


'''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


_lowercase      :      int            =					{
    """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 	UpperCamelCase__(       unittest.TestCase	):




				@classmethod
				def 					a__(		cls      :			Dict				)->					Optional[Any]:

										"""simple docstring"""




										UpperCAmelCase					    =     TOKEN
										HfFolder.save_token(lowercase_				)




				@classmethod
				def 					a__(		cls      :			str				)->					Optional[int]:

										"""simple docstring"""




										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 					a__(		self      :			Union[str, Any]				)->					Dict:

										"""simple docstring"""




										UpperCAmelCase					    =     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				)

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

        # 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(lowercase_				,   repo_id='''test-config'''				,   push_to_hub=lowercase_				,   use_auth_token=self._token				)

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




				def 					a__(		self      :			Union[str, Any]				)->					Optional[int]:

										"""simple docstring"""




										UpperCAmelCase					    =     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				)

										UpperCAmelCase					    =     BertConfig.from_pretrained('''valid_org/test-config-org'''				)
										for k, v in config.to_dict().items():
																if k != "transformers_version":
																						self.assertEqual(lowercase_				,   getattr(lowercase_				,   lowercase_				)				)

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

										UpperCAmelCase					    =     BertConfig.from_pretrained('''valid_org/test-config-org'''				)
										for k, v in config.to_dict().items():
																if k != "transformers_version":
																						self.assertEqual(lowercase_				,   getattr(lowercase_				,   lowercase_				)				)





				def 					a__(		self      :			Tuple				)->					Optional[int]:

										"""simple docstring"""




										CustomConfig.register_for_auto_class()
										UpperCAmelCase					    =     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'''}				)

										UpperCAmelCase					    =     AutoConfig.from_pretrained(F"""{USER}/test-dynamic-config"""				,   trust_remote_code=lowercase_				)
										# 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 	UpperCamelCase__(       unittest.TestCase	):




				def 					a__(		self      :			str				)->					Optional[int]:

										"""simple docstring"""




										UpperCAmelCase					    =     GPTaConfig()

										# attempt to modify each of int/float/bool/str config records and verify they were updated
										UpperCAmelCase					    =     c.n_embd + 1  # int
										UpperCAmelCase					    =     c.resid_pdrop + 1.0  # float
										UpperCAmelCase					    =     not c.scale_attn_weights  # bool
										UpperCAmelCase					    =     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(lowercase_				,   c.n_embd				,   '''mismatch for key: n_embd'''				)
										self.assertEqual(lowercase_				,   c.resid_pdrop				,   '''mismatch for key: resid_pdrop'''				)
										self.assertEqual(lowercase_				,   c.scale_attn_weights				,   '''mismatch for key: scale_attn_weights'''				)
										self.assertEqual(lowercase_				,   c.summary_type				,   '''mismatch for key: summary_type'''				)




				def 					a__(		self      :			Tuple				)->					Dict:

										"""simple docstring"""




										UpperCAmelCase					    =     PretrainedConfig()
										UpperCAmelCase					    =     [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(
										    lowercase_				,   ['''is_encoder_decoder''', '''_name_or_path''', '''_commit_hash''', '''transformers_version''']				)
										UpperCAmelCase					    =     [key for key, value in config_common_kwargs.items() if value == getattr(lowercase_				,   lowercase_				)]
										if len(lowercase_				) > 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(lowercase_				)}."""				)




				def 					a__(		self      :			Dict				)->					int:

										"""simple docstring"""




										with self.assertRaises(lowercase_				):
																# config is in subfolder, the following should not work without specifying the subfolder
																UpperCAmelCase					    =     BertConfig.from_pretrained('''hf-internal-testing/tiny-random-bert-subfolder'''				)

										UpperCAmelCase					    =     BertConfig.from_pretrained('''hf-internal-testing/tiny-random-bert-subfolder'''				,   subfolder='''bert'''				)

										self.assertIsNotNone(lowercase_				)




				def 					a__(		self      :			List[Any]				)->					Optional[int]:

										"""simple docstring"""




										UpperCAmelCase					    =     mock.Mock()
										UpperCAmelCase					    =     500
										UpperCAmelCase					    =     {}
										UpperCAmelCase					    =     HTTPError
										UpperCAmelCase					    =     {}

										# Download this model to make sure it's in the cache.
										UpperCAmelCase					    =     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=lowercase_				) as mock_head:
																UpperCAmelCase					    =     BertConfig.from_pretrained('''hf-internal-testing/tiny-random-bert'''				)
																# This check we did call the fake head request
																mock_head.assert_called()




				def 					a__(		self      :			Dict				)->					List[Any]:

										"""simple docstring"""




										UpperCAmelCase					    =     BertConfig.from_pretrained(
										    '''https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json'''				)




				def 					a__(		self      :			Optional[Any]				)->					Tuple:

										"""simple docstring"""




										UpperCAmelCase					    =     AutoConfig.from_pretrained('''bert-base-cased'''				)
										UpperCAmelCase					    =     ['''config.4.0.0.json''']

										with tempfile.TemporaryDirectory() as tmp_dir:
																configuration.save_pretrained(lowercase_				)
																UpperCAmelCase					    =     2
																json.dump(configuration.to_dict()				,   open(os.path.join(lowercase_				,   '''config.4.0.0.json'''				)				,   '''w'''				)				)

																# This should pick the new configuration file as the version of Transformers is > 4.0.0
																UpperCAmelCase					    =     AutoConfig.from_pretrained(lowercase_				)
																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
																UpperCAmelCase					    =     ['''config.42.0.0.json''']
																UpperCAmelCase					    =     768
																configuration.save_pretrained(lowercase_				)
																shutil.move(os.path.join(lowercase_				,   '''config.4.0.0.json'''				)				,   os.path.join(lowercase_				,   '''config.42.0.0.json'''				)				)
																UpperCAmelCase					    =     AutoConfig.from_pretrained(lowercase_				)
																self.assertEqual(new_configuration.hidden_size				,   768				)





				def 					a__(		self      :			List[Any]				)->					List[Any]:

										"""simple docstring"""




										UpperCAmelCase					    =     '''hf-internal-testing/test-two-configs'''

										import transformers as new_transformers

										UpperCAmelCase					    =     '''v4.0.0'''
										UpperCAmelCase    ,    UpperCAmelCase					    =     new_transformers.models.auto.AutoConfig.from_pretrained(
										    lowercase_				,   return_unused_kwargs=lowercase_				)
										self.assertEqual(new_configuration.hidden_size				,   2				)
										# This checks `_configuration_file` ia not kept in the kwargs by mistake.
										self.assertDictEqual(lowercase_				,   {}				)

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

										UpperCAmelCase					    =     '''v3.0.0'''
										UpperCAmelCase					    =     old_transformers.models.auto.AutoConfig.from_pretrained(lowercase_				)
										self.assertEqual(old_configuration.hidden_size				,   768				)









'''simple docstring'''



import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey


def 				lowerCamelCase__				(	A       :      int				,       A       :      int				,       A       :      int				,       A       :      int				,       A       :      int				,       A       :      int					):




						'''simple docstring'''






						if (ksize % 2) == 0:
												UpperCAmelCase					    =     ksize + 1
						UpperCAmelCase					    =     np.zeros((ksize, ksize)				,       dtype=np.floataa					)

						# each value
						for y in range(A					):
												for x in range(A					):
																		# distance from center
																		UpperCAmelCase					    =     x - ksize // 2
																		UpperCAmelCase					    =     y - ksize // 2

																		# degree to radiant
																		UpperCAmelCase					    =     theta / 1_80 * np.pi
																		UpperCAmelCase					    =     np.cos(_theta					)
																		UpperCAmelCase					    =     np.sin(_theta					)

																		# get kernel x
																		UpperCAmelCase					    =     cos_theta * px + sin_theta * py

																		# get kernel y
																		UpperCAmelCase					    =     -sin_theta * px + cos_theta * py

																		# fill kernel
																		UpperCAmelCase					    =     np.exp(
																		    -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)					) * np.cos(2 * np.pi * _x / lambd + psi					)

						return gabor


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	# read original image
	_lowercase      :      Tuple            =					imread("""../image_data/lena.jpg""")
	# turn image in gray scale value
	_lowercase      :      int            =					cvtColor(img, COLOR_BGR2GRAY)

	# Apply multiple Kernel to detect edges
	_lowercase      :      List[str]            =					np.zeros(gray.shape[:2])
	for theta in [0, 30, 60, 90, 120, 150]:
		_lowercase      :      List[Any]            =					gabor_filter_kernel(10, 8, theta, 10, 0, 0)
		out += filteraD(gray, CV_8UC3, kernel_aa)
	_lowercase      :      Optional[int]            =					out / out.max() * 255
	_lowercase      :      Optional[int]            =					out.astype(np.uinta)

	imshow("""Original""", gray)
	imshow("""Gabor filter with 20x20 mask and 6 directions""", out)

	waitKey(0)





