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# tf.random_uniform_initializer

Initializer that generates tensors with a uniform distribution.

### Used in the notebooks

Used in the tutorials

Initializers allow you to pre-specify an initialization strategy, encoded in the Initializer object, without knowing the shape and dtype of the variable being initialized.

#### Examples:

````def make_variables(k, initializer):`
`  return (tf.Variable(initializer(shape=[k], dtype=tf.float32)),`
`          tf.Variable(initializer(shape=[k, k], dtype=tf.float32)))`
`v1, v2 = make_variables(3, tf.ones_initializer())`
`v1`
`<tf.Variable ... shape=(3,) ... numpy=array([1., 1., 1.], dtype=float32)>`
`v2`
`<tf.Variable ... shape=(3, 3) ... numpy=`
`array([[1., 1., 1.],`
`       [1., 1., 1.],`
`       [1., 1., 1.]], dtype=float32)>`
`make_variables(4, tf.random_uniform_initializer(minval=-1., maxval=1.))`
`(<tf.Variable...shape=(4,) dtype=float32...>, <tf.Variable...shape=(4, 4) ...`
```

`minval` A python scalar or a scalar tensor. Lower bound of the range of random values to generate (inclusive).
`maxval` A python scalar or a scalar tensor. Upper bound of the range of random values to generate (exclusive).
`seed` A Python integer. Used to create random seeds. See `tf.random.set_seed` for behavior.

## Methods

### `from_config`

View source

Instantiates an initializer from a configuration dictionary.

#### Example:

``````initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)
``````

Args
`config` A Python dictionary. It will typically be the output of `get_config`.

Returns
An Initializer instance.

### `get_config`

View source

Returns the configuration of the initializer as a JSON-serializable dict.

Returns
A JSON-serializable Python dict.

### `__call__`

View source

Returns a tensor object initialized as specified by the initializer.

Args
`shape` Shape of the tensor.
`dtype` Optional dtype of the tensor. Only floating point and integer types are supported.
`**kwargs` Additional keyword arguments.

Raises
`ValueError` If the dtype is not numeric.

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