I am using TensorRT 3.0.1 and TensorFlow 1.3.
I am using transposed convolution in my model and I do element-wise sum on the output of the transposed convolution and the output of a convolution (from a previous layer). It worked fine during training.
When I try to optimize with TensorRT, it gives me shape mismatch error on element-wise operation. I set the padding parameter as ‘same’ in all conv and trans conv layers. Here is the error,
Using output node dev_0/cnn/decoder/conv2d_transpose_2/conv2d_transpose
Converting to UFF graph
No. nodes: 142
[TensorRT] ERROR: dev_0/cnn/decoder/add: all elementwise inputs must have same dimensions or follow the broadcasting rules
[TensorRT] ERROR: Failed to create engine
Is TensorRT doing additional paddings while conversion to UFF graph? Please help me to resolve this.