Repository Analysis

NVIDIA/TensorRT-LLM

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

20.1 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of NVIDIA/TensorRT-LLM, a Python project with 14,114 GitHub stars. SynthScan v2.0 examined 1,828,041 lines of code across 5507 source files, recording 23751 pattern matches distributed across 26 syntactic categories. The overall adjusted score of 20.1 places this repository in the Moderate AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

20.1
Adjusted Score
20.1
Raw Score
100%
Time Factor
2026-07-14
Last Push
14.1K
Stars
Python
Language
1.8M
Lines of Code
5.5K
Files
23.8K
Pattern Hits
2026-07-14
Scan Date
0.12
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 42HIGH 611MEDIUM 4755LOW 18343

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 23751 distinct pattern matches across 26 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Decorative Section Separators4185 hits · 14018 pts
SeverityFileLineSnippetContext
MEDIUMtests/unittest/metrics/test_collector.py683# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/metrics/test_collector.py685# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/metrics/test_collector.py946# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/metrics/test_collector.py949# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/metrics/test_collector.py285# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/metrics/test_collector.py287# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/test_triton_prefill.py168# ===========================================================================COMMENT
MEDIUMtests/unittest/_torch/attention/test_triton_prefill.py170# ===========================================================================COMMENT
MEDIUMtests/unittest/_torch/attention/test_triton_prefill.py398# ===========================================================================COMMENT
MEDIUMtests/unittest/_torch/attention/test_triton_prefill.py400# ===========================================================================COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py83# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py85# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py568# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py570# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py661# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py663# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py727# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/model_attn_config.py730# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py265# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py277# ---------------------------------------------------------------------------COMMENT
MEDIUM…s/unittest/_torch/attention/test_attention_backends.py229# ---------------------------------------------------------------------------COMMENT
MEDIUM…s/unittest/_torch/attention/test_attention_backends.py234# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py36# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py39# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py137# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py139# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py215# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py217# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py292# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py294# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py550# ---------------------------------------------------------------------------COMMENT
MEDIUM…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py552# ---------------------------------------------------------------------------COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py36# ---------------------------------------------------------------------------COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py38# ---------------------------------------------------------------------------COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py44# ===================================================================COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py46# ===================================================================COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py323# ===================================================================COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py325# ===================================================================COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py490# ===================================================================COMMENT
MEDIUM…nittest/_torch/attention/sparse/test_cpp_custom_ops.py492# ===================================================================COMMENT
MEDIUM…orch/attention/sparse/test_cute_dsl_gvr_topk_decode.py305# ===========================================================================COMMENT
MEDIUM…orch/attention/sparse/test_cute_dsl_gvr_topk_decode.py313# ===========================================================================COMMENT
MEDIUM…orch/attention/sparse/test_cute_dsl_gvr_topk_decode.py432# ===========================================================================COMMENT
MEDIUM…orch/attention/sparse/test_cute_dsl_gvr_topk_decode.py448# ===========================================================================COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py53# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py55# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py71# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py73# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py89# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py91# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py148# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py150# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py404# ---------------------------------------------------------------------------COMMENT
MEDIUM…test/_torch/attention/sparse/dsa/test_short_seq_mha.py406# ---------------------------------------------------------------------------COMMENT
MEDIUM…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py39# ---------------------------------------------------------------------------COMMENT
MEDIUM…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py41# ---------------------------------------------------------------------------COMMENT
MEDIUM…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py68# ---------------------------------------------------------------------------COMMENT
MEDIUM…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py70# ---------------------------------------------------------------------------COMMENT
MEDIUM…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py108# ---------------------------------------------------------------------------COMMENT
MEDIUM…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py114# ---------------------------------------------------------------------------COMMENT
4125 more matches not shown…
Hyper-Verbose Identifiers9952 hits · 9098 pts
SeverityFileLineSnippetContext
LOWsetup.py200def should_skip_precompiled_package_data(filename: str) -> bool:CODE
LOWtests/unittest/conftest.py301def pytest_collection_modifyitems(session, config, items):CODE
LOWtests/unittest/conftest.py452def process_gpu_memory_info_available():CODE
LOWtests/unittest/test_pip_install.py11def get_expected_license_files():CODE
LOWtests/unittest/test_pip_install.py160def get_torch_constraint_file(constraint_dir="."):CODE
LOWtests/unittest/test_s3_output.py54def test_small_stdout_is_inlined_without_upload(tmp_path):CODE
LOWtests/unittest/test_s3_output.py67def test_empty_stdout_is_removed_after_report(tmp_path):CODE
LOWtests/unittest/test_s3_output.py80def test_large_stdout_keeps_existing_upload_report(tmp_path):CODE
LOWtests/unittest/test_s3_output.py96def test_uploaded_stdout_is_removed_after_sync_upload(tmp_path):CODE
LOWtests/unittest/test_s3_output.py117def test_deferred_stdout_is_removed_after_upload_finishes(tmp_path):CODE
LOWtests/unittest/test_s3_output.py138def test_small_log_file_is_not_inlined(tmp_path):CODE
LOWtests/unittest/test_s3_output.py152def test_fd_redirector_reader_thread_is_daemon_when_pipe_writer_lingers(tmp_path):CODE
LOWtests/unittest/metrics/test_collector.py99 def test_queue_and_load_gauges(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py106 def test_completed_requests_counter(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py114 def test_completed_requests_zero_not_incremented(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py119 def test_iteration_latency_ms_to_seconds(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py161 def test_inflight_batching_gauges(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py171 def test_missing_inflight_batching_stats(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py180 def test_spec_decoding_metrics(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py188 def test_missing_spec_decoding_stats(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py330 def test_prompt_tokens_incremented(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py334 def test_generation_tokens_incremented(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py338 def test_token_counters_accumulate(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py345 def test_missing_token_counts_no_error(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py428 def test_prefill_time_observed(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py433 def test_decode_time_observed(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py438 def test_inference_time_observed(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py513 def test_phase_timings_computed(self):CODE
LOWtests/unittest/metrics/test_collector.py520 def test_base_latencies_computed(self):CODE
LOWtests/unittest/metrics/test_collector.py526 def test_zero_queue_time_is_included(self):CODE
LOWtests/unittest/metrics/test_collector.py538 def test_generation_tokens_in_stat(self):CODE
LOWtests/unittest/metrics/test_collector.py542 def test_output_length_one_has_tokens_but_no_tpot(self):CODE
LOWtests/unittest/metrics/test_collector.py548 def test_per_candidate_metrics_computed_independently(self):CODE
LOWtests/unittest/metrics/test_collector.py664 def test_empty_bucket_list_raises(self):CODE
LOWtests/unittest/metrics/test_collector.py670 def test_unsorted_bucket_list_raises(self):CODE
LOWtests/unittest/metrics/test_collector.py676 def test_duplicate_bucket_values_raises(self):CODE
LOWtests/unittest/metrics/test_collector.py952def _counter_value_with_labels(metric, labels: Dict[str, str]) -> float:CODE
LOWtests/unittest/metrics/test_collector.py960 def test_cached_tokens_counter_incremented(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py968 def test_cached_tokens_histogram_observed(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py990 def test_cached_tokens_accumulate(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1000 def test_cache_metrics_absent_no_increment(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1009 def test_no_observation_without_finish_reason(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1200 def test_missing_ifb_stats_no_error(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1210 def test_error_counter_incremented_by_code(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1215 def test_error_counter_accumulates_per_code(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1224 def test_error_counter_accepts_string_code(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py1231 def test_error_counter_default_empty_code(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py141 def test_kv_cache_block_gauges(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py149 def test_kv_cache_utilization(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py233 def test_parallel_config_info(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py247 def test_speculative_config_info(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py262 def test_kv_cache_config_info(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py308 def test_success_counter_incremented(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py313 def test_success_counter_tracks_finish_reason_separately(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py356 def test_zero_tokens_not_incremented(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py462 def test_missing_phase_times_no_observation(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py474 def test_no_observation_without_finish_reason(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py488 def test_queue_time_zero_is_recorded_to_prometheus(self, collector):CODE
LOWtests/unittest/metrics/test_collector.py560 def test_zero_output_length_excludes_tokens(self):CODE
LOWtests/unittest/metrics/test_collector.py564 def test_missing_timestamps_no_phase_timings(self):CODE
9892 more matches not shown…
Over-Commented Block2783 hits · 2618 pts
SeverityFileLineSnippetContext
LOWconstraints.txt1# These vulnerabilities were inherited from the base image (pytorch:25.12-py3) and should be removed when the base imageCOMMENT
LOWsetup.py1# SPDX-FileCopyrightText: Copyright (c) 2022-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWruff-legacy.toml1# <<<< AUTO-GENERATED by scripts/legacy_utils.py gen-configs >>>>COMMENT
LOW.coderabbit.yaml1# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWdocker/common/install_ci.sh1#!/bin/bashCOMMENT
LOWtests/unittest/conftest.py1# SPDX-FileCopyrightText: Copyright (c) 2022-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/test_s3_output.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/metrics/test_collector.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/test_connector.py1# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/test_hf_quant_config.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/test_torch_multi_arange.py1# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.COMMENT
LOW…ittest/_torch/weight_sharing/_source_identity_fakes.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…_torch/weight_sharing/test_gms_source_identity_gate.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…/_torch/weight_sharing/test_mx_source_identity_gate.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…unittest/_torch/weight_sharing/test_source_identity.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/attention/test_triton_prefill.py1# SPDX-FileCopyrightText: Copyright (c) 2022-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/attention/backend_capability.py21# sliding_window - sliding-window attention via attention_window_sizeCOMMENT
LOW…s/unittest/_torch/attention/test_skip_softmax_sm120.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/attention/backend_case.py101 fused_rope: bool = FalseCOMMENT
LOWtests/unittest/_torch/attention/backend_case.py261 )COMMENT
LOW…ts/unittest/_torch/attention/test_attention_op_sync.py1# Copyright (c) 2025-2026, NVIDIA CORPORATION. All rights reserved.COMMENT
LOW…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1# Copyright (c) 2026, NVIDIA CORPORATION. All rights reserved.COMMENT
LOW…attention/sparse/test_cute_dsl_fp8_paged_mqa_logits.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…attention/sparse/test_cute_dsl_fp8_paged_mqa_logits.py261 # next_n positions in one atom regardless of value).COMMENT
LOW…nittest/_torch/attention/sparse/test_cpp_custom_ops.py1# SPDX-FileCopyrightText: Copyright (c) 2022-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…orch/attention/sparse/test_cute_dsl_gvr_topk_decode.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…test/_torch/attention/sparse/dsa/test_short_seq_mha.py1# SPDX-FileCopyrightText: Copyright (c) 2022-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py1821 # Previously cached tokensCOMMENT
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2081 # Expected results:COMMENT
LOW…est/_torch/attention/sparse/dsa/test_dsa_sparse_mla.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…n/sparse/deepseek_v4/test_deepseek_v4_cache_manager.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ttention/sparse/deepseek_v4/test_deepseek_v4_o_proj.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…tion/sparse/deepseek_v4/test_deepseek_v4_sparse_mla.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…attention/sparse/deepseek_v4/test_compressor_module.py1#!/usr/bin/env python3COMMENT
LOW…ittest/_torch/attention/sparse/deepseek_v4/__init__.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…arse/deepseek_v4/test_deepseek_v4_indices_transform.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/distributed/test_safe_mpi_comm.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…/unittest/_torch/visual_gen/test_attention_cute_dsl.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…isual_gen/test_wan21_t2v_teacache_user_coefficients.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/visual_gen/test_utils.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/visual_gen/test_teacache.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…/unittest/_torch/visual_gen/test_wan22_i2v_teacache.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py1# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ttest/_torch/visual_gen/test_attention_cute_dsl_vsa.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…/unittest/_torch/visual_gen/test_wan22_t2v_teacache.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…s/unittest/_torch/visual_gen/test_visual_gen_params.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…t/_torch/visual_gen/multi_gpu/test_attn2d_attention.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…isual_gen/multi_gpu/test_flux2_transformer_parallel.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ttest/_torch/visual_gen/multi_gpu/test_ltx2_ulysses.py101# =============================================================================COMMENT
LOW…/_torch/visual_gen/multi_gpu/_visual_gen_dist_utils.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…st/_torch/visual_gen/multi_gpu/test_wan_vsa_ulysses.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…est/_torch/visual_gen/multi_gpu/test_ring_attention.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…s/unittest/_torch/visual_gen/multi_gpu/test_flux_tp.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ch/visual_gen/multi_gpu/test_ulysses_sage_attention.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…/visual_gen/multi_gpu/test_wan_transformer_parallel.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ttest/_torch/visual_gen/multi_gpu/test_tp_attention.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…ts/unittest/_torch/visual_gen/multi_gpu/test_wan_tp.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOW…rch/visual_gen/multi_gpu/test_wan_pipeline_parallel.py1# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
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Cross-File Repetition417 hits · 2085 pts
SeverityFileLineSnippetContext
HIGHtests/unittest/conftest.py0apply waives based on the waive state specified by the given waives_file.STRING
HIGHtests/integration/defs/test_list_parser.py0apply waives based on the waive state specified by the given waives_file.STRING
HIGH…sts/integration/defs/triton_server/test_list_parser.py0apply waives based on the waive state specified by the given waives_file.STRING
HIGH…s/unittest/_torch/attention/test_attention_no_cache.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGHtests/unittest/_torch/attention/test_attention_mla.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGHtests/unittest/_torch/attention/test_attention.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…est/_torch/attention/sparse/dsa/test_dsa_sparse_mla.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…ch/auto_deploy/custom_ops/attention/torch_attention.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…h/auto_deploy/models/custom/modeling_nemotron_flash.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGHtensorrt_llm/_torch/attention_backend/vanilla.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…ts/unittest/_torch/visual_gen/test_wan_vsa_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…/unittest/_torch/visual_gen/test_wan21_i2v_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…sts/unittest/_torch/visual_gen/test_wan_transformer.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…ts/unittest/_torch/visual_gen/test_trtllm_serve_e2e.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGHtests/unittest/_torch/visual_gen/test_flux_pipeline.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGHtests/unittest/_torch/visual_gen/test_model_loader.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGHtests/integration/defs/conftest.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGHtests/integration/defs/triton_server/conftest.py0return llm_models_root path if it is set in env, assert when it's set but not a valid pathSTRING
HIGH…ts/unittest/_torch/visual_gen/test_wan_vsa_pipeline.py0run full trtllm pipeline including vae decode; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_i2v_pipeline.py0run full trtllm pipeline including vae decode; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0run full trtllm pipeline including vae decode; return (t, h, w, c) float in [0, 1].STRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0run full trtllm pipeline including vae decode; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0run full trtllm pipeline including vae decode; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0run full trtllm pipeline including vae decode; return (t, h, w, c) float in [0, 1].STRING
HIGH…ts/unittest/_torch/visual_gen/test_wan_vsa_pipeline.py0cosine similarity between two tensors (flattened to 1d, cast to float32 on cpu).STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_i2v_pipeline.py0cosine similarity between two tensors (flattened to 1d, cast to float32 on cpu).STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0cosine similarity between two tensors (flattened to 1d, cast to float32 on cpu).STRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0cosine similarity between two tensors (flattened to 1d, cast to float32 on cpu).STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0cosine similarity between two tensors (flattened to 1d, cast to float32 on cpu).STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0cosine similarity between two tensors (flattened to 1d, cast to float32 on cpu).STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_i2v_pipeline.py0load huggingface diffusers pipeline (auto-detects class from model_index.json).STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0load huggingface diffusers pipeline (auto-detects class from model_index.json).STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0load huggingface diffusers pipeline (auto-detects class from model_index.json).STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0load huggingface diffusers pipeline (auto-detects class from model_index.json).STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_i2v_pipeline.py0run hf pipeline with output_type='np'; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0run hf pipeline with output_type='np'; return (t, h, w, c) float in [0, 1].STRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0run hf pipeline with output_type='np'; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0run hf pipeline with output_type='np'; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0run hf pipeline with output_type='np'; return (t, h, w, c) float in [0, 1].STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_i2v_pipeline.py0run trtllm and hf pipelines sequentially, compare decoded video output.STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0run trtllm and hf pipelines sequentially, compare decoded video output.STRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0run trtllm and hf pipelines sequentially, compare decoded video output.STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0run trtllm and hf pipelines sequentially, compare decoded video output.STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0run trtllm and hf pipelines sequentially, compare decoded video output.STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0load trtllm wanpipeline without torch.compile or warmup.STRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0load trtllm wanpipeline without torch.compile or warmup.STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0load trtllm wanpipeline without torch.compile or warmup.STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_t2v_pipeline.py0i2v single prompt returns (b, t, h, w, c) for backward compatibility.STRING
HIGH…/unittest/_torch/visual_gen/test_wan22_i2v_pipeline.py0i2v single prompt returns (b, t, h, w, c) for backward compatibility.STRING
HIGH…/unittest/_torch/visual_gen/test_wan21_t2v_pipeline.py0i2v single prompt returns (b, t, h, w, c) for backward compatibility.STRING
HIGH…ttest/_torch/visual_gen/test_wan22_ti2v_5b_pipeline.py0i2v single prompt returns (b, t, h, w, c) for backward compatibility.STRING
HIGH…s/unittest/_torch/visual_gen/multi_gpu/test_flux_tp.py0clean up tllm_disable_mpi env var after tests complete.STRING
HIGH…ch/visual_gen/multi_gpu/test_ulysses_sage_attention.py0clean up tllm_disable_mpi env var after tests complete.STRING
HIGH…/_torch/visual_gen/multi_gpu/test_ulysses_attention.py0clean up tllm_disable_mpi env var after tests complete.STRING
HIGH…ttest/_torch/visual_gen/multi_gpu/test_flux_ulysses.py0clean up tllm_disable_mpi env var after tests complete.STRING
HIGH…ts/unittest/_torch/visual_gen/multi_gpu/test_wan_tp.py0clean up tllm_disable_mpi env var after tests complete.STRING
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Unused Imports1660 hits · 1446 pts
SeverityFileLineSnippetContext
LOWtests/conftest.py18CODE
LOWtests/conftest.py18CODE
LOWtests/conftest.py18CODE
LOWtests/unittest/conftest.py35CODE
LOW…sts/unittest/_torch/test_custom_config_registration.py20CODE
LOW…test/_torch/custom_ops/test_deepseek_v4_block_table.py7CODE
LOW…est/_torch/custom_ops/test_fused_inv_rope_fp8_quant.py19CODE
LOW…/unittest/_torch/custom_ops/test_deepseek_v4_q_norm.py9CODE
LOW…ittest/_torch/attention/sparse/test_dsa_fp4_indexer.py27CODE
LOW…nittest/_torch/attention/sparse/test_cpp_custom_ops.py27CODE
LOW…orch/attention/sparse/test_cute_dsl_gvr_topk_decode.py21CODE
LOW…st/_torch/attention/sparse/dsa/test_dsa_fp4_indexer.py27CODE
LOW…ion/sparse/deepseek_v4/test_deepseek_v4_fp4_indexer.py25CODE
LOWtests/unittest/_torch/visual_gen/test_cache_dit.py11CODE
LOW…unittest/_torch/visual_gen/test_qwen_image_registry.py26CODE
LOWtests/unittest/_torch/visual_gen/test_tensor_payload.py10CODE
LOW…t/_torch/visual_gen/test_qwen_image_pipeline_config.py12CODE
LOW…ts/unittest/_torch/visual_gen/test_visual_gen_utils.py12CODE
LOWtests/unittest/_torch/models/test_minimax_m3_vl.py16CODE
LOWtests/unittest/_torch/models/test_minimax_m3.py21CODE
LOW…ttest/_torch/modeling/test_multimodal_encoder_graph.py10CODE
LOW…sts/unittest/_torch/modeling/test_gemma4_multimodal.py35CODE
LOW…ttest/_torch/modeling/test_modeling_qwen3_embedding.py24CODE
LOW…/unittest/_torch/modeling/test_modeling_out_of_tree.py83CODE
LOW…parallel/test_fused_dit_gate_resid_norm_shift_scale.py22CODE
LOW…st/_torch/thop/parallel/test_weight_only_quant_gemm.py49CODE
LOW…sts/unittest/_torch/thop/parallel/test_arcquant_fp4.py6CODE
LOW…sts/unittest/_torch/thop/parallel/test_indexer_topk.py46CODE
LOW…est/_torch/thop/parallel/test_weight_only_quant_ops.py24CODE
LOW…thop/parallel_hw_agnostic/test_cuda_tile_custom_ops.py22CODE
LOW…ch/thop/parallel_hw_agnostic/test_logits_bitmask_op.py5CODE
LOW…thop/parallel_hw_agnostic/test_fused_dit_split_norm.py10CODE
LOW…st/_torch/thop/parallel_hw_agnostic/test_custom_ops.py5CODE
LOW…h/thop/parallel_hw_agnostic/test_inplace_slice_copy.py25CODE
LOW…allel_hw_agnostic/test_fused_dit_split_qk_norm_rope.py9CODE
LOWtests/unittest/_torch/thop/serial/test_fused_cat_fp8.py39CODE
LOWtests/unittest/_torch/thop/serial/test_moe_gate.py25CODE
LOW…s/unittest/_torch/executor/test_iter_stats_populate.py39CODE
LOW…/flashinfer/test_trtllm_flashinfer_symbol_collision.py33CODE
LOW…_deploy/unit/singlegpu/models/test_gpt_oss_modeling.py19CODE
LOW…/_torch/modules/fused_ops/test_rmsnorm_residual_add.py34CODE
LOW…/_torch/modules/fused_ops/test_rmsnorm_residual_add.py35CODE
LOW…est/_torch/modules/fused_ops/test_rmsnorm_fp4_quant.py37CODE
LOW…est/_torch/modules/fused_ops/test_rmsnorm_fp4_quant.py38CODE
LOW…orch/modules/fused_ops/test_gelu_tanh_mul_fp4_quant.py30CODE
LOW…orch/modules/fused_ops/test_gelu_tanh_mul_fp4_quant.py31CODE
LOW…t/_torch/modules/mamba/test_ssd_combined_flashinfer.py34CODE
LOW…test/_torch/modules/mamba/test_flashinfer_chunk_gdn.py97CODE
LOW…torch/modules/fused_moe/test_triton_fp8_block_scale.py10CODE
LOW…dules/fused_moe/test_deepgemm_fused_gather_finalize.py30CODE
LOW…dules/fused_moe/test_deepgemm_fused_gather_finalize.py37CODE
LOW…/modules/fused_moe/test_deepgemm_fused_expand_quant.py34CODE
LOW…/modules/fused_moe/test_deepgemm_fused_expand_quant.py41CODE
LOWtests/unittest/api_stability/test_serve_cli.py50CODE
LOWtests/unittest/api_stability/test_serve_api.py62CODE
LOWtests/unittest/api_stability/api_stability_core.py5CODE
LOWtests/unittest/api_stability/api_stability_core.py6CODE
LOWtests/unittest/api_stability/api_stability_core.py8CODE
LOWtests/unittest/api_stability/api_stability_core.py10CODE
LOWtests/unittest/api_stability/api_stability_core.py10CODE
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Deep Nesting1311 hits · 1094 pts
SeverityFileLineSnippetContext
LOWsetup.py23CODE
LOWsetup.py212CODE
LOWtests/unittest/conftest.py340CODE
LOWtests/unittest/gc_utils.py11CODE
LOWtests/unittest/metrics/test_collector.py403CODE
LOWtests/unittest/metrics/test_collector.py414CODE
LOWtests/unittest/_torch/helpers.py183CODE
LOWtests/unittest/_torch/misc/test_autotuner.py718CODE
LOWtests/unittest/_torch/misc/test_share_tensor.py20CODE
LOWtests/unittest/_torch/misc/test_share_tensor.py188CODE
LOWtests/unittest/_torch/attention/backend_case.py860CODE
LOWtests/unittest/_torch/attention/test_attention_mla.py590CODE
LOW…ts/unittest/_torch/attention/test_attention_op_sync.py105CODE
LOW…ts/unittest/_torch/attention/test_attention_op_sync.py161CODE
LOW…ts/unittest/_torch/attention/test_attention_op_sync.py321CODE
LOW…s/unittest/_torch/attention/test_attention_backends.py124CODE
LOW…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py555CODE
LOW…attention/sparse/test_cute_dsl_fp4_paged_mqa_logits.py733CODE
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py828CODE
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1040CODE
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1154CODE
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1660CODE
LOW…attention/sparse/test_cute_dsl_fp8_paged_mqa_logits.py578CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2178CODE
LOW…est/_torch/attention/sparse/dsa/test_dsa_sparse_mla.py176CODE
LOW…est/_torch/attention/sparse/dsa/test_dsa_sparse_mla.py530CODE
LOW…test/_torch/attention/sparse/rocketkv/test_rocketkv.py407CODE
LOW…n/sparse/deepseek_v4/test_deepseek_v4_cache_manager.py1318CODE
LOW…n/sparse/deepseek_v4/test_deepseek_v4_cache_manager.py1383CODE
LOW…n/sparse/deepseek_v4/test_deepseek_v4_cache_manager.py1592CODE
LOW…tion/sparse/deepseek_v4/test_deepseek_v4_sparse_mla.py324CODE
LOW…tion/sparse/deepseek_v4/test_deepseek_v4_sparse_mla.py452CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py1591CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2168CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2293CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2366CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2411CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2491CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2564CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py2660CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py250CODE
LOW…attention/sparse/deepseek_v4/test_compressor_kernel.py461CODE
LOW…attention/sparse/deepseek_v4/test_compressor_kernel.py1127CODE
LOW…attention/sparse/deepseek_v4/test_compressor_kernel.py1421CODE
LOW…arse/deepseek_v4/test_deepseek_v4_indices_transform.py172CODE
LOW…unittest/_torch/attention/sparse/kernel/test_triton.py72CODE
LOW…unittest/_torch/attention/sparse/kernel/test_triton.py168CODE
LOWtests/unittest/_torch/visual_gen/test_flux_pipeline.py230CODE
LOWtests/unittest/_torch/visual_gen/test_flux_pipeline.py271CODE
LOW…sts/unittest/_torch/visual_gen/test_wan_transformer.py189CODE
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py154CODE
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py395CODE
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py474CODE
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py711CODE
LOWtests/unittest/_torch/visual_gen/test_ltx2_pipeline.py204CODE
LOW…ts/unittest/_torch/visual_gen/test_ltx2_transformer.py63CODE
LOW…ts/unittest/_torch/visual_gen/test_ltx2_transformer.py88CODE
LOW…unittest/_torch/visual_gen/test_cosmos3_transformer.py137CODE
LOWtests/unittest/_torch/visual_gen/test_wan_vae.py74CODE
LOW…ttest/_torch/visual_gen/test_attention_cute_dsl_vsa.py248CODE
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Excessive Try-Catch Wrapping980 hits · 1082 pts
SeverityFileLineSnippetContext
LOWsetup.py192 except Exception as e:CODE
LOWsetup.py295 except Exception as e:CODE
LOWtests/unittest/conftest.py447 except Exception:CODE
LOWtests/unittest/conftest.py498 except Exception:CODE
MEDIUMtests/unittest/conftest.py133def pytest_pyfunc_call(pyfuncitem) -> Any:CODE
LOWtests/unittest/test_pip_install.py126 except Exception as e:CODE
LOWtests/unittest/metrics/test_collector.py37 except Exception:CODE
LOWtests/unittest/_torch/misc/test_share_tensor.py35 except Exception as e:CODE
LOWtests/unittest/_torch/misc/test_share_tensor.py204 except Exception as e:CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py69 except Exception:CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2593 except Exception as e:CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2645 except Exception as e:CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2754 except Exception as e:CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2862 except Exception as e:CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2914 except Exception as e:CODE
MEDIUM…attention/sparse/deepseek_v4/test_compressor_module.py844def __del__(self):CODE
LOW…attention/sparse/deepseek_v4/test_compressor_module.py847 except Exception:CODE
LOW…attention/sparse/deepseek_v4/test_compressor_kernel.py1769except Exception:CODE
LOW…ts/unittest/_torch/visual_gen/test_trtllm_serve_e2e.py166 except Exception as err:CODE
LOWtests/unittest/_torch/visual_gen/test_flux_pipeline.py1018 except Exception as e:CODE
LOWtests/unittest/_torch/visual_gen/test_flux_pipeline.py1199 except Exception as e:CODE
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py770 except Exception as e:CODE
LOWtests/unittest/_torch/visual_gen/test_attention_perf.py604 except Exception as e:CODE
LOW…ts/unittest/_torch/visual_gen/test_ltx2_transformer.py112 except Exception:CODE
LOW…t/_torch/visual_gen/multi_gpu/test_attn2d_attention.py157 except Exception as e:CODE
MEDIUM…t/_torch/visual_gen/multi_gpu/test_attn2d_attention.py153def _distributed_worker(rank, world_size, backend, test_fn, port):CODE
LOW…/_torch/visual_gen/multi_gpu/test_wan_async_ulysses.py88 except Exception as e:CODE
MEDIUM…/_torch/visual_gen/multi_gpu/test_wan_async_ulysses.py84def _distributed_worker(rank, world_size, backend, test_fn, port, fn_args):CODE
LOW…ttest/_torch/visual_gen/multi_gpu/test_parallel_vae.py70 except Exception as e:CODE
MEDIUM…ttest/_torch/visual_gen/multi_gpu/test_parallel_vae.py66def _distributed_worker(rank, world_size, test_fn, port):CODE
LOW…isual_gen/multi_gpu/test_flux2_transformer_parallel.py96 except Exception as e:CODE
MEDIUM…isual_gen/multi_gpu/test_flux2_transformer_parallel.py92def _distributed_worker(rank, world_size, backend, test_fn, port, kwargs):CODE
LOW…torch/visual_gen/multi_gpu/test_parallel_group_norm.py62 except Exception as e:CODE
MEDIUM…torch/visual_gen/multi_gpu/test_parallel_group_norm.py58def _distributed_worker(rank, world_size, test_fn, port):CODE
LOW…ttest/_torch/visual_gen/multi_gpu/test_ltx2_ulysses.py79 except Exception as e:CODE
MEDIUM…ttest/_torch/visual_gen/multi_gpu/test_ltx2_ulysses.py75def _distributed_worker(rank, world_size, backend, test_fn, port, fn_args):CODE
LOW…st/_torch/visual_gen/multi_gpu/test_wan_vsa_ulysses.py92 except Exception as e:CODE
MEDIUM…st/_torch/visual_gen/multi_gpu/test_wan_vsa_ulysses.py88def _distributed_worker(rank, world_size, backend, test_fn, port, kwargs):CODE
MEDIUM…est/_torch/visual_gen/multi_gpu/test_ring_attention.py140def _distributed_worker(rank, world_size, backend, test_fn, port):CODE
LOW…est/_torch/visual_gen/multi_gpu/test_ring_attention.py144 except Exception as e:CODE
LOW…s/unittest/_torch/visual_gen/multi_gpu/test_flux_tp.py99 except Exception as e:CODE
LOW…test/_torch/visual_gen/multi_gpu/test_parallel_conv.py73 except Exception as e:CODE
MEDIUM…test/_torch/visual_gen/multi_gpu/test_parallel_conv.py69def _distributed_worker(rank, world_size, test_fn, port):CODE
LOW…ch/visual_gen/multi_gpu/test_ulysses_sage_attention.py98 except Exception as e:CODE
LOW…/visual_gen/multi_gpu/test_wan_transformer_parallel.py102 except Exception as e:CODE
MEDIUM…/visual_gen/multi_gpu/test_wan_transformer_parallel.py98def _distributed_worker(rank, world_size, backend, test_fn, port, kwargs):CODE
LOW…/_torch/visual_gen/multi_gpu/test_ulysses_attention.py77 except Exception as e:CODE
LOW…ual_gen/multi_gpu/test_cosmos3_transformer_parallel.py179 except Exception as e:CODE
MEDIUM…ual_gen/multi_gpu/test_cosmos3_transformer_parallel.py161def cleanup_distributed():CODE
LOW…/_torch/visual_gen/multi_gpu/test_ltx2_parallel_vae.py69 except Exception as e:CODE
MEDIUM…/_torch/visual_gen/multi_gpu/test_ltx2_parallel_vae.py65def _distributed_worker(rank, world_size, test_fn, port):CODE
MEDIUM…ttest/_torch/visual_gen/multi_gpu/test_tp_attention.py88def _distributed_worker(rank, world_size, test_fn, port, *args):CODE
LOW…ttest/_torch/visual_gen/multi_gpu/test_tp_attention.py92 except Exception as e:CODE
LOW…_torch/visual_gen/multi_gpu/test_parallel_attention.py68 except Exception as e:CODE
MEDIUM…_torch/visual_gen/multi_gpu/test_parallel_attention.py64def _distributed_worker(rank, world_size, test_fn, port):CODE
LOW…ttest/_torch/visual_gen/multi_gpu/test_flux_ulysses.py82 except Exception as e:CODE
LOW…ts/unittest/_torch/visual_gen/multi_gpu/test_wan_tp.py105 except Exception as e:CODE
LOW…rch/visual_gen/multi_gpu/test_wan_pipeline_parallel.py148 except Exception as e:CODE
MEDIUM…rch/visual_gen/multi_gpu/test_wan_pipeline_parallel.py144def _distributed_worker(rank, world_size, backend, test_fn, port, kwargs):CODE
LOW…_torch/visual_gen/multi_gpu/test_ltx2_async_ulysses.py90 except Exception as e:CODE
920 more matches not shown…
Self-Referential Comments278 hits · 836 pts
SeverityFileLineSnippetContext
MEDIUMtests/unittest/_torch/test_connector.py186 # Create a mock request in generation state with draft tokensCOMMENT
MEDIUMtests/unittest/_torch/misc/test_share_tensor.py194 # Create a new tensor each timeCOMMENT
MEDIUM…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py212 # Create a mock instance with a simple forward methodCOMMENT
MEDIUM…attention/sparse/deepseek_v4/test_compressor_module.py797 # Create the CompressorCOMMENT
MEDIUMtests/unittest/_torch/distributed/test_cp_broadcast.py139 # Create a large list to test chunking behaviorCOMMENT
MEDIUM…ttest/_torch/visual_gen/test_trtllm_serve_endpoints.py820 # Create a dummy reference image fileCOMMENT
MEDIUM…s/unittest/_torch/modeling/test_modeling_multimodal.py842 # Create a dummy torch module if skipping HF inference.COMMENT
MEDIUMtests/unittest/_torch/multi_gpu/test_mnnvl_allreduce.py377 # Create a single AllReduce instance to be reused for all sequence lengthsCOMMENT
MEDIUMtests/unittest/_torch/sampler/test_beam_search_util.py33# Define a dummy model to create deterministic outputs for the testCOMMENT
MEDIUM…test/_torch/thop/parallel/test_fp8_block_scale_gemm.py486 # Create a copy of the current environmentCOMMENT
MEDIUMtests/unittest/_torch/thop/serial/test_moe_alltoall.py67 # Create a random input tensorCOMMENT
MEDIUMtests/unittest/_torch/executor/test_py_executor.py125 # Create a mock requestCOMMENT
MEDIUM…/unittest/_torch/executor/test_pytorch_model_engine.py657 # Create a dedicated execution streamCOMMENT
MEDIUMtests/unittest/_torch/executor/test_resource_manager.py259 # Create the PeftCacheConfig with parameter names that match the expected APICOMMENT
MEDIUMtests/unittest/_torch/executor/test_resource_manager.py713 # Create a real KVCacheManager, it will run calculate_max_num_blocks_for_vswa in __init__COMMENT
MEDIUMtests/unittest/_torch/executor/test_resource_manager.py868 # Create a dedicated execution streamCOMMENT
MEDIUM…nittest/_torch/executor/test_executor_request_queue.py286 # Create a mock request without sampling_config to avoid beam validationCOMMENT
MEDIUMtests/unittest/_torch/speculative/test_eagle3.py166 # Create a mock KV cache managerCOMMENT
MEDIUMtests/unittest/_torch/speculative/test_eagle3.py327 # Create the LLM instanceCOMMENT
MEDIUMtests/unittest/_torch/speculative/test_eagle3.py873 # Create the LLM instanceCOMMENT
MEDIUMtests/unittest/_torch/speculative/test_eagle3.py927 # Create the LLM instanceCOMMENT
MEDIUMtests/unittest/_torch/speculative/test_eagle3.py1053 # Create the LLM instanceCOMMENT
MEDIUMtests/unittest/_torch/speculative/test_eagle3.py1113 # Create the LLM instanceCOMMENT
MEDIUM…s/unittest/_torch/speculative/hw_agnostic/test_pard.py65 # Create the LLM instanceCOMMENT
MEDIUM…ch/speculative/hw_agnostic/test_dynamic_spec_decode.py38 # Create a Mock object with the mock function as side_effectCOMMENT
MEDIUM…culative/hw_agnostic/test_draft_token_tree_sampling.py60 # Create the chain drafterCOMMENT
MEDIUMtests/unittest/_torch/modules/test_awq_quantization.py30 # Create a Linear module with NVFP4 quantization using actual initializationCOMMENT
MEDIUMtests/unittest/_torch/modules/test_moe_load_balancer.py342 # Create a real MoeLoadBalancerCOMMENT
MEDIUMtests/unittest/_torch/modules/test_moe_load_balancer.py406 # Create a real MoeLoadBalancerCOMMENT
MEDIUMtests/unittest/_torch/modules/test_fused_moe.py2963# Create a mock module with required attributes for NVFP4CutlassFusedMoEMethod.get_weights_shapes test.COMMENT
MEDIUMtests/unittest/_torch/modules/moe/test_moe_backend.py732# This file provides a UNIFIED TEST FRAMEWORK for testing all MoE backendCOMMENT
MEDIUMtests/unittest/_torch/modules/moe/quantize_utils.py1319 # Initialize base class with use_cute_dsl_blockscaling_mm=FalseCOMMENT
MEDIUMtests/unittest/api_stability/api_stability_core.py261 # Create a MethodSnapshot for Pydantic model's __init__,COMMENT
MEDIUMtests/unittest/others/test_time_breakdown.py341 # Create a temporary JSON file for testingCOMMENT
MEDIUMtests/unittest/others/test_time_breakdown.py368 # Create a temporary fileCOMMENT
MEDIUMtests/unittest/others/test_time_breakdown.py566 # Create the diagramCOMMENT
MEDIUMtests/unittest/others/test_time_breakdown.py625 # Create the diagramCOMMENT
MEDIUMtests/unittest/others/test_leak.py62 # Create a TRT builder to warm up the memory, and avoid the noise of leak detection.COMMENT
MEDIUMtests/unittest/disaggregated/test_remoteDictionary.py59 # Create a clean etcd client for test setup/teardownCOMMENT
MEDIUMtests/unittest/disaggregated/test_remoteDictionary.py62 # Create the dictionary under testCOMMENT
MEDIUMtests/unittest/llmapi/test_llm_encode.py213 # Create a batch that exceeds max_batch_sizeCOMMENT
MEDIUMtests/unittest/llmapi/test_grpc.py949 # Create a synthetic RGBA image to test RGB conversionCOMMENT
MEDIUMtests/unittest/llmapi/test_llm_kv_cache_events.py224 # Create a mock mm_key with new format (hash, offset, uuid)COMMENT
MEDIUMtests/unittest/llmapi/test_llm_kv_cache_events.py313 # Create a different imageCOMMENT
MEDIUM…nittest/llmapi/apps/test_harmony_channel_validation.py309 # Create a proper output mockCOMMENT
MEDIUM…_deploy/multigpu/custom_ops/test_ad_dist_strategies.py331 # Create a simple MLP modelCOMMENT
MEDIUM…y/multigpu/transformations/library/test_ep_sharding.py208 # Create a simple graph with torch_moe node using stacked tensor formatCOMMENT
MEDIUM…egpu/transformations/library/test_attention_matcher.py137 # Define the scaling approach based on use_division flagCOMMENT
MEDIUM…egpu/transformations/library/test_attention_matcher.py972 # Create a llama-3.1 style causal maskCOMMENT
MEDIUM…egpu/transformations/library/test_attention_matcher.py1063 # Create a deterministic pseudo-random attention maskCOMMENT
MEDIUM…y/singlegpu/transformations/library/test_moe_fusion.py793 # Create a module with the FP8 MoE opCOMMENT
MEDIUM…y/singlegpu/transformations/library/test_moe_fusion.py1124 # Create a module with the NVFP4 MoE opCOMMENT
MEDIUM…pu/transformations/library/test_rope_transformation.py63 # Create a complex tensor from magnitude=1 and the computed angles.COMMENT
MEDIUM…u/transformations/library/test_redundant_transposes.py245 # Create a check function for this specific modelCOMMENT
MEDIUM…loy/singlegpu/transformations/library/test_kv_cache.py547 # Create a mock moduleCOMMENT
MEDIUM…loy/singlegpu/transformations/library/test_kv_cache.py550 # Create the transform with a proper configCOMMENT
MEDIUM…loy/singlegpu/transformations/library/test_kv_cache.py586 # Create the transform with a proper configCOMMENT
MEDIUM…loy/singlegpu/transformations/library/test_kv_cache.py589 # Create a mock moduleCOMMENT
MEDIUM…loy/singlegpu/transformations/library/test_kv_cache.py260 # Create the model with embedding layer and SDPA, wrap it in a fake factoryCOMMENT
MEDIUM…loy/singlegpu/transformations/library/test_kv_cache.py629 # Create the transform with a proper configCOMMENT
218 more matches not shown…
Structural Annotation Overuse446 hits · 800 pts
SeverityFileLineSnippetContext
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1460 # Step 2: Run TRT-LLM forward to populate actual KV cacheCOMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1590 # Step 1: Call indexer to get topk indices (indexer internally uses its compressor)COMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1603 # Step 2: Call MLA's compressor to compress KV cacheCOMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1614 # Step 3: Process context requestsCOMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1632 # Step 4: Process generation requestsCOMMENT
LOWtests/unittest/_torch/thop/parallel/test_fp4_linear.py544 # Step 3: For each backend, capture and immediately test all tacticsCOMMENT
LOWtests/unittest/_torch/thop/parallel/test_fp4_linear.py600 # Step 4: Test cuda_core if it's available (single tactic, no capture needed)COMMENT
LOW…/unittest/_torch/thop/serial/test_nvfp4_marlin_gemm.py103 # Step 1: Repack weights to Marlin tiled formatCOMMENT
LOW…/unittest/_torch/thop/serial/test_nvfp4_marlin_gemm.py115 # Step 2: Process weight scales for Marlin kernelCOMMENT
LOW…/unittest/_torch/thop/serial/test_nvfp4_marlin_gemm.py124 # Step 3: Process global scale (includes exponent bias correction)COMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py464 # Step 3: first 2 complete, now context 2,3 get scheduledCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py540 # Step 1: slot 0 — req0, req1 scheduledCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py545 # Step 2: slot 1 — req0/req1 still inflight, req2/req3 scheduledCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py550 # Step 3: slot 0 freed (inflight = slot1 only) — req0/req1 scheduled againCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py436 # Step 1: 4 context requests, only 2 fitCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py449 # Step 2: first 2 become generation, remaining 2 still contextCOMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2801 # Step 1: Apply pre_quant_scale (AWQ smoothing) if presentCOMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2805 # Step 2: Quantize activation to FP8 and dequantize back (Q/DQ simulation)COMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2813 # Step 3: Dequantize weightCOMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2820 # Step 4: Compute matmul and scale outputCOMMENT
LOWtests/unittest/disaggregated/test_router.py265 # Step 3: s2 uniquely least (10 < 100 < 500)COMMENT
LOWtests/unittest/disaggregated/test_router.py269 # Step 4: s0 uniquely least (100 < 410 < 500)COMMENT
LOWtests/unittest/disaggregated/test_router.py273 # Step 5: s2 uniquely least (410 < 500 < 2100)COMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py949 # Step 1: Context side calls prepare_context_requests, no kvcache request is sent, thus no requestCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py963 # Step 2: Generation side submits receive requestsCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py993 # Step 1: Generation side submits receive requests, now context side doesn't know the requestsCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py1008 # Step 2: Context side calls prepare_context_requests, now context side knows the requestsCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py1018 # Step 3: Context side sends the dataCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py75 # Step 1: Load real model, capture report_usage kwargsCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py96 # Step 2: Call _background_reporter with real args, capture payloadCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py119 # Step 3: Spot-check against ground truthCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py133 # Step 4: String length checks (ShortString<=128, LongString<=256)COMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py158 # Step 5: Integer range checks (0 <= x <= 4294967295)COMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py174 # Step 6: featuresJson checkCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py187 # Step 7: Full jsonschema validationCOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py53 # Step 1: Retrieve KV cacheCOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py56 # Step 2: Dequantize KV cacheCOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py59 # Step 3: Apply RoPECOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py60 # Step 4: Compute attentionCOMMENT
LOW…o_deploy/singlegpu/custom_ops/rope/test_triton_rope.py137 # Step 1: Index cos/sin with position_idsCOMMENT
LOW…o_deploy/singlegpu/custom_ops/rope/test_triton_rope.py141 # Step 2: Apply PyTorch rope with qk interleavingCOMMENT
LOW…stom_ops/moe/test_trtllm_quant_mxfp4_trtllm_gen_moe.py278 # Step 1: deinterleave gate/up halves so dst gets [up | gate] in the row dim.COMMENT
LOW…inglegpu/transformations/library/test_bmm_moe_hooks.py241 # Step 1: Split gate_up into w1 and w3COMMENT
LOW…inglegpu/transformations/library/test_bmm_moe_hooks.py251 # Step 2: Split down into w2COMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py113 # Step 1: Decompose — rmsnorm should be expanded into primitivesCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py117 # Step 2: Discover fusible subgraphsCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py125 # Step 3: Generate kernelCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py293 # Step 1: Decompose — rmsnorm decomposes into primitivesCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py297 # Step 2: Discover fusible subgraphsCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py314 # Step 3: Generate Triton kernel from the novel subgraphCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py408 # Step 1: FX → MLIRCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py412 # Step 2: DecomposeCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py416 # Step 3: DiscoverCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py421 # Step 4: Generate kernel + replaceCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py426 # Step 5: MLIR → FXCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py430 # Step 6: Run the new graph and verify correctnessCOMMENT
LOWtests/integration/defs/common.py984 # Step 1: Get base model outputs (no LoRA) as the ground truth.COMMENT
LOWtests/integration/defs/common.py1017 # Step 2: Run with LoRA adapters and compare against base outputs.COMMENT
LOW…egration/defs/disaggregated/test_disaggregated_etcd.py321 # Step 1: Start etcd serverCOMMENT
LOW…egration/defs/disaggregated/test_disaggregated_etcd.py326 # Step 2: Clean etcd dataCOMMENT
386 more matches not shown…
Verbosity Indicators316 hits · 574 pts
SeverityFileLineSnippetContext
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1460 # Step 2: Run TRT-LLM forward to populate actual KV cacheCOMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1590 # Step 1: Call indexer to get topk indices (indexer internally uses its compressor)COMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1603 # Step 2: Call MLA's compressor to compress KV cacheCOMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1614 # Step 3: Process context requestsCOMMENT
LOW…est/_torch/attention/sparse/test_sparse_mla_forward.py1632 # Step 4: Process generation requestsCOMMENT
LOWtests/unittest/_torch/thop/parallel/test_fp4_linear.py544 # Step 3: For each backend, capture and immediately test all tacticsCOMMENT
LOWtests/unittest/_torch/thop/parallel/test_fp4_linear.py600 # Step 4: Test cuda_core if it's available (single tactic, no capture needed)COMMENT
LOW…/unittest/_torch/thop/serial/test_nvfp4_marlin_gemm.py103 # Step 1: Repack weights to Marlin tiled formatCOMMENT
LOW…/unittest/_torch/thop/serial/test_nvfp4_marlin_gemm.py115 # Step 2: Process weight scales for Marlin kernelCOMMENT
LOW…/unittest/_torch/thop/serial/test_nvfp4_marlin_gemm.py124 # Step 3: Process global scale (includes exponent bias correction)COMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py464 # Step 3: first 2 complete, now context 2,3 get scheduledCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py540 # Step 1: slot 0 — req0, req1 scheduledCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py545 # Step 2: slot 1 — req0/req1 still inflight, req2/req3 scheduledCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py550 # Step 3: slot 0 freed (inflight = slot1 only) — req0/req1 scheduled againCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py436 # Step 1: 4 context requests, only 2 fitCOMMENT
LOWtests/unittest/_torch/executor/test_py_scheduler.py449 # Step 2: first 2 become generation, remaining 2 still contextCOMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2801 # Step 1: Apply pre_quant_scale (AWQ smoothing) if presentCOMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2805 # Step 2: Quantize activation to FP8 and dequantize back (Q/DQ simulation)COMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2813 # Step 3: Dequantize weightCOMMENT
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2820 # Step 4: Compute matmul and scale outputCOMMENT
LOWtests/unittest/disaggregated/test_router.py265 # Step 3: s2 uniquely least (10 < 100 < 500)COMMENT
LOWtests/unittest/disaggregated/test_router.py269 # Step 4: s0 uniquely least (100 < 410 < 500)COMMENT
LOWtests/unittest/disaggregated/test_router.py273 # Step 5: s2 uniquely least (410 < 500 < 2100)COMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py949 # Step 1: Context side calls prepare_context_requests, no kvcache request is sent, thus no requestCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py963 # Step 2: Generation side submits receive requestsCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py993 # Step 1: Generation side submits receive requests, now context side doesn't know the requestsCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py1008 # Step 2: Context side calls prepare_context_requests, now context side knows the requestsCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py1018 # Step 3: Context side sends the dataCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py75 # Step 1: Load real model, capture report_usage kwargsCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py96 # Step 2: Call _background_reporter with real args, capture payloadCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py119 # Step 3: Spot-check against ground truthCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py133 # Step 4: String length checks (ShortString<=128, LongString<=256)COMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py158 # Step 5: Integer range checks (0 <= x <= 4294967295)COMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py174 # Step 6: featuresJson checkCOMMENT
LOWtests/unittest/llmapi/test_llm_telemetry_payload.py187 # Step 7: Full jsonschema validationCOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py53 # Step 1: Retrieve KV cacheCOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py56 # Step 2: Dequantize KV cacheCOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py59 # Step 3: Apply RoPECOMMENT
LOW…u/custom_ops/attention/test_flashinfer_attention_op.py60 # Step 4: Compute attentionCOMMENT
LOW…o_deploy/singlegpu/custom_ops/rope/test_triton_rope.py137 # Step 1: Index cos/sin with position_idsCOMMENT
LOW…o_deploy/singlegpu/custom_ops/rope/test_triton_rope.py141 # Step 2: Apply PyTorch rope with qk interleavingCOMMENT
LOW…stom_ops/moe/test_trtllm_quant_mxfp4_trtllm_gen_moe.py278 # Step 1: deinterleave gate/up halves so dst gets [up | gate] in the row dim.COMMENT
LOW…inglegpu/transformations/library/test_bmm_moe_hooks.py241 # Step 1: Split gate_up into w1 and w3COMMENT
LOW…inglegpu/transformations/library/test_bmm_moe_hooks.py251 # Step 2: Split down into w2COMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py113 # Step 1: Decompose — rmsnorm should be expanded into primitivesCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py117 # Step 2: Discover fusible subgraphsCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py125 # Step 3: Generate kernelCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py293 # Step 1: Decompose — rmsnorm decomposes into primitivesCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py297 # Step 2: Discover fusible subgraphsCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py314 # Step 3: Generate Triton kernel from the novel subgraphCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py408 # Step 1: FX → MLIRCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py412 # Step 2: DecomposeCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py416 # Step 3: DiscoverCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py421 # Step 4: Generate kernel + replaceCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py426 # Step 5: MLIR → FXCOMMENT
LOW…o_deploy/singlegpu/mlir/test_elementwise_fusion_e2e.py430 # Step 6: Run the new graph and verify correctnessCOMMENT
LOWtests/integration/defs/common.py984 # Step 1: Get base model outputs (no LoRA) as the ground truth.COMMENT
LOWtests/integration/defs/common.py1017 # Step 2: Run with LoRA adapters and compare against base outputs.COMMENT
LOW…egration/defs/disaggregated/test_disaggregated_etcd.py321 # Step 1: Start etcd serverCOMMENT
LOW…egration/defs/disaggregated/test_disaggregated_etcd.py326 # Step 2: Clean etcd dataCOMMENT
256 more matches not shown…
Hallucination Indicators42 hits · 560 pts
SeverityFileLineSnippetContext
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1184 mla_layer.mqa.indexer.wq_b.weight.normal_(mean=0.0,CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1186 mla_layer.mqa.indexer.wk.weight.normal_(mean=0.0,CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1188 mla_layer.mqa.indexer.weights_proj.weight.normal_(CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1198 mla_layer.mqa.indexer.wq_b.weight.normal_(mean=0.0,CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1200 mla_layer.mqa.indexer.weights_proj.weight.normal_(CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1205 mla_layer.mqa.indexer.compressor.wkv_gate.weight.normal_(CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1207 mla_layer.mqa.indexer.compressor.ape.normal_(CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1210 mla_layer.mqa.indexer.compressor.norm.weight.fill_(1.0)CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1214 mla_layer.mqa.compressor.wkv_gate.weight.normal_(CODE
CRITICAL…est/_torch/attention/sparse/test_sparse_mla_forward.py1219 mla_layer.mqa.compressor.norm.weight.fill_(1.0)CODE
CRITICAL…test/_torch/attention/sparse/dsa/test_short_seq_mha.py302 mla.mqa.indexer.wq_b.weight.normal_(mean=0.0, std=NN_INIT_STD)CODE
CRITICAL…test/_torch/attention/sparse/dsa/test_short_seq_mha.py303 mla.mqa.indexer.wk.weight.normal_(mean=0.0, std=NN_INIT_STD)CODE
CRITICAL…test/_torch/attention/sparse/dsa/test_short_seq_mha.py304 mla.mqa.indexer.weights_proj.weight.normal_(mean=0.0, std=NN_INIT_STD)CODE
CRITICAL…attention/sparse/deepseek_v4/test_compressor_module.py1518 comp.compressor.norm.weight.data.copy_(ref.norm.weight.data)CODE
CRITICALtests/unittest/_torch/models/test_minimax_m3_vl.py549 pe = model.vision_model.embeddings.patch_embedding.weight.detach()CODE
CRITICALtests/unittest/_torch/modeling/test_modeling_gemma4.py1037 layer.self_attn.k_norm.weight.data.normal_(0, 0.5)CODE
CRITICAL…u/custom_ops/mamba/test_torch_causal_conv_cached_op.py108 tensorrt_llm._torch.auto_deploy.custom_ops.mamba.torch_backend_causal_conv._torch_causal_conv1d_decode( # type:CODE
CRITICAL…u/custom_ops/mamba/test_torch_causal_conv_cached_op.py179 tensorrt_llm._torch.auto_deploy.custom_ops.mamba.torch_backend_causal_conv._torch_causal_conv1d_prefill( # CODE
CRITICAL…nglegpu/custom_ops/mamba/test_torch_mamba_cached_op.py119 tensorrt_llm._torch.auto_deploy.custom_ops.mamba.torch_backend_mamba._torch_cached_ssm_decode( # type: ignore CODE
CRITICAL…nglegpu/custom_ops/mamba/test_torch_mamba_cached_op.py199 y_i, s_i = tensorrt_llm._torch.auto_deploy.custom_ops.mamba.torch_mamba._torch_ssm_prefill( # type: ignore # nCODE
CRITICAL…pu/custom_ops/mamba/test_cuda_causal_conv_cached_op.py184 tensorrt_llm._torch.auto_deploy.custom_ops.mamba.torch_backend_causal_conv._torch_causal_conv1d_prefill( # CODE
CRITICAL…pu/transformations/library/test_shared_kv_attention.py339 shared_op_name = torch.ops.auto_deploy.flashinfer_attention_mha_with_cache.default.name()CODE
CRITICAL…o_deploy/singlegpu/models/test_hunyuan_moe_modeling.py467 custom_moe.gate.wg.weight.data.copy_(hf_moe.gate_wg.weight.data)CODE
CRITICAL…o_deploy/singlegpu/models/test_hunyuan_moe_modeling.py486 custom_model.model.embed_tokens.weight.data.copy_(hf_model.model.embed_tokens.weight.data)CODE
CRITICAL…o_deploy/singlegpu/models/test_hunyuan_moe_modeling.py487 custom_model.model.norm.weight.data.copy_(hf_model.model.norm.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1469 ad_mlp.gate_proj.linear.weight.data.copy_(ref_mlp.gate_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1470 ad_mlp.up_proj.linear.weight.data.copy_(ref_mlp.up_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1471 ad_mlp.down_proj.linear.weight.data.copy_(ref_mlp.down_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1476 ad_attn.q_proj.linear.weight.data.copy_(ref_attn.q_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1477 ad_attn.k_proj.linear.weight.data.copy_(ref_attn.k_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1478 ad_attn.v_proj.linear.weight.data.copy_(ref_attn.v_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_gemma4_modeling.py1479 ad_attn.o_proj.linear.weight.data.copy_(ref_attn.o_proj.weight.data)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_llama4_modeling.py476 hf_layer.feed_forward.experts.gate_up_proj.data.normal_(mean=0.0, std=std)CODE
CRITICAL…t/auto_deploy/singlegpu/models/test_llama4_modeling.py477 hf_layer.feed_forward.experts.down_proj.data.normal_(mean=0.0, std=std)CODE
CRITICAL…/auto_deploy/singlegpu/models/test_gemma3n_modeling.py375 model.lm_head.weight.data_ptr() == model.model.language_model.embed_tokens.weight.data_ptr()CODE
CRITICAL…deploy/singlegpu/models/test_hunyuan_dense_modeling.py211 custom_model.model.embed_tokens.weight.data.copy_(hf_model.model.embed_tokens.weight.data)CODE
CRITICAL…deploy/singlegpu/models/test_hunyuan_dense_modeling.py212 custom_model.model.norm.weight.data.copy_(hf_model.model.norm.weight.data)CODE
CRITICAL…crobenchmarks/attention_perf/attention_perf_harness.py672 mla.mqa.indexer.wq_b.weight.normal_(mean=0.0, std=std)CODE
CRITICAL…crobenchmarks/attention_perf/attention_perf_harness.py673 mla.mqa.indexer.wk.weight.normal_(mean=0.0, std=std)CODE
CRITICAL…crobenchmarks/attention_perf/attention_perf_harness.py674 mla.mqa.indexer.weights_proj.weight.normal_(mean=0.0, std=std)CODE
CRITICALtensorrt_llm/_torch/modules/fla/utils.py260 return triton.runtime.driver.active.utils.get_device_properties(CODE
CRITICALtensorrt_llm/_torch/modules/fla/utils.py313 triton.runtime.driver.active.utils.get_device_properties(i)CODE
Docstring Block Structure109 hits · 545 pts
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HIGHtests/unittest/tools/test_prepare_dataset.py52 Build the base command for running prepare_dataset.py. Args: output_path: Path to the outpSTRING
HIGHtests/unittest/tools/test_prepare_dataset.py112 Execute prepare_dataset.py with specified parameters and capture output. Args: llmSTRING
HIGH…/unittest/auto_deploy/_utils_test/_model_test_utils.py616 Get the small model configuration for a given HuggingFace model hub ID. Args: model_hub_id: The HugginSTRING
HIGH…/integration/defs/stress_test/disagg_cancel/harness.py99Parse and validate a marathon YAML in one call. Callers that construct ``StressConfig`` directly via ``STRING
HIGH…/integration/defs/stress_test/disagg_cancel/harness.py426Map a YAML target string to a tracked worker. Args: target: One of ``gen_worker_random``, ``ctx_worker_randSTRING
HIGHtests/integration/defs/utils/timeout_manager.py71 Context manager for timing an operation and updating remaining timeout. Args: phase_name: STRING
HIGHtests/integration/defs/utils/timeout_manager.py100 Execute an operation with timeout tracking. Args: operation: The operation to execute. STRING
HIGHtests/integration/defs/utils/timeout_manager.py122 Call a function with timeout tracking. Args: func: The function to call. *argsSTRING
HIGH…pts/cute_dsl_kernels/run_dense_bf16_gemm_persistent.py101Runs and benchmarks the persistent dense BF16/FP16 GEMM/BMM. This function prepares input tensors, launches the kerSTRING
HIGH…e_dsl_kernels/run_dense_blockscaled_gemm_persistent.py94Runs and benchmarks the persistent batched dense block-scaled GEMM. This function prepares input tensors, launches STRING
HIGH…e_dsl_kernels/run_dense_blockscaled_gemm_act_fusion.py153Runs and benchmarks the persistent batched dense block-scaled GEMM with activation fusion. This function prepares iSTRING
HIGHtensorrt_llm/lora_manager.py70Extract and organize NeMo LoRA weights by layer and direction. Args: lora_weights: Dictionary mapping weighSTRING
HIGHtensorrt_llm/lora_manager.py116Iterate over HuggingFace LoRA weights and call iterator function for each weight. Args: iter_fn: Function tSTRING
HIGHtensorrt_llm/lora_manager.py323Find .nemo files from a single path (file or directory). This function is cached per individual path to maximize caSTRING
HIGHtensorrt_llm/lora_manager.py358Find all .nemo files from a list of directories or file paths. This function is optimized for repeated calls at genSTRING
HIGHtensorrt_llm/lora_manager.py523Unpack model config and weights from a NeMo .nemo archive file. Args: nemo_archive_path: Path to the .nemo STRING
HIGHtensorrt_llm/_torch/weight_sharing/source_identity.py523Decide whether a receiver may consume `source`'s shared weights. Args: local: The receiver's own identity. STRING
HIGHtensorrt_llm/_torch/shared_tensor/shared_tensor.py112Get a rebuild method by its key. Args: key: The numeric key of the method Returns: STRING
HIGHtensorrt_llm/_torch/shared_tensor/shared_tensor.py380Create a SharedTensorContainer from a serialized dictionary (Consumer side). This method is called by the consuSTRING
HIGHtensorrt_llm/_torch/custom_ops/torch_custom_ops.py1211Unified NVFP4 GEMM with automatic backend selection. This function automatically chooses the best backend from the STRING
HIGHtensorrt_llm/_torch/memory/gpu_memory_backend.py303Context manager scoping CUDA allocations to the GMS pool. All `torch.empty` / `torch.zeros` / etc. allocations STRING
HIGHtensorrt_llm/_torch/memory/gpu_memory_backend.py418Register tensors, commit them, and transition this client to RO. After this returns successfully, `is_rw` flipsSTRING
HIGHtensorrt_llm/_torch/visual_gen/pipeline_loader.py77Resolve checkpoint_dir to a local directory path. If checkpoint_dir is an existing local path, returns it unchaSTRING
HIGHtensorrt_llm/_torch/models/modeling_deepseekv4.py126 Dequantizes the given weight tensor using the provided scale tensor. Args: x (torch.Tensor): The quantSTRING
HIGHtensorrt_llm/_torch/models/modeling_deepseekv3.py113 Dequantizes the given weight tensor using the provided scale tensor. Args: x (torch.Tensor): The quantSTRING
HIGHtensorrt_llm/_torch/models/modeling_nemotron_nano.py1621Replace each `<video>` placeholder in `prompt_token_ids` with the full per-frame expansion (optional "This is a STRING
HIGHtensorrt_llm/_torch/models/modeling_hyperclovax.py627 Get the number of tokens per image. This method must be called after __call__ is executed. UseSTRING
HIGHtensorrt_llm/_torch/peft/lora/layer.py93Convert a string to the corresponding LoraModuleType. Args: name: The string name of the module typSTRING
HIGHtensorrt_llm/_torch/pyexecutor/request_utils.py248Partition context for Helix CP. Args: input_token_ids: List of input token IDs. cp_rank: Current CPSTRING
HIGHtensorrt_llm/_torch/pyexecutor/request_utils.py462Merge RequestQueueItems to LlmRequests based on CP configuration. This is a router function that dispatches to the STRING
HIGHtensorrt_llm/_torch/pyexecutor/layerwise_nvtx_marker.py20 Initialize module variables Args: None: Returns: None: Raises: STRING
HIGHtensorrt_llm/_torch/pyexecutor/layerwise_nvtx_marker.py38 Descends iterators that contains Tensors and prints the Tensor Recursive function that descends iterator type STRING
HIGHtensorrt_llm/_torch/pyexecutor/layerwise_nvtx_marker.py65 Callback function that ends the NVTX marker Records the module name and tensor information Called afteSTRING
HIGHtensorrt_llm/_torch/pyexecutor/layerwise_nvtx_marker.py92 Creates an NVTX marker with the module name in it. This function is called before the module executes STRING
HIGHtensorrt_llm/_torch/pyexecutor/layerwise_nvtx_marker.py130 User level function that activates all the hooks The user needs to call this method from the network source coSTRING
HIGHtensorrt_llm/_torch/pyexecutor/sampler/sampler.py231Validate that the request can be processed by the sampler. If the request is not supported by the sampler, thisSTRING
HIGH…/_torch/auto_deploy/custom_ops/fused_moe/trtllm_moe.py679TensorRT-LLM Cutlass FP8 (W8A8) MoE for gated and non-gated MLP. Computes (per expert): For gated_mlp: STRING
HIGH…/_torch/auto_deploy/custom_ops/fused_moe/trtllm_moe.py949TensorRT-LLM Cutlass FP8 Block Scale MoE for FineGrainedFP8 format. This op uses the DeepSeek FP8 block scale formaSTRING
HIGHtensorrt_llm/_torch/auto_deploy/utils/_graph.py612Get an attribute specified by a dot-separated path on an object. Args: obj: The root object from which to rSTRING
HIGHtensorrt_llm/_torch/auto_deploy/utils/_graph.py767Remove a graph input from the given GraphModule. This is the inverse operation of add_graph_input(). It removes a pSTRING
HIGH…llm/_torch/auto_deploy/models/custom/modeling_eagle.py721Forward pass for Eagle drafter. Args: inputs_embeds: Input token embeddings [batch, seq, hidden_sizSTRING
HIGH…lm/_torch/auto_deploy/transform/library/sharding_ir.py106Convert string names like 'AUTO' to AllReduceStrategy enum. This is a shared validator for allreduce_strategy fieldSTRING
HIGH…rrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py947 Run MoE computation with DeepGemm backend. This method encapsulates the core MoE computation logic, haSTRING
HIGHtensorrt_llm/_torch/modules/fused_moe/interface.py879 Quantize input tensor - unified interface for all MoE backends NOTE: This is a temporary interface. InSTRING
HIGH…t_llm/_torch/modules/fused_moe/fused_moe_trtllm_gen.py687 Run MoE computation with TRTLLMGen backend. This method encapsulates the core MoE computation logic, hSTRING
HIGH…rrt_llm/_torch/modules/fused_moe/fused_moe_cute_dsl.py814 Run MoE computation with CuteDSL backend. This method encapsulates the core MoE computation logic, hanSTRING
HIGHtensorrt_llm/_torch/modules/fused_moe/routing.py1086 Generate GPU-aware load balanced expert indices with rank-aware scheduling. Dispatch kernel backgroundSTRING
HIGHtensorrt_llm/_torch/modules/fused_moe/routing.py1622 Create logits that produce GPU-aware load balanced expert assignment. The heavy lifting is delegated to a routSTRING
HIGH…nsorrt_llm/_torch/modules/fused_moe/ep_group_health.py129Mark ``rank`` as failed. Idempotent. Args: rank: Index of the rank to mark, in ``[0, moe_world_sizeSTRING
HIGH…nsorrt_llm/_torch/modules/fused_moe/ep_group_health.py153Mark ``rank`` as active. Idempotent. Used when a replacement rank rejoins the group after a failure. HiSTRING
HIGH…nsorrt_llm/_torch/modules/fused_moe/ep_group_health.py200Return the active-rank bitmask split into little-endian uint64 words. Suitable for passing to CUDA kernels thatSTRING
HIGHtensorrt_llm/_torch/modules/dwdp/specs.py297Compute page-aligned layout for given parameters. Args: expert_bytes: Bytes per single expert. STRING
HIGHtensorrt_llm/_torch/modules/dwdp/page_pool.py237Get handle for a specific page. Args: slot: Double buffer slot (0 or 1). page_idx: PageSTRING
HIGHtensorrt_llm/_torch/modules/dwdp/page_pool.py268Map pages from pool[slot] starting at page_offset into VA. Maps ceil(size / page_size) pool page handles sequenSTRING
HIGHtensorrt_llm/_torch/modules/dwdp/transport.py234Allocate MNNVL handles, populate them, and exchange with all peers. This is the main entry point. Each of the `STRING
HIGHtensorrt_llm/_torch/modules/dwdp/vmm.py47Check CUDA driver API result and raise on error. Args: cu_func_ret: Return value from CUDA driver API call.STRING
HIGHtensorrt_llm/_torch/modules/dwdp/vmm.py75Align value up to the nearest multiple of alignment. Args: value: Value to align. alignment: AlignmSTRING
HIGHtensorrt_llm/_torch/modules/dwdp/vmm.py93Align value down to the nearest multiple of alignment. Args: value: Value to align. alignment: AligSTRING
HIGHtensorrt_llm/_torch/modules/dwdp/vmm.py213Create a peer-shareable memory handle. The handle type is selected by ``peer_handle_type()``: FABRIC on aarch64STRING
HIGHtensorrt_llm/_torch/modules/dwdp/vmm.py235Create a local (non-shareable) memory handle. Uses CU_MEM_HANDLE_TYPE_NONE — the handle cannot be exported to otherSTRING
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AI Structural Patterns417 hits · 365 pts
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LOW…ittest/_torch/weight_sharing/_source_identity_fakes.py94CODE
LOWtests/unittest/_torch/misc/test_virtual_memory.py240CODE
LOW…ttest/_torch/attention/sparse/test_sparse_attention.py457CODE
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py465CODE
LOW…ttention/sparse/deepseek_v4/test_deepseek_v4_o_proj.py104CODE
LOW…ittest/_torch/visual_gen/test_attention_integration.py86CODE
LOW…ittest/_torch/visual_gen/test_attention_integration.py121CODE
LOW…ittest/_torch/visual_gen/test_attention_trtllm_sage.py53CODE
LOW…ts/unittest/_torch/visual_gen/test_qwen_image_infer.py26CODE
LOW…unittest/_torch/visual_gen/test_cosmos3_transformer.py154CODE
LOW…ts/unittest/_torch/modeling/test_modeling_step3p7vl.py98CODE
LOWtests/unittest/_torch/multi_gpu/test_user_buffers.py437CODE
LOWtests/unittest/_torch/multi_gpu/test_user_buffers.py1140CODE
LOWtests/unittest/_torch/multi_gpu/test_user_buffers.py109CODE
LOW…unittest/_torch/thop/parallel/test_fp4_bmm_quantize.py59CODE
LOW…unittest/_torch/thop/parallel/test_fp4_bmm_quantize.py72CODE
LOW…h/thop/parallel_hw_agnostic/test_fused_qk_norm_rope.py94CODE
LOWtests/unittest/_torch/thop/serial/test_moe.py523CODE
LOWtests/unittest/_torch/thop/serial/test_moe.py554CODE
LOW…tor/multi_gpu/test_accuracy_with_allreduce_strategy.py71CODE
LOW…unittest/_torch/executor/test_kv_cache_v2_scheduler.py182CODE
LOWtests/unittest/_torch/executor/test_benchmark_disagg.py72CODE
LOWtests/unittest/_torch/executor/test_benchmark_disagg.py482CODE
LOW…s/unittest/_torch/executor/test_iter_stats_populate.py596CODE
LOW…sts/unittest/_torch/executor/test_kv_pool_rebalance.py42CODE
LOW…test/_torch/executor/test_kv_cache_v2_extra_buffers.py29CODE
LOW…ts/unittest/_torch/executor/test_per_layer_head_dim.py34CODE
LOWtests/unittest/_torch/modules/test_fused_moe.py1466CODE
LOW…test/_torch/modules/mamba/test_mamba2_mtp_ssm_cache.py22CODE
LOWtests/unittest/_torch/modules/moe/test_moe_module.py435CODE
LOWtests/unittest/_torch/modules/moe/test_moe_module.py496CODE
LOWtests/unittest/_torch/modules/moe/test_moe_module.py822CODE
LOWtests/unittest/_torch/modules/moe/quantize_utils.py237CODE
LOWtests/unittest/_torch/modules/moe/quantize_utils.py2118CODE
LOW…cache_manager_v2_tests/test_kv_cache_stats_behavior.py228CODE
LOW…/kv_cache_manager_v2_tests/test_kv_cache_manager_v2.py1012CODE
LOW…/kv_cache_manager_v2_tests/test_kv_cache_manager_v2.py1939CODE
LOWtests/unittest/utils/torch_ref.py552CODE
LOWtests/unittest/utils/torch_ref.py747CODE
LOWtests/unittest/disaggregated/test_peer.py78CODE
LOWtests/unittest/disaggregated/region/test_block.py17CODE
LOWtests/unittest/llmapi/test_utils.py57CODE
LOWtests/unittest/llmapi/lora_test_utils.py186CODE
LOWtests/unittest/llmapi/apps/openai_server.py22CODE
LOWtests/unittest/executor/test_stats_serializer.py48CODE
LOW…y/multigpu/transformations/library/test_tp_sharding.py282CODE
LOW…egpu/transformations/library/test_attention_matcher.py99CODE
LOW…egpu/transformations/library/test_attention_matcher.py200CODE
LOW…egpu/transformations/library/test_attention_matcher.py290CODE
LOW…egpu/transformations/library/test_attention_matcher.py419CODE
LOW…egpu/transformations/library/test_attention_matcher.py923CODE
LOW…egpu/transformations/library/test_attention_matcher.py1029CODE
LOW…egpu/transformations/library/test_attention_matcher.py1118CODE
LOW…egpu/transformations/library/test_attention_matcher.py1156CODE
LOW…y/singlegpu/transformations/library/test_moe_fusion.py111CODE
LOW…y/singlegpu/transformations/library/test_moe_fusion.py186CODE
LOW…y/singlegpu/transformations/library/test_moe_fusion.py604CODE
LOW…y/singlegpu/transformations/library/test_moe_fusion.py1438CODE
LOW…y/singlegpu/transformations/library/test_moe_fusion.py1491CODE
LOW…_deploy/singlegpu/models/test_skywork_r1v2_modeling.py63CODE
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AI Slop Vocabulary129 hits · 364 pts
SeverityFileLineSnippetContext
MEDIUMdocker/common/install.sh6# Resolve script directory for robust relative pathingCOMMENT
MEDIUMtests/unittest/_torch/attention/backend_capability.py29 # backend harness. (1) The NVFP4 attention op aborts without the per-tensor /COMMENT
LOW…unittest/_torch/attention/test_flashinfer_attention.py488 # For simplicity, just use 1 page per request in this example.COMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py100 # Vanilla golden / FlashInfer get harness-applied RoPE. Only affects TRTLLM.COMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py108 # MLA latent dims (only meaningful when is_mla). The unified harness runs theCOMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py111 # Vanilla golden vs FlashInfer and TRTLLM. The harness skipsCOMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py273# harness feeds the *absorbed* fused_q + latent directly (random), exercisingCOMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py502 # The harness feeds a pre-RoPE'd fused_q, so skip the RoPE step;COMMENT
MEDIUMtests/unittest/_torch/attention/backend_case.py1015 # num_seqs+1). The model engine sets these; the standalone harnessCOMMENT
LOW…ttest/_torch/visual_gen/test_trtllm_serve_endpoints.py638 # we can verify per-image output mapping, not just call counts.COMMENT
MEDIUM…rch/visual_gen/multi_gpu/test_wan_pipeline_parallel.py126# Distributed harness (mirrors tests/.../multi_gpu/test_wan_attn2d.py)COMMENT
MEDIUM…ittest/_torch/multimodal/test_mm_encoder_standalone.py749 # the tensor's contents), while others should actually differ (those pertaining to the underlyingCOMMENT
MEDIUM…sts/unittest/_torch/lora/test_moe_lora_grouped_gemm.py463 # *reassignment* invariant, and uses a precision-robust discriminative checkCOMMENT
LOWtests/unittest/_torch/modules/test_awq_quantization.py74 # just return a dummy output since we are capturing the input before input quantizationCOMMENT
LOWtests/unittest/_torch/modules/test_awq_quantization.py175 # just return a dummy output since we are capturing the input before input quantizationCOMMENT
MEDIUM…dules/fused_moe/test_deepgemm_fused_gather_finalize.py204 # Committed gate: tight tolerance (robust across FMA-contraction differencesCOMMENT
MEDIUM…/unittest/_torch/modules/dwdp/test_dwdp_peer_ranges.py57 # ``compute_peer_ranges`` itself stays robust.COMMENT
MEDIUMtests/unittest/_torch/modules/moe/test_moe_module.py1004# fused kernel, so the test harness must NOT force a hostCOMMENT
MEDIUMtests/unittest/others/test_kv_cache_transceiver.py514 # Drive the transfer to completion so the harness tears down cleanly.COMMENT
MEDIUMtests/unittest/others/test_lm_eval.py52# The helpers are mirrored from lm-evaluation-harness so the behaviour mustCOMMENT
MEDIUMtests/unittest/others/test_lm_eval.py168# can override the greedy defaults baked into lm-eval-harness task YAMLs.COMMENT
MEDIUMtests/unittest/llmapi/test_llm_pytorch.py160 # anyways more robust than delegating cleanup to __del__.COMMENT
MEDIUMtests/unittest/llmapi/test_llm_pytorch.py176 # anyways more robust than delegating cleanup to __del__.COMMENT
MEDIUMtests/unittest/llmapi/test_gms_args.py76 # field path so the assertion is robust across Pydantic 2.x errorCOMMENT
MEDIUM…llmapi/apps/_test_trtllm_serve_multimodal_benchmark.py54 # Use pytorch backend for multimodal support and fix port to facilitate benchmarkingCOMMENT
MEDIUM…sts/unittest/llmapi/apps/_test_trtllm_serve_example.py36 # fix port to facilitate concise trtllm-serve examplesCOMMENT
LOWtests/unittest/llmapi/apps/utils.py258 # No brackets, just add the node as-isCOMMENT
MEDIUM…to_deploy/multigpu/transformations/library/conftest.py49# registered as CausalLM classes for this harness. Keep canonical discoveryCOMMENT
MEDIUM…pu/transformations/library/test_step3p7_sharding_ir.py34# The generic harness and helpers live alongside this file / under _utils_test.COMMENT
MEDIUM…pu/transformations/library/test_step3p7_sharding_ir.py45# A bare module name lets the harness resolve the model from either bundledCOMMENT
MEDIUM…ansformations/library/test_sharding_num_correctness.py498 # the standalone-export test harness has no factory or per-model YAMLCOMMENT
MEDIUM…ansformations/library/test_sharding_num_correctness.py662 # * the on-the-fly NVFP4 quant harness yields packed-uint8 / pack-factorCOMMENT
MEDIUM…ansformations/library/test_sharding_num_correctness.py669 # quant). Skip them for nvfp4 until the tiny-config FP4 harness isCOMMENT
MEDIUM…ansformations/library/test_sharding_num_correctness.py696 # *pre-existing* sharding-compat issues unrelated to this test harness.COMMENT
MEDIUM…ansformations/library/test_sharding_num_correctness.py829 # legacy source we can drive from this standalone-export harness.COMMENT
MEDIUM…ansformations/library/test_sharding_num_correctness.py227# tiny harness reproduce the real fused-kernel bug -- something the unfusedSTRING
MEDIUM…u/transformations/library/test_attention_matcher_hf.py104 # TODO (lucaslie, #4783): don't check for causal mask until we have more robust handlingCOMMENT
LOW…to_deploy/singlegpu/models/test_modeling_nemotron_h.py186 # 2. Can't get `padding` / `truncation` to work without other steps so just use the promptsCOMMENT
LOW…st/auto_deploy/singlegpu/models/test_hybrid_patches.py89 # 2. Can't get `padding` / `truncation` to work without other steps so just use the promptsCOMMENT
MEDIUM…/integration/defs/stress_test/disagg_cancel/harness.py93 # Full YAML subtree, for fields the harness consumes lazilyCOMMENT
MEDIUM…ration/defs/stress_test/disagg_cancel/test_injector.py195# Injector thread integration (harness wiring)COMMENT
MEDIUM…integration/defs/stress_test/disagg_cancel/_testing.py34# Minimal valid marathon YAML for tests that only need the harness toCOMMENT
MEDIUM…ion/defs/stress_test/disagg_cancel/test_log_scanner.py418# Tests: _LogSource unit behaviour (without the harness wrapper)COMMENT
MEDIUM…st/disagg_cancel/configs/marathon_cpp_v1_deepseek.yaml51# Stress harness configuration (consumed by harness.py::StressConfig).COMMENT
MEDIUMtests/integration/defs/deterministic/payload.json4 "content": "DOCUMENTS:\n[\n {\n \"id\": \"doc_1\",\n \"title\": \"Employee Benefits - India\",\n \"conCODE
MEDIUMtests/integration/defs/deterministic/payload.json4 "content": "DOCUMENTS:\n[\n {\n \"id\": \"doc_1\",\n \"title\": \"Employee Benefits - India\",\n \"conCODE
MEDIUM…ntegration/defs/accuracy/test_epd_disagg_multimodal.py13# harness. Placing them on different physical GPUs silently corrupts theCOMMENT
MEDIUMtests/integration/defs/accuracy/accuracy_core.py532 # NOTE: LongBench v1 is driven by lm-evaluation-harness task configs.COMMENT
MEDIUM…tegration/defs/accuracy/test_llm_api_pytorch_encode.py412 # Chosen to be robust to near-tie argmax flips under FP16/BF16 roundingCOMMENT
MEDIUMtests/integration/defs/accuracy/references/mmmu.yaml52# While enabling reasoning for current test harness is not supported, the metric here is for modelCOMMENT
MEDIUM…/defs/examples/visual_gen/test_visual_gen_multi_gpu.py74# Distributed helpers (mirrors unittest multi_gpu harness)COMMENT
MEDIUMtests/integration/defs/perf/session_data_writer.py42 # Perf specific session properties and values to utilizeCOMMENT
MEDIUMtests/microbenchmarks/all_reduce.py375# ── nccl-tests style comprehensive benchmark (--benchmark mode) ──────────────COMMENT
MEDIUM…enchmarks/attention_perf/test_attention_perf_module.py72# independent session) and gates on the median-of-medians, which is robust to aCOMMENT
MEDIUM…enchmarks/attention_perf/test_attention_perf_module.py355# harness extensions — added in follow-ups.COMMENT
MEDIUM…enchmarks/attention_perf/test_attention_perf_module.py431# routes the harness to the latent-KV two-call forward (mla_rope_generation ->COMMENT
MEDIUM…enchmarks/attention_perf/test_attention_perf_module.py433# qk_rope 64, v 128 (harness defaults). use_paged_context_fmha is forced FalseCOMMENT
MEDIUM…enchmarks/attention_perf/test_attention_perf_module.py505# attention path. is_dsa routes the harness to an MLA module whose backend isCOMMENT
MEDIUM…crobenchmarks/attention_perf/attention_perf_harness.py178 # MLA (DeepSeek-style latent attention). When True the harness uses the MLACOMMENT
MEDIUM…crobenchmarks/attention_perf/attention_perf_harness.py192 # DSA (DeepSeek-V3.2 sparse attention). When True the harness uses the DSACOMMENT
69 more matches not shown…
Redundant / Tautological Comments242 hits · 354 pts
SeverityFileLineSnippetContext
LOWsetup.py268 # Check if file matches any pattern using fnmatch (same as wheel extraction)COMMENT
LOW…ittest/_torch/attention/sparse/dsa/test_dsa_indexer.py2357 # Check if exactly the sameCOMMENT
LOW…attention/sparse/deepseek_v4/test_compressor_kernel.py2623 # Print resultsCOMMENT
LOW…attention/sparse/deepseek_v4/test_compressor_kernel.py2739 # Print resultsCOMMENT
LOW…arse/deepseek_v4/test_deepseek_v4_indices_transform.py65 # Set compressed_topk to 2048 to test all compressed tokensCOMMENT
LOW…s/unittest/_torch/modeling/test_modeling_starcoder2.py334 # Check if we have enough GPU memory (need ~10GB for StarCoder2-3B + LoRA)COMMENT
LOW…ittest/_torch/multi_gpu/test_lowprecision_allreduce.py164 # Check if total differences is multiple of 8COMMENT
LOW…ittest/_torch/multi_gpu/test_lowprecision_allreduce.py166 # Check if all diff_values_output are in tmp_raw_resultCOMMENT
LOW…ittest/_torch/multi_gpu/test_lowprecision_allreduce.py214 # Print resultsCOMMENT
LOWtests/unittest/_torch/sampler/test_logits_logprobs.py498 # Check if the logprob matches the top-rank logprob from the logitsCOMMENT
LOWtests/unittest/_torch/sampler/test_logits_logprobs.py508 # Check if the logprob matches the token-id logprob from the logitsCOMMENT
LOWtests/unittest/_torch/sampler/test_torch_sampler.py1026 # Check if sizes are correctCOMMENT
LOWtests/unittest/_torch/sampler/test_torch_sampler.py1037 # Check if values are added correctlyCOMMENT
LOW…sts/unittest/_torch/thop/parallel/test_fp8_quantize.py194 # Check if the bits of paddings are zero.COMMENT
LOW…test/_torch/thop/parallel/test_fp8_block_scale_gemm.py498 # Print the outputCOMMENT
LOW…sts/unittest/_torch/executor/test_router_dealer_ipc.py84 # Check if any process is still alive and terminate if neededCOMMENT
LOWtests/unittest/_torch/modules/test_moe_host_sharer.py41 # Check if the data matches the expected patternCOMMENT
LOWtests/unittest/_torch/modules/test_moe_host_sharer.py154 # Check if all expert tensors are correctly shared and stored in all_tensorsCOMMENT
LOWtests/unittest/_torch/modules/moe/test_moe_module.py309 # Check if we should run full tactic replayCOMMENT
LOWtests/unittest/_torch/modules/moe/test_moe_backend.py990 # Check if this backend+quant_algo combination supports autotuner capture/replayCOMMENT
LOWtests/unittest/tools/test_test_to_stage_mapping.py239 # Check if stage name contains the backend identifierCOMMENT
LOWtests/unittest/scaffolding/test_mcp_worker.py145 # Check if process exited unexpectedlyCOMMENT
LOWtests/unittest/scaffolding/test_mcp_worker.py149 # Check if timeout occurredCOMMENT
LOW…unittest/disaggregated/test_py_cache_transceiver_mp.py778 # Print results and assert on rank 0COMMENT
LOWtests/unittest/llmapi/test_llm_args.py2222 # Check if this field is exempt (check class and all parent classes)COMMENT
LOWtests/unittest/llmapi/test_llm_args.py2394 # Check if the default is a mutable type instanceCOMMENT
LOWtests/unittest/llmapi/apps/_test_openai_prometheus.py167 # Check if iteration stats metrics have sample valuesCOMMENT
LOWtests/unittest/llmapi/apps/utils.py218 # Check if this group has bracket notationCOMMENT
LOWtests/unittest/llmapi/apps/utils.py230 # Check if it's a range (contains dash)COMMENT
LOWtests/unittest/llmapi/apps/_test_openai_cache_salt.py79 # Check if metrics endpoint is availableCOMMENT
LOWtests/unittest/llmapi/apps/_test_openai_cache_salt.py157 # Check if metrics are availableCOMMENT
LOW…ions/library/test_allreduce_residual_rmsnorm_fusion.py141 # Check if fused node in the graph and verify strategyCOMMENT
LOW…glegpu/transformations/library/test_trtllm_gen_diag.py382 # Print valuesCOMMENT
LOW…eploy/singlegpu/utils/test_delete_unused_submodules.py171 # Check if any of the node's inputs come from a target module's get_attrCOMMENT
LOW…deploy/singlegpu/models/test_glm4_moe_lite_modeling.py398 # Check if this is an MoE expert weightCOMMENT
LOWtests/unittest/bindings/test_executor_bindings.py781 # Check if finish reason is correct.COMMENT
LOWtests/integration/defs/conftest.py1930 # Check if nvidia-smi returned a valid numeric valueCOMMENT
LOWtests/integration/defs/conftest.py2285 # Check if any suite name matches the test nameCOMMENT
LOWtests/integration/defs/common.py1232 # Check if the port is freeCOMMENT
LOWtests/integration/defs/test_e2e.py1739 # Set max_seq_len to 4096 to use short rope factor.COMMENT
LOWtests/integration/defs/test_e2e.py1859 # Print the outputs.COMMENT
LOWtests/integration/defs/test_list_validation.py81 # Check if perf test config can be successfully loaded.COMMENT
LOWtests/integration/defs/stress_test/stress_test.py1476 # Check if we have any valid dataCOMMENT
LOWtests/integration/defs/stress_test/stress_test.py623 # Check if port is availableCOMMENT
LOWtests/integration/defs/stress_test/stress_test.py627 # Check if server is already runningCOMMENT
LOWtests/integration/defs/stress_test/stress_test.py769 # Check if process is still runningCOMMENT
LOWtests/integration/defs/stress_test/stress_test.py1339 # Check if process completed successfullyCOMMENT
LOW…s/integration/defs/disaggregated/test_disaggregated.py2252 # Check if process completed successfullyCOMMENT
LOW…s/integration/defs/accuracy/test_llm_api_autodeploy.py429 # Set explicitly to match default build_config behaviorCOMMENT
LOW…ntegration/defs/accuracy/test_disaggregated_serving.py75 # Check if the command executed successfullyCOMMENT
LOW…integration/defs/examples/run_llm_quickstart_atexit.py23 # Print the outputs.COMMENT
LOW…tegration/defs/examples/run_llm_fp8_quant_llama_70b.py33 # Print the outputs.COMMENT
LOW…egration/defs/examples/test_ad_speculative_decoding.py322# Set up to test the prefill-only version of the EagleWrapper model in test_eagle_wrapper_forward().COMMENT
LOW…egration/defs/examples/test_ad_speculative_decoding.py911 # Set previously_accepted_tokens to the length of input_ids (all context tokens are accepted)COMMENT
LOWtests/integration/defs/examples/test_flux.py24# Check if CLIP is availableCOMMENT
LOWtests/integration/defs/sysinfo/get_sysinfo.py251 #Set is_remote to False temporarilyCOMMENT
LOWtests/integration/defs/perf/perf_regression_utils.py101 # Set trigger_mr_commit to commitCOMMENT
LOWtests/integration/defs/perf/perf_regression_utils.py157 # Check if all valid values are identicalCOMMENT
LOWtests/integration/defs/perf/perf_regression_utils.py346 # Check if this metric is regressive (only for key regression metrics)COMMENT
LOWtests/integration/defs/perf/test_perf.py637 # Check if device subtype is present (for autodeploy tests)COMMENT
182 more matches not shown…
Cross-Language Confusion77 hits · 330 pts
SeverityFileLineSnippetContext
HIGHtests/unittest/test_pip_install.py155 subprocess.check_call("rm *.whl || true", shell=True)CODE
HIGHtests/unittest/test_pip_install.py156 subprocess.check_call(f"apt-get install -y wget && wget -q {wheel_url}",CODE
HIGHtests/unittest/test_pip_install.py247 subprocess.check_call("pip3 install --ignore-installed pip || true",CODE
HIGHtests/unittest/test_pip_install.py249 subprocess.check_call("pip3 install --ignore-installed setuptools || true",CODE
HIGHtests/unittest/test_pip_install.py251 subprocess.check_call("pip3 install --ignore-installed wheel || true",CODE
HIGH…ts/unittest/_torch/visual_gen/test_visual_gen_utils.py315 """Schema-aware null sentinel: ``{"stg_scale": null}`` does notSTRING
HIGH…ts/unittest/_torch/visual_gen/test_visual_gen_utils.py334 null}`` reach the engine as a silent no-op."""STRING
HIGHtests/unittest/kv_cache_manager_v2_tests/kernels.py84 return token == other.token && layer == other.layer && role == other.role && beam == other.beam;CODE
HIGHtests/unittest/kv_cache_manager_v2_tests/kernels.py106 if (idxToken < numTokens && idxHead < numHeads) {CODE
HIGHtests/unittest/kv_cache_manager_v2_tests/kernels.py111 if (sleepTime > 0 && tid == 0) {CODE
HIGHtests/unittest/kv_cache_manager_v2_tests/kernels.py137 if (idxToken < numTokens && idxHead < numHeads) {CODE
HIGHtests/unittest/kv_cache_manager_v2_tests/kernels.py142 if (sleepTime > 0 && tid == 0) {CODE
HIGHtests/unittest/usage/test_llmapi_config_capture.py619 """None on an Optional allowlist field is captured as null, not excluded.STRING
HIGHtests/unittest/llmapi/apps/test_tool_parsers.py1185 "command": "pwd && ls"CODE
HIGHtests/unittest/llmapi/apps/test_tool_parsers.py1155 "pwd && ls\n"CODE
HIGHtests/integration/defs/triton_server/common.py17 r"curl -s -w %{http_code} 0.0.0.0:8000/v2/health/ready || true",CODE
HIGHtests/integration/defs/triton_server/common.py21 r"curl -s -w %{http_code} 0.0.0.0:8003/v2/health/ready || true",CODE
HIGH.devcontainer/make_env.py37 ("(echo set -a && cat " +CODE
HIGH.devcontainer/make_env.py39 " && echo && echo exec /usr/bin/env python3 -c \"'import json; import os; print(json.dumps(dict(os.environ)CODE
HIGHtensorrt_llm/lora_manager.py825 "enable_lora": null,STRING
HIGH…m/_torch/visual_gen/models/cosmos3/pipeline_cosmos3.py175 "- `pip install cosmos_guardrail==0.3.0 && pip uninstall opencv-python`"CODE
HIGH…ch/cute_dsl_kernels/blackwell/moe_as_dense_gemm/fc1.py2517 :param c_sf_ptr: Pointer to scale factor tensor for C (can be null)STRING
HIGH…ch/cute_dsl_kernels/blackwell/moe_as_dense_gemm/fc1.py2524 :param norm_const_ptr: Pointer to normalization constant for SFC generation (can be null)STRING
HIGHtensorrt_llm/scaffolding/contrib/Dynasor/evaluator.py986 if a.equals(b) or simplify(a - b) == 0:CODE
HIGHtensorrt_llm/scaffolding/contrib/Dynasor/evaluator.py1010 if _a.equals(_b):CODE
HIGHtensorrt_llm/scaffolding/contrib/Coder/prompts.py331 ``cd /testbed && git diff --no-color -- path/to/file1.py path/to/file2.py > patch.txt``STRING
HIGHtensorrt_llm/usage/llmapi_config.py480 # None: Optional field unset -> capture as null, regardless of converter.COMMENT
HIGHtensorrt_llm/evaluate/mmlu.py261 "wget https://people.eecs.berkeley.edu/~hendrycks/data.tar && tar -xf data.tar. "CODE
HIGHtensorrt_llm/serve/visual_gen_utils.py69 ``{"stg_sclae": null}`` produce a 200 with retained defaults.STRING
HIGHtensorrt_llm/serve/harmony_adapter.py1462 # Now process the actual harmony deltas (all with role=null)COMMENT
HIGHtensorrt_llm/serve/tool_parser/minimax_m2_parser.py44 # Try JSON parsing for structured types (object, array, null, etc.).COMMENT
HIGHtensorrt_llm/serve/tool_parser/qwen3_coder_parser.py26 pwd && lsSTRING
HIGHtensorrt_llm/serve/tool_parser/minimax_m3_parser.py49 (object / array / null) attempt JSON first; numerics and booleansSTRING
HIGHtensorrt_llm/serve/tool_parser/gemma4_parser.py233 # Bare value (number, boolean, null, or unquoted string)COMMENT
HIGHtensorrt_llm/serve/tool_parser/gemma4_parser.py303 - Supports: strings, numbers, booleans, null, nested objects, arraysSTRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1638 }}).filter(function(t) {{ return t !== null; }});CODE
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1643 pageYLabels.push('Req ' + reqId + ' (GPU)');CODE
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1644 pageYLabels.push('Req ' + reqId + ' (CPU)');CODE
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1650 if (trace.base && trace.x) {{CODE
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1621 indices.push(i);CODE
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1625 if (indices.length === 0) return null;CODE
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1868 if (y === cpuLabel || y === gpuLabel) {{STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1869 indices.push(i);STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1873 if (indices.length === 0) return null;STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1815 var originalData = null;STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1816 var plotDiv = null;STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1827 if (data.points && data.points.length > 0) {{STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1886 }}).filter(function(t) {{ return t !== null; }});STRING
HIGH…rrt_llm/serve/scripts/time_breakdown/time_breakdown.py1891 if (trace.base && trace.x) {{STRING
HIGHtensorrt_llm/inputs/multimodal.py825 and the content together: BLAKE3(UUID || Content). This ensures:STRING
HIGHtensorrt_llm/inputs/multimodal.py849 """Hash UUID and content together: BLAKE3(UUID || Content).STRING
HIGHcpp/kernels/fmha_v2/setup.py1618 USE_TMA_STORE && false,STRING
HIGHcpp/kernels/fmha_v2/setup.py1639 USE_TMA_STORE && false,STRING
HIGHcpp/kernels/fmha_v2/setup.py1660 USE_TMA_STORE && false,STRING
HIGHcpp/kernels/fmha_v2/setup.py2518 code = 'if (!{has_noloop} || (!force_unroll && (ignore_b1opt || b > {unroll_threshold})))'.format(STRING
HIGHcpp/kernels/fmha_v2/setup.py2521 code = 'if (!{has_noloop} || (!force_unroll && (ignore_b1opt || b * h > {unroll_threshold})))'.format(STRING
HIGHexamples/mmlu.py21 tar -xf data/mmlu.tar -C data && mv data/data data/mmluSTRING
HIGHexamples/scaffolding/mcp/coder/coder_mcp.py118 "NR >= start && (max_lines < 0 || printed < max_lines) { "CODE
HIGHexamples/scaffolding/contrib/Coder/run_swebench.py367 "Start it with `apiary init && apiary daemon --bind ...`."CODE
HIGHexamples/scaffolding/contrib/Coder/run_coder.py123 "Start it with `apiary init && apiary daemon --bind ...`."CODE
17 more matches not shown…
Modern Structural Boilerplate261 hits · 256 pts
SeverityFileLineSnippetContext
LOWtests/unittest/_torch/visual_gen/test_cache_dit.py172 def set_timesteps(self, n: int, device=None) -> None:CODE
LOWtests/unittest/_torch/modules/test_alltoall_watchdog.py49 def set_flags(self, phase: str, flags: list[int]) -> None:CODE
LOWtests/unittest/_torch/modules/moe/test_moe_backend.py74logger = logging.getLogger(__name__)CODE
LOW…cache_manager_v2_tests/test_kv_cache_stats_behavior.py85 def set_prepopulated_prompt_len(self, length: int, tokens_per_block: int) -> None:CODE
LOW…/kv_cache_manager_v2_tests/test_kv_cache_manager_v2.py775 def update_batch(self, stream: CudaStream) -> None:CODE
LOWtests/unittest/others/test_tracing.py29logger = logging.getLogger(__name__)CODE
LOWtests/unittest/utils/llm_data.py12__all__ = [CODE
LOWtests/unittest/scripts/test_fetch_cache.py165def _set_origin_url(worktree: Path, url: str) -> None:CODE
LOWtests/unittest/llmapi/apps/_test_openai_prometheus.py33logger = logging.getLogger(__name__)CODE
LOWtests/unittest/llmapi/apps/_test_openai_perf_metrics.py15logger = logging.getLogger(__name__)CODE
LOW…sts/unittest/executor/test_fatal_error_health_check.py42logger = logging.getLogger(__name__)CODE
LOW…_deploy/singlegpu/custom_ops/test_multi_stream_attn.py109def _set_linear_meta(node: Node, out_features: int) -> None:CODE
LOWtests/integration/defs/conftest.py62logger = logging.getLogger(__name__)CODE
LOW…/integration/defs/stress_test/disagg_cancel/harness.py50logger = logging.getLogger(__name__)CODE
LOWtests/integration/defs/utils/__init__.py26__all__ = [CODE
LOW…s/integration/defs/accuracy/test_llm_api_autodeploy.py69def _set_quant_config(llm, model_id: str) -> None:CODE
LOWtests/integration/defs/sysinfo/get_sysinfo.py34logger = logging.getLogger(__name__)CODE
LOWtests/integration/defs/perf/utils.py487 def set_runtime_configs(self, *args) -> None:CODE
LOWtests/integration/defs/thirdparty/test_git_modules.py14logger = logging.getLogger(__name__)CODE
LOW…/integration/defs/thirdparty/test_cmake_third_party.py16logger = logging.getLogger(__name__)CODE
LOWtests/test_common/s3_output.py28logger = logging.getLogger(__name__)CODE
LOWtests/microbenchmarks/bench_moe/cli.py663 def set_if_unset(dest: str, value: Any) -> None:CODE
LOWtests/microbenchmarks/bench_moe/timing/__init__.py48__all__ = [CODE
LOWtests/microbenchmarks/bench_moe/routing/__init__.py76__all__ = [CODE
LOW…crobenchmarks/attention_perf/attention_perf_harness.py72__all__ = ["AttnCase", "Signals", "collect_signals", "sm_arch", "device_name"]CODE
LOWtensorrt_llm/__init__.py149__all__ = [CODE
LOWtensorrt_llm/lora_manager.py34logger = logging.getLogger(__name__)CODE
LOWtensorrt_llm/metrics/__init__.py5__all__ = [CODE
LOWtensorrt_llm/_torch/virtual_memory.py14__all__ = [CODE
LOWtensorrt_llm/_torch/__init__.py3__all__ = ["LLM"]CODE
LOWtensorrt_llm/_torch/llm.py13__all__ = ['LLM']CODE
LOWtensorrt_llm/_torch/mmap_utils.py27__all__ = [CODE
LOWtensorrt_llm/_torch/hostfunc.py12def set_low_latency_dispatch(enabled: bool) -> None:CODE
LOWtensorrt_llm/_torch/expert_statistic.py38 def set_iter(iter_id: int) -> None:CODE
LOWtensorrt_llm/_torch/expert_statistic.py43 def set_layer(layer_id: int) -> None:CODE
LOWtensorrt_llm/_torch/expert_statistic.py67 def _set_iter(self, iter_id: int) -> None:CODE
LOWtensorrt_llm/_torch/expert_statistic.py82 def _set_layer(self, layer: int) -> None:CODE
LOWtensorrt_llm/_torch/weight_sharing/__init__.py27__all__ = [CODE
LOWtensorrt_llm/_torch/shared_tensor/__init__.py7__all__ = [CODE
LOWtensorrt_llm/_torch/shared_tensor/shared_tensor.py16logger = logging.getLogger(__name__)CODE
LOW…rt_llm/_torch/custom_ops/cute_dsl_megamoe_custom_op.py52__all__ = [CODE
LOWtensorrt_llm/_torch/custom_ops/__init__.py21__all__ = [CODE
LOWtensorrt_llm/_torch/custom_ops/torch_custom_ops.py2404def set_stream(stream_id: int) -> None:CODE
LOW…rt_llm/_torch/disaggregation/native/bounce/__init__.py34__all__ = [CODE
LOWtensorrt_llm/_torch/memory/__init__.py18__all__ = ["GPUMemoryBackend", "GMSBackend"]CODE
LOWtensorrt_llm/_torch/distributed/__init__.py11__all__ = [CODE
LOWtensorrt_llm/_torch/visual_gen/pipeline_loader.py145 def _setup_visual_gen_mapping(self, config: DiffusionPipelineConfig) -> None:CODE
LOWtensorrt_llm/_torch/visual_gen/__init__.py21__all__ = [CODE
LOWtensorrt_llm/_torch/visual_gen/pipeline.py490 def _setup_cache_acceleration(self) -> None:CODE
LOWtensorrt_llm/_torch/visual_gen/cache/__init__.py10__all__ = [CODE
LOWtensorrt_llm/_torch/visual_gen/checkpoints/__init__.py5__all__ = [CODE
LOWtensorrt_llm/_torch/visual_gen/models/__init__.py42__all__ = [CODE
LOWtensorrt_llm/_torch/visual_gen/models/ltx2/__init__.py8__all__ = [CODE
LOW…_llm/_torch/visual_gen/models/ltx2/transformer_ltx2.py2052 def set_ulysses_enabled(self, enabled: bool) -> None:CODE
LOW…lm/_torch/visual_gen/models/ltx2/ltx2_core/__init__.py48__all__ = [CODE
LOW…visual_gen/models/ltx2/ltx2_core/audio_vae/__init__.py10__all__ = [CODE
LOW…visual_gen/models/ltx2/ltx2_core/video_vae/__init__.py9__all__ = [CODE
LOW…l_gen/models/ltx2/ltx2_core/video_vae/normalization.py7__all__ = ["PixelNorm", "build_normalization_layer"]CODE
LOWtensorrt_llm/_torch/visual_gen/models/flux/__init__.py11__all__ = [CODE
LOW…rt_llm/_torch/visual_gen/models/qwen_image/__init__.py25__all__ = [CODE
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Modern AI Meta-Vocabulary45 hits · 134 pts
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MEDIUM…ittest/_torch/modeling/test_modeling_qwen3_5_vl_moe.py170# --- Layered parity test scaffold -------------------------------------------COMMENT
MEDIUM…s/unittest/_torch/modeling/test_modeling_qwen3_5_vl.py188# --- Layered parity test scaffold -------------------------------------------COMMENT
MEDIUMtests/unittest/_torch/modules/helix_test_utils.py281# MPI orchestrationCOMMENT
MEDIUMtests/unittest/others/test_lm_eval.py490# format, thinking-mode chain-of-thought, empty output, etc.).COMMENT
MEDIUMtests/unittest/disaggregated/test_mamba_transfer.py207 # dummy attention layer (page table scaffolding)COMMENT
MEDIUMtests/unittest/llmapi/apps/_test_openai_embeddings.py286# sentence-embedding model. A separate, opt-in server (loads a multi-GBCOMMENT
MEDIUMtests/unittest/executor/test_proxy_fast_death.py91 # Broadcast happened event-driven: sticky flag set + EngineDeadError pushed.COMMENT
MEDIUM…ation/defs/accuracy/test_llm_api_pytorch_multimodal.py633 # chain-of-thought reasoning before outputting the answer.COMMENT
MEDIUM…ation/defs/accuracy/test_llm_api_pytorch_multimodal.py908 # the chain-of-thought). The text-only GSM8K path lives inCOMMENT
MEDIUM…ntegration/defs/examples/visual_gen/test_visual_gen.py112# Cosmos3 requires VANILLA attention and guardrails disabled in CI.COMMENT
MEDIUM…e/skills/perf-host-optimization/references/examples.md149# Use UPPER_WORKSPACE_DIR to isolate agentic runs from manual runsCOMMENT
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md9 - [Introduction for Scaffolding: A Framework for inference-time compute](#introduction-for-scaffolding)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md10 - [Core Features](#scaffolding-core-feature)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md11 - [Architecture](#scaffolding-architecture)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md12 - [Worker](#scaffolding-architecture-worker)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md13 - [Controller](#scaffolding-architecture-controller)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md14 - [ScaffoldingLlm](#scaffolding-architecture-scaffoldingllm)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md15 - [An Example: Implement Dynasor on Scaffolding](#example-for-scaffolding)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md17 - [Implement Dynasor-CoT in Scaffolding](#dynasor-cot-implement-in-scaffolding)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md18 - [Implement Dynasor-CoT based Majority Voting in Scaffolding](#dynasor-cot-based-majority-vote-in-scaffolding)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md21 - [Feature List on Scaffolding](#scaffolding-feature-list)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md22 - [Future Work](#scaffolding-future-work)CODE
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md334 # For the probe task, append the suffix to force a chain-of-thought leading to an answer.COMMENT
MEDIUM…ference_Time_Compute_Implementation_in_TensorRT-LLM.md347 # If the current prompt indicates the chain-of-thought phase has ended, use one type of suffix.COMMENT
MEDIUMtensorrt_llm/_torch/pyexecutor/sampler/__init__.py41 # Lazily forward everything else to the sampler orchestration module.COMMENT
MEDIUMtensorrt_llm/_torch/modules/dwdp/__init__.py84 # Setup orchestrationCOMMENT
MEDIUM…_llm/scaffolding/contrib/Dynasor/dynasor_controller.py104 # For the probe task, append the suffix to force a chain-of-thought leading to an answer.COMMENT
MEDIUMtensorrt_llm/scaffolding/contrib/Dynasor/evaluator.py468 # Handle Chinese few-shot multiple choice problem answer extractionCOMMENT
MEDIUM…nsorrt_llm/scaffolding/contrib/iter_research/README.md31### MCP tools under `examples/scaffolding/mcp`COMMENT
MEDIUMtensorrt_llm/scaffolding/contrib/Coder/__init__.py21 # python examples/scaffolding/mcp/coder/coder_mcp.py --port 8083STRING
MEDIUMtensorrt_llm/scaffolding/contrib/Coder/coder.py262 # python examples/scaffolding/mcp/coder/coder_mcp.py --port 8083STRING
MEDIUMtensorrt_llm/evaluate/covost2.py264 # rfind so that if the model dumps chain-of-thought with theCOMMENT
MEDIUMtensorrt_llm/evaluate/longbench_v2.py238 # Handle RAG modeCOMMENT
MEDIUMtensorrt_llm/evaluate/lm_eval.py78 # whose chain-of-thought output exceeds lm-eval's default (~512).COMMENT
MEDIUMtensorrt_llm/evaluate/lm_eval.py151 # thinking mode produces long chain-of-thought output. DefaultCOMMENT
MEDIUMtensorrt_llm/evaluate/lm_eval_tasks/mmmu_pro/utils.py29# smaller / MoE models that benefit the most from chain-of-thought).COMMENT
MEDIUMtensorrt_llm/executor/proxy.py377 # event-driven (see _handle_worker_death), so a coarse interval isCOMMENT
MEDIUMtensorrt_llm/commands/serve.py646 # causal-LM architecture; remap it to the text-embedding model class so theCOMMENT
MEDIUMtensorrt_llm/serve/openai_server.py109# request body: the large agentic chat body otherwise blocks the serving eventCOMMENT
MEDIUM…mples/scaffolding/contrib/open_deep_research/README.md1# Open Deep Research (scaffolding example)COMMENT
MEDIUM…scaffolding/contrib/tree_of_thought_research/README.md1# Tree-of-Thought Research (scaffolding example)COMMENT
MEDIUMexamples/scaffolding/contrib/iter_research/README.md1# IterResearch (scaffolding example)COMMENT
MEDIUMexamples/scaffolding/trace_replay/README.md269### 1) Generate traces from a scaffold runCOMMENT
MEDIUM…lding/trace_replay/analysis/compute_cache_hit_trace.py28# directly (``python examples/scaffolding/trace_replay/analysis/compute_cache_hit_trace.py``).STRING
MEDIUMjenkins/scripts/perf/local/run_disagg.sh219 # be launched with the disagg orchestration (and produce no report.xml).COMMENT
Fake / Example Data65 hits · 65 pts
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LOW…/unittest/_torch/multimodal/test_multimodal_runtime.py883 extra = {"multimodal_data": {"multimodal_embedding": "placeholder"}}CODE
LOW…ts/unittest/disaggregated/test_disagg_openai_client.py158 dummy_data = [CODE
LOW…ts/unittest/disaggregated/test_disagg_openai_client.py165 for data in dummy_data:CODE
LOW…ts/unittest/disaggregated/test_disagg_openai_client.py186 assert chunk == dummy_data[i]CODE
LOWtests/unittest/llmapi/test_llm_pytorch.py1627 "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et dolore magCODE
LOWtests/unittest/llmapi/test_llm_pytorch.py1627 "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et dolore magCODE
LOWtests/unittest/llmapi/test_llm_pytorch.py1712 "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et doCODE
LOWtests/unittest/llmapi/test_llm_pytorch.py1712 "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et doCODE
LOWtests/unittest/llmapi/test_llm_pytorch.py1895 "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et doCODE
LOWtests/unittest/llmapi/test_llm_pytorch.py1895 "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et doCODE
LOW…y/multigpu/transformations/library/test_tp_sharding.py501 placeholder_targets = [node.target for node in gm.graph.nodes if node.op == "placeholder"]CODE
LOW…eploy/singlegpu/transformations/test_pipeline_cache.py807 restored_input = next(node for node in restored.graph.nodes if node.op == "placeholder")CODE
LOW…y/singlegpu/transformations/library/test_moe_fusion.py1869 if node.op == "placeholder" and node.target == "routing_weights":CODE
LOW…/singlegpu/transformations/library/test_gemm_fusion.py720 if node.op in ("placeholder", "output", "get_attr"):CODE
LOW…/transformations/library/test_kvcache_vswa_metadata.py89 return [node.target for node in gm.graph.nodes if node.op == "placeholder"]CODE
LOW…/transformations/library/test_kvcache_vswa_metadata.py142 and arg.op == "placeholder"CODE
LOW…/transformations/library/test_kvcache_vswa_metadata.py184 if node.op == "placeholder" and "seq_len_with_cache" in str(node.target):CODE
LOW…pu/transformations/library/test_shared_kv_attention.py172 placeholder_names = [node.target for node in gm.graph.nodes if node.op == "placeholder"]CODE
LOW…pu/transformations/library/test_shared_kv_attention.py312 placeholder_names = [node.target for node in gm.graph.nodes if node.op == "placeholder"]CODE
LOW…pu/transformations/library/test_shared_kv_attention.py395 placeholder_names = [node.target for node in gm.graph.nodes if node.op == "placeholder"]CODE
LOW…inglegpu/transformations/library/test_fuse_silu_mul.py48 if n.op == "placeholder":CODE
LOW…inglegpu/transformations/library/test_fuse_silu_mul.py73 if n.op == "placeholder":CODE
LOW…inglegpu/transformations/library/test_fuse_silu_mul.py100 if n.op == "placeholder":CODE
LOW…t/auto_deploy/singlegpu/compile/test_captured_graph.py119 node for node in gm.graph.nodes if node.op == "placeholder" and node.target == "out"CODE
LOW…/auto_deploy/singlegpu/compile/test_piecewise_utils.py243 for op_type in ("placeholder", "call_method", "call_module", "output", "get_attr"):CODE
LOWtests/integration/defs/llmapi/test_llm_api_connector.py173 "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore mCODE
LOWtests/integration/defs/llmapi/test_llm_api_connector.py173 "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore mCODE
LOWtensorrt_llm/_torch/pyexecutor/resource_manager.py230 TODO(TRTLLM-12045): each model should provide its own warmup dummy_dataSTRING
LOWtensorrt_llm/_torch/pyexecutor/_util.py571 # Gate on `MultimodalModelMixin`: the dummy-data sizing below onlyCOMMENT
LOWtensorrt_llm/_torch/auto_deploy/utils/node_utils.py989 # in the graph, and this input_id_node op is "placeholder". Nevertheless, it serves as a properCOMMENT
LOWtensorrt_llm/_torch/auto_deploy/utils/node_utils.py977 if input_id_node is None and node.op == "placeholder":CODE
LOWtensorrt_llm/_torch/auto_deploy/utils/_graph.py418 inps = [node.meta.get("val", _NO_VAL) for node in gm.graph.nodes if node.op == "placeholder"]CODE
LOWtensorrt_llm/_torch/auto_deploy/utils/_graph.py502 node_last_input = graph.find_nodes(op="placeholder", sort=True)[-1]CODE
LOWtensorrt_llm/_torch/auto_deploy/utils/_graph.py545 if n.op != "placeholder":CODE
LOWtensorrt_llm/_torch/auto_deploy/utils/_graph.py789 if input_node.op != "placeholder":CODE
LOWtensorrt_llm/_torch/auto_deploy/utils/_graph.py796 placeholder_nodes = graph.find_nodes(op="placeholder", sort=True)CODE
LOWtensorrt_llm/_torch/auto_deploy/utils/graph_writer.py54 if node.op == "placeholder":CODE
LOW…lm/_torch/auto_deploy/models/custom/modeling_gemma4.py2251 node.target for node in language_model.graph.nodes if node.op == "placeholder"CODE
LOW…llm/_torch/auto_deploy/models/custom/modeling_eagle.py996 return {node.name for node in submodule.graph.nodes if node.op == "placeholder"}CODE
LOWtensorrt_llm/_torch/auto_deploy/mlir/fx_to_mlir.py175 if node.op == "placeholder":CODE
LOW…orrt_llm/_torch/auto_deploy/compile/piecewise_utils.py291 if node.op in ("placeholder", "output"):CODE
LOW…_torch/auto_deploy/compile/backends/torch_cudagraph.py719 if node.op == "placeholder":CODE
LOW…_torch/auto_deploy/compile/backends/torch_cudagraph.py130 if node.op == "placeholder":CODE
LOWtensorrt_llm/_torch/auto_deploy/shim/ad_executor.py791 dummy_token = -1CODE
LOWtensorrt_llm/_torch/auto_deploy/shim/ad_executor.py850 input_ids.extend([dummy_token] * (1 + draft_len))CODE
LOWtensorrt_llm/_torch/auto_deploy/transform/interface.py801 input_nodes = gm.graph.find_nodes(op="placeholder", target=name)CODE
LOW…torch/auto_deploy/transform/graph_module_visualizer.py208 "placeholder": {"fillcolor": "lightgreen", "shape": "box"},CODE
LOW…torch/auto_deploy/transform/graph_module_visualizer.py615 elif node.op == "placeholder":CODE
LOW…rch/auto_deploy/transform/pipeline_cache/structural.py242 if node.op in ("placeholder", "get_attr"):CODE
LOW…lm/_torch/auto_deploy/transform/library/sharding_ir.py1284 batch_info_host_nodes = gm.graph.find_nodes(op="placeholder", target="batch_info_host")CODE
LOW…rt_llm/_torch/auto_deploy/transform/library/kvcache.py142 op="placeholder", target=input_nameCODE
LOW…rt_llm/_torch/auto_deploy/transform/library/kvcache.py153 node_last_input = gm.graph.find_nodes(op="placeholder", sort=True)[-1]CODE
LOW…rt_llm/_torch/auto_deploy/transform/library/kvcache.py177 node_last_input = gm.graph.find_nodes(op="placeholder", sort=True)[-1]CODE
LOW…sorrt_llm/_torch/auto_deploy/transform/library/rope.py435 if current.op in ("get_attr", "placeholder"):CODE
LOW…_deploy/transform/library/cleanup_input_constraints.py46 input_node = graph.find_nodes(op="placeholder")[1]CODE
LOWtensorrt_llm/_torch/modules/fused_moe/moe_scheduler.py170 # Existing truncation at Step 4 discards dummy-token outputs automatically.COMMENT
LOWtensorrt_llm/_torch/compilation/piecewise_optimizer.py88 if node.op == "placeholder":CODE
LOWtensorrt_llm/_torch/compilation/piecewise_optimizer.py291 if node.op in ("output", "placeholder"):CODE
LOWtensorrt_llm/_torch/compilation/backend.py209 if node.op == "placeholder":CODE
LOW…m/_torch/compilation/multi_stream/auto_multi_stream.py183 if node.op == "placeholder":CODE
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Slop Phrases13 hits · 22 pts
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LOWtensorrt_llm/functional.py440 # Note: When not using deepseek_yarn, make sure to set mscale_all_dim to 0.0.COMMENT
LOW…m/_torch/auto_deploy/custom_ops/attention_interface.py1371 # set new input_ids and make sure to flatten itCOMMENT
LOW…m/_torch/auto_deploy/custom_ops/attention_interface.py1446 # set new position_ids and make sure to flatten itCOMMENT
LOW…m/_torch/auto_deploy/transform/library/export_to_gm.py79 # make sure to prepend the hook so that it is called before any other hooks so we canCOMMENT
MEDIUMtensorrt_llm/_torch/modules/fused_moe/deep_ep_utils.py157 # Later, you can use our GEMM library to do the computation with this specific formatCOMMENT
MEDIUMtensorrt_llm/commands/utils.py116 "registered LLM/VLM architecture; treating it as a language model."CODE
LOWcpp/kernels/fmha_v2/src/softmax_impl.h615 // Don't forget to put the value in sum_fp32 :)COMMENT
LOWcpp/kernels/fmha_v2/src/softmax_impl.h709 // Don't forget to put the value in sum_fp32 :)COMMENT
LOWcpp/kernels/fmha_v2/src/softmax_impl.h753 // Don't forget to put the value in sum_fp32 :)COMMENT
LOWcpp/kernels/fmha_v2/src/softmax_impl.h792 // Don't forget to put the value in sum_fp32 :)COMMENT
LOW…ecutor/cache_transmission/nixl_utils/transferAgent.cpp502 // Don't forget to add the last regionCOMMENT
MEDIUMexamples/llm-api/llm_kv_cache_connector.py79**NOTE:** This example connector implementation is designed for demonstration purposesSTRING
MEDIUMexamples/llm-api/llm_mgmn_llm_distributed.sh44# NOTE: This is a template - you can replace quickstart_advanced.py with anyCOMMENT
Magic Placeholder Names5 hits · 22 pts
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HIGHtensorrt_llm/scaffolding/contrib/Coder/__init__.py16 api_key="your-api-key",STRING
HIGHtensorrt_llm/scaffolding/contrib/Coder/coder.py257 api_key="your-api-key",STRING
HIGHexamples/scaffolding/mcp/README.md45export TAVILY_API_KEY=<your_api_key>CODE
HIGHexamples/scaffolding/mcp/README.md90python3 mcptest.py --API_KEY YOUR_API_KEYCODE
HIGH.github/ISSUE_TEMPLATE/06-bug-report.yml21 Consider redacting or replacing sensitive values with placeholders like `<YOUR_TOKEN_HERE>` when sharing configuraCODE
AI Response Leakage2 hits · 12 pts
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HIGHCODING_GUIDELINES.md734# In this example, the return type can be expressed asCOMMENT
HIGH…sts/integration/test_input_files/pg64317_sanitized.txt1The Project Gutenberg eBook of The Great Gatsby\n\nThis ebook is for the use of anyone anywhere in the United States anCODE
TODO Padding5 hits · 9 pts
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LOW…/unittest/_torch/multimodal/test_external_embedding.py34 # TODO: Add test for more VLM modelsCOMMENT
LOW…/unittest/_torch/multimodal/test_external_embedding.py139 # TODO: Add test for more modalities (audio, video, etc.)COMMENT
LOW…/singlegpu/transformations/library/test_gemm_fusion.py251# TODO: consider adding test cases for classic GQA and MLP layersCOMMENT
LOWtensorrt_llm/_torch/pyexecutor/kv_cache_manager_v2.py3020 # TODO: implement thisCOMMENT
LOWtensorrt_llm/_torch/pyexecutor/kv_cache_manager_v2.py3024 # TODO: implement thisCOMMENT
Example Usage Blocks6 hits · 9 pts
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LOWcpp/kernels/fmha_v2/src/fmha/utils.h74// Example usage:COMMENT
LOWexamples/visual_gen/serve/benchmark_visual_gen.sh8# Usage:COMMENT
LOWexamples/trtllm-eval/install_nemo_skills.sh16# Usage:COMMENT
LOWscripts/release_check.py164 # Usage:COMMENT
LOWjenkins/scripts/bash_utils.sh9# Usage:COMMENT
LOWjenkins/scripts/perf/local/run_disagg.sh5# Usage:COMMENT
Synthetic Comment Markers1 hit · 5 pts
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HIGHexamples/openai_triton/manual_plugin/README.md150When the plugin is used more than once within a model, the function cuModuleUnload() will be invoked multiple times duriCODE
Overly Generic Function Names4 hits · 3 pts
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LOWtests/unittest/llmapi/_run_multi_mpi_comm_tasks.py12def run_task(task_type: Literal["submit", "submit_sync"]):CODE
LOWtensorrt_llm/scaffolding/worker.py44 async def run_task(self, task: Task) -> TaskStatus:CODE
LOWtensorrt_llm/llmapi/utils.py835 def my_method(self, *args, **kwargs):STRING
LOWtensorrt_llm/llmapi/utils.py840 def my_method(self, *args, **kwargs):STRING