


'''simple docstring'''






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


def       _snake_case     (  A				,					A				,					A				,					A				,					A				,					A )		->					np.ndarray:

							# prepare kernel
							# the kernel size have to be odd
							if (ksize % 2) == 0:
														lowerCAmelCase__      =			ksize + 1
							lowerCAmelCase__      =			np.zeros((ksize, ksize)				,					dtype=np.floataa )

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

																					# degree to radiant
																					lowerCAmelCase__      =			theta / 180 * np.pi
																					lowerCAmelCase__      =			np.cos(_theta )
																					lowerCAmelCase__      =			np.sin(_theta )

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

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

																					# fill kernel
																					lowerCAmelCase__      =			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
		__UpperCAmelCase					       =							imread('''../image_data/lena.jpg''')
		# turn image in gray scale value
		__UpperCAmelCase					       =							cvtColor(img, COLOR_BGR2GRAY)

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

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

		waitKey(0)



'''simple docstring'''






import tempfile
import unittest

import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax


if is_flax_available():
		import os

		from flax.core.frozen_dict import unfreeze
		from flax.traverse_util import flatten_dict

		from transformers import FlaxBertModel

		__UpperCAmelCase					       =							'''0.12'''  # assumed parallelism: 8




@require_flax
@is_staging_test
class 	a__       (							unittest.TestCase						):





							'''simple docstring'''






							@classmethod
							def 						__SCREAMING_SNAKE_CASE							(	cls     ) ->							Any:
														lowerCAmelCase__      =			TOKEN
														HfFolder.save_token(lowerCamelCase_     )







							@classmethod
							def 						__SCREAMING_SNAKE_CASE							(	cls     ) ->							Tuple:
														try:
																					delete_repo(token=cls._token      ,					repo_id='''test-model-flax'''     )
														except HTTPError:
																					pass

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







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[Any]:
														lowerCAmelCase__      =			BertConfig(
														    vocab_size=99      ,					hidden_size=32      ,					num_hidden_layers=5      ,					num_attention_heads=4      ,					intermediate_size=37     )
														lowerCAmelCase__      =			FlaxBertModel(lowerCamelCase_     )
														model.push_to_hub('''test-model-flax'''      ,					use_auth_token=self._token     )

														lowerCAmelCase__      =			FlaxBertModel.from_pretrained(F"""{USER}/test-model-flax"""     )

														lowerCAmelCase__      =			flatten_dict(unfreeze(model.params     )     )
														lowerCAmelCase__      =			flatten_dict(unfreeze(new_model.params     )     )

														for key in base_params.keys():
																					lowerCAmelCase__      =			(base_params[key] - new_params[key]).sum().item()
																					self.assertLessEqual(lowerCamelCase_      ,					1e-3      ,					msg=F"""{key} not identical"""     )

														# Reset repo
														delete_repo(token=self._token      ,					repo_id='''test-model-flax'''     )

														# Push to hub via save_pretrained
														with tempfile.TemporaryDirectory() as tmp_dir:
																					model.save_pretrained(lowerCamelCase_      ,					repo_id='''test-model-flax'''      ,					push_to_hub=lowerCamelCase_      ,					use_auth_token=self._token     )

														lowerCAmelCase__      =			FlaxBertModel.from_pretrained(F"""{USER}/test-model-flax"""     )

														lowerCAmelCase__      =			flatten_dict(unfreeze(model.params     )     )
														lowerCAmelCase__      =			flatten_dict(unfreeze(new_model.params     )     )

														for key in base_params.keys():
																					lowerCAmelCase__      =			(base_params[key] - new_params[key]).sum().item()
																					self.assertLessEqual(lowerCamelCase_      ,					1e-3      ,					msg=F"""{key} not identical"""     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Union[str, Any]:
														lowerCAmelCase__      =			BertConfig(
														    vocab_size=99      ,					hidden_size=32      ,					num_hidden_layers=5      ,					num_attention_heads=4      ,					intermediate_size=37     )
														lowerCAmelCase__      =			FlaxBertModel(lowerCamelCase_     )
														model.push_to_hub('''valid_org/test-model-flax-org'''      ,					use_auth_token=self._token     )

														lowerCAmelCase__      =			FlaxBertModel.from_pretrained('''valid_org/test-model-flax-org'''     )

														lowerCAmelCase__      =			flatten_dict(unfreeze(model.params     )     )
														lowerCAmelCase__      =			flatten_dict(unfreeze(new_model.params     )     )

														for key in base_params.keys():
																					lowerCAmelCase__      =			(base_params[key] - new_params[key]).sum().item()
																					self.assertLessEqual(lowerCamelCase_      ,					1e-3      ,					msg=F"""{key} not identical"""     )

														# Reset repo
														delete_repo(token=self._token      ,					repo_id='''valid_org/test-model-flax-org'''     )

														# Push to hub via save_pretrained
														with tempfile.TemporaryDirectory() as tmp_dir:
																					model.save_pretrained(
																					    lowerCamelCase_      ,					repo_id='''valid_org/test-model-flax-org'''      ,					push_to_hub=lowerCamelCase_      ,					use_auth_token=self._token     )

														lowerCAmelCase__      =			FlaxBertModel.from_pretrained('''valid_org/test-model-flax-org'''     )

														lowerCAmelCase__      =			flatten_dict(unfreeze(model.params     )     )
														lowerCAmelCase__      =			flatten_dict(unfreeze(new_model.params     )     )

														for key in base_params.keys():
																					lowerCAmelCase__      =			(base_params[key] - new_params[key]).sum().item()
																					self.assertLessEqual(lowerCamelCase_      ,					1e-3      ,					msg=F"""{key} not identical"""     )


def       _snake_case     (  A				,					A )		->					Optional[int]:
							lowerCAmelCase__      =			True
							lowerCAmelCase__      =			flatten_dict(modela.params )
							lowerCAmelCase__      =			flatten_dict(modela.params )
							for key in flat_params_a.keys():
														if np.sum(np.abs(flat_params_a[key] - flat_params_a[key] ) ) > 1E-4:
																					lowerCAmelCase__      =			False

							return models_are_equal






@require_flax
class 	a__       (							unittest.TestCase						):





							'''simple docstring'''






							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Optional[Any]:
														lowerCAmelCase__      =			BertConfig.from_pretrained('''hf-internal-testing/tiny-bert-flax-only'''     )
														lowerCAmelCase__      =			FlaxBertModel(lowerCamelCase_     )

														lowerCAmelCase__      =			'''bert'''
														with tempfile.TemporaryDirectory() as tmp_dir:
																					model.save_pretrained(os.path.join(lowerCamelCase_      ,					lowerCamelCase_     )     )

																					with self.assertRaises(lowerCamelCase_     ):
																												lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_     )

																					lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_      ,					subfolder=lowerCamelCase_     )

														self.assertTrue(check_models_equal(lowerCamelCase_      ,					lowerCamelCase_     )     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[Any]:
														lowerCAmelCase__      =			BertConfig.from_pretrained('''hf-internal-testing/tiny-bert-flax-only'''     )
														lowerCAmelCase__      =			FlaxBertModel(lowerCamelCase_     )

														lowerCAmelCase__      =			'''bert'''
														with tempfile.TemporaryDirectory() as tmp_dir:
																					model.save_pretrained(os.path.join(lowerCamelCase_      ,					lowerCamelCase_     )      ,					max_shard_size='''10KB'''     )

																					with self.assertRaises(lowerCamelCase_     ):
																												lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_     )

																					lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_      ,					subfolder=lowerCamelCase_     )

														self.assertTrue(check_models_equal(lowerCamelCase_      ,					lowerCamelCase_     )     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Optional[Any]:
														lowerCAmelCase__      =			'''bert'''
														lowerCAmelCase__      =			'''hf-internal-testing/tiny-random-bert-subfolder'''

														with self.assertRaises(lowerCamelCase_     ):
																					lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_     )

														lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_      ,					subfolder=lowerCamelCase_     )

														self.assertIsNotNone(lowerCamelCase_     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[Any]:
														lowerCAmelCase__      =			'''bert'''
														lowerCAmelCase__      =			'''hf-internal-testing/tiny-random-bert-sharded-subfolder'''
														with self.assertRaises(lowerCamelCase_     ):
																					lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_     )

														lowerCAmelCase__      =			FlaxBertModel.from_pretrained(lowerCamelCase_      ,					subfolder=lowerCamelCase_     )

														self.assertIsNotNone(lowerCamelCase_     )