




import argparse

import numpy as np
import torch

from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging


logging.set_verbosity_info()
UpperCamelCase__         =      logging.get_logger("""transformers.models.speecht5""")







def      _a				(						SCREAMING_SNAKE_CASE_							:    Any				,				SCREAMING_SNAKE_CASE_							:    Tuple				,				SCREAMING_SNAKE_CASE_							:    str					):
					hf_model.apply_weight_norm()

					__lowerCAmelCase           =	checkpoint["input_conv.weight_g"]
					__lowerCAmelCase           =	checkpoint["input_conv.weight_v"]
					__lowerCAmelCase           =	checkpoint["input_conv.bias"]

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

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

					__lowerCAmelCase           =	checkpoint["output_conv.1.weight_g"]
					__lowerCAmelCase           =	checkpoint["output_conv.1.weight_v"]
					__lowerCAmelCase           =	checkpoint["output_conv.1.bias"]

					hf_model.remove_weight_norm()







@torch.no_grad()
def      _a				(						SCREAMING_SNAKE_CASE_							:    List[Any]				,				SCREAMING_SNAKE_CASE_							:    Dict				,				SCREAMING_SNAKE_CASE_							:    List[Any]				,				SCREAMING_SNAKE_CASE_							:    Optional[int]=None				,				SCREAMING_SNAKE_CASE_							:    Union[str, Any]=None				,				):
					if config_path is not None:
										__lowerCAmelCase           =	SpeechTaHifiGanConfig.from_pretrained(SCREAMING_SNAKE_CASE_					)
					else:
										__lowerCAmelCase           =	SpeechTaHifiGanConfig()

					__lowerCAmelCase           =	SpeechTaHifiGan(SCREAMING_SNAKE_CASE_					)

					__lowerCAmelCase           =	torch.load(SCREAMING_SNAKE_CASE_					)
					load_weights(orig_checkpoint["model"]["generator"]				,				SCREAMING_SNAKE_CASE_				,				SCREAMING_SNAKE_CASE_					)

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

					model.save_pretrained(SCREAMING_SNAKE_CASE_					)

					if repo_id:
										print("Pushing to the hub..."					)
										model.push_to_hub(SCREAMING_SNAKE_CASE_					)


if __name__ == "__main__":
					UpperCamelCase__         =      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__         =      parser.parse_args()
					convert_hifigan_checkpoint(
					    args.checkpoint_path,
					    args.stats_path,
					    args.pytorch_dump_folder_path,
					    args.config_path,
					    args.push_to_hub,
					)










from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__         =      logging.get_logger(__name__)

UpperCamelCase__         =      {
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class       a__   ( snake_case__				):
						_a							:   Dict =   """mgp-str"""






						def __init__(       self		,      _A=[3_2, 1_2_8]		,      _A=4		,      _A=3		,      _A=2_7		,      _A=3_8		,      _A=5_0_2_5_7		,      _A=3_0_5_2_2		,      _A=7_6_8		,      _A=1_2		,      _A=1_2		,      _A=4.0		,      _A=True		,      _A=False		,      _A=1E-5		,      _A=0.0		,      _A=0.0		,      _A=0.0		,      _A=False		,      _A=0.02		,      **_A		,      ):




											"""simple docstring"""



											super().__init__(**_A      )

											__lowerCAmelCase           =	image_size
											__lowerCAmelCase           =	patch_size
											__lowerCAmelCase           =	num_channels
											__lowerCAmelCase           =	max_token_length
											__lowerCAmelCase           =	num_character_labels
											__lowerCAmelCase           =	num_bpe_labels
											__lowerCAmelCase           =	num_wordpiece_labels
											__lowerCAmelCase           =	hidden_size
											__lowerCAmelCase           =	num_hidden_layers
											__lowerCAmelCase           =	num_attention_heads
											__lowerCAmelCase           =	mlp_ratio
											__lowerCAmelCase           =	distilled
											__lowerCAmelCase           =	layer_norm_eps
											__lowerCAmelCase           =	drop_rate
											__lowerCAmelCase           =	qkv_bias
											__lowerCAmelCase           =	attn_drop_rate
											__lowerCAmelCase           =	drop_path_rate
											__lowerCAmelCase           =	output_aa_attentions
											__lowerCAmelCase           =	initializer_range




