# tf.random_uniform

tf.random_uniform(
shape,
minval=0,
maxval=None,
dtype=tf.float32,
seed=None,
name=None
)


See the guide: Constants, Sequences, and Random Values > Random Tensors

Outputs random values from a uniform distribution.

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.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.