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#!/usr/bin/env python
# Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
import os
from typing import IO, Any, Dict, List, Sequence
from onnx import AttributeProto, defs, load
from onnx.backend.test.case import collect_snippets
from onnx.backend.test.loader import load_model_tests
from onnx.backend.test.runner import Runner
def is_ml(schemas: Sequence[defs.OpSchema]) -> bool:
return any(s.domain == "ai.onnx.ml" for s in schemas)
def gen_outlines(f: IO[Any], ml: bool) -> None:
f.write("# Test Coverage Report")
if ml:
f.write(" (ONNX-ML Operators)\n")
else:
f.write(" (ONNX Core Operators)\n")
f.write("## Outlines\n")
f.write("* [Node Test Coverage](#node-test-coverage)\n")
f.write("* [Model Test Coverage](#model-test-coverage)\n")
f.write("* [Overall Test Coverage](#overall-test-coverage)\n")
common_covered: Sequence[str] = []
experimental_covered: Sequence[str] = []
def gen_node_test_coverage(
schemas: Sequence[defs.OpSchema], f: IO[Any], ml: bool
) -> None:
global common_covered # noqa: PLW0603
global experimental_covered # noqa: PLW0603
generators = set(
{
"Multinomial",
"RandomNormal",
"RandomNormalLike",
"RandomUniform",
"RandomUniformLike",
}
)
node_tests = collect_snippets()
common_covered = sorted(
s.name
for s in schemas
if s.name in node_tests
and s.support_level == defs.OpSchema.SupportType.COMMON
and (s.domain == "ai.onnx.ml") == ml
)
common_no_cover = sorted(
s.name
for s in schemas
if s.name not in node_tests
and s.support_level == defs.OpSchema.SupportType.COMMON
and (s.domain == "ai.onnx.ml") == ml
)
common_generator = sorted(name for name in common_no_cover if name in generators)
experimental_covered = sorted(
s.name
for s in schemas
if s.name in node_tests
and s.support_level == defs.OpSchema.SupportType.EXPERIMENTAL
and (s.domain == "ai.onnx.ml") == ml
)
experimental_no_cover = sorted(
s.name
for s in schemas
if s.name not in node_tests
and s.support_level == defs.OpSchema.SupportType.EXPERIMENTAL
and (s.domain == "ai.onnx.ml") == ml
)
experimental_generator = sorted(
name for name in experimental_no_cover if name in generators
)
num_common = len(common_covered) + len(common_no_cover) - len(common_generator)
num_experimental = (
len(experimental_covered)
+ len(experimental_no_cover)
- len(experimental_generator)
)
f.write("# Node Test Coverage\n")
f.write("## Summary\n")
if num_common:
f.write(
f"Node tests have covered {len(common_covered)}/{num_common} "
f"({len(common_covered) / float(num_common) * 100:.2f}%, {len(common_generator)} "
f"generators excluded) common operators.\n\n"
)
else:
f.write("Node tests have covered 0/0 (N/A) common operators. \n\n")
if num_experimental:
f.write(
"Node tests have covered {}/{} ({:.2f}%, {} generators excluded) "
"experimental operators.\n\n".format(
len(experimental_covered),
num_experimental,
(len(experimental_covered) / float(num_experimental) * 100),
len(experimental_generator),
)
)
else:
f.write("Node tests have covered 0/0 (N/A) experimental operators.\n\n")
titles = [
"💚Covered Common Operators",
"💔No Cover Common Operators",
"💚Covered Experimental Operators",
"💔No Cover Experimental Operators",
]
all_lists = [
common_covered,
common_no_cover,
experimental_covered,
experimental_no_cover,
]
for t in titles:
f.write(f"* [{t[9:]}](#{t[9:].lower().replace(' ', '-')})\n")
f.write("\n")
for t, l in zip(titles, all_lists): # noqa: E741
f.write(f"## {t}\n")
for s in l:
f.write(f"### {s}")
if s in node_tests:
f.write(
f"\nThere are {len(node_tests[s])} test cases, listed as following:\n"
)
for summary, code in sorted(node_tests[s]):
f.write("<details>\n")
f.write(f"<summary>{summary}</summary>\n\n")
f.write(f"```python\n{code}\n```\n\n")
f.write("</details>\n")
else: # noqa: PLR5501
if s in generators:
f.write(" (random generator operator)\n")
else:
f.write(" (call for test cases)\n")
f.write("\n\n")
f.write("<br/>\n\n")
def gen_model_test_coverage(
schemas: Sequence[defs.OpSchema], f: IO[Any], ml: bool
) -> None:
f.write("# Model Test Coverage\n")
# Process schemas
schema_dict = {}
for schema in schemas:
schema_dict[schema.name] = schema
# Load models from each model test using Runner.prepare_model_data
# Need to grab associated nodes
attrs: Dict[str, Dict[str, List[Any]]] = {}
model_paths: List[Any] = []
for rt in load_model_tests(kind="real"):
if rt.url.startswith("onnx/backend/test/data/light/"):
# testing local files
model_name = os.path.normpath(
os.path.join(os.path.dirname(__file__), "..", "..", "..", rt.url)
)
if not os.path.exists(model_name):
raise FileNotFoundError(f"Unable to find model {model_name!r}.")
model_paths.append(model_name)
else:
model_dir = Runner.prepare_model_data(rt)
model_paths.append(os.path.join(model_dir, "model.onnx"))
model_paths.sort()
model_written = False
for model_pb_path in model_paths:
model = load(model_pb_path)
if ml:
ml_present = False
for opset in model.opset_import:
if opset.domain == "ai.onnx.ml":
ml_present = True
if not ml_present:
continue
else:
model_written = True
f.write(f"## {model.graph.name}\n")
# Deconstruct model
num_covered = 0
for node in model.graph.node:
if node.op_type in common_covered or node.op_type in experimental_covered:
num_covered += 1
# Add details of which nodes are/aren't covered
# Iterate through and store each node's attributes
for attr in node.attribute:
if node.op_type not in attrs:
attrs[node.op_type] = {}
if attr.name not in attrs[node.op_type]:
attrs[node.op_type][attr.name] = []
if attr.type == AttributeProto.FLOAT:
if attr.f not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.f)
elif attr.type == AttributeProto.INT:
if attr.i not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.i)
elif attr.type == AttributeProto.STRING:
if attr.s not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.s)
elif attr.type == AttributeProto.TENSOR:
if attr.t not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.t)
elif attr.type == AttributeProto.GRAPH:
if attr.g not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.g)
elif attr.type == AttributeProto.FLOATS:
if attr.floats not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.floats)
elif attr.type == AttributeProto.INTS:
if attr.ints not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.ints)
elif attr.type == AttributeProto.STRINGS:
if attr.strings not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.strings)
elif attr.type == AttributeProto.TENSORS:
if attr.tensors not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.tensors)
elif attr.type == AttributeProto.GRAPHS:
if attr.graphs not in attrs[node.op_type][attr.name]:
attrs[node.op_type][attr.name].append(attr.graphs)
f.write(
f"\n{model.graph.name} has {num_covered} nodes. "
f"Of these, {len(model.graph.node)} are covered by node tests "
f"({100.0 * float(num_covered) / float(len(model.graph.node))}%)\n\n\n"
)
# Iterate through attrs, print
f.write("<details>\n")
f.write("<summary>nodes</summary>\n\n")
for op in sorted(attrs):
f.write("<details>\n")
# Get total number of attributes for node schema
f.write(
f"<summary>{op}: {len(attrs[op])} out of {len(schema_dict[op].attributes)} attributes covered</summary>\n\n"
)
for attribute in sorted(schema_dict[op].attributes):
if attribute in attrs[op]:
f.write(f"{attribute}: {len(attrs[op][attribute])}\n")
else:
f.write(f"{attribute}: 0\n")
f.write("</details>\n")
f.write("</details>\n\n\n")
if not model_written and ml:
f.write("No model tests present for selected domain\n")
def gen_overall_test_coverage(
schemas: Sequence[defs.OpSchema], f: IO[Any], ml: bool
) -> None:
f.write("# Overall Test Coverage\n")
f.write("## To be filled.\n")
def gen_spdx(f: IO[Any]) -> None:
f.write("<!--- SPDX-License-Identifier: Apache-2.0 -->\n")
def main() -> None:
base_dir = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
)
docs_dir = os.path.join(base_dir, "docs")
schemas = defs.get_all_schemas()
has_ml = is_ml(schemas)
fname = os.path.join(docs_dir, "TestCoverage.md")
with open(fname, "w+", newline="", encoding="utf-8") as f: # type: ignore
gen_spdx(f)
gen_outlines(f, False)
gen_node_test_coverage(schemas, f, False)
gen_model_test_coverage(schemas, f, False)
gen_overall_test_coverage(schemas, f, False)
if has_ml:
fname = os.path.join(docs_dir, "TestCoverage-ml.md")
with open(fname, "w+", newline="", encoding="utf-8") as f: # type: ignore
gen_spdx(f)
gen_outlines(f, True)
gen_node_test_coverage(schemas, f, True)
gen_model_test_coverage(schemas, f, True)
gen_overall_test_coverage(schemas, f, True)
if __name__ == "__main__":
main()
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