Best Practices on Recommendation Systems
This report presents the forensic synthetic code analysis of recommenders-team/recommenders, a Python project with 21,829 GitHub stars. SynthScan v2.0 examined 52,430 lines of code across 337 source files, recording 558 pattern matches distributed across 17 syntactic categories. The overall adjusted score of 18.5 places this repository in the Moderate AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 558 distinct pattern matches across 17 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. 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 diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/databricks_install.py | 133 | def prepare_for_operationalization( | STRING |
| LOW | tests/conftest.py | 133 | def train_test_dummy_timestamp(pandas_dummy_timestamp): | CODE |
| LOW | tests/conftest.py | 435 | def dataset_ncf_files_unsorted(data_paths, dataset_ncf_files): | CODE |
| LOW | tests/conftest.py | 462 | def dataset_ncf_files_missing_column(data_paths, dataset_ncf_files): | CODE |
| LOW | tests/README.md | 168 | def test_sar_single_node_runs(notebooks, output_notebook, kernel_name): | CODE |
| LOW | tests/README.md | 203 | def test_sar_single_node_smoke(notebooks, output_notebook, kernel_name): | CODE |
| LOW | tests/smoke/examples/test_notebooks_python.py | 15 | def test_sar_single_node_smoke(notebooks, output_notebook, kernel_name): | CODE |
| LOW | tests/smoke/examples/test_notebooks_python.py | 32 | def test_baseline_deep_dive_smoke(notebooks, output_notebook, kernel_name): | CODE |
| LOW | tests/smoke/examples/test_notebooks_python.py | 97 | def test_lightgbm_quickstart_smoke(notebooks, output_notebook, kernel_name): | CODE |
| LOW | tests/smoke/examples/test_notebooks_python.py | 121 | def test_lightgbm_movielens_smoke(notebooks, output_notebook, kernel_name): | CODE |
| LOW | tests/smoke/examples/test_notebooks_pyspark.py | 45 | def test_mmlspark_lightgbm_criteo_smoke(notebooks, output_notebook, kernel_name): | CODE |
| LOW | …sts/unit/recommenders/datasets/test_python_splitter.py | 350 | def test_int_numpy_stratified_splitter(test_specs, python_int_dataset): | CODE |
| LOW | …sts/unit/recommenders/datasets/test_python_splitter.py | 394 | def test_float_numpy_stratified_splitter(test_specs, python_float_dataset): | CODE |
| LOW | tests/unit/recommenders/datasets/test_download_utils.py | 37 | def test_maybe_download_wrong_bytes(caplog, files_fixtures): | CODE |
| LOW | tests/unit/recommenders/datasets/test_download_utils.py | 50 | def test_maybe_download_maybe(caplog, files_fixtures): | CODE |
| LOW | tests/unit/recommenders/datasets/test_download_utils.py | 64 | def test_maybe_download_retry(caplog): | CODE |
| LOW | tests/unit/recommenders/datasets/test_download_utils.py | 74 | def test_maybe_download_sets_default_timeout(tmp_path, monkeypatch): | CODE |
| LOW | tests/unit/recommenders/datasets/test_download_utils.py | 112 | def test_maybe_download_redownloads_corrupt_zip(tmp, caplog): | CODE |
| LOW | …sts/unit/recommenders/datasets/test_pandas_df_utils.py | 34 | def test_negative_feedback_sampler(): | CODE |
| LOW | tests/unit/recommenders/utils/test_gpu_utils.py | 24 | def test_get_number_gpus_without_torch(monkeypatch): | CODE |
| LOW | tests/unit/recommenders/utils/test_gpu_utils.py | 53 | def test_clear_memory_all_gpus(): | CODE |
| LOW | tests/unit/recommenders/utils/test_python_utils.py | 98 | def test_get_top_k_scored_items(scores): | CODE |
| LOW | tests/unit/recommenders/utils/test_notebook_utils.py | 120 | def test_notebook_execution_with_parameters( | STRING |
| LOW | tests/unit/recommenders/utils/test_notebook_utils.py | 141 | def test_notebook_execution_value_error_fails( | STRING |
| LOW | tests/unit/recommenders/utils/test_general_utils.py | 14 | def test_get_number_processors(): | CODE |
| LOW | tests/unit/recommenders/utils/test_timer.py | 29 | def test_interval_before_stop(t): | CODE |
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 302 | def test_get_popularity_based_topk(header): | CODE |
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 324 | def test_get_normalized_scores(header): | CODE |
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 383 | def test_match_similarity_type_from_json_file(header): | CODE |
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 406 | def test_dataset_with_duplicates(header): | CODE |
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 419 | def test_get_topk_most_similar_users(header): | CODE |
| LOW | tests/unit/recommenders/models/test_ncf_dataset.py | 79 | def test_datafile_init_unsorted(dataset_ncf_files_unsorted): | CODE |
| LOW | tests/unit/recommenders/models/test_ncf_dataset.py | 107 | def test_datafile_missing_column(dataset_ncf_files_missing_column): | CODE |
| LOW | tests/unit/recommenders/models/test_tfidf_utils.py | 111 | def test_recommend_top_k_items(model_fit, df_clean): | CODE |
| LOW | tests/unit/recommenders/models/test_tfidf_utils.py | 116 | def test_get_top_k_recommendations(model_fit, df_clean): | CODE |
| LOW | tests/unit/recommenders/models/test_deeprec_model.py | 117 | def test_xdeepfm_component_definition(deeprec_resource_path): | CODE |
| LOW | tests/unit/recommenders/models/test_deeprec_model.py | 144 | def test_dkn_component_definition(dkn_files): | CODE |
| LOW | tests/unit/recommenders/models/test_deeprec_model.py | 227 | def test_slirec_component_definition(sequential_files, deeprec_config_path): | CODE |
| LOW | tests/unit/recommenders/models/test_deeprec_model.py | 264 | def test_nextitnet_component_definition(sequential_files, deeprec_config_path): | CODE |
| LOW | tests/unit/recommenders/models/test_deeprec_model.py | 302 | def test_sum_component_definition(sequential_files, deeprec_config_path): | CODE |
| LOW | tests/unit/recommenders/models/test_deeprec_model.py | 340 | def test_lightgcn_component_definition(): | CODE |
| LOW | tests/unit/recommenders/models/test_sasrec_model.py | 178 | def test_split_default_parameters(temp_data_file): | CODE |
| LOW | tests/unit/recommenders/models/test_sasrec_model.py | 241 | def test_split_invalid_min_interactions(temp_data_file): | CODE |
| LOW | tests/unit/recommenders/models/test_newsrec_model.py | 21 | def test_nrms_component_definition(mind_resource_path): | CODE |
| LOW | tests/unit/recommenders/models/test_newsrec_model.py | 51 | def test_naml_component_definition(mind_resource_path): | CODE |
| LOW | tests/unit/recommenders/models/test_newsrec_model.py | 85 | def test_npa_component_definition(mind_resource_path): | CODE |
| LOW | tests/unit/recommenders/models/test_newsrec_model.py | 115 | def test_lstur_component_definition(mind_resource_path): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_model.py | 56 | def test_embedding_dot_bias_weight_method(sample_classes): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_model.py | 72 | def test_embedding_dot_bias_from_classes(sample_classes): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_model.py | 86 | def test_embedding_dot_bias_init(sample_model_params): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_model.py | 98 | def test_embedding_dot_bias_forward(sample_model_params): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_utils.py | 33 | def test_cartesian_product_two_arrays(): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_utils.py | 41 | def test_cartesian_product_three_arrays(): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_utils.py | 61 | def test_cartesian_product_single_array(): | CODE |
| LOW | tests/unit/recommenders/models/test_embdotbias_utils.py | 68 | def test_cartesian_product_empty_array(): | CODE |
| LOW | tests/unit/recommenders/models/test_wide_deep_utils.py | 178 | def test_wide_deep_model_with_item_features(pd_df): | CODE |
| LOW | tests/unit/recommenders/models/test_wide_deep_utils.py | 235 | def test_recommend_k_items_with_item_features(pd_df): | CODE |
| LOW | tests/unit/recommenders/models/test_wide_deep_utils.py | 296 | def test_seed_reproducibility(pd_df): | CODE |
| LOW | tests/unit/recommenders/tuning/test_nni_utils.py | 58 | def test_get_experiment_status(): | CODE |
| LOW | tests/unit/recommenders/tuning/test_nni_utils.py | 71 | def test_check_experiment_status_done(): | CODE |
| 156 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | tests/conftest.py | 0 | helper function to generate random timestamps. reference: https://stackoverflow.com/questions/41006182/generate-random-d | STRING |
| HIGH | …sts/unit/recommenders/datasets/test_python_splitter.py | 0 | helper function to generate random timestamps. reference: https://stackoverflow.com/questions/41006182/generate-random-d | STRING |
| HIGH | tests/unit/recommenders/datasets/test_sparse.py | 0 | helper function to generate random timestamps. reference: https://stackoverflow.com/questions/41006182/generate-random-d | STRING |
| HIGH | recommenders/models/newsrec/io/mind_all_iterator.py | 0 | initialize an iterator. create necessary placeholders for the model. args: hparams (object): global hyper-parameters. so | STRING |
| HIGH | recommenders/models/deeprec/io/iterator.py | 0 | initialize an iterator. create necessary placeholders for the model. args: hparams (object): global hyper-parameters. so | STRING |
| HIGH | recommenders/models/deeprec/io/dkn_iterator.py | 0 | initialize an iterator. create necessary placeholders for the model. args: hparams (object): global hyper-parameters. so | STRING |
| HIGH | recommenders/models/deeprec/io/nextitnet_iterator.py | 0 | initialize an iterator. create necessary placeholders for the model. args: hparams (object): global hyper-parameters. so | STRING |
| HIGH | recommenders/models/deeprec/io/sequential_iterator.py | 0 | initialize an iterator. create necessary placeholders for the model. args: hparams (object): global hyper-parameters. so | STRING |
| HIGH | recommenders/models/newsrec/models/lstur.py | 0 | initialization steps for nrms. compared with the basemodel, nrms need word embedding. after creating word embedding matr | STRING |
| HIGH | recommenders/models/newsrec/models/naml.py | 0 | initialization steps for nrms. compared with the basemodel, nrms need word embedding. after creating word embedding matr | STRING |
| HIGH | recommenders/models/newsrec/models/nrms.py | 0 | initialization steps for nrms. compared with the basemodel, nrms need word embedding. after creating word embedding matr | STRING |
| HIGH | recommenders/models/newsrec/models/npa.py | 0 | initialization steps for nrms. compared with the basemodel, nrms need word embedding. after creating word embedding matr | STRING |
| HIGH | recommenders/models/newsrec/models/lstur.py | 0 | build npa model and scorer. returns: object: a model used to train. object: a model used to evaluate and inference. | STRING |
| HIGH | recommenders/models/newsrec/models/naml.py | 0 | build npa model and scorer. returns: object: a model used to train. object: a model used to evaluate and inference. | STRING |
| HIGH | recommenders/models/newsrec/models/nrms.py | 0 | build npa model and scorer. returns: object: a model used to train. object: a model used to evaluate and inference. | STRING |
| HIGH | recommenders/models/newsrec/models/npa.py | 0 | build npa model and scorer. returns: object: a model used to train. object: a model used to evaluate and inference. | STRING |
| HIGH | recommenders/models/newsrec/models/lstur.py | 0 | the main function to create user encoder of npa. args: titleencoder (object): the news encoder of npa. return: object: t | STRING |
| HIGH | recommenders/models/newsrec/models/nrms.py | 0 | the main function to create user encoder of npa. args: titleencoder (object): the news encoder of npa. return: object: t | STRING |
| HIGH | recommenders/models/newsrec/models/npa.py | 0 | the main function to create user encoder of npa. args: titleencoder (object): the news encoder of npa. return: object: t | STRING |
| HIGH | recommenders/models/newsrec/models/lstur.py | 0 | the main function to create news encoder of npa. args: embedding_layer (object): a word embedding layer. return: object: | STRING |
| HIGH | recommenders/models/newsrec/models/nrms.py | 0 | the main function to create news encoder of npa. args: embedding_layer (object): a word embedding layer. return: object: | STRING |
| HIGH | recommenders/models/newsrec/models/npa.py | 0 | the main function to create news encoder of npa. args: embedding_layer (object): a word embedding layer. return: object: | STRING |
| HIGH | recommenders/models/newsrec/models/base_model.py | 0 | initializing the model. create common logics which are needed by all sequential models, such as loss function, parameter | STRING |
| HIGH | recommenders/models/deeprec/models/base_model.py | 0 | initializing the model. create common logics which are needed by all sequential models, such as loss function, parameter | STRING |
| HIGH | …els/deeprec/models/sequential/sequential_base_model.py | 0 | initializing the model. create common logics which are needed by all sequential models, such as loss function, parameter | STRING |
| HIGH | recommenders/models/newsrec/models/base_model.py | 0 | evaluate the given file and returns some evaluation metrics. args: filename (str): a file name that will be evaluated. r | STRING |
| HIGH | recommenders/models/deeprec/models/base_model.py | 0 | evaluate the given file and returns some evaluation metrics. args: filename (str): a file name that will be evaluated. r | STRING |
| HIGH | recommenders/models/deeprec/models/dkn_item2item.py | 0 | evaluate the given file and returns some evaluation metrics. args: filename (str): a file name that will be evaluated. r | STRING |
| HIGH | recommenders/models/deeprec/io/iterator.py | 0 | construct a dictionary that maps graph elements to values. args: data_dict (dict): a dictionary that maps string name to | STRING |
| HIGH | recommenders/models/deeprec/io/dkn_iterator.py | 0 | construct a dictionary that maps graph elements to values. args: data_dict (dict): a dictionary that maps string name to | STRING |
| HIGH | recommenders/models/deeprec/io/sequential_iterator.py | 0 | construct a dictionary that maps graph elements to values. args: data_dict (dict): a dictionary that maps string name to | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | …models/deeprec/models/sequential/rnn_cell_implement.py | 14 | # ============================================================================== | COMMENT |
| MEDIUM | recommenders/models/wide_deep/wide_deep_utils.py | 184 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | recommenders/models/wide_deep/wide_deep_utils.py | 186 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | recommenders/models/wide_deep/wide_deep_utils.py | 427 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | recommenders/models/wide_deep/wide_deep_utils.py | 429 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/self-hosted-runner.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/self-hosted-runner.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/compshare-vm.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/compshare-vm.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/unit-tests.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/unit-tests.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/sarplus.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/sarplus.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 9 | # ┌───────────── minute (0 - 59) | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 10 | # │ ┌───────────── hour (0 - 23) | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 11 | # │ │ ┌───────────── day of the month (1 - 31) | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 12 | # │ │ │ ┌───────────── month (1 - 12 or JAN-DEC) | COMMENT |
| MEDIUM⚡ | .github/workflows/spark-nightly.yml | 13 | # │ │ │ │ ┌───────────── day of the week (0 - 6 or SUN-SAT) | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 9 | # ┌───────────── minute (0 - 59) | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 10 | # │ ┌───────────── hour (0 - 23) | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 11 | # │ │ ┌───────────── day of the month (1 - 31) | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 12 | # │ │ │ ┌───────────── month (1 - 12 or JAN-DEC) | COMMENT |
| MEDIUM⚡ | .github/workflows/gpu-nightly.yml | 13 | # │ │ │ │ ┌───────────── day of the week (0 - 6 or SUN-SAT) | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 4 | # --------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 9 | # ┌───────────── minute (0 - 59) | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 10 | # │ ┌───────────── hour (0 - 23) | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 11 | # │ │ ┌───────────── day of the month (1 - 31) | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 12 | # │ │ │ ┌───────────── month (1 - 12 or JAN-DEC) | COMMENT |
| MEDIUM⚡ | .github/workflows/cpu-nightly.yml | 13 | # │ │ │ │ ┌───────────── day of the week (0 - 6 or SUN-SAT) | COMMENT |
| MEDIUM | .github/workflows/update_documentation.yml | 1 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | .github/workflows/update_documentation.yml | 4 | # --------------------------------------------------------- | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | recommenders/utils/tf_utils.py | 272 | self.summary_writer = tf.compat.v1.summary.FileWriterCache.get( | CODE |
| CRITICAL | recommenders/models/newsrec/models/base_model.py | 68 | tf.compat.v1.keras.backend.set_session(sess) | CODE |
| CRITICAL | recommenders/models/deeprec/models/dkn.py | 402 | initializer=tf.compat.v1.keras.initializers.VarianceScaling( | CODE |
| CRITICAL | recommenders/models/deeprec/models/dkn_item2item.py | 77 | initializer=tf.compat.v1.keras.initializers.VarianceScaling( | CODE |
| CRITICAL⚡ | recommenders/models/deeprec/models/base_model.py | 183 | return tf.compat.v1.keras.initializers.VarianceScaling( | CODE |
| CRITICAL⚡ | recommenders/models/deeprec/models/base_model.py | 190 | return tf.compat.v1.keras.initializers.VarianceScaling( | CODE |
| CRITICAL⚡ | recommenders/models/deeprec/models/base_model.py | 197 | return tf.compat.v1.keras.initializers.VarianceScaling( | CODE |
| CRITICAL⚡ | recommenders/models/deeprec/models/base_model.py | 204 | return tf.compat.v1.keras.initializers.VarianceScaling( | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/ci/compshare/utils.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | tools/ci/compshare/utils.sh | 21 | # "GPUType": "P40", | COMMENT |
| LOW | tools/ci/compshare/utils.sh | 121 | COMMENT | |
| LOW | tools/ci/compshare/setup_vm.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | tools/ci/compshare/install_docker.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | tools/ci/compshare/delete_vm.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | tests/test_groups.yml | 1 | # Copyright (c) Recommenders contributors. | COMMENT |
| LOW | tests/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/smoke/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/smoke/recommenders/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/smoke/recommenders/models/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/smoke/examples/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/recommenders/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/recommenders/datasets/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/recommenders/utils/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/recommenders/models/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/recommenders/tuning/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/recommenders/evaluation/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/unit/examples/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/responsible_ai/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/responsible_ai/recommenders/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/responsible_ai/recommenders/datasets/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/security/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/integration/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/integration/recommenders/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/integration/recommenders/utils/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/data_validation/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/data_validation/recommenders/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/data_validation/recommenders/datasets/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/data_validation/examples/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/regression/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/performance/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/performance/recommenders/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/performance/recommenders/evaluation/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/functional/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | tests/functional/examples/__init__.py | 1 | # Needed to execute the AzureML tests | COMMENT |
| LOW | contrib/sarplus/README.md | 81 | ) | COMMENT |
| LOW | contrib/sarplus/README.md | 101 | # ```python | COMMENT |
| LOW | contrib/sarplus/README.md | 121 | # col_rating="rating", | COMMENT |
| LOW | contrib/sarplus/python/src/pysarplus.cpp | 1 | /* | COMMENT |
| LOW | recommenders/utils/notebook_memory_management.py | 1 | # Original code: https://raw.githubusercontent.com/miguelgfierro/codebase/master/python/system/notebook_memory_managemen | COMMENT |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 1 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved. | COMMENT |
| LOW | …amples/07_tutorials/KDD2020-tutorial/reco_gpu_kdd.yaml | 1 | # | COMMENT |
| LOW | …amples/07_tutorials/KDD2020-tutorial/reco_cpu_kdd.yaml | 1 | # | COMMENT |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/data_helper.py | 61 | # Returns: | COMMENT |
| LOW | .github/workflows/self-hosted-runner.yml | 1 | # --------------------------------------------------------- | COMMENT |
| LOW | .github/workflows/compshare-vm.yml | 1 | # --------------------------------------------------------- | COMMENT |
| LOW | .github/workflows/sarplus.yml | 1 | # --------------------------------------------------------- | COMMENT |
| LOW | .github/workflows/spark-nightly.yml | 1 | # --------------------------------------------------------- | COMMENT |
| LOW | .github/workflows/gpu-nightly.yml | 1 | # --------------------------------------------------------- | COMMENT |
| LOW | .github/workflows/cpu-nightly.yml | 1 | # --------------------------------------------------------- | COMMENT |
| LOW | .github/workflows/tools/compshare/utils.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | .github/workflows/tools/compshare/utils.sh | 21 | # "GPUType": "P40", | COMMENT |
| LOW | .github/workflows/tools/compshare/utils.sh | 181 | response="$(curl -sSf "${request_url}")" | COMMENT |
| LOW | .github/workflows/tools/compshare/utils.sh | 361 | | .[0] | [path(..)] | COMMENT |
| LOW | .github/workflows/tools/compshare/setup_vm.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | .github/workflows/tools/compshare/setup_vm.sh | 21 | # | COMMENT |
| LOW | .github/workflows/tools/compshare/install_docker.sh | 1 | #! /bin/bash - | COMMENT |
| LOW | .github/workflows/tools/compshare/delete_vm.sh | 1 | #! /bin/bash - | COMMENT |
| 1 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/unit/recommenders/utils/test_tf_utils.py | 41 | CODE | |
| LOW | tests/unit/recommenders/models/test_sasrec_model.py | 40 | CODE | |
| LOW | recommenders/datasets/mind.py | 274 | CODE | |
| LOW | recommenders/datasets/mind.py | 409 | CODE | |
| LOW | recommenders/datasets/pandas_df_utils.py | 182 | CODE | |
| LOW | recommenders/datasets/download_utils.py | 20 | CODE | |
| LOW | recommenders/datasets/wikidata.py | 263 | CODE | |
| LOW | recommenders/datasets/amazon_reviews.py | 192 | CODE | |
| LOW | recommenders/datasets/amazon_reviews.py | 266 | CODE | |
| LOW | recommenders/datasets/amazon_reviews.py | 459 | CODE | |
| LOW | recommenders/utils/gpu_utils.py | 101 | CODE | |
| LOW | recommenders/utils/gpu_utils.py | 108 | CODE | |
| LOW | recommenders/utils/tf_utils.py | 25 | CODE | |
| LOW | recommenders/utils/tf_utils.py | 40 | CODE | |
| LOW | recommenders/utils/notebook_utils.py | 130 | CODE | |
| LOW | recommenders/models/newsrec/newsrec_utils.py | 82 | CODE | |
| LOW | recommenders/models/deeprec/deeprec_utils.py | 134 | CODE | |
| LOW | recommenders/models/deeprec/deeprec_utils.py | 514 | CODE | |
| LOW | recommenders/models/deeprec/io/nextitnet_iterator.py | 72 | CODE | |
| LOW | recommenders/models/deeprec/io/sequential_iterator.py | 277 | CODE | |
| LOW | recommenders/models/deeprec/models/dkn.py | 349 | CODE | |
| LOW | recommenders/models/deeprec/models/base_model.py | 169 | CODE | |
| LOW | recommenders/models/deeprec/models/base_model.py | 215 | CODE | |
| LOW | recommenders/models/deeprec/models/base_model.py | 274 | CODE | |
| LOW | recommenders/models/deeprec/models/base_model.py | 339 | CODE | |
| LOW | recommenders/models/deeprec/models/base_model.py | 652 | CODE | |
| LOW | recommenders/models/deeprec/models/xDeepFM.py | 161 | CODE | |
| LOW | recommenders/models/deeprec/models/xDeepFM.py | 295 | CODE | |
| LOW | …els/deeprec/models/sequential/sequential_base_model.py | 76 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 128 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 393 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 594 | CODE | |
| LOW | recommenders/models/deeprec/models/graphrec/lightgcn.py | 372 | CODE | |
| LOW | recommenders/models/rlrmc/conjugate_gradient_ms.py | 56 | CODE | |
| LOW | recommenders/models/sar/sar_singlenode.py | 226 | CODE | |
| LOW | recommenders/models/ncf/ncf_singlenode.py | 180 | CODE | |
| LOW | recommenders/models/ncf/dataset.py | 142 | CODE | |
| LOW | recommenders/models/ncf/dataset.py | 404 | CODE | |
| LOW | recommenders/models/wide_deep/wide_deep_utils.py | 509 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 461 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 657 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 784 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 881 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 22 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 236 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 293 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 356 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 487 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 552 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 635 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 742 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | tools/databricks_install.py | 238 | # Create a cluster if flagged | STRING |
| MEDIUM | tools/ci/compshare/utils.sh | 127 | # Create a VM instance | COMMENT |
| MEDIUM | tools/ci/compshare/utils.sh | 243 | # Create a VM with random names and password from available types | COMMENT |
| MEDIUM | tools/ci/compshare/setup_vm.sh | 7 | # Create a CompShare VM and prepare the environment for testing | COMMENT |
| MEDIUM | tests/unit/recommenders/models/test_embdotbias_utils.py | 79 | # Create a dummy model | COMMENT |
| MEDIUM | recommenders/utils/notebook_utils.py | 59 | # Define a regular expression pattern to match parameter assignments and ignore comments | COMMENT |
| MEDIUM | recommenders/utils/notebook_utils.py | 98 | # Create an execution preprocessor | COMMENT |
| MEDIUM | recommenders/models/deeprec/models/dkn.py | 385 | # Create a convolution + maxpool layer for each filter size | COMMENT |
| MEDIUM | recommenders/models/embdotbias/model.py | 99 | # Create a mapping from entity ID (user or item) to its integer index in the embedding matrix | COMMENT |
| MEDIUM | recommenders/models/tfidf/tfidf_utils.py | 37 | # Initialize other variables used in this class | COMMENT |
| MEDIUM | recommenders/models/rbm/rbm.py | 451 | # Create the data pipeline for faster training | COMMENT |
| MEDIUM | .github/workflows/tools/compshare/utils.sh | 192 | # Create a VM instance | COMMENT |
| MEDIUM | .github/workflows/tools/compshare/utils.sh | 369 | # Create a VM with random names and password from available types | COMMENT |
| MEDIUM | .github/workflows/tools/compshare/setup_vm.sh | 7 | # Create a CompShare VM and prepare the environment for testing | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | recommenders/datasets/split_utils.py | 10 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/datasets/pandas_df_utils.py | 17 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/datasets/wikidata.py | 11 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/utils/k8s_utils.py | 7 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/utils/gpu_utils.py | 12 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/newsrec/io/mind_iterator.py | 11 | __all__ = ["MINDIterator"] | CODE |
| LOW | recommenders/models/newsrec/io/mind_all_iterator.py | 11 | __all__ = ["MINDAllIterator"] | CODE |
| LOW | recommenders/models/newsrec/models/lstur.py | 15 | __all__ = ["LSTURModel"] | CODE |
| LOW | recommenders/models/newsrec/models/naml.py | 12 | __all__ = ["NAMLModel"] | CODE |
| LOW | recommenders/models/newsrec/models/base_model.py | 15 | __all__ = ["BaseModel"] | CODE |
| LOW | recommenders/models/newsrec/models/nrms.py | 11 | __all__ = ["NRMSModel"] | CODE |
| LOW | recommenders/models/newsrec/models/npa.py | 11 | __all__ = ["NPAModel"] | CODE |
| LOW | recommenders/models/deeprec/io/dkn_iterator.py | 10 | __all__ = ["DKNTextIterator"] | CODE |
| LOW | recommenders/models/deeprec/io/nextitnet_iterator.py | 12 | __all__ = ["NextItNetIterator"] | CODE |
| LOW | recommenders/models/deeprec/io/sequential_iterator.py | 12 | __all__ = ["SequentialIterator"] | CODE |
| LOW | recommenders/models/deeprec/models/dkn.py | 9 | __all__ = ["DKN"] | CODE |
| LOW | recommenders/models/deeprec/models/base_model.py | 14 | __all__ = ["BaseModel"] | CODE |
| LOW | recommenders/models/deeprec/models/xDeepFM.py | 10 | __all__ = ["XDeepFMModel"] | CODE |
| LOW | …els/deeprec/models/sequential/sequential_base_model.py | 14 | __all__ = ["SequentialBaseModel"] | CODE |
| LOW | …commenders/models/deeprec/models/sequential/sli_rec.py | 13 | __all__ = ["SLI_RECModel"] | CODE |
| LOW | recommenders/models/deeprec/models/sequential/caser.py | 9 | __all__ = ["CaserModel"] | CODE |
| LOW | recommenders/models/deeprec/models/sequential/asvd.py | 9 | __all__ = ["A2SVDModel"] | CODE |
| LOW | recommenders/models/deeprec/models/sequential/gru.py | 11 | __all__ = ["GRUModel"] | CODE |
| LOW | …mmenders/models/deeprec/models/sequential/nextitnet.py | 9 | __all__ = ["NextItNetModel"] | CODE |
| LOW | recommenders/models/deeprec/models/graphrec/lightgcn.py | 32 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/deeprec/DataModel/ImplicitCF.py | 18 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/rlrmc/RLRMCalgorithm.py | 17 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/embdotbias/training_utils.py | 18 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/ncf/ncf_singlenode.py | 13 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/ncf/dataset.py | 20 | logger = logging.getLogger(__name__) | CODE |
| LOW | recommenders/models/wide_deep/wide_deep_utils.py | 21 | logger = logging.getLogger(__name__) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 5 | CODE | |
| LOW | tests/unit/recommenders/models/test_embdotbias_model.py | 7 | CODE | |
| LOW | tests/unit/examples/test_notebooks_python.py | 5 | CODE | |
| LOW | tests/regression/test_compatibility_tf.py | 13 | CODE | |
| LOW | tests/regression/test_compatibility_tf.py | 14 | CODE | |
| LOW | contrib/sarplus/python/pysarplus/__init__.py | 6 | CODE | |
| LOW | contrib/sarplus/python/pysarplus/__init__.py | 7 | CODE | |
| LOW | recommenders/datasets/python_splitters.py | 4 | CODE | |
| LOW | recommenders/utils/notebook_memory_management.py | 14 | CODE | |
| LOW | recommenders/utils/notebook_memory_management.py | 15 | CODE | |
| LOW | recommenders/utils/notebook_memory_management.py | 16 | CODE | |
| LOW | recommenders/utils/notebook_memory_management.py | 17 | CODE | |
| LOW | recommenders/utils/spark_utils.py | 8 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 23 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 24 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 25 | CODE | |
| LOW | recommenders/models/deeprec/models/graphrec/lightgcn.py | 4 | CODE | |
| LOW | recommenders/models/rlrmc/conjugate_gradient_ms.py | 6 | CODE | |
| LOW | recommenders/models/rlrmc/conjugate_gradient_ms.py | 6 | CODE | |
| LOW | recommenders/models/embdotbias/training_utils.py | 9 | CODE | |
| LOW | recommenders/models/embdotbias/training_utils.py | 9 | CODE | |
| LOW | recommenders/models/embdotbias/training_utils.py | 9 | CODE | |
| LOW | recommenders/models/embdotbias/training_utils.py | 9 | CODE | |
| LOW | recommenders/models/embdotbias/training_utils.py | 9 | CODE | |
| LOW | recommenders/models/sar/__init__.py | 4 | CODE | |
| LOW | …odel_select_and_optimize/train_scripts/svd_training.py | 17 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/data_helper.py | 8 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 12 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 18 | CODE | |
| LOW | …les/07_tutorials/KDD2020-tutorial/utils/task_helper.py | 19 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | recommenders/models/deeprec/config/sli_rec.yaml | 12 | layer_sizes : [100, 64] # layers' size of DNN. In this example, DNN has two layers, and each layer has 100 hidden n | CODE |
| HIGH | recommenders/models/deeprec/config/nextitnet.yaml | 12 | layer_sizes : [100, 64] # layers' size of DNN. In this example, DNN has two layers, and each layer has 100 hidden n | CODE |
| HIGH | recommenders/models/deeprec/config/sum.yaml | 12 | layer_sizes : [100, 64] # layers' size of DNN. In this example, DNN has two layers, and each layer has 100 hidden n | CODE |
| HIGH | recommenders/models/deeprec/config/asvd.yaml | 12 | layer_sizes : [100, 64] # layers' size of DNN. In this example, DNN has two layers, and each layer has 100 hidden n | CODE |
| HIGH | recommenders/models/deeprec/config/caser.yaml | 12 | layer_sizes : [100, 64] # layers' size of DNN. In this example, DNN has two layers, and each layer has 100 hidden n | CODE |
| HIGH | recommenders/models/deeprec/config/gru.yaml | 12 | layer_sizes : [100, 64] # layers' size of DNN. In this example, DNN has two layers, and each layer has 100 hidden n | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/ci/compshare/utils.sh | 361 | # Set timeout to (5 + 5) * 18 = 180 seconds | COMMENT |
| LOW⚡ | …sts/unit/recommenders/datasets/test_pandas_df_utils.py | 173 | # Check if the dim is the same. | COMMENT |
| LOW⚡ | …sts/unit/recommenders/datasets/test_pandas_df_utils.py | 176 | # Check if the columns are converted successfully. | COMMENT |
| LOW⚡ | …sts/unit/recommenders/datasets/test_pandas_df_utils.py | 185 | # Check if the duplicated column entries are indexed correctly. | COMMENT |
| LOW⚡ | …sts/unit/recommenders/datasets/test_pandas_df_utils.py | 195 | # Check if the file is written successfully. | COMMENT |
| LOW | tests/unit/recommenders/models/test_sar_singlenode.py | 178 | # Set time_now to 60 days later | COMMENT |
| LOW | …unit/recommenders/evaluation/test_python_evaluation.py | 71 | # Check if _check_column_dtypes wraps the input function (i.e. returns the same output as the input function's) | COMMENT |
| LOW | contrib/sarplus/python/tests/test_pyspark_sar.py | 323 | # Set time_now to 60 days later | COMMENT |
| LOW | recommenders/utils/notebook_utils.py | 56 | # Check if the new value is a string and surround it with quotes if necessary | COMMENT |
| LOW | recommenders/models/tfidf/tfidf_utils.py | 104 | # Check if for BERT tokenization | COMMENT |
| LOW | recommenders/evaluation/spark_evaluation.py | 65 | # Check if inputs are Spark DataFrames. | COMMENT |
| LOW | recommenders/evaluation/spark_evaluation.py | 76 | # Check if columns exist. | COMMENT |
| LOW | recommenders/evaluation/spark_evaluation.py | 217 | # Check if inputs are Spark DataFrames. | COMMENT |
| LOW | recommenders/evaluation/spark_evaluation.py | 228 | # Check if columns exist. | COMMENT |
| LOW | .github/workflows/tools/compshare/utils.sh | 322 | # Check if the VM specification match the requirements. | COMMENT |
| LOW | .github/workflows/tools/compshare/utils.sh | 521 | # Set timeout to (5 + 5) * 30 = 300 seconds | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | contrib/sarplus/python/pysarplus/SARPlus.py | 29 | CODE | |
| LOW | recommenders/datasets/python_splitters.py | 44 | CODE | |
| LOW | recommenders/datasets/pandas_df_utils.py | 267 | CODE | |
| LOW | recommenders/datasets/movielens.py | 368 | CODE | |
| LOW | recommenders/datasets/spark_splitters.py | 48 | CODE | |
| LOW | recommenders/utils/plot.py | 4 | CODE | |
| LOW | recommenders/models/newsrec/models/base_model.py | 340 | CODE | |
| LOW | recommenders/models/deeprec/models/dkn_item2item.py | 129 | CODE | |
| LOW | recommenders/models/deeprec/models/base_model.py | 650 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 47 | CODE | |
| LOW | …models/deeprec/models/sequential/rnn_cell_implement.py | 312 | CODE | |
| LOW | recommenders/models/deeprec/models/graphrec/lightgcn.py | 217 | CODE | |
| LOW | recommenders/models/sar/sar_singlenode.py | 43 | CODE | |
| LOW | recommenders/models/ncf/ncf_singlenode.py | 27 | CODE | |
| LOW | recommenders/models/ncf/dataset.py | 304 | CODE | |
| LOW | recommenders/models/wide_deep/wide_deep_utils.py | 55 | CODE | |
| LOW | recommenders/models/wide_deep/wide_deep_utils.py | 188 | CODE | |
| LOW | recommenders/models/rbm/rbm.py | 17 | CODE | |
| LOW | recommenders/models/vae/standard_vae.py | 83 | CODE | |
| LOW | recommenders/models/vae/multinomial_vae.py | 98 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 167 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 255 | CODE | |
| LOW | recommenders/models/sasrec/model.py | 354 | CODE | |
| LOW | recommenders/evaluation/python_evaluation.py | 616 | CODE | |
| LOW | examples/06_benchmarks/benchmark_utils.py | 230 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | recommenders/datasets/pandas_df_utils.py | 87 | Converts an input dataframe to another dataframe in libffm format. A text file of the converted Dataframe is optiona | STRING |
| HIGH | recommenders/datasets/pandas_df_utils.py | 279 | Utility function to sample negative feedback from user-item interaction dataset. This negative sampling function wil | STRING |
| HIGH | recommenders/datasets/download_utils.py | 95 | Return a path to download data. If `path=None`, then it yields a temporal path that is eventually deleted, otherwise | STRING |
| HIGH | recommenders/datasets/movielens.py | 610 | Generate a fake movielens DataFrame with all columns. Args: size (int): number of rows to generate. | STRING |
| HIGH | recommenders/models/sasrec/util.py | 48 | Split user interactions into train/valid/test sets using leave-k-out strategy. For each user with enou | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/databricks_install.py | 106 | except Exception: | STRING |
| LOW | recommenders/datasets/criteo.py | 118 | except Exception: | CODE |
| LOW | recommenders/datasets/wikidata.py | 41 | except Exception as e: | CODE |
| LOW | recommenders/datasets/wikidata.py | 105 | except Exception as e: | CODE |
| LOW | recommenders/datasets/wikidata.py | 126 | except Exception as e: | CODE |
| LOW | recommenders/datasets/wikidata.py | 190 | except Exception as e: | STRING |
| LOW | recommenders/datasets/wikidata.py | 257 | except Exception as e: | STRING |
| LOW | recommenders/datasets/wikidata.py | 280 | except Exception as e: | STRING |
| LOW | recommenders/datasets/wikidata.py | 291 | except Exception as e: | STRING |
| MEDIUM | recommenders/datasets/wikidata.py | 38 | def wrapper(*args, **kwargs): | CODE |
| LOW | recommenders/datasets/covid_utils.py | 137 | except Exception: | CODE |
| LOW | recommenders/utils/general_utils.py | 42 | except Exception: | CODE |
| LOW | recommenders/utils/notebook_memory_management.py | 35 | except Exception: | CODE |
| LOW | recommenders/utils/gpu_utils.py | 31 | except Exception: # numba.cuda.cudadrv.error.CudaSupportError: | CODE |
| LOW | recommenders/models/deeprec/deeprec_utils.py | 301 | except Exception: # for other exceptions | CODE |
| LOW | recommenders/models/deeprec/models/base_model.py | 433 | except Exception: | CODE |
| LOW | recommenders/models/deeprec/models/graphrec/lightgcn.py | 367 | except Exception: | CODE |
| LOW | recommenders/models/embdotbias/training_utils.py | 136 | except Exception as e: | CODE |
| LOW | recommenders/models/tfidf/tfidf_utils.py | 82 | except Exception: | CODE |
| LOW | recommenders/models/tfidf/tfidf_utils.py | 218 | except Exception: | CODE |
| LOW | recommenders/models/tfidf/tfidf_utils.py | 230 | except Exception: | CODE |
| LOW | recommenders/tuning/nni/ncf_training.py | 171 | except Exception as exception: | CODE |
| LOW | recommenders/tuning/nni/nni_utils.py | 70 | except Exception: | CODE |
| LOW | recommenders/tuning/nni/svd_training.py | 183 | except Exception as exception: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | tests/unit/recommenders/models/test_ncf_dataset.py | 66 | assert train.equals(datafile_df) | CODE |
| HIGH | tests/unit/recommenders/models/test_ncf_dataset.py | 201 | assert train_file_data.equals(train_loader_df) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/databricks_install.py | 235 | # first make sure you are using the correct profile and connecting to the intended workspace | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | recommenders/datasets/wikidata.py | 34 | def my_function(): | STRING |