code: 
  
  
  '''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 						__lowerCAmelCase		(unittest.TestCase  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				tf.constant([-100, -1.0, -0.1, 0, 0.1, 1.0, 1_00.0]				)
               lowercase__       =				get_tf_activation('''gelu'''				)
               lowercase__       =				get_tf_activation('''gelu_10'''				)
  
               lowercase__       =				gelu(UpperCamelCase				)
               lowercase__       =				geluaa(UpperCamelCase				)
  
               lowercase__       =				tf.where(y_gelu_aa < 10.0     ,		1.0     ,		0.0				)
  
               self.assertEqual(tf.math.reduce_max(UpperCamelCase				).numpy().item()     ,		10.0				)
               self.assertTrue(np.allclose(y_gelu * clipped_mask     ,		y_gelu_aa * clipped_mask				)				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''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(UpperCamelCase				):
                      get_tf_activation('''bogus'''				)
               with self.assertRaises(UpperCamelCase				):
                      get_tf_activation(UpperCamelCase				)
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  import torch
  
  from accelerate import Accelerator, DistributedType
  class 						__lowerCAmelCase		:
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def __enter__(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.enabled:
                      lowercase__       =				self.model.no_sync()
                      self.model_sync_obj.__enter__()
  
               return self
  
  
  
        def __exit__(self					:					List[str]     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					Optional[int]     ,		UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.enabled:
                      # Average all models on exit
                      self._sync_and_avg_model_params()
                      self.model_sync_obj.__exit__(UpperCamelCase     ,		UpperCamelCase     ,		UpperCamelCase				)
  
  
  
        def __init__(self					:					Dict     ,		UpperCamelCase					:					Accelerator     ,		UpperCamelCase					:					torch.nn.Module     ,		UpperCamelCase					:					int     ,		UpperCamelCase					:					bool = True				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if accelerator.distributed_type not in [
                   DistributedType.NO,
                   DistributedType.MULTI_CPU,
                   DistributedType.MULTI_GPU,
               ]:
                      raise NotImplementedError('''LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'''				)
               lowercase__       =				enabled and accelerator.distributed_type != DistributedType.NO
               lowercase__       =				0
               if self.enabled:
                      lowercase__       =				accelerator
                      lowercase__       =				model
                      lowercase__       =				local_sgd_steps
  
  
  
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               self.num_steps += 1
               if not self.enabled:
                      return
  
               if self.num_steps % self.local_sgd_steps == 0:
                      self._sync_and_avg_model_params()
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Any				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               self.accelerator.wait_for_everyone()
               with self.accelerator.autocast():
                      for param in self.model.parameters():
                             lowercase__       =				self.accelerator.reduce(param.data     ,		reduction='''mean'''				)
  
  
  
  
  