
'''simple docstring'''



import argparse

import torch

from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging


logging.set_verbosity_info()
_lowercase    =		logging.get_logger(__name__)

_lowercase    =		[
    ["""attention""", """attn"""],
    ["""encoder_attention""", """encoder_attn"""],
    ["""q_lin""", """q_proj"""],
    ["""k_lin""", """k_proj"""],
    ["""v_lin""", """v_proj"""],
    ["""out_lin""", """out_proj"""],
    ["""norm_embeddings""", """layernorm_embedding"""],
    ["""position_embeddings""", """embed_positions"""],
    ["""embeddings""", """embed_tokens"""],
    ["""ffn.lin""", """fc"""],
]


def A				(__lowerCamelCase				:Dict		):
						if k == "embeddings.weight":
												return "shared.weight"

						for parlai_name, hf_name in PATTERNS:
												_lowerCAmelCase  						=			k.replace(__lowerCamelCase			,     __lowerCamelCase		)

						if k.startswith("""encoder"""		):
												_lowerCAmelCase  						=			k.replace(""".attn"""			,     """.self_attn"""		)
												_lowerCAmelCase  						=			k.replace("""norm1"""			,     """self_attn_layer_norm"""		)
												_lowerCAmelCase  						=			k.replace("""norm2"""			,     """final_layer_norm"""		)
						elif k.startswith("""decoder"""		):
												_lowerCAmelCase  						=			k.replace("""norm1"""			,     """self_attn_layer_norm"""		)
												_lowerCAmelCase  						=			k.replace("""norm2"""			,     """encoder_attn_layer_norm"""		)
												_lowerCAmelCase  						=			k.replace("""norm3"""			,     """final_layer_norm"""		)
						return k


def A				(__lowerCamelCase				:Union[str, Any]		):
						_lowerCAmelCase  						=			[
						    """model.encoder.layernorm_embedding.weight""",
						    """model.encoder.layernorm_embedding.bias""",
						    """model.decoder.layernorm_embedding.weight""",
						    """model.decoder.layernorm_embedding.bias""",
						]
						for k in keys:
												_lowerCAmelCase  						=			sd.pop(__lowerCamelCase		)
												_lowerCAmelCase  						=			k.replace("""layernorm_embedding"""			,     """layer_norm"""		)
												assert new_k not in sd
												_lowerCAmelCase  						=			v


_lowercase    =		["""START"""]


@torch.no_grad()
def A				(__lowerCamelCase				:str			,     __lowerCamelCase				:str			,     __lowerCamelCase				:Any		):
						_lowerCAmelCase  						=			torch.load(__lowerCamelCase			,     map_location="""cpu"""		)
						_lowerCAmelCase  						=			model["""model"""]
						_lowerCAmelCase  						=			BlenderbotConfig.from_json_file(__lowerCamelCase		)
						_lowerCAmelCase  						=			BlenderbotForConditionalGeneration(__lowerCamelCase		)
						_lowerCAmelCase  						=			m.model.state_dict().keys()
						_lowerCAmelCase  						=			[]
						_lowerCAmelCase  						=			{}
						for k, v in sd.items():
												if k in IGNORE_KEYS:
																		continue

												_lowerCAmelCase  						=			rename_state_dict_key(__lowerCamelCase		)
												if new_k not in valid_keys:
																		failures.append([k, new_k]		)
												else:
																		_lowerCAmelCase  						=			v
						if cfg.normalize_before:  # Blenderbot-3B checkpoints. Rename layernorm_embedding -> layer_norm
												rename_layernorm_keys(__lowerCamelCase		)
						m.model.load_state_dict(__lowerCamelCase			,     strict=__lowerCamelCase		)
						m.half()
						m.save_pretrained(__lowerCamelCase		)


if __name__ == "__main__":
						_lowercase    =		argparse.ArgumentParser()
						# Required parameters
						parser.add_argument("""--src_path""", type=str, help="""like blenderbot-model.bin""")
						parser.add_argument("""--save_dir""", default="""hf_blenderbot""", type=str, help="""Where to save converted model.""")
						parser.add_argument(
						    """--hf_config_json""", default="""blenderbot-3b-config.json""", type=str, help="""Path to config to use"""
						)
						_lowercase    =		parser.parse_args()
						convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)



'''simple docstring'''



# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

_lowercase    =		"""2.13.1"""

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("""3.7"""):
						raise ImportWarning(
						    """To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."""
						)

if version.parse(pyarrow.__version__).major < 8:
						raise ImportWarning(
						    """To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"""
						    """If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."""
						)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

_lowercase    =		concatenate_datasets
_lowercase    =		DownloadConfig
_lowercase    =		DownloadManager
_lowercase    =		DownloadMode
_lowercase    =		DownloadConfig
_lowercase    =		DownloadMode
_lowercase    =		DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager
