

'''simple docstring'''
import unittest

import numpy as np

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
     import tensorflow as tf

     from transformers.activations_tf import get_tf_activation







@require_tf
class 							A__					( unittest.TestCase						):





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





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE												=tf.constant([-100, -1.0, -0.1, 0, 0.1, 1.0, 100.0]				)
       _SCREAMING_SNAKE_CASE												=get_tf_activation('gelu'				)
       _SCREAMING_SNAKE_CASE												=get_tf_activation('gelu_10'				)

       _SCREAMING_SNAKE_CASE												=gelu(_a				)
       _SCREAMING_SNAKE_CASE												=geluaa(_a				)

       _SCREAMING_SNAKE_CASE												=tf.where(y_gelu_aa < 10.0							,      1.0							,      0.0				)

       self.assertEqual(tf.math.reduce_max(_a				).numpy().item()							,      10.0				)
       self.assertTrue(np.allclose(y_gelu * clipped_mask							,      y_gelu_aa * clipped_mask				)				)





  def 		A						(	self   :			Any				)			->					int:





       '''simple docstring'''






       get_tf_activation('gelu'				)
       get_tf_activation('gelu_10'				)
       get_tf_activation('gelu_fast'				)
       get_tf_activation('gelu_new'				)
       get_tf_activation('glu'				)
       get_tf_activation('mish'				)
       get_tf_activation('quick_gelu'				)
       get_tf_activation('relu'				)
       get_tf_activation('sigmoid'				)
       get_tf_activation('silu'				)
       get_tf_activation('swish'				)
       get_tf_activation('tanh'				)
       with self.assertRaises(_a				):
            get_tf_activation('bogus'				)
       with self.assertRaises(_a				):
            get_tf_activation(_a				)



'''simple docstring'''
from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


lowerCamelCase				:   Dict      				=  datasets.utils.logging.get_logger(__name__)







class 							A__					( folder_based_builder.FolderBasedBuilderConfig						):
  A__					=       None
  A__					=       None







class 							A__					( folder_based_builder.FolderBasedBuilder						):
  A__					=       datasets.Image()
  A__					=       'image'
  A__					=       ImageFolderConfig
  A__					=       42  # definition at the bottom of the script
  A__					=       ImageClassification(image_column='image'  ,     label_column='label'						)

lowerCamelCase				:   Optional[int]      				=  [
    ".blp",
    ".bmp",
    ".dib",
    ".bufr",
    ".cur",
    ".pcx",
    ".dcx",
    ".dds",
    ".ps",
    ".eps",
    ".fit",
    ".fits",
    ".fli",
    ".flc",
    ".ftc",
    ".ftu",
    ".gbr",
    ".gif",
    ".grib",
    ".h5",
    ".hdf",
    ".png",
    ".apng",
    ".jp2",
    ".j2k",
    ".jpc",
    ".jpf",
    ".jpx",
    ".j2c",
    ".icns",
    ".ico",
    ".im",
    ".iim",
    ".tif",
    ".tiff",
    ".jfif",
    ".jpe",
    ".jpg",
    ".jpeg",
    ".mpg",
    ".mpeg",
    ".msp",
    ".pcd",
    ".pxr",
    ".pbm",
    ".pgm",
    ".ppm",
    ".pnm",
    ".psd",
    ".bw",
    ".rgb",
    ".rgba",
    ".sgi",
    ".ras",
    ".tga",
    ".icb",
    ".vda",
    ".vst",
    ".webp",
    ".wmf",
    ".emf",
    ".xbm",
    ".xpm",
]
lowerCamelCase				:   Any      				=  IMAGE_EXTENSIONS
