# tf.reverse_v2

tf.reverse_v2(
tensor,
axis,
name=None
)


Defined in generated file: tensorflow/python/ops/gen_array_ops.py.

See the guide: Tensor Transformations > Slicing and Joining

Reverses specific dimensions of a tensor.

NOTE tf.reverse has now changed behavior in preparation for 1.0. tf.reverse_v2 is currently an alias that will be deprecated before TF 1.0.

Given a tensor, and a int32 tensor axis representing the set of dimensions of tensor to reverse. This operation reverses each dimension i for which there exists j s.t. axis[j] == i.

tensor can have up to 8 dimensions. The number of dimensions specified in axis may be 0 or more entries. If an index is specified more than once, a InvalidArgument error is raised.

For example:

# tensor 't' is [[[[ 0,  1,  2,  3],
#                  [ 4,  5,  6,  7],
#                  [ 8,  9, 10, 11]],
#                 [[12, 13, 14, 15],
#                  [16, 17, 18, 19],
#                  [20, 21, 22, 23]]]]
# tensor 't' shape is [1, 2, 3, 4]

# 'dims' is [3] or 'dims' is [-1]
reverse(t, dims) ==> [[[[ 3,  2,  1,  0],
[ 7,  6,  5,  4],
[ 11, 10, 9, 8]],
[[15, 14, 13, 12],
[19, 18, 17, 16],
[23, 22, 21, 20]]]]

# 'dims' is '[1]' (or 'dims' is '[-3]')
reverse(t, dims) ==> [[[[12, 13, 14, 15],
[16, 17, 18, 19],
[20, 21, 22, 23]
[[ 0,  1,  2,  3],
[ 4,  5,  6,  7],
[ 8,  9, 10, 11]]]]

# 'dims' is '[2]' (or 'dims' is '[-2]')
reverse(t, dims) ==> [[[[8, 9, 10, 11],
[4, 5, 6, 7],
[0, 1, 2, 3]]
[[20, 21, 22, 23],
[16, 17, 18, 19],
[12, 13, 14, 15]]]]


#### Args:

• tensor: A Tensor. Must be one of the following types: uint8, int8, uint16, int16, int32, int64, bool, bfloat16, half, float32, float64, complex64, complex128, string. Up to 8-D.
• axis: A Tensor. Must be one of the following types: int32, int64. 1-D. The indices of the dimensions to reverse. Must be in the range [-rank(tensor), rank(tensor)).
• name: A name for the operation (optional).

#### Returns:

A Tensor. Has the same type as tensor.