Construct an identity matrix, or a batch of matrices.

# Aliases:

• tf.compat.v1.eye
• tf.compat.v1.linalg.eye
• tf.compat.v2.eye
• tf.compat.v2.linalg.eye
• tf.linalg.eye

 tf.eye(
    num_rows,
    num_columns=None,
    batch_shape=None,
    dtype=tf.dtypes.float32,
    name=None
)

 # 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]