"""simple docstring"""


import argparse

import torch

from transformers import RoFormerConfig, RoFormerForMaskedLM, load_tf_weights_in_roformer
from transformers.utils import logging


logging.set_verbosity_info()







def        __a (		A     ,					A     ,					A   ):






     '''simple docstring'''



     lowercase__								=				RoFormerConfig.from_json_file(__SCREAMING_SNAKE_CASE   )
     print(f'''Building PyTorch model from configuration: {config}'''   )
     lowercase__								=				RoFormerForMaskedLM(__SCREAMING_SNAKE_CASE   )

     # Load weights from tf checkpoint
     load_tf_weights_in_roformer(__SCREAMING_SNAKE_CASE     ,					__SCREAMING_SNAKE_CASE     ,					__SCREAMING_SNAKE_CASE   )

     # Save pytorch-model
     print(f'''Save PyTorch model to {pytorch_dump_path}'''   )
     torch.save(model.state_dict()     ,					__SCREAMING_SNAKE_CASE     ,					_use_new_zipfile_serialization=__SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
 lowerCAmelCase_:       Union[str, Any]			     =       argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
 )
 parser.add_argument(
     "--bert_config_file",
     default=None,
     type=str,
     required=True,
     help=(
         "The config json file corresponding to the pre-trained BERT model. \n"
         "This specifies the model architecture."
     ),
 )
 parser.add_argument(
     "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
 )
 lowerCAmelCase_:       int			     =       parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)






'''simple docstring'''







from typing import TYPE_CHECKING

from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available


_lowercase					:    Tuple       				=			{
    "configuration_utils": ["GenerationConfig"],
    "streamers": ["TextIteratorStreamer", "TextStreamer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase					:    List[Any]       				=			[
							    "Constraint",
							    "ConstraintListState",
							    "DisjunctiveConstraint",
							    "PhrasalConstraint",
							]
							_lowercase					:    int       				=			[
							    "BeamHypotheses",
							    "BeamScorer",
							    "BeamSearchScorer",
							    "ConstrainedBeamSearchScorer",
							]
							_lowercase					:    str       				=			[
							    "EpsilonLogitsWarper",
							    "EtaLogitsWarper",
							    "ForcedBOSTokenLogitsProcessor",
							    "ForcedEOSTokenLogitsProcessor",
							    "HammingDiversityLogitsProcessor",
							    "InfNanRemoveLogitsProcessor",
							    "LogitsProcessor",
							    "LogitsProcessorList",
							    "LogitsWarper",
							    "MinLengthLogitsProcessor",
							    "MinNewTokensLengthLogitsProcessor",
							    "NoBadWordsLogitsProcessor",
							    "NoRepeatNGramLogitsProcessor",
							    "PrefixConstrainedLogitsProcessor",
							    "RepetitionPenaltyLogitsProcessor",
							    "SequenceBiasLogitsProcessor",
							    "EncoderRepetitionPenaltyLogitsProcessor",
							    "TemperatureLogitsWarper",
							    "TopKLogitsWarper",
							    "TopPLogitsWarper",
							    "TypicalLogitsWarper",
							    "EncoderNoRepeatNGramLogitsProcessor",
							    "ExponentialDecayLengthPenalty",
							    "LogitNormalization",
							]
							_lowercase					:    int       				=			[
							    "MaxNewTokensCriteria",
							    "MaxLengthCriteria",
							    "MaxTimeCriteria",
							    "StoppingCriteria",
							    "StoppingCriteriaList",
							    "validate_stopping_criteria",
							]
							_lowercase					:    List[Any]       				=			[
							    "GenerationMixin",
							    "top_k_top_p_filtering",
							    "GreedySearchEncoderDecoderOutput",
							    "GreedySearchDecoderOnlyOutput",
							    "SampleEncoderDecoderOutput",
							    "SampleDecoderOnlyOutput",
							    "BeamSearchEncoderDecoderOutput",
							    "BeamSearchDecoderOnlyOutput",
							    "BeamSampleEncoderDecoderOutput",
							    "BeamSampleDecoderOnlyOutput",
							    "ContrastiveSearchEncoderDecoderOutput",
							    "ContrastiveSearchDecoderOnlyOutput",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase					:    Optional[Any]       				=			[
							    "TFForcedBOSTokenLogitsProcessor",
							    "TFForcedEOSTokenLogitsProcessor",
							    "TFLogitsProcessor",
							    "TFLogitsProcessorList",
							    "TFLogitsWarper",
							    "TFMinLengthLogitsProcessor",
							    "TFNoBadWordsLogitsProcessor",
							    "TFNoRepeatNGramLogitsProcessor",
							    "TFRepetitionPenaltyLogitsProcessor",
							    "TFTemperatureLogitsWarper",
							    "TFTopKLogitsWarper",
							    "TFTopPLogitsWarper",
							    "TFForceTokensLogitsProcessor",
							    "TFSuppressTokensAtBeginLogitsProcessor",
							    "TFSuppressTokensLogitsProcessor",
							]
							_lowercase					:    List[Any]       				=			[
							    "TFGenerationMixin",
							    "tf_top_k_top_p_filtering",
							    "TFGreedySearchDecoderOnlyOutput",
							    "TFGreedySearchEncoderDecoderOutput",
							    "TFSampleEncoderDecoderOutput",
							    "TFSampleDecoderOnlyOutput",
							    "TFBeamSearchEncoderDecoderOutput",
							    "TFBeamSearchDecoderOnlyOutput",
							    "TFBeamSampleEncoderDecoderOutput",
							    "TFBeamSampleDecoderOnlyOutput",
							    "TFContrastiveSearchEncoderDecoderOutput",
							    "TFContrastiveSearchDecoderOnlyOutput",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase					:    List[str]       				=			[
							    "FlaxForcedBOSTokenLogitsProcessor",
							    "FlaxForcedEOSTokenLogitsProcessor",
							    "FlaxLogitsProcessor",
							    "FlaxLogitsProcessorList",
							    "FlaxLogitsWarper",
							    "FlaxMinLengthLogitsProcessor",
							    "FlaxTemperatureLogitsWarper",
							    "FlaxTopKLogitsWarper",
							    "FlaxTopPLogitsWarper",
							]
							_lowercase					:    Optional[int]       				=			[
							    "FlaxGenerationMixin",
							    "FlaxGreedySearchOutput",
							    "FlaxSampleOutput",
							    "FlaxBeamSearchOutput",
							]

if TYPE_CHECKING:
							from .configuration_utils import GenerationConfig
							from .streamers import TextIteratorStreamer, TextStreamer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
														from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
														from .logits_process import (
														    EncoderNoRepeatNGramLogitsProcessor,
														    EncoderRepetitionPenaltyLogitsProcessor,
														    EpsilonLogitsWarper,
														    EtaLogitsWarper,
														    ExponentialDecayLengthPenalty,
														    ForcedBOSTokenLogitsProcessor,
														    ForcedEOSTokenLogitsProcessor,
														    HammingDiversityLogitsProcessor,
														    InfNanRemoveLogitsProcessor,
														    LogitNormalization,
														    LogitsProcessor,
														    LogitsProcessorList,
														    LogitsWarper,
														    MinLengthLogitsProcessor,
														    MinNewTokensLengthLogitsProcessor,
														    NoBadWordsLogitsProcessor,
														    NoRepeatNGramLogitsProcessor,
														    PrefixConstrainedLogitsProcessor,
														    RepetitionPenaltyLogitsProcessor,
														    SequenceBiasLogitsProcessor,
														    TemperatureLogitsWarper,
														    TopKLogitsWarper,
														    TopPLogitsWarper,
														    TypicalLogitsWarper,
														)
														from .stopping_criteria import (
														    MaxLengthCriteria,
														    MaxNewTokensCriteria,
														    MaxTimeCriteria,
														    StoppingCriteria,
														    StoppingCriteriaList,
														    validate_stopping_criteria,
														)
														from .utils import (
														    BeamSampleDecoderOnlyOutput,
														    BeamSampleEncoderDecoderOutput,
														    BeamSearchDecoderOnlyOutput,
														    BeamSearchEncoderDecoderOutput,
														    ContrastiveSearchDecoderOnlyOutput,
														    ContrastiveSearchEncoderDecoderOutput,
														    GenerationMixin,
														    GreedySearchDecoderOnlyOutput,
														    GreedySearchEncoderDecoderOutput,
														    SampleDecoderOnlyOutput,
														    SampleEncoderDecoderOutput,
														    top_k_top_p_filtering,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tf_logits_process import (
														    TFForcedBOSTokenLogitsProcessor,
														    TFForcedEOSTokenLogitsProcessor,
														    TFForceTokensLogitsProcessor,
														    TFLogitsProcessor,
														    TFLogitsProcessorList,
														    TFLogitsWarper,
														    TFMinLengthLogitsProcessor,
														    TFNoBadWordsLogitsProcessor,
														    TFNoRepeatNGramLogitsProcessor,
														    TFRepetitionPenaltyLogitsProcessor,
														    TFSuppressTokensAtBeginLogitsProcessor,
														    TFSuppressTokensLogitsProcessor,
														    TFTemperatureLogitsWarper,
														    TFTopKLogitsWarper,
														    TFTopPLogitsWarper,
														)
														from .tf_utils import (
														    TFBeamSampleDecoderOnlyOutput,
														    TFBeamSampleEncoderDecoderOutput,
														    TFBeamSearchDecoderOnlyOutput,
														    TFBeamSearchEncoderDecoderOutput,
														    TFContrastiveSearchDecoderOnlyOutput,
														    TFContrastiveSearchEncoderDecoderOutput,
														    TFGenerationMixin,
														    TFGreedySearchDecoderOnlyOutput,
														    TFGreedySearchEncoderDecoderOutput,
														    TFSampleDecoderOnlyOutput,
														    TFSampleEncoderDecoderOutput,
														    tf_top_k_top_p_filtering,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .flax_logits_process import (
														    FlaxForcedBOSTokenLogitsProcessor,
														    FlaxForcedEOSTokenLogitsProcessor,
														    FlaxLogitsProcessor,
														    FlaxLogitsProcessorList,
														    FlaxLogitsWarper,
														    FlaxMinLengthLogitsProcessor,
														    FlaxTemperatureLogitsWarper,
														    FlaxTopKLogitsWarper,
														    FlaxTopPLogitsWarper,
														)
														from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
else:
							import sys

							_lowercase					:    Tuple       				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



