






import functools
import operator

from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case__   :						Any													=   logging.get_logger(__name__)

snake_case__   :						List[Any]													=   {
    """asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
    # See all SEW-D models at https://huggingface.co/models?filter=sew-d
}


class     _a							(	__UpperCAmelCase     ):






  """simple docstring"""





  A_						       = '''sew-d'''




  def __init__(  self		,		_UpperCAmelCase=32		,		_UpperCAmelCase=768		,		_UpperCAmelCase=12		,		_UpperCAmelCase=12		,		_UpperCAmelCase=3072		,		_UpperCAmelCase=2		,		_UpperCAmelCase=512		,		_UpperCAmelCase=256		,		_UpperCAmelCase=True		,		_UpperCAmelCase=True		,		_UpperCAmelCase=("p2c", "c2p")		,		_UpperCAmelCase="layer_norm"		,		_UpperCAmelCase="gelu_python"		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.0		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.0_2		,		_UpperCAmelCase=1e-7		,		_UpperCAmelCase=1e-5		,		_UpperCAmelCase="group"		,		_UpperCAmelCase="gelu"		,		_UpperCAmelCase=(64, 128, 128, 128, 128, 256, 256, 256, 256, 512, 512, 512, 512)		,		_UpperCAmelCase=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1)		,		_UpperCAmelCase=(10, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)		,		_UpperCAmelCase=False		,		_UpperCAmelCase=128		,		_UpperCAmelCase=16		,		_UpperCAmelCase=True		,		_UpperCAmelCase=0.0_5		,		_UpperCAmelCase=10		,		_UpperCAmelCase=2		,		_UpperCAmelCase=0.0		,		_UpperCAmelCase=10		,		_UpperCAmelCase=0		,		_UpperCAmelCase="mean"		,		_UpperCAmelCase=False		,		_UpperCAmelCase=False		,		_UpperCAmelCase=256		,		_UpperCAmelCase=0		,		_UpperCAmelCase=1		,		_UpperCAmelCase=2		,		**_UpperCAmelCase		,		)      ->			Optional[int]:
     super().__init__(**lowerCamelCase__		,		pad_token_id=lowerCamelCase__		,		bos_token_id=lowerCamelCase__		,		eos_token_id=lowerCamelCase__			)
     UpperCamelCase_						=  hidden_size
     UpperCamelCase_						=  feat_extract_norm
     UpperCamelCase_						=  feat_extract_activation
     UpperCamelCase_						=  list(lowerCamelCase__			)
     UpperCamelCase_						=  list(lowerCamelCase__			)
     UpperCamelCase_						=  list(lowerCamelCase__			)
     UpperCamelCase_						=  conv_bias
     UpperCamelCase_						=  num_conv_pos_embeddings
     UpperCamelCase_						=  num_conv_pos_embedding_groups
     UpperCamelCase_						=  len(self.conv_dim			)
     UpperCamelCase_						=  num_hidden_layers
     UpperCamelCase_						=  intermediate_size
     UpperCamelCase_						=  squeeze_factor
     UpperCamelCase_						=  max_position_embeddings
     UpperCamelCase_						=  position_buckets
     UpperCamelCase_						=  share_att_key
     UpperCamelCase_						=  relative_attention
     UpperCamelCase_						=  norm_rel_ebd
     UpperCamelCase_						=  list(lowerCamelCase__			)
     UpperCamelCase_						=  hidden_act
     UpperCamelCase_						=  num_attention_heads
     UpperCamelCase_						=  hidden_dropout
     UpperCamelCase_						=  attention_dropout
     UpperCamelCase_						=  activation_dropout
     UpperCamelCase_						=  feat_proj_dropout
     UpperCamelCase_						=  final_dropout
     UpperCamelCase_						=  layer_norm_eps
     UpperCamelCase_						=  feature_layer_norm_eps
     UpperCamelCase_						=  initializer_range
     UpperCamelCase_						=  vocab_size

     if (
         (len(self.conv_stride			) != self.num_feat_extract_layers)
         or (len(self.conv_kernel			) != self.num_feat_extract_layers)
         or (len(self.conv_dim			) != self.num_feat_extract_layers)
     ):
        raise ValueError(
            'Configuration for convolutional layers is incorrect.'
            'It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,'
            f"""but is `len(config.conv_dim) = {len(self.conv_dim			)}`, `len(config.conv_stride)"""
            f"""= {len(self.conv_stride			)}`, `len(config.conv_kernel) = {len(self.conv_kernel			)}`."""			)

     # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
     UpperCamelCase_						=  apply_spec_augment
     UpperCamelCase_						=  mask_time_prob
     UpperCamelCase_						=  mask_time_length
     UpperCamelCase_						=  mask_time_min_masks
     UpperCamelCase_						=  mask_feature_prob
     UpperCamelCase_						=  mask_feature_length
     UpperCamelCase_						=  mask_feature_min_masks

     # ctc loss
     UpperCamelCase_						=  ctc_loss_reduction
     UpperCamelCase_						=  ctc_zero_infinity

     # sequence classification
     UpperCamelCase_						=  use_weighted_layer_sum
     UpperCamelCase_						=  classifier_proj_size




  @property
  def  _UpperCAmelCase  (  self			)      ->			str:
     return functools.reduce(operator.mul		,		self.conv_stride		,		1			)









"""simple docstring"""


import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402


__snake_case    					=					{
    'return_dict': False,
    'output_hidden_states': True,
    'output_attentions': True,
    'torchscript': True,
    'torch_dtype': 'float16',
    'use_bfloat16': True,
    'tf_legacy_loss': True,
    'pruned_heads': {'a': 1},
    'tie_word_embeddings': False,
    'is_decoder': True,
    'cross_attention_hidden_size': 128,
    'add_cross_attention': True,
    'tie_encoder_decoder': True,
    'max_length': 50,
    'min_length': 3,
    'do_sample': True,
    'early_stopping': True,
    'num_beams': 3,
    'num_beam_groups': 3,
    'diversity_penalty': 0.5,
    'temperature': 2.0,
    'top_k': 10,
    'top_p': 0.7,
    'typical_p': 0.2,
    'repetition_penalty': 0.8,
    'length_penalty': 0.8,
    'no_repeat_ngram_size': 5,
    'encoder_no_repeat_ngram_size': 5,
    'bad_words_ids': [1, 2, 3],
    'num_return_sequences': 3,
    'chunk_size_feed_forward': 5,
    'output_scores': True,
    'return_dict_in_generate': True,
    'forced_bos_token_id': 2,
    'forced_eos_token_id': 3,
    'remove_invalid_values': True,
    'architectures': ['BertModel'],
    'finetuning_task': 'translation',
    'id2label': {0: 'label'},
    'label2id': {'label': '0'},
    'tokenizer_class': 'BertTokenizerFast',
    'prefix': 'prefix',
    'bos_token_id': 6,
    'pad_token_id': 7,
    'eos_token_id': 8,
    'sep_token_id': 9,
    'decoder_start_token_id': 10,
    'exponential_decay_length_penalty': (5, 1.01),
    'suppress_tokens': [0, 1],
    'begin_suppress_tokens': 2,
    'task_specific_params': {'translation': 'some_params'},
    'problem_type': 'regression',
}

@is_staging_test
class 				_SCREAMING_SNAKE_CASE				(							unittest.TestCase  ):
   """simple docstring"""



   @classmethod
   def 					UpperCAmelCase__(						cls						)      ->							Dict:
    lowercase__       :       str				=						TOKEN
    HfFolder.save_token(lowerCamelCase__						)


   @classmethod
   def 					UpperCAmelCase__(						cls						)      ->							Optional[Any]:
    try:
     delete_repo(token=cls._token ,     repo_id="""test-config"""						)
    except HTTPError:
     pass

    try:
     delete_repo(token=cls._token ,     repo_id="""valid_org/test-config-org"""						)
    except HTTPError:
     pass

    try:
     delete_repo(token=cls._token ,     repo_id="""test-dynamic-config"""						)
    except HTTPError:
     pass


   def 					UpperCAmelCase__(						self						)      ->							List[str]:
    lowercase__       :       Union[str, Any]				=						BertConfig(
        vocab_size=99 ,     hidden_size=32 ,     num_hidden_layers=5 ,     num_attention_heads=4 ,     intermediate_size=37						)
    config.push_to_hub("""test-config""" ,     use_auth_token=self._token						)

    lowercase__       :       Union[str, Any]				=						BertConfig.from_pretrained(F'''{USER}/test-config'''						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)

        # Reset repo
    delete_repo(token=self._token ,     repo_id="""test-config"""						)

    # Push to hub via save_pretrained
    with tempfile.TemporaryDirectory() as tmp_dir:
     config.save_pretrained(lowerCamelCase__ ,     repo_id="""test-config""" ,     push_to_hub=lowerCamelCase__ ,     use_auth_token=self._token						)

    lowercase__       :       Optional[Any]				=						BertConfig.from_pretrained(F'''{USER}/test-config'''						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[Any]:
    lowercase__       :       int				=						BertConfig(
        vocab_size=99 ,     hidden_size=32 ,     num_hidden_layers=5 ,     num_attention_heads=4 ,     intermediate_size=37						)
    config.push_to_hub("""valid_org/test-config-org""" ,     use_auth_token=self._token						)

    lowercase__       :       List[str]				=						BertConfig.from_pretrained("""valid_org/test-config-org"""						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)

        # Reset repo
    delete_repo(token=self._token ,     repo_id="""valid_org/test-config-org"""						)

    # Push to hub via save_pretrained
    with tempfile.TemporaryDirectory() as tmp_dir:
     config.save_pretrained(
         lowerCamelCase__ ,     repo_id="""valid_org/test-config-org""" ,     push_to_hub=lowerCamelCase__ ,     use_auth_token=self._token						)

    lowercase__       :       Optional[Any]				=						BertConfig.from_pretrained("""valid_org/test-config-org"""						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)







   def 					UpperCAmelCase__(						self						)      ->							Dict:
    CustomConfig.register_for_auto_class()
    lowercase__       :       int				=						CustomConfig(attribute=42						)

    config.push_to_hub("""test-dynamic-config""" ,     use_auth_token=self._token						)

    # This has added the proper auto_map field to the config
    self.assertDictEqual(config.auto_map ,     {"""AutoConfig""": """custom_configuration.CustomConfig"""}						)

    lowercase__       :       Any				=						AutoConfig.from_pretrained(F'''{USER}/test-dynamic-config''' ,     trust_remote_code=lowerCamelCase__						)
    # Can't make an isinstance check because the new_config is from the FakeConfig class of a dynamic module
    self.assertEqual(new_config.__class__.__name__ ,     """CustomConfig"""						)
    self.assertEqual(new_config.attribute ,     42						)

class 				_SCREAMING_SNAKE_CASE				(							unittest.TestCase  ):
   """simple docstring"""



   def 					UpperCAmelCase__(						self						)      ->							Tuple:
    lowercase__       :       str				=						GPTaConfig()

    # attempt to modify each of int/float/bool/str config records and verify they were updated
    lowercase__       :       List[str]				=						c.n_embd + 1  # int
    lowercase__       :       Union[str, Any]				=						c.resid_pdrop + 1.0  # float
    lowercase__       :       int				=						not c.scale_attn_weights  # bool
    lowercase__       :       Optional[int]				=						c.summary_type + """foo"""  # str
    c.update_from_string(
        F'''n_embd={n_embd},resid_pdrop={resid_pdrop},scale_attn_weights={scale_attn_weights},summary_type={summary_type}'''						)
    self.assertEqual(lowerCamelCase__ ,     c.n_embd ,     """mismatch for key: n_embd"""						)
    self.assertEqual(lowerCamelCase__ ,     c.resid_pdrop ,     """mismatch for key: resid_pdrop"""						)
    self.assertEqual(lowerCamelCase__ ,     c.scale_attn_weights ,     """mismatch for key: scale_attn_weights"""						)
    self.assertEqual(lowerCamelCase__ ,     c.summary_type ,     """mismatch for key: summary_type"""						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[int]:
    lowercase__       :       List[str]				=						PretrainedConfig()
    lowercase__       :       Union[str, Any]				=						[key for key in base_config.__dict__ if key not in config_common_kwargs]
    # If this part of the test fails, you have arguments to addin config_common_kwargs above.
    self.assertListEqual(
        lowerCamelCase__ ,     ["""is_encoder_decoder""", """_name_or_path""", """_commit_hash""", """transformers_version"""]						)
    lowercase__       :       List[Any]				=						[key for key, value in config_common_kwargs.items() if value == getattr(lowerCamelCase__ ,     lowerCamelCase__						)]
    if len(lowerCamelCase__						) > 0:
     raise ValueError(
         """The following keys are set with the default values in"""
         """ `test_configuration_common.config_common_kwargs` pick another value for them:"""
         F''' {', '.join(lowerCamelCase__						)}.'''						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[Any]:
    with self.assertRaises(lowerCamelCase__						):
     # config is in subfolder, the following should not work without specifying the subfolder
     lowercase__       :       str				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert-subfolder"""						)

    lowercase__       :       Union[str, Any]				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert-subfolder""" ,     subfolder="""bert"""						)

    self.assertIsNotNone(lowerCamelCase__						)


   def 					UpperCAmelCase__(						self						)      ->							Union[str, Any]:
    # A mock response for an HTTP head request to emulate server down
    lowercase__       :       Dict				=						mock.Mock()
    lowercase__       :       str				=						500
    lowercase__       :       int				=						{}
    lowercase__       :       Optional[int]				=						HTTPError
    lowercase__       :       Dict				=						{}

    # Download this model to make sure it's in the cache.
    lowercase__       :       Any				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert"""						)

    # Under the mock environment we get a 500 error when trying to reach the model.
    with mock.patch("""requests.Session.request""" ,     return_value=lowerCamelCase__						) as mock_head:
     lowercase__       :       int				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert"""						)
     # This check we did call the fake head request
     mock_head.assert_called()


   def 					UpperCAmelCase__(						self						)      ->							int:
    # This test is for deprecated behavior and can be removed in v5
    lowercase__       :       Optional[Any]				=						BertConfig.from_pretrained(
        """https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json"""						)


   def 					UpperCAmelCase__(						self						)      ->							List[Any]:
    lowercase__       :       Optional[int]				=						AutoConfig.from_pretrained("""bert-base-cased"""						)
    lowercase__       :       Union[str, Any]				=						["""config.4.0.0.json"""]

    with tempfile.TemporaryDirectory() as tmp_dir:
     configuration.save_pretrained(lowerCamelCase__						)
     lowercase__       :       Optional[Any]				=						2
     json.dump(configuration.to_dict() ,     open(os.path.join(lowerCamelCase__ ,     """config.4.0.0.json"""						) ,     """w"""						)						)

     # This should pick the new configuration file as the version of Transformers is > 4.0.0
     lowercase__       :       Optional[int]				=						AutoConfig.from_pretrained(lowerCamelCase__						)
     self.assertEqual(new_configuration.hidden_size ,     2						)

     # Will need to be adjusted if we reach v42 and this test is still here.
     # Should pick the old configuration file as the version of Transformers is < 4.42.0
     lowercase__       :       Optional[int]				=						["""config.42.0.0.json"""]
     lowercase__       :       Optional[int]				=						768
     configuration.save_pretrained(lowerCamelCase__						)
     shutil.move(os.path.join(lowerCamelCase__ ,     """config.4.0.0.json"""						) ,     os.path.join(lowerCamelCase__ ,     """config.42.0.0.json"""						)						)
     lowercase__       :       Dict				=						AutoConfig.from_pretrained(lowerCamelCase__						)
     self.assertEqual(new_configuration.hidden_size ,     768						)







   def 					UpperCAmelCase__(						self						)      ->							List[Any]:
    # This repo has two configuration files, one for v4.0.0 and above with a different hidden size.
    lowercase__       :       Any				=						"""hf-internal-testing/test-two-configs"""

    import transformers as new_transformers

    lowercase__       :       Union[str, Any]				=						"""v4.0.0"""
    lowercase__	,       lowercase__       :       int				=						new_transformers.models.auto.AutoConfig.from_pretrained(
        lowerCamelCase__ ,     return_unused_kwargs=lowerCamelCase__						)
    self.assertEqual(new_configuration.hidden_size ,     2						)
    # This checks `_configuration_file` ia not kept in the kwargs by mistake.
    self.assertDictEqual(lowerCamelCase__ ,     {}						)

    # Testing an older version by monkey-patching the version in the module it's used.
    import transformers as old_transformers

    lowercase__       :       str				=						"""v3.0.0"""
    lowercase__       :       int				=						old_transformers.models.auto.AutoConfig.from_pretrained(lowerCamelCase__						)
    self.assertEqual(old_configuration.hidden_size ,     768						)