tf.eye

Aliases:

• `tf.eye`
• `tf.linalg.eye`
``````tf.eye(
num_rows,
num_columns=None,
batch_shape=None,
dtype=tf.float32,
name=None
)
``````

See the guide: Math > Matrix Math Functions

Construct an identity matrix, or a batch of matrices.

``````# Construct one identity matrix.
tf.eye(2)
==> [[1., 0.],
[0., 1.]]

# Construct a batch of 3 identity matricies, each 2 x 2.
# batch_identity[i, :, :] is a 2 x 2 identity matrix, i = 0, 1, 2.
batch_identity = tf.eye(2, batch_shape=[3])

# Construct one 2 x 3 "identity" matrix
tf.eye(2, num_columns=3)
==> [[ 1.,  0.,  0.],
[ 0.,  1.,  0.]]
``````

Args:

• `num_rows`: Non-negative `int32` scalar `Tensor` giving the number of rows in each batch matrix.
• `num_columns`: Optional non-negative `int32` scalar `Tensor` giving the number of columns in each batch matrix. Defaults to `num_rows`.
• `batch_shape`: A list or tuple of Python integers or a 1-D `int32` `Tensor`. If provided, the returned `Tensor` will have leading batch dimensions of this shape.
• `dtype`: The type of an element in the resulting `Tensor`
• `name`: A name for this `Op`. Defaults to "eye".

Returns:

A `Tensor` of shape `batch_shape + [num_rows, num_columns]`