⚡ TabPFN: Foundation Model for Tabular Data ⚡
This report summarizes scanner evidence for PriorLabs/TabPFN, a Python project with 8,153 GitHub stars. SynthScan examined 106,244 lines of code across 274 source files, recording 2173 pattern matches distributed across 17 syntactic categories. The legacy adjusted pattern signal is 25.7 (Elevated 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? 1604 finding(s).
Are imports declared and package/API names verified? 305 finding(s).
Are wrappers, guards, and repeated structures necessary? 1771 finding(s).
Which changes need focused human review? 2173 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 2173 distinct pattern matches across 17 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 | tests/test_inference.py | 114 | def reset_save_peak_mem_factor(self, factor: int | None = None) -> None: | CODE |
| LOW | tests/test_inference.py | 161 | def reset_save_peak_mem_factor(self, factor: int | None = None) -> None: | CODE |
| LOW | tests/test_inference.py | 234 | def reset_save_peak_mem_factor(self, factor: int | None = None) -> None: | CODE |
| LOW | tests/test_inference.py | 266 | def test__cache_preprocessing__result_equal_in_serial_and_in_parallel() -> None: | CODE |
| LOW | tests/test_inference.py | 319 | def test__cache_preprocessing__with_outlier_removal() -> None: | CODE |
| LOW | tests/test_inference.py | 373 | def test__on_demand__result_equal_in_serial_and_in_parallel() -> None: | CODE |
| LOW | tests/test_inference.py | 436 | def test__iter_outputs__task_type_forwarded( | CODE |
| LOW | tests/test_inference.py | 480 | def _create_test_ensemble_configs( | CODE |
| LOW | tests/test_inference.py | 529 | def test__explicit_kv_cache__produces_outputs() -> None: | CODE |
| LOW | tests/test_inference.py | 582 | def test__explicit_kv_cache__drops_member_train_features_after_build() -> None: | CODE |
| LOW | tests/test_inference.py | 634 | def test__explicit_kv_cache__task_type_forwarded_to_cache_build( | CODE |
| LOW | tests/test_inference.py | 682 | def test__explicit_kv_cache__keep_on_device_reuses_tensors(device: str) -> None: | CODE |
| LOW | tests/test_inference.py | 756 | def test__public_keep_cache_on_device__controls_cache_placement( | CODE |
| LOW | tests/test_inference.py | 818 | def test__init__mps_target_device__applies_mps_linear_bug_workaround( | CODE |
| LOW | tests/test_inference.py | 875 | def test__to__mps_target_device__applies_mps_linear_bug_workaround( | CODE |
| LOW | tests/test_inference.py | 928 | def test__kv_cache_chunking__matches_unchunked( | CODE |
| LOW | tests/test_inference.py | 998 | def test__kv_cache__embeddings_test_only_and_chunk_safe( | CODE |
| LOW | tests/test_inference.py | 1044 | def get_supported_kv_cache_precisions(self) -> tuple[str, ...]: | CODE |
| LOW | tests/test_inference.py | 1062 | def test__explicit_kv_cache__precision__reaches_the_cache_build( | CODE |
| LOW | tests/test_inference.py | 1102 | def test__resolve_kv_cache_precision__warns_when_unsupported() -> None: | CODE |
| LOW | tests/test_consistency.py | 51 | def _get_tiny_classification_data() -> tuple[np.ndarray, np.ndarray, np.ndarray]: | CODE |
| LOW | tests/test_consistency.py | 68 | def _get_tiny_regression_data() -> tuple[np.ndarray, np.ndarray, np.ndarray]: | CODE |
| LOW | tests/test_consistency.py | 84 | def _get_iris_multiclass_data() -> tuple[np.ndarray, np.ndarray, np.ndarray]: | CODE |
| LOW | tests/test_consistency.py | 245 | def _get_current_platform_string() -> str: | CODE |
| LOW | tests/test_consistency.py | 271 | def test__fit_predict__predictions_match_reference( | CODE |
| LOW | tests/test_consistency.py | 314 | def _load_reference_predictions_or_fail(test_name: str) -> np.ndarray: | CODE |
| LOW | tests/test_consistency.py | 324 | def save_reference_predictions() -> None: | CODE |
| LOW | tests/test_utils.py | 48 | def test__infer_devices__auto__cuda_and_mps_not_available__selects_cpu( | CODE |
| LOW | tests/test_utils.py | 57 | def test__infer_devices__auto__single_cuda_gpu_available__selects_it( | CODE |
| LOW | tests/test_utils.py | 68 | def test__infer_devices__auto__multiple_cuda_gpus_available__selects_all( | CODE |
| LOW | tests/test_utils.py | 84 | def test__infer_devices__auto__cuda_and_mps_available_but_excluded__selects_cpu( | CODE |
| LOW | tests/test_utils.py | 95 | def test__infer_devices__auto__mps_available_but_torch_too_old__selects_cpu( | CODE |
| LOW | tests/test_utils.py | 104 | def test__infer_devices__device_specified__selects_it( | CODE |
| LOW | tests/test_utils.py | 115 | def test__infer_devices__multiple_devices_specified___selects_them( | CODE |
| LOW | tests/test_utils.py | 128 | def test__infer_devices__device_specified_twice__raises() -> None: | CODE |
| LOW | tests/test_utils.py | 136 | def test__infer_devices__mps_specified_but_torch_too_old__raises( | CODE |
| LOW | tests/test_utils.py | 226 | def test_balance_probas_by_class_counts(): | CODE |
| LOW | tests/test_utils.py | 242 | def test__translate_probs_across_borders__matches_unchunked(batch: int) -> None: | CODE |
| LOW | tests/test_utils.py | 263 | def test__translate_probs_across_borders__forces_chunking( | CODE |
| LOW | tests/test_utils.py | 307 | def test__translate_probs_across_borders__small_buckets_survive( | CODE |
| LOW | tests/test_utils.py | 332 | def test__translate_probs_across_borders__identity_remap_is_the_identity( | CODE |
| LOW | tests/test_utils.py | 351 | def test__translate_probs_across_borders__identity_remap_costs_nothing( | CODE |
| LOW | tests/test_utils.py | 380 | def test__translate_probs_across_borders__outer_buckets_are_half_normal_tails() -> None: | CODE |
| LOW | tests/test_utils.py | 420 | def test__translate_probs_across_borders__tails_leave_interior_buckets_untouched() -> ( | CODE |
| LOW | tests/test_utils.py | 442 | def test__translate_probs_across_borders__fills_buckets_outside_source_range() -> None: | CODE |
| LOW | tests/test_utils.py | 483 | def test__translate_probs_across_borders__upper_tail_mirrors_lower_tail() -> None: | CODE |
| LOW | tests/test_utils.py | 520 | def test__translate_probs_across_borders__upper_tail_matches_analytic() -> None: | CODE |
| LOW | tests/test_utils.py | 552 | def test__translate_probs_across_borders__interior_is_mirror_symmetric() -> None: | CODE |
| LOW | tests/test_utils.py | 584 | def test__translate_probs_across_borders__to_inside_one_source_tail_sums_to_one( | CODE |
| LOW | tests/test_utils.py | 605 | def test__translate_probs_across_borders__device_matches_cpu( | CODE |
| LOW | tests/test_utils.py | 638 | def test__translate_probs_across_borders__cuda_is_bitwise_reproducible() -> None: | CODE |
| LOW | tests/test_utils.py | 667 | def test__translate_probs_across_borders__zero_width_source_bucket_keeps_its_mass() -> ( | CODE |
| LOW | tests/test_utils.py | 694 | def test__translate_probs_across_borders__degenerate_outer_bucket_is_finite() -> None: | CODE |
| LOW | tests/test_utils.py | 747 | def test__infer_autocast_inference_mode__cpu( | CODE |
| LOW | tests/test_utils.py | 779 | def test__repair_borders__collapsed_top_gap__widens_upwards(borders, expected_last): | CODE |
| LOW | tests/test_utils.py | 794 | def test__repair_borders__nan_top__widens_upwards(borders, expected_last): | CODE |
| LOW | tests/test_estimators.py | 43 | def _batched_cache_moved_onto_mps(fit_mode: str, device_1: str, device_2: str) -> bool: | CODE |
| LOW | tests/test_estimators.py | 53 | def test__to__before_fit__does_not_crash( | CODE |
| LOW | tests/test_estimators.py | 71 | def test__to__between_fit_and_predict__does_not_crash( | CODE |
| LOW | tests/test_estimators.py | 93 | def test__to__between_fits__outputs_equal( | CODE |
| 1439 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | tests/test_inference_config.py | 213 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_inference_config.py | 215 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_inference_config.py | 520 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_inference_config.py | 522 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_inference_config.py | 637 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_inference_config.py | 639 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_logging.py | 15 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_logging.py | 17 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 56 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 58 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 108 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 110 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 131 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 133 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 591 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_browser_auth.py | 593 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 26 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 28 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 235 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 237 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 358 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 360 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 405 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_browser_auth.py | 407 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_regressor_interface.py | 1116 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_regressor_interface.py | 1118 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 1322 | # ============================================================================= | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 1324 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_classifier.py | 544 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_classifier.py | 546 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_classifier.py | 997 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_classifier.py | 999 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_classifier.py | 1374 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_finetuning_classifier.py | 1376 | # ============================================================================= | COMMENT |
| MEDIUM | tests/test_finetuning_classifier.py | 124 | # ============================================================================= | COMMENT |
| MEDIUM | tests/test_finetuning_classifier.py | 126 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_classifier_interface.py | 1492 | # ============================================================================= | COMMENT |
| MEDIUM⚡ | tests/test_classifier_interface.py | 1494 | # ============================================================================= | COMMENT |
| MEDIUM | …preprocessing/test_encode_categorical_features_step.py | 556 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …preprocessing/test_encode_categorical_features_step.py | 558 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_preprocessing/test_preprocessing_steps.py | 582 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_preprocessing/test_preprocessing_steps.py | 584 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …ch_preprocessing/test_gpu_preprocessing_consistency.py | 39 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …ch_preprocessing/test_gpu_preprocessing_consistency.py | 41 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …ch_preprocessing/test_gpu_preprocessing_consistency.py | 231 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …ch_preprocessing/test_gpu_preprocessing_consistency.py | 233 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …ch_preprocessing/test_gpu_preprocessing_consistency.py | 258 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …ch_preprocessing/test_gpu_preprocessing_consistency.py | 260 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_architectures/test_mlx_backend.py | 171 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | tests/test_architectures/test_mlx_backend.py | 173 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_mlx_backend.py | 244 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_mlx_backend.py | 246 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 205 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 207 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 400 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 402 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 661 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 663 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 850 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tests/test_architectures/test_tabpfn_v3_5.py | 852 | # --------------------------------------------------------------------------- | COMMENT |
| 90 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …torch_preprocessing/test_torch_quantile_transformer.py | 0 | test with 3d tensor (t, b, h) shape commonly used in tabpfn. | STRING |
| HIGH | …t_torch_preprocessing/test_torch_soft_clip_outliers.py | 0 | test with 3d tensor (t, b, h) shape commonly used in tabpfn. | STRING |
| HIGH | …test_torch_preprocessing/test_torch_standard_scaler.py | 0 | test with 3d tensor (t, b, h) shape commonly used in tabpfn. | STRING |
| HIGH | tests/test_architectures/test_tabpfn_v2.py | 0 | kv-cache inference must match the standard (full train+test) forward. | STRING |
| HIGH | tests/test_architectures/test_tabpfn_v2_6.py | 0 | kv-cache inference must match the standard (full train+test) forward. | STRING |
| HIGH | tests/test_architectures/test_tabpfn_v2_5.py | 0 | kv-cache inference must match the standard (full train+test) forward. | STRING |
| HIGH | tests/test_architectures/test_tabpfn_v2.py | 0 | the cache path also returns matching embeddings dicts. | STRING |
| HIGH | tests/test_architectures/test_tabpfn_v2_6.py | 0 | the cache path also returns matching embeddings dicts. | STRING |
| HIGH | tests/test_architectures/test_tabpfn_v2_5.py | 0 | the cache path also returns matching embeddings dicts. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | number of key/value heads to use for per-column-inter-row attention. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | number of key/value heads to use for per-column-inter-row attention. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | number of key/value heads to use for per-column-inter-row attention. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | if > 1, the features will be grouped into groups of this size and the attention is across groups. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | if > 1, the features will be grouped into groups of this size and the attention is across groups. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | if > 1, the features will be grouped into groups of this size and the attention is across groups. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | base class for the between-features and between-rows attention layers. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | base class for the between-features and between-rows attention layers. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | base class for the between-features and between-rows attention layers. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | construct a new instance. args: embedding_size: the size of the input embedding. num_heads: the number of heads to use. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | construct a new instance. args: embedding_size: the size of the input embedding. num_heads: the number of heads to use. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | construct a new instance. args: embedding_size: the size of the input embedding. num_heads: the number of heads to use. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | computes the attention between features of a single row. this is standard multi-head self-attention, where all features | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | computes the attention between features of a single row. this is standard multi-head self-attention, where all features | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | computes the attention between features of a single row. this is standard multi-head self-attention, where all features | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | forward pass for along-row attention between features. args: x_brse: the input tensor of shape (br, c, e), where: - br: | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | forward pass for along-row attention between features. args: x_brse: the input tensor of shape (br, c, e), where: - br: | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | forward pass for along-row attention between features. args: x_brse: the input tensor of shape (br, c, e), where: - br: | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | computes the attention between cells of a single column. this is multi-head attention featuring: - an implicit mask: the | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | computes the attention between cells of a single column. this is multi-head attention featuring: - an implicit mask: the | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | computes the attention between cells of a single column. this is multi-head attention featuring: - an implicit mask: the | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | forward pass for attention between cells of a single column. args: x_bcre: the input tensor of shape (bc, r, e), where: | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | forward pass for attention between cells of a single column. args: x_bcre: the input tensor of shape (bc, r, e), where: | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | forward pass for attention between cells of a single column. args: x_bcre: the input tensor of shape (bc, r, e), where: | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | layernorm that maintains fp16 precision in autocast mode. pytorch autocast runs layernorm in fp32, which has bad effects | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | layernorm that maintains fp16 precision in autocast mode. pytorch autocast runs layernorm in fp32, which has bad effects | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | layernorm that maintains fp16 precision in autocast mode. pytorch autocast runs layernorm in fp32, which has bad effects | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | a block of one column-wise, one row-wise attention layer and an mlp layer. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | a block of one column-wise, one row-wise attention layer and an mlp layer. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | a block of one column-wise, one row-wise attention layer and an mlp layer. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | tabpfnblock constructor. args: emsize: the input embedding size. nhead: the number of query attention heads to use. dim_ | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | tabpfnblock constructor. args: emsize: the input embedding size. nhead: the number of query attention heads to use. dim_ | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | tabpfnblock constructor. args: emsize: the input embedding size. nhead: the number of query attention heads to use. dim_ | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | compute one column-wise, one row-wise attention, and an mlp layer. uses post-norm. b: batch size r: number of rows / ite | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | compute one column-wise, one row-wise attention, and an mlp layer. uses post-norm. b: batch size r: number of rows / ite | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | compute one column-wise, one row-wise attention, and an mlp layer. uses post-norm. b: batch size r: number of rows / ite | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | move all cached tensors to the given device. returns a new cache. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | move all cached tensors to the given device. returns a new cache. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | move all cached tensors to the given device. returns a new cache. | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | perform a forward pass. see modelinterface.forward() for the full docstring of the shared arguments. in addition to thos | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | perform a forward pass. see modelinterface.forward() for the full docstring of the shared arguments. in addition to thos | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | perform a forward pass. see modelinterface.forward() for the full docstring of the shared arguments. in addition to thos | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | parse the config dict into a tabpfnv2config, return unused keys. args: config: config dict to parse. this function shoul | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | parse the config dict into a tabpfnv2config, return unused keys. args: config: config dict to parse. this function shoul | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | parse the config dict into a tabpfnv2config, return unused keys. args: config: config dict to parse. this function shoul | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 0 | construct tabpfnv2 based on the given config. this factory method implements the interface defined in tabpfn.architectur | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 0 | construct tabpfnv2 based on the given config. this factory method implements the interface defined in tabpfn.architectur | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 0 | construct tabpfnv2 based on the given config. this factory method implements the interface defined in tabpfn.architectur | STRING |
| HIGH | src/tabpfn/finetuning/finetuned_regressor.py | 0 | fine-tune the tabpfn model on the provided training data. args: x: the training input samples of shape (n_samples, n_fea | STRING |
| HIGH | src/tabpfn/finetuning/finetuned_base.py | 0 | fine-tune the tabpfn model on the provided training data. args: x: the training input samples of shape (n_samples, n_fea | STRING |
| HIGH | src/tabpfn/finetuning/finetuned_classifier.py | 0 | fine-tune the tabpfn model on the provided training data. args: x: the training input samples of shape (n_samples, n_fea | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_debug_versions.py | 3 | CODE | |
| LOW | tests/test_inference.py | 5 | CODE | |
| LOW | tests/test_consistency.py | 26 | CODE | |
| LOW | tests/test_utils.py | 3 | CODE | |
| LOW | tests/test_estimators.py | 5 | CODE | |
| LOW | tests/conftest.py | 5 | CODE | |
| LOW | tests/test_notebook_installs.py | 16 | CODE | |
| LOW | tests/quick_test.py | 9 | CODE | |
| LOW | tests/test_validation.py | 5 | CODE | |
| LOW | tests/test_batched_members.py | 4 | CODE | |
| LOW | tests/test_save_load_fitted_model.py | 5 | CODE | |
| LOW | tests/test_errors.py | 5 | CODE | |
| LOW | tests/test_inference_config.py | 5 | CODE | |
| LOW | tests/test_downsample_correction.py | 4 | CODE | |
| LOW | tests/test_batched_prediction_data_util.py | 3 | CODE | |
| LOW | tests/test_visualisation.py | 3 | CODE | |
| LOW | tests/test_parallel_execute.py | 5 | CODE | |
| LOW | tests/test_finetuning_regressor.py | 13 | CODE | |
| LOW | tests/test_input_immutability.py | 23 | CODE | |
| LOW | tests/test_finetuning_logging.py | 5 | CODE | |
| LOW | tests/test_ft_utils.py | 3 | CODE | |
| LOW | tests/utils.py | 3 | CODE | |
| LOW | tests/test_config.py | 3 | CODE | |
| LOW | tests/test_model_loading.py | 3 | CODE | |
| LOW | tests/test_browser_auth.py | 5 | CODE | |
| LOW | tests/test_batched_prediction_shape_safety.py | 3 | CODE | |
| LOW | tests/test_regression_metrics.py | 3 | CODE | |
| LOW | tests/test_regressor_interface.py | 3 | CODE | |
| LOW | tests/test_model_cache.py | 5 | CODE | |
| LOW | tests/test_download_fallbacks.py | 3 | CODE | |
| LOW | tests/test_inference_tuning.py | 3 | CODE | |
| LOW | tests/test_model_specs.py | 5 | CODE | |
| LOW | tests/test_finetuning_classifier.py | 12 | CODE | |
| LOW | tests/test_checkpoint.py | 3 | CODE | |
| LOW | tests/test_settings.py | 3 | CODE | |
| LOW | tests/test_classifier_interface.py | 3 | CODE | |
| LOW | …st_preprocessing/test_adaptive_quantile_transformer.py | 3 | CODE | |
| LOW | …preprocessing/test_encode_categorical_features_step.py | 5 | CODE | |
| LOW | …ocessing/test_nan_handling_polynomial_features_step.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_modality_detection.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_power_transformer.py | 3 | CODE | |
| LOW | tests/test_preprocessing/test_data_cleaning.py | 5 | CODE | |
| LOW | …reprocessing/test_reshape_feature_distribution_step.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_add_svd_features_step.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_kdi_transformer.py | 3 | CODE | |
| LOW | …sts/test_preprocessing/test_feature_name_uniqueness.py | 13 | CODE | |
| LOW | tests/test_preprocessing/test_text.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_preprocessing_steps.py | 3 | CODE | |
| LOW | tests/test_preprocessing/test_label_encoder.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_ops.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_inf_handling.py | 13 | CODE | |
| LOW | …st_preprocessing/test_add_fingerprint_features_step.py | 5 | CODE | |
| LOW | …t_preprocessing/test_numeric_parsing_below_pandas_3.py | 17 | CODE | |
| LOW | …s/test_preprocessing/test_differentiable_znorm_step.py | 3 | CODE | |
| LOW | tests/test_preprocessing/test_datamodel.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_datetimes.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_ensemble.py | 3 | CODE | |
| LOW | …st_preprocessing/test_remove_constant_features_step.py | 5 | CODE | |
| LOW | tests/test_preprocessing/test_pipeline_consistency.py | 16 | CODE | |
| LOW | …ts/test_preprocessing/test_sklearn_estimator_checks.py | 5 | CODE | |
| 241 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | tests/test_model_loading.py | 676 | # Create a fake checkpoint to simulate a successful download | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 472 | # Create a simple preprocessing pipeline | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 697 | # Create a CPU model | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 738 | # Create a CPU model | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 786 | # Create a TabPFNRegressor with fixed random state for reproducibility | COMMENT |
| MEDIUM | tests/test_regressor_interface.py | 803 | # Create a new dataset with added constant features | COMMENT |
| MEDIUM | tests/test_finetuning_classifier.py | 1655 | # Initialize two classifiers with the necessary modes | COMMENT |
| MEDIUM | tests/test_finetuning_classifier.py | 1825 | # Create a larger dataset where columns have distinct mean values | COMMENT |
| MEDIUM⚡ | tests/test_classifier_interface.py | 931 | # Create a TabPFNClassifier with fixed random state for reproducibility | COMMENT |
| MEDIUM⚡ | tests/test_classifier_interface.py | 939 | # Create a new dataset with added constant features | COMMENT |
| MEDIUM | tests/test_classifier_interface.py | 506 | # Create a subset of X to match the length of y_imbalanced | COMMENT |
| MEDIUM | tests/test_classifier_interface.py | 696 | # Create an IMBALANCED dataset | COMMENT |
| MEDIUM | tests/test_classifier_interface.py | 738 | # Create a simple preprocessing pipeline | COMMENT |
| MEDIUM | tests/test_classifier_interface.py | 975 | # Create a DataFrame with text and NA values | COMMENT |
| MEDIUM | tests/test_preprocessing/test_add_svd_features_step.py | 239 | # Create an invalid enum value by bypassing the enum | COMMENT |
| MEDIUM | examples/tabpfn_classifier_with_tuning.py | 38 | # Initialize a classifier with tuning and fit | COMMENT |
| MEDIUM | examples/tabpfn_classifier_with_tuning.py | 46 | # Initialize a classifier with tuning and fit | COMMENT |
| MEDIUM | examples/tabpfn_for_binary_classification.py | 20 | # Initialize a classifier | COMMENT |
| MEDIUM | examples/tabpfn_for_multiclass_classification.py | 23 | # Initialize a classifier | COMMENT |
| MEDIUM | src/tabpfn/regressor.py | 1477 | # Create a dictionary of outputs with proper typing via TypedDict | COMMENT |
| MEDIUM | src/tabpfn/misc/_sklearn_compat.py | 31 | # The following code does not depend on the sklearn version | COMMENT |
| MEDIUM | src/tabpfn/architectures/tabpfn_v2_6.py | 1235 | # The following class imputation is performed for backwards compatibility. | COMMENT |
| MEDIUM | src/tabpfn/architectures/tabpfn_v2_5.py | 1357 | # The following class imputation is performed for backwards compatibility. | COMMENT |
| MEDIUM | …tabpfn/preprocessing/torch/torch_soft_clip_outliers.py | 61 | # Create a clean copy with outliers masked as NaN | COMMENT |
| MEDIUM | src/tabpfn/preprocessing/torch/ops.py | 131 | # Create a mask to zero out the padding positions. | COMMENT |
| MEDIUM | …reprocessing/steps/encode_categorical_features_step.py | 204 | # Create a column transformer | COMMENT |
| MEDIUM | …reprocessing/steps/encode_categorical_features_step.py | 262 | # Create a column transformer | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | examples/sagemaker.py | 87 | Serialize TabPFN input data and parameters into a JSON request body. This utility converts NumPy arrays and configu | STRING |
| HIGH | examples/sagemaker.py | 173 | Invoke the TabPFN SageMaker endpoint with tabular data. This helper prepares the payload for a TabPFN 2.5 model, se | STRING |
| HIGH | src/tabpfn/classifier.py | 1119 | Predict probabilities for several independent datasets in one pass. Each ``(X_train, y_train, X_test)`` triple | STRING |
| HIGH | src/tabpfn/utils.py | 271 | Infer whether reduced-precision (autocast) inference should be enabled. On GPU this is fp16 autocast; on CPU ``torc | STRING |
| HIGH | src/tabpfn/regressor.py | 1804 | Predict for several independent datasets in one pass. Each triple is preprocessed exactly as ``fit()`` + ``pred | STRING |
| HIGH | src/tabpfn/base.py | 664 | Extract embeddings from a fitted TabPFN model. Args: model : TabPFNClassifier | TabPFNRegressor | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_6.py | 1057 | Parse the config dict into a TabPFNV2Config, return unused keys. Args: config: Config dict to parse. This f | STRING |
| HIGH | src/tabpfn/architectures/interface.py | 131 | Parses the given config dict into ArchitectureConfig or a subclass. This config will then be passed to get_arch | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2_5.py | 1080 | Parse the config dict into a TabPFNV2Config, return unused keys. Args: config: Config dict to parse. This f | STRING |
| HIGH | src/tabpfn/architectures/tabpfn_v2.py | 1096 | Parse the config dict into a TabPFNV2Config, return unused keys. Args: config: Config dict to parse. This f | STRING |
| HIGH | src/tabpfn/finetuning/data_util.py | 370 | Retrieves, splits, and preprocesses the dataset config at the index. Performs train/test splitting and applies | STRING |
| HIGH | src/tabpfn/finetuning/train_util.py | 233 | Create and initialize AdamW optimizer, optionally loading from checkpoint. Args: model_parameters: Iterator | STRING |
| HIGH | src/tabpfn/preprocessing/datetimes.py | 95 | Fit one encoder per point in time in `X`, refusing a date it cannot. Args: X: The input data, befor | STRING |
| HIGH | src/tabpfn/preprocessing/datetimes.py | 111 | `fit(X).transform(X)`, encoding each date column only once. Expansion changes the column count: `feature_names_ | STRING |
| HIGH | src/tabpfn/preprocessing/ensemble.py | 542 | Keep every non-majority row and allocate the rest to the majority group. The majority is the single group whose siz | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_consistency.py | 48 | logger = logging.getLogger(__name__) | CODE |
| LOW | tests/conftest.py | 49 | def set_global_seed() -> None: | CODE |
| LOW | tests/test_preprocessing/test_pipeline_consistency.py | 35 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/classifier.py | 115 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/__init__.py | 59 | __all__ = [ | CODE |
| LOW⚡ | src/tabpfn/browser_auth.py | 38 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/model_loading.py | 60 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/inference.py | 426 | def _set_models(self, models: list[Architecture]) -> None: | CODE |
| LOW | src/tabpfn/inference.py | 492 | def _set_models(self, models: list[Architecture]) -> None: | CODE |
| LOW | src/tabpfn/inference.py | 530 | def _set_models(self, models: list[Architecture]) -> None: | CODE |
| LOW | src/tabpfn/inference.py | 1716 | def set_dtype(self, dtype: torch.dtype) -> None: | CODE |
| LOW | src/tabpfn/regressor.py | 118 | logger = logging.getLogger(__name__) | CODE |
| LOW | …bpfn/architectures/shared/workaround_mps_linear_bug.py | 28 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/finetuning/finetuned_regressor.py | 30 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/finetuning/finetuned_regressor.py | 370 | def _setup_batch(self, batch: RegressorBatch) -> None: # type: ignore[override] | CODE |
| LOW | src/tabpfn/finetuning/_torch_compat.py | 53 | __all__ = [ | CODE |
| LOW | src/tabpfn/finetuning/__init__.py | 15 | __all__ = [ | CODE |
| LOW | src/tabpfn/finetuning/train_util.py | 25 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/finetuning/finetuned_base.py | 62 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/finetuning/finetuned_base.py | 600 | def _setup_batch(self, batch: ClassifierBatch | RegressorBatch) -> None: | CODE |
| LOW | src/tabpfn/finetuning/finetuned_classifier.py | 27 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/tabpfn/finetuning/finetuned_classifier.py | 237 | def _setup_batch(self, batch: ClassifierBatch) -> None: # type: ignore[override] | CODE |
| LOW | src/tabpfn/visualisation/__init__.py | 7 | __all__ = ["plot_regression_distribution"] | CODE |
| LOW | src/tabpfn/preprocessing/configs.py | 193 | __all__ = [ | CODE |
| LOW | src/tabpfn/preprocessing/presets.py | 85 | __all__ = [ | CODE |
| LOW | src/tabpfn/preprocessing/datetimes.py | 37 | __all__ = ["DateTransformer"] | CODE |
| LOW | src/tabpfn/preprocessing/__init__.py | 27 | __all__ = [ | CODE |
| LOW | src/tabpfn/preprocessing/text.py | 50 | __all__ = ["TextTransformer"] | CODE |
| LOW | src/tabpfn/preprocessing/torch/__init__.py | 29 | __all__ = [ | CODE |
| LOW | …bpfn/preprocessing/steps/differentiable_z_norm_step.py | 48 | __all__ = [ | CODE |
| LOW | …eprocessing/steps/reshape_feature_distribution_step.py | 776 | __all__ = [ | CODE |
| LOW | …reprocessing/steps/encode_categorical_features_step.py | 467 | __all__ = [ | CODE |
| LOW | …c/tabpfn/preprocessing/steps/safe_power_transformer.py | 211 | __all__ = [ | CODE |
| LOW | …n/preprocessing/steps/add_fingerprint_features_step.py | 158 | __all__ = [ | CODE |
| LOW | src/tabpfn/preprocessing/steps/__init__.py | 36 | __all__ = [ | CODE |
| LOW | …n/preprocessing/steps/adaptive_quantile_transformer.py | 185 | __all__ = [ | CODE |
| LOW | src/tabpfn/preprocessing/steps/kdi_transformer.py | 165 | __all__ = [ | CODE |
| LOW | …fn/preprocessing/steps/squashing_scaler_transformer.py | 371 | __all__ = ["SquashingScaler"] | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_estimators.py | 313 | CODE | |
| LOW | …reprocessing/test_reshape_feature_distribution_step.py | 335 | CODE | |
| LOW | src/tabpfn/classifier.py | 610 | CODE | |
| LOW | src/tabpfn/classifier.py | 1904 | CODE | |
| LOW | src/tabpfn/model_loading.py | 267 | CODE | |
| LOW | src/tabpfn/model_loading.py | 360 | CODE | |
| LOW | src/tabpfn/model_loading.py | 415 | CODE | |
| LOW | src/tabpfn/model_loading.py | 670 | CODE | |
| LOW | src/tabpfn/model_loading.py | 1139 | CODE | |
| LOW | src/tabpfn/utils.py | 325 | CODE | |
| LOW | src/tabpfn/regressor.py | 635 | CODE | |
| LOW | src/tabpfn/regressor.py | 1795 | CODE | |
| LOW | src/tabpfn/regressor.py | 2155 | CODE | |
| LOW | src/tabpfn/misc/debug_versions.py | 188 | CODE | |
| LOW | src/tabpfn/misc/debug_versions.py | 269 | CODE | |
| LOW | src/tabpfn/misc/debug_versions.py | 347 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v2_6.py | 701 | CODE | |
| LOW | src/tabpfn/architectures/interface.py | 44 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v3.py | 1888 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v3.py | 2313 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v2_5.py | 703 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v3_5.py | 2275 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v3_5.py | 2832 | CODE | |
| LOW | src/tabpfn/architectures/tabpfn_v2.py | 799 | CODE | |
| LOW | src/tabpfn/finetuning/finetuned_base.py | 763 | CODE | |
| LOW | src/tabpfn/preprocessing/clean.py | 263 | CODE | |
| LOW | src/tabpfn/preprocessing/torch/torch_svd.py | 76 | CODE | |
| LOW | …eprocessing/steps/reshape_feature_distribution_step.py | 191 | CODE | |
| LOW | …eprocessing/steps/reshape_feature_distribution_step.py | 274 | CODE | |
| LOW | …n/preprocessing/steps/add_fingerprint_features_step.py | 68 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | src/tabpfn/browser_auth.py | 629 | ' 4. Set the environment variable: export TABPFN_TOKEN="<your-api-key>"\n' | CODE |
| HIGH | src/tabpfn/browser_auth.py | 631 | ' import os; os.environ["TABPFN_TOKEN"] = "<your-api-key>"' | CODE |
| HIGH | src/tabpfn/errors.py | 49 | ' export TABPFN_TOKEN="<your-api-key>"\n' | CODE |
| HIGH | src/tabpfn/errors.py | 51 | ' import os; os.environ["TABPFN_TOKEN"] = "<your-api-key>"' | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_preprocessing/test_pipeline_consistency.py | 425 | except Exception as e: | CODE |
| MEDIUM⚡ | examples/sagemaker.py | 348 | print(f"Error parsing JSON response: {e}") | CODE |
| LOW | src/tabpfn/classifier.py | 927 | except Exception as e: # noqa: BLE001 | CODE |
| LOW⚡ | src/tabpfn/browser_auth.py | 137 | except Exception: | CODE |
| LOW⚡ | src/tabpfn/browser_auth.py | 207 | except Exception: | CODE |
| LOW | src/tabpfn/browser_auth.py | 166 | except Exception as exc: | CODE |
| LOW | src/tabpfn/browser_auth.py | 331 | except Exception: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/browser_auth.py | 507 | except Exception: | CODE |
| LOW | src/tabpfn/model_loading.py | 343 | except Exception as e: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/model_loading.py | 403 | except Exception: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/model_loading.py | 408 | except Exception as e: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/model_loading.py | 570 | except Exception as e: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/model_loading.py | 581 | except Exception as e: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/model_loading.py | 609 | except Exception as e: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/regressor.py | 1082 | except Exception as e: # noqa: BLE001 | CODE |
| LOW | src/tabpfn/preprocessing/steps/kdi_transformer.py | 161 | except Exception: # noqa: BLE001 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | pyproject.toml | 155 | # "DTZ", # One day I should know how to utilize timezones and dates... | COMMENT |
| MEDIUM | tests/test_finetuning_classifier.py | 1631 | n_total = 50 # Increased slightly for more robust testing | CODE |
| MEDIUM | …t_torch_preprocessing/test_torch_soft_clip_outliers.py | 58 | """Test that two-pass approach produces more robust bounds.""" | STRING |
| MEDIUM | src/tabpfn/inference_tuning.py | 391 | """Selects the robust optimal threshold for the given metric. | STRING |
| LOW⚡ | src/tabpfn/parallel_execute.py | 85 | # If we only have one device then just use the current thread to avoid overhead. | COMMENT |
| MEDIUM | src/tabpfn/preprocessing/configs.py | 79 | "robust", # a standard sklearn robust scaler | CODE |
| MEDIUM | src/tabpfn/preprocessing/steps/preprocessing_helpers.py | 559 | # TODO: Could utilize the categorical dtype values directly instead of "auto" | COMMENT |
| MEDIUM | …fn/preprocessing/steps/squashing_scaler_transformer.py | 88 | r"""Perform robust centering and scaling followed by soft clipping. | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | examples/finetune_classifier.py | 41 | # ============================================================================= | COMMENT |
| LOW | examples/sagemaker.py | 61 | # | COMMENT |
| LOW | examples/finetune_regressor.py | 41 | # | COMMENT |
| LOW | .github/workflows/claude-code-review.yml | 21 | COMMENT | |
| LOW | .github/workflows/assign-pr-reviewer.yml | 1 | # When a PR is opened from a fork or by dependabot, request a review from a randomly | COMMENT |
| LOW | .github/workflows/ci.yml | 121 | name: Save model cache | COMMENT |
| LOW | .github/workflows/ci.yml | 141 | # only lever available: Linux lets a process request that state with | COMMENT |
| LOW | src/tabpfn/misc/_sklearn_compat.py | 1001 | COMMENT | |
| LOW | src/tabpfn/preprocessing/clean.py | 301 | ) | COMMENT |
| LOW | src/tabpfn/preprocessing/clean.py | 321 | # `np.nan` instead of `pd.NA`. | COMMENT |
| LOW | …c/tabpfn/preprocessing/torch/torch_squashing_scaler.py | 21 | from __future__ import annotations | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/tabpfn/classifier.py | 254 | CODE | |
| LOW | src/tabpfn/regressor.py | 283 | CODE | |
| LOW | src/tabpfn/misc/_sklearn_compat.py | 448 | CODE | |
| LOW | src/tabpfn/misc/_sklearn_compat.py | 502 | CODE | |
| LOW | src/tabpfn/finetuning/finetuned_regressor.py | 259 | CODE | |
| LOW | src/tabpfn/finetuning/finetuned_base.py | 448 | CODE | |
| LOW | src/tabpfn/finetuning/finetuned_classifier.py | 143 | CODE | |
| LOW | src/tabpfn/preprocessing/ensemble.py | 91 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/tabpfn/model_loading.py | 350 | # Check if this is an authentication/gating error | COMMENT |
| LOW | src/tabpfn/utils.py | 218 | # Check if the function is available in torch | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_parallel_execute.py | 15 | def test_function(device: torch.device) -> int: # noqa: ARG001 | CODE |
| LOW | tests/test_parallel_execute.py | 42 | def test_function(device: torch.device) -> int: # noqa: ARG001 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_finetuning_classifier.py | 1866 | # Step 3: Validate that columns are in the same order across all batches. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_finetuning_classifier.py | 1866 | # Step 3: Validate that columns are in the same order across all batches. | COMMENT |