


"""simple docstring"""
import collections
import os
import re
from pathlib import Path


__SCREAMING_SNAKE_CASE							:    Union[str, Any]		=    'src/transformers'


# Matches is_xxx_available()
__SCREAMING_SNAKE_CASE							:    List[str]		=    re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
__SCREAMING_SNAKE_CASE							:    int		=    re.compile(R'^_import_structure\s+=\s+\{([^\}]+)\}')
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
__SCREAMING_SNAKE_CASE							:    str		=    re.compile(R'\s+"\S*":\s+\[([^\]]*)\]')
# Catches a line if not is_foo_available
__SCREAMING_SNAKE_CASE							:    Tuple		=    re.compile(R'^\s*if\s+not\s+is\_[a-z_]*\_available\(\)')
# Catches a line _import_struct["bla"].append("foo")
__SCREAMING_SNAKE_CASE							:    List[str]		=    re.compile(R'^\s*_import_structure\["\S*"\]\.append\("(\S*)"\)')
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
__SCREAMING_SNAKE_CASE							:    Tuple		=    re.compile(R'^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]')
# Catches a line with an object between quotes and a comma:     "MyModel",
__SCREAMING_SNAKE_CASE							:    List[str]		=    re.compile(R'^\s+"([^"]+)",')
# Catches a line with objects between brackets only:    ["foo", "bar"],
__SCREAMING_SNAKE_CASE							:    Dict		=    re.compile(R'^\s+\[([^\]]+)\]')
# Catches a line with from foo import bar, bla, boo
__SCREAMING_SNAKE_CASE							:    Dict		=    re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')
# Catches a line with try:
__SCREAMING_SNAKE_CASE							:    int		=    re.compile(R'^\s*try:')
# Catches a line with else:
__SCREAMING_SNAKE_CASE							:    Tuple		=    re.compile(R'^\s*else:')







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				Optional[int]:
							if _re_test_backend.search(_SCREAMING_SNAKE_CASE				) is None:
														return None
							snake_case_           =		[b[0] for b in _re_backend.findall(_SCREAMING_SNAKE_CASE				)]
							backends.sort()
							return "_and_".join(_SCREAMING_SNAKE_CASE				)







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				Optional[int]:
							with open(_SCREAMING_SNAKE_CASE				, """r"""				, encoding="""utf-8"""				, newline="""\n"""				) as f:
														snake_case_           =		f.readlines()

							snake_case_           =		0
							while line_index < len(_SCREAMING_SNAKE_CASE				) and not lines[line_index].startswith("""_import_structure = {"""				):
														line_index += 1

							# If this is a traditional init, just return.
							if line_index >= len(_SCREAMING_SNAKE_CASE				):
														return None

							# First grab the objects without a specific backend in _import_structure
							snake_case_           =		[]
							while not lines[line_index].startswith("""if TYPE_CHECKING"""				) and find_backend(lines[line_index]				) is None:
														snake_case_           =		lines[line_index]
														# If we have everything on a single line, let's deal with it.
														if _re_one_line_import_struct.search(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		_re_one_line_import_struct.search(_SCREAMING_SNAKE_CASE				).groups()[0]
																					snake_case_           =		re.findall(r"""\[([^\]]+)\]"""				, _SCREAMING_SNAKE_CASE				)
																					for imp in imports:
																												objects.extend([obj[1:-1] for obj in imp.split(""", """				)]				)
																					line_index += 1
																					continue
														snake_case_           =		_re_import_struct_key_value.search(_SCREAMING_SNAKE_CASE				)
														if single_line_import_search is not None:
																					snake_case_           =		[obj[1:-1] for obj in single_line_import_search.groups()[0].split(""", """				) if len(_SCREAMING_SNAKE_CASE				) > 0]
																					objects.extend(_SCREAMING_SNAKE_CASE				)
														elif line.startswith(""" """ * 8 + """\""""				):
																					objects.append(line[9:-3]				)
														line_index += 1

							snake_case_           =		{"""none""": objects}
							# Let's continue with backend-specific objects in _import_structure
							while not lines[line_index].startswith("""if TYPE_CHECKING"""				):
														# If the line is an if not is_backend_available, we grab all objects associated.
														snake_case_           =		find_backend(lines[line_index]				)
														# Check if the backend declaration is inside a try block:
														if _re_try.search(lines[line_index - 1]				) is None:
																					snake_case_           =		None

														if backend is not None:
																					line_index += 1

																					# Scroll until we hit the else block of try-except-else
																					while _re_else.search(lines[line_index]				) is None:
																												line_index += 1

																					line_index += 1

																					snake_case_           =		[]
																					# Until we unindent, add backend objects to the list
																					while len(lines[line_index]				) <= 1 or lines[line_index].startswith(""" """ * 4				):
																												snake_case_           =		lines[line_index]
																												if _re_import_struct_add_one.search(_SCREAMING_SNAKE_CASE				) is not None:
																																			objects.append(_re_import_struct_add_one.search(_SCREAMING_SNAKE_CASE				).groups()[0]				)
																												elif _re_import_struct_add_many.search(_SCREAMING_SNAKE_CASE				) is not None:
																																			snake_case_           =		_re_import_struct_add_many.search(_SCREAMING_SNAKE_CASE				).groups()[0].split(""", """				)
																																			snake_case_           =		[obj[1:-1] for obj in imports if len(_SCREAMING_SNAKE_CASE				) > 0]
																																			objects.extend(_SCREAMING_SNAKE_CASE				)
																												elif _re_between_brackets.search(_SCREAMING_SNAKE_CASE				) is not None:
																																			snake_case_           =		_re_between_brackets.search(_SCREAMING_SNAKE_CASE				).groups()[0].split(""", """				)
																																			snake_case_           =		[obj[1:-1] for obj in imports if len(_SCREAMING_SNAKE_CASE				) > 0]
																																			objects.extend(_SCREAMING_SNAKE_CASE				)
																												elif _re_quote_object.search(_SCREAMING_SNAKE_CASE				) is not None:
																																			objects.append(_re_quote_object.search(_SCREAMING_SNAKE_CASE				).groups()[0]				)
																												elif line.startswith(""" """ * 8 + """\""""				):
																																			objects.append(line[9:-3]				)
																												elif line.startswith(""" """ * 12 + """\""""				):
																																			objects.append(line[13:-3]				)
																												line_index += 1

																					snake_case_           =		objects
														else:
																					line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
							snake_case_           =		[]
							while (
							    line_index < len(_SCREAMING_SNAKE_CASE				)
							    and find_backend(lines[line_index]				) is None
							    and not lines[line_index].startswith("""else"""				)
							):
														snake_case_           =		lines[line_index]
														snake_case_           =		_re_import.search(_SCREAMING_SNAKE_CASE				)
														if single_line_import_search is not None:
																					objects.extend(single_line_import_search.groups()[0].split(""", """				)				)
														elif line.startswith(""" """ * 8				):
																					objects.append(line[8:-2]				)
														line_index += 1

							snake_case_           =		{"""none""": objects}
							# Let's continue with backend-specific objects
							while line_index < len(_SCREAMING_SNAKE_CASE				):
														# If the line is an if is_backend_available, we grab all objects associated.
														snake_case_           =		find_backend(lines[line_index]				)
														# Check if the backend declaration is inside a try block:
														if _re_try.search(lines[line_index - 1]				) is None:
																					snake_case_           =		None

														if backend is not None:
																					line_index += 1

																					# Scroll until we hit the else block of try-except-else
																					while _re_else.search(lines[line_index]				) is None:
																												line_index += 1

																					line_index += 1

																					snake_case_           =		[]
																					# Until we unindent, add backend objects to the list
																					while len(lines[line_index]				) <= 1 or lines[line_index].startswith(""" """ * 8				):
																												snake_case_           =		lines[line_index]
																												snake_case_           =		_re_import.search(_SCREAMING_SNAKE_CASE				)
																												if single_line_import_search is not None:
																																			objects.extend(single_line_import_search.groups()[0].split(""", """				)				)
																												elif line.startswith(""" """ * 12				):
																																			objects.append(line[12:-2]				)
																												line_index += 1

																					snake_case_           =		objects
														else:
																					line_index += 1

							return import_dict_objects, type_hint_objects







def 						_a				(      _SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)    ->				Tuple:

							def find_duplicates(_SCREAMING_SNAKE_CASE				):
														return [k for k, v in collections.Counter(_SCREAMING_SNAKE_CASE				).items() if v > 1]

							if list(import_dict_objects.keys()				) != list(type_hint_objects.keys()				):
														return ["Both sides of the init do not have the same backends!"]

							snake_case_           =		[]
							for key in import_dict_objects.keys():
														snake_case_           =		find_duplicates(import_dict_objects[key]				)
														if duplicate_imports:
																					errors.append(f"""Duplicate _import_structure definitions for: {duplicate_imports}"""				)
														snake_case_           =		find_duplicates(type_hint_objects[key]				)
														if duplicate_type_hints:
																					errors.append(f"""Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}"""				)

														if sorted(set(import_dict_objects[key]				)				) != sorted(set(type_hint_objects[key]				)				):
																					snake_case_           =		"""base imports""" if key == """none""" else f"""{key} backend"""
																					errors.append(f"""Differences for {name}:"""				)
																					for a in type_hint_objects[key]:
																												if a not in import_dict_objects[key]:
																																			errors.append(f"""  {a} in TYPE_HINT but not in _import_structure."""				)
																					for a in import_dict_objects[key]:
																												if a not in type_hint_objects[key]:
																																			errors.append(f"""  {a} in _import_structure but not in TYPE_HINT."""				)
							return errors







def 						_a				(      )    ->				str:
							snake_case_           =		[]
							for root, _, files in os.walk(_SCREAMING_SNAKE_CASE				):
														if "__init__.py" in files:
																					snake_case_           =		os.path.join(_SCREAMING_SNAKE_CASE				, """__init__.py"""				)
																					snake_case_           =		parse_init(_SCREAMING_SNAKE_CASE				)
																					if objects is not None:
																												snake_case_           =		analyze_results(*_SCREAMING_SNAKE_CASE				)
																												if len(_SCREAMING_SNAKE_CASE				) > 0:
																																			snake_case_           =		f"""Problem in {fname}, both halves do not define the same objects.\n{errors[0]}"""
																																			failures.append("""\n""".join(_SCREAMING_SNAKE_CASE				)				)
							if len(_SCREAMING_SNAKE_CASE				) > 0:
														raise ValueError("""\n\n""".join(_SCREAMING_SNAKE_CASE				)				)







def 						_a				(      )    ->				int:
							snake_case_           =		[]
							for path, directories, files in os.walk(_SCREAMING_SNAKE_CASE				):
														for folder in directories:
																					# Ignore private modules
																					if folder.startswith("""_"""				):
																												directories.remove(_SCREAMING_SNAKE_CASE				)
																												continue
																					# Ignore leftovers from branches (empty folders apart from pycache)
																					if len(list((Path(_SCREAMING_SNAKE_CASE				) / folder).glob("""*.py"""				)				)				) == 0:
																												continue
																					snake_case_           =		str((Path(_SCREAMING_SNAKE_CASE				) / folder).relative_to(_SCREAMING_SNAKE_CASE				)				)
																					snake_case_           =		short_path.replace(os.path.sep				, """."""				)
																					submodules.append(_SCREAMING_SNAKE_CASE				)
														for fname in files:
																					if fname == "__init__.py":
																												continue
																					snake_case_           =		str((Path(_SCREAMING_SNAKE_CASE				) / fname).relative_to(_SCREAMING_SNAKE_CASE				)				)
																					snake_case_           =		short_path.replace(""".py"""				, """"""				).replace(os.path.sep				, """."""				)
																					if len(submodule.split("""."""				)				) == 1:
																												submodules.append(_SCREAMING_SNAKE_CASE				)
							return submodules


__SCREAMING_SNAKE_CASE							:    Dict		=    [
    'convert_pytorch_checkpoint_to_tf2',
    'modeling_flax_pytorch_utils',
    'models.esm.openfold_utils',
]







def 						_a				(      )    ->				Tuple:
							# This is to make sure the transformers module imported is the one in the repo.
							from transformers.utils import direct_transformers_import

							snake_case_           =		direct_transformers_import(_SCREAMING_SNAKE_CASE				)

							snake_case_           =		set(transformers._import_structure.keys()				)
							# This contains all the base keys of the _import_structure object defined in the init, but if the user is missing
							# some optional dependencies, they may not have all of them. Thus we read the init to read all additions and
							# (potentiall re-) add them.
							with open(os.path.join(_SCREAMING_SNAKE_CASE				, """__init__.py"""				)				, """r"""				) as f:
														snake_case_           =		f.read()
							import_structure_keys.update(set(re.findall(r"""import_structure\[\"([^\"]*)\"\]"""				, _SCREAMING_SNAKE_CASE				)				)				)

							snake_case_           =		[
							    module
							    for module in get_transformers_submodules()
							    if module not in IGNORE_SUBMODULES and module not in import_structure_keys
							]

							if len(_SCREAMING_SNAKE_CASE				) > 0:
														snake_case_           =		"""\n""".join(f"""- {module}""" for module in module_not_registered				)
														raise ValueError(
														    """The following submodules are not properly registed in the main init of Transformers:\n"""
														    f"""{list_of_modules}\n"""
														    """Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value."""				)


if __name__ == "__main__":
				check_all_inits()
				check_submodules()







"""simple docstring"""
import argparse
import json
import os
from pathlib import Path

import requests
import torch

from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging


logging.set_verbosity_info()
__SCREAMING_SNAKE_CASE							:    str		=    logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE							:    Optional[int]		=    'https://openaipublic.azureedge.net/jukebox/models/'
__SCREAMING_SNAKE_CASE							:    List[Any]		=    {
    'jukebox-1b-lyrics': [
        '5b/vqvae.pth.tar',
        '5b/prior_level_0.pth.tar',
        '5b/prior_level_1.pth.tar',
        '1b_lyrics/prior_level_2.pth.tar',
    ],
    'jukebox-5b-lyrics': [
        '5b/vqvae.pth.tar',
        '5b/prior_level_0.pth.tar',
        '5b/prior_level_1.pth.tar',
        '5b_lyrics/prior_level_2.pth.tar',
    ],
}







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				int:
							if key.endswith(""".model.1.bias"""				) and len(key.split("""."""				)				) > 10:
														snake_case_           =		key.replace(""".model.1.bias"""				, """.conv1d_1.bias"""				)
							elif key.endswith(""".model.1.weight"""				) and len(key.split("""."""				)				) > 10:
														snake_case_           =		key.replace(""".model.1.weight"""				, """.conv1d_1.weight"""				)
							elif key.endswith(""".model.3.bias"""				) and len(key.split("""."""				)				) > 10:
														snake_case_           =		key.replace(""".model.3.bias"""				, """.conv1d_2.bias"""				)
							elif key.endswith(""".model.3.weight"""				) and len(key.split("""."""				)				) > 10:
														snake_case_           =		key.replace(""".model.3.weight"""				, """.conv1d_2.weight"""				)

							if "conditioner_blocks.0." in key:
														snake_case_           =		key.replace("""conditioner_blocks.0"""				, """conditioner_blocks"""				)

							if "prime_prior" in key:
														snake_case_           =		key.replace("""prime_prior"""				, """encoder"""				)

							if ".emb." in key and "total" not in key and "absolute" not in key and "relative" not in key:
														snake_case_           =		key.replace(""".emb."""				, """."""				)

							if key.endswith("""k"""				):  # replace vqvae.X.k with vqvae.X.codebook
														return key.replace(""".k"""				, """.codebook"""				)
							if "y_emb." in key:
														return key.replace("""y_emb."""				, """metadata_embedding."""				)

							if "x_emb.emb." in key:
														snake_case_           =		key.replace("""0.x_emb.emb"""				, """embed_tokens"""				)

							if "prime_state_ln" in key:
														return key.replace("""prime_state_ln"""				, """encoder.final_layer_norm"""				)
							if ".ln" in key:
														return key.replace(""".ln"""				, """.layer_norm"""				)
							if "_ln" in key:
														return key.replace("""_ln"""				, """_layer_norm"""				)

							if "prime_state_proj" in key:
														return key.replace("""prime_state_proj"""				, """encoder.proj_in"""				)
							if "prime_x_out" in key:
														return key.replace("""prime_x_out"""				, """encoder.lm_head"""				)
							if "prior.x_out" in key:
														return key.replace("""x_out"""				, """fc_proj_out"""				)
							if "x_emb" in key:
														return key.replace("""x_emb"""				, """embed_tokens"""				)

							return key







def 						_a				(      _SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)    ->				Union[str, Any]:
							snake_case_           =		{}
							import re

							snake_case_           =		re.compile(r"""encoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).(bias|weight)"""				)
							snake_case_           =		re.compile(
							    r"""encoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).model.(\d*).model.(\d*).(bias|weight)"""				)
							snake_case_           =		re.compile(r"""encoders.(\d*).level_blocks.(\d*).model.(\d*).(bias|weight)"""				)

							snake_case_           =		re.compile(r"""decoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).(bias|weight)"""				)
							snake_case_           =		re.compile(
							    r"""decoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).model.(\d*).model.(\d*).(bias|weight)"""				)
							snake_case_           =		re.compile(r"""decoders.(\d*).level_blocks.(\d*).model.(\d*).(bias|weight)"""				)

							snake_case_           =		re.compile(r"""conditioner_blocks.(\d*).cond.model.(\d*).(\d).(bias|weight)"""				)
							snake_case_           =		re.compile(
							    r"""conditioner_blocks.(\d*).cond.model.(\d*).(\d).model.(\d*).model.(\d*).(bias|weight)"""				)
							snake_case_           =		re.compile(r"""conditioner_blocks.(\d*).cond.model.(\d*).(bias|weight)"""				)

							for original_key, value in state_dict.items():
														# rename vqvae.encoder keys
														if re_encoder_block_conv_in.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_encoder_block_conv_in.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		int(groups[2]				) * 2 + int(groups[3]				)
																					snake_case_           =		f"""encoders.{groups[0]}.level_blocks.{groups[1]}.downsample_block.{block_index}.{groups[-1]}"""
																					snake_case_           =		re_encoder_block_conv_in.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														elif re_encoder_block_resnet.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_encoder_block_resnet.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		int(groups[2]				) * 2 + int(groups[3]				)
																					snake_case_           =		{"""1""": 1, """3""": 2}[groups[-2]]
																					snake_case_           =		f"""encoders.{groups[0]}.level_blocks.{groups[1]}.downsample_block.{block_index}."""
																					snake_case_           =		f"""resnet_block.{groups[-3]}.conv1d_{conv_index}.{groups[-1]}"""
																					snake_case_           =		prefix + resnet_block
																					snake_case_           =		re_encoder_block_resnet.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														elif re_encoder_block_proj_out.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_encoder_block_proj_out.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		f"""encoders.{groups[0]}.level_blocks.{groups[1]}.proj_out.{groups[-1]}"""
																					snake_case_           =		re_encoder_block_proj_out.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														# rename vqvae.decoder keys
														elif re_decoder_block_conv_out.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_decoder_block_conv_out.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		int(groups[2]				) * 2 + int(groups[3]				) - 2
																					snake_case_           =		f"""decoders.{groups[0]}.level_blocks.{groups[1]}.upsample_block.{block_index}.{groups[-1]}"""
																					snake_case_           =		re_decoder_block_conv_out.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														elif re_decoder_block_resnet.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_decoder_block_resnet.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		int(groups[2]				) * 2 + int(groups[3]				) - 2
																					snake_case_           =		{"""1""": 1, """3""": 2}[groups[-2]]
																					snake_case_           =		f"""decoders.{groups[0]}.level_blocks.{groups[1]}.upsample_block.{block_index}."""
																					snake_case_           =		f"""resnet_block.{groups[-3]}.conv1d_{conv_index}.{groups[-1]}"""
																					snake_case_           =		prefix + resnet_block
																					snake_case_           =		re_decoder_block_resnet.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														elif re_decoder_block_proj_in.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_decoder_block_proj_in.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		f"""decoders.{groups[0]}.level_blocks.{groups[1]}.proj_in.{groups[-1]}"""
																					snake_case_           =		re_decoder_block_proj_in.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														# rename prior cond.model to upsampler.upsample_block and resnet
														elif re_prior_cond_conv_out.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_prior_cond_conv_out.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		int(groups[1]				) * 2 + int(groups[2]				) - 2
																					snake_case_           =		f"""conditioner_blocks.upsampler.upsample_block.{block_index}.{groups[-1]}"""
																					snake_case_           =		re_prior_cond_conv_out.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														elif re_prior_cond_resnet.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_prior_cond_resnet.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		int(groups[1]				) * 2 + int(groups[2]				) - 2
																					snake_case_           =		{"""1""": 1, """3""": 2}[groups[-2]]
																					snake_case_           =		f"""conditioner_blocks.upsampler.upsample_block.{block_index}."""
																					snake_case_           =		f"""resnet_block.{groups[-3]}.conv1d_{conv_index}.{groups[-1]}"""
																					snake_case_           =		prefix + resnet_block
																					snake_case_           =		re_prior_cond_resnet.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														elif re_prior_cond_proj_in.fullmatch(_SCREAMING_SNAKE_CASE				):
																					snake_case_           =		re_prior_cond_proj_in.match(_SCREAMING_SNAKE_CASE				)
																					snake_case_           =		regex_match.groups()
																					snake_case_           =		f"""conditioner_blocks.upsampler.proj_in.{groups[-1]}"""
																					snake_case_           =		re_prior_cond_proj_in.sub(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

														# keep original key
														else:
																					snake_case_           =		original_key

														snake_case_           =		replace_key(_SCREAMING_SNAKE_CASE				)

														if f"""{key_prefix}.{key}""" not in model_state_dict or key is None:
																					print(f"""failed converting {original_key} to {key}, does not match"""				)

														# handle missmatched shape
														elif value.shape != model_state_dict[f"""{key_prefix}.{key}"""].shape:
																					snake_case_           =		model_state_dict[f"""{key_prefix}.{key}"""]
																					print(f"""{original_key}-> {key} : \nshape {val.shape} and { value.shape}, do not match"""				)
																					snake_case_           =		original_key

														snake_case_           =		original_key
														snake_case_           =		value

							return new_dict







@torch.no_grad()
def 						_a				(      _SCREAMING_SNAKE_CASE=None				, _SCREAMING_SNAKE_CASE=None				)    ->				Optional[int]:
							for file in MODEL_MAPPING[model_name]:
														if not os.path.isfile(f"""{pytorch_dump_folder_path}/{file.split("/"				)[-1]}"""				):
																					snake_case_           =		requests.get(f"""{PREFIX}{file}"""				, allow_redirects=_SCREAMING_SNAKE_CASE				)
																					os.makedirs(f"""{pytorch_dump_folder_path}/"""				, exist_ok=_SCREAMING_SNAKE_CASE				)
																					open(f"""{pytorch_dump_folder_path}/{file.split("/"				)[-1]}"""				, """wb"""				).write(r.content				)

							snake_case_           =		MODEL_MAPPING[model_name.split("""/"""				)[-1]]

							snake_case_           =		JukeboxConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
							snake_case_           =		JukeboxModel(_SCREAMING_SNAKE_CASE				)

							snake_case_           =		[]
							snake_case_           =		{}
							for i, dict_name in enumerate(_SCREAMING_SNAKE_CASE				):
														snake_case_           =		torch.load(f"""{pytorch_dump_folder_path}/{dict_name.split("/"				)[-1]}"""				)["""model"""]

														snake_case_           =		{}
														for k in old_dic.keys():
																					if k.endswith(""".b"""				):
																												snake_case_           =		old_dic[k]
																					elif k.endswith(""".w"""				):
																												snake_case_           =		old_dic[k]
																					elif "level_2" not in dict_name and "cond.model." in k:
																												snake_case_           =		old_dic[k]
																					else:
																												snake_case_           =		old_dic[k]

														snake_case_           =		"""vqvae""" if i == 0 else f"""priors.{3 - i}"""
														snake_case_           =		fix_jukebox_keys(_SCREAMING_SNAKE_CASE				, model.state_dict()				, _SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)
														weight_dict.append(_SCREAMING_SNAKE_CASE				)

							snake_case_           =		weight_dict.pop(0				)
							model.vqvae.load_state_dict(_SCREAMING_SNAKE_CASE				)
							for i in range(len(_SCREAMING_SNAKE_CASE				)				):
														model.priors[i].load_state_dict(weight_dict[2 - i]				)

							Path(_SCREAMING_SNAKE_CASE				).mkdir(exist_ok=_SCREAMING_SNAKE_CASE				)
							with open(f"""{pytorch_dump_folder_path}/mapping.json"""				, """w"""				) as txtfile:
														json.dump(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				)

							print(f"""Saving model {model_name} to {pytorch_dump_folder_path}"""				)
							model.save_pretrained(_SCREAMING_SNAKE_CASE				)

							return weight_dict


if __name__ == "__main__":
				__SCREAMING_SNAKE_CASE							:    Union[str, Any]		=    argparse.ArgumentParser()
				# Required parameters
				parser.add_argument(
				    '--model_name',
				    default='jukebox-5b-lyrics',
				    type=str,
				    help='Name of the model you\'d like to convert.',
				)
				parser.add_argument(
				    '--pytorch_dump_folder_path',
				    default='jukebox-5b-lyrics-converted',
				    type=str,
				    help='Path to the output PyTorch model directory.',
				)
				__SCREAMING_SNAKE_CASE							:    str		=    parser.parse_args()
				convert_openai_checkpoint(args.model_name, args.pytorch_dump_folder_path)



