





import math
import sys

import cva
import numpy as np


def     lowerCamelCase_	(      lowerCAmelCase:	str    ,							lowerCAmelCase:	Any				)->		np.ndarray:
  # For applying gaussian function for each element in matrix.
  _snake_case   :				Union[str, Any]														=	math.sqrt(__lowerCAmelCase				)
  _snake_case   :				Optional[Any]														=	1 / (sigma * math.sqrt(2 * math.pi				))
  return cons * np.exp(-((img / sigma) ** 2) * 0.5				)


def     lowerCamelCase_	(      lowerCAmelCase:	Optional[Any]    ,							lowerCAmelCase:	Any    ,							lowerCAmelCase:	int    ,							lowerCAmelCase:	Union[str, Any]				)->		np.ndarray:
  _snake_case   :				str														=	kernel_size // 2
  return img[x - half : x + half + 1, y - half : y + half + 1]


def     lowerCamelCase_	(      lowerCAmelCase:	List[Any]    ,							lowerCAmelCase:	Tuple				)->		np.ndarray:
  # Creates a gaussian kernel of given dimension.
  _snake_case   :				int														=	np.zeros((kernel_size, kernel_size)				)
  for i in range(0    ,							__lowerCAmelCase				):
    for j in range(0    ,							__lowerCAmelCase				):
      _snake_case   :				Tuple														=	math.sqrt(
          abs(i - kernel_size // 2				) ** 2 + abs(j - kernel_size // 2				) ** 2				)
  return vec_gaussian(__lowerCAmelCase    ,							__lowerCAmelCase				)


def     lowerCamelCase_	(      lowerCAmelCase:	int    ,							lowerCAmelCase:	Tuple    ,							lowerCAmelCase:	int    ,							lowerCAmelCase:	str    ,							)->		np.ndarray:
  _snake_case   :				Optional[Any]														=	np.zeros(img.shape				)
  _snake_case   :				Any														=	get_gauss_kernel(__lowerCAmelCase    ,							__lowerCAmelCase				)
  _snake_case   :				Any														=	img.shape
  for i in range(kernel_size // 2    ,							size_x - kernel_size // 2				):
    for j in range(kernel_size // 2    ,							size_y - kernel_size // 2				):
      _snake_case   :				str														=	get_slice(__lowerCAmelCase    ,							__lowerCAmelCase    ,							__lowerCAmelCase    ,							__lowerCAmelCase				)
      _snake_case   :				int														=	img_s - img_s[kernel_size // 2, kernel_size // 2]
      _snake_case   :				Optional[int]														=	vec_gaussian(__lowerCAmelCase    ,							__lowerCAmelCase				)
      _snake_case   :				Optional[Any]														=	np.multiply(__lowerCAmelCase    ,							__lowerCAmelCase				)
      _snake_case   :				List[str]														=	np.multiply(__lowerCAmelCase    ,							__lowerCAmelCase				)
      _snake_case   :				Dict														=	np.sum(__lowerCAmelCase				) / np.sum(__lowerCAmelCase				)
      _snake_case   :				Optional[Any]														=	val
  return imga


def     lowerCamelCase_	(      lowerCAmelCase:	Optional[Any]				)->		tuple:
  _snake_case   :				List[Any]														=	args[1] if args[1:] else """../image_data/lena.jpg"""
  _snake_case   :				Any														=	float(args[2]				) if args[2:] else 1.0
  _snake_case   :				Any														=	float(args[3]				) if args[3:] else 1.0
  if args[4:]:
    _snake_case   :				int														=	int(args[4]				)
    _snake_case   :				Tuple														=	kernel_size + abs(kernel_size % 2 - 1				)
  else:
    _snake_case   :				Union[str, Any]														=	5
  return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
   lowerCAmelCase_						   =    parse_args(sys.argv)
   lowerCAmelCase_						   =    cva.imread(filename, 0)
   cva.imshow("""input image""", img)

   lowerCAmelCase_						   =    img / 255
   lowerCAmelCase_						   =    out.astype("""float32""")
   lowerCAmelCase_						   =    bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
   lowerCAmelCase_						   =    out * 255
   lowerCAmelCase_						   =    np.uinta(out)
   cva.imshow("""output image""", out)
   cva.waitKey(0)
   cva.destroyAllWindows()











# 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 argparse
import os

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


lowerCAmelCase_						   =    """Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine"""


def     lowerCamelCase_	(      )->		Tuple:
  _snake_case   :				int														=	_ask_options(
      'In which compute environment are you running?'    ,							['This machine', 'AWS (Amazon SageMaker)']    ,							_convert_compute_environment    ,							)
  if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
    _snake_case   :				int														=	get_sagemaker_input()
  else:
    _snake_case   :				Any														=	get_cluster_input()
  return config


def     lowerCamelCase_	(      lowerCAmelCase:	str=None				)->		Any:
  if subparsers is not None:
    _snake_case   :				List[Any]														=	subparsers.add_parser('config'    ,							description=lowerCAmelCase				)
  else:
    _snake_case   :				Dict														=	argparse.ArgumentParser('Accelerate config command'    ,							description=lowerCAmelCase				)

  parser.add_argument(
      '--config_file'    ,							default=lowerCAmelCase    ,							help=(
          'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
          'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
          'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
          'with \'huggingface\'.'
      )    ,							)

  if subparsers is not None:
    parser.set_defaults(func=lowerCAmelCase				)
  return parser


def     lowerCamelCase_	(      lowerCAmelCase:	Any				)->		Any:
  _snake_case   :				Dict														=	get_user_input()
  if args.config_file is not None:
    _snake_case   :				List[str]														=	args.config_file
  else:
    if not os.path.isdir(lowerCAmelCase				):
      os.makedirs(lowerCAmelCase				)
    _snake_case   :				Union[str, Any]														=	default_yaml_config_file

  if config_file.endswith('.json'				):
    config.to_json_file(lowerCAmelCase				)
  else:
    config.to_yaml_file(lowerCAmelCase				)
  print(F"""accelerate configuration saved at {config_file}"""				)


def     lowerCamelCase_	(      )->		Dict:
  _snake_case   :				List[str]														=	config_command_parser()
  _snake_case   :				str														=	parser.parse_args()
  config_command(lowerCAmelCase				)


if __name__ == "__main__":
      main()




