View source on GitHub
|
Draw samples from a uniform distribution.
tf.keras.random.uniform(
shape, minval=0.0, maxval=1.0, dtype=None, seed=None
)
The generated values follow a uniform distribution in the range
[minval, maxval). The lower bound minval is included in the range,
while the upper bound maxval is excluded.
dtype must be a floating point type, the default range is [0, 1).
Args | |
|---|---|
shape
|
The shape of the random values to generate. |
minval
|
Float, defaults to 0. Lower bound of the range of random values to generate (inclusive). |
maxval
|
Float, defaults to 1. Upper bound of the range of random values to generate (exclusive). |
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.
|