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onnx/onnx

Open standard for machine learning interoperability

12.0 Moderate pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for onnx/onnx, a Python project with 21,575 GitHub stars. SynthScan examined 183,356 lines of code across 857 source files, recording 2369 pattern matches distributed across 20 syntactic categories. The legacy adjusted pattern signal is 12.0 (Moderate pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

12.0
Adjusted Signal
12.0
Raw Pattern Score
100%
Time Factor
2026-10-10
Last Push
21.6K
Stars
Python
Language
183.4K
Lines of Code
857
Files
2.4K
Pattern Hits
2026-10-12
Scan Date
0.06
HC Hit Rate

Risk Review · v3

Use each vector to guide manual verification of the underlying findings.

Cognitive Ownership Risk 26.9/100 · MEDIUM

Can maintainers explain intent, assumptions, and trade-offs? 1398 finding(s).

Hallucinated Dependency & Supply Chain Risk 18.5/100 · LOW

Are imports declared and package/API names verified? 878 finding(s).

Agent Over-Engineering Ratio 26.6/100 · MEDIUM

Are wrappers, guards, and repeated structures necessary? 1248 finding(s).

PR Review Velocity Impact 52.3/100 · HIGH

Which changes need focused human review? 2369 finding(s).

What These Metrics Mean

Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.

Pattern-Signal History

This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.

Severity Breakdown

Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.

CRITICAL 0HIGH 52MEDIUM 43LOW 2274

Directory Score Breakdown

This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.

Pattern Findings

The scanner identified 2369 distinct pattern matches across 20 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.

Hyper-Verbose Identifiers1129 hits · 805 pts
SeverityFileLineSnippetContext
LOWonnx/model_container.py120 def is_in_memory_external_initializer(self, name: str) -> bool:CODE
LOWonnx/__init__.py462def _operator_set_protos_repr(protos: Sequence[OperatorSetIdProto]) -> str:CODE
LOWonnx/shape_inference.py159def infer_function_output_types(CODE
LOWonnx/utils.py66 def _dfs_search_reachable_nodes(CODE
LOWonnx/utils.py109 def _collect_referred_local_functions(CODE
LOWonnx/utils.py137 def _collect_reachable_tensors(CODE
LOWonnx/helper.py86def _create_op_set_id_version_map(table: VersionTableType) -> VersionMapType:CODE
LOWonnx/helper.py790def make_empty_tensor_value_info(name: str) -> ValueInfoProto:CODE
LOWonnx/helper.py859def make_sparse_tensor_type_proto(CODE
LOWonnx/helper.py904def make_sparse_tensor_value_info(CODE
LOWonnx/helper.py982def make_tensor_sequence_value_info(CODE
LOWonnx/helper.py1294def tensor_dtype_to_storage_tensor_dtype(tensor_dtype: int) -> int:CODE
LOWonnx/inliner.py30def inline_selected_functions(CODE
LOWonnx/external_data_helper.py111def _validate_external_data_file_bounds(CODE
LOWonnx/external_data_helper.py146def _read_external_data_bytes(tensor: TensorProto, base_dir: str) -> bytes:CODE
LOWonnx/external_data_helper.py166def load_external_data_for_tensor(tensor: TensorProto, base_dir: str) -> None:CODE
LOWonnx/external_data_helper.py183def load_external_data_for_model(model: ModelProto, base_dir: str) -> None:CODE
LOWonnx/external_data_helper.py223def convert_model_to_external_data(CODE
LOWonnx/external_data_helper.py275def convert_model_from_external_data(model: ModelProto) -> None:CODE
LOWonnx/external_data_helper.py341def _recursive_attribute_processor(CODE
LOWonnx/external_data_helper.py352def _get_initializer_tensors_from_graph(graph: GraphProto, /) -> Iterable[TensorProto]:CODE
LOWonnx/external_data_helper.py367def _get_attribute_tensors_from_graph(CODE
LOWonnx/external_data_helper.py403def remove_external_data_field(tensor: TensorProto, field_key: str) -> None:CODE
LOWonnx/external_data_helper.py417def write_external_data_tensors(model: ModelProto, filepath: str) -> ModelProto:CODE
LOWonnx/serialization.py82 def get_format_from_file_extension(self, file_extension: str) -> str | None:CODE
LOWonnx/tools/replace_constants.py71def _replace_constant_of_shape_with_range(CODE
LOWonnx/tools/replace_constants.py153def _replace_constant_of_shape_value(CODE
LOWonnx/tools/replace_constants.py199def replace_initializer_by_constant_of_shape( # noqa: PLR0911CODE
LOWonnx/tools/update_model_dims.py12def update_inputs_outputs_dims(CODE
LOWonnx/backend/test/stat_coverage.py256def gen_overall_test_coverage(CODE
LOWonnx/backend/test/case/model/gradient.py16 def export_gradient_scalar_add() -> None:CODE
LOWonnx/backend/test/case/model/gradient.py61 def export_gradient_scalar_add_and_mul() -> None:CODE
LOWonnx/backend/test/case/node/globalmaxpool.py26 def export_globalmaxpool_precomputed() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py101 def export_softmaxcrossentropy_none() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py125 def export_softmaxcrossentropy_none_log_prob() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py156 def export_softmaxcrossentropy_none_weights() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py186 def export_softmaxcrossentropy_none_weights_log_prob() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py218 def export_softmaxcrossentropy_sum() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py242 def export_softmaxcrossentropy_sum_log_prob() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py273 def export_softmaxcrossentropy_mean() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py297 def export_softmaxcrossentropy_mean_log_prob() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py379 def export_softmaxcrossentropy_mean_weights() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py409 def export_softmaxcrossentropy_mean_weights_log_prob() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py441 def export_softmaxcrossentropy_mean_weights_ii() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py474 def export_softmaxcrossentropy_mean_weights_ii_log_prob() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py509 def export_softmaxcrossentropy_mean_no_weights_ii() -> None:CODE
LOW…x/backend/test/case/node/softmax_cross_entropy_loss.py538 def export_softmaxcrossentropy_mean_no_weights_ii_log_prob() -> None:CODE
LOWonnx/backend/test/case/node/max.py51 def export_max_all_numeric_types() -> None:CODE
LOWonnx/backend/test/case/node/reducesum.py89 def export_default_axes_keepdims() -> None:CODE
LOWonnx/backend/test/case/node/reducesum.py124 def export_negative_axes_keepdims() -> None:CODE
LOWonnx/backend/test/case/node/reducesum.py161 def export_empty_axes_input_noop() -> None:CODE
LOWonnx/backend/test/case/node/reducesum.py225 def export_non_reduced_axis_zero() -> None:CODE
LOWonnx/backend/test/case/node/sequence_map.py263 def export_sequence_map_extract_shapes(): # type: () -> NoneCODE
LOWonnx/backend/test/case/node/gather.py72 def export_gather_negative_indices() -> None:CODE
LOWonnx/backend/test/case/node/attention.py71 def export_attention_diff_head_sizes() -> None:CODE
LOWonnx/backend/test/case/node/attention.py113 def export_attention_gqa_scaled() -> None:CODE
LOWonnx/backend/test/case/node/attention.py137 def export_attention_diff_head_sizes_scaled() -> None:CODE
LOWonnx/backend/test/case/node/attention.py184 def export_attention_gqa_causal() -> None:CODE
LOWonnx/backend/test/case/node/attention.py207 def export_attention_diff_head_sizes_causal() -> None:CODE
LOWonnx/backend/test/case/node/attention.py235 def export_attention_attn_mask() -> None:CODE
1069 more matches not shown…
Unused Imports876 hits · 740 pts
SeverityFileLineSnippetContext
LOWtools/gen_coverage_report.py6CODE
LOWtools/pretty_clang_tidy.py5CODE
LOWtools/check_namespace.py10CODE
LOWonnx/model_container.py8CODE
LOWonnx/gen_proto.py6CODE
LOWonnx/version.py10CODE
LOWonnx/version.py14CODE
LOWonnx/compose.py4CODE
LOWonnx/__init__.py5CODE
LOWonnx/__init__.py82CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py88CODE
LOWonnx/__init__.py125CODE
LOWonnx/__init__.py125CODE
LOWonnx/__init__.py126CODE
LOWonnx/__init__.py126CODE
LOWonnx/__init__.py126CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/__init__.py130CODE
LOWonnx/parser.py4CODE
LOWonnx/shape_inference.py10CODE
LOWonnx/utils.py4CODE
LOWonnx/numpy_helper.py4CODE
816 more matches not shown…
Cross-File Repetition46 hits · 230 pts
SeverityFileLineSnippetContext
HIGHonnx/backend/test/case/node/flexattention.py0test flexattention with different head sizes for q/k vs v.STRING
HIGHdocs/TestCoverage.md0test flexattention with different head sizes for q/k vs v.STRING
HIGHtests/python/shape_inference_test.py0test flexattention with different head sizes for q/k vs v.STRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 5, 5] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 5, 5] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHdocs/TestCoverage.md0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 5, 5] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 2, 2]STRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 2, 2]STRING
HIGHdocs/TestCoverage.md0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 2, 2]STRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 3, 3] pad_shape: [2, 2] -> [1, 1, 1, 1] by axisSTRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 3, 3] pad_shape: [2, 2] -> [1, 1, 1, 1] by axisSTRING
HIGHdocs/TestCoverage.md0input_shape: [1, 1, 5, 5] output_shape: [1, 1, 3, 3] pad_shape: [2, 2] -> [1, 1, 1, 1] by axisSTRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 3, 32, 32, 32] output_shape: [1, 3, 31, 31, 31]STRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 3, 32, 32, 32] output_shape: [1, 3, 31, 31, 31]STRING
HIGHonnx/backend/test/case/node/lppool.py0input_shape: [1, 3, 32, 32, 32] output_shape: [1, 3, 31, 31, 31]STRING
HIGHdocs/TestCoverage.md0input_shape: [1, 3, 32, 32, 32] output_shape: [1, 3, 31, 31, 31]STRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 32, 32] pad_shape: [1, 1] -> [1, 0, 1, 0] by axisSTRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 32, 32] pad_shape: [1, 1] -> [1, 0, 1, 0] by axisSTRING
HIGHonnx/backend/test/case/node/lppool.py0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 32, 32] pad_shape: [1, 1] -> [1, 0, 1, 0] by axisSTRING
HIGHdocs/TestCoverage.md0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 32, 32] pad_shape: [1, 1] -> [1, 0, 1, 0] by axisSTRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 3, 28, 28] output_shape: [1, 3, 30, 30] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 3, 28, 28] output_shape: [1, 3, 30, 30] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHonnx/backend/test/case/node/lppool.py0input_shape: [1, 3, 28, 28] output_shape: [1, 3, 30, 30] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHdocs/TestCoverage.md0input_shape: [1, 3, 28, 28] output_shape: [1, 3, 30, 30] pad_shape: [4, 4] -> [2, 2, 2, 2] by axisSTRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 10, 10]STRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 10, 10]STRING
HIGHonnx/backend/test/case/node/lppool.py0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 10, 10]STRING
HIGHdocs/TestCoverage.md0input_shape: [1, 3, 32, 32] output_shape: [1, 3, 10, 10]STRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 1, 4, 4, 4] output_shape: [1, 1, 2, 2, 2]STRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 1, 4, 4, 4] output_shape: [1, 1, 2, 2, 2]STRING
HIGHonnx/backend/test/case/node/lppool.py0input_shape: [1, 1, 4, 4, 4] output_shape: [1, 1, 2, 2, 2]STRING
HIGHdocs/TestCoverage.md0input_shape: [1, 1, 4, 4, 4] output_shape: [1, 1, 2, 2, 2]STRING
HIGHonnx/backend/test/case/node/averagepool.py0input_shape: [1, 1, 2, 2] output_shape: [1, 1, 1, 1]STRING
HIGHdocs/TestCoverage.md0input_shape: [1, 1, 2, 2] output_shape: [1, 1, 1, 1]STRING
HIGHonnx/backend/test/case/node/maxpool.py0input_shape: [1, 1, 2, 2] output_shape: [1, 1, 1, 1]STRING
HIGHonnx/backend/test/case/node/gru.py0run a forward pass of the rnn. assumes that the num_directions axis has been squeezed out of the inputs. (and returns y,STRING
HIGHonnx/reference/ops/op_gru.py0run a forward pass of the rnn. assumes that the num_directions axis has been squeezed out of the inputs. (and returns y,STRING
HIGHonnx/backend/test/case/node/rnn.py0run a forward pass of the rnn. assumes that the num_directions axis has been squeezed out of the inputs. (and returns y,STRING
HIGHonnx/reference/ops/op_rnn.py0run a forward pass of the rnn. assumes that the num_directions axis has been squeezed out of the inputs. (and returns y,STRING
HIGHonnx/reference/ops/experimental/_op_list.py0loads the implemented for a specified operator. args: domain: domain op_type: operator type version: requested version cSTRING
HIGHonnx/reference/ops/aionnx_preview_training/_op_list.py0loads the implemented for a specified operator. args: domain: domain op_type: operator type version: requested version cSTRING
HIGHonnx/reference/ops/aionnx_preview/_op_list.py0loads the implemented for a specified operator. args: domain: domain op_type: operator type version: requested version cSTRING
HIGHonnx/reference/ops/aionnxml/_op_list.py0loads the implemented for a specified operator. args: domain: domain op_type: operator type version: requested version cSTRING
HIGHtests/python/checker_test.py0<ir_version: 8, opset_import: [ "" : 17, "local" : 1 ]> agraph (float[n] x) => (float[n] y) { y = local.foo (x) } <opsetSTRING
HIGHtests/python/inliner_test.py0<ir_version: 8, opset_import: [ "" : 17, "local" : 1 ]> agraph (float[n] x) => (float[n] y) { y = local.foo (x) } <opsetSTRING
HIGHtests/python/shape_inference_test.py0<ir_version: 8, opset_import: [ "" : 17, "local" : 1 ]> agraph (float[n] x) => (float[n] y) { y = local.foo (x) } <opsetSTRING
Deep Nesting100 hits · 100 pts
SeverityFileLineSnippetContext
LOWtools/check_namespace.py15CODE
LOWonnx/gen_proto.py41CODE
LOWonnx/compose.py91CODE
LOWonnx/compose.py446CODE
LOWonnx/compose.py569CODE
LOWonnx/compose.py221CODE
LOWonnx/numpy_helper.py408CODE
LOWonnx/numpy_helper.py494CODE
LOWonnx/numpy_helper.py689CODE
LOWonnx/helper.py86CODE
LOWonnx/helper.py365CODE
LOWonnx/helper.py517CODE
LOWonnx/helper.py579CODE
LOWonnx/helper.py617CODE
LOWonnx/helper.py796CODE
LOWonnx/helper.py859CODE
LOWonnx/helper.py1002CODE
LOWonnx/helper.py1240CODE
LOWonnx/external_data_helper.py223CODE
LOWonnx/external_data_helper.py60CODE
LOWonnx/tools/replace_constants.py199CODE
LOWonnx/backend/test/stat_coverage.py40CODE
LOWonnx/backend/test/stat_coverage.py152CODE
LOWonnx/backend/test/cmd_tools.py18CODE
LOWonnx/backend/test/runner/__init__.py123CODE
LOWonnx/backend/test/runner/__init__.py187CODE
LOWonnx/backend/test/runner/__init__.py264CODE
LOWonnx/backend/test/runner/__init__.py351CODE
LOWonnx/backend/test/runner/__init__.py527CODE
LOWonnx/backend/test/runner/__init__.py377CODE
LOWonnx/backend/test/loader/__init__.py25CODE
LOWonnx/backend/test/case/node/cast.py27CODE
LOWonnx/backend/test/case/node/cast.py321CODE
LOWonnx/backend/test/case/node/__init__.py34CODE
LOWonnx/backend/test/case/node/__init__.py261CODE
LOWonnx/backend/test/case/node/scatternd.py13CODE
LOWonnx/backend/test/case/node/scatterelements.py19CODE
LOWonnx/backend/test/case/node/castlike.py23CODE
LOWonnx/backend/test/report/coverage.py147CODE
LOWonnx/reference/op_run.py157CODE
LOWonnx/reference/op_run.py240CODE
LOWonnx/reference/op_run.py395CODE
LOWonnx/reference/shape_annotation_checker.py59CODE
LOWonnx/reference/reference_evaluator.py199CODE
LOWonnx/reference/reference_evaluator.py392CODE
LOWonnx/reference/reference_evaluator.py560CODE
LOWonnx/reference/ops/op_scatter_elements.py11CODE
LOWonnx/reference/ops/op_constant.py71CODE
LOWonnx/reference/ops/op_roi_align.py28CODE
LOWonnx/reference/ops/op_roi_align.py117CODE
LOWonnx/reference/ops/op_grid_sample.py294CODE
LOWonnx/reference/ops/op_sequence_insert.py41CODE
LOWonnx/reference/ops/op_conv.py56CODE
LOWonnx/reference/ops/_op_common_pool.py72CODE
LOWonnx/reference/ops/_op_common_pool.py130CODE
LOWonnx/reference/ops/op_affine_grid.py11CODE
LOWonnx/reference/ops/op_non_max_suppression.py176CODE
LOWonnx/reference/ops/op_pool_common.py171CODE
LOWonnx/reference/ops/op_deform_conv.py12CODE
LOWonnx/reference/ops/op_prelu.py12CODE
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Over-Commented Block93 hits · 90 pts
SeverityFileLineSnippetContext
LOW.lintrunner.toml1# Configuration for lintrunner https://github.com/suo/lintrunnerCOMMENT
LOW.lintrunner.toml21#COMMENT
LOWonnx/onnx_pb.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/onnx_pb.h21#define ONNX_EXPORT __attribute__((__visibility__("default")))COMMENT
LOWonnx/onnx_pb.h41//COMMENT
LOWonnx/checker.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/onnx-operators_pb.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/proto_utils.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/convert.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/convert.h21#include "onnx/version_converter/adapters/Attention_25_24.h"COMMENT
LOWonnx/version_converter/convert.h41#include "onnx/version_converter/adapters/no_previous_version.h"COMMENT
LOWonnx/version_converter/convert.h61#include "onnx/version_converter/adapters/softmax_12_13.h"COMMENT
LOWonnx/version_converter/BaseConverter.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/optional_ops.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/q_dq_21_20.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/type_restriction.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/adapter.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/reduce_log_sum_27_28.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOW…_converter/adapters/broadcast_backward_compatibility.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/range_27_26.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/upsample_9_8.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/scatter_16_15.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOW…nx/version_converter/adapters/extend_supported_types.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/version_converter/adapters/transformers.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/tools/__init__.py1# Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/frontend/__init__.py1# Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/bin/__init__.py1# Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/shape_inference/implementation.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/backend/__init__.py1# Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/backend/test/case/node/__init__.py241 in {"ai.onnx.training version", "ai.onnx.preview.training"}COMMENT
LOWonnx/backend/test/case/node/resize.py401 )COMMENT
LOWonnx/backend/test/case/node/resize.py541COMMENT
LOWonnx/backend/test/case/node/resize.py641 # 3.96160918 4.50364964 4.75976814]COMMENT
LOWonnx/backend/test/case/node/resize.py741 # [ 2.625 3.03125 3.625 4.125 4.625 5.21875 5.625COMMENT
LOWonnx/backend/test/case/node/mod.py261 # [5, 6, 0, 1, 2]],COMMENT
LOWonnx/backend/test/case/node/trilu.py141 outputs=["y"],COMMENT
LOWonnx/backend/test/case/node/trilu.py201 x = np.random.randint(10, size=(3, 1, 5)).astype(np.int64)COMMENT
LOWonnx/backend/test/case/node/trilu.py361COMMENT
LOWonnx/backend/test/case/node/trilu.py421 x = np.random.randint(10, size=(3, 1, 5)).astype(np.int64)COMMENT
LOWonnx/common/file_utils.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/path.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/ir.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/ir.h21#include <unordered_map>COMMENT
LOWonnx/common/ir.h641 // with an input which is topologically before the current node.COMMENT
LOWonnx/common/ir.h661 // Replace the input of 'this' at position 'i' withCOMMENT
LOWonnx/common/ir.h701 // and unattached: %5 = h(%1)COMMENT
LOWonnx/common/ir.h741 removeFromList();COMMENT
LOWonnx/common/ir.h761 //COMMENT
LOWonnx/common/ir.h961 // having corner cases where the list is empty.COMMENT
LOWonnx/common/ir.h1001 // (called from Attributes<Node> after set/removeAttribute/copyAttributes)COMMENT
LOWonnx/common/scoped_resource.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/scoped_resource.h21COMMENT
LOWonnx/common/graph_node_list.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/graph_node_list.h21// things, you will have to do some refactoring.COMMENT
LOWonnx/common/common.h21COMMENT
LOWonnx/common/safe_math.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/proto_util.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/tensor.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/array_ref.h1// Copyright (c) ONNX Project ContributorsCOMMENT
LOWonnx/common/array_ref.h21// removed a bunch of slice variants for simplicity...COMMENT
33 more matches not shown…
Decorative Section Separators12 hits · 36 pts
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MEDIUMonnx/backend/test/case/node/gridsample.py303 # ============================================================================COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py59 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py61 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py260 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py262 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py329 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py331 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py437 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py439 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py509 # ------------------------------------------------------------------COMMENT
MEDIUMonnx/backend/test/case/node/linear_attention.py511 # ------------------------------------------------------------------COMMENT
MEDIUMdocs/TestCoverage.md13246# ============================================================================COMMENT
Self-Referential Comments16 hits · 34 pts
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MEDIUMonnx/gen_proto.py214 # This file is generated by 'gen_proto.py'. DO NOT EDIT!COMMENT
MEDIUMonnx/numpy_helper.py102 # Create a 1D copyCOMMENT
MEDIUMonnx/numpy_helper.py146 # Create a 1D copyCOMMENT
MEDIUMonnx/backend/test/case/node/image_decoder.py16 # Create an empty RGB imageCOMMENT
MEDIUMonnx/backend/test/case/node/_image_decoder_data.py5# This file contains freeze NumPy array for ImageDecoder backend test's input/outputCOMMENT
MEDIUMonnx/reference/ops/op_pool_common.py184 """This function is used to calculate the pooling result of a padded tensorSTRING
MEDIUMtests/python/version_converter_test.py3047 # Create a model with external dataCOMMENT
MEDIUMtests/python/external_data_test.py987 # Create a target file and replace external data with a symlink to itCOMMENT
MEDIUMtests/python/external_data_test.py1037 # Create a model directory with a real subdir for savingCOMMENT
MEDIUMtests/python/external_data_test.py1083 # Create a hardlink to the external data fileCOMMENT
MEDIUMtests/python/shape_inference_test.py6611 # Create a simple If node where the 'then' subgraph adds to the current value, and the 'else' subgraphSTRING
MEDIUMtests/python/shape_inference_test.py6633 # Create a simple If node where the 'then' subgraph adds to the current value, and the 'else' subgraphSTRING
MEDIUMtests/python/shape_inference_test.py6653 # Create a simple If node where the 'then' subgraph adds to the current value, and the 'else' subgraphSTRING
MEDIUMtests/python/shape_inference_test.py8531 # Create a TensorProto with incorrect data type for `delta`.STRING
MEDIUMtests/python/shape_inference_test.py8557 # Create a TensorProto with empty raw data for `delta`.STRING
MEDIUMtests/python/training_tool_test.py69 # Create a model with both inference and training information.COMMENT
AI Slop Vocabulary10 hits · 30 pts
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MEDIUMpyproject.toml286 "PERF203", # try-except in loop is unavoidable in the version-converter harnessCODE
MEDIUMonnx/fuzz/make_seed_corpus.py187# ModelProto with no trailing bytes: the harness's raw path passes the fullSTRING
MEDIUMonnx/fuzz/make_seed_corpus.py334# harness's raw path: a 4-byte big-endian length prefix for m1's serializedCOMMENT
MEDIUMonnx/fuzz/make_seed_corpus.py337# The harness derives the io_map from m1's output names and m2's input names,COMMENT
MEDIUMonnx/fuzz/make_seed_corpus.py518 # serialized ModelProto with no trailing bytes, so the harness's raw pathCOMMENT
MEDIUMonnx/reference/ops/op_lp_pool.py24 # utilize AvgPool the same fashion Pytorch does. Note that there is a difference in computation.COMMENT
MEDIUM⚡.github/workflows/fuzz.yml8# (see google/oss-fuzz#15382) — it exists to catch harness regressionsCOMMENT
MEDIUM⚡.github/workflows/fuzz.yml9# (import errors, API drift, a harness file going missing) at PR timeCOMMENT
MEDIUM⚡.github/workflows/fuzz.yml14# for the harness/toggle-byte details.COMMENT
MEDIUM.github/workflows/fuzz.yml32 - cron: '0 6 * * *' # nightly: run each harness for longer than the PR smoke testCODE
AI Structural Patterns26 hits · 26 pts
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LOWonnx/compose.py300CODE
LOWonnx/compose.py446CODE
LOWonnx/compose.py569CODE
LOWonnx/reference/ops/op_attention.py123CODE
LOWonnx/reference/ops/op_attention.py405CODE
LOWonnx/reference/ops/op_roi_align.py12CODE
LOWonnx/reference/ops/op_linear_attention.py23CODE
LOWonnx/reference/ops/op_scan.py114CODE
LOWonnx/reference/ops/op_gru.py136CODE
LOWonnx/reference/ops/op_lstm.py147CODE
LOWonnx/reference/ops/op_lp_pool.py12CODE
LOWonnx/reference/ops/op_conv_integer.py13CODE
LOWonnx/reference/ops/op_rnn.py104CODE
LOWonnx/reference/ops/op_deform_conv.py149CODE
LOWonnx/reference/ops/op_attribute_has_value.py12CODE
LOWonnx/reference/ops/op_resize.py652CODE
LOWonnx/reference/ops/op_tfidf_vectorizer.py237CODE
LOWonnx/reference/ops/op_tfidf_vectorizer.py300CODE
LOWonnx/reference/ops/op_conv_transpose.py13CODE
LOW…/reference/ops/aionnxml/op_tree_ensemble_classifier.py19CODE
LOWonnx/reference/ops/aionnxml/op_svm_classifier.py223CODE
LOW…x/reference/ops/aionnxml/op_tree_ensemble_regressor.py15CODE
LOWonnx/reference/ops/aionnxml/op_svm_regressor.py13CODE
LOWonnx/reference/ops/aionnxml/op_label_encoder.py12CODE
LOWtests/python/compose_test.py740CODE
LOW…on/version_converter/automatic_conversion_test_base.py51CODE
Docstring Block Structure4 hits · 20 pts
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HIGHonnx/serialization.py64Get a serializer for a format. Args: fmt: The format to get a serializer for. Returns: STRING
HIGHonnx/reference/op_run.py396Calls method ``_run``, catches exceptions, displays a longer error message. Args: *args: inSTRING
HIGHonnx/reference/reference_evaluator.py569Executes the onnx model. Args: output_names: requested outputs by names, None for all fSTRING
HIGHonnx/reference/ops/op_resize.py135Return the n nearest indexes to x among `[0, limit)`, prefer the indexes smaller than x. As a result, the ratio STRING
Excessive Try-Catch Wrapping17 hits · 19 pts
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LOWonnx/backend/test/runner/__init__.py49 except Exception:CODE
LOWonnx/backend/test/runner/__init__.py259 except Exception as e:CODE
LOWonnx/fuzz/fuzz_version_converter.py40 except Exception:CODE
LOWonnx/fuzz/fuzz_version_converter.py46 except Exception:CODE
MEDIUMonnx/fuzz/fuzz_version_converter.py37def TestOneInput(data):CODE
LOWonnx/fuzz/fuzz_compose.py133 except Exception:CODE
LOWonnx/fuzz/fuzz_parser.py17 except Exception:CODE
MEDIUMonnx/fuzz/fuzz_parser.py13def TestOneInput(data):CODE
LOWonnx/fuzz/fuzz_model_loader.py20 except Exception:CODE
MEDIUMonnx/fuzz/fuzz_model_loader.py13def TestOneInput(data):CODE
LOWonnx/fuzz/fuzz_shape_inference.py175 except Exception:CODE
LOWonnx/fuzz/fuzz_checker.py16 except Exception:CODE
MEDIUMonnx/fuzz/fuzz_checker.py13def TestOneInput(data):CODE
LOW⚡tests/python/reference_evaluator_test.py451 except Exception as e:STRING
LOWdocs/docsgen/source/intro/python.md1168 except Exception as e:STRING
LOWdocs/docsgen/source/intro/python.md1585 except Exception as e:STRING
LOWdocs/docsgen/source/intro/python.md1592 except Exception as e:STRING
Modern Structural Boilerplate18 hits · 18 pts
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LOWonnx/version.py24__all__ = ["version", "git_version"]CODE
LOWonnx/__init__.py7__all__ = [CODE
LOWonnx/helper.py361def set_model_props(model: ModelProto, dict_value: dict[str, str]) -> None:CODE
LOWonnx/serialization.py9__all__ = [CODE
LOWonnx/checker.py8__all__ = [CODE
LOWonnx/tools/update_model_dims.py62 def update_dim(tensor: ValueInfoProto, dim: Any, j: int, name: str) -> None:CODE
LOWonnx/backend/test/__init__.py6__all__ = ["BackendTest"]CODE
LOWonnx/reference/__init__.py6__all__ = ["ReferenceEvaluator"]CODE
LOWonnx/reference/ops/__init__.py6__all__ = ["load_op"]CODE
LOWonnx/reference/ops/_op_list.py15__all__ = [CODE
LOWonnx/reference/ops/experimental/__init__.py6__all__ = ["load_op"]CODE
LOWonnx/reference/ops/aionnx_preview_training/__init__.py6__all__ = ["load_op", "OpRunTraining"]CODE
LOWonnx/reference/ops/aionnx_preview_training/_op_list.py6__all__ = [CODE
LOWonnx/reference/ops/aionnx_preview/__init__.py6__all__ = ["load_op"]CODE
LOWonnx/reference/ops/aionnx_preview/_op_list.py6__all__ = [CODE
LOWonnx/reference/ops/aionnxml/__init__.py4__all__ = ["load_op"]CODE
LOWonnx/reference/ops/aionnxml/_op_list.py8__all__ = [CODE
LOWonnx/defs/__init__.py6__all__ = [CODE
Structural Annotation Overuse8 hits · 15 pts
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LOW⚡onnx/reference/ops/op_causal_conv_with_state.py41 # Step 1: build the left-padded input (B, C, L + k - 1).COMMENT
LOW⚡onnx/reference/ops/op_causal_conv_with_state.py48 # Step 2: depthwise Conv1d (group = channels, valid padding).COMMENT
LOW⚡onnx/reference/ops/op_causal_conv_with_state.py61 # Step 3: optional fused SiLU/Swish activation.COMMENT
LOW⚡onnx/reference/ops/op_causal_conv_with_state.py68 # Step 4: present_state = last (k - 1) positions of the padded input.COMMENT
LOWdocs/AddNewOp.md43### Step 1: Proposing a new operator/functionCOMMENT
LOWdocs/AddNewOp.md61### Step 2: Submit PRCOMMENT
LOWdocs/AddNewOp.md113### Step 3: PR Review by Operators SIGCOMMENT
LOWdocs/AddNewOp.md121### Step 4: ONNX releaseCOMMENT
Verbosity Indicators4 hits · 9 pts
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LOW⚡onnx/reference/ops/op_causal_conv_with_state.py41 # Step 1: build the left-padded input (B, C, L + k - 1).COMMENT
LOW⚡onnx/reference/ops/op_causal_conv_with_state.py48 # Step 2: depthwise Conv1d (group = channels, valid padding).COMMENT
LOW⚡onnx/reference/ops/op_causal_conv_with_state.py61 # Step 3: optional fused SiLU/Swish activation.COMMENT
LOW⚡onnx/reference/ops/op_causal_conv_with_state.py68 # Step 4: present_state = last (k - 1) positions of the padded input.COMMENT
Redundant / Tautological Comments5 hits · 8 pts
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LOWonnx/reference/ops/op_string_split.py30 # Add padding to lists that are shorter than the maximum lengthCOMMENT
LOWtests/python/training_tool_test.py71 # Check if the inference-only part is correct.COMMENT
LOW⚡tests/python/basic_test.py208 # Check if the version is correct.COMMENT
LOW⚡tests/python/basic_test.py212 # Check if the __repr__ methods work without errorCOMMENT
LOWtests/python/compose_test.py482 # Check if all inputs are prefixed even if input is not connected to node. e.g., 'unused_input'.STRING
Cross-Language Confusion1 hit · 8 pts
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HIGHonnx/reference/op_run.py277 # default value is undefined, it depends on the inputsCOMMENT
AI Response Leakage1 hit · 8 pts
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HIGHonnx/reference/ops/op_grid_sample.py327 # In this implementation, we took the latter approach.COMMENT
Modern AI Meta-Vocabulary1 hit · 2 pts
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MEDIUMpyproject.toml284 "PLR2004", # Magic numbers are fine in low-level fuzz scaffoldingCODE
Fake / Example Data1 hit · 1 pts
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LOWdocs/docsgen/source/_static/diff2html-ui-slim.min.js1!function(e,n){if("object"==typeof exports&&"object"==typeof module)module.exports=n();else if("function"==typeof defineCODE
Overly Generic Function Names1 hit · 0 pts
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LOWtests/python/external_data_test.py865 def test_function(self) -> None:CODE