






from dataclasses import dataclass
from typing import Tuple

import numpy as np
import torch
@dataclass
class  _UpperCAmelCase   :

				"""simple docstring"""




				lowercase__											=			42  # [batch_size x 3]
				lowercase__											=			42  # [batch_size x 3]
				lowercase__											=			42  # [batch_size x 3]
				lowercase__											=			42  # [batch_size x 3]
				lowercase__											=			42
				lowercase__											=			42
				lowercase__											=			42
				lowercase__											=			42
				lowercase__											=			42




				def 							lowercase__  (	self		:       Optional[int]    ):

								'''simple docstring'''
								assert self.x.shape[0] == self.y.shape[0] == self.z.shape[0] == self.origin.shape[0]
								assert self.x.shape[1] == self.y.shape[1] == self.z.shape[1] == self.origin.shape[1] == 3
								assert len(self.x.shape    ) == len(self.y.shape    ) == len(self.z.shape    ) == len(self.origin.shape    ) == 2




				def 							lowercase__  (	self		:       Dict    ):

								'''simple docstring'''
								return torch.from_numpy(np.array([self.width, self.height],    dtype=np.floataa    )    )




				def 							lowercase__  (	self		:       Optional[int]    ):

								'''simple docstring'''
								return torch.from_numpy(np.array([self.x_fov, self.y_fov],    dtype=np.floataa    )    )




				def 							lowercase__  (	self		:       Dict    ):

								'''simple docstring'''
								lowercase__  					=     torch.arange(self.height * self.width    )
								lowercase__  					=     torch.stack(
								    [
								        pixel_indices % self.width,
								        torch.div(lowerCamelCase,    self.width,    rounding_mode='''trunc'''    ),
								    ],    axis=1,    )
								return coords




				@property
				def 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								lowercase__					,		*lowercase__  					=     self.shape
								lowercase__  					=     int(np.prod(lowerCamelCase    )    )

								lowercase__  					=     self.get_image_coords()
								lowercase__  					=     torch.broadcast_to(coords.unsqueeze(0    ),    [batch_size * inner_batch_size, *coords.shape]    )
								lowercase__  					=     self.get_camera_rays(lowerCamelCase    )

								lowercase__  					=     rays.view(lowerCamelCase,    inner_batch_size * self.height * self.width,    2,    3    )

								return rays




				def 							lowercase__  (	self		:       Union[str, Any],    lowerCamelCase		:       torch.Tensor    ):

								'''simple docstring'''
								lowercase__					,		*lowercase__					,		lowercase__  					=     coords.shape
								assert n_coords == 2
								assert batch_size == self.origin.shape[0]

								lowercase__  					=     coords.view(lowerCamelCase,    -1,    2    )

								lowercase__  					=     self.resolution()
								lowercase__  					=     self.fov()

								lowercase__  					=     (flat.float() / (res - 1)) * 2 - 1
								lowercase__  					=     fracs * torch.tan(fov / 2    )

								lowercase__  					=     fracs.view(lowerCamelCase,    -1,    2    )
								lowercase__  					=     (
								    self.z.view(lowerCamelCase,    1,    3    )
								    + self.x.view(lowerCamelCase,    1,    3    ) * fracs[:, :, :1]
								    + self.y.view(lowerCamelCase,    1,    3    ) * fracs[:, :, 1:]
								)
								lowercase__  					=     directions / directions.norm(dim=-1,    keepdim=lowerCamelCase    )
								lowercase__  					=     torch.stack(
								    [
								        torch.broadcast_to(self.origin.view(lowerCamelCase,    1,    3    ),    [batch_size, directions.shape[1], 3]    ),
								        directions,
								    ],    dim=2,    )
								return rays.view(lowerCamelCase,    *lowerCamelCase,    2,    3    )




				def 							lowercase__  (	self		:       Optional[int],    lowerCamelCase		:       int,    lowerCamelCase		:       int    ):

								'''simple docstring'''
								assert width * self.height == height * self.width, "The aspect ratio should not change."
								return DifferentiableProjectiveCamera(
								    origin=self.origin,    x=self.x,    y=self.y,    z=self.z,    width=lowerCamelCase,    height=lowerCamelCase,    x_fov=self.x_fov,    y_fov=self.y_fov,    )






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     []
				lowercase__  					=     []
				lowercase__  					=     []
				lowercase__  					=     []
				for theta in np.linspace(0						,  2 * np.pi						,  num=20							):
								lowercase__  					=     np.array([np.sin(lowerCamelCase_							), np.cos(lowerCamelCase_							), -0.5]							)
								z /= np.sqrt(np.sum(z**2							)							)
								lowercase__  					=     -z * 4
								lowercase__  					=     np.array([np.cos(lowerCamelCase_							), -np.sin(lowerCamelCase_							), 0.0]							)
								lowercase__  					=     np.cross(lowerCamelCase_						,  lowerCamelCase_							)
								origins.append(lowerCamelCase_							)
								xs.append(lowerCamelCase_							)
								ys.append(lowerCamelCase_							)
								zs.append(lowerCamelCase_							)
				return DifferentiableProjectiveCamera(
				    origin=torch.from_numpy(np.stack(lowerCamelCase_						,  axis=0							)							).float()						,  x=torch.from_numpy(np.stack(lowerCamelCase_						,  axis=0							)							).float()						,  y=torch.from_numpy(np.stack(lowerCamelCase_						,  axis=0							)							).float()						,  z=torch.from_numpy(np.stack(lowerCamelCase_						,  axis=0							)							).float()						,  width=lowerCamelCase_						,  height=lowerCamelCase_						,  x_fov=0.7						,  y_fov=0.7						,  shape=(1, len(lowerCamelCase_							))						,  )












import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


A__      :     Tuple       =					{
    '<': operator.lt,
    '<=': operator.le,
    '==': operator.eq,
    '!=': operator.ne,
    '>=': operator.ge,
    '>': operator.gt,
}






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				if got_ver is None or want_ver is None:
								raise ValueError(
								    F"""Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider"""
								    F""" reinstalling {pkg}."""							)
				if not ops[op](version.parse(lowerCamelCase_							)						,  version.parse(lowerCamelCase_							)							):
								raise ImportError(
								    F"""{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}"""							)






def     a     (		lowerCamelCase_						,  lowerCamelCase_ = None							):






				'''simple docstring'''
				lowercase__  					=     F"""\n{hint}""" if hint is not None else ''''''

				# non-versioned check
				if re.match(r'''^[\w_\-\d]+$'''						,  lowerCamelCase_							):
								lowercase__					,		lowercase__					,		lowercase__  					=     requirement, None, None
				else:
								lowercase__  					=     re.findall(r'''^([^!=<>\s]+)([\s!=<>]{1,2}.+)'''						,  lowerCamelCase_							)
								if not match:
												raise ValueError(
												    '''requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but'''
												    F""" got {requirement}"""							)
								lowercase__					,		lowercase__  					=     match[0]
								lowercase__  					=     want_full.split(''','''							)  # there could be multiple requirements
								lowercase__  					=     {}
								for w in want_range:
												lowercase__  					=     re.findall(r'''^([\s!=<>]{1,2})(.+)'''						,  lowerCamelCase_							)
												if not match:
																raise ValueError(
																    '''requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,'''
																    F""" but got {requirement}"""							)
												lowercase__					,		lowercase__  					=     match[0]
												lowercase__  					=     want_ver
												if op not in ops:
																raise ValueError(F"""{requirement}: need one of {list(ops.keys()							)}, but got {op}"""							)

    # special case
				if pkg == "python":
								lowercase__  					=     '''.'''.join([str(lowerCamelCase_							) for x in sys.version_info[:3]]							)
								for op, want_ver in wanted.items():
												_compare_versions(lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							)
								return

				# check if any version is installed
				try:
								lowercase__  					=     importlib.metadata.version(lowerCamelCase_							)
				except importlib.metadata.PackageNotFoundError:
								raise importlib.metadata.PackageNotFoundError(
								    F"""The '{requirement}' distribution was not found and is required by this application. {hint}"""							)

				# check that the right version is installed if version number or a range was provided
				if want_ver is not None:
								for op, want_ver in wanted.items():
												_compare_versions(lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							)






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     '''Try: pip install transformers -U or pip install -e \'.[dev]\' if you\'re working with git main'''
				return require_version(lowerCamelCase_						,  lowerCamelCase_							)




