

"""simple docstring"""


import numpy as np

class      __a							:






     '''simple docstring'''

     def __init__(						self	,    _a=None	,    _a=None	,    _a=None	,    _a=None	,    _a=None  )  ->      Dict:


           """simple docstring"""


           self.set_matricies(red=_a	,    green=_a	,    blue=_a	,    red_edge=_a	,    nir=_a  )

     def 					_a			(						self	,    _a=None	,    _a=None	,    _a=None	,    _a=None	,    _a=None  )  ->      Optional[Any]:


           """simple docstring"""


           if red is not None:
                 SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	red
           if green is not None:
                 SCREAMING_SNAKE_CASE__   :      Tuple      		=	green
           if blue is not None:
                 SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	blue
           if red_edge is not None:
                 SCREAMING_SNAKE_CASE__   :      List[str]      		=	red_edge
           if nir is not None:
                 SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	nir
           return True

     def 					_a			(						self	,    _a=""	,    _a=None	,    _a=None	,    _a=None	,    _a=None	,    _a=None  )  ->      Optional[Any]:


           """simple docstring"""


           self.set_matricies(red=_a	,    green=_a	,    blue=_a	,    red_edge=_a	,    nir=_a  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	{
               """ARVI2""": self.arvaa,
               """CCCI""": self.ccci,
               """CVI""": self.cvi,
               """GLI""": self.gli,
               """NDVI""": self.ndvi,
               """BNDVI""": self.bndvi,
               """redEdgeNDVI""": self.red_edge_ndvi,
               """GNDVI""": self.gndvi,
               """GBNDVI""": self.gbndvi,
               """GRNDVI""": self.grndvi,
               """RBNDVI""": self.rbndvi,
               """PNDVI""": self.pndvi,
               """ATSAVI""": self.atsavi,
               """BWDRVI""": self.bwdrvi,
               """CIgreen""": self.ci_green,
               """CIrededge""": self.ci_rededge,
               """CI""": self.ci,
               """CTVI""": self.ctvi,
               """GDVI""": self.gdvi,
               """EVI""": self.evi,
               """GEMI""": self.gemi,
               """GOSAVI""": self.gosavi,
               """GSAVI""": self.gsavi,
               """Hue""": self.hue,
               """IVI""": self.ivi,
               """IPVI""": self.ipvi,
               """I""": self.i,
               """RVI""": self.rvi,
               """MRVI""": self.mrvi,
               """MSAVI""": self.m_savi,
               """NormG""": self.norm_g,
               """NormNIR""": self.norm_nir,
               """NormR""": self.norm_r,
               """NGRDI""": self.ngrdi,
               """RI""": self.ri,
               """S""": self.s,
               """IF""": self._if,
               """DVI""": self.dvi,
               """TVI""": self.tvi,
               """NDRE""": self.ndre,
           }

           try:
                 return funcs[index]()
           except KeyError:
                 print("""Index not in the list!"""  )
                 return False

     def 					_a			(						self  )  ->      Optional[int]:


           """simple docstring"""


           return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
               (self.nir - self.red) / (self.nir + self.red)
           )

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


           """simple docstring"""


           return self.nir * (self.red / (self.green**2))

     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           return (2 * self.green - self.red - self.blue) / (
               2 * self.green + self.red + self.blue
           )

     def 					_a			(						self  )  ->      List[str]:


           """simple docstring"""


           return (self.nir - self.red) / (self.nir + self.red)

     def 					_a			(						self  )  ->      List[str]:


           """simple docstring"""


           return (self.nir - self.blue) / (self.nir + self.blue)

     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           return (self.redEdge - self.red) / (self.redEdge + self.red)

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return (self.nir - self.green) / (self.nir + self.green)

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


           """simple docstring"""


           return (self.nir - (self.green + self.blue)) / (
               self.nir + (self.green + self.blue)
           )

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return (self.nir - (self.green + self.red)) / (
               self.nir + (self.green + self.red)
           )

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return (self.nir - (self.green + self.red + self.blue)) / (
               self.nir + (self.green + self.red + self.blue)
           )

     def 					_a			(						self	,    _a=0.08	,    _a=1.22	,    _a=0.03  )  ->      List[str]:


           """simple docstring"""


           return a * (
               (self.nir - a * self.red - b)
               / (a * self.nir + self.red - a * b + x * (1 + a**2))
           )

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)

     def 					_a			(						self  )  ->      List[str]:


           """simple docstring"""


           return (self.nir / self.green) - 1

     def 					_a			(						self  )  ->      Tuple:


           """simple docstring"""


           return (self.nir / self.redEdge) - 1

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return (self.red - self.blue) / self.red

     def 					_a			(						self  )  ->      str:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      List[str]      		=	self.ndvi()
           return ((ndvi + 0.5) / (abs(ndvi + 0.5  ))) * (abs(ndvi + 0.5  ) ** (1 / 2))

     def 					_a			(						self  )  ->      Tuple:


           """simple docstring"""


           return self.nir - self.green

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return 2.5 * (
               (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
           )

     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	(2 * (self.nir**2 - self.red**2) + 1.5 * self.nir + 0.5 * self.red) / (
               self.nir + self.red + 0.5
           )
           return n * (1 - 0.25 * n) - (self.red - 0.125) / (1 - self.red)

     def 					_a			(						self	,    _a=0.16  )  ->      str:


           """simple docstring"""


           return (self.nir - self.green) / (self.nir + self.green + y)

     def 					_a			(						self	,    _a=0.5  )  ->      Optional[Any]:


           """simple docstring"""


           return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return np.arctan(
               ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)  )

     def 					_a			(						self	,    _a=None	,    _a=None  )  ->      Optional[int]:


           """simple docstring"""


           return (self.nir - b) / (a * self.red)

     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)

     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


           return (self.red + self.green + self.blue) / 30.5

     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           return self.nir / self.red

     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           return (self.rvi() - 1) / (self.rvi() + 1)

     def 					_a			(						self  )  ->      Optional[int]:


           """simple docstring"""


           return (
               (2 * self.nir + 1)
               - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
           ) / 2

     def 					_a			(						self  )  ->      List[str]:


           """simple docstring"""


           return self.green / (self.nir + self.red + self.green)

     def 					_a			(						self  )  ->      Tuple:


           """simple docstring"""


           return self.nir / (self.nir + self.red + self.green)

     def 					_a			(						self  )  ->      Optional[int]:


           """simple docstring"""


           return self.red / (self.nir + self.red + self.green)

     def 					_a			(						self  )  ->      str:


           """simple docstring"""


           return (self.green - self.red) / (self.green + self.red)

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return (self.red - self.green) / (self.red + self.green)

     def 					_a			(						self  )  ->      Any:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	np.max([np.max(self.red  ), np.max(self.green  ), np.max(self.blue  )]  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	np.min([np.min(self.red  ), np.min(self.green  ), np.min(self.blue  )]  )
           return (max_value - min_value) / max_value

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return (2 * self.red - self.green - self.blue) / (self.green - self.blue)

     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           return self.nir / self.red

     def 					_a			(						self  )  ->      Optional[int]:


           """simple docstring"""


           return (self.ndvi() + 0.5) ** (1 / 2)





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


           """simple docstring"""


           return (self.nir - self.redEdge) / (self.nir + self.redEdge)







"""simple docstring"""


from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
  import numpy as np
  import tensorflow as tf

  from transformers import TFCamembertModel

@require_tf
@require_sentencepiece
@require_tokenizers
class      __a							(unittest.TestCase):






     '''simple docstring'''

     @slow
     def 					_a			(						self  )  ->      Union[str, Any]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	TFCamembertModel.from_pretrained("""jplu/tf-camembert-base"""  )

           SCREAMING_SNAKE_CASE__   :      Any      		=	tf.convert_to_tensor(
               [[5, 121, 11, 660, 16, 730, 25_543, 110, 83, 6]]	,    dtype=tf.intaa	,    )  # J'aime le camembert !"

           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	model(_a  )["""last_hidden_state"""]
           SCREAMING_SNAKE_CASE__   :      List[str]      		=	tf.TensorShape((1, 10, 768)  )
           self.assertEqual(output.shape	,    _a  )
           # compare the actual values for a slice.
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	tf.convert_to_tensor(
               [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]	,    dtype=tf.floataa	,    )
           # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
           # camembert.eval()
           # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

           self.assertTrue(np.allclose(output[:, :3, :3].numpy()	,    expected_slice.numpy()	,    atol=1E-4  )  )




