



import argparse

from tax import checkpoints

from transformers import FlaxTaForConditionalGeneration, TaConfig







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       str:



						'''simple docstring'''






						UpperCAmelCase_     							=     TaConfig.from_pretrained(__UpperCAmelCase	)
						UpperCAmelCase_     							=     FlaxTaForConditionalGeneration(config=__UpperCAmelCase	)
						UpperCAmelCase_     							=     checkpoints.load_tax_checkpoint(__UpperCAmelCase	)

						UpperCAmelCase_     							=     '''wi_0''' in tax_model['''target''']['''encoder''']['''layers_0''']['''mlp''']

						# Encoder
						for layer_index in range(config.num_layers	):
												UpperCAmelCase_     							=     f"layers_{str(__UpperCAmelCase	)}"

												# Self-Attention
												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''key''']['''kernel''']
												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''out''']['''kernel''']
												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''query''']['''kernel''']
												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''value''']['''kernel''']

												# Layer Normalization
												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''pre_attention_layer_norm''']['''scale''']

												if split_mlp_wi:
																		UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi_0''']['''kernel''']
																		UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi_1''']['''kernel''']
												else:
																		UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi''']['''kernel''']

												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wo''']['''kernel''']

												# Layer Normalization
												UpperCAmelCase_     							=     tax_model['''target''']['''encoder'''][layer_name]['''pre_mlp_layer_norm''']['''scale''']

												# Assigning
												UpperCAmelCase_     							=     tax_attention_key
												UpperCAmelCase_     							=     tax_attention_out
												UpperCAmelCase_     							=     tax_attention_query
												UpperCAmelCase_     							=     tax_attention_value

												UpperCAmelCase_     							=     tax_attention_layer_norm

												if split_mlp_wi:
																		UpperCAmelCase_     							=     tax_mlp_wi_a
																		UpperCAmelCase_     							=     tax_mlp_wi_a
												else:
																		UpperCAmelCase_     							=     tax_mlp_wi

												UpperCAmelCase_     							=     tax_mlp_wo
												UpperCAmelCase_     							=     tax_mlp_layer_norm

						# Only for layer 0:
						UpperCAmelCase_     							=     tax_model['''target''']['''encoder''']['''relpos_bias''']['''rel_embedding'''].T
						UpperCAmelCase_     							=     tax_encoder_rel_embedding

						# Assigning
						UpperCAmelCase_     							=     tax_model['''target''']['''encoder''']['''encoder_norm''']['''scale''']
						UpperCAmelCase_     							=     tax_encoder_norm

						# Decoder
						for layer_index in range(config.num_decoder_layers	):
												UpperCAmelCase_     							=     f"layers_{str(__UpperCAmelCase	)}"

												# Self-Attention
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''key''']['''kernel''']
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''out''']['''kernel''']
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''query''']['''kernel''']
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''value''']['''kernel''']

												# Layer Normalization
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''pre_self_attention_layer_norm'''][
												    '''scale'''
												]

												# Encoder-Decoder-Attention
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''key'''][
												    '''kernel'''
												]
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''out'''][
												    '''kernel'''
												]
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''query'''][
												    '''kernel'''
												]
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''value'''][
												    '''kernel'''
												]

												# Layer Normalization
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''pre_cross_attention_layer_norm''']['''scale''']

												# MLP
												if split_mlp_wi:
																		UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi_0''']['''kernel''']
																		UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi_1''']['''kernel''']
												else:
																		UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi''']['''kernel''']

												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wo''']['''kernel''']

												# Layer Normalization
												UpperCAmelCase_     							=     tax_model['''target''']['''decoder'''][layer_name]['''pre_mlp_layer_norm''']['''scale''']

												# Assigning
												UpperCAmelCase_     							=     tax_attention_key
												UpperCAmelCase_     							=     tax_attention_out
												UpperCAmelCase_     							=     tax_attention_query
												UpperCAmelCase_     							=     tax_attention_value

												UpperCAmelCase_     							=     tax_pre_attention_layer_norm

												UpperCAmelCase_     							=     tax_enc_dec_attention_key
												UpperCAmelCase_     							=     tax_enc_dec_attention_out
												UpperCAmelCase_     							=     tax_enc_dec_attention_query
												UpperCAmelCase_     							=     tax_enc_dec_attention_value

												UpperCAmelCase_     							=     tax_cross_layer_norm

												if split_mlp_wi:
																		UpperCAmelCase_     							=     tax_mlp_wi_a
																		UpperCAmelCase_     							=     tax_mlp_wi_a
												else:
																		UpperCAmelCase_     							=     tax_mlp_wi

												UpperCAmelCase_     							=     tax_mlp_wo

												UpperCAmelCase_     							=     txa_mlp_layer_norm

						# Decoder Normalization
						UpperCAmelCase_     							=     tax_model['''target''']['''decoder''']['''decoder_norm''']['''scale''']
						UpperCAmelCase_     							=     txa_decoder_norm

						# Only for layer 0:
						UpperCAmelCase_     							=     tax_model['''target''']['''decoder''']['''relpos_bias''']['''rel_embedding'''].T
						UpperCAmelCase_     							=     tax_decoder_rel_embedding

						# Token Embeddings
						UpperCAmelCase_     							=     tax_model['''target''']['''token_embedder''']['''embedding''']
						UpperCAmelCase_     							=     txa_token_embeddings

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

						flax_model.save_pretrained(__UpperCAmelCase	)
						print('''T5X Model was sucessfully converted!'''	)


if __name__ == "__main__":
							UpperCamelCase_	       =   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."
							)
							UpperCamelCase_	       =   parser.parse_args()
							convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)










from .chunk_utils import chunk_layer
from .data_transforms import make_atomaa_masks
from .feats import atomaa_to_atomaa, frames_and_literature_positions_to_atomaa_pos, torsion_angles_to_frames
from .loss import compute_predicted_aligned_error, compute_tm
from .protein import Protein as OFProtein
from .protein import to_pdb
from .rigid_utils import Rigid, Rotation
from .tensor_utils import dict_multimap, flatten_final_dims, permute_final_dims





