




"""simple docstring"""







import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english







@require_tokenizers
class  lowerCamelCase__ (	snake_case   ,					unittest.TestCase			):
    SCREAMING_SNAKE_CASE		=      RoCBertTokenizer
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      False
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      filter_non_english






    def     _UpperCamelCase							(			self ):
          super().setUp()

          UpperCAmelCase          =	["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """你""", """好""", """是""", """谁""", """a""", """b""", """c""", """d"""]
          UpperCAmelCase          =	{}
          UpperCAmelCase          =	{}
          for i, value in enumerate(A ):
                UpperCAmelCase          =	i
                UpperCAmelCase          =	i
          UpperCAmelCase          =	os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES["""vocab_file"""] )
          UpperCAmelCase          =	os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES["""word_shape_file"""] )
          UpperCAmelCase          =	os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES["""word_pronunciation_file"""] )
          with open(self.vocab_file     ,"""w"""     ,encoding="""utf-8""" ) as vocab_writer:
                vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens] ) )
          with open(self.word_shape_file     ,"""w"""     ,encoding="""utf-8""" ) as word_shape_writer:
                json.dump(A     ,A     ,ensure_ascii=A )
          with open(self.word_pronunciation_file     ,"""w"""     ,encoding="""utf-8""" ) as word_pronunciation_writer:
                json.dump(A     ,A     ,ensure_ascii=A )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	self.tokenizer_class(self.vocab_file     ,self.word_shape_file     ,self.word_pronunciation_file )

          UpperCAmelCase          =	tokenizer.tokenize("""你好[SEP]你是谁""" )
          self.assertListEqual(A     ,["""你""", """好""", """[SEP]""", """你""", """是""", """谁"""] )
          self.assertListEqual(tokenizer.convert_tokens_to_ids(A )     ,[5, 6, 2, 5, 7, 8] )
          self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(A )     ,[5, 6, 2, 5, 7, 8] )
          self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(A )     ,[5, 6, 2, 5, 7, 8] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer()

          self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz""" )     ,["""ah""", """\u535A""", """\u63A8""", """zz"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """ )     ,["""hello""", """!""", """how""", """are""", """you""", """?"""] )
          self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" )     ,["""hello"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A     ,strip_accents=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ )     ,["""hällo""", """!""", """how""", """are""", """you""", """?"""] )
          self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" )     ,["""h\u00E9llo"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A     ,strip_accents=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ )     ,["""hallo""", """!""", """how""", """are""", """you""", """?"""] )
          self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" )     ,["""hello"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ )     ,["""hallo""", """!""", """how""", """are""", """you""", """?"""] )
          self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" )     ,["""hello"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """ )     ,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A     ,strip_accents=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ )     ,["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A     ,strip_accents=A )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ )     ,["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	RoCBertBasicTokenizer(do_lower_case=A     ,never_split=["""[UNK]"""] )

          self.assertListEqual(
              tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]""" )     ,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

          UpperCAmelCase          =	{}
          for i, token in enumerate(A ):
                UpperCAmelCase          =	i
          UpperCAmelCase          =	RoCBertWordpieceTokenizer(vocab=A     ,unk_token="""[UNK]""" )

          self.assertListEqual(tokenizer.tokenize("""""" )     ,[] )

          self.assertListEqual(tokenizer.tokenize("""unwanted running""" )     ,["""un""", """##want""", """##ed""", """runn""", """##ing"""] )

          self.assertListEqual(tokenizer.tokenize("""unwantedX running""" )     ,["""[UNK]""", """runn""", """##ing"""] )






    def     _UpperCamelCase							(			self ):
          self.assertTrue(_is_whitespace(""" """ ) )
          self.assertTrue(_is_whitespace("""\t""" ) )
          self.assertTrue(_is_whitespace("""\r""" ) )
          self.assertTrue(_is_whitespace("""\n""" ) )
          self.assertTrue(_is_whitespace("""\u00A0""" ) )

          self.assertFalse(_is_whitespace("""A""" ) )
          self.assertFalse(_is_whitespace("""-""" ) )






    def     _UpperCamelCase							(			self ):
          self.assertTrue(_is_control("""\u0005""" ) )

          self.assertFalse(_is_control("""A""" ) )
          self.assertFalse(_is_control(""" """ ) )
          self.assertFalse(_is_control("""\t""" ) )
          self.assertFalse(_is_control("""\r""" ) )






    def     _UpperCamelCase							(			self ):
          self.assertTrue(_is_punctuation("""-""" ) )
          self.assertTrue(_is_punctuation("""$""" ) )
          self.assertTrue(_is_punctuation("""`""" ) )
          self.assertTrue(_is_punctuation(""".""" ) )

          self.assertFalse(_is_punctuation("""A""" ) )
          self.assertFalse(_is_punctuation(""" """ ) )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	self.get_tokenizer()

          # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
          self.assertListEqual([tokenizer.tokenize(A ) for t in ["""Test""", """\xad""", """test"""]]     ,[["""[UNK]"""], [], ["""[UNK]"""]] )

          if self.test_rust_tokenizer:
                UpperCAmelCase          =	self.get_rust_tokenizer()
                self.assertListEqual(
                    [rust_tokenizer.tokenize(A ) for t in ["""Test""", """\xad""", """test"""]]     ,[["""[UNK]"""], [], ["""[UNK]"""]] )






    def     _UpperCamelCase							(			self ):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
                      UpperCAmelCase          =	self.rust_tokenizer_class.from_pretrained(A     ,**A )

                      UpperCAmelCase          =	F'''A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'''
                      UpperCAmelCase          =	tokenizer_r.encode_plus(
                          A     ,return_attention_mask=A     ,return_token_type_ids=A     ,return_offsets_mapping=A     ,add_special_tokens=A     ,)

                      UpperCAmelCase          =	tokenizer_r.do_lower_case if hasattr(A     ,"""do_lower_case""" ) else False
                      UpperCAmelCase          =	(
                          [
                              ((0, 0), tokenizer_r.cls_token),
                              ((0, 1), """A"""),
                              ((1, 2), ""","""),
                              ((3, 5), """na"""),
                              ((5, 6), """##ï"""),
                              ((6, 8), """##ve"""),
                              ((9, 15), tokenizer_r.mask_token),
                              ((16, 21), """Allen"""),
                              ((21, 23), """##NL"""),
                              ((23, 24), """##P"""),
                              ((25, 33), """sentence"""),
                              ((33, 34), """."""),
                              ((0, 0), tokenizer_r.sep_token),
                          ]
                          if not do_lower_case
                          else [
                              ((0, 0), tokenizer_r.cls_token),
                              ((0, 1), """a"""),
                              ((1, 2), ""","""),
                              ((3, 8), """naive"""),
                              ((9, 15), tokenizer_r.mask_token),
                              ((16, 21), """allen"""),
                              ((21, 23), """##nl"""),
                              ((23, 24), """##p"""),
                              ((25, 33), """sentence"""),
                              ((33, 34), """."""),
                              ((0, 0), tokenizer_r.sep_token),
                          ]
                      )

                      self.assertEqual(
                          [e[1] for e in expected_results]     ,tokenizer_r.convert_ids_to_tokens(tokens["""input_ids"""] ) )
                      self.assertEqual([e[0] for e in expected_results]     ,tokens["""offset_mapping"""] )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	["""的""", """人""", """有"""]
          UpperCAmelCase          =	"""""".join(A )
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
                      UpperCAmelCase          =	True
                      UpperCAmelCase          =	self.tokenizer_class.from_pretrained(A     ,**A )
                      UpperCAmelCase          =	self.rust_tokenizer_class.from_pretrained(A     ,**A )

                      UpperCAmelCase          =	tokenizer_p.encode(A     ,add_special_tokens=A )
                      UpperCAmelCase          =	tokenizer_r.encode(A     ,add_special_tokens=A )

                      UpperCAmelCase          =	tokenizer_r.convert_ids_to_tokens(A )
                      UpperCAmelCase          =	tokenizer_p.convert_ids_to_tokens(A )

                      # it is expected that each Chinese character is not preceded by "##"
                      self.assertListEqual(A     ,A )
                      self.assertListEqual(A     ,A )

                      UpperCAmelCase          =	False
                      UpperCAmelCase          =	self.rust_tokenizer_class.from_pretrained(A     ,**A )
                      UpperCAmelCase          =	self.tokenizer_class.from_pretrained(A     ,**A )

                      UpperCAmelCase          =	tokenizer_r.encode(A     ,add_special_tokens=A )
                      UpperCAmelCase          =	tokenizer_p.encode(A     ,add_special_tokens=A )

                      UpperCAmelCase          =	tokenizer_r.convert_ids_to_tokens(A )
                      UpperCAmelCase          =	tokenizer_p.convert_ids_to_tokens(A )

                      # it is expected that only the first Chinese character is not preceded by "##".
                      UpperCAmelCase          =	[
                          F'''##{token}''' if idx != 0 else token for idx, token in enumerate(A )
                      ]
                      self.assertListEqual(A     ,A )
                      self.assertListEqual(A     ,A )






    @slow
    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	self.tokenizer_class(self.vocab_file     ,self.word_shape_file     ,self.word_pronunciation_file )

          UpperCAmelCase          =	tokenizer.encode("""你好"""     ,add_special_tokens=A )
          UpperCAmelCase          =	tokenizer.encode("""你是谁"""     ,add_special_tokens=A )

          UpperCAmelCase          =	tokenizer.build_inputs_with_special_tokens(A )
          UpperCAmelCase          =	tokenizer.build_inputs_with_special_tokens(A     ,A )

          assert encoded_sentence == [1] + text + [2]
          assert encoded_pair == [1] + text + [2] + text_a + [2]






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	self.get_tokenizers(do_lower_case=A )
          for tokenizer in tokenizers:
                with self.subTest(F'''{tokenizer.__class__.__name__}''' ):
                      UpperCAmelCase          =	"""你好，你是谁"""
                      UpperCAmelCase          =	tokenizer.tokenize(A )
                      UpperCAmelCase          =	tokenizer.convert_tokens_to_ids(A )
                      UpperCAmelCase          =	tokenizer.convert_tokens_to_shape_ids(A )
                      UpperCAmelCase          =	tokenizer.convert_tokens_to_pronunciation_ids(A )
                      UpperCAmelCase          =	tokenizer.prepare_for_model(
                          A     ,A     ,A     ,add_special_tokens=A )

                      UpperCAmelCase          =	tokenizer.encode_plus(A     ,add_special_tokens=A )

                      self.assertEqual(A     ,A )











"""simple docstring"""







import argparse
import re

import torch
from CLAP import create_model

from transformers import AutoFeatureExtractor, ClapConfig, ClapModel


_UpperCamelCase					      =  {
    """text_branch""": """text_model""",
    """audio_branch""": """audio_model.audio_encoder""",
    """attn""": """attention.self""",
    """self.proj""": """output.dense""",
    """attention.self_mask""": """attn_mask""",
    """mlp.fc1""": """intermediate.dense""",
    """mlp.fc2""": """output.dense""",
    """norm1""": """layernorm_before""",
    """norm2""": """layernorm_after""",
    """bn0""": """batch_norm""",
}

_UpperCamelCase					      =  AutoFeatureExtractor.from_pretrained("""laion/clap-htsat-unfused""", truncation="""rand_trunc""")

def _a			(		_snake_case				,	_snake_case=False							):







      """simple docstring"""






      UpperCAmelCase      , UpperCAmelCase          =	create_model(
          """HTSAT-tiny"""				,	"""roberta"""				,	_snake_case				,	precision="""fp32"""				,	device="""cuda:0""" if torch.cuda.is_available() else """cpu"""				,	enable_fusion=_snake_case				,	fusion_type="""aff_2d""" if enable_fusion else None				,	)
      return model, model_cfg

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	{}

      UpperCAmelCase          =	R""".*sequential.(\d+).*"""
      UpperCAmelCase          =	R""".*_projection.(\d+).*"""

      for key, value in state_dict.items():
            # check if any key needs to be modified
            for key_to_modify, new_key in KEYS_TO_MODIFY_MAPPING.items():
                  if key_to_modify in key:
                        UpperCAmelCase          =	key.replace(_snake_case				,	_snake_case							)

            if re.match(_snake_case				,	_snake_case							):
                  # replace sequential layers with list
                  UpperCAmelCase          =	re.match(_snake_case				,	_snake_case							).group(1							)

                  UpperCAmelCase          =	key.replace(F'''sequential.{sequential_layer}.'''				,	F'''layers.{int(_snake_case							)//3}.linear.'''							)
            elif re.match(_snake_case				,	_snake_case							):
                  UpperCAmelCase          =	int(re.match(_snake_case				,	_snake_case							).group(1							)							)

                  # Because in CLAP they use `nn.Sequential`...
                  UpperCAmelCase          =	1 if projecton_layer == 0 else 2

                  UpperCAmelCase          =	key.replace(F'''_projection.{projecton_layer}.'''				,	F'''_projection.linear{transformers_projection_layer}.'''							)

            if "audio" and "qkv" in key:
                  # split qkv into query key and value
                  UpperCAmelCase          =	value
                  UpperCAmelCase          =	mixed_qkv.size(0							) // 3

                  UpperCAmelCase          =	mixed_qkv[:qkv_dim]
                  UpperCAmelCase          =	mixed_qkv[qkv_dim : qkv_dim * 2]
                  UpperCAmelCase          =	mixed_qkv[qkv_dim * 2 :]

                  UpperCAmelCase          =	query_layer
                  UpperCAmelCase          =	key_layer
                  UpperCAmelCase          =	value_layer
            else:
                  UpperCAmelCase          =	value

      return model_state_dict

def _a			(		_snake_case				,	_snake_case				,	_snake_case				,	_snake_case=False							):







      """simple docstring"""






      UpperCAmelCase      , UpperCAmelCase          =	init_clap(_snake_case				,	enable_fusion=_snake_case							)

      clap_model.eval()
      UpperCAmelCase          =	clap_model.state_dict()
      UpperCAmelCase          =	rename_state_dict(_snake_case							)

      UpperCAmelCase          =	ClapConfig()
      UpperCAmelCase          =	enable_fusion
      UpperCAmelCase          =	ClapModel(_snake_case							)

      # ignore the spectrogram embedding layer
      model.load_state_dict(_snake_case				,	strict=_snake_case							)

      model.save_pretrained(_snake_case							)
      transformers_config.save_pretrained(_snake_case							)


if __name__ == "__main__":
  _UpperCamelCase					      =  argparse.ArgumentParser()
  parser.add_argument("""--pytorch_dump_folder_path""", default=None, type=str, help="""Path to the output PyTorch model.""")
  parser.add_argument("""--checkpoint_path""", default=None, type=str, help="""Path to fairseq checkpoint""")
  parser.add_argument("""--config_path""", default=None, type=str, help="""Path to hf config.json of model to convert""")
  parser.add_argument("""--enable_fusion""", action="""store_true""", help="""Whether to enable fusion or not""")
  _UpperCamelCase					      =  parser.parse_args()

  convert_clap_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path, args.enable_fusion)



