

import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin






class 		__magic_name__ (				snake_case       ,	unittest.TestCase							):
     UpperCamelCase_     :Union[str, Any]									=	SpeechaTextaTokenizer
     UpperCamelCase_     :Optional[Any]									=	False






     def      UpperCAmelCase_							(							self     )->			Dict:
         super().setUp()

         UpperCamelCase_          =		"<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" "     )
         UpperCamelCase_          =		["he re</w> 123", "here a 1456"]
         UpperCamelCase_          =		dict(zip(_lowercase						,		range(len(_lowercase     )     )     )     )

         UpperCamelCase_          =		{"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

         UpperCamelCase_          =		tempfile.mkdtemp()
         UpperCamelCase_          =		os.path.join(self.tmpdirname						,		VOCAB_FILES_NAMES["vocab_file"]     )
         UpperCamelCase_          =		os.path.join(self.tmpdirname						,		VOCAB_FILES_NAMES["merges_file"]     )

         with open(self.vocab_file						,		"w"						,		encoding="utf-8"     ) as fp:
             fp.write(json.dumps(_lowercase     ) + "\n"     )

         with open(self.merges_file						,		"w"     ) as fp:
             fp.write("\n".join(_lowercase     )     )






     def      UpperCAmelCase_							(							self     )->			Any:
         UpperCamelCase_          =		list(self.get_tokenizer().get_vocab().keys()     )

         self.assertEqual(vocab_keys[0]						,		"<s>"     )
         self.assertEqual(vocab_keys[1]						,		"<pad>"     )
         self.assertEqual(vocab_keys[-1]						,		"vocab"     )
         self.assertEqual(len(_lowercase     )						,		14     )






     def      UpperCAmelCase_							(							self     )->			int:
         self.assertEqual(self.get_tokenizer().vocab_size						,		14     )






     def      UpperCAmelCase_							(							self     )->			List[str]:
         UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(self.tmpdirname     )

         # make sure @@ is correctly concatenated
         UpperCamelCase_          =		[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
         UpperCamelCase_          =		tokenizer.decode(_lowercase     )

         self.assertTrue(output_string == "herecouple words ofthe"     )






     def      UpperCAmelCase_							(							self     )->			Any:
         UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(self.tmpdirname     )

         with tempfile.TemporaryDirectory() as tmp_dirname:
             tokenizer.save_pretrained(_lowercase     )
             os.remove(os.path.join(_lowercase						,		"merges.txt"     )     )

             # load tokenizer without merges file should not throw an error
             UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(_lowercase     )

         with tempfile.TemporaryDirectory() as tmp_dirname:
             # save tokenizer and load again
             tokenizer.save_pretrained(_lowercase     )
             UpperCamelCase_          =		SpeechaTextaTokenizer.from_pretrained(_lowercase     )

         self.assertIsNotNone(_lowercase     )






     def      UpperCAmelCase_							(							self     )->			Dict:
         if not self.test_slow_tokenizer:
             return

         UpperCamelCase_          =		inspect.signature(self.tokenizer_class.__init__     )
         UpperCamelCase_          =		self.get_tokenizer()

         for parameter_name, parameter in signature.parameters.items():
             if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
                 self.assertIn(_lowercase						,		tokenizer.init_kwargs     )






'''simple docstring'''
import argparse

from tax import checkpoints

from transformers import FlaxTaForConditionalGeneration, TaConfig
def 				snake_case_  (   a__		:	Optional[int]    ,a__		:	str    ,a__		:	int			):



    """simple docstring"""




    __lowercase							=						TaConfig.from_pretrained(a__			)
    __lowercase							=						FlaxTaForConditionalGeneration(config=a__			)
    __lowercase							=						checkpoints.load_tax_checkpoint(a__			)

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

    # Encoder
    for layer_index in range(config.num_layers			):
        __lowercase							=						f'layers_{str(a__			)}'

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

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

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

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

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

        # Assigning
        __lowercase							=						tax_attention_key
        __lowercase							=						tax_attention_out
        __lowercase							=						tax_attention_query
        __lowercase							=						tax_attention_value

        __lowercase							=						tax_attention_layer_norm

        if split_mlp_wi:
            __lowercase							=						tax_mlp_wi_a
            __lowercase							=						tax_mlp_wi_a
        else:
            __lowercase							=						tax_mlp_wi

        __lowercase							=						tax_mlp_wo
        __lowercase							=						tax_mlp_layer_norm

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

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

    # Decoder
    for layer_index in range(config.num_decoder_layers			):
        __lowercase							=						f'layers_{str(a__			)}'

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

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

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

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

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

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

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

        # Assigning
        __lowercase							=						tax_attention_key
        __lowercase							=						tax_attention_out
        __lowercase							=						tax_attention_query
        __lowercase							=						tax_attention_value

        __lowercase							=						tax_pre_attention_layer_norm

        __lowercase							=						tax_enc_dec_attention_key
        __lowercase							=						tax_enc_dec_attention_out
        __lowercase							=						tax_enc_dec_attention_query
        __lowercase							=						tax_enc_dec_attention_value

        __lowercase							=						tax_cross_layer_norm

        if split_mlp_wi:
            __lowercase							=						tax_mlp_wi_a
            __lowercase							=						tax_mlp_wi_a
        else:
            __lowercase							=						tax_mlp_wi

        __lowercase							=						tax_mlp_wo

        __lowercase							=						txa_mlp_layer_norm

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

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

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

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

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


if __name__ == "__main__":
  A							:      Optional[Any] 	=       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."""
  )
  A							:      Dict 	=       parser.parse_args()
  convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)




