




import argparse
import json
import os

import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile

from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_switch_transformers_original_flax_checkpoint_to_pytorch import (
    rename_keys,
)
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
from transformers.utils.hub import convert_file_size_to_int







def 	_a      (						SCREAMING_SNAKE_CASE_							:				int      ,      SCREAMING_SNAKE_CASE_							:				Dict     ):
					if flax_key_tuple[-1] == "kernel" and flax_tensor.ndim == 3:
										# expert layer
										__lowerCAmelCase				   =       flax_key_tuple[:-1] + ("weight",)
										__lowerCAmelCase				   =       torch.permute(SCREAMING_SNAKE_CASE_      ,      (0, 2, 1)     )
					elif flax_key_tuple[-1] == "kernel" and ".".join(SCREAMING_SNAKE_CASE_     ):
										# linear layer
										__lowerCAmelCase				   =       flax_key_tuple[:-1] + ("weight",)
										__lowerCAmelCase				   =       flax_tensor.T
					elif flax_key_tuple[-1] in ["scale", "embedding"]:
										__lowerCAmelCase				   =       flax_key_tuple[:-1] + ("weight",)

					return flax_key_tuple, flax_tensor







def 	_a      (						SCREAMING_SNAKE_CASE_							:				Optional[Any]      ,      SCREAMING_SNAKE_CASE_							:				List[Any]      ,      SCREAMING_SNAKE_CASE_							:				List[str]     ):
					if "metadata" in layer:
										__lowerCAmelCase				   =       layer.split("metadata"     )
										__lowerCAmelCase				   =       "".join(split_layer[0]     )[:-1]
										__lowerCAmelCase				   =       [tuple(("metadata" + split_layer[1]).split("/"     )     )]
					elif "kvstore" in layer:
										__lowerCAmelCase				   =       layer.split("kvstore"     )
										__lowerCAmelCase				   =       "".join(split_layer[0]     )[:-1]
										__lowerCAmelCase				   =       [tuple(("kvstore" + split_layer[1]).split("/"     )     )]

					else:
										__lowerCAmelCase				   =       layer.split("/"     )
										__lowerCAmelCase				   =       "/".join(split_layer[:-1]     )
										__lowerCAmelCase				   =       (split_layer[-1],)

					if "kvstore/path" in layer:
										__lowerCAmelCase				   =       F"""{switch_checkpoint_path}/{checkpoint_info[layer]}"""
					elif "kvstore/driver" in layer:
										__lowerCAmelCase				   =       "file"
					else:
										__lowerCAmelCase				   =       checkpoint_info[layer]

					return curr_real_layer_name, split_layer, content







def 	_a      (						SCREAMING_SNAKE_CASE_							:				int      ,      SCREAMING_SNAKE_CASE_							:				List[str]     ):
					__lowerCAmelCase				   =       rename_keys(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       {}
					for k, v in current_block.items():
										__lowerCAmelCase				   =       v
					__lowerCAmelCase				   =       new_current_block
					torch.save(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )







def 	_a      (						SCREAMING_SNAKE_CASE_							:				List[Any]      ,      SCREAMING_SNAKE_CASE_							:				str      ,      SCREAMING_SNAKE_CASE_							:				Union[str, Any]      ,      SCREAMING_SNAKE_CASE_							:				int      ,      SCREAMING_SNAKE_CASE_							:				str = WEIGHTS_NAME     ):
					__lowerCAmelCase				   =       convert_file_size_to_int(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       []
					__lowerCAmelCase				   =       {}
					__lowerCAmelCase				   =       0
					__lowerCAmelCase				   =       0

					os.makedirs(SCREAMING_SNAKE_CASE_      ,      exist_ok=SCREAMING_SNAKE_CASE_     )
					with gfile.GFile(switch_checkpoint_path + "/checkpoint"      ,      "rb"     ) as fp:
										__lowerCAmelCase				   =       serialization.msgpack_restore(fp.read()     )["optimizer"]["target"]
										__lowerCAmelCase				   =       flatten_dict(SCREAMING_SNAKE_CASE_      ,      sep="/"     )

					__lowerCAmelCase				   =       {}
					for layer in checkpoint_info.keys():
										__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase				   =       get_key_and_tensorstore_dict(
										    SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )
										if curr_real_layer_name in all_layers:
															__lowerCAmelCase				   =       content
										else:
															__lowerCAmelCase				   =       {split_layer[-1]: content}

					for key in all_layers.keys():
										# open tensorstore file
										__lowerCAmelCase				   =       ts.open(unflatten_dict(all_layers[key]     )     ).result().read().result()
										__lowerCAmelCase				   =       torch.tensor(SCREAMING_SNAKE_CASE_     )
										__lowerCAmelCase				   =       raw_weights.numel() * dtype_byte_size(raw_weights.dtype     )

										# use the renaming pattern from the small conversion scripts
										__lowerCAmelCase   ,							__lowerCAmelCase				   =       rename_base_flax_keys(tuple(key.split("/"     )     )      ,      SCREAMING_SNAKE_CASE_     )
										__lowerCAmelCase				   =       "/".join(SCREAMING_SNAKE_CASE_     )

										# If this weight is going to tip up over the maximal size, we split.
										if current_block_size + weight_size > max_shard_size:
															__lowerCAmelCase				   =       os.path.join(
															    SCREAMING_SNAKE_CASE_      ,      weights_name.replace(".bin"      ,      F"""-{len(SCREAMING_SNAKE_CASE_     )+1:05d}-of-???.bin"""     )     )
															rename_and_save_block(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )
															sharded_state_dicts.append(current_block.keys()     )
															del current_block
															__lowerCAmelCase				   =       {}
															__lowerCAmelCase				   =       0

										__lowerCAmelCase				   =       raw_weights.to(getattr(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )     )
										current_block_size += weight_size
										total_size += weight_size

					# Add the last block
					__lowerCAmelCase				   =       os.path.join(SCREAMING_SNAKE_CASE_      ,      weights_name.replace(".bin"      ,      F"""-{len(SCREAMING_SNAKE_CASE_     )+1:05d}-of-???.bin"""     )     )
					rename_and_save_block(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )
					sharded_state_dicts.append(current_block.keys()     )

					# If we only have one shard, we return it
					if len(SCREAMING_SNAKE_CASE_     ) == 1:
										return {weights_name: sharded_state_dicts[0]}, None

					# Otherwise, let's build the index
					__lowerCAmelCase				   =       {}
					__lowerCAmelCase				   =       {}
					for idx, shard in enumerate(SCREAMING_SNAKE_CASE_     ):
										__lowerCAmelCase				   =       weights_name.replace(
										    ".bin"      ,      F"""-{idx+1:05d}-of-{len(SCREAMING_SNAKE_CASE_     ):05d}.bin"""     )  # len(sharded_state_dicts):05d}
										__lowerCAmelCase				   =       os.path.join(SCREAMING_SNAKE_CASE_      ,      weights_name.replace(".bin"      ,      F"""-{idx+1:05d}-of-???.bin"""     )     )
										os.rename(SCREAMING_SNAKE_CASE_      ,      os.path.join(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )     )
										__lowerCAmelCase				   =       shard
										for key in shard:
															__lowerCAmelCase				   =       shard_file

    # Add the metadata
					__lowerCAmelCase				   =       {"total_size": total_size}
					__lowerCAmelCase				   =       {"metadata": metadata, "weight_map": weight_map}

					with open(os.path.join(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )      ,      "w"      ,      encoding="utf-8"     ) as f:
										__lowerCAmelCase				   =       json.dumps(SCREAMING_SNAKE_CASE_      ,      indent=2      ,      sort_keys=SCREAMING_SNAKE_CASE_     ) + "\n"
										f.write(SCREAMING_SNAKE_CASE_     )

					return metadata, index


if __name__ == "__main__":
					UpperCamelCase__    			=			argparse.ArgumentParser()
					# Required parameters
					parser.add_argument(
					    """--switch_t5x_checkpoint_path""",
					    default="""/mnt/disks/disk_switch/original_checkpoints/switch-xxl-128/checkpoint_634600""",
					    type=str,
					    required=False,
					    help="""Path to a directory containing a folder per layer. Follows the original Google format.""",
					)
					parser.add_argument("""--max_shard_size""", default="""10GB""", required=False, help="""Max shard size""")
					parser.add_argument("""--dtype""", default="""bfloat16""", type=str, required=False, help="""dtype of the saved model""")
					parser.add_argument(
					    """--pytorch_dump_folder_path""",
					    default="""/mnt/disks/disk_switch/original_checkpoints/switch-xxl-128-converted""",
					    type=str,
					    required=False,
					    help="""Path to the output pytorch model.""",
					)
					UpperCamelCase__    			=			parser.parse_args()
					shard_on_the_fly(
					    args.switch_tax_checkpoint_path,
					    args.pytorch_dump_folder_path,
					    args.max_shard_size,
					    args.dtype,
					)







def 	_a      (						):
					from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration, TaTokenizer

					__lowerCAmelCase				   =       SwitchTransformersConfig.from_pretrained("google/switch-base-8"     )
					config.save_pretrained("/home/arthur_huggingface_co/transformers/switch_converted"     )
					__lowerCAmelCase				   =       SwitchTransformersForConditionalGeneration.from_pretrained(
					    "/home/arthur_huggingface_co/transformers/switch_converted"      ,      device_map="auto"     )

					__lowerCAmelCase				   =       TaTokenizer.from_pretrained("t5-small"     )
					__lowerCAmelCase				   =       "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."

					__lowerCAmelCase				   =       tokenizer(SCREAMING_SNAKE_CASE_      ,      return_tensors="pt"     ).input_ids
					__lowerCAmelCase				   =       model.generate(SCREAMING_SNAKE_CASE_      ,      decoder_start_token_id=0     )
					print(tokenizer.decode(out[0]     )     )










import argparse
import os
import re

import packaging.version


UpperCamelCase__    			=			"""examples/"""
UpperCamelCase__    			=			{
    """examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
    """init""": (re.compile(R"""^__version__\s+=\s+\"([^\"]+)\"\s*$""", re.MULTILINE), """__version__ = \"VERSION\"\n"""),
    """setup""": (re.compile(R"""^(\s*)version\s*=\s*\"[^\"]+\",""", re.MULTILINE), R"""\1version=\"VERSION\","""),
    """doc""": (re.compile(R"""^(\s*)release\s*=\s*\"[^\"]+\"$""", re.MULTILINE), """release = \"VERSION\"\n"""),
}
UpperCamelCase__    			=			{
    """init""": """src/transformers/__init__.py""",
    """setup""": """setup.py""",
}
UpperCamelCase__    			=			"""README.md"""







def 	_a      (						SCREAMING_SNAKE_CASE_							:				Optional[int]      ,      SCREAMING_SNAKE_CASE_							:				Any      ,      SCREAMING_SNAKE_CASE_							:				List[str]     ):
					with open(SCREAMING_SNAKE_CASE_      ,      "r"      ,      encoding="utf-8"      ,      newline="\n"     ) as f:
										__lowerCAmelCase				   =       f.read()
					__lowerCAmelCase   ,							__lowerCAmelCase				   =       REPLACE_PATTERNS[pattern]
					__lowerCAmelCase				   =       replace.replace("VERSION"      ,      SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       re_pattern.sub(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )
					with open(SCREAMING_SNAKE_CASE_      ,      "w"      ,      encoding="utf-8"      ,      newline="\n"     ) as f:
										f.write(SCREAMING_SNAKE_CASE_     )







def 	_a      (						SCREAMING_SNAKE_CASE_							:				List[Any]     ):
					for folder, directories, fnames in os.walk(SCREAMING_SNAKE_CASE_     ):
										# Removing some of the folders with non-actively maintained examples from the walk
										if "research_projects" in directories:
															directories.remove("research_projects"     )
										if "legacy" in directories:
															directories.remove("legacy"     )
										for fname in fnames:
															if fname.endswith(".py"     ):
																				update_version_in_file(os.path.join(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )      ,      SCREAMING_SNAKE_CASE_      ,      pattern="examples"     )







def 	_a      (						SCREAMING_SNAKE_CASE_							:				Tuple      ,      SCREAMING_SNAKE_CASE_							:				Optional[int]=False     ):
					for pattern, fname in REPLACE_FILES.items():
										update_version_in_file(SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_      ,      SCREAMING_SNAKE_CASE_     )
					if not patch:
										update_version_in_examples(SCREAMING_SNAKE_CASE_     )







def 	_a      (						):
					__lowerCAmelCase				   =       "🤗 Transformers currently provides the following architectures"
					__lowerCAmelCase				   =       "1. Want to contribute a new model?"
					with open(SCREAMING_SNAKE_CASE_      ,      "r"      ,      encoding="utf-8"      ,      newline="\n"     ) as f:
										__lowerCAmelCase				   =       f.readlines()

					# Find the start of the list.
					__lowerCAmelCase				   =       0
					while not lines[start_index].startswith(_start_prompt     ):
										start_index += 1
					start_index += 1

					__lowerCAmelCase				   =       start_index
					# Update the lines in the model list.
					while not lines[index].startswith(_end_prompt     ):
										if lines[index].startswith("1."     ):
															__lowerCAmelCase				   =       lines[index].replace(
															    "https://huggingface.co/docs/transformers/main/model_doc"      ,      "https://huggingface.co/docs/transformers/model_doc"      ,      )
										index += 1

					with open(SCREAMING_SNAKE_CASE_      ,      "w"      ,      encoding="utf-8"      ,      newline="\n"     ) as f:
										f.writelines(SCREAMING_SNAKE_CASE_     )







def 	_a      (						):
					with open(REPLACE_FILES["init"]      ,      "r"     ) as f:
										__lowerCAmelCase				   =       f.read()
					__lowerCAmelCase				   =       REPLACE_PATTERNS["init"][0].search(SCREAMING_SNAKE_CASE_     ).groups()[0]
					return packaging.version.parse(SCREAMING_SNAKE_CASE_     )







def 	_a      (						SCREAMING_SNAKE_CASE_							:				List[Any]=False     ):
					__lowerCAmelCase				   =       get_version()
					if patch and default_version.is_devrelease:
										raise ValueError("Can't create a patch version from the dev branch, checkout a released version!"     )
					if default_version.is_devrelease:
										__lowerCAmelCase				   =       default_version.base_version
					elif patch:
										__lowerCAmelCase				   =       F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
					else:
										__lowerCAmelCase				   =       F"""{default_version.major}.{default_version.minor + 1}.0"""

					# Now let's ask nicely if that's the right one.
					__lowerCAmelCase				   =       input(F"""Which version are you releasing? [{default_version}]"""     )
					if len(SCREAMING_SNAKE_CASE_     ) == 0:
										__lowerCAmelCase				   =       default_version

					print(F"""Updating version to {version}."""     )
					global_version_update(SCREAMING_SNAKE_CASE_      ,      patch=SCREAMING_SNAKE_CASE_     )
					if not patch:
										print("Cleaning main README, don't forget to run `make fix-copies`."     )
										clean_main_ref_in_model_list()







def 	_a      (						):
					__lowerCAmelCase				   =       get_version()
					__lowerCAmelCase				   =       F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
					__lowerCAmelCase				   =       current_version.base_version

					# Check with the user we got that right.
					__lowerCAmelCase				   =       input(F"""Which version are we developing now? [{dev_version}]"""     )
					if len(SCREAMING_SNAKE_CASE_     ) == 0:
										__lowerCAmelCase				   =       dev_version

					print(F"""Updating version to {version}."""     )
					global_version_update(SCREAMING_SNAKE_CASE_     )
					print("Cleaning main README, don't forget to run `make fix-copies`."     )
					clean_main_ref_in_model_list()


if __name__ == "__main__":
					UpperCamelCase__    			=			argparse.ArgumentParser()
					parser.add_argument("""--post_release""", action="""store_true""", help="""Whether this is pre or post release.""")
					parser.add_argument("""--patch""", action="""store_true""", help="""Whether or not this is a patch release.""")
					UpperCamelCase__    			=			parser.parse_args()
					if not args.post_release:
										pre_release_work(patch=args.patch)
					elif args.patch:
										print("""Nothing to do after a patch :-)""")
					else:
										post_release_work()




