DeepLearning/Tensor/CrossProduct - Maple Programming Help

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DeepLearning/Tensor/CrossProduct

compute cross product of Tensors

DeepLearning/Tensor/DotProduct

compute dot product of Tensors

 

Calling Sequence

Parameters

Options

Description

Examples

Compatibility

Calling Sequence

CrossProduct(x,y,opts)

DotProduct(x,y,opts)

Parameters

x

-

Tensor

y

-

Tensor

opts

-

zero or more options as specified below

Options

• 

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.

Description

• 

The CrossProduct(x,y,opts) command computes the cross product of two Tensor objects.

• 

The DotProduct(x,y,opts) command computes the dot product of two Tensor objects.

Examples

withDeepLearning:

v1Constant35.0,65.0,41.0

v1DeepLearning TensorName: Const:0Shape: [3]Data Type: float[8]

(1)

v2Constant14.0,45.0,24.0

v2DeepLearning TensorName: Const_1:0Shape: [3]Data Type: float[8]

(2)

valueCrossProductv1,v2

−285.266.−665.

(3)

m1Constant92.1,31.3,67.3

m1DeepLearning TensorName: Const_2:0Shape: [3, 1]Data Type: float[8]

(4)

m2Constant99.7|29.0|44.5

m2DeepLearning TensorName: Const_3:0Shape: [1, 3]Data Type: float[8]

(5)

valueDotProductm1,m2

−9182.37000000000−2670.90000000000−4098.45000000000−3120.61000000000−907.700000000000−1392.850000000006709.810000000001951.700000000002994.85000000000

(6)

Compatibility

• 

The DeepLearning/Tensor/CrossProduct and DeepLearning/Tensor/DotProduct commands were introduced in Maple 2018.

• 

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

See Also

DeepLearning Overview

LinearAlgebra

Tensor