# tf.gather

Gather slices from params axis axis according to indices.

### Aliases:

tf.gather(
params,
indices,
validate_indices=None,
name=None,
axis=None,
batch_dims=0
)

Gather slices from params axis axis according to indices. indices must be an integer tensor of any dimension (usually 0-D or 1-D).

For 0-D (scalar) indices:

output

$$[p_0, ..., p_{axis-1}, \hspace{5.1em} p_{axis + 1}, ..., p_{N-1}]$$
=
params
$$[p_0, ..., p_{axis-1}, \hspace{1em} indices, \hspace{1em} p_{axis + 1}, ..., p_{N-1}]$$
.

For 1-D (vector) indices with batch_dims=0:

output

$$[p_0, ..., p_{axis-1}, \hspace{2.6em} i, \hspace{2.6em} p_{axis + 1}, ..., p_{N-1}]$$
=
params
$$[p_0, ..., p_{axis-1}, \hspace{1em} indices[i], \hspace{1em} p_{axis + 1}, ..., p_{N-1}]$$
.

In the general case, produces an output tensor where:

\begin{align*} output[p_0, &..., p_{axis-1}, & &i_{B}, ..., i_{M-1}, & p_{axis + 1}, &..., p_{N-1}] = \\ params[p_0, &..., p_{axis-1}, & indices[p_0, ..., p_{B-1}, &i_{B}, ..., i_{M-1}], & p_{axis + 1}, &..., p_{N-1}] \end{align*}

Where

$$N$$
=ndims(params),
$$M$$
=ndims(indices), and
$$B$$
=batch_dims. Note that params.shape[:batch_dims] must be identical to indices.shape[:batch_dims].

The shape of the output tensor is:

output.shape = params.shape[:axis] + indices.shape[batch_dims:] + params.shape[axis + 1:].

Note that on CPU, if an out of bound index is found, an error is returned. On GPU, if an out of bound index is found, a 0 is stored in the corresponding output value.