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Can a 1×n convolution kernel be applied to a row vector #146

@achinastone

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@achinastone

The convolutional layer seems to use square matrices, providing services for image recognition.
Can convolutional layers have different FFeatureSizeX and FFeatureSizeY to enable convolution operations to be applied in non-image recognition fields?
constructor TNNetConvolutionAbstract.Create(pFeatureSize, pInputPadding, pStride: integer; pSuppressBias: integer = 0); begin inherited Create(); FFeatureSizeX := pFeatureSize; FFeatureSizeY := pFeatureSize; FPadding := pInputPadding; FStride := Max(pStride,1); FSuppressBias := pSuppressBias; if FPadding > 0 then begin FInputCopy := TNNetVolume.Create; end; FPrevLayerErrorPadded := TNNetVolume.Create; end;

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