Inconsistent inference results between PyTorch and converted TensorRT model with ConvTranspose2d operator

[hongliyu0716]

Description:

I'm experiencing a discrepancy between the inference results of PyTorch model and the TensorRT model obtained by converting it using the torch2trt tool.

Reproduce

This issue can be reproduced by the following script:

import torch
from torch.nn import Module
from torch2trt import torch2trt


model = torch.nn.ConvTranspose2d(3,4,3,3,0,2,).eval()
input_data = torch.randn([2, 3, 6, 6], dtype=torch.float32).cuda()
model_trt = torch2trt(model, [input_data])
output = model(input_data)
output_trt = model_trt(input_data)
print(torch.max(torch.abs(output - output_trt)))

Environment

• torch: 2.1.1
• torch2trt: 0.4.0
• tensorrt: 8.6.1