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)`

.

## Arguments

- 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,

`config_floatx()`

is used, which defaults to`float32`

unless you configured it otherwise (via`config_set_floatx(float_dtype)`

)- seed
An R integer or instance of

`random_seed_generator()`

. Used to make the behavior of the initializer deterministic. Note that an initializer seeded with an integer or`NULL`

(unseeded) will produce the same random values across multiple calls. To get different random values across multiple calls, use as seed an instance of`random_seed_generator()`

.

## See also

Other random: `random_beta()`

`random_binomial()`

`random_categorical()`

`random_dropout()`

`random_gamma()`

`random_integer()`

`random_normal()`

`random_seed_generator()`

`random_shuffle()`

`random_truncated_normal()`