






"""simple docstring"""







# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import json
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import yaml

from ...utils import ComputeEnvironment, DistributedType, SageMakerDistributedType
from ...utils.constants import SAGEMAKER_PYTHON_VERSION, SAGEMAKER_PYTORCH_VERSION, SAGEMAKER_TRANSFORMERS_VERSION


lowerCAmelCase_		:			int				   =					os.path.expanduser(
    os.getenv('''HF_HOME''', os.path.join(os.getenv('''XDG_CACHE_HOME''', '''~/.cache'''), '''huggingface'''))
)
lowerCAmelCase_		:			Optional[int]				   =					os.path.join(hf_cache_home, '''accelerate''')
lowerCAmelCase_		:			List[Any]				   =					os.path.join(cache_dir, '''default_config.yaml''')
lowerCAmelCase_		:			Dict				   =					os.path.join(cache_dir, '''default_config.yaml''')

# For backward compatibility: the default config is the json one if it's the only existing file.
if os.path.isfile(default_yaml_config_file) or not os.path.isfile(default_json_config_file):
 lowerCAmelCase_		:			Optional[int]				   =					default_yaml_config_file
else:
 lowerCAmelCase_		:			Optional[Any]				   =					default_json_config_file






def 					_lowerCAmelCase				(					lowerCAmelCase						):







       '''simple docstring'''
       if config_file is not None:
              if not os.path.isfile(lowerCAmelCase						):
                     raise FileNotFoundError(
                         F'''The passed configuration file `{config_file}` does not exist. '''
                         """Please pass an existing file to `accelerate launch`, or use the the default one """
                         """created through `accelerate config` and run `accelerate launch` """
                         """without the `--config_file` argument."""						)
       else:
              UpperCAmelCase					=	default_config_file
       with open(lowerCAmelCase		,					"""r"""		,					encoding="""utf-8"""						) as f:
              if config_file.endswith(""".json"""						):
                     if (
                         json.load(lowerCAmelCase						).get("""compute_environment"""		,					ComputeEnvironment.LOCAL_MACHINE						)
                         == ComputeEnvironment.LOCAL_MACHINE
                     ):
                            UpperCAmelCase					=	ClusterConfig
                     else:
                            UpperCAmelCase					=	SageMakerConfig
                     return config_class.from_json_file(json_file=lowerCAmelCase						)
              else:
                     if (
                         yaml.safe_load(lowerCAmelCase						).get("""compute_environment"""		,					ComputeEnvironment.LOCAL_MACHINE						)
                         == ComputeEnvironment.LOCAL_MACHINE
                     ):
                            UpperCAmelCase					=	ClusterConfig
                     else:
                            UpperCAmelCase					=	SageMakerConfig
                     return config_class.from_yaml_file(yaml_file=lowerCAmelCase						)





@dataclass
class      UpperCamelCase_       :
  _A				:    ComputeEnvironment
  _A				:    Union[DistributedType, SageMakerDistributedType]
  _A				:    str
  _A				:    bool



  def 						UpperCamelCase_ (					self )	->	Tuple:



         """simple docstring"""





         UpperCAmelCase					=	self.__dict__
         # For serialization, it's best to convert Enums to strings (or their underlying value type).
         for key, value in result.items():
                if isinstance(snake_case__       ,						snake_case__ ):
                       UpperCAmelCase					=	value.value
                if isinstance(snake_case__       ,						snake_case__ ) and not bool(snake_case__ ):
                       UpperCAmelCase					=	None
         UpperCAmelCase					=	{k: v for k, v in result.items() if v is not None}
         return result



  @classmethod
  def 						UpperCamelCase_ (					cls       ,						snake_case__=None )	->	int:



         """simple docstring"""





         UpperCAmelCase					=	default_json_config_file if json_file is None else json_file
         with open(snake_case__       ,						"""r"""       ,						encoding="""utf-8""" ) as f:
                UpperCAmelCase					=	json.load(snake_case__ )
         if "compute_environment" not in config_dict:
                UpperCAmelCase					=	ComputeEnvironment.LOCAL_MACHINE
         if "mixed_precision" not in config_dict:
                UpperCAmelCase					=	"""fp16""" if ("""fp16""" in config_dict and config_dict["""fp16"""]) else None
         if "fp16" in config_dict:  # Convert the config to the new format.
                del config_dict["fp16"]
         if "dynamo_backend" in config_dict:  # Convert the config to the new format.
                UpperCAmelCase					=	config_dict.pop("""dynamo_backend""" )
                UpperCAmelCase					=	{} if dynamo_backend == """NO""" else {"""dynamo_backend""": dynamo_backend}
         if "use_cpu" not in config_dict:
                UpperCAmelCase					=	False
         return cls(**snake_case__ )



  def 						UpperCamelCase_ (					self       ,						snake_case__ )	->	Optional[int]:



         """simple docstring"""





         with open(snake_case__       ,						"""w"""       ,						encoding="""utf-8""" ) as f:
                UpperCAmelCase					=	json.dumps(self.to_dict()       ,						indent=2       ,						sort_keys=snake_case__ ) + """\n"""
                f.write(snake_case__ )



  @classmethod
  def 						UpperCamelCase_ (					cls       ,						snake_case__=None )	->	Union[str, Any]:



         """simple docstring"""





         UpperCAmelCase					=	default_yaml_config_file if yaml_file is None else yaml_file
         with open(snake_case__       ,						"""r"""       ,						encoding="""utf-8""" ) as f:
                UpperCAmelCase					=	yaml.safe_load(snake_case__ )
         if "compute_environment" not in config_dict:
                UpperCAmelCase					=	ComputeEnvironment.LOCAL_MACHINE

         if "mixed_precision" not in config_dict:
                UpperCAmelCase					=	"""fp16""" if ("""fp16""" in config_dict and config_dict["""fp16"""]) else None
         if isinstance(config_dict["""mixed_precision"""]       ,						snake_case__ ) and not config_dict["mixed_precision"]:
                UpperCAmelCase					=	"""no"""
         if "fp16" in config_dict:  # Convert the config to the new format.
                del config_dict["fp16"]
         if "dynamo_backend" in config_dict:  # Convert the config to the new format.
                UpperCAmelCase					=	config_dict.pop("""dynamo_backend""" )
                UpperCAmelCase					=	{} if dynamo_backend == """NO""" else {"""dynamo_backend""": dynamo_backend}
         if "use_cpu" not in config_dict:
                UpperCAmelCase					=	False
         return cls(**snake_case__ )



  def 						UpperCamelCase_ (					self       ,						snake_case__ )	->	Dict:



         """simple docstring"""





         with open(snake_case__       ,						"""w"""       ,						encoding="""utf-8""" ) as f:
                yaml.safe_dump(self.to_dict()       ,						snake_case__ )



  def 						UpperCamelCase_ (					self )	->	Optional[Any]:



         """simple docstring"""





         if isinstance(self.compute_environment       ,						snake_case__ ):
                UpperCAmelCase					=	ComputeEnvironment(self.compute_environment )
         if isinstance(self.distributed_type       ,						snake_case__ ):
                if self.compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
                       UpperCAmelCase					=	SageMakerDistributedType(self.distributed_type )
                else:
                       UpperCAmelCase					=	DistributedType(self.distributed_type )
         if self.dynamo_config is None:
                UpperCAmelCase					=	{}





@dataclass
class      UpperCamelCase_       (				a_     ):
  _A				:    int
  _A				:    int =		0
  _A				:    int =		1
  _A				:    Optional[str] =		None
  _A				:    Optional[str] =		None
  _A				:    Optional[int] =		None
  _A				:    Optional[str] =		"static"
  _A				:    Optional[bool] =		False
  _A				:    str =		"main"

  # args for deepspeed_plugin
  _A				:    dict =		None
  # args for fsdp
  _A				:    dict =		None
  # args for megatron_lm
  _A				:    dict =		None
  # args for ipex
  _A				:    dict =		None
  # args for TPU
  _A				:    bool =		False

  # args for TPU pods
  _A				:    str =		None
  _A				:    str =		None
  _A				:    bool =		False
  _A				:    bool =		False
  _A				:    str =		None
  _A				:    List[str] =		None
  _A				:    List[str] =		None
  _A				:    List[str] =		None

  # args for dynamo
  _A				:    dict =		None



  def 						UpperCamelCase_ (					self )	->	Any:



         """simple docstring"""





         if self.deepspeed_config is None:
                UpperCAmelCase					=	{}
         if self.fsdp_config is None:
                UpperCAmelCase					=	{}
         if self.megatron_lm_config is None:
                UpperCAmelCase					=	{}
         if self.ipex_config is None:
                UpperCAmelCase					=	{}
         return super().__post_init__()





@dataclass
class      UpperCamelCase_       (				a_     ):
  _A				:    str
  _A				:    str
  _A				:    Optional[str] =		None
  _A				:    Optional[str] =		None
  _A				:    str =		"us-east-1"
  _A				:    int =		1
  _A				:    str =		"all"
  _A				:    str =		f'''accelerate-sagemaker-{num_machines}'''
  _A				:    str =		SAGEMAKER_PYTORCH_VERSION
  _A				:    str =		SAGEMAKER_TRANSFORMERS_VERSION
  _A				:    str =		SAGEMAKER_PYTHON_VERSION
  _A				:    str =		None
  _A				:    str =		None
  _A				:    dict =		None
  _A				:    dict =		None








"""simple docstring"""







import cva
import numpy as np

from digital_image_processing.filters.convolve import img_convolve
from digital_image_processing.filters.sobel_filter import sobel_filter

lowerCAmelCase_		:			List[Any]				   =					1_8_0






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       UpperCAmelCase					=	k_size // 2
       UpperCAmelCase			,				UpperCAmelCase					=	np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
       UpperCAmelCase					=	(
           1
           / (2 * np.pi * sigma)
           * np.exp(-(np.square(lowerCAmelCase						) + np.square(lowerCAmelCase						)) / (2 * np.square(lowerCAmelCase						))						)
       )
       return g






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       UpperCAmelCase					=	np.zeros(lowerCAmelCase						)

       for row in range(1		,					image_shape[0] - 1						):
              for col in range(1		,					image_shape[1] - 1						):
                     UpperCAmelCase					=	gradient_direction[row, col]

                     if (
                         0 <= direction < PI / 8
                         or 15 * PI / 8 <= direction <= 2 * PI
                         or 7 * PI / 8 <= direction <= 9 * PI / 8
                     ):
                            UpperCAmelCase					=	sobel_grad[row, col - 1]
                            UpperCAmelCase					=	sobel_grad[row, col + 1]
                            if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
                                   UpperCAmelCase					=	sobel_grad[row, col]

                     elif (
                         PI / 8 <= direction < 3 * PI / 8
                         or 9 * PI / 8 <= direction < 11 * PI / 8
                     ):
                            UpperCAmelCase					=	sobel_grad[row + 1, col - 1]
                            UpperCAmelCase					=	sobel_grad[row - 1, col + 1]
                            if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
                                   UpperCAmelCase					=	sobel_grad[row, col]

                     elif (
                         3 * PI / 8 <= direction < 5 * PI / 8
                         or 11 * PI / 8 <= direction < 13 * PI / 8
                     ):
                            UpperCAmelCase					=	sobel_grad[row - 1, col]
                            UpperCAmelCase					=	sobel_grad[row + 1, col]
                            if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
                                   UpperCAmelCase					=	sobel_grad[row, col]

                     elif (
                         5 * PI / 8 <= direction < 7 * PI / 8
                         or 13 * PI / 8 <= direction < 15 * PI / 8
                     ):
                            UpperCAmelCase					=	sobel_grad[row - 1, col - 1]
                            UpperCAmelCase					=	sobel_grad[row + 1, col + 1]
                            if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
                                   UpperCAmelCase					=	sobel_grad[row, col]

       return destination






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       for row in range(1		,					image_shape[0] - 1						):
              for col in range(1		,					image_shape[1] - 1						):
                     if destination[row, col] >= threshold_high:
                            UpperCAmelCase					=	strong
                     elif destination[row, col] <= threshold_low:
                            UpperCAmelCase					=	0
                     else:
                            UpperCAmelCase					=	weak






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       for row in range(1		,					image_shape[0]						):
              for col in range(1		,					image_shape[1]						):
                     if destination[row, col] == weak:
                            if 255 in (
                                destination[row, col + 1],
                                destination[row, col - 1],
                                destination[row - 1, col],
                                destination[row + 1, col],
                                destination[row - 1, col - 1],
                                destination[row + 1, col - 1],
                                destination[row - 1, col + 1],
                                destination[row + 1, col + 1],
                            ):
                                   UpperCAmelCase					=	strong
                            else:
                                   UpperCAmelCase					=	0






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase=15		,					lowerCAmelCase=30		,					lowerCAmelCase=128		,					lowerCAmelCase=255						):







       '''simple docstring'''
       # gaussian_filter
       UpperCAmelCase					=	img_convolve(lowerCAmelCase		,					gen_gaussian_kernel(9		,					sigma=1.4						)						)
       # get the gradient and degree by sobel_filter
       UpperCAmelCase			,				UpperCAmelCase					=	sobel_filter(lowerCAmelCase						)
       UpperCAmelCase					=	PI + np.radadeg(lowerCAmelCase						)

       UpperCAmelCase					=	suppress_non_maximum(image.shape		,					lowerCAmelCase		,					lowerCAmelCase						)

       detect_high_low_threshold(
           image.shape		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase						)

       track_edge(image.shape		,					lowerCAmelCase		,					lowerCAmelCase		,					lowerCAmelCase						)

       return destination


if __name__ == "__main__":
 # read original image in gray mode
 lowerCAmelCase_		:			Optional[Any]				   =					cva.imread(R'''../image_data/lena.jpg''', 0)
 # canny edge detection
 lowerCAmelCase_		:			Dict				   =					canny(lena)
 cva.imshow('''canny''', canny_destination)
 cva.waitKey(0)
