AI Slop Code RIsk Monitor

pytorch/rl

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

24.4 Elevated pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for pytorch/rl, a Python project with 3,595 GitHub stars. SynthScan examined 587,908 lines of code across 1365 source files, recording 10987 pattern matches distributed across 26 syntactic categories. The legacy adjusted pattern signal is 24.4 (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.

24.4
Adjusted Signal
24.4
Raw Pattern Score
100%
Time Factor
2026-10-11
Last Push
3.6K
Stars
Python
Language
587.9K
Lines of Code
1.4K
Files
11.0K
Pattern Hits
2026-10-12
Scan Date
0.41
HC Hit Rate

Risk Review · v3

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

Cognitive Ownership Risk 42.7/100 · MEDIUM

Can maintainers explain intent, assumptions, and trade-offs? 6339 finding(s).

Hallucinated Dependency & Supply Chain Risk 17.7/100 · LOW

Are imports declared and package/API names verified? 2538 finding(s).

Agent Over-Engineering Ratio 54.0/100 · HIGH

Are wrappers, guards, and repeated structures necessary? 6631 finding(s).

PR Review Velocity Impact 75.3/100 · CRITICAL

Which changes need focused human review? 10987 finding(s).

What These Metrics Mean

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

Pattern-Signal History

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

Severity Breakdown

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

CRITICAL 3HIGH 557MEDIUM 1333LOW 9094

Directory Score Breakdown

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

Pattern Findings

The scanner identified 10987 distinct pattern matches across 26 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

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

Hyper-Verbose Identifiers4229 hits · 3352 pts
SeverityFileLineSnippetContext
LOWsetup.py145def _check_and_clean_stale_builds():CODE
LOWAGENTS.md156def test_something_cuda_specific():CODE
LOWCLAUDE.md156def test_something_cuda_specific():CODE
LOWtest/test_configs.py188def _make_resume_test_trainer(CODE
LOWtest/test_configs.py451 def test_wrapped_class_kwargs_have_config_fields(self, config_name):CODE
LOWtest/test_configs.py470 def test_wrapped_class_kwarg_defaults_match_config(self, config_name):CODE
LOWtest/test_configs.py524 def test_vmas_env_config_instantiation(self):CODE
LOWtest/test_configs.py560 def test_async_env_shared_exchange_config(self):CODE
LOWtest/test_configs.py585 def test_batched_env_config_omegaconf_schema(self):CODE
LOWtest/test_configs.py609 def test_batched_env_config_validation(self, field, value):CODE
LOWtest/test_configs.py640 def test_round_robin_writer_config(self):CODE
LOWtest/test_configs.py664 def test_random_sampler_config(self):CODE
LOWtest/test_configs.py699 def test_tensor_storage_config(self):CODE
LOWtest/test_configs.py720 def test_tensordict_replay_buffer_config(self):CODE
LOWtest/test_configs.py761 def test_replay_buffer_config(self):CODE
LOWtest/test_configs.py815 def test_tensordict_replay_buffer_config_optional_fields(self):CODE
LOWtest/test_configs.py832 def test_writer_ensemble_config(self):CODE
LOWtest/test_configs.py851 def test_tensor_dict_max_value_writer_config(self):CODE
LOWtest/test_configs.py868 def test_tensor_dict_round_robin_writer_config(self):CODE
LOWtest/test_configs.py887 def test_immutable_dataset_writer_config(self):CODE
LOWtest/test_configs.py929 def test_sampler_ensemble_config(self, strategy, expected_members):CODE
LOWtest/test_configs.py949 def test_sampler_ensemble_config_member_samplers(self):CODE
LOWtest/test_configs.py968 def test_sampler_ensemble_config_conflicting_strategy(self):CODE
LOWtest/test_configs.py985 def test_prioritized_slice_sampler_config(self):CODE
LOWtest/test_configs.py1039 def test_slice_sampler_without_replacement_config(self):CODE
LOWtest/test_configs.py1076 def test_slice_sampler_config(self):CODE
LOWtest/test_configs.py1114 def test_slice_sampler_structured_config_instantiation(self):CODE
LOWtest/test_configs.py1131 def test_streaming_slice_sampler_config(self):CODE
LOWtest/test_configs.py1144 def test_prioritized_sampler_config(self):CODE
LOWtest/test_configs.py1169 def test_sampler_without_replacement_config(self):CODE
LOWtest/test_configs.py1188 def test_storage_ensemble_writer_config(self):CODE
LOWtest/test_configs.py1209 def test_lazy_stack_storage_config(self):CODE
LOWtest/test_configs.py1227 def test_storage_ensemble_config(self):CODE
LOWtest/test_configs.py1244 def test_lazy_memmap_storage_config(self):CODE
LOWtest/test_configs.py1265 def test_lazy_tensor_storage_config(self):CODE
LOWtest/test_configs.py1294 def test_complex_replay_buffer_configuration(self):CODE
LOWtest/test_configs.py1357 def test_controller_deployment_from_config(self):CODE
LOWtest/test_configs.py1726 def test_rssm_state_estimator_nested_config(self):CODE
LOWtest/test_configs.py1832 def test_tensor_dict_module_config(self):CODE
LOWtest/test_configs.py1854 def test_tanh_normal_model_config(self):CODE
LOWtest/test_configs.py1888 def test_tanh_normal_model_config_defaults(self):CODE
LOWtest/test_configs.py1909 def test_tanh_normal_model_config_bounds(self, bounds):CODE
LOWtest/test_configs.py1936 def test_tensordict_sequential_config(self):CODE
LOWtest/test_configs.py2066 def test_qmixer_network_config(self):CODE
LOWtest/test_configs.py2080 def test_additive_gaussian_module_config(self):CODE
LOWtest/test_configs.py2120 def test_generic_collector_backend_fields(self):CODE
LOWtest/test_configs.py2143 def test_multi_collector_config_without_policy(self, collector):CODE
LOWtest/test_configs.py2247 def test_collector_auto_configures_exploration_modules(self, factory, collector):CODE
LOWtest/test_configs.py2337 def test_gae_config_instantiates_nested_group_key(self):CODE
LOWtest/test_configs.py2356 def test_gae_config_average_gae_default_matches_gae(self):CODE
LOWtest/test_configs.py2466 def test_ppo_loss_config_delay_actor(self, loss_type):CODE
LOWtest/test_configs.py2685 def test_reinforce_loss_config(self):CODE
LOWtest/test_configs.py2769 def test_wandb_logger_config_instantiation(self, monkeypatch, tmp_path):CODE
LOWtest/test_configs.py2798 def test_trackio_logger_config(self):CODE
LOWtest/test_configs.py2817 def test_trackio_logger_config_instantiation(self, monkeypatch):CODE
LOWtest/test_configs.py2869 def test_checkpoint_config_parity(self, config_name, field_name):CODE
LOWtest/test_configs.py3004 def test_nested_key_normalization_for_hydra_lists(self):CODE
LOWtest/test_configs.py3060 def test_ppo_telemetry_config_and_factory_parity(self):CODE
LOWtest/test_configs.py3137 def test_reinforce_trainer_config(self):CODE
LOWtest/test_configs.py3167 def test_ppo_trainer_config_optional_fields(self):CODE
4169 more matches not shown…
Decorative Section Separators988 hits · 3104 pts
SeverityFileLineSnippetContext
MEDIUM⚡test/test_inference_server.py196# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py198# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py2498# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py2500# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py4863# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py4865# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py4906# =============================================================================COMMENT
MEDIUM⚡test/test_inference_server.py4908# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py103# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py105# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py1396# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py1398# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py1497# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py1499# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py1589# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py1591# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py2248# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py2250# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py2438# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py2440# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py2755# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/test_inference_server.py2757# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/test_inference_server.py4749# =============================================================================COMMENT
MEDIUMtest/test_inference_server.py4751# =============================================================================COMMENT
MEDIUM⚡test/test_collectors.py7952 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py7954 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8274 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8276 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8602 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8604 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8806 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8808 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8908 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8910 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8957 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py8959 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py9065 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py9067 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py9317 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_collectors.py9319 # ------------------------------------------------------------------COMMENT
MEDIUMtest/test_collectors.py7936 # ------------------------------------------------------------------COMMENT
MEDIUMtest/test_collectors.py7938 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_rnd.py98# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_rnd.py100# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_rnd.py230# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡test/test_rnd.py232# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/test_rnd.py20# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/test_rnd.py22# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/test_rnd.py35# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/test_rnd.py37# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡test/llm/test_wrapper.py1630 # ================================================COMMENT
MEDIUM⚡test/llm/test_wrapper.py1632 # ================================================COMMENT
MEDIUM⚡test/llm/test_wrapper.py1708 # ================================================COMMENT
MEDIUM⚡test/llm/test_wrapper.py1710 # ================================================COMMENT
MEDIUM⚡test/llm/test_wrapper.py4160 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/llm/test_wrapper.py4162 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/llm/test_wrapper.py4331 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/llm/test_wrapper.py4333 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/llm/test_wrapper.py4586 # ------------------------------------------------------------------COMMENT
MEDIUM⚡test/llm/test_wrapper.py4588 # ------------------------------------------------------------------COMMENT
928 more matches not shown…
Unused Imports2415 hits · 1928 pts
SeverityFileLineSnippetContext
LOWsetup.py1CODE
LOWtest/test_configs.py6CODE
LOWtest/test_shared.py5CODE
LOWtest/test_exploration.py5CODE
LOWtest/smoke_test.py5CODE
LOWtest/test_utils.py5CODE
LOWtest/conftest.py5CODE
LOWtest/opengl_rendering.py26CODE
LOWtest/opengl_rendering.py33CODE
LOWtest/opengl_rendering.py71CODE
LOWtest/test_docstring_args_checker.py1CODE
LOWtest/test_offline_to_online.py5CODE
LOWtest/test_custom_envs.py5CODE
LOWtest/test_inference_server.py5CODE
LOWtest/test_loggers.py5CODE
LOWtest/test_rlhf.py5CODE
LOWtest/test_postprocs.py5CODE
LOWtest/test_specs.py5CODE
LOWtest/smoke_test_deps.py5CODE
LOWtest/smoke_test_deps.py33CODE
LOWtest/smoke_test_deps.py34CODE
LOWtest/smoke_test_deps.py35CODE
LOWtest/smoke_test_deps.py36CODE
LOWtest/smoke_test_deps.py108CODE
LOWtest/test_render.py5CODE
LOWtest/test_distributions.py5CODE
LOWtest/test_collectors.py5CODE
LOWtest/test_helpers.py5CODE
LOWtest/test_distributed.py9CODE
LOWtest/test_trainer.py5CODE
LOWtest/test_rnd.py5CODE
LOWtest/test_checkpoint.py5CODE
LOWtest/collectors/test_evaluator.py5CODE
LOWtest/llm/test_vllm.py5CODE
LOWtest/llm/test_llm_objectives.py5CODE
LOWtest/llm/test_wrapper.py5CODE
LOWtest/llm/smoke_test_llm.py5CODE
LOWtest/llm/test_sglang_updaters.py6CODE
LOWtest/llm/test_sglang.py6CODE
LOWtest/llm/test_vllm_plugin.py5CODE
LOWtest/llm/test_llm_envs.py5CODE
LOWtest/llm/smoke_test_llm_deps.py5CODE
LOWtest/llm/test_llm_transforms.py6CODE
LOWtest/llm/test_llm_collectors.py5CODE
LOWtest/llm/test_llm_updaters.py5CODE
LOWtest/llm/test_llm_updaters.py30CODE
LOWtest/llm/test_data.py6CODE
LOWtest/llm/libs/test_mlgym.py5CODE
LOWtest/objectives/test_controllers.py6CODE
LOWtest/objectives/test_loss_module.py6CODE
LOWtest/objectives/test_loss_module.py79CODE
LOWtest/objectives/test_loss_module.py79CODE
LOWtest/objectives/conftest.py5CODE
LOWtest/objectives/test_mappo.py12CODE
LOWtest/objectives/test_cql.py6CODE
LOWtest/objectives/test_cql.py28CODE
LOWtest/objectives/test_cql.py28CODE
LOWtest/objectives/test_cql.py28CODE
LOWtest/objectives/test_bc.py5CODE
LOWtest/objectives/_objectives_common.py5CODE
2355 more matches not shown…
Empty Error Handlers265 hits · 1322 pts
SeverityFileLineSnippetContext
HIGHtest/opengl_rendering.py98except error.GLError:CODE
HIGHtest/test_inference_server.py4927except Exception:CODE
HIGHtest/test_collectors.py5580except Exception:CODE
HIGHtest/test_collectors.py5611except Exception:CODE
HIGHtest/test_distributed.py898except Exception:CODE
HIGHtest/test_distributed.py1784except Exception:CODE
HIGHtest/llm/conftest.py32except ImportError:CODE
HIGHtest/llm/test_wrapper.py3543except Exception:CODE
HIGHtest/transforms/test_device_transforms.py127except RuntimeError:CODE
HIGHtest/transforms/test_device_transforms.py183except RuntimeError:CODE
HIGHtest/transforms/test_device_transforms.py328except RuntimeError:CODE
HIGHtest/transforms/test_device_transforms.py352except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py183except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py193except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py203except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py566except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py586except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py687except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py707except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3096except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3116except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3317except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3337except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3593except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3615except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3804except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3816except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3826except RuntimeError:CODE
HIGHtest/transforms/test_action_transforms.py3838except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py139except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py165except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py377except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py403except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py614except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py635except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py702except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py719except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py954except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py1135except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py1181except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py1408except RuntimeError:CODE
HIGHtest/transforms/test_key_transforms.py1440except RuntimeError:CODE
HIGHtest/transforms/test_clip_transform.py241except RuntimeError:CODE
HIGHtest/transforms/test_clip_transform.py276except RuntimeError:CODE
HIGHtest/transforms/test_encoder_transforms.py524except RuntimeError:CODE
HIGHtest/transforms/test_encoder_transforms.py545except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py183except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py210except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1123except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1141except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1332except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1352except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1409except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1435except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1685except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1707except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1816except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py1846except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py2407except RuntimeError:CODE
HIGHtest/transforms/test_observation_transforms.py2427except RuntimeError:CODE
205 more matches not shown…
Docstring Block Structure185 hits · 912 pts
SeverityFileLineSnippetContext
HIGH…ta-implementations/vla_grpo/openvla_oft/train_utils.py59 Find a specific checkpoint file matching a pattern. Args: pretrained_checkpoint: Path to the checkpoinSTRING
HIGHsota-implementations/dreamer/dreamer_utils.py85Allocate CUDA devices for collectors, reserving cuda:0 for training. Device allocation strategy: - Training alwSTRING
HIGHsota-implementations/grpo/grpo_utils.py111Creates and configures the training model with LoRA adapters. This function initializes the main training model witSTRING
HIGHsota-implementations/grpo/grpo_utils.py196Creates the inference model for fast generation. This function initializes a model server (vLLM or SGLang) for effiSTRING
HIGHsota-implementations/grpo/grpo_utils.py540Creates and configures a HuggingFace model with optional optimizations. Args: model_name (str): HuggingFaceSTRING
HIGHsota-implementations/redq/utils.py177Creates a Trainer instance given its constituents. Args: collector (BaseCollector): A data collector to be STRING
HIGHsota-implementations/expert-iteration/ei_utils.py107Creates and configures the training model with LoRA adapters. This function initializes the main training model witSTRING
HIGHsota-implementations/expert-iteration/ei_utils.py188Creates the vLLM-based inference model for fast generation. This function initializes a vLLM model server for efficSTRING
HIGHsota-implementations/expert-iteration/ei_utils.py342Creates and configures a HuggingFace model with optional optimizations. Args: model_name (str): HuggingFaceSTRING
HIGHtorchrl/_utils.py1171Return the available accelerator device, or CPU if none is found. Checks for accelerator availability in the followSTRING
HIGHtorchrl/_utils.py1292Compile a model with warm-up. This function wraps :func:`~torch.compile` to add a warm-up phase. During the warm-upSTRING
HIGHtorchrl/_utils.py1470Return current CUDA memory statistics for ``device`` in gigabytes. Wraps :func:`torch.cuda.memory_allocated`, :funcSTRING
HIGHtorchrl/_utils.py1856Merge user-provided ray_init_config with default runtime_env excludes. This function ensures that the default TorchSTRING
HIGHtorchrl/weight_update/utils.py32Resolve an attribute path like 'policy' or 'env.value_net' to actual object. Also processes getitem notation like 'STRING
HIGHtorchrl/collectors/_base.py764Execute a method on a nested attribute of this collector. This method allows remote callers to invoke methods oSTRING
HIGHtorchrl/collectors/_base.py797Get a nested attribute of this collector. This method allows remote callers to retrieve attributes from nested STRING
HIGHtorchrl/collectors/_base.py828Apply a method to each set of arguments. This method executes a method on the collector with different argumentSTRING
HIGHtorchrl/collectors/_base.py1099Update policy weights for the data collector. This method synchronizes the policy weights used by the collectorSTRING
HIGHtorchrl/collectors/_base.py1380Receive and apply weights to the collector's policy. This method applies weights to the local policy. When receSTRING
HIGHtorchrl/collectors/_multi_base.py1335Receive from a pipe while periodically checking worker health. This method prevents the main process from hangiSTRING
HIGHtorchrl/collectors/_multi_base.py2126Sets the seeds of the environments stored in the DataCollector. Args: seed: integer representing thSTRING
HIGHtorchrl/collectors/_multi_base.py2304Get an attribute from the policy of the first worker. Args: attr (str): The attribute name to retriSTRING
HIGHtorchrl/collectors/_multi_base.py2330Get an attribute from the environment of the first worker. Args: attr (str): The attribute name to STRING
HIGHtorchrl/collectors/_multi_base.py2360Get model instance by ID (for weight sync schemes). Args: model_id: Model identifier (e.g., "policySTRING
HIGHtorchrl/collectors/utils.py98A util function for trajectory separation. Takes a tensordict with a key traj_ids that indicates the id of each traSTRING
HIGHtorchrl/collectors/_single.py1758Sets the seeds of the environments stored in the DataCollector. Args: seed (int): integer representSTRING
HIGHtorchrl/collectors/_single.py2606Get model instance by ID (for weight sync schemes). Args: model_id: Model identifier (e.g., "policySTRING
HIGHtorchrl/collectors/distributed/default_configs.py61Create a TCPStore with retry logic for handling port conflicts. This function attempts to create a TCPStore, and ifSTRING
HIGHtorchrl/checkpoint/_hydra.py30Return the configuration of a run resumed from ``checkpoint_path``. The configuration saved with the checkpoint undSTRING
HIGHtorchrl/checkpoint/_checkpoint.py1157Return one component's stored payload without a live object. State-dict components return the decoded state dicSTRING
HIGHtorchrl/checkpoint/_checkpoint.py1800Return the checkpoint at ``path`` or the newest checkpoint of a rotation directory. Args: path: A checkpoinSTRING
HIGHtorchrl/record/recorder.py333Convert recorded frames to a Matplotlib animation. This helper is intended for tutorials and notebooks where thSTRING
HIGHtorchrl/render/checkpoint.py52Writes a checkpoint in the layout expected by rlrender factories. The model weights are stored under the canonical STRING
HIGHtorchrl/render/mujoco_wasm.py57Writes a local Vite viewer for MuJoCo WASM notebook rendering. Args: output_dir: Directory that will contaiSTRING
HIGHtorchrl/render/mujoco_wasm.py125Starts and displays a generated MuJoCo WASM viewer in a notebook. Args: viewer_dir: Directory produced by :STRING
HIGHtorchrl/render/mujoco_wasm.py184Sends one qpos vector to a live MuJoCo WASM notebook viewer. Args: qpos: Iterable of joint position values.STRING
HIGHtorchrl/render/mujoco_wasm.py235Plays a qpos trajectory in a live MuJoCo WASM notebook viewer. Args: qpos: Iterable of waypoints, each contSTRING
HIGHtorchrl/render/mujoco_wasm.py312Extracts a qpos trajectory from a rollout TensorDict. Args: rollout: Rollout TensorDict saved by ``rlrenderSTRING
HIGHtorchrl/render/backends/mujoco.py53Returns a detached snapshot of the environment's MuJoCo state. Args: env: TorchRL-native MuJoCo envSTRING
HIGHtorchrl/objectives/dreamer_v3.py88Return DreamerV3 dynamics and representation KL losses. The dynamics term stops gradients through the posterior andSTRING
HIGHtorchrl/objectives/dreamer_v3.py136KL divergence with balancing between posterior and prior. Computes: loss = alpha * KL(sg(posterior) || prioSTRING
HIGHtorchrl/objectives/dreamer_v3.py1225Compute the DreamerV3 critic loss on a replay sequence. The return of each replay state uses the reward of the STRING
HIGHtorchrl/objectives/common.py870Value-function constructor. If the non-default value function is wanted, it must be built using this meSTRING
HIGHtorchrl/objectives/llm/distillation.py28Per-token k3 estimate of the KL divergence to a target distribution. Uses the k3 estimator ``exp(d) - 1 - d`` with STRING
HIGHtorchrl/objectives/value/advantages.py1171Computes the TD(0) advantage given the data in tensordict. If a functional module is provided, a nested TensorDSTRING
HIGHtorchrl/objectives/value/advantages.py1470Computes the TD(1) advantage given the data in tensordict. If a functional module is provided, a nested TensorDSTRING
HIGHtorchrl/objectives/value/advantages.py1793Computes the TD(:math:`\lambda`) advantage given the data in tensordict. If a functional module is provided, a STRING
HIGHtorchrl/objectives/value/advantages.py2153Construct GAE with correctness-first recurrent-network defaults. This constructor disables ``vmap`` and uses thSTRING
HIGHtorchrl/objectives/value/advantages.py2402Computes the GAE given the data in tensordict. If a functional module is provided, a nested TensorDict containiSTRING
HIGHtorchrl/objectives/value/advantages.py3174Computes the V-Trace correction given the data in tensordict. If a functional module is provided, a nested TensSTRING
HIGHtorchrl/objectives/value/functional.py1396Compute the discounted cumulative sum of rewards given multiple trajectories and the episode ends. Args: reSTRING
HIGHtorchrl/_comm/backends.py79Return the canonical spelling of a TorchRL service backend. The long ``threading`` and ``multiprocessing`` spellingSTRING
HIGHtorchrl/_comm/backends.py104Return the canonical spelling of a TorchRL payload transport. Args: backend: Transport selector to validateSTRING
HIGHtorchrl/trainers/trainers.py3092Resolve a module from a trainer using a string path. Args: trainer (Trainer): The trainer instance to resolSTRING
HIGHtorchrl/trainers/algorithms/ppo.py77Build a PPO trainer from an environment, actor and critic. Constructs a :class:`~torchrl.collectors.Collector`,STRING
HIGHtorchrl/trainers/algorithms/configs/entrypoint.py24Instantiate ``cfg.trainer``, resuming from ``cfg.resume`` when it is set. Without ``resume`` this is :func:`hydra.uSTRING
HIGHtorchrl/trainers/helpers/models.py67DQN constructor helper function. Args: proof_environment (EnvBase): a dummy environment to retrieve the obsSTRING
HIGHtorchrl/trainers/helpers/trainers.py90Creates a Trainer instance given its constituents. Args: collector (BaseCollector): A data collector to be STRING
HIGHtorchrl/modules/functional.py12Apply the element-wise symmetric logarithm transform. The transform is defined as ``sign(value) * log(1 + abs(vSTRING
HIGHtorchrl/modules/functional.py42Apply the inverse symmetric exponential transform element-wise. Args: value (torch.Tensor): Input tensor inSTRING
125 more matches not shown…
Self-Referential Comments198 hits · 506 pts
SeverityFileLineSnippetContext
MEDIUMtest/test_configs.py1303 # Create a complex configurationCOMMENT
MEDIUMtest/test_configs.py3658 # Create a test script that follows the patternCOMMENT
MEDIUMtest/test_configs.py3679 # Create the config directory structureSTRING
MEDIUMtest/test_exploration.py688 # Create a policy with exploration module that has spec=NoneCOMMENT
MEDIUMtest/test_exploration.py1132 # Create a simple network with NoisyLinear using new behaviorCOMMENT
MEDIUMtest/test_utils.py690 # Create a tensor with batch dimensionCOMMENT
MEDIUMtest/test_postprocs.py230 # Create a sample TensorDictCOMMENT
MEDIUMtest/test_postprocs.py244 # Create an instance of LastRewardToTrajCOMMENT
MEDIUM⚡test/test_specs.py4760 # Create a OneHot spec with a mask that varies across batch dimensionCOMMENT
MEDIUMtest/smoke_test_deps.py16# This file is a smoke test for optional deps. All optional-dep imports mustCOMMENT
MEDIUMtest/test_collectors.py6962 # Create a ParallelEnv factory - this is the key component that was failingCOMMENT
MEDIUMtest/test_collectors.py6980 # Create the multi-collector with ParallelEnv and replay_bufferCOMMENT
MEDIUMtest/test_collectors.py7052 # Create a simple dummy environmentCOMMENT
MEDIUMtest/test_collectors.py7058 # Create a simple dummy policyCOMMENT
MEDIUMtest/test_collectors.py7366 # Create a deterministic policy (linear, no bias) so zeroing weights → zero actionsCOMMENT
MEDIUM⚡test/llm/test_conversions.py116 # Create a batch of ChatHistory objectsCOMMENT
MEDIUM⚡test/llm/test_conversions.py427 # Create a 2x2 batchCOMMENT
MEDIUM⚡test/llm/test_conversions.py429 # Create a 2x2 batch of ChatHistory objectsCOMMENT
MEDIUMtest/llm/test_conversions.py62 # Create a batch of ChatHistory objectsCOMMENT
MEDIUMtest/llm/test_conversions.py181 # Create a batch of ChatHistory objectsCOMMENT
MEDIUMtest/llm/test_conversions.py233 # Create a batch of ChatHistory objectsCOMMENT
MEDIUMtest/llm/test_conversions.py310 # Create a batch of ChatHistory objectsCOMMENT
MEDIUMtest/llm/test_conversions.py408 # Create a batch of ChatHistory objectsCOMMENT
MEDIUMtest/llm/test_vllm.py118 # Create a transformer policy with the same modelCOMMENT
MEDIUMtest/llm/test_vllm.py153 # Create a proper collector mock that provides access to the AsyncVLLM serviceCOMMENT
MEDIUMtest/llm/test_wrapper.py2741 # Create a custom mask matching the logits shapeCOMMENT
MEDIUMtest/llm/test_wrapper.py3392 # Create a simple mock function to test the decoratorCOMMENT
MEDIUMtest/llm/test_wrapper.py3400 # Create a mock self object with batching attributesCOMMENT
MEDIUMtest/llm/test_llm_envs.py987 # Define a simple calculator toolCOMMENT
MEDIUMtest/llm/test_llm_envs.py996 # Define the tool schemaCOMMENT
MEDIUMtest/llm/test_llm_envs.py1107 # Define a tool that waits for a random amount of timeCOMMENT
MEDIUMtest/llm/test_llm_envs.py1120 # Define the tool schemaCOMMENT
MEDIUMtest/llm/test_data.py577 # Create a simple historyCOMMENT
MEDIUMtest/llm/test_data.py726 # Create a custom template (trivially different from Qwen)COMMENT
MEDIUMtest/llm/test_data.py1009 # Create a batch of 2 prompt historiesCOMMENT
MEDIUM⚡test/objectives/test_loss_module.py1371 # Create a value estimator instanceCOMMENT
MEDIUM⚡test/objectives/test_loss_module.py1377 # Create a loss module that supports value estimationCOMMENT
MEDIUM⚡test/objectives/test_loss_module.py1470 # Create a GAE instanceCOMMENT
MEDIUM⚡test/objectives/test_loss_module.py1477 # Create a PPO lossCOMMENT
MEDIUMtest/objectives/test_loss_module.py1398 # Create a loss moduleCOMMENT
MEDIUMtest/objectives/test_loss_module.py1424 # Create a loss moduleCOMMENT
MEDIUMtest/objectives/test_loss_module.py1446 # Create a PPO loss which supports GAECOMMENT
MEDIUMtest/libs/test_envpool.py234 # Create the first env, set the seed, and perform a sequence of operationsCOMMENT
MEDIUMtest/libs/test_envpool.py248 # Create a new env, set the seed, and repeat same operationsCOMMENT
MEDIUMtest/libs/test_isaac.py992 # Create a fresh env with InitTracker (required for LSTM)COMMENT
MEDIUMtest/libs/test_isaac.py1023 # Create a simple policy using the LSTM and move to correct deviceCOMMENT
MEDIUM⚡test/transforms/test_reward_transforms.py1208 # Create a simple env with multi-objective rewardsCOMMENT
MEDIUM⚡test/transforms/test_reward_transforms.py1211 # Create a composed transform with LineariseRewards and RewardScalingCOMMENT
MEDIUMtest/transforms/test_reward_transforms.py1250 # Create a dummy env that produces nested rewardsCOMMENT
MEDIUMtest/transforms/test_compose_and_env.py666 # Create a Compose transform that renames "action" to "action_1" and then to "action_2"COMMENT
MEDIUM⚡test/transforms/test_module_transforms.py322 # Create a simple module that adds a learnable bias to observationsCOMMENT
MEDIUMtest/rb/test_samplers.py2044 # Create a new buffer with the loaded storage but NEW samplerCOMMENT
MEDIUMtest/rb/test_storages.py433 # Create a list of tensordicts (like a collector would produce)COMMENT
MEDIUMtest/rb/test_storages.py771 # Create an instance of LazyStackStorage with given parametersCOMMENT
MEDIUMtest/rb/test_storages.py773 # Create a ReplayBuffer using the created storageCOMMENT
MEDIUMtest/rb/test_storages.py1736 # Create a script that creates a storage and exits normallyCOMMENT
MEDIUMtest/rb/test_storages.py1767 # Create a script that sleeps and can be interruptedCOMMENT
MEDIUM…ta-implementations/vla_grpo/openvla_oft/train_utils.py9 # Create a tensor marking positions of IGNORE_INDEXCOMMENT
MEDIUM…ta-implementations/vla_grpo/openvla_oft/train_utils.py15 # Create the maskCOMMENT
MEDIUM…ta-implementations/vla_grpo/openvla_oft/train_utils.py26 # Create a tensor marking positions of IGNORE_INDEXCOMMENT
138 more matches not shown…
Deep Nesting595 hits · 470 pts
SeverityFileLineSnippetContext
LOWsetup.py145CODE
LOWpackaging/wheel/relocate.py76CODE
LOWtest/test_configs.py2171CODE
LOWtest/test_configs.py3654CODE
LOWtest/test_utils.py445CODE
LOWtest/opengl_rendering.py87CODE
LOWtest/test_inference_server.py4397CODE
LOWtest/test_inference_server.py4448CODE
LOWtest/test_specs.py3666CODE
LOWtest/test_specs.py3712CODE
LOWtest/test_specs.py2094CODE
LOWtest/test_specs.py2429CODE
LOWtest/test_specs.py2714CODE
LOWtest/test_specs.py3010CODE
LOWtest/test_collectors.py1717CODE
LOWtest/test_collectors.py1799CODE
LOWtest/test_collectors.py2689CODE
LOWtest/test_collectors.py3068CODE
LOWtest/test_collectors.py3972CODE
LOWtest/test_collectors.py4411CODE
LOWtest/test_collectors.py4572CODE
LOWtest/test_collectors.py4787CODE
LOWtest/test_collectors.py4853CODE
LOWtest/test_collectors.py5931CODE
LOWtest/test_collectors.py5952CODE
LOWtest/test_collectors.py5982CODE
LOWtest/test_collectors.py6548CODE
LOWtest/test_collectors.py7030CODE
LOWtest/test_collectors.py7192CODE
LOWtest/test_collectors.py7447CODE
LOWtest/test_collectors.py9322CODE
LOWtest/test_collectors.py9379CODE
LOWtest/test_mcts.py107CODE
LOWtest/test_mcts.py853CODE
LOWtest/test_distributed.py442CODE
LOWtest/test_distributed.py568CODE
LOWtest/test_distributed.py784CODE
LOWtest/test_distributed.py1524CODE
LOWtest/test_distributed.py1623CODE
LOWtest/test_trainer.py738CODE
LOWtest/test_trainer.py1115CODE
LOWtest/test_trainer.py1506CODE
LOWtest/llm/test_vllm.py116CODE
LOWtest/llm/test_wrapper.py476CODE
LOWtest/llm/test_wrapper.py2344CODE
LOWtest/llm/test_llm_envs.py202CODE
LOWtest/llm/test_llm_collectors.py244CODE
LOWtest/llm/test_llm_collectors.py351CODE
LOWtest/llm/test_data.py494CODE
LOWtest/objectives/test_loss_module.py182CODE
LOWtest/objectives/test_cql.py174CODE
LOWtest/objectives/_objectives_common.py208CODE
LOWtest/objectives/_objectives_common.py209CODE
LOWtest/objectives/test_dreamer_v3.py2926CODE
LOWtest/objectives/test_iql.py289CODE
LOWtest/objectives/test_iql.py544CODE
LOWtest/objectives/test_iql.py1205CODE
LOWtest/objectives/test_iql.py1378CODE
LOWtest/objectives/test_fql.py209CODE
LOWtest/objectives/test_ddpg.py375CODE
535 more matches not shown…
Excessive Try-Catch Wrapping410 hits · 410 pts
SeverityFileLineSnippetContext
LOWsetup.py353 except Exception:CODE
MEDIUMsetup.py346def _git_output(args) -> str | None:CODE
LOWtest/test_configs.py3733 except Exception:STRING
LOWtest/test_setup.py216except Exception as err:CODE
MEDIUMtest/test_inference_server.py1662def run(idx):CODE
MEDIUMtest/test_inference_server.py2060def run(idx):CODE
MEDIUMtest/test_inference_server.py3055def _hammer(server, fn_name):CODE
LOWtest/test_inference_server.py1668 except Exception as exc: # noqa: BLE001CODE
LOWtest/test_inference_server.py2067 except Exception as exc: # noqa: BLE001CODE
LOWtest/test_inference_server.py3060 except Exception as exc:CODE
LOWtest/test_inference_server.py4927 except Exception:CODE
LOWtest/test_loggers.py1095 except Exception:CODE
LOWtest/smoke_test_deps.py109 except Exception: # pragma: no coverCODE
LOWtest/smoke_test_deps.py113 except Exception as err: # gymnasium.error.NamespaceNotFound and similarCODE
MEDIUMtest/smoke_test_deps.py89def test_gym():CODE
MEDIUMtest/test_collectors.py2634def test_cudagraph_policy_stochastic_diversity(self):CODE
LOW⚡test/test_collectors.py5565 except Exception:CODE
LOW⚡test/test_collectors.py5580 except Exception:CODE
LOWtest/test_collectors.py5530 except Exception as e:CODE
LOWtest/test_collectors.py5611 except Exception:CODE
MEDIUMtest/test_distributed.py309def _test_distributed_collector_basic(cls, queue, frames_per_batch):CODE
MEDIUMtest/test_distributed.py355def _test_distributed_collector_mult(cls, queue, frames_per_batch):CODE
MEDIUMtest/test_distributed.py398def _test_distributed_collector_sync(cls, queue, sync):CODE
MEDIUMtest/test_distributed.py517def _test_distributed_collector_class(cls, queue, collector_class):CODE
MEDIUMtest/test_distributed.py568def _test_distributed_collector_updatepolicy(CODE
MEDIUMtest/test_distributed.py895def reset_process_group(self):CODE
MEDIUMtest/test_distributed.py1781def reset_process_group(self):CODE
LOWtest/test_distributed.py329 except Exception as e:CODE
LOWtest/test_distributed.py374 except Exception as e:CODE
LOWtest/test_distributed.py418 except Exception as e:CODE
LOWtest/test_distributed.py479 except Exception as e:CODE
LOWtest/test_distributed.py537 except Exception as e:CODE
LOWtest/test_distributed.py630 except Exception as e:CODE
LOWtest/test_distributed.py698 except Exception as e:CODE
LOWtest/test_distributed.py830 except Exception as e:CODE
LOWtest/test_distributed.py898 except Exception:CODE
LOWtest/test_distributed.py1784 except Exception:CODE
LOWtest/llm/test_llm_objectives.py1636 except Exception as e:CODE
LOWtest/llm/test_wrapper.py116 except Exception as e:CODE
LOWtest/llm/test_wrapper.py149 except Exception as e:CODE
LOWtest/llm/test_wrapper.py595 except Exception as e:CODE
LOWtest/llm/test_wrapper.py2897 except Exception as e:CODE
LOWtest/llm/test_wrapper.py3162 except Exception as e:CODE
LOWtest/llm/test_wrapper.py3316 except Exception as e:CODE
LOWtest/llm/test_wrapper.py3543 except Exception:CODE
LOWtest/llm/test_sglang_updaters.py255 except Exception as e:CODE
LOWtest/llm/test_llm_envs.py1437 except Exception as e:CODE
LOWtest/llm/test_llm_updaters.py135 except Exception as e:CODE
LOWtest/llm/test_llm_updaters.py272 except Exception as e:CODE
LOWtest/llm/test_llm_updaters.py346 except Exception as e:CODE
LOWtest/llm/test_llm_updaters.py400 except Exception as e:CODE
LOWtest/llm/test_data.py691 except Exception as e:CODE
LOWtest/libs/conftest.py33 except Exception:CODE
LOWtest/libs/test_datasets.py450 except Exception as err:CODE
LOWtest/libs/test_datasets.py620 except Exception:CODE
LOWtest/libs/test_datasets.py625 except Exception:CODE
MEDIUMtest/libs/test_gym.py121def get_gym_pixel_wrapper():CODE
LOWtest/libs/test_gym.py70 except Exception:CODE
LOWtest/libs/test_gym.py127 except Exception:CODE
LOWtest/libs/test_gym.py141 except Exception:CODE
350 more matches not shown…
Over-Commented Block528 hits · 392 pts
SeverityFileLineSnippetContext
LOWbuild_nightly.sh41# PyPI rejects PEP 440 local version identifiers (e.g. "+g<sha>"). Pin theCOMMENT
LOWpyproject.toml261first_party_detection = falseCOMMENT
LOWpackaging/pkg_helpers.bash1# A set of useful bash functions for common functionality we need to do inCOMMENT
LOWpackaging/pkg_helpers.bash21# /usr/local/cuda-*COMMENT
LOWpackaging/pkg_helpers.bash201COMMENT
LOWtest/opengl_rendering.py1# Copyright (c) Meta Platforms, Inc. and affiliates.COMMENT
LOWtest/opengl_rendering.py41COMMENT
LOWtest/test_collectors.py481COMMENT
LOWtest/test_collectors.py3121COMMENT
LOWtest/test_collectors.py3761 collector.shutdown()COMMENT
LOWtest/test_collectors.py3781# if IS_WINDOWS and PYTHON_3_7:COMMENT
LOWtest/test_collectors.py3801# # 1226: faster executionCOMMENT
LOWtest/test_collectors.py3821# total_frames=20000,COMMENT
LOWtest/test_collectors.py3841# device=_device,COMMENT
LOWtest/test_collectors.py3861#COMMENT
LOWtest/test_collectors.py3881# return envCOMMENT
LOWtest/test_collectors.py3901# del collectorCOMMENT
LOWtest/test_collectors.py3921# frames_per_batch=20,COMMENT
LOWtest/test_collectors.py4021COMMENT
LOWtest/test_collectors.py4041 # for i, data in enumerate(collector): # noqa: B007COMMENT
LOWtest/llm/test_wrapper.py2841 result_packed = wrapper_packed(td)COMMENT
LOWtest/llm/test_wrapper.py2861 # wrapper_class._batching_lock.release()COMMENT
LOWtest/objectives/test_loss_module.py1181class TestBuffer:COMMENT
LOWtest/libs/test_isaac.py461 # "AnymalTerrain",COMMENT
LOWtest/libs/test_isaac.py501 try:COMMENT
LOWtest/modules/test_td_module.py221COMMENT
LOWtest/envs/test_env_base.py661COMMENT
LOWtest/rb/conftest.py1# Copyright (c) Meta Platforms, Inc. and affiliates.COMMENT
LOWtest/rb/test_storage_map.py561 node_id = vertex.node_idCOMMENT
LOWsota-implementations/reward_model_training/utils.py81 vocab_size=256,COMMENT
LOWsota-implementations/multiagent/utils/__init__.py1# Copyright (c) Meta Platforms, Inc. and affiliates.COMMENT
LOWsota-implementations/vla_grpo/openvla.py61PROMPT_TEMPLATE = "In: What action should the robot take to {instruction}?\nOut:"COMMENT
LOWsota-implementations/vla_grpo/openvla_oft/__init__.py1# Vendored from SimpleVLA-RL (https://github.com/PRIME-RL/SimpleVLA-RL),COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py521 dtype=labels.dtype,COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py541 # proprio=None,COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py561COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py581 # # === Handle Unimodal Forward ===COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py601 # assert past_key_values is None, "Unexpected key `past_key_values` provided during multimodal forward!"COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py621 # # Add proprioceptive state if providedCOMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py641 # noisy_actions = noisy_actions.reshape(B, -1).unsqueeze(-1)COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py661 # # Build labels for multimodal sequence if neededCOMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py681COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py821 output_hidden_states=False,COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py841 COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py861COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py881 # #print("!!!!!!!!!!!!!!Entering forward!!!!!!!!!!")COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py901 # # Add stop token to sequence (needed in non-causal bi-directional self-attention, as it appears at train time)COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py921 # #test COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py941 COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py961 # newline_positions = labels != IGNORE_INDEXCOMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py981COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1001 # projected_patch_embeddings, proprio, proprio_projectorCOMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1021 # # Run diffusion-based predictionCOMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1041 # # labels,COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1061 # (projected_patch_embeddings.shape[0], projected_patch_embeddings.shape[1]),COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1081COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1281 else:COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1641 # if action_head is not None:COMMENT
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py1661 device = language_model_output.logits.deviceCOMMENT
LOW…a-implementations/vla_grpo/config/vla_grpo_libero.yaml1# SimpleVLA-RL (arXiv:2509.09674) on LIBERO: OpenVLA-OFT token variant (7B),COMMENT
468 more matches not shown…
Modern Structural Boilerplate372 hits · 361 pts
SeverityFileLineSnippetContext
LOWsetup.py26logger = logging.getLogger(__name__)CODE
LOWpackaging/prepare_nightly_build.py7logger = logging.getLogger(__name__)CODE
LOWtest/conftest.py81def set_warnings() -> None:STRING
LOWtest/test_render.py162 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/test_collectors.py1924 def _set_seed(self, seed: Optional[int]) -> None:CODE
LOWtest/test_collectors.py3404 def _set_seed(self, seed: int | None = None) -> None:CODE
LOWtest/test_collectors.py3461 def _set_seed(self, seed: int | None = None) -> None:CODE
LOWtest/test_collectors.py3636 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/test_collectors.py4747 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/collectors/test_evaluator.py1041 def set_extra_state(self, state: OrderedDict) -> None:CODE
LOWtest/objectives/_objectives_common.py132 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/libs/test_gym.py197 def _set_seed(self, seed: int | None) -> None:CODE
LOW⚡test/transforms/test_action_transforms.py160 def _set_seed(self, seed: int | None) -> None:CODE
LOW⚡test/transforms/test_key_transforms.py95 def _set_seed(self, seed: int | None) -> None:CODE
LOW⚡test/transforms/test_key_transforms.py333 def _set_seed(self, seed: int | None) -> None:CODE
LOW⚡test/transforms/test_key_transforms.py934 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/transforms/test_reward_transforms.py1284 def _set_seed(self, seed: int | None = None) -> None:CODE
LOWtest/transforms/test_reward_transforms.py1344 def _set_seed(self, seed: int | None = None) -> None:CODE
LOWtest/transforms/test_compose_and_env.py175 def _set_seed(self, seed: int) -> None:CODE
LOWtest/transforms/test_compose_and_env.py1208 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/transforms/test_env_transforms.py441 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/transforms/test_env_transforms.py553 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/transforms/test_normalization.py79 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/modules/test_planners.py139 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/envs/test_env_base.py142 def _set_seed(self, seed: int | None) -> None:CODE
LOWtest/envs/test_env_base.py318 def _set_seed(self, seed: int | None) -> None:CODE
LOWsota-implementations/multiagent/utils/utils.py9__all__ = ["DoneTransform"]CODE
LOW…implementations/vla_grpo/compare_simplevla_rollouts.py229def _set_seed(seed: int) -> None:CODE
LOW⚡…ementations/vla_grpo/openvla_oft/modeling_prismatic.py395 def set_input_embeddings(self, value: nn.Module) -> None:CODE
LOW⚡…ementations/vla_grpo/openvla_oft/modeling_prismatic.py401 def set_output_embeddings(self, new_embeddings: nn.Module) -> None:CODE
LOW⚡…ementations/vla_grpo/openvla_oft/modeling_prismatic.py407 def set_decoder(self, decoder: nn.Module) -> None:CODE
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py43logger = logging.getLogger(__name__)CODE
LOW…ementations/vla_grpo/openvla_oft/modeling_prismatic.py199 def set_num_images_in_input(self, num_images_in_input: int) -> None:CODE
LOWsota-implementations/bandits/dqn.py91 def _set_seed(self, seed: int | None) -> None:CODE
LOWexamples/replay-buffers/filter-imcomplete-trajs.py33 def _update_repertoire(self, tensordict: TensorDictBase) -> None:CODE
LOWexamples/rlhf/models/actor_critic.py15__all__ = ["init_actor_critic"]CODE
LOWexamples/rlhf/data/__init__.py3__all__ = ["get_prompt_dataloader_tldr"]CODE
LOWexamples/envs/benchmark_compile_step_and_maybe_reset.py110 def _set_seed(self, seed: int | None) -> None:CODE
LOWbenchmarks/conftest.py143def set_warnings() -> None:STRING
LOWbenchmarks/test_collectors_benchmark.py286 def _set_seed(self, seed: int | None) -> None:CODE
LOWbenchmarks/bench_collectors.py150 def _set_seed(self, seed: int) -> None:CODE
LOWtorchrl/__init__.py143__all__ = [CODE
LOWtorchrl/_utils.py460def set_profiling_enabled(enabled: bool) -> None:CODE
LOWtorchrl/_utils.py1220 def set_mode(self, type: Any | None) -> None:CODE
LOWtorchrl/weight_update/weight_sync_schemes.py23__all__ = [CODE
LOWtorchrl/weight_update/__init__.py20__all__ = [CODE
LOWtorchrl/weight_update/_shared.py266 def _update_single_worker(self, worker_idx: int, weights: TensorDictBase) -> None:CODE
LOW⚡torchrl/weight_update/_ray.py163 def set_model(self, model: Any) -> None:CODE
LOW⚡torchrl/weight_update/_ray.py171 def set_process_group(self, process_group, store=None) -> None:CODE
LOW⚡torchrl/weight_update/_ray.py176 def set_model_version(self, model_version: int | None) -> None:CODE
LOWtorchrl/weight_update/_ray.py534 def _set_model_version(self, model_version: int) -> None:CODE
LOWtorchrl/weight_update/_ray.py971 def _set_transform(self, ray_transform) -> None:CODE
LOWtorchrl/weight_update/llm/vllm_nccl.py641 def update_weights(self, weights: Any | None = None) -> None:CODE
LOWtorchrl/weight_update/llm/__init__.py26__all__ = [CODE
LOWtorchrl/weight_update/llm/vllm_double_buffer.py260 def update_weights(self, weights: Any | None = None) -> None:CODE
LOWtorchrl/collectors/_constants.py26__all__ = [CODE
LOWtorchrl/collectors/_base.py1322 def _set_received_policy_version(self, model_version: int | None) -> None:CODE
LOWtorchrl/collectors/collectors.py31__all__ = [CODE
LOWtorchrl/collectors/__init__.py27__all__ = [CODE
LOWtorchrl/collectors/_multi_base.py1016 def _setup_preemptive_threshold(self, preemptive_threshold: float | None) -> None:CODE
312 more matches not shown…
Cross-File Repetition59 hits · 295 pts
SeverityFileLineSnippetContext
HIGHtest/llm/test_llm_objectives.py0create transformers model and tokenizer for testing.STRING
HIGHtest/llm/test_wrapper.py0create transformers model and tokenizer for testing.STRING
HIGHtest/llm/test_llm_envs.py0create transformers model and tokenizer for testing.STRING
HIGHtest/objectives/test_cql.py0regression test for target_entropy='auto' should be -dim(a).STRING
HIGHtest/objectives/test_dt.py0regression test for target_entropy='auto' should be -dim(a).STRING
HIGHtest/objectives/test_sac.py0regression test for target_entropy='auto' should be -dim(a).STRING
HIGHtest/libs/test_dm_control.py0smoke test that setting seed and reset works (seed forwarded into build).STRING
HIGHtest/libs/test_gym.py0smoke test that setting seed and reset works (seed forwarded into build).STRING
HIGHtest/libs/test_habitat.py0smoke test that setting seed and reset works (seed forwarded into build).STRING
HIGHsota-implementations/sac/sac.py0crossq example. this is a simple self-contained example of a crossq training script. it supports state environments likeSTRING
HIGHsota-implementations/discrete_sac/discrete_sac.py0crossq example. this is a simple self-contained example of a crossq training script. it supports state environments likeSTRING
HIGHsota-implementations/ddpg/ddpg.py0crossq example. this is a simple self-contained example of a crossq training script. it supports state environments likeSTRING
HIGHsota-implementations/td3/td3.py0crossq example. this is a simple self-contained example of a crossq training script. it supports state environments likeSTRING
HIGHsota-implementations/crossq/crossq.py0crossq example. this is a simple self-contained example of a crossq training script. it supports state environments likeSTRING
HIGHsota-implementations/cql/cql_offline.py0decision transformer example. this is a self-contained example of an offline decision transformer training script. the hSTRING
HIGHsota-implementations/cql/discrete_cql_offline.py0decision transformer example. this is a self-contained example of an offline decision transformer training script. the hSTRING
HIGHsota-implementations/iql/iql_offline.py0decision transformer example. this is a self-contained example of an offline decision transformer training script. the hSTRING
HIGHsota-implementations/td3_bc/td3_bc.py0decision transformer example. this is a self-contained example of an offline decision transformer training script. the hSTRING
HIGHsota-implementations/decision_transformer/online_dt.py0decision transformer example. this is a self-contained example of an offline decision transformer training script. the hSTRING
HIGHsota-implementations/decision_transformer/dt.py0decision transformer example. this is a self-contained example of an offline decision transformer training script. the hSTRING
HIGHsota-implementations/cql/cql_online.py0iql example. this is a self-contained example of an online iql training script. it works across gym and mujoco over a vaSTRING
HIGHsota-implementations/iql/discrete_iql.py0iql example. this is a self-contained example of an online iql training script. it works across gym and mujoco over a vaSTRING
HIGHsota-implementations/iql/iql_online.py0iql example. this is a self-contained example of an online iql training script. it works across gym and mujoco over a vaSTRING
HIGHsota-implementations/impala/impala_multi_node_ray.py0this script reproduces the impala algorithm results from espeholt et al. 2018 for the on atari environments.STRING
HIGHsota-implementations/impala/impala_single_node.py0this script reproduces the impala algorithm results from espeholt et al. 2018 for the on atari environments.STRING
HIGH…a-implementations/impala/impala_multi_node_submitit.py0this script reproduces the impala algorithm results from espeholt et al. 2018 for the on atari environments.STRING
HIGHsota-implementations/grpo/grpo-async.py0setup required environment variables and configurations.STRING
HIGHsota-implementations/grpo/grpo-sync.py0setup required environment variables and configurations.STRING
HIGH…lementations/expert-iteration/expert-iteration-sync.py0setup required environment variables and configurations.STRING
HIGH…ementations/expert-iteration/expert-iteration-async.py0setup required environment variables and configurations.STRING
HIGHexamples/distributed/collectors/single_machine/sync.py0rpc data collection on a single node. the default configuration works fine on machines equipped with 4 gpus, but can be STRING
HIGH…mples/distributed/collectors/single_machine/generic.py0rpc data collection on a single node. the default configuration works fine on machines equipped with 4 gpus, but can be STRING
HIGHexamples/distributed/collectors/single_machine/rpc.py0rpc data collection on a single node. the default configuration works fine on machines equipped with 4 gpus, but can be STRING
HIGHtorchrl/record/loggers/mlflow.py0logs a scalar value to the tensorboard. args: name (str): the name of the scalar. value (float): the value of the scalarSTRING
HIGHtorchrl/record/loggers/trackio.py0logs a scalar value to the tensorboard. args: name (str): the name of the scalar. value (float): the value of the scalarSTRING
HIGHtorchrl/record/loggers/csv.py0logs a scalar value to the tensorboard. args: name (str): the name of the scalar. value (float): the value of the scalarSTRING
HIGHtorchrl/record/loggers/tensorboard.py0logs a scalar value to the tensorboard. args: name (str): the name of the scalar. value (float): the value of the scalarSTRING
HIGHtorchrl/record/loggers/mlflow.py0logs the hyperparameters of the experiment. args: cfg (dictconfig or dict): the configuration of the experiment.STRING
HIGHtorchrl/record/loggers/wandb.py0logs the hyperparameters of the experiment. args: cfg (dictconfig or dict): the configuration of the experiment.STRING
HIGHtorchrl/record/loggers/trackio.py0logs the hyperparameters of the experiment. args: cfg (dictconfig or dict): the configuration of the experiment.STRING
HIGHtorchrl/record/loggers/csv.py0logs the hyperparameters of the experiment. args: cfg (dictconfig or dict): the configuration of the experiment.STRING
HIGHtorchrl/record/loggers/tensorboard.py0logs the hyperparameters of the experiment. args: cfg (dictconfig or dict): the configuration of the experiment.STRING
HIGHtorchrl/objectives/td3.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/td3_bc.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/iql.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/crossq.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/deprecated.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/redq.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/sac.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/ddpg.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/cql.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/dqn.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/objectives/multiagent/qmixer.py0maintains default values for all configurable tensordict keys. this class defines which tensordict keys can be set usingSTRING
HIGHtorchrl/_comm/distributed.py0return ``true`` when the result can be read without blocking.STRING
HIGHtorchrl/_comm/mailbox.py0return ``true`` when the result can be read without blocking.STRING
HIGHtorchrl/modules/inference_server/_shared_memory.py0return ``true`` when the result can be read without blocking.STRING
HIGHtorchrl/modules/llm/policies/vllm_wrapper.py0returns a new version of the module with altered parameters. for instance, the generate parameter can be altered to enabSTRING
HIGHtorchrl/modules/llm/policies/common.py0returns a new version of the module with altered parameters. for instance, the generate parameter can be altered to enabSTRING
HIGHtorchrl/modules/llm/policies/transformers_wrapper.py0returns a new version of the module with altered parameters. for instance, the generate parameter can be altered to enabSTRING
AI Structural Patterns292 hits · 256 pts
SeverityFileLineSnippetContext
LOWtest/test_postprocs.py300CODE
LOWtest/test_trainer.py312CODE
LOWtest/llm/test_llm_objectives.py670CODE
LOWtest/llm/test_wrapper.py643CODE
LOWtest/objectives/test_iql.py199CODE
LOWtest/objectives/test_iql.py1111CODE
LOWtest/objectives/test_dqn.py90CODE
LOWtest/objectives/test_dqn.py1082CODE
LOWtest/objectives/test_ddpg.py138CODE
LOWtest/objectives/test_ddpg.py179CODE
LOWtest/objectives/test_ddpg.py907CODE
LOWtest/objectives/test_ddpg.py1829CODE
LOWtest/objectives/test_ppo.py112CODE
LOWtest/objectives/test_ppo.py300CODE
LOWtest/objectives/test_ppo.py352CODE
LOWtest/objectives/test_ppo.py2231CODE
LOWtest/objectives/test_ppo.py2383CODE
LOWtest/objectives/test_sac.py75CODE
LOWtest/objectives/test_sac.py257CODE
LOWtest/objectives/test_sac.py1585CODE
LOWtest/objectives/test_sac.py2420CODE
LOWtest/objectives/test_sac.py3295CODE
LOWtest/libs/test_datasets.py1200CODE
LOWtest/libs/test_envpool.py150CODE
LOWsota-implementations/vla_grpo/utils.py529CODE
LOWsota-implementations/vla_grpo/utils.py584CODE
LOWsota-implementations/vla_grpo/openvla.py186CODE
LOWsota-implementations/vla_grpo/openvla.py476CODE
LOWsota-implementations/vla_grpo/openvla.py815CODE
LOWsota-implementations/vla_grpo/openvla.py1101CODE
LOW…ations/vla_grpo/openvla_oft/configuration_prismatic.py76CODE
LOWsota-implementations/grpo/grpo_utils.py518CODE
LOWsota-implementations/decision_transformer/lamb.py38CODE
LOWsota-implementations/ppo/utils_mujoco.py43CODE
LOWsota-implementations/redq/utils.py560CODE
LOWsota-implementations/expert-iteration/ei_utils.py319CODE
LOWexamples/microduck/heuristic_gait.py270CODE
LOWexamples/microduck/ppo_mujoco.py122CODE
LOWexamples/microduck/ppo_mujoco.py694CODE
LOWexamples/satellite/_utils.py443CODE
LOWexamples/satellite/_utils.py538CODE
LOWexamples/menagerie/ppo.py633CODE
LOWtorchrl/weight_update/_shared.py386CODE
LOWtorchrl/weight_update/_shared.py511CODE
LOWtorchrl/weight_update/_mp.py83CODE
LOWtorchrl/collectors/_base.py581CODE
LOWtorchrl/collectors/_single_async.py175CODE
LOWtorchrl/collectors/_multi_base.py422CODE
LOWtorchrl/collectors/_async_batched.py846CODE
LOWtorchrl/collectors/_single.py683CODE
LOWtorchrl/collectors/_single.py1782CODE
LOWtorchrl/collectors/_evaluator.py289CODE
LOWtorchrl/collectors/_runner.py57CODE
LOWtorchrl/collectors/llm/ray_collector.py84CODE
LOWtorchrl/collectors/llm/base.py151CODE
LOWtorchrl/collectors/distributed/sync.py288CODE
LOWtorchrl/collectors/distributed/generic.py546CODE
LOWtorchrl/collectors/distributed/ray.py360CODE
LOWtorchrl/collectors/distributed/rpc.py320CODE
LOWtorchrl/record/recorder.py142CODE
232 more matches not shown…
Cross-Language Confusion45 hits · 235 pts
SeverityFileLineSnippetContext
HIGHtest/test_inference_server.py2611 ws.push(new_weights)CODE
HIGHtest/test_inference_server.py2640 ws.push(new_weights)CODE
HIGHtest/envs/test_special.py323 board.push(move)CODE
HIGHsota-implementations/dreamer_v3/dreamer_v3_utils.py97 f"optimization.compile_rssm must be null, 'step' or 'scan', got {rssm!r}."CODE
HIGH.github/scripts/generate_dashboard.py310 document.getElementById('new-flaky-count').textContent = report.summary.new_flaky_count || 0;CODE
HIGH.github/scripts/generate_dashboard.py311 document.getElementById('resolved-count').textContent = report.summary.resolved_count || 0;CODE
HIGH.github/scripts/generate_dashboard.py344 if (!flakyTests || flakyTests.length === 0) {CODE
HIGH.github/scripts/generate_dashboard.py370 const lastFailed = test.recent_failures && test.recent_failures.length > 0CODE
HIGHtorchrl/_extension.py59 " - make sure you ran `python setup.py clean && python setup.py develop` and that no error was raised\n"CODE
HIGH⚡torchrl/render/mujoco_wasm.py863let model = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py864let data = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py865let mujoco = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py868let threeScene = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py869let renderer = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py870let camera = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py871let controls = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py874let trajectoryPlayback = null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py1121 jointControls.push({name, jointId, qposAddress, slider, output});CODE
HIGH⚡torchrl/render/mujoco_wasm.py1128 if (!trajectoryUrl || params.get("autoplay") === "0") return;CODE
HIGH⚡torchrl/render/mujoco_wasm.py1133 const result = applyTrajectoryMessage(payload, null);CODE
HIGH⚡torchrl/render/mujoco_wasm.py1138 if (!value || typeof value !== "object") return null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py1138 if (!value || typeof value !== "object") return null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py1139 if (value.type !== "torchrl:mujoco_wasm:setQpos" && value.type !== "torchrl:mujoco_wasm:playTrajectory") return null;CODE
HIGH⚡torchrl/render/mujoco_wasm.py1244 if (renderer && camera) renderer.render(rendererScene(), camera);CODE
HIGH⚡torchrl/render/mujoco_wasm.py1252 if (!playback.loop && framePosition >= finalIndex) {CODE
HIGH⚡torchrl/render/mujoco_wasm.py1254 trajectoryPlayback = null;CODE
HIGHtorchrl/render/mujoco_wasm.py643 if (requestId && callbackUrl) {{CODE
HIGHtorchrl/render/mujoco_wasm.py650 if (message.ok === false || done || cancelled) {{CODE
HIGHtorchrl/render/mujoco_wasm.py1026 visuals.push({geomId, object: mesh});CODE
HIGHtorchrl/render/mujoco_wasm.py1047 return null;CODE
HIGHtorchrl/render/mujoco_wasm.py1087 if (jointType !== HINGE_JOINT_TYPE && jointType !== SLIDE_JOINT_TYPE) continue;CODE
HIGHtorchrl/render/mujoco_wasm.py1192 if (out.length !== model.nq && out.length !== jointControls.length) throw new Error(`qpos must have model.nq (${model.CODE
HIGHtorchrl/render/mujoco_wasm.py1211 if (message.dt !== undefined) {CODE
HIGHtorchrl/render/mujoco_wasm.py1216 if (message.fps !== undefined) {CODE
HIGHtorchrl/render/mujoco_wasm.py1283 trajectoryPlayback = null;CODE
HIGHtorchrl/render/mujoco_wasm.py1293 if (!data || homeQpos.length < 3) return;CODE
HIGHtorchrl/render/mujoco_wasm.py1366 while (end < bytes.length && bytes[end] !== 0) end++;CODE
HIGHtorchrl/objectives/dreamer_v3.py140 + (1 - alpha) * KL(posterior || sg(prior))STRING
HIGHtorchrl/objectives/llm/distillation.py38 ``KL(sampling distribution || target distribution)``, and the directionSTRING
HIGHtorchrl/objectives/llm/distillation.py119 - ``"reverse"`` (default): minimizes ``KL(student || teacher)``. This isCODE
HIGHtorchrl/objectives/llm/distillation.py122 - ``"forward"``: minimizes ``KL(teacher || student)``. Here the scoredCODE
HIGHtorchrl/envs/common.py885 - The number of actions can be undefined, e.g., ``Categorical(n=-1)``;STRING
HIGHtorchrl/envs/transforms/_reward.py336 """Maps the reward to a binary value (0 or 1) if the reward is null or non-null, respectively.STRING
HIGHtorchrl/envs/custom/chess.py522 board.push(move)CODE
HIGHtorchrl/data/tensor_specs.py3852 n (int): number of possible outcomes. If set to -1, the cardinality of the categorical spec is undefined,STRING
Modern AI Meta-Vocabulary44 hits · 154 pts
SeverityFileLineSnippetContext
MEDIUMREADME.md143# Nested keys make multi-agent, recurrent, and next-state data explicit.COMMENT
MEDIUMtest/libs/test_mujoco_playground.py67# Cached environment dims for the multi-agent test env, avoiding O(n_tests)COMMENT
MEDIUMexamples/multiagent/mappo_vmas.py148 # multi-agent value estimator broadcasts the latter across agents.COMMENT
MEDIUMtorchrl/envs/utils.py641 # "multi-agent-emergence-environments": None,COMMENT
MEDIUMtorchrl/envs/utils.py642 # OpenAI, https://github.com/openai/multi-agent-emergence-environmentsCOMMENT
MEDIUMtorchrl/envs/libs/meltingpot.py312 # Create multi-agent specsCOMMENT
MEDIUMtorchrl/envs/libs/vmas.py429 # Create multi-agent specsCOMMENT
MEDIUMtorchrl/envs/libs/mujoco_playground.py220# Predefined multi-agent partitionings for common MuJoCo locomotion tasks.COMMENT
MEDIUMtorchrl/envs/model_based/world_model_env.py229 # done structure (e.g. multi-agent dones) consistent with the spec.COMMENT
MEDIUMtorchrl/data/postprocs/postprocs.py45 # Note: rewards could have a different shape than done (e.g. multi-agent with a singleCOMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py936# - How to create a competitive multi-group multi-agent environment in TorchRL, how its specs work, and how it integrateCOMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py937# - How to create multi-agent network architectures in TorchRL for multiple groups;COMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py938# - How we can use :class:`tensordict.TensorDict` to carry multi-agent multi-group data;COMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py939# - How we can tie all the library components (collectors, modules, replay buffers, and losses) in a multi-agent multi-gCOMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py941# Now that you are proficient with multi-agent DDPG, you can check out all the TorchRL multi-agent implementations in thCOMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py63# This approach has been extended to multi-agent learning in `Multi-Agent Actor-Critic for Mixed Cooperative-CompetitiveCOMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py65# In multi-agent settings, things are a bit different. We now have multiple policies :math:`\mathbf{\pi}`,COMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py88# 2. Subsequently, we will construct a multi-agent environment, utilizing TorchRL'sCOMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py196# TorchRL API allows integrating various types of multi-agent environment flavors.COMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py311# (``"done", "terminated", "truncated"``), which do not have a leading multi-agent dimension.COMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py333# We stress that, in multi-agent contexts, it is paramount to provide explicitly the keys to modify.COMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py612# **From this point on, the multi-agent-specific components have been instantiated, and we will simply use the sameCOMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py677 ), # We will store up to memory_size multi-agent transitionsCODE
MEDIUMtutorials/sphinx-tutorials/getting-started-0.py180# multiple copies across various processes, a multi-agent environment, or evenCOMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-0.py243# :ref:`multi-agent environment API <MARL-environment-API>`COMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-4.py20# The final chapter of this series before we orchestrate everything in aCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py190# TorchRL API allows integrating various types of multi-agent environment flavors.COMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py192# For more information on how the multi-agent environments API works in TorchRL, you can check out the dedicatedCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py205# The multi-agent task we will solve today is *Navigation* (see animated figure above).COMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py532# **From this point on, the multi-agent-specific components have been instantiated, and we will simply use the sameCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py773# - How to create a multi-agent environment in TorchRL, how its specs work, and how it integrates with the library;COMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py775# - How to create different multi-agent network architectures in TorchRL (e.g., using parameter sharing, centralised criCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py776# - How we can use :class:`tensordict.TensorDict` to carry multi-agent data;COMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py777# - How we can tie all the library components (collectors, modules, replay buffers, and losses) in a multi-agent MAPPO/ICOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py779# Now that you are proficient with multi-agent DDPG, you can check out all the TorchRL multi-agent implementations in thCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py784# You can also check out our other multi-agent tutorial on how to train competitiveCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py787# If you are interested in creating or wrapping your own multi-agent environments in TorchRL,COMMENT
MEDIUMtutorials/sphinx-tutorials/multiagent_ppo.py76# In multi-agent settings, things are a bit different. We now have multiple policies :math:`\mathbf{\pi}`,COMMENT
MEDIUMtutorials/sphinx-tutorials/multiagent_ppo.py98# 2. Next, we will create a vectorized multi-agent environment, using TorchRL'sCOMMENT
MEDIUMtutorials/sphinx-tutorials/multiagent_ppo.py301# We stress that, in multi-agent contexts, it is paramount to provide explicitly the keys to modify.COMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-2.py47# module orchestrates the various components of your algorithm andCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/low_level_controller.py267# :class:`~torchrl.modules.GRUModule`, and the multi-agent PPO tutorial.COMMENT
MEDIUMtutorials/sphinx-tutorials/pendulum.py292# it (for example, in multi-agent settings we may want to indicate which agents needCOMMENT
MEDIUMtutorials/sphinx-tutorials/coding_dqn.py172# the training script. The trainer is there to orchestrate everything for you!COMMENT
Redundant / Tautological Comments83 hits · 118 pts
SeverityFileLineSnippetContext
LOWbuild_nightly.sh4# Check if we're in a nightly buildCOMMENT
LOWpackaging/verify_nightly_version.py15# Check if __version__ attribute existsCOMMENT
LOWpackaging/verify_nightly_version.py53 # Check if it's the nightly version by looking at the versionCOMMENT
LOWpackaging/verify_nightly_version.py57 # Check if it's a nightly version (either date format or contains 'd' followed by date)COMMENT
LOWpackaging/verify_nightly_version.py68 # Check if it's a stable version that should not be used in nightly buildsCOMMENT
LOW⚡test/test_collectors.py5574 # Check if there was an exception even with exitcode 0COMMENT
LOWtest/test_mcts.py451 ): # Check if action_prob_key was also populatedCODE
LOW⚡test/llm/test_conversions.py109 # Check if it's a nested tensor by checking if it has the _values attributeCOMMENT
LOW⚡test/llm/test_conversions.py126 # Check if it's a nested tensorCOMMENT
LOWtest/llm/test_conversions.py144 # Check if they're nested tensorsCOMMENT
LOWtest/llm/conftest.py78 # Check if test already has a timeout markerCOMMENT
LOWtest/llm/test_llm_envs.py107 # Set list to stack for tensordictCOMMENT
LOWtest/objectives/test_loss_module.py1529 # Assign float to entropy_coeffCOMMENT
LOWtest/transforms/test_module_transforms.py248 # Check if ray is initializedCOMMENT
LOWsota-implementations/vla_grpo/openvla_oft/constants.py90# Assign constants to global variablesCOMMENT
LOWsota-implementations/dreamer/dreamer.py462 # Check if profiling is complete and we should exitCOMMENT
LOWsota-implementations/dreamer/dreamer_utils.py233 # Check if we should stop profilingCOMMENT
LOWsota-implementations/grpo/grpo-async.py272 # Check if num_devices is setCOMMENT
LOWsota-implementations/grpo/grpo-sync.py251 # Check if num_devices is setCOMMENT
LOW…lementations/expert-iteration/expert-iteration-sync.py407 # Check if num_devices is setCOMMENT
LOW…ementations/expert-iteration/expert-iteration-async.py408 # Check if num_devices is setCOMMENT
LOWsota-check/submitit-release-check.sh19# Check if the script is called with --help or without any argumentsCOMMENT
LOW⚡examples/agents/recurrent_actor.py126# Print result:COMMENT
LOW.github/unittest/linux_libs/scripts_isaaclab/isaac.sh42# Check if isaaclab.sh existsCOMMENT
LOW.github/workflows/auto-tag.yml100 # Check if title starts with [...]COMMENT
LOW.github/workflows/release.yml151 # Check if it's on a release branch matching the versionCOMMENT
LOW.github/workflows/release.yml437 # Check if the version folder existsCOMMENT
LOW.github/workflows/release.yml480 # Check if changes were madeCOMMENT
LOW.github/workflows/release.yml546 # Check if release already existsCOMMENT
LOW.github/workflows/nightly_status_collector.yml151 # Check if success rate dropped below 70% in last 7 daysCOMMENT
LOW.github/scripts/td_script.sh16# Check if ARCH is set to aarch64COMMENT
LOWtorchrl/_utils.py57 # Check if user has explicitly set a global start methodCOMMENT
LOWtorchrl/weight_update/_rpc.py256 # Check if all futures are completeCOMMENT
LOWtorchrl/weight_update/_shared.py211 # Check if per-worker weights dict is providedCOMMENT
LOWtorchrl/weight_update/_shared.py581 # Check if policy factories are uniform or distinctCOMMENT
LOWtorchrl/weight_update/_shared.py936 # Check if per-worker weights dict is providedCOMMENT
LOWtorchrl/weight_update/_shared.py1108 # Check if already shutdownCOMMENT
LOWtorchrl/weight_update/_distributed.py478 # Check if we have weights to sendCOMMENT
LOWtorchrl/weight_update/_distributed.py549 # Check if already shutdownCOMMENT
LOWtorchrl/weight_update/_distributed.py716 # Check if all futures are completeSTRING
LOWtorchrl/weight_update/llm/vllm_double_buffer.py326 # Check if this is an AsyncVLLM instance (uses RPC to coordinate workers)COMMENT
LOWtorchrl/collectors/_multi_base.py1371 # Check if any worker has diedCOMMENT
LOWtorchrl/collectors/_multi_base.py1673 # Check if it's an error dict from workerCOMMENT
LOW⚡torchrl/collectors/_single.py1108 # Check if policy has meta-device parameters (sent from weight sync schemes)COMMENT
LOW⚡torchrl/collectors/_single.py1245 # Check if we need to cast to env deviceCOMMENT
LOWtorchrl/collectors/_single.py1449 # Check if policy has meta-device parameters (not yet initialized)COMMENT
LOWtorchrl/collectors/llm/weight_update/vllm.py311 # Check if it's a LoRA modelCOMMENT
LOWtorchrl/collectors/llm/weight_update/vllm.py339 # Check if the model has a LoRA adapterCOMMENT
LOWtorchrl/collectors/llm/weight_update/vllm_v2.py119 # Check if it's a LoRA modelCOMMENT
LOWtorchrl/collectors/llm/weight_update/vllm_v2.py126 # Check if it's a LoRA modelCOMMENT
LOWtorchrl/collectors/llm/weight_update/vllm_v2.py290 # Check if it's a LoRA modelCOMMENT
LOWtorchrl/collectors/llm/weight_update/vllm_v2.py297 # Check if it's a LoRA modelCOMMENT
LOWtorchrl/trainers/trainers.py2006 # Check if we've reached the target framesCOMMENT
LOWtorchrl/trainers/trainers.py2114 # Check if enough frames have passed since last logging for this keyCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py254 # Check if it's a list of lists or a single listCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py832 # Check if this is actually a single prompt represented as token IDsCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py966 # Check if this is a batch requestCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py1797 # Check if preferred actor is overloadedCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py2050 # Set tensor_parallel_size to num_devices if not setCOMMENT
LOWtorchrl/modules/llm/backends/sglang/sglang_utils.py87 # Check if subprocess diedCOMMENT
23 more matches not shown…
Structural Annotation Overuse60 hits · 108 pts
SeverityFileLineSnippetContext
LOW⚡test/llm/test_wrapper.py2396 # Step 1: Generate the canonical response tokens with vLLM.COMMENT
LOW⚡test/llm/test_wrapper.py2402 # Step 2: Extract generated tokens and create new input for log-probs computationCOMMENT
LOWtest/llm/test_wrapper.py2445 # Step 3: Create log-probs only wrappersCOMMENT
LOWtest/llm/test_wrapper.py2464 # Step 4: Compute log-probs for the full sequence (original + generated)COMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py142 # Step 1: Stack to contiguous (this allocates new memory)COMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py144 # Step 2: Write to storageCOMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py176 # Step 1: Create lazy stack (no allocation, just wrapping)COMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py178 # Step 2: Write to storage (storage handles the lazy stack)COMMENT
LOW.github/RELEASE_AGENT_PROMPT.md60## Step 1: Analyze Commits for Release NotesCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md167## Step 2: Draft Release NotesCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md231## Step 3: Update Version FilesCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md270## Step 4: Commit Version Changes on the main branch (Major releases only)COMMENT
LOW.github/RELEASE_AGENT_PROMPT.md284## Step 5: Create Release BranchCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md298## Step 6: Commit Version Changes (Minor releases only)COMMENT
LOW.github/RELEASE_AGENT_PROMPT.md309## Step 7: Create and Push TagCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md322## Step 8: Trigger Release WorkflowCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md337## Step 9: Create Draft GitHub ReleaseCOMMENT
LOW.github/RELEASE_AGENT_PROMPT.md350## Step 10: Monitor WorkflowCOMMENT
LOW⚡torchrl/weight_update/_rpc.py181 # Step 1: Signal the remote collector via RPC to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_rpc.py185 # Step 2: Send weights via torch.distributed (blocks until receiver calls recv())COMMENT
LOW⚡torchrl/weight_update/_rpc.py188 # Step 3: Wait for RPC to complete (receiver has applied weights)COMMENT
LOW⚡torchrl/weight_update/_rpc.py207 # Step 1: Signal the remote collector via RPC to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_rpc.py213 # Step 2: Send weights asynchronously via torch.distributedCOMMENT
LOW⚡torchrl/weight_update/_ray.py206 # Step 1: Signal the remote actor via Ray to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_ray.py214 # Step 2: Send weights via torch.distributed (async)COMMENT
LOW⚡torchrl/weight_update/_ray.py218 # Step 3: Wait for the Ray call to complete (receiver has applied weights)COMMENT
LOW⚡torchrl/weight_update/_ray.py232 # Step 1: Signal the actor via Ray to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_ray.py242 # Step 2: Send weights via torch.distributed (async)COMMENT
LOW⚡torchrl/weight_update/llm/sglang_nccl.py604 # Step 1: Send a single HTTP request with all weight metadata.COMMENT
LOW⚡torchrl/weight_update/llm/sglang_nccl.py614 # Step 2: Broadcast each weight tensor via NCCL in the same order.COMMENT
LOW⚡torchrl/weight_update/llm/sglang_nccl.py623 # Step 3: Wait for the HTTP response confirming server received all weightsCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1190 # Step 1: Start trainer NCCL group in a background thread — it blocksCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1204 # Step 2: Dispatch init_weight_transfer_engine to all vLLM actorsCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1220 # Step 3: Wait for both sides to completeCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1293 # Step 1: Tell all actors to start receiving weightsCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1298 # Step 2: Send weights from trainer sideCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py1317 # Step 3: Wait for all actors to finish receivingCOMMENT
LOW⚡torchrl/modules/llm/backends/sglang/sglang_server.py707 # Step 1: Signal server to expect this weightCOMMENT
LOW⚡torchrl/modules/llm/backends/sglang/sglang_server.py712 # Step 2: Broadcast the weight via NCCLCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py81# Step 1: Basic Environment ConfigurationCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py189# Step 2: Tool Execution HelperCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py262# Step 3: Starting the InteractionCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py292# Step 4: Performing the SearchCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py321# Step 5: Providing the AnswerCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py50# Step 1: build and populate a replay bufferCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py77# Step 2: wrap the buffer as an IterableDatasetCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py109# Step 3: key filteringCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py124# Step 4: device placementCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py137# Step 5: nested keysCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py181# Step 1: define a stand-in reward modelCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py216# Step 2: wrap with default TorchRL token keysCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py234# Step 3: run a batch through the wrapperCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py256# Step 4: custom keys and nested reward keyCOMMENT
LOWknowledge_base/FLAKY_TESTS.md42## Step 1: Gather Flaky Test InformationCOMMENT
LOWknowledge_base/FLAKY_TESTS.md96## Step 2: Identify Non-Deterministic Failure CausesCOMMENT
LOWknowledge_base/FLAKY_TESTS.md131## Step 3: Implement the FixCOMMENT
LOWknowledge_base/FLAKY_TESTS.md184## Step 4: Create a PR with the Fix AND Test ValidationCOMMENT
LOWknowledge_base/FLAKY_TESTS.md274## Step 5: Monitor the CI RunCOMMENT
LOWknowledge_base/FLAKY_TESTS.md302## Step 6: Verify the FixCOMMENT
LOWknowledge_base/FLAKY_TESTS.md328## Step 7: Cleanup Before MergingCOMMENT
AI Slop Vocabulary47 hits · 107 pts
SeverityFileLineSnippetContext
LOWtest/llm/test_llm_collectors.py644 # We have the tokens, let's just use themCOMMENT
LOWsota-implementations/expert-iteration/ei_utils.py88 # we can just use 0 here.COMMENT
LOW…lementations/expert-iteration/expert-iteration-sync.py433 # we can just set a big number, the buffer will be emptied anywayCOMMENT
MEDIUMexamples/agents/recurrent_actor.py182# its recurrent connections to maintain state across time steps. This mode may utilize CuDNN to accelerate the processinCOMMENT
MEDIUMbenchmarks/dreamer_v3.yaml31 # The harness sets inference_backend per series; chunking follows theCOMMENT
MEDIUMbenchmarks/dreamer_v3.yaml91 max_time: 600.0 # Safety ceiling; the harness stops after its measured rounds.CODE
MEDIUM.github/scripts/compare_pr_benchmarks.py45 """Return a rate based on the robust per-round duration statistic."""STRING
LOWtorchrl/weight_update/_shared.py909 # If no shared transport, just return the fresh weightsCOMMENT
MEDIUMtorchrl/collectors/_single.py1810 # this way of checking cuda is robust to lazy stacks with mismatching shapesCOMMENT
MEDIUMtorchrl/objectives/tdmpc2.py99 """Track the robust value scale used by the TD-MPC2 policy objective."""STRING
MEDIUMtorchrl/objectives/common.py492 # To make it robust to device casting, we must register list ofCOMMENT
LOWtorchrl/objectives/llm/grpo.py620 # TODO: eventually, we want to always use `get_dist` and just pass the key of the maskCOMMENT
MEDIUMtorchrl/objectives/llm/grpo.py1503 # Cat is the most robust way to combine the trajsCOMMENT
MEDIUMtorchrl/trainers/algorithms/on_policy.py596 # Set up comprehensive logging for on-policy trainingCOMMENT
MEDIUMtorchrl/trainers/algorithms/sac.py258 # Set up comprehensive logging for SAC trainingCOMMENT
LOWtorchrl/modules/llm/policies/common.py747 # For log-prob distributions, we just return the pre-computed log-probsCOMMENT
MEDIUMtorchrl/modules/llm/policies/transformers_wrapper.py1042 # We are going to map this tokens_in to a tensordict to facilitate the padding in case we need itCOMMENT
MEDIUMtorchrl/modules/llm/policies/transformers_wrapper.py1465 # We are going to map this tokens_in to a tensordict to facilitate the padding in case we need itCOMMENT
LOWtorchrl/modules/mcts/scores.py425 # Don't update weights for zero probability - just returnCOMMENT
LOWtorchrl/envs/utils.py1489 # case we just return the dataCOMMENT
MEDIUMtorchrl/envs/utils.py200 """Represents the keys as a tree to facilitate iteration."""STRING
LOWtorchrl/envs/libs/dm_control.py318 # just use a common EGL_DEVICE_ID environment variable for all processes.COMMENT
MEDIUMtorchrl/envs/transforms/_normalization.py711 # to facilitate the computation of the stats using TD internals.COMMENT
MEDIUMtorchrl/envs/transforms/_misc.py75 """Calls pin_memory on the tensordict to facilitate writing on CUDA devices."""STRING
MEDIUMtorchrl/data/llm/topk.py122 # Cat is the most robust way to combine the trajsCOMMENT
MEDIUMtorchrl/data/replay_buffers/utils.py1200 # We currently ignore out in this call but we should leverage thatCOMMENT
LOWtorchrl/data/replay_buffers/utils.py1379 # if Tensor, we just create a MemoryMappedTensor of the desired shape, device and dtypeCOMMENT
LOWtorchrl/data/replay_buffers/utils.py1396 # if Tensor, we just create a MemoryMappedTensor of the desired shape, device and dtypeCOMMENT
LOWtorchrl/data/replay_buffers/storages/tensor.py1125 # if Tensor, we just create a MemoryMappedTensor of the desired shape, device and dtypeCOMMENT
MEDIUMtutorials/sphinx-tutorials/dqn_with_rnn.py229# values for these attributes to facilitate its construction.COMMENT
MEDIUMtutorials/sphinx-tutorials/torchrl_envs.py655# One can therefore think carefully about the transform design to leverage theCOMMENT
LOWtutorials/sphinx-tutorials/torchrl_envs.py344# To compose transforms, simply use the ``Compose`` class:COMMENT
MEDIUM⚡tutorials/sphinx-tutorials/getting-started-1.py26# Accommodating all these scenarios can be quite intricate. In this succinctCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/getting-started-1.py27# tutorial, we will delve into the core functionality of TorchRL in terms ofCOMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py337# Essentially we just say that theCOMMENT
LOW…orials/sphinx-tutorials/multiagent_competitive_ddpg.py612# **From this point on, the multi-agent-specific components have been instantiated, and we will simply use the sameCOMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-0.py79# Essentially, :class:`~tensordict.TensorDict` is a generic key-based dataCOMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-3.py144# Data collectors are very useful when it comes to coding state-of-the-artCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py200# This allows leveraging the Single Instruction Multiple Data (SIMD) paradigm of GPUs and significantlyCOMMENT
MEDIUMtutorials/sphinx-tutorials/multiagent_ppo.py224# We will also use ``num_vmas_envs`` vectorized environments, to leverage batch simulation.COMMENT
LOW⚡tutorials/sphinx-tutorials/multiagent_ppo.py532# **From this point on, the multi-agent-specific components have been instantiated, and we will simply use the sameCOMMENT
LOWtutorials/sphinx-tutorials/rb_tutorial.py387# To enable multithreaded sampling, just pass a positive integer to theCOMMENT
MEDIUMtutorials/sphinx-tutorials/coding_ddpg.py577# To leverage the vectorization capabilities of PyTorch, we adoptCOMMENT
LOWtutorials/sphinx-tutorials/coding_ddpg.py184# accessible but this will just return a **detached** version of theCOMMENT
LOWtutorials/sphinx-tutorials/coding_ddpg.py430# are collected by :func:`env.step()`, simply pass the ``from_pixels=True``COMMENT
MEDIUMtutorials/sphinx-tutorials/pendulum.py170# To facilitate the reading and writing from that ``tensordict`` and to make sureCOMMENT
MEDIUMtutorials/sphinx-tutorials/coding_dqn.py67# past, we can still pass it in conjunction with the various actions availableCOMMENT
Fake / Example Data75 hits · 86 pts
SeverityFileLineSnippetContext
LOWREADME.md217processes, weight updaters, evaluator loops, profiling hooks, and fake-dataCODE
LOWtest/llm/test_llm_objectives.py48 "Lorem ipsum dolor sit amet,",CODE
LOWtest/llm/test_llm_objectives.py48 "Lorem ipsum dolor sit amet,",CODE
LOW⚡test/objectives/test_dreamer.py421 loss_td, fake_data = loss_module(tensordict.reshape(-1))CODE
LOW⚡test/objectives/test_dreamer.py422 assert not fake_data.requires_gradCODE
LOW⚡test/objectives/test_dreamer.py423 assert fake_data.shape == torch.Size([tensordict.numel(), imagination_horizon])CODE
LOWtest/objectives/test_dreamer.py450 loss_td, fake_data = loss_module(tensordict)CODE
LOWtest/objectives/test_dreamer.py452 assert not fake_data.requires_gradCODE
LOW⚡test/objectives/test_dreamer_v3.py814 loss_td, fake_data = loss_module(CODE
LOW⚡test/objectives/test_dreamer_v3.py819 fake_data.select(*actor_model.in_keys).detach()CODE
LOW⚡test/objectives/test_dreamer_v3.py822 fake_data["discount_weight"] * distribution.entropy().unsqueeze(-1)CODE
LOW⚡test/objectives/test_dreamer_v3.py908 loss_td, fake_data = loss_module(CODE
LOW⚡test/objectives/test_dreamer_v3.py914 fake_data["discount_weight"][0, :, 0], expected_weightCODE
LOW⚡test/objectives/test_dreamer_v3.py917 fake_data["next", "continuation"],CODE
LOW⚡test/objectives/test_dreamer_v3.py918 torch.full_like(fake_data["next", "continuation"], 0.5),CODE
LOW⚡test/objectives/test_dreamer_v3.py920 assert not fake_data["discount_weight"].requires_gradCODE
LOW⚡test/objectives/test_dreamer_v3.py926 actor_inputs = fake_data.select(*actor_model.in_keys, strict=False).detach()CODE
LOW⚡test/objectives/test_dreamer_v3.py928 log_prob = distribution.log_prob(fake_data["action"].detach())CODE
LOW⚡test/objectives/test_dreamer_v3.py929 log_prob = _match_trailing_dim(log_prob, fake_data["lambda_target"])CODE
LOW⚡test/objectives/test_dreamer_v3.py930 baseline_td = fake_data.select(*value_model.in_keys, strict=False)CODE
LOW⚡test/objectives/test_dreamer_v3.py932 advantage = (fake_data["lambda_target"] - baseline_td["state_value"]).detach()CODE
LOW⚡test/objectives/test_dreamer_v3.py933 expected_loss = -(fake_data["discount_weight"] * log_prob * advantage).mean()CODE
LOW⚡test/objectives/test_dreamer_v3.py943 value_loss(fake_data.detach())CODE
LOW⚡test/objectives/test_dreamer_v3.py2090 loss_td, fake_data = loss_module(CODE
LOW⚡test/objectives/test_dreamer_v3.py2093 baseline_td = fake_data.select(*value_model.in_keys, strict=False)CODE
LOW⚡test/objectives/test_dreamer_v3.py2095 advantage = (fake_data["lambda_target"] - baseline_td["state_value"]).detach()CODE
LOW⚡test/objectives/test_dreamer_v3.py2097 fake_data["action_log_prob"], fake_data["lambda_target"]CODE
LOWtest/objectives/test_dreamer_v3.py792 loss_td, fake_data = loss_module(tensordict.reshape(-1))CODE
LOWtest/objectives/test_dreamer_v3.py868 loss_td, fake_data = loss_module(tensordict)CODE
LOWtest/objectives/test_dreamer_v3.py873 assert fake_data.shape == (tensordict.shape[0], 3)CODE
LOWtest/objectives/test_dreamer_v3.py1111 loss_td, fake_data = actor_loss(CODE
LOWtest/objectives/test_dreamer_v3.py1115 assert fake_data["lambda_target"].shape[-1] == 1CODE
LOWtest/objectives/test_dreamer_v3.py2109 compiled_scale(fake_data["lambda_target"]),CODE
LOWtest/objectives/test_dreamer_v3.py2132 loss_td, fake_data = loss_module(CODE
LOWtest/objectives/test_dreamer_v3.py2135 expected = -(fake_data["lambda_target"] / 10.0).mean()CODE
LOWtest/objectives/test_dreamer_v3.py2154 loss_td, fake_data = loss_module(CODE
LOWtest/objectives/test_dreamer_v3.py2158 fake_data["lambda_target"].detach(),CODE
LOWtest/objectives/test_dreamer_v3.py2179 loss_td, fake_data = loss_module(CODE
LOWtest/objectives/test_dreamer_v3.py2183 fake_data["lambda_target"].detach(),CODE
LOW⚡test/transforms/test_module_transforms.py308 dummy_data = TensorDict(observation=torch.zeros(2, 3), batch_size=[2])CODE
LOW⚡test/transforms/test_module_transforms.py311 assert (module(dummy_data)["action"] == 2).all()CODE
LOW⚡test/transforms/test_module_transforms.py319 assert (module(dummy_data)["action"] == 1).all()CODE
LOW⚡benchmarks/test_llm.py64 "Lorem ipsum dolor sit amet",CODE
LOW⚡benchmarks/test_llm.py64 "Lorem ipsum dolor sit amet",CODE
LOW⚡benchmarks/test_llm.py72 "Lorem ipsum dolor sit amet",CODE
LOW⚡benchmarks/test_llm.py72 "Lorem ipsum dolor sit amet",CODE
LOW⚡torchrl/objectives/dreamer.py299 fake_data = self.model_based_env.rollout(CODE
LOW⚡torchrl/objectives/dreamer.py305 next_tensordict = step_mdp(fake_data, keep_other=True)CODE
LOW⚡torchrl/objectives/dreamer.py309 reward = fake_data.get(("next", self.tensor_keys.reward))CODE
LOW⚡torchrl/objectives/dreamer.py312 fake_data.set("lambda_target", lambda_target)CODE
LOWtorchrl/objectives/dreamer.py325 return loss_tensordict, fake_data.dataCODE
LOW⚡torchrl/objectives/dreamer.py427 def forward(self, fake_data) -> torch.Tensor:CODE
LOW⚡torchrl/objectives/dreamer.py428 lambda_target = fake_data.get("lambda_target")CODE
LOW⚡torchrl/objectives/dreamer.py430 tensordict_select = fake_data.select(*self.value_model.in_keys, strict=False)CODE
LOWtorchrl/objectives/dreamer.py463 self._clear_weakrefs(fake_data, loss_tensordict)CODE
LOWtorchrl/objectives/dreamer.py465 return loss_tensordict, fake_dataCODE
LOW⚡torchrl/objectives/dreamer_v3.py810 fake_data = self.model_based_env.rollout(CODE
LOW⚡torchrl/objectives/dreamer_v3.py819 next_tensordict = step_mdp(fake_data, keep_other=True)CODE
LOW⚡torchrl/objectives/dreamer_v3.py824 reward = fake_data.get(("next", self.tensor_keys.reward))CODE
LOW⚡torchrl/objectives/dreamer_v3.py830 first_td = fake_data[..., :1].select(CODE
15 more matches not shown…
Verbosity Indicators44 hits · 85 pts
SeverityFileLineSnippetContext
LOW⚡test/llm/test_wrapper.py2396 # Step 1: Generate the canonical response tokens with vLLM.COMMENT
LOW⚡test/llm/test_wrapper.py2402 # Step 2: Extract generated tokens and create new input for log-probs computationCOMMENT
LOWtest/llm/test_wrapper.py2445 # Step 3: Create log-probs only wrappersCOMMENT
LOWtest/llm/test_wrapper.py2464 # Step 4: Compute log-probs for the full sequence (original + generated)COMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py142 # Step 1: Stack to contiguous (this allocates new memory)COMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py144 # Step 2: Write to storageCOMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py176 # Step 1: Create lazy stack (no allocation, just wrapping)COMMENT
LOW⚡benchmarks/test_storage_write_benchmark.py178 # Step 2: Write to storage (storage handles the lazy stack)COMMENT
LOW⚡torchrl/weight_update/_rpc.py181 # Step 1: Signal the remote collector via RPC to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_rpc.py185 # Step 2: Send weights via torch.distributed (blocks until receiver calls recv())COMMENT
LOW⚡torchrl/weight_update/_rpc.py188 # Step 3: Wait for RPC to complete (receiver has applied weights)COMMENT
LOW⚡torchrl/weight_update/_rpc.py207 # Step 1: Signal the remote collector via RPC to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_rpc.py213 # Step 2: Send weights asynchronously via torch.distributedCOMMENT
LOW⚡torchrl/weight_update/_ray.py206 # Step 1: Signal the remote actor via Ray to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_ray.py214 # Step 2: Send weights via torch.distributed (async)COMMENT
LOW⚡torchrl/weight_update/_ray.py218 # Step 3: Wait for the Ray call to complete (receiver has applied weights)COMMENT
LOW⚡torchrl/weight_update/_ray.py232 # Step 1: Signal the actor via Ray to start receiving (async)COMMENT
LOW⚡torchrl/weight_update/_ray.py242 # Step 2: Send weights via torch.distributed (async)COMMENT
LOW⚡torchrl/weight_update/llm/sglang_nccl.py604 # Step 1: Send a single HTTP request with all weight metadata.COMMENT
LOW⚡torchrl/weight_update/llm/sglang_nccl.py614 # Step 2: Broadcast each weight tensor via NCCL in the same order.COMMENT
LOW⚡torchrl/weight_update/llm/sglang_nccl.py623 # Step 3: Wait for the HTTP response confirming server received all weightsCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1190 # Step 1: Start trainer NCCL group in a background thread — it blocksCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1204 # Step 2: Dispatch init_weight_transfer_engine to all vLLM actorsCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1220 # Step 3: Wait for both sides to completeCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1293 # Step 1: Tell all actors to start receiving weightsCOMMENT
LOW⚡torchrl/modules/llm/backends/vllm/vllm_async.py1298 # Step 2: Send weights from trainer sideCOMMENT
LOWtorchrl/modules/llm/backends/vllm/vllm_async.py1317 # Step 3: Wait for all actors to finish receivingCOMMENT
LOW⚡torchrl/modules/llm/backends/sglang/sglang_server.py707 # Step 1: Signal server to expect this weightCOMMENT
LOW⚡torchrl/modules/llm/backends/sglang/sglang_server.py712 # Step 2: Broadcast the weight via NCCLCOMMENT
LOWtorchrl/modules/distributions/discrete.py844 # For token-level masking, we need to check if specific tokens are maskedCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py81# Step 1: Basic Environment ConfigurationCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py189# Step 2: Tool Execution HelperCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py262# Step 3: Starting the InteractionCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py292# Step 4: Performing the SearchCOMMENT
LOW⚡tutorials/sphinx-tutorials/llm_browser.py321# Step 5: Providing the AnswerCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py50# Step 1: build and populate a replay bufferCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py77# Step 2: wrap the buffer as an IterableDatasetCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py109# Step 3: key filteringCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py124# Step 4: device placementCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py137# Step 5: nested keysCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py181# Step 1: define a stand-in reward modelCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py216# Step 2: wrap with default TorchRL token keysCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py234# Step 3: run a batch through the wrapperCOMMENT
LOW⚡tutorials/sphinx-tutorials/trl_interop.py256# Step 4: custom keys and nested reward keyCOMMENT
Slop Phrases18 hits · 43 pts
SeverityFileLineSnippetContext
LOWtorchrl/envs/transforms/_base.py212 - Don't forget to edits the specs if needed: top level: :meth:`~torchrl.envs.Transform.transform_output_spec`,STRING
MEDIUMtorchrl/data/llm/history.py316 >>> # Now you can use it with auto-detectionCODE
MEDIUMtutorials/sphinx-tutorials/dqn_with_rnn.py266# As mentioned earlier, we still need aCOMMENT
LOWtutorials/sphinx-tutorials/dqn_with_rnn.py61# If you are running this in Google Colab, make sure you install the following dependencies:COMMENT
LOWtutorials/sphinx-tutorials/torchrl_envs.py280# To run this part of the tutorial, make sure you have installed dm_control:COMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-1.py310# - Have a look at how you can use an RNN within the policy (aCOMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py948# Finally, you can modify the parameters of this tutorial to try many other configurations and scenariosCOMMENT
MEDIUM⚡…orials/sphinx-tutorials/multiagent_competitive_ddpg.py952# Here are a few videos of some possible scenarios you can try in VMAS.COMMENT
MEDIUM…orials/sphinx-tutorials/multiagent_competitive_ddpg.py663# To store your buffer on the GPU, you can use :class:`~torchrl.data.replay_buffers.LazyTensorStorage`, passing the desiCOMMENT
LOW…orials/sphinx-tutorials/multiagent_competitive_ddpg.py43# If you are running this in Google Colab, make sure you install the following dependencies:COMMENT
MEDIUMtutorials/sphinx-tutorials/getting-started-4.py31# portable CSV logger (:class:`~torchrl.record.loggers.csv.CSVLogger`) that you can useCOMMENT
MEDIUMtutorials/sphinx-tutorials/export.py335# Here's an example of how you can use AOTInductor to export your policy, inspired by theCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py791# Finally, you can modify the parameters of this tutorial to try many other configurations and scenariosCOMMENT
MEDIUM⚡tutorials/sphinx-tutorials/multiagent_ppo.py793# Here are a few videos of some possible scenarios you can try in VMAS.COMMENT
LOWtutorials/sphinx-tutorials/multiagent_ppo.py43# If you are running this in Google Colab, make sure you install the following dependencies:COMMENT
LOWtutorials/sphinx-tutorials/coding_ddpg.py286# When computing this value, we must make sure to take the value parameters outCOMMENT
LOWtutorials/sphinx-tutorials/getting-started-2.py111# loss. If you want to make sure you're fully in control of what is happening,COMMENT
LOWtutorials/sphinx-tutorials/coding_ppo.py39# If you are running this in Google Colab, make sure you install the following dependencies:COMMENT
Hallucination Indicators3 hits · 40 pts
SeverityFileLineSnippetContext
CRITICAL⚡test/test_render.py1356 env.base_env.unwrapped.data.qpos.copy(),CODE
CRITICAL⚡test/test_render.py1362 env.base_env.unwrapped.data.qpos.copy(),CODE
CRITICALtorchrl/envs/libs/gym.py819 return gym.envs.registration.registry.env_specs.keys()CODE
Dead Code16 hits · 32 pts
SeverityFileLineSnippetContext
MEDIUMtest/objectives/test_bc.py41CODE
MEDIUMtest/objectives/test_bc.py42CODE
MEDIUMtorchrl/envs/common.py1069CODE
MEDIUMtorchrl/envs/transforms/_normalization.py912CODE
MEDIUMtorchrl/envs/transforms/_normalization.py913CODE
MEDIUMtorchrl/envs/transforms/_normalization.py915CODE
MEDIUMtorchrl/envs/transforms/_normalization.py916CODE
MEDIUMtorchrl/envs/transforms/_normalization.py917CODE
MEDIUMtorchrl/envs/transforms/_normalization.py918CODE
MEDIUMtorchrl/envs/transforms/_normalization.py919CODE
MEDIUMtorchrl/envs/transforms/_normalization.py924CODE
MEDIUMtorchrl/envs/transforms/_normalization.py925CODE
MEDIUMtorchrl/envs/transforms/_normalization.py937CODE
MEDIUMtorchrl/envs/transforms/_normalization.py938CODE
MEDIUMtorchrl/envs/transforms/_normalization.py939CODE
MEDIUMtorchrl/envs/transforms/_normalization.py941CODE
AI Response Leakage3 hits · 22 pts
SeverityFileLineSnippetContext
HIGHtutorials/sphinx-tutorials/rb_tutorial.py807# ``("collector", "traj_ids")``. In this example, we construct dataCOMMENT
HIGHtutorials/sphinx-tutorials/pendulum.py307# In this example, we do not pass a done state as this is not mandatoryCOMMENT
HIGHtutorials/sphinx-tutorials/pendulum.py852# In this example, we will train a simple policy using the reward as aCOMMENT
Example Usage Blocks5 hits · 8 pts
SeverityFileLineSnippetContext
LOWdocs/build_local.sh4# Usage:COMMENT
LOW…b/unittest/helpers/assert_torch_tensordict_versions.sh4# Usage:COMMENT
LOW.github/unittest/helpers/assert_torch_version.sh4# Usage:COMMENT
LOW.github/workflows/auto-tag.yml3# Usage:COMMENT
LOW.github/workflows/assign.yml3# Usage:COMMENT
TODO Padding3 hits · 4 pts
SeverityFileLineSnippetContext
LOWtorchrl/envs/llm/libs/mlgym.py228 # TODO: implement add commands method in environmentCOMMENT
LOWtorchrl/data/map/tree.py228 # TODO: implement specsCOMMENT
LOWtorchrl/data/map/tree.py245 # TODO: implement specsCOMMENT
Overly Generic Function Names5 hits · 2 pts
SeverityFileLineSnippetContext
LOWtest/test_docstring_args_checker.py31def helper(first, second):STRING
LOWtest/test_docstring_args_checker.py71def helper(first, second, *, mode="strict", retries=0):STRING
LOWtest/test_docstring_args_checker.py93def helper(first, second, *, mode="strict", retries=0):STRING
LOWtorchrl/_utils.py250 >>> def my_function():STRING
LOWtorchrl/_utils.py1372 ... def my_function():STRING