Construct an identity matrix, or a batch of matrices.
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]
 |