




'''simple docstring'''






import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__UpperCAmelCase       =							logging.get_logger(__name__)


__UpperCAmelCase       =							{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

__UpperCAmelCase       =							{
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
}

__UpperCAmelCase       =							{
    "allenai/longformer-base-4096": 4_096,
    "allenai/longformer-large-4096": 4_096,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_096,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_096,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_096,
}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def  _snake_case       (					)						->   List[str]:
							lowerCAmelCase__	       =     (
							    list(range(ord('''!'''	)			,   ord('''~'''	) + 1	)	) + list(range(ord('''¡'''	)			,   ord('''¬'''	) + 1	)	) + list(range(ord('''®'''	)			,   ord('''ÿ'''	) + 1	)	)
							)
							lowerCAmelCase__	       =     bs[:]
							lowerCAmelCase__	       =     0
							for b in range(2**8	):
														if b not in bs:
																					bs.append(A	)
																					cs.append(2**8 + n	)
																					n += 1
							lowerCAmelCase__	       =     [chr(A	) for n in cs]
							return dict(zip(A			,   A	)	)


def  _snake_case       (					A	)						->   Optional[Any]:
							lowerCAmelCase__	       =     set()
							lowerCAmelCase__	       =     word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)	)
														lowerCAmelCase__	       =     char
							return pairs






class 		a__    (							lowercase_  ):





							'''simple docstring'''






							lowercase__      :       Optional[int]     						=				VOCAB_FILES_NAMES
							lowercase__      :       str     						=				PRETRAINED_VOCAB_FILES_MAP
							lowercase__      :       int     						=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__      :       Optional[Any]     						=				["input_ids", "attention_mask"]







							def __init__(		self ,   lowerCamelCase_ ,   lowerCamelCase_ ,   lowerCamelCase_="replace" ,   lowerCamelCase_="<s>" ,   lowerCamelCase_="</s>" ,   lowerCamelCase_="</s>" ,   lowerCamelCase_="<s>" ,   lowerCamelCase_="<unk>" ,   lowerCamelCase_="<pad>" ,   lowerCamelCase_="<mask>" ,   lowerCamelCase_=False ,   **lowerCamelCase_ ,   )	->							Tuple:
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else bos_token
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else eos_token
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else sep_token
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else cls_token
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else unk_token
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else pad_token

														# Mask token behave like a normal word, i.e. include the space before it
														lowerCAmelCase__	       =     AddedToken(a__ ,   lstrip=a__ ,   rstrip=a__       ) if isinstance(a__ ,   a__       ) else mask_token

														super().__init__(
														    errors=a__ ,   bos_token=a__ ,   eos_token=a__ ,   unk_token=a__ ,   sep_token=a__ ,   cls_token=a__ ,   pad_token=a__ ,   mask_token=a__ ,   add_prefix_space=a__ ,   **a__ ,   )

														with open(a__ ,   encoding='''utf-8'''       ) as vocab_handle:
																					lowerCAmelCase__	       =     json.load(a__       )
														lowerCAmelCase__	       =     {v: k for k, v in self.encoder.items()}
														lowerCAmelCase__	       =     errors  # how to handle errors in decoding
														lowerCAmelCase__	       =     bytes_to_unicode()
														lowerCAmelCase__	       =     {v: k for k, v in self.byte_encoder.items()}
														with open(a__ ,   encoding='''utf-8'''       ) as merges_handle:
																					lowerCAmelCase__	       =     merges_handle.read().split('''\n'''       )[1:-1]
														lowerCAmelCase__	       =     [tuple(merge.split()       ) for merge in bpe_merges]
														lowerCAmelCase__	       =     dict(zip(a__ ,   range(len(a__       )       )       )       )
														lowerCAmelCase__	       =     {}
														lowerCAmelCase__	       =     add_prefix_space

														# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
														lowerCAmelCase__	       =     re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''       )







							@property
							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Dict:
														return len(self.encoder       )







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							List[str]:
														return dict(self.encoder ,   **self.added_tokens_encoder       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							List[Any]:




														if token in self.cache:
																					return self.cache[token]
														lowerCAmelCase__	       =     tuple(a__       )
														lowerCAmelCase__	       =     get_pairs(a__       )

														if not pairs:
																					return token

														while True:
																					lowerCAmelCase__	       =     min(a__ ,   key=lambda lowerCamelCase_       : self.bpe_ranks.get(a__ ,   float('''inf'''       )       )       )
																					if bigram not in self.bpe_ranks:
																												break
																					lowerCAmelCase__       , lowerCAmelCase__	       =     bigram
																					lowerCAmelCase__	       =     []
																					lowerCAmelCase__	       =     0
																					while i < len(a__       ):
																												try:
																																			lowerCAmelCase__	       =     word.index(a__ ,   a__       )
																												except ValueError:
																																			new_word.extend(word[i:]       )
																																			break
																												else:
																																			new_word.extend(word[i:j]       )
																																			lowerCAmelCase__	       =     j

																												if word[i] == first and i < len(a__       ) - 1 and word[i + 1] == second:
																																			new_word.append(first + second       )
																																			i += 2
																												else:
																																			new_word.append(word[i]       )
																																			i += 1
																					lowerCAmelCase__	       =     tuple(a__       )
																					lowerCAmelCase__	       =     new_word
																					if len(a__       ) == 1:
																												break
																					else:
																												lowerCAmelCase__	       =     get_pairs(a__       )
														lowerCAmelCase__	       =     ''' '''.join(a__       )
														lowerCAmelCase__	       =     word
														return word







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							int:
														lowerCAmelCase__	       =     []
														for token in re.findall(self.pat ,   a__       ):
																					lowerCAmelCase__	       =     ''''''.join(
																					    self.byte_encoder[b] for b in token.encode('''utf-8'''       )       )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
																					bpe_tokens.extend(bpe_token for bpe_token in self.bpe(a__       ).split(''' '''       )       )
														return bpe_tokens







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							Union[str, Any]:
														return self.encoder.get(a__ ,   self.encoder.get(self.unk_token       )       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							Union[str, Any]:
														return self.decoder.get(a__       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							int:
														lowerCAmelCase__	       =     ''''''.join(a__       )
														lowerCAmelCase__	       =     bytearray([self.byte_decoder[c] for c in text]       ).decode('''utf-8''' ,   errors=self.errors       )
														return text







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_ = None       )	->							Tuple[str]:




														if not os.path.isdir(a__       ):
																					logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
																					return
														lowerCAmelCase__	       =     os.path.join(
														    a__ ,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']       )
														lowerCAmelCase__	       =     os.path.join(
														    a__ ,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']       )

														with open(a__ ,   '''w''' ,   encoding='''utf-8'''       ) as f:
																					f.write(json.dumps(self.encoder ,   indent=2 ,   sort_keys=a__ ,   ensure_ascii=a__       ) + '''\n'''       )

														lowerCAmelCase__	       =     0
														with open(a__ ,   '''w''' ,   encoding='''utf-8'''       ) as writer:
																					writer.write('''#version: 0.2\n'''       )
																					for bpe_tokens, token_index in sorted(self.bpe_ranks.items() ,   key=lambda lowerCamelCase_       : kv[1]       ):
																												if index != token_index:
																																			logger.warning(
																																			    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																																			    ''' Please check that the tokenizer is not corrupted!'''       )
																																			lowerCAmelCase__	       =     token_index
																												writer.write(''' '''.join(a__       ) + '''\n'''       )
																												index += 1

														return vocab_file, merge_file







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_ = None       )	->							List[int]:




														if token_ids_a is None:
																					return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
														lowerCAmelCase__	       =     [self.cls_token_id]
														lowerCAmelCase__	       =     [self.sep_token_id]
														return cls + token_ids_a + sep + sep + token_ids_a + sep







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_ = None ,   lowerCamelCase_ = False       )	->							List[int]:




														if already_has_special_tokens:
																					return super().get_special_tokens_mask(
																					    token_ids_a=a__ ,   token_ids_a=a__ ,   already_has_special_tokens=a__       )

														if token_ids_a is None:
																					return [1] + ([0] * len(a__       )) + [1]
														return [1] + ([0] * len(a__       )) + [1, 1] + ([0] * len(a__       )) + [1]







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_ = None       )	->							List[int]:
														lowerCAmelCase__	       =     [self.sep_token_id]
														lowerCAmelCase__	       =     [self.cls_token_id]

														if token_ids_a is None:
																					return len(cls + token_ids_a + sep       ) * [0]
														return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_=False ,   **lowerCamelCase_       )	->							int:
														lowerCAmelCase__	       =     kwargs.pop('''add_prefix_space''' ,   self.add_prefix_space       )
														if (is_split_into_words or add_prefix_space) and (len(a__       ) > 0 and not text[0].isspace()):
																					lowerCAmelCase__	       =     ''' ''' + text
														return (text, kwargs)



'''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()
__UpperCAmelCase       =							logging.get_logger(__name__)


__UpperCAmelCase       =							'''https://openaipublic.azureedge.net/jukebox/models/'''
__UpperCAmelCase       =							{
    '''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  _snake_case       (					A	)						->   Union[str, Any]:
							if key.endswith('''.model.1.bias'''	) and len(key.split('''.'''	)	) > 10:
														lowerCAmelCase__	       =     key.replace('''.model.1.bias'''			,   '''.conv1d_1.bias'''	)
							elif key.endswith('''.model.1.weight'''	) and len(key.split('''.'''	)	) > 10:
														lowerCAmelCase__	       =     key.replace('''.model.1.weight'''			,   '''.conv1d_1.weight'''	)
							elif key.endswith('''.model.3.bias'''	) and len(key.split('''.'''	)	) > 10:
														lowerCAmelCase__	       =     key.replace('''.model.3.bias'''			,   '''.conv1d_2.bias'''	)
							elif key.endswith('''.model.3.weight'''	) and len(key.split('''.'''	)	) > 10:
														lowerCAmelCase__	       =     key.replace('''.model.3.weight'''			,   '''.conv1d_2.weight'''	)

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

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

							if ".emb." in key and "total" not in key and "absolute" not in key and "relative" not in key:
														lowerCAmelCase__	       =     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:
														lowerCAmelCase__	       =     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  _snake_case       (					A			,   A			,   A			,   A	)						->   Optional[int]:
							lowerCAmelCase__	       =     {}
							import re

							lowerCAmelCase__	       =     re.compile(R'''encoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).(bias|weight)'''	)
							lowerCAmelCase__	       =     re.compile(
							    R'''encoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).model.(\d*).model.(\d*).(bias|weight)'''	)
							lowerCAmelCase__	       =     re.compile(R'''encoders.(\d*).level_blocks.(\d*).model.(\d*).(bias|weight)'''	)

							lowerCAmelCase__	       =     re.compile(R'''decoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).(bias|weight)'''	)
							lowerCAmelCase__	       =     re.compile(
							    R'''decoders.(\d*).level_blocks.(\d*).model.(\d*).(\d).model.(\d*).model.(\d*).(bias|weight)'''	)
							lowerCAmelCase__	       =     re.compile(R'''decoders.(\d*).level_blocks.(\d*).model.(\d*).(bias|weight)'''	)

							lowerCAmelCase__	       =     re.compile(R'''conditioner_blocks.(\d*).cond.model.(\d*).(\d).(bias|weight)'''	)
							lowerCAmelCase__	       =     re.compile(
							    R'''conditioner_blocks.(\d*).cond.model.(\d*).(\d).model.(\d*).model.(\d*).(bias|weight)'''	)
							lowerCAmelCase__	       =     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(A	):
																					lowerCAmelCase__	       =     re_encoder_block_conv_in.match(A	)
																					lowerCAmelCase__	       =     regex_match.groups()
																					lowerCAmelCase__	       =     int(groups[2]	) * 2 + int(groups[3]	)
																					lowerCAmelCase__	       =     F"""encoders.{groups[0]}.level_blocks.{groups[1]}.downsample_block.{block_index}.{groups[-1]}"""
																					lowerCAmelCase__	       =     re_encoder_block_conv_in.sub(A			,   A	)

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

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

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

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

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

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

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

														elif re_prior_cond_proj_in.fullmatch(A	):
																					lowerCAmelCase__	       =     re_prior_cond_proj_in.match(A	)
																					lowerCAmelCase__	       =     regex_match.groups()
																					lowerCAmelCase__	       =     F"""conditioner_blocks.upsampler.proj_in.{groups[-1]}"""
																					lowerCAmelCase__	       =     re_prior_cond_proj_in.sub(A			,   A	)

														# keep original key
														else:
																					lowerCAmelCase__	       =     original_key

														lowerCAmelCase__	       =     replace_key(A	)

														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:
																					lowerCAmelCase__	       =     model_state_dict[F"""{key_prefix}.{key}"""]
																					print(F"""{original_key}-> {key} : \nshape {val.shape} and { value.shape}, do not match"""	)
																					lowerCAmelCase__	       =     original_key

														lowerCAmelCase__	       =     original_key
														lowerCAmelCase__	       =     value

							return new_dict


@torch.no_grad()
def  _snake_case       (					A=None			,   A=None	)						->   str:
							for file in MODEL_MAPPING[model_name]:
														if not os.path.isfile(F"""{pytorch_dump_folder_path}/{file.split("/"	)[-1]}"""	):
																					lowerCAmelCase__	       =     requests.get(F"""{PREFIX}{file}"""			,   allow_redirects=A	)
																					os.makedirs(F"""{pytorch_dump_folder_path}/"""			,   exist_ok=A	)
																					open(F"""{pytorch_dump_folder_path}/{file.split("/"	)[-1]}"""			,   '''wb'''	).write(r.content	)

							lowerCAmelCase__	       =     MODEL_MAPPING[model_name.split('''/'''	)[-1]]

							lowerCAmelCase__	       =     JukeboxConfig.from_pretrained(A	)
							lowerCAmelCase__	       =     JukeboxModel(A	)

							lowerCAmelCase__	       =     []
							lowerCAmelCase__	       =     {}
							for i, dict_name in enumerate(A	):
														lowerCAmelCase__	       =     torch.load(F"""{pytorch_dump_folder_path}/{dict_name.split("/"	)[-1]}"""	)['''model''']

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

														lowerCAmelCase__	       =     '''vqvae''' if i == 0 else F"""priors.{3 - i}"""
														lowerCAmelCase__	       =     fix_jukebox_keys(A			,   model.state_dict()			,   A			,   A	)
														weight_dict.append(A	)

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

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

							print(F"""Saving model {model_name} to {pytorch_dump_folder_path}"""	)
							model.save_pretrained(A	)

							return weight_dict


if __name__ == "__main__":
		__UpperCAmelCase       =							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.''',
		)
		__UpperCAmelCase       =							parser.parse_args()
		convert_openai_checkpoint(args.model_name, args.pytorch_dump_folder_path)