torch.map ============= dynamic_shape_map ^^^^^^^^^^^^^^^^^ .. note:: Tags: :doc:`torch.map `, :doc:`torch.dynamic-shape ` Support Level: SUPPORTED Original source code: .. code-block:: python import torch from functorch.experimental.control_flow import map def dynamic_shape_map(xs, y): """ functorch map() maps a function over the first tensor dimension. """ def body(x, y): return x + y return map(body, xs, y) Result: .. code-block:: ExportedProgram: class GraphModule(torch.nn.Module): def forward(self, arg0_1: f32[3, 2], arg1_1: f32[2]): # submodule_0 = self.submodule_0 map_impl = torch.ops.map_impl(submodule_0, 1, arg0_1, arg1_1); submodule_0 = arg0_1 = arg1_1 = None getitem: f32[3, 2] = map_impl[0]; map_impl = None return (getitem,) class GraphModule(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] Graph Signature: ExportGraphSignature(parameters=[], buffers=[], user_inputs=['arg0_1', 'arg1_1'], user_outputs=['getitem'], inputs_to_parameters={}, inputs_to_buffers={}, buffers_to_mutate={}, backward_signature=None, assertion_dep_token=None) Symbol to range: {}