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TensorFlow 1 version
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View source on GitHub
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Stacks a list of rank-R tensors into one rank-(R+1) tensor.
tf.stack(
values, axis=0, name='stack'
)
Used in the notebooks
| Used in the guide | Used in the tutorials |
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See also tf.concat, tf.tile, tf.repeat.
Packs the list of tensors in values into a tensor with rank one higher than
each tensor in values, by packing them along the axis dimension.
Given a list of length N of tensors of shape (A, B, C);
if axis == 0 then the output tensor will have the shape (N, A, B, C).
if axis == 1 then the output tensor will have the shape (A, N, B, C).
Etc.
For example:
x = tf.constant([1, 4])y = tf.constant([2, 5])z = tf.constant([3, 6])tf.stack([x, y, z])<tf.Tensor: shape=(3, 2), dtype=int32, numpy=array([[1, 4],[2, 5],[3, 6]], dtype=int32)>tf.stack([x, y, z], axis=1)<tf.Tensor: shape=(2, 3), dtype=int32, numpy=array([[1, 2, 3],[4, 5, 6]], dtype=int32)>
This is the opposite of unstack. The numpy equivalent is np.stack
np.array_equal(np.stack([x, y, z]), tf.stack([x, y, z]))True
Args | |
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values
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A list of Tensor objects with the same shape and type.
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axis
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An int. The axis to stack along. Defaults to the first dimension.
Negative values wrap around, so the valid range is [-(R+1), R+1).
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name
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A name for this operation (optional). |
Returns | |
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output
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A stacked Tensor with the same type as values.
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Raises | |
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ValueError
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If axis is out of the range [-(R+1), R+1).
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