torch-mlir/python/torch_mlir/fx.py

69 lines
2.3 KiB
Python

# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
# See https://llvm.org/LICENSE.txt for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
# Also available under a BSD-style license. See LICENSE.
from typing import Optional, Union, Dict, Tuple, Any
import warnings
import torch
import torch.export
import torch.nn as nn
from torch_mlir.extras.fx_importer import FxImporter, FxImporterHooks
from torch_mlir import ir
from torch_mlir.dialects import torch as torch_d
from torch_mlir.extras.fx_decomp_util import get_decomposition_table
def export_and_import(
f,
*args,
fx_importer: Optional[FxImporter] = None,
dynamic_shapes: Optional[Union[Dict[str, Any], Tuple[Any]]] = None,
experimental_support_mutation: bool = False,
hooks: Optional[FxImporterHooks] = None,
decomposition_table: Optional[list] = None,
func_name: str = "main",
enable_graph_printing: bool = False,
**kwargs,
):
context = ir.Context()
torch_d.register_dialect(context)
if fx_importer is None:
fx_importer = FxImporter(context=context, hooks=hooks)
prog = torch.export.export(f, args, kwargs, dynamic_shapes=dynamic_shapes)
if decomposition_table is None:
decomposition_table = get_decomposition_table()
if decomposition_table:
prog = prog.run_decompositions(decomposition_table)
if enable_graph_printing:
prog.graph_module.print_readable()
if experimental_support_mutation:
if torch.__version__ < "2.3.0.dev20240207":
warnings.warn("Mutable program import only supported on PyTorch 2.3+")
fx_importer.import_program(prog, func_name=func_name)
else:
fx_importer.import_frozen_program(prog, func_name=func_name)
return fx_importer.module
def stateless_fx_import(
gm: torch.fx.GraphModule,
fx_importer: Optional[FxImporter] = None,
hooks: Optional[FxImporterHooks] = None,
model_name: str = "main",
enable_graph_printing: bool = False,
):
if enable_graph_printing:
gm.print_readable()
context = ir.Context()
torch_d.register_dialect(context)
if fx_importer is None:
fx_importer = FxImporter(context=context, hooks=hooks)
fx_importer.import_stateless_graph(gm.graph, func_name=model_name)
return fx_importer.module