






import os


def   lowerCamelCase__			(     lowercase = "input.txt"				):

  """simple docstring"""






  with open(os.path.join(os.path.dirname(lowercase				)						,     lowercase				)				) as input_file:
    SCREAMING_SNAKE_CASE       :      List[str]							=    [
        [int(lowercase				) for element in line.split(","				)]
        for line in input_file.readlines()
    ]

  SCREAMING_SNAKE_CASE       :      Tuple							=    len(lowercase				)
  SCREAMING_SNAKE_CASE       :      Optional[Any]							=    len(matrix[0]				)

  SCREAMING_SNAKE_CASE       :      str							=    [[-1 for _ in range(lowercase				)] for _ in range(lowercase				)]
  for i in range(lowercase				):
    SCREAMING_SNAKE_CASE       :      Dict							=    matrix[i][0]

  for j in range(1						,     lowercase				):
    for i in range(lowercase				):
      SCREAMING_SNAKE_CASE       :      str							=    minimal_path_sums[i][j - 1] + matrix[i][j]

    for i in range(1						,     lowercase				):
      SCREAMING_SNAKE_CASE       :      Optional[Any]							=    min(
          minimal_path_sums[i][j]						,     minimal_path_sums[i - 1][j] + matrix[i][j]				)

    for i in range(rows - 2						,     -1						,     -1				):
      SCREAMING_SNAKE_CASE       :      str							=    min(
          minimal_path_sums[i][j]						,     minimal_path_sums[i + 1][j] + matrix[i][j]				)

  return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums				)


if __name__ == "__main__":
   print(F"""{solution() = }""")














# 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.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


snake_case    				=		"""Create a default config file for Accelerate with only a few flags set."""


def   lowerCamelCase__			(     lowercase="no"						,     lowercase = default_json_config_file						,     lowercase = False				):

  """simple docstring"""






  SCREAMING_SNAKE_CASE       :      Tuple							=    Path(lowercase				)
  path.parent.mkdir(parents=lowercase						,     exist_ok=lowercase				)
  if path.exists():
    print(
        F'''Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.'''				)
    return False
  SCREAMING_SNAKE_CASE       :      int							=    mixed_precision.lower()
  if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
    raise ValueError(
        F'''`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}'''				)
  SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    {
      "compute_environment": "LOCAL_MACHINE",
      "mixed_precision": mixed_precision,
  }
  if torch.cuda.is_available():
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    torch.cuda.device_count()
    SCREAMING_SNAKE_CASE       :      int							=    num_gpus
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    False
    if num_gpus > 1:
      SCREAMING_SNAKE_CASE       :      Tuple							=    "MULTI_GPU"
    else:
      SCREAMING_SNAKE_CASE       :      Optional[Any]							=    "NO"
  elif is_xpu_available() and use_xpu:
    SCREAMING_SNAKE_CASE       :      List[str]							=    torch.xpu.device_count()
    SCREAMING_SNAKE_CASE       :      str							=    num_xpus
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    False
    if num_xpus > 1:
      SCREAMING_SNAKE_CASE       :      Any							=    "MULTI_XPU"
    else:
      SCREAMING_SNAKE_CASE       :      str							=    "NO"
  elif is_npu_available():
    SCREAMING_SNAKE_CASE       :      List[Any]							=    torch.npu.device_count()
    SCREAMING_SNAKE_CASE       :      Optional[Any]							=    num_npus
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    False
    if num_npus > 1:
      SCREAMING_SNAKE_CASE       :      str							=    "MULTI_NPU"
    else:
      SCREAMING_SNAKE_CASE       :      int							=    "NO"
  else:
    SCREAMING_SNAKE_CASE       :      Dict							=    0
    SCREAMING_SNAKE_CASE       :      List[Any]							=    True
    SCREAMING_SNAKE_CASE       :      Dict							=    1
    SCREAMING_SNAKE_CASE       :      int							=    "NO"
  SCREAMING_SNAKE_CASE       :      Dict							=    ClusterConfig(**lowercase				)
  config.to_json_file(lowercase				)
  return path


def   lowerCamelCase__			(     lowercase						,     lowercase				):

  """simple docstring"""






  SCREAMING_SNAKE_CASE       :      Dict							=    parser.add_parser("default"						,     parents=lowercase						,     help=lowercase						,     formatter_class=lowercase				)
  parser.add_argument(
      "--config_file"						,     default=lowercase						,     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'."
      )						,     dest="save_location"						,     )

  parser.add_argument(
      "--mixed_precision"						,     choices=["no", "fp16", "bf16"]						,     type=lowercase						,     help="Whether or not to use mixed precision training. "
      "Choose between FP16 and BF16 (bfloat16) training. "
      "BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later."						,     default="no"						,     )
  parser.set_defaults(func=lowercase				)
  return parser


def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






  SCREAMING_SNAKE_CASE       :      Optional[int]							=    write_basic_config(args.mixed_precision						,     args.save_location				)
  if config_file:
    print(F'''accelerate configuration saved at {config_file}'''				)






