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|
Initializer capable of adapting its scale to the shape of weights tensors.
Inherits From: Initializer
tf.keras.initializers.VarianceScaling(
scale=1.0, mode='fan_in', distribution='truncated_normal',
seed=None
)
Used in the notebooks
| Used in the tutorials |
|---|
Also available via the shortcut function
tf.keras.initializers.variance_scaling.
With distribution="truncated_normal" or "untruncated_normal", samples are
drawn from a truncated/untruncated normal distribution with a mean of zero and
a standard deviation (after truncation, if used) stddev = sqrt(scale / n),
where n is:
- number of input units in the weight tensor, if
mode="fan_in" - number of output units, if
mode="fan_out" - average of the numbers of input and output units, if
mode="fan_avg"
With distribution="uniform", samples are drawn from a uniform distribution
within [-limit, limit], where limit = sqrt(3 * scale / n).
Examples:
# Standalone usage:initializer = tf.keras.initializers.VarianceScaling(scale=0.1, mode='fan_in', distribution='uniform')values = initializer(shape=(2, 2))
# Usage in a Keras layer:initializer = tf.keras.initializers.VarianceScaling(scale=0.1, mode='fan_in', distribution='uniform')layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)
Args | |
|---|---|
scale
|
Scaling factor (positive float). |
mode
|
One of "fan_in", "fan_out", "fan_avg". |
distribution
|
Random distribution to use. One of "truncated_normal", "untruncated_normal" and "uniform". |
seed
|
A Python integer. An initializer created with a given seed will always produce the same random tensor for a given shape and dtype. |
Methods
from_config
@classmethodfrom_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.
It will typically be the output of get_config.
|
| Returns | |
|---|---|
| An Initializer instance. |
get_config
get_config()
Returns the configuration of the initializer as a JSON-serializable dict.
| Returns | |
|---|---|
| A JSON-serializable Python dict. |
__call__
__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. |