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torch.jit.ignore#

torch.jit.ignore(drop=False, **kwargs)[source]#

此裝飾器指示編譯器忽略函式或方法,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,被忽略的函式將把呼叫分派給 Python 直譯器。包含被忽略函式的模型無法匯出;請改用 @torch.jit.unused

示例(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")

示例(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")