tests/test_configs/latest.yaml',
             '--command',
             self.command,
             '--command',
             'echo "Hello World"',
             '--debug',
         ]							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls; echo \"Hello World\" --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      str    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd
         + ['--config_file', 'tests/test_configs/latest.yaml', '--command_file', self.command_file, '--debug']							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      Optional[int]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd
         + [
             '--config_file',
             'tests/test_configs/0_12_0.yaml',
             '--command_file',
             self.command_file,
             '--tpu_zone',
             self.tpu_zone,
             '--tpu_name',
             self.tpu_name,
             '--debug',
         ]							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"""							,    snake_case__							,    )

    def UpperCamelCase			(			self :      Optional[Any]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--install_accelerate', '--debug']							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate -U; echo \"hello world\"; echo \"this is a second command\" --worker all"""							,    snake_case__							,    )




    def UpperCamelCase			(			self :      Optional[Any]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			run_command(
         self.cmd
         + [
             '--config_file',
             'tests/test_configs/latest.yaml',
             '--install_accelerate',
             '--accelerate_version',
             '12.0.0',
             '--debug',
         ]							,    return_stdout=snake_case__							,    )
     self.assertIn(
         F"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate==12.0.0; echo \"hello world\"; echo \"this is a second command\" --worker all"""							,    snake_case__							,    )




import argparse

import numpy as np
import torch

from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging


logging.set_verbosity_info()
a_    :						List[Any]    		=      logging.get_logger("transformers.models.speecht5")


def        __lowerCAmelCase    (       _UpperCamelCase		:  Tuple		,							_UpperCamelCase		:  Tuple		,							_UpperCamelCase		:  Any	)		->							Dict:
 '''simple docstring'''


 hf_model.apply_weight_norm()

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

 for i in range(len(config.upsample_rates	)	):
  SCREAMING_SNAKE_CASE								=			checkpoint[f"""upsamples.{i}.1.weight_g"""]
  SCREAMING_SNAKE_CASE								=			checkpoint[f"""upsamples.{i}.1.weight_v"""]
  SCREAMING_SNAKE_CASE								=			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	)	):
   SCREAMING_SNAKE_CASE								=			checkpoint[f"""blocks.{i}.convs1.{j}.1.weight_g"""]
   SCREAMING_SNAKE_CASE								=			checkpoint[f"""blocks.{i}.convs1.{j}.1.weight_v"""]
   SCREAMING_SNAKE_CASE								=			checkpoint[f"""blocks.{i}.convs1.{j}.1.bias"""]

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

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

 hf_model.remove_weight_norm()


@torch.no_grad()
def        __lowerCAmelCase    (       _UpperCamelCase		:  Optional[int]		,							_UpperCamelCase		:  Dict		,							_UpperCamelCase		:  Tuple		,							_UpperCamelCase		:  Any=None		,							_UpperCamelCase		:  List[str]=None		,							)		->							Tuple:
 '''simple docstring'''


 if config_path is not None:
  SCREAMING_SNAKE_CASE								=			SpeechTaHifiGanConfig.from_pretrained(_UpperCamelCase	)
 else:
  SCREAMING_SNAKE_CASE								=			SpeechTaHifiGanConfig()

 SCREAMING_SNAKE_CASE								=			SpeechTaHifiGan(_UpperCamelCase	)

 SCREAMING_SNAKE_CASE								=			torch.load(_UpperCamelCase	)
 load_weights(orig_checkpoint['model']['generator']		,							_UpperCamelCase		,							_UpperCamelCase	)

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

 model.save_pretrained(_UpperCamelCase	)

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


if __name__ == "__main__":
      a_    :						Dict    		=      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."
      )

      a_    :						Tuple    		=      parser.parse_args()
      convert_hifigan_checkpoint(
          args.checkpoint_path,
          args.stats_path,
          args.pytorch_dump_folder_path,
          args.config_path,
          args.push_to_hub,
      )

