





"""simple docstring"""


import argparse

from tax import checkpoints

from transformers import FlaxTaForConditionalGeneration, TaConfig

def     UpperCamelCase       (SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    ):
						UpperCamelCase							:		List[Any]							      = TaConfig.from_pretrained(SCREAMING_SNAKE_CASE    )
						UpperCamelCase							:		Dict							      = FlaxTaForConditionalGeneration(config=SCREAMING_SNAKE_CASE    )
						UpperCamelCase							:		int							      = checkpoints.load_tax_checkpoint(SCREAMING_SNAKE_CASE    )

						UpperCamelCase							:		List[Any]							      = """wi_0""" in tax_model["""target"""]["""encoder"""]["""layers_0"""]["""mlp"""]

						# Encoder
						for layer_index in range(config.num_layers    ):
												UpperCamelCase							:		List[str]							      = f"""layers_{str(SCREAMING_SNAKE_CASE    )}"""

												# Self-Attention
												UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""key"""]["""kernel"""]
												UpperCamelCase							:		Union[str, Any]							      = tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""out"""]["""kernel"""]
												UpperCamelCase							:		Optional[int]							      = tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""query"""]["""kernel"""]
												UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""value"""]["""kernel"""]

												# Layer Normalization
												UpperCamelCase							:		Any							      = tax_model["""target"""]["""encoder"""][layer_name]["""pre_attention_layer_norm"""]["""scale"""]

												if split_mlp_wi:
																		UpperCamelCase							:		List[Any]							      = tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
																		UpperCamelCase							:		str							      = tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
												else:
																		UpperCamelCase							:		Optional[int]							      = tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

												UpperCamelCase							:		Optional[int]							      = tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

												# Layer Normalization
												UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""encoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

												# Assigning
												UpperCamelCase							:		Any							      = tax_attention_key
												UpperCamelCase							:		Optional[Any]							      = tax_attention_out
												UpperCamelCase							:		Optional[int]							      = tax_attention_query
												UpperCamelCase							:		Tuple							      = tax_attention_value

												UpperCamelCase							:		int							      = tax_attention_layer_norm

												if split_mlp_wi:
																		UpperCamelCase							:		Optional[Any]							      = tax_mlp_wi_a
																		UpperCamelCase							:		int							      = tax_mlp_wi_a
												else:
																		UpperCamelCase							:		Optional[int]							      = tax_mlp_wi

												UpperCamelCase							:		List[Any]							      = tax_mlp_wo
												UpperCamelCase							:		Tuple							      = tax_mlp_layer_norm

						# Only for layer 0:
						UpperCamelCase							:		Any							      = tax_model["""target"""]["""encoder"""]["""relpos_bias"""]["""rel_embedding"""].T
						UpperCamelCase							:		Union[str, Any]							      = tax_encoder_rel_embedding

						# Assigning
						UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""encoder"""]["""encoder_norm"""]["""scale"""]
						UpperCamelCase							:		Tuple							      = tax_encoder_norm

						# Decoder
						for layer_index in range(config.num_decoder_layers    ):
												UpperCamelCase							:		Tuple							      = f"""layers_{str(SCREAMING_SNAKE_CASE    )}"""

												# Self-Attention
												UpperCamelCase							:		Optional[int]							      = tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""key"""]["""kernel"""]
												UpperCamelCase							:		Optional[int]							      = tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""out"""]["""kernel"""]
												UpperCamelCase							:		int							      = tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""query"""]["""kernel"""]
												UpperCamelCase							:		Tuple							      = tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""value"""]["""kernel"""]

												# Layer Normalization
												UpperCamelCase							:		Union[str, Any]							      = tax_model["""target"""]["""decoder"""][layer_name]["""pre_self_attention_layer_norm"""][
												    """scale"""
												]

												# Encoder-Decoder-Attention
												UpperCamelCase							:		Optional[Any]							      = tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""key"""][
												    """kernel"""
												]
												UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""out"""][
												    """kernel"""
												]
												UpperCamelCase							:		Optional[Any]							      = tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""query"""][
												    """kernel"""
												]
												UpperCamelCase							:		List[Any]							      = tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""value"""][
												    """kernel"""
												]

												# Layer Normalization
												UpperCamelCase							:		List[Any]							      = tax_model["""target"""]["""decoder"""][layer_name]["""pre_cross_attention_layer_norm"""]["""scale"""]

												# MLP
												if split_mlp_wi:
																		UpperCamelCase							:		int							      = tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
																		UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
												else:
																		UpperCamelCase							:		Optional[Any]							      = tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

												UpperCamelCase							:		Any							      = tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

												# Layer Normalization
												UpperCamelCase							:		Optional[int]							      = tax_model["""target"""]["""decoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

												# Assigning
												UpperCamelCase							:		List[str]							      = tax_attention_key
												UpperCamelCase							:		Any							      = tax_attention_out
												UpperCamelCase							:		Tuple							      = tax_attention_query
												UpperCamelCase							:		Union[str, Any]							      = tax_attention_value

												UpperCamelCase							:		Any							      = tax_pre_attention_layer_norm

												UpperCamelCase							:		Optional[int]							      = tax_enc_dec_attention_key
												UpperCamelCase							:		List[Any]							      = tax_enc_dec_attention_out
												UpperCamelCase							:		List[str]							      = tax_enc_dec_attention_query
												UpperCamelCase							:		List[str]							      = tax_enc_dec_attention_value

												UpperCamelCase							:		Optional[Any]							      = tax_cross_layer_norm

												if split_mlp_wi:
																		UpperCamelCase							:		List[Any]							      = tax_mlp_wi_a
																		UpperCamelCase							:		Optional[Any]							      = tax_mlp_wi_a
												else:
																		UpperCamelCase							:		Tuple							      = tax_mlp_wi

												UpperCamelCase							:		List[str]							      = tax_mlp_wo

												UpperCamelCase							:		Optional[int]							      = txa_mlp_layer_norm

						# Decoder Normalization
						UpperCamelCase							:		Any							      = tax_model["""target"""]["""decoder"""]["""decoder_norm"""]["""scale"""]
						UpperCamelCase							:		int							      = txa_decoder_norm

						# Only for layer 0:
						UpperCamelCase							:		Any							      = tax_model["""target"""]["""decoder"""]["""relpos_bias"""]["""rel_embedding"""].T
						UpperCamelCase							:		Any							      = tax_decoder_rel_embedding

						# Token Embeddings
						UpperCamelCase							:		Dict							      = tax_model["""target"""]["""token_embedder"""]["""embedding"""]
						UpperCamelCase							:		Dict							      = txa_token_embeddings

						# LM Head (only in v1.1 checkpoints)
						if "logits_dense" in tax_model["target"]["decoder"]:
												UpperCamelCase							:		List[str]							      = tax_model["""target"""]["""decoder"""]["""logits_dense"""]["""kernel"""]

						flax_model.save_pretrained(SCREAMING_SNAKE_CASE    )
						print("""T5X Model was sucessfully converted!"""    )


if __name__ == "__main__":
		__magic_name__					:				Dict	= argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    """--t5x_checkpoint_path""", default=None, type=str, required=True, help="""Path the TX5 checkpoint."""
		)
		parser.add_argument("""--config_name""", default=None, type=str, required=True, help="""Config name of T5 model.""")
		parser.add_argument(
		    """--flax_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output FLAX model."""
		)
		__magic_name__					:				Dict	= parser.parse_args()
		convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)










"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__magic_name__					:				str	= {"""configuration_levit""": ["""LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LevitConfig""", """LevitOnnxConfig"""]}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__					:				Optional[int]	= ["""LevitFeatureExtractor"""]
		__magic_name__					:				Any	= ["""LevitImageProcessor"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__					:				List[Any]	= [
		    """LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """LevitForImageClassification""",
		    """LevitForImageClassificationWithTeacher""",
		    """LevitModel""",
		    """LevitPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig, LevitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_levit import LevitFeatureExtractor
				from .image_processing_levit import LevitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_levit import (
				    LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LevitForImageClassification,
				    LevitForImageClassificationWithTeacher,
				    LevitModel,
				    LevitPreTrainedModel,
				)
else:
		import sys

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



