torch.map¶

dynamic_shape_map¶

注意

支持级别：支持

原始源代码：

import torch

from functorch.experimental.control_flow import map


class DynamicShapeMap(torch.nn.Module):
    """
    functorch map() 将一个函数映射到第一个张量维度上。
    """

    def __init__(self):
        super().__init__()

    def forward(self, xs, y):
        def body(x, y):
            return x + y

        return map(body, xs, y)

结果:

导出的程序:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: "f32[3, 2]", arg1_1: "f32[2]"):
                body_graph_0 = self.body_graph_0
            map_impl = torch.ops.higher_order.map_impl(body_graph_0, [arg0_1], [arg1_1]);  body_graph_0 = arg0_1 = arg1_1 = None
            getitem: "f32[3, 2]" = map_impl[0];  map_impl = None
            return (getitem,)

        class (torch.nn.Module):
            def forward(self, arg0_1: "f32[2]", arg1_1: "f32[2]"):
                        add: "f32[2]" = torch.ops.aten.add.Tensor(arg0_1, arg1_1);  arg0_1 = arg1_1 = None
                return (add,)

图的签名: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='arg0_1'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='arg1_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
范围约束: {}