TensorFlow 2 version
|
View source on GitHub
|
Outputs random values from a uniform distribution.
tf.random.uniform(
shape, minval=0, maxval=None, dtype=tf.dtypes.float32, seed=None, name=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.
For floats, the default range is [0, 1). For ints, at least maxval must
be specified explicitly.
In the integer case, the random integers are slightly biased unless
maxval - minval is an exact power of two. The bias is small for values of
maxval - minval significantly smaller than the range of the output (either
2**32 or 2**64).
Args | |
|---|---|
shape
|
A 1-D integer Tensor or Python array. The shape of the output tensor. |
minval
|
A 0-D Tensor or Python value of type dtype. The lower bound on the
range of random values to generate. Defaults to 0.
|
maxval
|
A 0-D Tensor or Python value of type dtype. The upper bound on
the range of random values to generate. Defaults to 1 if dtype is
floating point.
|
dtype
|
The type of the output: float16, float32, float64, int32,
or int64.
|
seed
|
A Python integer. Used to create a random seed for the distribution.
See tf.compat.v1.set_random_seed
for behavior.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
| A tensor of the specified shape filled with random uniform values. |
Raises | |
|---|---|
ValueError
|
If dtype is integral and maxval is not specified.
|
TensorFlow 2 version
View source on GitHub