



'''simple docstring'''





from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> Optional[int]:
      snake_case__  :    Union[str, Any]    						=      k_size // 2
      snake_case__  :    str    						=      mgrid[0 - center : k_size - center, 0 - center : k_size - center]
      snake_case__  :    Union[str, Any]    						=      1 / (2 * pi * sigma) * exp(-(square(_lowerCAmelCase		) + square(_lowerCAmelCase		)) / (2 * square(_lowerCAmelCase		))		)
      return g





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		)		-> List[Any]:
      snake_case__  :    str    						=      image.shape[0], image.shape[1]
      # dst image height and width
      snake_case__  :    str    						=      height - k_size + 1
      snake_case__  :    int    						=      width - k_size + 1

      # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
      snake_case__  :    int    						=      zeros((dst_height * dst_width, k_size * k_size)		)
      snake_case__  :    Tuple    						=      0
      for i, j in product(range(_lowerCAmelCase		)     ,   range(_lowerCAmelCase		)		):
            snake_case__  :    Optional[int]    						=      ravel(image[i : i + k_size, j : j + k_size]		)
            snake_case__  :    Optional[Any]    						=      window
            row += 1

      #  turn the kernel into shape(k*k, 1)
      snake_case__  :    Union[str, Any]    						=      gen_gaussian_kernel(_lowerCAmelCase     ,   _lowerCAmelCase		)
      snake_case__  :    List[Any]    						=      ravel(_lowerCAmelCase		)

      # reshape and get the dst image
      snake_case__  :    Dict    						=      dot(_lowerCAmelCase     ,   _lowerCAmelCase		).reshape(_lowerCAmelCase     ,   _lowerCAmelCase		).astype(_lowerCAmelCase		)

      return dst


if __name__ == "__main__":
       # read original image
       __a          =		imread(R"../image_data/lena.jpg")
       # turn image in gray scale value
       __a          =		cvtColor(img, COLOR_BGR2GRAY)

       # get values with two different mask size
       __a          =		gaussian_filter(gray, 3, sigma=1)
       __a          =		gaussian_filter(gray, 5, sigma=0.8)

       # show result images
       imshow("gaussian filter with 3x3 mask", gaussianaxa)
       imshow("gaussian filter with 5x5 mask", gaussianaxa)
       waitKey()


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


_lowerCamelCase					   ={
    """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""": 1_2_8,
    """add_cross_attention""": True,
    """tie_encoder_decoder""": True,
    """max_length""": 5_0,
    """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""": 1_0,
    """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""": 1_0,
    """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 							A__		(	unittest.TestCase):
      @classmethod
      def 						UpperCamelCase__							(      cls      ):
       lowerCamelCase		:	int							=      TOKEN
       HfFolder.save_token(__magic_name__      )
      @classmethod
      def 						UpperCamelCase__							(      cls      ):
       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      ):
       lowerCamelCase		:	List[Any]							=      BertConfig(
           vocab_size=9_9    ,  hidden_size=3_2    ,  num_hidden_layers=5    ,  num_attention_heads=4    ,  intermediate_size=3_7      )
       config.push_to_hub("""test-config"""    ,  use_auth_token=self._token      )

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

        # 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(__magic_name__    ,  repo_id="""test-config"""    ,  push_to_hub=__magic_name__    ,  use_auth_token=self._token      )

       lowerCamelCase		:	Optional[Any]							=      BertConfig.from_pretrained(F'''{USER}/test-config'''      )
       for k, v in config.to_dict().items():
        if k != "transformers_version":
         self.assertEqual(__magic_name__    ,  getattr(__magic_name__    ,  __magic_name__      )      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Dict							=      BertConfig(
           vocab_size=9_9    ,  hidden_size=3_2    ,  num_hidden_layers=5    ,  num_attention_heads=4    ,  intermediate_size=3_7      )
       config.push_to_hub("""valid_org/test-config-org"""    ,  use_auth_token=self._token      )

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

        # 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(
            __magic_name__    ,  repo_id="""valid_org/test-config-org"""    ,  push_to_hub=__magic_name__    ,  use_auth_token=self._token      )

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






      def 						UpperCamelCase__							(      self      ):
       CustomConfig.register_for_auto_class()
       lowerCamelCase		:	Optional[Any]							=      CustomConfig(attribute=4_2      )

       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"""}      )

       lowerCamelCase		:	List[str]							=      AutoConfig.from_pretrained(F'''{USER}/test-dynamic-config'''    ,  trust_remote_code=__magic_name__      )
       # 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    ,  4_2      )





class 							A__		(	unittest.TestCase):
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	str							=      GPTaConfig()

       # attempt to modify each of int/float/bool/str config records and verify they were updated
       lowerCamelCase		:	Optional[int]							=      c.n_embd + 1  # int
       lowerCamelCase		:	Optional[int]							=      c.resid_pdrop + 1.0  # float
       lowerCamelCase		:	Tuple							=      not c.scale_attn_weights  # bool
       lowerCamelCase		:	Any							=      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(__magic_name__    ,  c.n_embd    ,  """mismatch for key: n_embd"""      )
       self.assertEqual(__magic_name__    ,  c.resid_pdrop    ,  """mismatch for key: resid_pdrop"""      )
       self.assertEqual(__magic_name__    ,  c.scale_attn_weights    ,  """mismatch for key: scale_attn_weights"""      )
       self.assertEqual(__magic_name__    ,  c.summary_type    ,  """mismatch for key: summary_type"""      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	str							=      PretrainedConfig()
       lowerCamelCase		:	int							=      [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(
           __magic_name__    ,  ["""is_encoder_decoder""", """_name_or_path""", """_commit_hash""", """transformers_version"""]      )
       lowerCamelCase		:	List[str]							=      [key for key, value in config_common_kwargs.items() if value == getattr(__magic_name__    ,  __magic_name__      )]
       if len(__magic_name__      ) > 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(__magic_name__      )}.'''      )
      def 						UpperCamelCase__							(      self      ):
       with self.assertRaises(__magic_name__      ):
        # config is in subfolder, the following should not work without specifying the subfolder
        lowerCamelCase		:	Dict							=      BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert-subfolder"""      )

       lowerCamelCase		:	str							=      BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert-subfolder"""    ,  subfolder="""bert"""      )

       self.assertIsNotNone(__magic_name__      )
      def 						UpperCamelCase__							(      self      ):
       # A mock response for an HTTP head request to emulate server down
       lowerCamelCase		:	Dict							=      mock.Mock()
       lowerCamelCase		:	Optional[int]							=      5_0_0
       lowerCamelCase		:	List[Any]							=      {}
       lowerCamelCase		:	Tuple							=      HTTPError
       lowerCamelCase		:	Union[str, Any]							=      {}

       # Download this model to make sure it's in the cache.
       lowerCamelCase		:	List[str]							=      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=__magic_name__      ) as mock_head:
        lowerCamelCase		:	Any							=      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      ):
       # This test is for deprecated behavior and can be removed in v5
       lowerCamelCase		:	List[str]							=      BertConfig.from_pretrained(
           """https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json"""      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Optional[int]							=      AutoConfig.from_pretrained("""bert-base-cased"""      )
       lowerCamelCase		:	Optional[Any]							=      ["""config.4.0.0.json"""]

       with tempfile.TemporaryDirectory() as tmp_dir:
        configuration.save_pretrained(__magic_name__      )
        lowerCamelCase		:	str							=      2
        json.dump(configuration.to_dict()    ,  open(os.path.join(__magic_name__    ,  """config.4.0.0.json"""      )    ,  """w"""      )      )

        # This should pick the new configuration file as the version of Transformers is > 4.0.0
        lowerCamelCase		:	Union[str, Any]							=      AutoConfig.from_pretrained(__magic_name__      )
        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
        lowerCamelCase		:	Any							=      ["""config.42.0.0.json"""]
        lowerCamelCase		:	Optional[Any]							=      7_6_8
        configuration.save_pretrained(__magic_name__      )
        shutil.move(os.path.join(__magic_name__    ,  """config.4.0.0.json"""      )    ,  os.path.join(__magic_name__    ,  """config.42.0.0.json"""      )      )
        lowerCamelCase		:	int							=      AutoConfig.from_pretrained(__magic_name__      )
        self.assertEqual(new_configuration.hidden_size    ,  7_6_8      )






      def 						UpperCamelCase__							(      self      ):
       # This repo has two configuration files, one for v4.0.0 and above with a different hidden size.
       lowerCamelCase		:	str							=      """hf-internal-testing/test-two-configs"""

       import transformers as new_transformers

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

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

       lowerCamelCase		:	Tuple							=      """v3.0.0"""
       lowerCamelCase		:	Any							=      old_transformers.models.auto.AutoConfig.from_pretrained(__magic_name__      )
       self.assertEqual(old_configuration.hidden_size    ,  7_6_8      )




