torch.map¶
dynamic_shape_map¶
Original source code:
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:
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: {}