Graph Neural Network Library for PyTorch
This report summarizes scanner evidence for pyg-team/pytorch_geometric, a Python project with 24,112 GitHub stars. SynthScan examined 196,317 lines of code across 1412 source files, recording 2238 pattern matches distributed across 23 syntactic categories. The legacy adjusted pattern signal is 12.4 (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.
Use each vector to guide manual verification of the underlying findings.
Can maintainers explain intent, assumptions, and trade-offs? 1103 finding(s).
Are imports declared and package/API names verified? 901 finding(s).
Are wrappers, guards, and repeated structures necessary? 973 finding(s).
Which changes need focused human review? 2238 finding(s).
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.
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.
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.
The scanner identified 2238 distinct pattern matches across 23 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.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | benchmark/citation/__init__.py | 1 | CODE | |
| LOW | benchmark/citation/__init__.py | 2 | CODE | |
| LOW | benchmark/citation/__init__.py | 2 | CODE | |
| LOW | benchmark/runtime/__init__.py | 1 | CODE | |
| LOW | benchmark/utils/__init__.py | 1 | CODE | |
| LOW | benchmark/utils/__init__.py | 2 | CODE | |
| LOW | benchmark/utils/__init__.py | 2 | CODE | |
| LOW | benchmark/utils/__init__.py | 3 | CODE | |
| LOW | benchmark/utils/__init__.py | 4 | CODE | |
| LOW | benchmark/utils/__init__.py | 5 | CODE | |
| LOW | benchmark/utils/__init__.py | 5 | CODE | |
| LOW | benchmark/utils/__init__.py | 6 | CODE | |
| LOW | benchmark/utils/utils.py | 19 | CODE | |
| LOW | benchmark/multi_gpu/training/training_benchmark_xpu.py | 5 | CODE | |
| LOW | benchmark/points/__init__.py | 1 | CODE | |
| LOW | benchmark/points/__init__.py | 2 | CODE | |
| LOW | benchmark/kernel/__init__.py | 1 | CODE | |
| LOW | benchmark/kernel/__init__.py | 2 | CODE | |
| LOW | test/testing/test_decorators.py | 7 | CODE | |
| LOW | test/testing/test_decorators.py | 13 | CODE | |
| LOW | test/testing/test_decorators.py | 19 | CODE | |
| LOW | graphgym/main.py | 4 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 1 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 2 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 3 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 4 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 5 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 6 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 7 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 8 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 9 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 10 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 11 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 12 | CODE | |
| LOW | graphgym/custom_graphgym/__init__.py | 13 | CODE | |
| LOW | graphgym/custom_graphgym/network/example.py | 5 | CODE | |
| LOW | torch_geometric/experimental.py | 9 | CODE | |
| LOW | torch_geometric/__init__.py | 6 | CODE | |
| LOW | torch_geometric/__init__.py | 6 | CODE | |
| LOW | torch_geometric/__init__.py | 7 | CODE | |
| LOW | torch_geometric/__init__.py | 7 | CODE | |
| LOW | torch_geometric/__init__.py | 11 | CODE | |
| LOW | torch_geometric/__init__.py | 12 | CODE | |
| LOW | torch_geometric/__init__.py | 12 | CODE | |
| LOW | torch_geometric/__init__.py | 13 | CODE | |
| LOW | torch_geometric/__init__.py | 13 | CODE | |
| LOW | torch_geometric/__init__.py | 13 | CODE | |
| LOW | torch_geometric/__init__.py | 14 | CODE | |
| LOW | torch_geometric/__init__.py | 15 | CODE | |
| LOW | torch_geometric/__init__.py | 15 | CODE | |
| LOW | torch_geometric/__init__.py | 15 | CODE | |
| LOW | torch_geometric/__init__.py | 27 | CODE | |
| LOW | torch_geometric/__init__.py | 27 | CODE | |
| LOW | torch_geometric/__init__.py | 27 | CODE | |
| LOW | torch_geometric/config_store.py | 22 | CODE | |
| LOW | torch_geometric/typing.py | 166 | CODE | |
| LOW | torch_geometric/typing.py | 311 | CODE | |
| LOW | torch_geometric/visualization/__init__.py | 3 | CODE | |
| LOW | torch_geometric/visualization/__init__.py | 3 | CODE | |
| LOW | torch_geometric/visualization/__init__.py | 4 | CODE | |
| 825 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | benchmark/utils/utils.py | 39 | def get_dataset_with_transformation(name, root, use_sparse_tensor=False, | CODE |
| LOW | benchmark/kernel/train_eval.py | 20 | def cross_validation_with_val_set(dataset, model, folds, epochs, batch_size, | CODE |
| LOW | test/test_warnings.py | 15 | def test_no_warn_if_compiling(_): | CODE |
| LOW | test/test_onnx.py | 32 | def test_safe_onnx_export_ci_resilient() -> None: | CODE |
| LOW | test/test_onnx.py | 62 | def test_safe_onnx_export_success() -> None: | CODE |
| LOW | test/test_onnx.py | 107 | def test_safe_onnx_export_with_skip_on_error() -> None: | CODE |
| LOW | test/test_onnx.py | 134 | def test_serde_error_patterns() -> None: | CODE |
| LOW | test/test_onnx.py | 173 | def test_non_serde_error_reraise() -> None: | CODE |
| LOW | test/test_onnx.py | 303 | def test_pytest_environment_detection() -> None: | CODE |
| LOW | test/test_config_mixin.py | 116 | def test_config_mixin_compound() -> None: | CODE |
| LOW | test/test_edge_index.py | 1375 | def test_compile_create_edge_index(): | CODE |
| LOW | test/test_inspector.py | 102 | def test_get_params_from_method_call() -> None: | CODE |
| LOW | test/visualization/test_graph_visualization.py | 12 | def test_visualize_graph_via_graphviz(tmp_path, backend): | CODE |
| LOW | test/visualization/test_graph_visualization.py | 26 | def test_visualize_graph_via_graphviz_with_node_labels(tmp_path, backend): | CODE |
| LOW | test/visualization/test_graph_visualization.py | 41 | def test_visualize_graph_via_networkx(tmp_path, backend): | CODE |
| LOW | test/llm/conftest.py | 8 | def pytest_collection_modifyitems(items): | CODE |
| LOW | test/llm/test_rag_loader.py | 97 | def test_initialization_basic(self): | CODE |
| LOW | test/llm/test_rag_loader.py | 108 | def test_initialization_with_all_params(self): | CODE |
| LOW | test/llm/test_rag_loader.py | 140 | def test_basic_query_without_vector_retriever(self): | CODE |
| LOW | test/llm/test_rag_loader.py | 156 | def test_query_with_vector_retriever(self): | CODE |
| LOW | test/llm/test_rag_loader.py | 177 | def test_query_with_subgraph_filter(self): | CODE |
| LOW | test/llm/test_rag_loader.py | 204 | def test_rag_loader_integration(tmp_path): | CODE |
| LOW | test/llm/test_large_graph_indexer.py | 130 | def _sorted_tensors_are_close(tensor1, tensor2): | CODE |
| LOW | test/llm/test_txt2qa.py | 67 | def test_route_after_validation_continue(self): | CODE |
| LOW | test/llm/test_txt2qa.py | 73 | def test_route_after_validation_feedback(self): | CODE |
| LOW | test/llm/test_txt2qa.py | 95 | def test_generate_single_query_nim(tmp_path): | CODE |
| LOW | test/llm/utils/test_rag_backend_utils.py | 101 | def create_mock_graph_and_triples(): | CODE |
| LOW | test/llm/utils/test_rag_backend_utils.py | 121 | def test_apply_retrieval_via_pcst_isolated_node(): | CODE |
| LOW | test/llm/utils/test_rag_backend_utils.py | 171 | def test_create_graph_basic_functionality(self): | CODE |
| LOW | test/llm/utils/test_rag_backend_utils.py | 192 | def test_create_graph_empty_triples(self): | CODE |
| LOW | test/llm/utils/test_rag_backend_utils.py | 219 | def test_create_backend_data_load(self): | CODE |
| LOW | test/llm/utils/test_rag_feature_store.py | 43 | def test_retrieve_seed_nodes_single_query(self): | CODE |
| LOW | test/llm/utils/test_rag_feature_store.py | 78 | def test_retrieve_seed_nodes_multiple_queries(self): | CODE |
| LOW | test/llm/utils/test_rag_feature_store.py | 112 | def test_load_subgraph_valid_sample(self, induced): | CODE |
| LOW | test/llm/utils/test_rag_graph_store.py | 18 | def test_sample_subgraph_with_valid_tensor_input(): | CODE |
| LOW⚡ | test/llm/models/test_glem.py | 10 | def test_deal_nan_tensor_replaces_nans(): | CODE |
| LOW⚡ | test/llm/models/test_glem.py | 20 | def test_deal_nan_non_tensor_passthrough(): | CODE |
| LOW⚡ | test/llm/models/test_glem.py | 26 | def test_deal_nan_tensor_dtypes(dtype): | CODE |
| LOW | test/llm/models/test_glem.py | 46 | def test_deal_nan_is_non_mutating(): | CODE |
| LOW | test/llm/models/test_glem.py | 76 | def test_glem_bert_tiny_branch(monkeypatch): | CODE |
| LOW | test/llm/models/test_glem.py | 101 | def test_glem_auto_model_branch(monkeypatch): | CODE |
| LOW | test/llm/models/test_llm.py | 127 | def test_llm_variable_lengths(dummy_llm): | CODE |
| LOW | test/llm/models/test_sentence_transformer.py | 17 | def test_sentence_transformer(batch_size, pooling_strategy, device, verbose): | CODE |
| LOW | test/llm/models/test_g_retriever.py | 63 | def test_g_retriever_many_tokens() -> None: | CODE |
| LOW | test/llm/models/test_g_retriever.py | 160 | def test_gretriever_prefix_embedding_injection(batch_size): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 22 | def test_parse_n_check_triples_formats(): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 29 | def test_chunk_text_simple_sentence(): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 44 | def test_local_lm_integration(monkeypatch): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 83 | def test_merge_triples_deterministically_basic(): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 101 | def test_merge_triples_deterministically_unicode_and_nonstring(): | CODE |
| LOW⚡ | test/llm/models/test_txt2kg.py | 119 | def test_merge_triples_deterministically_empty(): | CODE |
| LOW⚡ | test/llm/models/test_txt2kg.py | 127 | def test_merge_triples_deterministically_singleton(): | CODE |
| LOW⚡ | test/llm/models/test_txt2kg.py | 135 | def test_chunk_to_triples_str_cloud(monkeypatch): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 194 | def test_extract_relevant_triples_cloud(monkeypatch): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 205 | def test_multiproc_helper_success(monkeypatch): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 237 | def test_multiproc_helper_retry(monkeypatch): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 300 | def test_add_doc_empty_text_cpu(kg_cpu): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 316 | def test_add_doc_nonempty_text_placeholder(kg_cpu, monkeypatch): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 332 | def test_is_retryable_exception_status_codes(): | CODE |
| LOW | test/llm/models/test_txt2kg.py | 341 | def test_is_retryable_exception_network_errors(): | CODE |
| 598 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | benchmark/citation/train_eval.py | 64 | except ImportError: | CODE |
| HIGH | benchmark/citation/train_eval.py | 101 | except ImportError: | CODE |
| HIGH | benchmark/kernel/train_eval.py | 50 | except ImportError: | CODE |
| HIGH | test/test_onnx.py | 58 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 103 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 129 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 192 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 228 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 268 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 298 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 373 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 407 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 100 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 169 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 265 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 330 | except (PermissionError, OSError): | CODE |
| HIGH | test/test_onnx.py | 166 | except (PermissionError, OSError): | CODE |
| HIGH | test/data/test_database.py | 40 | except NotImplementedError: | CODE |
| HIGH | test/data/test_database.py | 49 | except NotImplementedError: | CODE |
| HIGH | torch_geometric/config_mixin.py | 89 | except ImportError: | CODE |
| HIGH | torch_geometric/_onnx.py | 164 | except Exception: | CODE |
| HIGH | torch_geometric/_onnx.py | 186 | except Exception: | CODE |
| HIGH | torch_geometric/_onnx.py | 130 | except Exception: | CODE |
| HIGH | torch_geometric/llm/models/qa_gen.py | 1403 | except json.JSONDecodeError: | CODE |
| HIGH | torch_geometric/llm/models/qa_gen.py | 1492 | except json.JSONDecodeError: | CODE |
| HIGH | torch_geometric/llm/models/qa_gen.py | 1501 | except Exception: | CODE |
| HIGH | torch_geometric/llm/models/qa_gen.py | 635 | except Exception: | CODE |
| HIGH | torch_geometric/llm/models/qa_gen.py | 1477 | except json.JSONDecodeError: | CODE |
| HIGH | torch_geometric/llm/models/qa_gen.py | 1514 | except json.JSONDecodeError: | CODE |
| HIGH | torch_geometric/llm/models/txt2kg.py | 400 | except Exception: | CODE |
| HIGH | torch_geometric/llm/models/llm_judge.py | 144 | except: # noqa | CODE |
| HIGH | torch_geometric/llm/models/llm_judge.py | 155 | except: # noqa | CODE |
| HIGH | torch_geometric/nn/fx.py | 180 | except RuntimeError: | CODE |
| HIGH | torch_geometric/nn/conv/cugraph/gat_conv.py | 17 | except ImportError: | CODE |
| HIGH | torch_geometric/nn/conv/cugraph/sage_conv.py | 18 | except ImportError: | CODE |
| HIGH | torch_geometric/nn/conv/cugraph/base.py | 22 | except ImportError: | CODE |
| HIGH | torch_geometric/nn/conv/cugraph/rgcn_conv.py | 19 | except ImportError: | CODE |
| HIGH | torch_geometric/distributed/dist_neighbor_sampler.py | 392 | except Exception: | CODE |
| HIGH | torch_geometric/distributed/local_feature_store.py | 159 | except KeyError: | CODE |
| HIGH | torch_geometric/datasets/motif_generator/custom.py | 28 | except ImportError: | CODE |
| HIGH | torch_geometric/io/fs.py | 181 | except Exception: # FIXME | CODE |
| HIGH | torch_geometric/utils/convert.py | 279 | except Exception: | CODE |
| HIGH | torch_geometric/profile/utils.py | 80 | except Exception: | CODE |
| HIGH | torch_geometric/profile/utils.py | 99 | except Exception: | CODE |
| HIGH | torch_geometric/loader/cluster.py | 120 | except (AttributeError, RuntimeError): | CODE |
| HIGH | torch_geometric/data/storage.py | 899 | except Exception: | CODE |
| HIGH | examples/llm/txt2qa.py | 26 | except RuntimeError: | CODE |
| HIGH | examples/multi_gpu/papers100m_gcn_multinode.py | 29 | except Exception: | CODE |
| HIGH | examples/multi_gpu/papers100m_gcn.py | 23 | except Exception: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | benchmark/citation/train_eval.py | 43 | CODE | |
| LOW | benchmark/citation/train_eval.py | 121 | CODE | |
| LOW | benchmark/training/training_benchmark.py | 98 | CODE | |
| LOW | benchmark/loader/neighbor_loader.py | 16 | CODE | |
| LOW | benchmark/points/train_eval.py | 58 | CODE | |
| LOW | benchmark/inference/inference_benchmark.py | 44 | CODE | |
| LOW | benchmark/kernel/main_performance.py | 75 | CODE | |
| LOW | benchmark/kernel/main_performance.py | 117 | CODE | |
| LOW | benchmark/kernel/train_eval.py | 20 | CODE | |
| LOW | test/test_onnx.py | 32 | CODE | |
| LOW | test/test_onnx.py | 62 | CODE | |
| LOW | test/test_onnx.py | 107 | CODE | |
| LOW | test/test_onnx.py | 134 | CODE | |
| LOW | test/test_onnx.py | 173 | CODE | |
| LOW | test/test_onnx.py | 197 | CODE | |
| LOW | test/test_onnx.py | 233 | CODE | |
| LOW | test/test_onnx.py | 272 | CODE | |
| LOW | test/test_onnx.py | 303 | CODE | |
| LOW | test/test_onnx.py | 335 | CODE | |
| LOW | test/test_onnx.py | 385 | CODE | |
| LOW | test/explain/conftest.py | 106 | CODE | |
| LOW | test/explain/conftest.py | 138 | CODE | |
| LOW | test/explain/conftest.py | 86 | CODE | |
| LOW | test/explain/conftest.py | 107 | CODE | |
| LOW | test/explain/conftest.py | 139 | CODE | |
| LOW | test/explain/conftest.py | 289 | CODE | |
| LOW | test/explain/test_hetero_explanation.py | 13 | CODE | |
| LOW | test/explain/algorithm/test_captum.py | 65 | CODE | |
| LOW | test/explain/algorithm/test_attention_explainer.py | 69 | CODE | |
| LOW | test/explain/algorithm/test_attention_explainer.py | 145 | CODE | |
| LOW | test/explain/algorithm/test_graphmask_explainer.py | 28 | CODE | |
| LOW | test/explain/algorithm/test_gnn_explainer.py | 38 | CODE | |
| LOW | test/explain/algorithm/test_captum_hetero.py | 35 | CODE | |
| LOW | test/explain/algorithm/test_captum_explainer.py | 54 | CODE | |
| LOW | test/distributed/test_dist_neighbor_loader.py | 82 | CODE | |
| LOW | test/utils/conftest.py | 35 | CODE | |
| LOW | test/sampler/test_sampler_neighbor_sampler.py | 63 | CODE | |
| LOW | graphgym/configs_gen.py | 90 | CODE | |
| LOW | graphgym/configs_gen.py | 124 | CODE | |
| LOW | graphgym/configs_gen.py | 166 | CODE | |
| LOW | torch_geometric/experimental.py | 95 | CODE | |
| LOW | torch_geometric/experimental.py | 100 | CODE | |
| LOW | torch_geometric/experimental.py | 115 | CODE | |
| LOW | torch_geometric/index.py | 696 | CODE | |
| LOW | torch_geometric/edge_index.py | 1477 | CODE | |
| LOW | torch_geometric/edge_index.py | 1849 | CODE | |
| LOW | torch_geometric/inspector.py | 514 | CODE | |
| LOW | torch_geometric/inspector.py | 207 | CODE | |
| LOW | torch_geometric/inspector.py | 336 | CODE | |
| LOW | torch_geometric/config_store.py | 196 | CODE | |
| LOW | torch_geometric/config_store.py | 30 | CODE | |
| LOW | torch_geometric/config_store.py | 118 | CODE | |
| LOW | torch_geometric/config_store.py | 35 | CODE | |
| LOW | torch_geometric/config_store.py | 123 | CODE | |
| LOW | torch_geometric/hash_tensor.py | 39 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 1384 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 1715 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 2239 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 2350 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 2414 | CODE | |
| 185 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | torch_geometric/nn/attention/performer.py | 0 | forward pass. args: x (torch.tensor): node feature tensor :math:`\mathbf{x} \in \mathbb{r}^{b \times n \times f}`, with | STRING |
| HIGH | torch_geometric/nn/attention/polynormer.py | 0 | forward pass. args: x (torch.tensor): node feature tensor :math:`\mathbf{x} \in \mathbb{r}^{b \times n \times f}`, with | STRING |
| HIGH | torch_geometric/nn/attention/sgformer.py | 0 | forward pass. args: x (torch.tensor): node feature tensor :math:`\mathbf{x} \in \mathbb{r}^{b \times n \times f}`, with | STRING |
| HIGH | torch_geometric/nn/dense/dense_gat_conv.py | 0 | forward pass. args: x (torch.tensor): node feature tensor :math:`\mathbf{x} \in \mathbb{r}^{b \times n \times f}`, with | STRING |
| HIGH | torch_geometric/nn/dense/dense_gcn_conv.py | 0 | forward pass. args: x (torch.tensor): node feature tensor :math:`\mathbf{x} \in \mathbb{r}^{b \times n \times f}`, with | STRING |
| HIGH | torch_geometric/nn/dense/dense_gin_conv.py | 0 | forward pass. args: x (torch.tensor): node feature tensor :math:`\mathbf{x} \in \mathbb{r}^{b \times n \times f}`, with | STRING |
| HIGH | torch_geometric/nn/models/deep_graph_infomax.py | 0 | evaluates latent space quality via a logistic regression downstream task. | STRING |
| HIGH | torch_geometric/nn/models/node2vec.py | 0 | evaluates latent space quality via a logistic regression downstream task. | STRING |
| HIGH | torch_geometric/nn/models/metapath2vec.py | 0 | evaluates latent space quality via a logistic regression downstream task. | STRING |
| HIGH | torch_geometric/nn/conv/gatv2_conv.py | 0 | runs the forward pass of the module. args: x (torch.tensor or (torch.tensor, torch.tensor)): the input node features. ed | STRING |
| HIGH | torch_geometric/nn/conv/transformer_conv.py | 0 | runs the forward pass of the module. args: x (torch.tensor or (torch.tensor, torch.tensor)): the input node features. ed | STRING |
| HIGH | torch_geometric/nn/conv/fa_conv.py | 0 | runs the forward pass of the module. args: x (torch.tensor or (torch.tensor, torch.tensor)): the input node features. ed | STRING |
| HIGH | torch_geometric/nn/conv/gat_conv.py | 0 | runs the forward pass of the module. args: x (torch.tensor or (torch.tensor, torch.tensor)): the input node features. ed | STRING |
| HIGH | torch_geometric/nn/norm/pair_norm.py | 0 | forward pass. args: x (torch.tensor): the source tensor. batch (torch.tensor, optional): the batch vector :math:`\mathbf | STRING |
| HIGH | torch_geometric/nn/norm/graph_size_norm.py | 0 | forward pass. args: x (torch.tensor): the source tensor. batch (torch.tensor, optional): the batch vector :math:`\mathbf | STRING |
| HIGH | torch_geometric/nn/norm/instance_norm.py | 0 | forward pass. args: x (torch.tensor): the source tensor. batch (torch.tensor, optional): the batch vector :math:`\mathbf | STRING |
| HIGH | torch_geometric/nn/norm/graph_norm.py | 0 | forward pass. args: x (torch.tensor): the source tensor. batch (torch.tensor, optional): the batch vector :math:`\mathbf | STRING |
| HIGH | torch_geometric/nn/norm/layer_norm.py | 0 | forward pass. args: x (torch.tensor): the source tensor. batch (torch.tensor, optional): the batch vector :math:`\mathbf | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | test/llm/utils/test_rag_feature_store.py | 116 | # Create a mock SamplerOutput | COMMENT |
| MEDIUM⚡ | test/llm/models/test_glem.py | 27 | # Create a tensor with one NaN value | COMMENT |
| MEDIUM | test/explain/conftest.py | 268 | # Create a HeteroConv model | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 44 | # Create a single BaseGNN that uses all three attention mechanisms | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 105 | # Create a dictionary of attention-based convolutions for each edge | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 122 | # Create the HeteroConv layer | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 251 | # Create the hetero attention model | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 254 | # Create the explainer | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 290 | # Create the hetero conv attention model | COMMENT |
| MEDIUM | test/explain/algorithm/test_attention_explainer.py | 293 | # Create the explainer | COMMENT |
| MEDIUM | test/utils/test_negative_sampling.py | 33 | # Create a fully-connected graph: | COMMENT |
| MEDIUM | torch_geometric/llm/utils/vectorrag.py | 121 | # Create a new DocumentRetriever with the loaded data | COMMENT |
| MEDIUM | torch_geometric/nn/to_hetero_with_bases_transformer.py | 537 | # This method is used to split the output tensors into individual type-wise | STRING |
| MEDIUM | torch_geometric/nn/aggr/base.py | 47 | # Define the boundary indices for three sets: | COMMENT |
| MEDIUM | torch_geometric/datasets/web_qsp_dataset.py | 124 | # Create an iterator for each element's graph in the current split | STRING |
| MEDIUM | torch_geometric/datasets/ged_dataset.py | 208 | # Create a one-hot encoded feature matrix denoting the atom | STRING |
| MEDIUM | torch_geometric/data/remote_backend_utils.py | 1 | # This file defines a set of utilities for remote backends (backends that are | COMMENT |
| MEDIUM | torch_geometric/data/in_memory_dataset.py | 232 | # Create the on-disk dataset ========================================== | STRING |
| MEDIUM | torch_geometric/data/database.py | 307 | # Create the table (if it does not exist) by mapping the Python schema | STRING |
| MEDIUM | torch_geometric/data/hetero_data.py | 63 | # Create an edge type "(author, writes, paper)" and building the | COMMENT |
| MEDIUM | torch_geometric/data/lightning/datamodule.py | 127 | # Define a new `NeighborSampler` to be re-used across data loaders: | COMMENT |
| MEDIUM | examples/llm/relbench_gretriever.py | 88 | # Define the projector for heterogeneous node features | COMMENT |
| MEDIUM | examples/llm/txt2qa.py | 158 | # Create the graph | COMMENT |
| MEDIUM | examples/llm/g_retriever.py | 62 | # Create a dictionary mapping parameter names to their requires_grad status | COMMENT |
| MEDIUM | examples/llm/txt2qa_config/text_config_nim.yaml | 2 | # This file contains all the settings for the QA generation workflow | COMMENT |
| MEDIUM | examples/llm/txt2qa_config/text_config_vllm.yaml | 2 | # This file contains all the settings for the QA generation workflow | COMMENT |
| MEDIUM | examples/distributed/kuzu/papers_100M/train.py | 32 | # The below code sets up the remote backend of Kùzu for PyG. | COMMENT |
| MEDIUM | …d/graphlearn_for_pytorch/dist_train_sage_supervised.py | 126 | # Define the model and optimizer. | COMMENT |
| MEDIUM | examples/quiver/multi_gpu_quiver.py | 131 | # The below code enable Quiver for PyG. | COMMENT |
| MEDIUM⚡ | examples/quiver/single_gpu_quiver.py | 28 | # The below code enable Quiver for PyG. | COMMENT |
| MEDIUM | examples/pytorch_ignite/gin.py | 127 | # Create a tensorboard logger to write logs: | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | benchmark/runtime/dgl/rgcn.py | 66 | CODE | |
| LOW | benchmark/runtime/dgl/rgcn.py | 135 | CODE | |
| LOW | test/test_edge_index.py | 1307 | CODE | |
| LOW | test/test_edge_index.py | 1332 | CODE | |
| LOW | test/test_edge_index.py | 1350 | CODE | |
| LOW | torch_geometric/typing.py | 177 | CODE | |
| LOW | torch_geometric/visualization/graph.py | 155 | CODE | |
| LOW | torch_geometric/llm/utils/backend_utils.py | 319 | CODE | |
| LOW | torch_geometric/llm/models/sentence_transformer.py | 169 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 2414 | CODE | |
| LOW | torch_geometric/llm/models/qa_gen.py | 168 | CODE | |
| LOW | torch_geometric/llm/models/glem.py | 46 | CODE | |
| LOW | torch_geometric/llm/models/protein_mpnn.py | 188 | CODE | |
| LOW | …rch_geometric/explain/algorithm/graphmask_explainer.py | 83 | CODE | |
| LOW | …rch_geometric/explain/algorithm/graphmask_explainer.py | 140 | CODE | |
| LOW | torch_geometric/nn/attention/performer.py | 50 | CODE | |
| LOW | torch_geometric/nn/attention/performer.py | 63 | CODE | |
| LOW | torch_geometric/nn/attention/performer.py | 95 | CODE | |
| LOW | torch_geometric/nn/attention/performer.py | 173 | CODE | |
| LOW | torch_geometric/nn/attention/qformer.py | 66 | CODE | |
| LOW | torch_geometric/nn/dense/mincut_pool.py | 117 | CODE | |
| LOW | torch_geometric/nn/models/lpformer.py | 720 | CODE | |
| LOW | torch_geometric/nn/models/graph_mixer.py | 133 | CODE | |
| LOW | torch_geometric/nn/models/gpse.py | 494 | CODE | |
| LOW | torch_geometric/nn/models/visnet.py | 753 | CODE | |
| LOW | torch_geometric/nn/models/visnet.py | 1079 | CODE | |
| LOW | torch_geometric/nn/models/mlp.py | 78 | CODE | |
| LOW | torch_geometric/nn/models/dimenet.py | 126 | CODE | |
| LOW | torch_geometric/nn/models/dimenet.py | 501 | CODE | |
| LOW | torch_geometric/nn/models/dimenet.py | 768 | CODE | |
| LOW | torch_geometric/nn/models/basic_gnn.py | 70 | CODE | |
| LOW | torch_geometric/nn/models/polynormer.py | 45 | CODE | |
| LOW | torch_geometric/nn/models/attentive_fp.py | 50 | CODE | |
| LOW | torch_geometric/nn/models/schnet.py | 93 | CODE | |
| LOW | torch_geometric/nn/conv/gatv2_conv.py | 133 | CODE | |
| LOW | torch_geometric/nn/conv/general_conv.py | 69 | CODE | |
| LOW | torch_geometric/nn/conv/x_conv.py | 157 | CODE | |
| LOW | torch_geometric/nn/conv/point_transformer_conv.py | 138 | CODE | |
| LOW | torch_geometric/nn/conv/supergat_conv.py | 128 | CODE | |
| LOW | torch_geometric/nn/conv/cg_conv.py | 91 | CODE | |
| LOW | torch_geometric/nn/conv/gat_conv.py | 130 | CODE | |
| LOW | torch_geometric/nn/conv/dna_conv.py | 66 | CODE | |
| LOW | torch_geometric/nn/conv/dna_conv.py | 161 | CODE | |
| LOW | torch_geometric/nn/conv/transformer_conv.py | 283 | CODE | |
| LOW | torch_geometric/nn/conv/pan_conv.py | 130 | CODE | |
| LOW | torch_geometric/nn/conv/pna_conv.py | 91 | CODE | |
| LOW | torch_geometric/nn/conv/rgat_conv.py | 174 | CODE | |
| LOW | torch_geometric/nn/conv/cluster_gcn_conv.py | 124 | CODE | |
| LOW | torch_geometric/nn/conv/gps_conv.py | 62 | CODE | |
| LOW | torch_geometric/nn/conv/gen_conv.py | 120 | CODE | |
| LOW | torch_geometric/nn/aggr/basic.py | 139 | CODE | |
| LOW | …rch_geometric/distributed/dist_link_neighbor_loader.py | 42 | CODE | |
| LOW | torch_geometric/distributed/dist_neighbor_loader.py | 42 | CODE | |
| LOW | torch_geometric/distributed/dist_neighbor_sampler.py | 70 | CODE | |
| LOW | torch_geometric/datasets/graphland.py | 227 | CODE | |
| LOW | torch_geometric/datasets/fake.py | 43 | CODE | |
| LOW | torch_geometric/datasets/fake.py | 143 | CODE | |
| LOW | torch_geometric/datasets/opf.py | 69 | CODE | |
| LOW | torch_geometric/datasets/protein_mpnn_dataset.py | 75 | CODE | |
| LOW | torch_geometric/io/obj.py | 42 | CODE | |
| 21 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | test/nn/dense/test_linear.py | 274 | except Exception: | CODE |
| LOW | torch_geometric/device.py | 12 | except Exception: | CODE |
| LOW | torch_geometric/config_store.py | 18 | except Exception: | CODE |
| LOW | torch_geometric/config_store.py | 24 | except Exception: | CODE |
| LOW | torch_geometric/_onnx.py | 77 | except Exception as e: | STRING |
| LOW | torch_geometric/_onnx.py | 130 | except Exception: | STRING |
| LOW | torch_geometric/_onnx.py | 148 | except Exception: | STRING |
| LOW | torch_geometric/_onnx.py | 164 | except Exception: | STRING |
| LOW | torch_geometric/_onnx.py | 186 | except Exception: | STRING |
| LOW⚡ | torch_geometric/typing.py | 82 | except Exception: | CODE |
| LOW⚡ | torch_geometric/typing.py | 87 | except Exception: | CODE |
| LOW⚡ | torch_geometric/typing.py | 89 | except Exception as e: | CODE |
| LOW | torch_geometric/typing.py | 141 | except Exception as e: | CODE |
| LOW | torch_geometric/typing.py | 169 | except Exception as e: | CODE |
| LOW | torch_geometric/typing.py | 302 | except Exception: | CODE |
| LOW | torch_geometric/typing.py | 313 | except Exception: | CODE |
| LOW | torch_geometric/hash_tensor.py | 46 | except Exception: | CODE |
| LOW | torch_geometric/metrics/link_pred.py | 13 | except Exception: | CODE |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 1154 | except Exception as e: | CODE |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 1163 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 613 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 635 | except Exception: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 780 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 821 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 834 | except Exception: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 852 | except Exception as e2: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 1109 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 1344 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 1501 | except Exception: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 1551 | except Exception: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 1702 | except Exception: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 2753 | except Exception: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 2905 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3022 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3061 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3323 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3492 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3515 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3635 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3854 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3881 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 4201 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 4376 | except Exception as e: | CODE |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 3586 | except Exception as e: | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 3596 | except Exception as e1: | STRING |
| LOW | torch_geometric/llm/models/qa_gen.py | 2231 | except Exception: | STRING |
| LOW | torch_geometric/llm/models/qa_gen.py | 2369 | except Exception: | STRING |
| LOW | torch_geometric/llm/models/qa_gen.py | 3750 | except Exception as e: | STRING |
| LOW | torch_geometric/llm/models/txt2kg.py | 365 | except Exception as e: | CODE |
| LOW | torch_geometric/llm/models/txt2kg.py | 400 | except Exception: | CODE |
| LOW | …rch_geometric/explain/algorithm/graphmask_explainer.py | 410 | except Exception: | STRING |
| LOW | …rch_geometric/explain/algorithm/graphmask_explainer.py | 416 | except Exception: | STRING |
| LOW | torch_geometric/nn/sequential.py | 265 | except Exception as e: # pragma: no cover | CODE |
| LOW | torch_geometric/nn/conv/message_passing.py | 961 | except Exception as e: # pragma: no cover | STRING |
| LOW | torch_geometric/nn/conv/message_passing.py | 994 | except Exception as e: # pragma: no cover | STRING |
| LOW | torch_geometric/distributed/event_loop.py | 22 | except Exception as e: | CODE |
| LOW | torch_geometric/distributed/event_loop.py | 84 | except Exception as e: | STRING |
| MEDIUM | torch_geometric/distributed/event_loop.py | 19 | def on_done(*_): | CODE |
| LOW | torch_geometric/distributed/dist_neighbor_sampler.py | 392 | except Exception: | STRING |
| LOW | torch_geometric/distributed/rpc.py | 12 | except Exception: | CODE |
| 33 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | benchmark/citation/__init__.py | 4 | __all__ = [ | CODE |
| LOW | benchmark/runtime/__init__.py | 3 | __all__ = [ | CODE |
| LOW | benchmark/utils/__init__.py | 8 | __all__ = [ | CODE |
| LOW | benchmark/points/__init__.py | 4 | __all__ = [ | CODE |
| LOW | benchmark/kernel/__init__.py | 4 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/pooling/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/optimizer/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/loss/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/config/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/encoder/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/network/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/act/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/head/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/layer/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/loader/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/train/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/stage/__init__.py | 5 | __all__ = [ | CODE |
| LOW | graphgym/custom_graphgym/transform/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/experimental.py | 37 | def set_experimental_mode_enabled(mode: bool, options: Options = None) -> None: | STRING |
| LOW | torch_geometric/home.py | 23 | def set_home_dir(path: str) -> None: | STRING |
| LOW | torch_geometric/__init__.py | 36 | __all__ = [ | CODE |
| LOW | torch_geometric/debug.py | 11 | def set_debug_enabled(mode: bool) -> None: | CODE |
| LOW | torch_geometric/visualization/__init__.py | 6 | __all__ = [ | CODE |
| LOW | torch_geometric/llm/utils/feature_store.py | 31 | def _set_from_config(self, config: Dict[str, Any], attr_name: str) -> None: | CODE |
| LOW | torch_geometric/llm/utils/graph_store.py | 54 | def _set_from_config(self, config: Dict[str, Any], attr_name: str) -> None: | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 24 | logger = logging.getLogger(__name__) | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 329 | def update_generation_model(self, model: str) -> None: | CODE |
| LOW | torch_geometric/explain/__init__.py | 7 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/__init__.py | 22 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/sequential.py | 240 | def _set_jittable_template(self, raise_on_error: bool = False) -> None: | CODE |
| LOW | torch_geometric/nn/unpool/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/dense/__init__.py | 17 | __all__ = [ | STRING |
| LOW | torch_geometric/nn/models/basic_gnn.py | 692 | __all__ = [ | STRING |
| LOW | torch_geometric/nn/conv/__init__.py | 68 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/conv/message_passing.py | 926 | def _set_jittable_templates(self, raise_on_error: bool = False) -> None: | STRING |
| LOW | torch_geometric/nn/conv/cugraph/__init__.py | 6 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/conv/utils/__init__.py | 14 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/norm/__init__.py | 13 | __all__ = [ | CODE |
| LOW | torch_geometric/nn/pool/__init__.py | 378 | __all__ = [ | STRING |
| LOW | torch_geometric/nn/pool/select/__init__.py | 10 | __all__ = [ | STRING |
| LOW | torch_geometric/nn/pool/connect/__init__.py | 10 | __all__ = [ | STRING |
| LOW | torch_geometric/datasets/utils/__init__.py | 3 | __all__ = [ | CODE |
| LOW | torch_geometric/io/__init__.py | 10 | __all__ = [ | CODE |
| LOW | torch_geometric/utils/__init__.py | 62 | __all__ = [ | CODE |
| LOW | torch_geometric/contrib/__init__.py | 13 | __all__ = [] | CODE |
| LOW | torch_geometric/contrib/nn/__init__.py | 4 | __all__ = [] | CODE |
| LOW | torch_geometric/contrib/nn/models/mgnan.py | 9 | __all__ = [ | CODE |
| LOW | torch_geometric/contrib/utils/__init__.py | 3 | __all__ = ['from_relbench'] | CODE |
| LOW | torch_geometric/graphgym/utils/__init__.py | 8 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/models/__init__.py | 10 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/pooling/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/optimizer/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/loss/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/config/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/encoder/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/network/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/act/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/head/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/layer/__init__.py | 5 | __all__ = [ | CODE |
| LOW | torch_geometric/graphgym/contrib/loader/__init__.py | 5 | __all__ = [ | CODE |
| 6 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | test/test_config_store.py | 130 | assert (cfg.dataset.transform.NormalizeFeatures._target_.split('.')[-1] == | CODE |
| CRITICAL | test/test_config_store.py | 135 | assert (cfg.dataset.transform.AddSelfLoops._target_.split('.')[-1] == | CODE |
| CRITICAL | test/data/lightning/test_datamodule.py | 49 | self.trainer.datamodule.train_dataset._data.x.add_(1) | CODE |
| CRITICAL | test/data/lightning/test_datamodule.py | 176 | self.trainer.datamodule.data.x.add_(1) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | test/test_onnx.py | 67 | # Use comprehensive mocking to avoid any real ONNX calls | COMMENT |
| MEDIUM | test/test_onnx.py | 146 | # Use multiple patch targets to ensure comprehensive mocking | COMMENT |
| MEDIUM | test/test_onnx.py | 178 | # Use comprehensive mocking to prevent real ONNX calls | COMMENT |
| MEDIUM | torch_geometric/backend.py | 8 | # If set to `None`, will automatically decide whether to utilize | COMMENT |
| LOW | torch_geometric/llm/models/qa_gen.py | 2816 | # No hop contexts, just use top-level as-is | COMMENT |
| MEDIUM | torch_geometric/nn/sequential.py | 31 | r"""An extension of the :class:`torch.nn.Sequential` container in order to | CODE |
| LOW | torch_geometric/datasets/karate.py | 76 | # (we just use the first one). | STRING |
| MEDIUM | torch_geometric/datasets/medshapenet.py | 75 | r"""The absolute filepaths that must be present in order to skip | STRING |
| MEDIUM | torch_geometric/contrib/nn/models/rbcd_attack.py | 602 | <https://www.cs.cit.tum.de/daml/are-gnn-defenses-robust>`_ for details. | CODE |
| MEDIUM | torch_geometric/profile/profile.py | 49 | r"""A decorator to facilitate profiling a function, *e.g.*, obtaining | CODE |
| MEDIUM | torch_geometric/profile/profile.py | 145 | r"""A context decorator to facilitate timing a function, *e.g.*, obtaining | STRING |
| MEDIUM | torch_geometric/loader/node_loader.py | 274 | # f'best practices for PyG [{link}])') | STRING |
| MEDIUM | torch_geometric/loader/utils.py | 233 | # NOTE Here, we utilize `feature_store.multi_get` to give the feature store | STRING |
| MEDIUM | torch_geometric/loader/utils.py | 267 | # NOTE Here, we utilize `feature_store.multi_get` to give the feature store | STRING |
| LOW | torch_geometric/data/collate.py | 274 | # Other-wise, just return the list of values as it is. | COMMENT |
| MEDIUM | torch_geometric/data/dataset.py | 199 | r"""The absolute filepaths that must be present in order to skip | CODE |
| MEDIUM | torch_geometric/data/dataset.py | 211 | r"""The absolute filepaths that must be present in order to skip | STRING |
| MEDIUM | examples/llm/relbench_gretriever.py | 223 | # Single-graph paradigm: all nodes belong to batch index 0. | COMMENT |
| LOW | examples/llm/txt2qa.py | 510 | # If file_path is not relative to input_dir, just use the stem | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | test/llm/test_rag_loader.py | 237 | # Create RAG loader | COMMENT |
| MEDIUM | torch_geometric/llm/models/qa_gen.py | 3079 | # Truncate texts to fit embedding model's max length (512 tokens) | COMMENT |
| MEDIUM | torch_geometric/llm/models/qa_gen.py | 3140 | # Truncate answer to fit embedding model's max length (512 tokens) | COMMENT |
| MEDIUM | torch_geometric/llm/models/qa_gen.py | 3218 | # Truncate questions to fit embedding model's max length (512 tokens) | COMMENT |
| MEDIUM | torch_geometric/llm/models/qa_gen.py | 243 | # Handle embedding model GPU memory | STRING |
| MEDIUM | examples/rect.py | 12 | # RECT focuses on the zero-shot, i.e. completely-imbalanced label setting: | COMMENT |
| MEDIUM | examples/rect.py | 14 | # RECT (or more specifically its supervised part RECT-L) model in the zero-shot | COMMENT |
| MEDIUM | examples/llm/txt2kg_rag.py | 273 | # Read corpus data to create the KG and for document retrieval (RAG). | STRING |
| MEDIUM | examples/llm/txt2kg_rag.py | 381 | # creating the embedding model | STRING |
| MEDIUM | examples/llm/txt2kg_rag.py | 453 | # creating the embedding model | STRING |
| MEDIUM | examples/llm/txt2kg_rag.py | 521 | # VectorDB retrieval just vanilla vector RAG | STRING |
| MEDIUM | examples/llm/txt2qa_config/text_config_vllm.yaml | 31 | embedding: 0.3 # GPU memory for embedding model (typically smaller) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 1390 | # Step 1: Clean markdown code blocks | COMMENT |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 1395 | # Step 2: Try direct parsing first (fastest path) | COMMENT |
| LOW | torch_geometric/llm/models/qa_gen.py | 1406 | # Step 3: Find JSON array/object with bracket counting | COMMENT |
| LOW | torch_geometric/llm/models/qa_gen.py | 1470 | # Step 4: Last resort - old regex fallback | COMMENT |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2009 | # Step 1: Calculate exact (floating-point) values for each category | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2016 | # Step 2: Sort by fractional part descending (0.9, 0.9, 0.2) | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2021 | # Step 3: Assign floor values first (everyone gets their integer part) | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2027 | # Step 4: Distribute remaining items based on fractional parts | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2035 | # Step 5: Edge case - if still items left (e.g., rounding errors) | STRING |
| LOW | examples/distributed/graphlearn_for_pytorch/README.md | 22 | #### Step 1: Prepare and partition the data | COMMENT |
| LOW | examples/distributed/graphlearn_for_pytorch/README.md | 30 | #### Step 2: Run the example in each training node | COMMENT |
| LOW | examples/distributed/graphlearn_for_pytorch/README.md | 55 | #### Step 1: Setup a distributed file system | COMMENT |
| LOW | examples/distributed/graphlearn_for_pytorch/README.md | 62 | #### Step 2: Prepare and partition the data | COMMENT |
| LOW | examples/distributed/graphlearn_for_pytorch/README.md | 85 | #### Step 3: Set up the configure file | COMMENT |
| LOW | examples/distributed/graphlearn_for_pytorch/README.md | 89 | #### Step 4: Launch the distributed training | COMMENT |
| LOW⚡ | examples/quiver/single_gpu_quiver.py | 21 | # Step 1: Using Quiver's sampler | COMMENT |
| LOW | examples/quiver/single_gpu_quiver.py | 99 | # Step 2: Using Quiver's Feature | COMMENT |
| LOW | examples/quiver/single_gpu_quiver.py | 117 | # Step 3: Training the PyG Model with Quiver | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | test/utils/test_scatter.py | 144 | # ================ | COMMENT |
| MEDIUM | test/utils/test_scatter.py | 153 | # ================ | COMMENT |
| MEDIUM | test/utils/test_segment.py | 58 | # ================ | COMMENT |
| MEDIUM | test/utils/test_segment.py | 63 | # ================ | COMMENT |
| MEDIUM | torch_geometric/graphgym/config.py | 321 | # =================================== | STRING |
| MEDIUM | torch_geometric/graphgym/config.py | 329 | # =================================== | STRING |
| MEDIUM | examples/explain/mgnan_graph_mutagenicity.py | 246 | # -------------------------------------------------------------- | COMMENT |
| MEDIUM | examples/explain/mgnan_graph_mutagenicity.py | 248 | # -------------------------------------------------------------- | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | test/explain/algorithm/test_pg_explainer.py | 222 | # Check if the explanation is valid | COMMENT |
| LOW | test/explain/algorithm/test_pg_explainer.py | 371 | # Check if the explanation is valid | COMMENT |
| LOW | test/explain/algorithm/test_pg_explainer.py | 467 | # Check if the explanation is valid | COMMENT |
| LOW | test/loader/test_link_neighbor_loader.py | 284 | # Check if each seed edge has a different batch: | COMMENT |
| LOW | torch_geometric/llm/utils/backend_utils.py | 383 | ) # Check if pandas is installed | CODE |
| LOW | torch_geometric/llm/models/qa_gen.py | 3847 | # Check if segment overlaps with QA time range | COMMENT |
| LOW | torch_geometric/llm/models/qa_gen.py | 4174 | # Check if we have context_segments from processing | COMMENT |
| LOW | …rch_geometric/explain/algorithm/attention_explainer.py | 128 | # Check if all components appear in the module name in | COMMENT |
| LOW | …rch_geometric/explain/algorithm/attention_explainer.py | 180 | # Check if we collected any attention coefficients. | COMMENT |
| LOW | torch_geometric/datasets/tag_dataset.py | 368 | # Check if the .pt files already exist | STRING |
| LOW | torch_geometric/io/fs.py | 167 | # Open file has protocol stripped. | STRING |
| LOW | torch_geometric/utils/embedding.py | 97 | # Check if the outputs is a dictionary mapping node types to embeddings | COMMENT |
| LOW | torch_geometric/contrib/nn/models/rbcd_attack.py | 497 | # Check if middle point is root | COMMENT |
| LOW | examples/llm/txt2qa.py | 394 | # Check if file exists before removing | COMMENT |
| LOW | examples/llm/txt2qa.py | 531 | # Check if output file already exists (resume functionality) | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 1390 | # Step 1: Clean markdown code blocks | COMMENT |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 1395 | # Step 2: Try direct parsing first (fastest path) | COMMENT |
| LOW | torch_geometric/llm/models/qa_gen.py | 1406 | # Step 3: Find JSON array/object with bracket counting | COMMENT |
| LOW | torch_geometric/llm/models/qa_gen.py | 1470 | # Step 4: Last resort - old regex fallback | COMMENT |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2009 | # Step 1: Calculate exact (floating-point) values for each category | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2016 | # Step 2: Sort by fractional part descending (0.9, 0.9, 0.2) | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2021 | # Step 3: Assign floor values first (everyone gets their integer part) | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2027 | # Step 4: Distribute remaining items based on fractional parts | STRING |
| LOW⚡ | torch_geometric/llm/models/qa_gen.py | 2035 | # Step 5: Edge case - if still items left (e.g., rounding errors) | STRING |
| LOW⚡ | examples/quiver/single_gpu_quiver.py | 21 | # Step 1: Using Quiver's sampler | COMMENT |
| LOW | examples/quiver/single_gpu_quiver.py | 99 | # Step 2: Using Quiver's Feature | COMMENT |
| LOW | examples/quiver/single_gpu_quiver.py | 117 | # Step 3: Training the PyG Model with Quiver | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | test/transforms/test_pad.py | 20 | def fake_data() -> Data: | CODE |
| LOW⚡ | test/transforms/test_pad.py | 426 | data = fake_data() | CODE |
| LOW⚡ | test/transforms/test_pad.py | 439 | data = fake_data() | CODE |
| LOW⚡ | test/transforms/test_pad.py | 464 | data = fake_data() | CODE |
| LOW | test/transforms/test_pad.py | 327 | @pytest.mark.parametrize('data', [fake_data(), fake_hetero_data()]) | CODE |
| LOW | test/transforms/test_pad.py | 341 | data = fake_data() | CODE |
| LOW | test/transforms/test_pad.py | 367 | data = fake_data() | CODE |
| LOW | test/transforms/test_pad.py | 404 | @pytest.mark.parametrize('data', [fake_data(), fake_hetero_data()]) | CODE |
| LOW | test/transforms/test_pad.py | 479 | data = fake_data() | CODE |
| LOW | torch_geometric/nn/fx.py | 141 | if node.op == 'placeholder': | STRING |
| LOW | torch_geometric/nn/fx.py | 178 | if node.op not in ['placeholder', 'output']: | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | torch_geometric/nn/models/gpse.py | 1009 | Calculates the average cosine similarity between predicted and true features on a batch of graphs. Args: | STRING |
| HIGH | torch_geometric/contrib/utils/_relbench.py | 11 | Converts a :class:`relbench.base.Database` object into a :class:`~torch_geometric.data.HeteroData` object. Each | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | examples/datapipe.py | 1 | # In this example, you will find data loading implementations using PyTorch | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | test/utils/test_scatter.py | 141 | COMMENT | |
| LOW | test/sampler/test_sampler_neighbor_sampler.py | 521 | expected_output = SamplerOutput( | COMMENT |
| LOW | torch_geometric/nn/conv/meshcnn_conv.py | 401 | # Option 2 | COMMENT |
| LOW | torch_geometric/graphgym/config.py | 301 | # Auto match computational budget, match upper bound / lower bound | COMMENT |
| LOW | torch_geometric/graphgym/config.py | 321 | # =================================== | COMMENT |
| LOW | examples/tgn.py | 1 | # This code achieves a performance of around 96.60%. However, it is not | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | torch_geometric/utils/geodesic.py | 29 | To install, run :obj:`pip install cython && pip install gdist`. | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | torch_geometric/distributed/event_loop.py | 92 | def run_task(self, coro): | STRING |
| LOW | examples/llm/txt2qa.py | 516 | async def process_data(self, data: str, data_id: str, | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | torch_geometric/io/fs.py | 145 | # If the source path points to a directory, we need to make sure to | STRING |