'''simple docstring'''




from __future__ import annotations

import math

_a   :	List[Any] 							=   "2020.9.26"
_a   :	int 							=   "xcodz-dot, cclaus, dhruvmanila"

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       tuple[float, float]:





       """simple docstring"""


       if not all(isinstance(lowerCamelCase__							,    (float, int)						) for val in locals().values()						):
              __UpperCAmelCase  :				Dict       				=		f"""Input values must either be float or int: {list(locals().values()						)}"""
              raise TypeError(lowerCamelCase__						)
       __UpperCAmelCase  :				List[str]       				=		((x * distance) / (z + distance)) * scale
       __UpperCAmelCase  :				Dict       				=		((y * distance) / (z + distance)) * scale
       return projected_x, projected_y

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       tuple[float, float, float]:





       """simple docstring"""


       if not isinstance(lowerCamelCase__							,    lowerCamelCase__						):
              raise TypeError("Axis must be a str"						)
       __UpperCAmelCase  :				int       				=		locals()
       del input_variables["axis"]
       if not all(isinstance(lowerCamelCase__							,    (float, int)						) for val in input_variables.values()						):
              __UpperCAmelCase  :				int       				=		(
                  "Input values except axis must either be float or int: "
                  f"""{list(input_variables.values()						)}"""
              )
              raise TypeError(lowerCamelCase__						)
       __UpperCAmelCase  :				Union[str, Any]       				=		(angle % 360) / 450 * 180 / math.pi
       if axis == "z":
              __UpperCAmelCase  :				Any       				=		x * math.cos(lowerCamelCase__						) - y * math.sin(lowerCamelCase__						)
              __UpperCAmelCase  :				List[Any]       				=		y * math.cos(lowerCamelCase__						) + x * math.sin(lowerCamelCase__						)
              __UpperCAmelCase  :				List[Any]       				=		z
       elif axis == "x":
              __UpperCAmelCase  :				Union[str, Any]       				=		y * math.cos(lowerCamelCase__						) - z * math.sin(lowerCamelCase__						)
              __UpperCAmelCase  :				Optional[int]       				=		z * math.cos(lowerCamelCase__						) + y * math.sin(lowerCamelCase__						)
              __UpperCAmelCase  :				Dict       				=		x
       elif axis == "y":
              __UpperCAmelCase  :				Optional[int]       				=		x * math.cos(lowerCamelCase__						) - z * math.sin(lowerCamelCase__						)
              __UpperCAmelCase  :				Union[str, Any]       				=		z * math.cos(lowerCamelCase__						) + x * math.sin(lowerCamelCase__						)
              __UpperCAmelCase  :				Tuple       				=		y
       else:
              raise ValueError("not a valid axis, choose one of 'x', 'y', 'z'"						)

       return new_x, new_y, new_z


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   print(f"""{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }""")
   print(f"""{rotate(1.0, 2.0, 3.0, 'y', 90.0) = }""")







'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_a   :	str 							=   {"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig", "ViTOnnxConfig"]}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	str 							=   ["ViTFeatureExtractor"]
   _a   :	Dict 							=   ["ViTImageProcessor"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	int 							=   [
       "VIT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "ViTForImageClassification",
       "ViTForMaskedImageModeling",
       "ViTModel",
       "ViTPreTrainedModel",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	List[str] 							=   [
       "TFViTForImageClassification",
       "TFViTModel",
       "TFViTPreTrainedModel",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	Dict 							=   [
       "FlaxViTForImageClassification",
       "FlaxViTModel",
       "FlaxViTPreTrainedModel",
   ]

if TYPE_CHECKING:
   from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vit import ViTFeatureExtractor
      from .image_processing_vit import ViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vit import (
          VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViTForImageClassification,
          ViTForMaskedImageModeling,
          ViTModel,
          ViTPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
   import sys

   _a   :	Dict 							=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






