tf.unstack | TensorFlow v2.0.0 (original) (raw)
tf.unstack
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Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.
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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 slicevalue[i, :, :, :] and each tensor in output will have shape (B, C, D). (Note that the dimension unpacked along is gone, unlike split).
If axis == 1 then the i'th tensor in output is the slicevalue[:, 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 ifNone (the default). |
| axis | An int. The axis to unstack along. Defaults to the first dimension. Negative values wrap around, so the valid range is [-R, R). |
| name | A name for the operation (optional). |
| 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). |