# tf.raw_ops.Fill

<br />

Creates a tensor filled with a scalar value.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.Fill`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Fill)

<br />

    tf.raw_ops.Fill(
        dims, value, name=None
    )

This operation creates a tensor of shape `dims` and fills it with `value`.

#### For example:

    # Output tensor has shape [2, 3].
    fill([2, 3], 9) ==> [[9, 9, 9]
                         [9, 9, 9]]

[`tf.fill`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/fill) differs from [`tf.constant`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/constant) in a few ways:

- [`tf.fill`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/fill) only supports scalar contents, whereas [`tf.constant`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/constant) supports Tensor values.
- [`tf.fill`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/fill) creates an Op in the computation graph that constructs the actual Tensor value at runtime. This is in contrast to [`tf.constant`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/constant) which embeds the entire Tensor into the graph with a `Const` node.
- Because [`tf.fill`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/fill) evaluates at graph runtime, it supports dynamic shapes based on other runtime Tensors, unlike [`tf.constant`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/constant).

<br />

<br />

<br />

| ## Args ||
|---|---|
| `dims` | A `Tensor`. Must be one of the following types: `int32`, `int64`. 1-D. Represents the shape of the output tensor. |
| `value` | A `Tensor`. 0-D (scalar). Value to fill the returned tensor. |
| `name` | A name for the operation (optional). |

<br />

<br />

<br />

<br />

| ## Returns ||
|---|---|
| A `Tensor`. Has the same type as `value`. ||

<br />

<br />

## numpy compatibility

<br />

Equivalent to np.full

<br />

<br />