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# tf.random.uniform

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`).

#### Examples:

````tf.random.uniform(shape=[2])`
`<tf.Tensor: shape=(2,), dtype=float32, numpy=array([..., ...], dtype=float32)>`
`tf.random.uniform(shape=[], minval=-1., maxval=0.)`
`<tf.Tensor: shape=(), dtype=float32, numpy=-...>`
`tf.random.uniform(shape=[], minval=5, maxval=10, dtype=tf.int64)`
`<tf.Tensor: shape=(), dtype=int64, numpy=...>`
```

The `seed` argument produces a deterministic sequence of tensors across multiple calls. To repeat that sequence, use `tf.random.set_seed`:

````tf.random.set_seed(5)`
`tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)`
`<tf.Tensor: shape=(), dtype=int32, numpy=2>`
`tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)`
`<tf.Tensor: shape=(), dtype=int32, numpy=0>`
`tf.random.set_seed(5)`
`tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)`
`<tf.Tensor: shape=(), dtype=int32, numpy=2>`
`tf.random.uniform(shape=[], maxval=3, dtype=tf.int32, seed=10)`
`<tf.Tensor: shape=(), dtype=int32, numpy=0>`
```

Without `tf.random.set_seed` but with a `seed` argument is specified, small changes to function graphs or previously executed operations will change the returned value. See `tf.random.set_seed` for details.

`shape` A 1-D integer Tensor or Python array. The shape of the output tensor.
`minval` A Tensor or Python value of type `dtype`, broadcastable with `maxval`. The lower bound on the range of random values to generate (inclusive). Defaults to 0.
`maxval` A Tensor or Python value of type `dtype`, broadcastable with `minval`. The upper bound on the range of random values to generate (exclusive). 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 in combination with `tf.random.set_seed` to create a reproducible sequence of tensors across multiple calls.
`name` A name for the operation (optional).

A tensor of the specified shape filled with random uniform values.

`ValueError` If `dtype` is integral and `maxval` is not specified.

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