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|
Initializer capable of adapting its scale to the shape of weights tensors.
Inherits From: VarianceScaling
tf.compat.v1.keras.initializers.he_normal(
seed=None
)
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], with limit = sqrt(3 * scale / n).
Args | |
|---|---|
scale
|
Scaling factor (positive float). |
mode
|
One of "fan_in", "fan_out", "fan_avg". |
distribution
|
Random distribution to use. One of "normal", "uniform". |
seed
|
A Python integer. Used to create random seeds. See
tf.compat.v1.set_random_seed for behavior.
|
dtype
|
Default data type, used if no dtype argument is provided when
calling the initializer. Only floating point types are supported.
|
Raises | |
|---|---|
ValueError
|
In case of an invalid value for the "scale", mode" or "distribution" arguments. |
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, partition_info=None
)
Returns a tensor object initialized as specified by the initializer.
| Args | |
|---|---|
shape
|
Shape of the tensor. |
dtype
|
Optional dtype of the tensor. If not provided use the initializer dtype. |
partition_info
|
Optional information about the possible partitioning of a tensor. |