concatenate multiple Tensors
list or Array of Tensor or Variable objects, or list or Array of Layer objects
nonnegint; axis on which to join
zero or more options as specified below
name = string
The value of option name specifies an optional name for this Tensor, to be displayed in output and when visualizing the dataflow graph.
The Concatenate(L,axis,opts) command concatenates the list of Tensor objects L along the dimension specified by the zero-based index axis.
For example, if Tensors T1 and T2 have shape [2,3] and [4,3] respectively, then Concatenate([T1,T2],0) would join T1 and T2 in the first index, producing a Tensor with shape [6,3].
This function is part of the DeepLearning package, so it can be used in the short form Concatenate(..) only after executing the command with(DeepLearning). However, it can always be accessed through the long form of the command by using DeepLearning[Concatenate](..).
t1 ≔ Ones⁡3,2
t1≔DeepLearning TensorShape: [3, 2]Data Type: float
t2 ≔ Zeros⁡3,4
t2≔DeepLearning TensorShape: [3, 4]Data Type: float
t3 ≔ Concatenate⁡t1,t2,1
t3≔DeepLearning TensorShape: [3, 6]Data Type: float
The DeepLearning[Concatenate] command was introduced in Maple 2018.
For more information on Maple 2018 changes, see Updates in Maple 2018.
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