Hi again,
I am really sorry to bother you again, but I think I am failing to do something that must be relatively simple. Along the lines of the cudnn_convolution.cpp file of this repo ( PyTorch-cuDNN-Convolution/cudnn_convolution.cpp at master · ernoult/PyTorch-cuDNN-Convolution (github.com), I would like to create a wrapper around the C++ accelerated functions for convolution_tranpose and convolution_transpose_backward_weight. In cudnn_convolution.cpp, I have therefore added:
at::Tensor convolution_transpose(
    const at::Tensor& input,
    const at::Tensor& weight,
    const at::Tensor& bias,
    c10::ArrayRef<int64_t> stride,
    c10::ArrayRef<int64_t> padding,
    c10::ArrayRef<int64_t> output_padding,
    c10::ArrayRef<int64_t> dilation,
    int64_t groups,
    bool benchmark,
    bool deterministic) {

    return at::cudnn_convolution_transpose(
        input,
        weight,
        bias,
        padding,
        output_padding,
        stride,
        dilation,
        groups,
        benchmark,
        deterministic); 
}


at::Tensor convolution_transpose_backward_weight(
    const at::Tensor& input,
    c10::ArrayRef<int64_t> weight_size,
    const at::Tensor& grad_output,
    c10::ArrayRef<int64_t> stride,
    c10::ArrayRef<int64_t> padding,
    c10::ArrayRef<int64_t> dilation,
    int64_t groups,
    bool benchmark,
    bool deterministic,
    bool allow_tf32) {

    return at::cudnn_convolution_transpose_backward_weight(
        weight_size,
        grad_output,
        input,
        padding,
        stride,
        dilation,
        groups,
        benchmark,
        deterministic,
        allow_tf32);
}

Then, I load this cpp modules from a python script through:
cudnn_convolution = load(name="cudnn_convolution", sources=["cudnn_convolution.cpp"], verbose=True)

Finally, I try to use transpose convolution with the following script:
weight = torch.zeros(64, 3, 5, 5).to('cuda')
bias   = torch.zeros(64).to('cuda')

stride   = (2, 2)
padding  = (0, 0)
output_padding  = (0, 0)
dilation = (1, 1)
groups   = 1
dummy_input = torch.zeros(128, 64, 14, 14).to('cuda')
output = cudnn_convolution.convolution_transpose(dummy_input, weight, bias, stride, padding, output_padding, dilation, groups, False, False)

but it throws the following error message:
AttributeError: module 'cudnn_convolution' has no attribute 'convolution_transpose'

Do you have any idea of what happens? I am a bit desperate