# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. # pyre-strict import copy from typing import Dict, Union import torch from torch._guards import detect_fake_mode from torch.export import ExportedProgram def get_fake_program(real_exported_program: ExportedProgram) -> ExportedProgram: """Create a fake exported program. This uses fake tensors for the state dict to prevent mutation, and points to the real constants, to avoid large memory usage from copying when constants are large. Args: real_exported_program: the original exported program Returns: A new exported program, with fake tensors. """ fake_mode = detect_fake_mode( tuple( node.meta["val"] for node in real_exported_program.graph.nodes if node.op == "placeholder" ) ) if fake_mode is None: raise AssertionError( "Could not detect fake mode for graph: ", real_exported_program.graph ) new_state_dict: Dict[str, Union[torch.Tensor, torch.nn.Parameter]] = {} for key, tensor in real_exported_program.state_dict.items(): fake = fake_mode.from_tensor(tensor, static_shapes=True) new_state_dict[key] = fake gm = copy.deepcopy(real_exported_program.graph_module) fake_exported_program = ExportedProgram( root=gm, graph=gm.graph, graph_signature=copy.deepcopy(real_exported_program.graph_signature), state_dict=new_state_dict, range_constraints=copy.deepcopy(real_exported_program.range_constraints), module_call_graph=copy.deepcopy(real_exported_program.module_call_graph), constants=real_exported_program.constants, verifiers=[real_exported_program.verifier], ) return fake_exported_program def update_to_real_program( fake_exported_program: ExportedProgram, real_exported_program: ExportedProgram ) -> None: """Update the fake exported program to point to the real state dict. Modifies the fake exported program in-place. """ for k, v in real_exported_program.state_dict.items(): fake_exported_program._state_dict[k] = v