torch-mlir/python/torch_mlir/compiler_utils.py

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# 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 io import StringIO
import os
import sys
import tempfile
from torch_mlir.passmanager import PassManager
from torch_mlir.ir import StringAttr
def get_module_name_for_debug_dump(module):
"""Gets a name suitable for a debug dump.
The name is not guaranteed to be unique.
"""
if not "torch.debug_module_name" in module.operation.attributes:
return "UnnammedModule"
return StringAttr(module.operation.attributes["torch.debug_module_name"]).value
class TorchMlirCompilerError(Exception):
def __init__(self, value: str):
super().__init__()
self.value = value
def __str__(self) -> str:
return self.value
def run_pipeline_with_repro_report(module,
pipeline: str,
description: str):
"""Runs `pipeline` on `module`, with a nice repro report if it fails."""
module_name = get_module_name_for_debug_dump(module)
try:
original_stderr = sys.stderr
sys.stderr = StringIO()
asm_for_error_report = module.operation.get_asm(
large_elements_limit=10, enable_debug_info=True)
# Lower module in place to make it ready for compiler backends.
with module.context:
pm = PassManager.parse(pipeline)
pm.run(module.operation)
except Exception as e:
# TODO: More robust.
# - don't arbitrarily clutter up /tmp. When a test suite has many
# tests, this can be a big disk cost (also, /tmp/ is frequently a
# RAM fs, which increases worries about capacity).
# - don't have colliding filenames (hard to do without cluttering
# up /tmp)
# - if we do have have colliding filenames, writes should at least
# avoid being racy.
filename = os.path.join(tempfile.gettempdir(), module_name + ".mlir")
with open(filename, 'w') as f:
f.write(asm_for_error_report)
debug_options="-mlir-print-ir-after-all -mlir-disable-threading"
# Put something descriptive here even if description is empty.
description = description or f"{module_name} compile"
message = f"""\
{description} failed with the following diagnostics:
{sys.stderr.getvalue()}
2022-10-05 22:00:59 +08:00
For Torch-MLIR developers, the error can be reproduced with:
$ torch-mlir-opt -pass-pipeline='{pipeline}' {filename}
Add '{debug_options}' to get the IR dump for debugging purpose.
"""
trimmed_message = '\n'.join([m.lstrip() for m in message.split('\n')])
raise TorchMlirCompilerError(trimmed_message) from None
finally:
sys.stderr = original_stderr