tf.keras.initializers.GlorotUniform  The Glorot uniform initializer, also called Xavier uniform initializer. Inherits From: VarianceScaling, Initializer  View aliases  Main aliases 
tf.keras.initializers.glorot_uniform  
tf.keras.initializers.GlorotUniform(
    seed=None
)
 Also available via the shortcut function tf.keras.initializers.glorot_uniform. Draws samples from a uniform distribution within [-limit, limit], where limit = sqrt(6 / (fan_in + fan_out)) (fan_in is the number of input units in the weight tensor and fan_out is the number of output units). Examples: 
# Standalone usage:
initializer = tf.keras.initializers.GlorotUniform()
values = initializer(shape=(2, 2))
 
# Usage in a Keras layer:
initializer = tf.keras.initializers.GlorotUniform()
layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)

 


 Args
  seed   A Python integer. Used to make the behavior of the initializer deterministic. Note that a seeded initializer will not produce the same random values across multiple calls, but multiple initializers will produce the same sequence when constructed with the same seed value.    References:  Glorot et al., 2010  Methods from_config View source 
@classmethod
from_config(
    config
)
 Instantiates an initializer from a configuration dictionary. Example: initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)

 


 Args
  config   A Python dictionary, the output of get_config.   
 


 Returns   A tf.keras.initializers.Initializer instance.  
 get_config View source 
get_config()
 Returns the configuration of the initializer as a JSON-serializable dict.
 


 Returns   A JSON-serializable Python dict.  
 __call__ View source 
__call__(
    shape, dtype=None, **kwargs
)
 Returns a tensor object initialized as specified by the initializer.
 


 Args
  shape   Shape of the tensor.  
  dtype   Optional dtype of the tensor. Only floating point types are supported. If not specified, tf.keras.backend.floatx() is used, which default to float32 unless you configured it otherwise (via tf.keras.backend.set_floatx(float_dtype))  
  **kwargs   Additional keyword arguments.     

    
{'path': 'public/docs/tensorflow~2.9/keras/initializers/glorotuniform.html', 'source': 'DevDocs.IO'}