torch.jit.ignore

torch.jit.ignore(drop=False, **kwargs)

此裝飾器 (decorator) 向編譯器表明，應忽略某個函式或方法，並將其保留為 Python 函式。 這允許您在模型中保留尚未與 TorchScript 相容的程式碼。 如果從 TorchScript 呼叫，被忽略的函式會將呼叫分派給 Python 直譯器。 具有被忽略函式的模型無法匯出；請改用 @torch.jit.unused。

範例（在方法上使用 @torch.jit.ignore）

import torch
import torch.nn as nn


class MyModule(nn.Module):
    @torch.jit.ignore
    def debugger(self, x):
        import pdb

        pdb.set_trace()

    def forward(self, x):
        x += 10
        # The compiler would normally try to compile `debugger`,
        # but since it is `@ignore`d, it will be left as a call
        # to Python
        self.debugger(x)
        return x


m = torch.jit.script(MyModule())

# Error! The call `debugger` cannot be saved since it calls into Python
m.save("m.pt")

範例（在方法上使用 @torch.jit.ignore(drop=True)）

import torch
import torch.nn as nn

class MyModule(nn.Module):
    @torch.jit.ignore(drop=True)
    def training_method(self, x):
        import pdb
        pdb.set_trace()

    def forward(self, x):
        if self.training:
            self.training_method(x)
        return x

m = torch.jit.script(MyModule())

# This is OK since `training_method` is not saved, the call is replaced
# with a `raise`.
m.save("m.pt")