
"""simple docstring"""
import argparse

from tax import checkpoints

from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM

def  lowercase     (_lowerCAmelCase ,    _lowerCAmelCase ,    _lowerCAmelCase						):
						__lowerCAmelCase     =  AutoConfig.from_pretrained(_lowerCAmelCase						)
						__lowerCAmelCase     =  FlaxAutoModelForSeqaSeqLM.from_config(config=_lowerCAmelCase						)
						__lowerCAmelCase     =  checkpoints.load_tax_checkpoint(_lowerCAmelCase						)

						__lowerCAmelCase     =  """wi_0""" in tax_model["""target"""]["""encoder"""]["""layers_0"""]["""mlp"""]

						if config.model_type == "t5":
												__lowerCAmelCase     =  """SelfAttention"""
						if config.model_type == "longt5" and config.encoder_attention_type == "local":
												__lowerCAmelCase     =  """LocalSelfAttention"""
						elif config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
												__lowerCAmelCase     =  """TransientGlobalSelfAttention"""
						else:
												raise ValueError(
												    """Given config is expected to have `model_type='t5'`, or `model_type='longt5` with `encoder_attention_type`"""
												    """ attribute with a value from ['local', 'transient-global]."""						)

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

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

												# Global input layer norm
												if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
																		__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""T5LayerNorm_0"""]["""scale"""]

												# Layer Normalization
												__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""][layer_name]["""pre_attention_layer_norm"""]["""scale"""]

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

												__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

												# Layer Normalization
												__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

												# Assigning
												__lowerCAmelCase     =  flax_model.params["""encoder"""]["""block"""][str(_lowerCAmelCase						)]["""layer"""]
												__lowerCAmelCase     =  tax_attention_key
												__lowerCAmelCase     =  tax_attention_out
												__lowerCAmelCase     =  tax_attention_query
												__lowerCAmelCase     =  tax_attention_value

												__lowerCAmelCase     =  tax_attention_layer_norm

												# Global input layer norm
												if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
																		__lowerCAmelCase     =  tax_global_layer_norm

												if split_mlp_wi:
																		__lowerCAmelCase     =  tax_mlp_wi_a
																		__lowerCAmelCase     =  tax_mlp_wi_a
												else:
																		__lowerCAmelCase     =  tax_mlp_wi

												__lowerCAmelCase     =  tax_mlp_wo
												__lowerCAmelCase     =  tax_mlp_layer_norm

												__lowerCAmelCase     =  flax_model_encoder_layer_block

						# Only for layer 0:
						__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""]["""relpos_bias"""]["""rel_embedding"""].T
						__lowerCAmelCase     =  tax_encoder_rel_embedding

						# Side/global relative position_bias + layer norm
						if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
												__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""]["""side_relpos_bias"""]["""rel_embedding"""].T
												__lowerCAmelCase     =  tax_encoder_global_rel_embedding

						# Assigning
						__lowerCAmelCase     =  tax_model["""target"""]["""encoder"""]["""encoder_norm"""]["""scale"""]
						__lowerCAmelCase     =  tax_encoder_norm

						# Decoder
						for layer_index in range(config.num_layers						):
												__lowerCAmelCase     =  f"""layers_{str(_lowerCAmelCase						)}"""

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

												# Layer Normalization
												__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""][layer_name]["""pre_self_attention_layer_norm"""][
												    """scale"""
												]

												# Encoder-Decoder-Attention
												__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]
												__lowerCAmelCase     =  tax_enc_dec_attention_module["""key"""]["""kernel"""]
												__lowerCAmelCase     =  tax_enc_dec_attention_module["""out"""]["""kernel"""]
												__lowerCAmelCase     =  tax_enc_dec_attention_module["""query"""]["""kernel"""]
												__lowerCAmelCase     =  tax_enc_dec_attention_module["""value"""]["""kernel"""]

												# Layer Normalization
												__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""][layer_name]["""pre_cross_attention_layer_norm"""]["""scale"""]

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

												__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

												# Layer Normalization
												__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

												# Assigning
												__lowerCAmelCase     =  flax_model.params["""decoder"""]["""block"""][str(_lowerCAmelCase						)]["""layer"""]
												__lowerCAmelCase     =  tax_attention_key
												__lowerCAmelCase     =  tax_attention_out
												__lowerCAmelCase     =  tax_attention_query
												__lowerCAmelCase     =  tax_attention_value

												__lowerCAmelCase     =  tax_pre_attention_layer_norm

												__lowerCAmelCase     =  tax_enc_dec_attention_key
												__lowerCAmelCase     =  tax_enc_dec_attention_out
												__lowerCAmelCase     =  tax_enc_dec_attention_query
												__lowerCAmelCase     =  tax_enc_dec_attention_value

												__lowerCAmelCase     =  tax_cross_layer_norm

												if split_mlp_wi:
																		__lowerCAmelCase     =  tax_mlp_wi_a
																		__lowerCAmelCase     =  tax_mlp_wi_a
												else:
																		__lowerCAmelCase     =  tax_mlp_wi

												__lowerCAmelCase     =  tax_mlp_wo

												__lowerCAmelCase     =  txa_mlp_layer_norm

												__lowerCAmelCase     =  flax_model_decoder_layer_block

						# Decoder Normalization
						__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""]["""decoder_norm"""]["""scale"""]
						__lowerCAmelCase     =  txa_decoder_norm

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

						# Token Embeddings
						__lowerCAmelCase     =  tax_model["""target"""]["""token_embedder"""]["""embedding"""]
						__lowerCAmelCase     =  txa_token_embeddings

						# LM Head (only in v1.1 and LongT5 checkpoints)
						if "logits_dense" in tax_model["target"]["decoder"]:
												__lowerCAmelCase     =  tax_model["""target"""]["""decoder"""]["""logits_dense"""]["""kernel"""]

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


if __name__ == "__main__":
			SCREAMING_SNAKE_CASE_					     =	argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    '''--t5x_checkpoint_path''', default=None, type=str, required=True, help='''Path the T5X checkpoint.'''
			)
			parser.add_argument('''--config_name''', default=None, type=str, required=True, help='''Config name of LongT5/T5 model.''')
			parser.add_argument(
			    '''--flax_dump_folder_path''', default=None, type=str, required=True, help='''Path to the output FLAX model.'''
			)
			SCREAMING_SNAKE_CASE_					     =	parser.parse_args()
			convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)


"""simple docstring"""
import operator as op


SCREAMING_SNAKE_CASE_					     =	'''scaler.pt'''
SCREAMING_SNAKE_CASE_					     =	'''pytorch_model'''
SCREAMING_SNAKE_CASE_					     =	'''random_states'''
SCREAMING_SNAKE_CASE_					     =	'''optimizer'''
SCREAMING_SNAKE_CASE_					     =	'''scheduler'''
SCREAMING_SNAKE_CASE_					     =	'''pytorch_model.bin'''
SCREAMING_SNAKE_CASE_					     =	'''pytorch_model.bin.index.json'''
SCREAMING_SNAKE_CASE_					     =	'''model.safetensors'''
SCREAMING_SNAKE_CASE_					     =	'''model.safetensors.index.json'''
SCREAMING_SNAKE_CASE_					     =	'''1.10.2'''
SCREAMING_SNAKE_CASE_					     =	'''py38'''
SCREAMING_SNAKE_CASE_					     =	'''4.17.0'''
SCREAMING_SNAKE_CASE_					     =	['''ml.p3.16xlarge''', '''ml.p3dn.24xlarge''', '''ml.p4dn.24xlarge''']
SCREAMING_SNAKE_CASE_					     =	['''FULL_SHARD''', '''SHARD_GRAD_OP''', '''NO_SHARD''', '''HYBRID_SHARD''', '''HYBRID_SHARD_ZERO2''']
SCREAMING_SNAKE_CASE_					     =	['''TRANSFORMER_BASED_WRAP''', '''SIZE_BASED_WRAP''', '''NO_WRAP''']
SCREAMING_SNAKE_CASE_					     =	['''BACKWARD_PRE''', '''BACKWARD_POST''', '''NO_PREFETCH''']
SCREAMING_SNAKE_CASE_					     =	['''FULL_STATE_DICT''', '''LOCAL_STATE_DICT''', '''SHARDED_STATE_DICT''']
SCREAMING_SNAKE_CASE_					     =	'''2.0.1'''
SCREAMING_SNAKE_CASE_					     =	['''pdsh''', '''standard''', '''openmpi''', '''mvapich''']
SCREAMING_SNAKE_CASE_					     =	['''default''', '''reduce-overhead''', '''max-autotune''']

SCREAMING_SNAKE_CASE_					     =	{'''>''': op.gt, '''>=''': op.ge, '''==''': op.eq, '''!=''': op.ne, '''<=''': op.le, '''<''': op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
SCREAMING_SNAKE_CASE_					     =	[
    '''nnodes''',
    '''nproc_per_node''',
    '''rdzv_backend''',
    '''rdzv_endpoint''',
    '''rdzv_id''',
    '''rdzv_conf''',
    '''standalone''',
    '''max_restarts''',
    '''monitor_interval''',
    '''start_method''',
    '''role''',
    '''module''',
    '''m''',
    '''no_python''',
    '''run_path''',
    '''log_dir''',
    '''r''',
    '''redirects''',
    '''t''',
    '''tee''',
    '''node_rank''',
    '''master_addr''',
    '''master_port''',
]

SCREAMING_SNAKE_CASE_					     =	['''DEEPSPEED''', '''MULTI_GPU''', '''FSDP''', '''MEGATRON_LM''']
SCREAMING_SNAKE_CASE_					     =	['''DEEPSPEED''', '''MULTI_XPU''', '''FSDP''']
