How to convert the model with no fixed size input to Torch Script?

jit
1

If the size of input image is not fixed, how to convert the model to torch script?

2

You should use the @torch.jit.script annotation, which will recover the full semantics of your model (including any control flow that depends on input size). See the tutorial for more info: https://pytorch.org/tutorials/advanced/cpp_export.html

3

Thanks. But I got an error.

my code is like this:

class BidirectionalLSTM(torch.jit.ScriptModule):
    __constants__ = ['rnn']
    # Inputs hidden units Out
    def __init__(self, nIn, nHidden, nOut):
        super(BidirectionalLSTM, self).__init__()

        self.rnn = nn.LSTM(nIn, nHidden, bidirectional=True)
        self.embedding = nn.Linear(nHidden * 2, nOut)

    @torch.jit.script_method
    def forward(self, input):
        recurrent, _ = self.rnn(input)
        T, b, h = recurrent.size()
        t_rec = recurrent.view(T * b, h)

        output = self.embedding(t_rec)  # [T * b, nOut]
        output = output.view(T, b, -1)

        return output

xx = BidirectionalLSTM(256, 512, 512)
xx.save("xxh.pt")

got an error

could not export python function call <python_value>. Remove calls to python functions before export.:
@torch.jit.script_method
def forward(self, input):
    recurrent, _ = self.rnn(input)
                   ~~~~~~~~ <--- HERE

I add one line of code:
__constants__ = [ 'rnn']

and got this:

TypeError: 'LSTM' object for attribute 'rnn' is not a valid constant.
Valid constants are:
  1. a nn.ModuleList
  2. a value of type {bool, float, int, str, NoneType, function, device, layout, dtype}
  3. a list or tuple of (2)