Hi, I have looked into PyTorch TensorRT document, I have a question in the below line the inputs
variable takes min_shape, opt_shape, max_shape
does it means that I can leverage this for my use-case where my model takes dynamic input tensors.
import torch_tensorrt
model = MyModel().eval() # torch module needs to be in eval (not training) mode
inputs = [torch_tensorrt.Input(
min_shape=[1, 1, 16, 16],
opt_shape=[1, 1, 32, 32],
max_shape=[1, 1, 64, 64],
dtype=torch.half,
)]
I have built the model which takes dynamic inputs like the below example,
1. example1 = torch.rand(1, 3, 224, 224)
2. example2 = torch.rand(1, 3, 224, 550)
3. example3 = torch.rand(1, 3, 640, 480)
so, can I consider example1 as min_shape
and example2 as max_shape
?
like
inputs = [torch_tensorrt.Input(
min_shape=[1, 3, 224, 224],
max_shape=[1, 3, 640, 480],
dtype=torch.half,
)]
could you please clarify this? @ptrblck