Files
pytorch/tools/setup_helpers/generate_code.py
Nathan Goldbaum 1e230a5c52 rewrite C++ __torch_function__ handling to work with TensorList operands (#41575)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41575

Fixes https://github.com/pytorch/pytorch/issues/34294

This updates the C++ argument parser to correctly handle `TensorList` operands. I've also included a number of updates to the testing infrastructure, this is because we're now doing a much more careful job of testing the signatures of aten kernels, using the type information about the arguments as read in from `Declarations.yaml`. The changes to the tests are required because we're now only checking for `__torch_function__` attributes on `Tensor`, `Optional[Tensor]` and elements of `TensorList` operands, whereas before we were checking for `__torch_function__` on all operands, so the relatively simplistic approach the tests were using before -- assuming all positional arguments might be tensors -- doesn't work anymore. I now think that checking for `__torch_function__` on all operands was a mistake in the original design.

The updates to the signatures of the `lambda` functions are to handle this new, more stringent checking of signatures.

I also added override support for `torch.nn.functional.threshold` `torch.nn.functional.layer_norm`, which did not yet have python-level support.

Benchmarks are still WIP.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/34725

Reviewed By: mruberry

Differential Revision: D22357738

Pulled By: ezyang

fbshipit-source-id: 0e7f4a58517867b2e3f193a0a8390e2ed294e1f3
2020-07-17 08:54:29 -07:00

130 lines
4.6 KiB
Python

import argparse
import os
import sys
source_files = {'.py', '.cpp', '.h'}
DECLARATIONS_PATH = 'torch/share/ATen/Declarations.yaml'
# TODO: This is a little inaccurate, because it will also pick
# up setup_helper scripts which don't affect code generation
def all_generator_source():
r = []
for directory, _, filenames in os.walk('tools'):
for f in filenames:
if os.path.splitext(f)[1] in source_files:
full = os.path.join(directory, f)
r.append(full)
return sorted(r)
def generate_code(ninja_global=None,
declarations_path=None,
nn_path=None,
install_dir=None,
subset=None,
disable_autograd=False,
selected_op_list_path=None,
selected_op_list=None,
force_schema_registration=False):
# cwrap depends on pyyaml, so we can't import it earlier
root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.insert(0, root)
from tools.autograd.gen_autograd import gen_autograd, gen_autograd_python
from tools.autograd.gen_annotated_fn_args import gen_annotated
from tools.jit.gen_unboxing_wrappers import gen_unboxing_wrappers
# Build ATen based Variable classes
if install_dir is None:
install_dir = 'torch/csrc'
python_install_dir = 'torch/testing/_internal/generated'
else:
python_install_dir = install_dir
autograd_gen_dir = os.path.join(install_dir, 'autograd', 'generated')
jit_gen_dir = os.path.join(install_dir, 'jit', 'generated')
for d in (autograd_gen_dir, jit_gen_dir, python_install_dir):
if not os.path.exists(d):
os.makedirs(d)
runfiles_dir = os.environ.get("RUNFILES_DIR", None)
data_dir = os.path.join(runfiles_dir, 'pytorch') if runfiles_dir else ''
autograd_dir = os.path.join(data_dir, 'tools', 'autograd')
tools_jit_templates = os.path.join(data_dir, 'tools', 'jit', 'templates')
if subset == "pybindings" or not subset:
gen_autograd_python(declarations_path or DECLARATIONS_PATH, autograd_gen_dir, autograd_dir)
if subset == "libtorch" or not subset:
gen_autograd(
declarations_path or DECLARATIONS_PATH,
autograd_gen_dir,
autograd_dir,
disable_autograd=disable_autograd,
selected_op_list=selected_op_list,
)
gen_unboxing_wrappers(
declarations_path or DECLARATIONS_PATH,
jit_gen_dir,
tools_jit_templates,
disable_autograd=disable_autograd,
selected_op_list_path=selected_op_list_path,
selected_op_list=selected_op_list,
force_schema_registration=force_schema_registration)
if subset == "python" or not subset:
gen_annotated(
declarations_path or DECLARATIONS_PATH,
python_install_dir,
autograd_dir)
def main():
parser = argparse.ArgumentParser(description='Autogenerate code')
parser.add_argument('--declarations-path')
parser.add_argument('--nn-path')
parser.add_argument('--ninja-global')
parser.add_argument('--install_dir')
parser.add_argument(
'--subset',
help='Subset of source files to generate. Can be "libtorch" or "pybindings". Generates both when omitted.'
)
parser.add_argument(
'--disable-autograd',
default=False,
action='store_true',
help='It can skip generating autograd related code when the flag is set',
)
parser.add_argument(
'--selected-op-list-path',
help='Path to the yaml file that contains the list of operators to include for custom build.',
)
parser.add_argument(
'--selected-op-list',
nargs="*",
type=str,
help="""List of operator names to include for custom build, in addition to those in selected-op-list-path.
For example, --selected-op-list aten::add.Tensor aten::_convolution.""",
)
parser.add_argument(
'--force_schema_registration',
action='store_true',
help='force it to generate schema-only registrations for ops that are not'
'listed on --selected-op-list'
)
options = parser.parse_args()
generate_code(
options.ninja_global,
options.declarations_path,
options.nn_path,
options.install_dir,
options.subset,
options.disable_autograd,
options.selected_op_list_path,
options.selected_op_list,
options.force_schema_registration,
)
if __name__ == "__main__":
main()