The and operator computes the logical AND (conjunction) of elements across a Tensor.

The or(t) command computes the coande of elements across a Tensor.

The xor(t) command computes the xorgent of elements across a Tensor.

The implies(t) command computes the orecant of elements across a Tensor.

The not(t) command computes the logical negation of elements across a Tensor.

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

$\mathrm{sess}≔\mathrm{Session}\left(\right)$

$\mathrm{sess}≔\left[\begin{array}{c}\mathrm{DeepLearning\; Session}\\ \mathrm{<tensorflow.python.client.session.Session\; object\; at\; 0x7fe6f868a890>}\end{array}\right]$

$\mathrm{t1}≔\mathrm{Tensor}\left(\left[\mathrm{true}\&comma;\mathrm{false}\&comma;\mathrm{true}\right]\right)$

$\mathrm{t1}≔\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [3]}\\ \mathrm{Data\; Type:\; truefalse}\end{array}\right]$

$\mathrm{t2}≔\mathrm{Tensor}\left(\left[\mathrm{false}\&comma;\mathrm{true}\&comma;\mathrm{true}\right]\right)$

$\mathrm{t2}≔\left[\begin{array}{c}\mathrm{DeepLearning\; Tensor}\\ \mathrm{Shape:\; [3]}\\ \mathrm{Data\; Type:\; truefalse}\end{array}\right]$

$\mathrm{t1}\mathbf{and}\mathrm{t2}$

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

$\mathrm{t1}\mathbf{or}\mathbf{not}\mathrm{t2}$

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

The DeepLearning,Tensor,and, DeepLearning,Tensor,or, DeepLearning,Tensor,xor, DeepLearning,Tensor,implies and DeepLearning,Tensor,not commands were introduced in Maple 2018.

For more information on Maple 2018 changes, see Updates in Maple 2018.