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The Unstack(x,axis,opts) unpacks Tensors from x by splitting across the dimension specified by axis. The result is a list of Tensors corresponding to the slices of the original Tensor from the specified dimension.

$\mathrm{with}\left(\mathrm{DeepLearning}\right)\:$

$v≔\mathrm{Constant}\left(⟨-35.0\,65.0\,41.0\,67.2⟩\right)$

$v≔\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [4]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]$

$\mathrm{Unstack}\left(v\,1\right)$

$\left[\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; []}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\,\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; []}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\,\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; []}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\,\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; []}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\right]$

$m≔\mathrm{Constant}\left(⟨⟨-92.1\,-31.3\,67.3⟩\|⟨56.2\,65.3\,98.7⟩⟩\right)$

$m≔\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [3,\; 2]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]$

$\mathrm{Unstack}\left(m\,1\right)$

$\left[\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [2]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\,\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [2]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\,\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [2]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\right]$

$\mathrm{Unstack}\left(m\,2\right)$

$\left[\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [3]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\,\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [3]}\\ \mathrm{Data\; Type:\; float[8]}\end{array}\right]\right]$

The DeepLearning/Tensor/Unstack command was introduced in Maple 2019.

For more information on Maple 2019 changes, see Updates in Maple 2019.