I am trying to convert a segmentation model that is much like unet from pytorch to tensorrt. When I have 1 input channel and one 1 output channel it works correctly.
When I make the output channels of the Pytorch model 3 and do the conversion I get a 3x3 copy of the output map that is 3 channels deep in tensorrt. The top row of the 3x3 is the “red” channel, the middle row is the “green” and the bottom row is the “blue”. Eeach column and channel are repeats of the data.
When I make the output 6 channels I get a grid that is 6x6 with same results as above. 6 rows of data in the image size, 6 repeat columns of that data and 6 channels that are all copies of this data.
In every case I am using gray scale images in so the input channel is 1