onnxruntime/tools/python/gen_opkernel_doc.py
Scott McKay 0fbec1b9c1
Update the operator documentation generation (#7787)
* Update the operator documentation generation
  - Make layout a little nicer
  - Update to latest supported operators including training
  - Fix some links that are broken when the docs content is copied to github-pages
  - Fix incorrect usage of 'onnx.ai.ml' as the default domain
    - ML ops are now separated from the real default domain of 'onnx.ai'
  - Include CPU, CUDA and training kernels
    - exclude DNNL as it's not an EP we own

* There are separate paths for CUDA and CUDNN as they are not guaranteed to be in the same location on a Windows machine. Use the CUDNN path when looking for the CUDNN library.

* Enable validation of both contrib ops and operator kernels in build
Filter generation so it's deterministic
Add ability for CI to publish the md files as build artifacts if they differ so a developer can download and add to their PR to resolve any diffs.
Remove workarounds for github-pages as that will now link to the github docs which display correctly
2021-06-02 17:47:40 +10:00

173 lines
6.5 KiB
Python

#!/usr/bin/env python
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import argparse
import io
import os
import pathlib
from collections import defaultdict
import onnxruntime.capi.onnxruntime_pybind11_state as rtpy
def format_version_range(v):
if (v[1] >= 2147483647):
return str(v[0])+'+'
else:
if (v[0] == v[1]):
return str(v[0])
else:
return '['+str(v[0])+', '+str(v[1])+']'
def format_type_constraints(tc):
counter = 0
tcstr = ''
firsttcitem = True
for tcitem in tc:
counter += 1
if firsttcitem:
firsttcitem = False
else:
tcstr += ', '
tcstr += tcitem
return tcstr
def format_param_strings(params):
firstparam = True
s = ''
if params:
for param in sorted(params):
if firstparam:
firstparam = False
else:
s += '<br><br>or<br><br>'
s += param
return s
def expand_providers(provider_filter: [str]):
providers = set()
if provider_filter:
for provider in provider_filter:
p = provider.lower()
if not p.endswith('executionprovider'):
p += 'executionprovider'
providers.add(p)
return providers
def main(output_path: pathlib.Path, provider_filter: [str]):
providers = expand_providers(provider_filter)
with io.open(output_path, 'w', newline='', encoding="utf-8") as fout:
fout.write('## Supported Operators and Data Types\n')
fout.write(
"*This file is automatically generated from the registered kernels by "
"[this script](https://github.com/microsoft/onnxruntime/blob/master/tools/python/gen_opkernel_doc.py).\n"
"Do not modify directly.*\n\n")
opdef = rtpy.get_all_operator_schema()
paramdict = {}
for schema in opdef:
inputs = schema.inputs
domain = schema.domain
if (domain == ''):
domain = 'ai.onnx'
fullname = domain+'.'+schema.name
paramstr = ''
firstinput = True
if inputs:
for inp in inputs:
if firstinput:
firstinput = False
else:
paramstr += '<br> '
paramstr += '*in* {}:**{}**'.format(inp.name, inp.typeStr)
outputs = schema.outputs
if outputs:
for outp in outputs:
if firstinput:
firstinput = False
else:
paramstr += '<br> '
paramstr += '*out* {}:**{}**'.format(outp.name, outp.typeStr)
paramstr += ''
paramset = paramdict.get(fullname, None)
if paramset is None:
paramdict[fullname] = set()
paramdict[fullname].add(paramstr)
index = defaultdict(lambda: defaultdict(lambda: defaultdict(list)))
for op in rtpy.get_all_opkernel_def():
domain = op.domain
if (domain == ''):
domain = 'ai.onnx'
index[op.provider][domain][op.op_name].append(op)
# TOC
fout.write('## Execution Providers\n\n')
for provider in sorted(index.keys()):
if providers and provider.lower() not in providers:
continue
fout.write('- [{}](#{})\n'.format(provider, provider.lower()))
fout.write('\n---------------')
for provider, domainmap in sorted(index.items()):
if providers and provider.lower() not in providers:
continue
fout.write('\n\n<a name="{}"/>\n\n'.format(provider.lower()))
fout.write('## Operators implemented by {}\n\n'.format(provider))
fout.write('| Op Name | Parameters | OpSet Version | Types Supported |\n')
fout.write('|---------|------------|---------------|-----------------|\n')
for domain, namemap in sorted(domainmap.items()):
fout.write('|**Operator Domain:** *'+domain+'*||||\n')
for name, ops in sorted(namemap.items()):
version_type_index = defaultdict(lambda: defaultdict(set))
for op in ops:
for tname, tclist in op.type_constraints.items():
for c in tclist:
version_type_index[op.version_range][tname].add(c)
namefirsttime = True
for version_range, typemap in sorted(version_type_index.items(), key=lambda x: x[0], reverse=True):
if (namefirsttime):
params = paramdict.get(domain+'.'+name, None)
fout.write('|' + name + '|' + format_param_strings(params) + '|')
namefirsttime = False
else:
fout.write('|||')
fout.write(format_version_range(version_range) + '|')
tnameindex = 0
for tname, tcset in sorted(typemap.items()):
tnameindex += 1
tclist = []
for tc in sorted(tcset):
tclist.append(tc)
fout.write('**'+tname+'** = '+format_type_constraints(tclist))
if (tnameindex < len(typemap)):
fout.write('<br/> ')
fout.write('|\n')
fout.write('| |\n| |\n')
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='ONNX Runtime Operator Kernel Documentation Generator')
parser.add_argument('--providers', nargs='+',
help="Filter to specified execution providers. Case-insensitive. "
"Matches provider names from <ORT>/include/onnxruntime/core/graph/constants.h'. "
"'ExecutionProvider' is automatically appended as needed. "
"e.g. `--providers cpu cuda` will match CPUExecutionProvider and CUDAExecutionProvider.")
parser.add_argument('--output_path', help='output markdown file path', type=pathlib.Path, required=True,
default=os.path.join(os.path.dirname(os.path.realpath(__file__)), 'OperatorKernels.md'))
args = parser.parse_args()
main(args.output_path, args.providers)