Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.

# Aliases:

• tf.compat.v1.unstack
• tf.compat.v2.unstack

 tf.unstack(
    value,
    num=None,
    axis=0,
    name='unstack'
)

Unpacks num tensors from value by chipping it along the axis dimension. If num is not specified (the default), it is inferred from value's shape. If value.shape[axis] is not known, ValueError is raised. For example, given a tensor of shape (A, B, C, D); If axis == 0 then the i'th tensor in output is the slice value[i, :, :, :] and each tensor in output will have shape (B, C, DB, C, D). (Note that the dimension unpacked along is gone, unlike ``). If axis == 1 then the i'th tensor in output is the slice value[:, i, :, :] and each tensor in output will have shape (A, C, D). Etc. This is the opposite of stack.

# Args:

• value: A rank R > 0 Tensor to be unstacked.
• num: An int. The length of the dimension axis. Automatically inferred if None (the default).

# Returns:

The list of Tensor objects unstacked from value.

# Raises:

• ValueError: If num is unspecified and cannot be inferred.
• ValueError: If axis is out of the range [-R, R).