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Draw samples from a truncated normal distribution.
tf.keras.random.truncated_normal(
shape, mean=0.0, stddev=1.0, dtype=None, seed=None
)
The values are drawn from a normal distribution with specified mean and standard deviation, discarding and re-drawing any samples that are more than two standard deviations from the mean.
Args | |
|---|---|
shape
|
The shape of the random values to generate. |
mean
|
Float, defaults to 0. Mean of the random values to generate. |
stddev
|
Float, defaults to 1. Standard deviation of the random values to generate. |
dtype
|
Optional dtype of the tensor. Only floating point types are
supported. If not specified, keras.config.floatx() is used,
which defaults to float32 unless you configured it otherwise (via
keras.config.set_floatx(float_dtype))
|
seed
|
A Python integer or instance of
keras.random.SeedGenerator.
Used to make the behavior of the initializer
deterministic. Note that an initializer seeded with an integer
or None (unseeded) will produce the same random values
across multiple calls. To get different random values
across multiple calls, use as seed an instance
of keras.random.SeedGenerator.
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