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TensorFlow 1 version
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View source on GitHub
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Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.
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, D).
(Note that the dimension unpacked along is gone, unlike split).
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 | |
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value
|
A rank R > 0 Tensor to be unstacked.
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num
|
An int. The length of the dimension axis. Automatically inferred if
None (the default).
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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 | |
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The list of Tensor objects unstacked from value.
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Raises | |
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ValueError
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If num is unspecified and cannot be inferred.
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ValueError
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If axis is out of the range [-R, R).
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