




'''simple docstring'''





import argparse
import os
import platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available


def 					UpperCamelCase_(     snake_case							:	Union[str, Any]=None					):

							'''simple docstring'''






							if subparsers is not None:
														snake_case_      =				subparsers.add_parser("env"					)
							else:
														snake_case_      =				argparse.ArgumentParser("Accelerate env command"					)

							parser.add_argument(
							    "--config_file"							,    default=_UpperCamelCase							,    help="The config file to use for the default values in the launching script."					)

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


def 					UpperCamelCase_(     snake_case							:	Dict					):

							'''simple docstring'''






							snake_case_      =				torch.__version__
							snake_case_      =				torch.cuda.is_available()
							snake_case_      =				is_xpu_available()
							snake_case_      =				is_npu_available()

							snake_case_      =				"Not found"
							# Get the default from the config file.
							if args.config_file is not None or os.path.isfile(_UpperCamelCase					):
														snake_case_      =				load_config_from_file(args.config_file					).to_dict()

							snake_case_      =				{
							    "`Accelerate` version": version,
							    "Platform": platform.platform(),
							    "Python version": platform.python_version(),
							    "Numpy version": np.__version__,
							    "PyTorch version (GPU?)": f'{pt_version} ({pt_cuda_available})',
							    "PyTorch XPU available": str(_UpperCamelCase					),
							    "PyTorch NPU available": str(_UpperCamelCase					),
							    "System RAM": f'{psutil.virtual_memory().total / 1_0_2_4 ** 3:.2f} GB',
							}
							if pt_cuda_available:
														snake_case_      =				torch.cuda.get_device_name()

							print("\nCopy-and-paste the text below in your GitHub issue\n"					)
							print("\n".join([f'- {prop}: {val}' for prop, val in info.items()]					)					)

							print("- `Accelerate` default config:" if args.config_file is None else "- `Accelerate` config passed:"					)
							snake_case_      =				(
							    "\n".join([f'\t- {prop}: {val}' for prop, val in accelerate_config.items()]					)
							    if isinstance(_UpperCamelCase							,    _UpperCamelCase					)
							    else f'\t{accelerate_config}'
							)
							print(_UpperCamelCase					)

							snake_case_      =				accelerate_config

							return info


def 					UpperCamelCase_(     ):

							'''simple docstring'''






							snake_case_      =				env_command_parser()
							snake_case_      =				parser.parse_args()
							env_command(_UpperCamelCase					)
							return 0


if __name__ == "__main__":
		raise SystemExit(main())










'''simple docstring'''





from __future__ import annotations

from scipy.special import comb  # type: ignore




class 			_snake_case		:




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

										'''simple docstring'''




										snake_case_      =				list_of_points
										# Degree determines the flexibility of the curve.
										# Degree = 1 will produce a straight line.
										snake_case_      =				len(a__							) - 1




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    list[float]:

										'''simple docstring'''




										assert 0 <= t <= 1, "Time t must be between 0 and 1."
										snake_case_      =				[]
										for i in range(len(self.list_of_points							)							):
																	# basis function for each i
																	output_values.append(
																	    comb(self.degree    ,							a__							) * ((1 - t) ** (self.degree - i)) * (t**i)							)
										# the basis must sum up to 1 for it to produce a valid Bezier curve.
										assert round(sum(a__							)    ,							5							) == 1
										return output_values




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    tuple[float, float]:

										'''simple docstring'''




										assert 0 <= t <= 1, "Time t must be between 0 and 1."

										snake_case_      =				self.basis_function(a__							)
										snake_case_      =				0.0
										snake_case_      =				0.0
										for i in range(len(self.list_of_points							)							):
																	# For all points, sum up the product of i-th basis function and i-th point.
																	x += basis_function[i] * self.list_of_points[i][0]
																	y += basis_function[i] * self.list_of_points[i][1]
										return (x, y)




			def        lowerCAmelCase__    ( self    ,							a__ = 0.0_1							)    ->    Any:

										'''simple docstring'''




										from matplotlib import pyplot as plt  # type: ignore

										snake_case_      =				[]  # x coordinates of points to plot
										snake_case_      =				[]  # y coordinates of points to plot

										snake_case_      =				0.0
										while t <= 1:
																	snake_case_      =				self.bezier_curve_function(a__							)
																	to_plot_x.append(value[0]							)
																	to_plot_y.append(value[1]							)
																	t += step_size

										snake_case_      =				[i[0] for i in self.list_of_points]
										snake_case_      =				[i[1] for i in self.list_of_points]

										plt.plot(
										    a__    ,							a__    ,							color="blue"    ,							label="Curve of Degree " + str(self.degree							)    ,							)
										plt.scatter(a__    ,							a__    ,							color="red"    ,							label="Control Points"							)
										plt.legend()
										plt.show()


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
		BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
		BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3




