Hi @tom,
Can I ask you that the nn.CTCLoss grad_outputs are connected to the gradients caculation? According to here 26, @SeanNaren also experienced a longer convergence. Still, I’m comparing the training process of my code with nn.CTCLoss and warpctc.CTCLoss but pretty sure that the training with nn.CTCLoss is converging slowly than the other. Of course I filtered out the singular data that their input lengths < 2 * target lengths. If this is the origin of difference and the implementation of nn.CTCLoss is correct, then I need to know how I can make the convergence as fast as the warpctc even if I use the official nn.CTCLoss.
Thank you!