Repository Analysis

NVIDIA/cutlass

CUDA Templates and Python DSLs for High-Performance Linear Algebra

6.5 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of NVIDIA/cutlass, a C++ project with 10,076 GitHub stars. SynthScan v2.0 examined 1,597,983 lines of code across 4479 source files, recording 6377 pattern matches distributed across 19 syntactic categories. The overall adjusted score of 6.5 places this repository in the Low 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).

6.5
Adjusted Score
6.5
Raw Score
100%
Time Factor
2026-07-14
Last Push
10.1K
Stars
C++
Language
1.6M
Lines of Code
4.5K
Files
6.4K
Pattern Hits
2026-07-14
Scan Date
0.13
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 0HIGH 596MEDIUM 984LOW 4797

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 6377 distinct pattern matches across 19 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.

Cross-File Repetition573 hits · 2865 pts
SeverityFileLineSnippetContext
HIGHtest/python/cutlass/conv2d/conv2d_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_mixed_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f16_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f64_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f64_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f16_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_s8_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f32_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_s8_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f8_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHoperators/cutlass/operators/fusion/ir/compute_nodes.py0load node loads tensor under type `tensor.element` and returns an array of type `tensor.element`.STRING
HIGHoperators/cutlass/operators/fusion/ir/load_nodes.py0load node loads tensor under type `tensor.element` and returns an array of type `tensor.element`.STRING
HIGHpython/cutlass_cppgen/backend/evt/ir/compute_nodes.py0load node loads tensor under type `tensor.element` and returns an array of type `tensor.element`.STRING
HIGHpython/cutlass_cppgen/backend/evt/ir/load_nodes.py0load node loads tensor under type `tensor.element` and returns an array of type `tensor.element`.STRING
HIGH…rators/cutlass/operators/fusion/backend/sm100_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxload< {self.descriptor}::stages, typename {self.descriptor}:STRING
HIGH…erators/cutlass/operators/fusion/backend/sm90_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxload< {self.descriptor}::stages, typename {self.descriptor}:STRING
HIGH…thon/cutlass_cppgen/backend/evt/backend/sm100_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxload< {self.descriptor}::stages, typename {self.descriptor}:STRING
HIGHpython/cutlass_cppgen/backend/evt/backend/sm90_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxload< {self.descriptor}::stages, typename {self.descriptor}:STRING
HIGH…rators/cutlass/operators/fusion/backend/sm100_nodes.py0get the shared memory size based on epilogue_tile_mn, stages_c, and stages_dSTRING
HIGH…erators/cutlass/operators/fusion/backend/sm90_nodes.py0get the shared memory size based on epilogue_tile_mn, stages_c, and stages_dSTRING
HIGH…thon/cutlass_cppgen/backend/evt/backend/sm100_nodes.py0get the shared memory size based on epilogue_tile_mn, stages_c, and stages_dSTRING
HIGHpython/cutlass_cppgen/backend/evt/backend/sm90_nodes.py0get the shared memory size based on epilogue_tile_mn, stages_c, and stages_dSTRING
HIGH…rators/cutlass/operators/fusion/backend/sm100_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxstore< {self.descriptor}::stages, typename {self.descriptor}STRING
HIGH…erators/cutlass/operators/fusion/backend/sm90_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxstore< {self.descriptor}::stages, typename {self.descriptor}STRING
HIGH…thon/cutlass_cppgen/backend/evt/backend/sm100_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxstore< {self.descriptor}::stages, typename {self.descriptor}STRING
HIGHpython/cutlass_cppgen/backend/evt/backend/sm90_nodes.py0using {self.name_camel} = cutlass::epilogue::fusion::sm90auxstore< {self.descriptor}::stages, typename {self.descriptor}STRING
HIGH…/providers/cutedsl/gemm/sm100_static_persistent_efc.py0generator that yields all valid gemmoperandsmetadata that correspond to `args` and that are supported by this operator. STRING
HIGH…ators/providers/cutedsl/gemm/sm90_static_persistent.py0generator that yields all valid gemmoperandsmetadata that correspond to `args` and that are supported by this operator. STRING
HIGH…edsl/gemm/sm100_dense_blockscaled_static_persistent.py0generator that yields all valid gemmoperandsmetadata that correspond to `args` and that are supported by this operator. STRING
HIGH…s/operators/providers/cutedsl/gemm/sm100_persistent.py0generator that yields all valid gemmoperandsmetadata that correspond to `args` and that are supported by this operator. STRING
HIGH…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py0generator that yields all valid gemmoperandsmetadata that correspond to `args` and that are supported by this operator. STRING
HIGH…/operators/providers/cutedsl/gemm/sm100_mixed_input.py0generator that yields all valid gemmoperandsmetadata that correspond to `args` and that are supported by this operator. STRING
HIGH…/providers/cutedsl/gemm/sm100_static_persistent_efc.py0generator that yields all valid gemmoperandsmetadata combinations based on the validation rules in _valid_operands.STRING
HIGH…ators/providers/cutedsl/gemm/sm90_static_persistent.py0generator that yields all valid gemmoperandsmetadata combinations based on the validation rules in _valid_operands.STRING
HIGH…s/operators/providers/cutedsl/gemm/sm100_persistent.py0generator that yields all valid gemmoperandsmetadata combinations based on the validation rules in _valid_operands.STRING
HIGH…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py0generator that yields all valid gemmoperandsmetadata combinations based on the validation rules in _valid_operands.STRING
HIGH…/providers/cutedsl/gemm/sm100_static_persistent_efc.py0returns a list of all possible configurations of sm80tensoropgemmoperator that adhere to constraints passed in under kwaSTRING
HIGH…ators/providers/cutedsl/gemm/sm90_static_persistent.py0returns a list of all possible configurations of sm80tensoropgemmoperator that adhere to constraints passed in under kwaSTRING
HIGH…edsl/gemm/sm100_dense_blockscaled_static_persistent.py0returns a list of all possible configurations of sm80tensoropgemmoperator that adhere to constraints passed in under kwaSTRING
HIGH…s/operators/providers/cutedsl/gemm/sm100_persistent.py0returns a list of all possible configurations of sm80tensoropgemmoperator that adhere to constraints passed in under kwaSTRING
HIGH…utedsl/gemm/sm100_contiguous_offset_2d3d_dense_gemm.py0returns a list of all possible configurations of sm80tensoropgemmoperator that adhere to constraints passed in under kwaSTRING
HIGH…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py0returns a list of all possible configurations of sm80tensoropgemmoperator that adhere to constraints passed in under kwaSTRING
HIGH…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py0initializes the staticpersistenttilescheduler with the given parameters. :param params: tile schedule related params, inSTRING
HIGH…rs/providers/cutedsl/gemm/implementations/scheduler.py0initializes the staticpersistenttilescheduler with the given parameters. :param params: tile schedule related params, inSTRING
HIGH…eDSL/cutlass/utils/static_persistent_tile_scheduler.py0initializes the staticpersistenttilescheduler with the given parameters. :param params: tile schedule related params, inSTRING
HIGH…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py0initialize the static persistent tile scheduler. :param params: parameters for the persistent tile scheduler. :type paraSTRING
HIGH…rs/providers/cutedsl/gemm/implementations/scheduler.py0initialize the static persistent tile scheduler. :param params: parameters for the persistent tile scheduler. :type paraSTRING
HIGH…eDSL/cutlass/utils/static_persistent_tile_scheduler.py0initialize the static persistent tile scheduler. :param params: parameters for the persistent tile scheduler. :type paraSTRING
HIGH…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py0compute current tile coord given current_work_linear_idx and cta_id_in_cluster. :param current_work_linear_idx: the lineSTRING
HIGH…rs/providers/cutedsl/gemm/implementations/scheduler.py0compute current tile coord given current_work_linear_idx and cta_id_in_cluster. :param current_work_linear_idx: the lineSTRING
HIGH…eDSL/cutlass/utils/static_persistent_tile_scheduler.py0compute current tile coord given current_work_linear_idx and cta_id_in_cluster. :param current_work_linear_idx: the lineSTRING
HIGH…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py0initializes the configuration for a blackwell blockwise dense gemm kernel. this configuration includes several key aspecSTRING
HIGH…/kernel/dense_gemm/dense_gemm_alpha_beta_persistent.py0initializes the configuration for a blackwell blockwise dense gemm kernel. this configuration includes several key aspecSTRING
HIGH…cute/blackwell/kernel/blockwise_gemm/blockwise_gemm.py0initializes the configuration for a blackwell blockwise dense gemm kernel. this configuration includes several key aspecSTRING
HIGH…blackwell/kernel/blockwise_gemm/masked_grouped_gemm.py0initializes the configuration for a blackwell blockwise dense gemm kernel. this configuration includes several key aspecSTRING
HIGH…kwell/kernel/blockwise_gemm/contiguous_grouped_gemm.py0initializes the configuration for a blackwell blockwise dense gemm kernel. this configuration includes several key aspecSTRING
HIGH…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py0set up configurations that are dependent on gemm inputs this method configures various attributes based on the input tenSTRING
HIGH…/cutedsl/gemm/implementations/sm100_persistent_impl.py0set up configurations that are dependent on gemm inputs this method configures various attributes based on the input tenSTRING
HIGH…ell/kernel/dense_gemm/dense_gemm_persistent_dynamic.py0set up configurations that are dependent on gemm inputs this method configures various attributes based on the input tenSTRING
HIGH…well/kernel/dense_gemm/dense_gemm_software_pipeline.py0set up configurations that are dependent on gemm inputs this method configures various attributes based on the input tenSTRING
513 more matches not shown…
Decorative Section Separators764 hits · 2230 pts
SeverityFileLineSnippetContext
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py60# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py62# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py69# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py71# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py161# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py163# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py181# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py183# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py205# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py207# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py224# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py226# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py243# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py245# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py264# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py266# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py289# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py291# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py309# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py311# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py329# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py331# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py349# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py351# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py368# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py371# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py65# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py67# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py194# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py196# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py215# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py217# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py241# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py243# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py293# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py295# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py332# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py334# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py365# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py367# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py392# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py394# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py410# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py412# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py434# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py436# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py457# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py459# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py531# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py533# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py567# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py569# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py592# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py594# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py90# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py92# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py182# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py184# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py226# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py228# ---------------------------------------------------------------------------COMMENT
704 more matches not shown…
Over-Commented Block1764 hits · 1737 pts
SeverityFileLineSnippetContext
LOWCMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWCMakeLists.txt421# ASAN_OPTIONS=protect_shadow_gap=0:replace_intrin=0:detect_leaks=0COMMENT
LOWCMakeLists.txt861file(MAKE_DIRECTORY "${CMAKE_BINARY_DIR}/${CMAKE_INSTALL_BINDIR}")COMMENT
LOWtools/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/util/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/util/include/cutlass/util/print_error.hpp41#include <cute/tensor.hpp>COMMENT
LOWtools/util/include/cutlass/util/cublas_wrappers.hpp41# define BLAM_DEBUG_OUT(msg) std::cerr << "BLAM: " << msg << std::endlCOMMENT
LOW…l/include/cutlass/util/reference/host/rank_k_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…lude/cutlass/util/reference/host/gemm_planar_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…util/include/cutlass/util/reference/host/convolution.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…til/include/cutlass/util/reference/host/symm_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…til/include/cutlass/util/reference/host/gemm_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…/include/cutlass/util/reference/host/tensor_reduce.hpp41COMMENT
LOW…il/include/cutlass/util/reference/host/tensor_fill.hpp41COMMENT
LOW…include/cutlass/util/reference/host/tensor_compare.hpp41COMMENT
LOW…util/include/cutlass/util/reference/host/tensor_fill.h41#include <random>COMMENT
LOW…/include/cutlass/util/reference/host/rank_2k_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOWtools/util/include/cutlass/util/reference/device/gemm.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…il/include/cutlass/util/reference/device/convolution.h41#include "cutlass/matrix_shape.h"COMMENT
LOW…l/include/cutlass/util/reference/device/gemm_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…il/include/cutlass/util/reference/device/tensor_fill.h41COMMENT
LOWtools/util/scripts/split_test_cmake.py1#################################################################################################COMMENT
LOWtools/util/scripts/split_test_cmake.py21# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THECOMMENT
LOWtools/library/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/library/include/cutlass/library/library.h41COMMENT
LOWtools/library/include/cutlass/library/library.h61#include "cutlass/tensor_coord.h"COMMENT
LOWtools/library/src/conv_operation_3x.hpp501 // Convolutions split the metadata (in Conv2dConfiguration) fromCOMMENT
LOWtools/library/src/conv_operation_3x.hpp741 else {COMMENT
LOWtools/library/src/conv_operation_3x.hpp841 if (num_groups != 1) {COMMENT
LOWtools/library/src/conv2d_operation.h41#include "cutlass/conv/kernel/default_conv2d_dgrad.h"COMMENT
LOWtools/library/src/sparse_gemm_operation_3x.hpp41#include "cutlass/library/library.h"COMMENT
LOWtools/library/src/gemm_operation_3x.hpp41#include "cutlass/library/library.h"COMMENT
LOW…ary/src/reference/blockwise_gemm_reference_operation.h41#include <cstring>COMMENT
LOWtools/profiler/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/profiler/include/cutlass/profiler/debug.h41COMMENT
LOW…r/include/cutlass/profiler/conv2d_operation_profiler.h41#include <algorithm>COMMENT
LOWtools/profiler/include/cutlass/profiler/options.h221COMMENT
LOW…lude/cutlass/profiler/sparse_gemm_operation_profiler.h41#include <algorithm>COMMENT
LOW…ler/include/cutlass/profiler/symm_operation_profiler.h41#include <memory>COMMENT
LOW…e/cutlass/profiler/blockwise_gemm_operation_profiler.h41#include <memory>COMMENT
LOW…ler/include/cutlass/profiler/trmm_operation_profiler.h41#include <memory>COMMENT
LOW…nclude/cutlass/profiler/reduction_operation_profiler.h41#include <algorithm>COMMENT
LOW…/include/cutlass/profiler/rank_2k_operation_profiler.h41#include <memory>COMMENT
LOW…utlass/profiler/block_scaled_gemm_operation_profiler.h41#include <string>COMMENT
LOW…profiler/include/cutlass/profiler/operation_profiler.h41COMMENT
LOW…ler/include/cutlass/profiler/gemm_operation_profiler.h41#include <algorithm>COMMENT
LOW…r/include/cutlass/profiler/conv3d_operation_profiler.h41#include <algorithm>COMMENT
LOW…r/include/cutlass/profiler/rank_k_operation_profiler.h41#include <memory>COMMENT
LOW…ude/cutlass/profiler/grouped_gemm_operation_profiler.h41#include <unordered_map>COMMENT
LOWtools/profiler/src/performance_report.cpp41#include "cutlass/library/util.h"COMMENT
LOWtools/profiler/src/cudnn_helpers.cpp241 if(a_tensor.element != b_tensor.element) {COMMENT
LOWtools/profiler/src/cudnn_helpers.cpp381 // where; div_up(a, b) : (a - 1)/b + 1 //COMMENT
LOWtest/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/self_contained_includes/CMakeLists.txt1# Copyright (c) 2024 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/self_contained_includes/CMakeLists.txt21# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLECOMMENT
LOWtest/self_contained_includes/CMakeLists.txt221 # cutlass/archCOMMENT
LOWtest/unit/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/unit/pipeline/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/unit/pipeline/testbed_cluster_launch_control.h41 #define CUTLASS_UNIT_TEST_PIPELINE trueCOMMENT
LOWtest/unit/pipeline/testbed.h41#include "cutlass/util/command_line.h"COMMENT
1704 more matches not shown…
Unused Imports1215 hits · 1018 pts
SeverityFileLineSnippetContext
LOWtest/python/pycute/test_coalesce.py40CODE
LOWtest/python/pycute/test_left_inverse.py40CODE
LOWtest/python/pycute/test_complement.py40CODE
LOWtest/python/pycute/test_int_tuple.py39CODE
LOWtest/python/pycute/test_typing.py39CODE
LOWtest/python/pycute/test_composition.py40CODE
LOWtest/python/pycute/test_right_inverse.py40CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py24CODE
LOWtest/python/cutlass/interface/gemm_interface.py37CODE
LOWtest/python/cutlass/interface/conv2d_interface.py37CODE
LOWtest/python/cutlass/evt/evt_layout_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_layout_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_compute_sm80_90.py40CODE
LOWtest/python/cutlass/evt/evt_compute_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_compute_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_load_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_load_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_store_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_store_sm80_90.py42CODE
LOWtest/python/cutlass/conv2d/conv2d_sm80.py43CODE
LOWtest/python/cutlass/conv2d/conv2d_problem_sizes.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py55CODE
LOWtest/python/cutlass/gemm/gemm_batched.py37CODE
LOWtest/python/cutlass/gemm/gemm_batched.py43CODE
LOWtest/python/cutlass/gemm/gemm_batched.py46CODE
LOWtest/python/cutlass/gemm/utils.py36CODE
LOWtest/python/cutlass/gemm/utils.py45CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py34CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py35CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py36CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py40CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py51CODE
LOWtest/examples/CuTeDSL/conftest.py53CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py34CODE
LOWtest/examples/CuTeDSL/test_math.py29CODE
LOWtest/examples/CuTeDSL/test_math.py32CODE
LOWoperators/test/conftest.py32CODE
LOWoperators/test/unit/test_manifest.py33CODE
LOWoperators/test/test_utils/gemm.py37CODE
LOWoperators/test/test_utils/__init__.py29CODE
LOWoperators/test/test_utils/__init__.py29CODE
LOWoperators/test/test_utils/__init__.py30CODE
LOWoperators/test/test_utils/__init__.py30CODE
LOWoperators/test/test_utils/__init__.py30CODE
LOWoperators/test/test_utils/__init__.py31CODE
LOWoperators/test/test_utils/common.py29CODE
LOWoperators/test/test_utils/allocation.py45CODE
LOWoperators/test/test_utils/allocation.py45CODE
LOWoperators/test/test_utils/allocation.py46CODE
LOWoperators/test/test_utils/reference_check.py29CODE
LOWoperators/cutlass/operators/artifact.py29CODE
LOWoperators/cutlass/operators/manifest.py29CODE
LOWoperators/cutlass/operators/arch.py29CODE
1155 more matches not shown…
Hyper-Verbose Identifiers944 hits · 916 pts
SeverityFileLineSnippetContext
LOWtest/python/pycute/test_right_inverse.py46 def helper_test_right_inverse(self, layout):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py48 def test_get_tensor_inside_dynamic_if(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py70 def test_struct_use_outside_if_still_works(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py91 def test_nested_struct_inside_dynamic_if(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py137 def test_if_elif_else_warp_spec_pattern(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py166 def test_struct_captured_in_while_body(self):CODE
LOWtest/python/cutlass/installation.py45 def test_cutlass_source_paths(self):CODE
LOWtest/python/cutlass/interface/evt_interface.py92 def test_too_much_shared_memory(self):CODE
LOWtest/python/cutlass/interface/evt_interface.py96 def evt_too_much_shared_memory(accum, C1, C2, C3, C4, C5, C6, C7, C8):CODE
LOWtest/python/cutlass/interface/evt_interface.py175 def test_missing_example_tensor(self):CODE
LOWtest/python/cutlass/interface/evt_interface.py179 def evt_missing_example_tensor(accum, C):CODE
LOWtest/python/cutlass/interface/gemm_interface.py237 def test_tensorop_availability(self):CODE
LOWtest/python/cutlass/interface/gemm_interface.py272 def test_invalid_tile_description(self):CODE
LOWtest/python/cutlass/interface/conv2d_interface.py268 def test_invalid_tile_description(self):CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py53 def test_same_variable_used_multiple_times(self):CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py193 def test_mixed_dag_partition_k(self):CODE
LOWtest/utils/test_sharding.py245def pytest_collection_modifyitems(config, items):CODE
LOWtest/utils/test_sharding.py465def pytest_runtest_makereport(item, call):CODE
LOWtest/utils/test_sharding.py498def pytest_report_collectionfinish(config, start_path, items):CODE
LOWtest/examples/CuTeDSL/test_for_control_flow.py41def _for_loop_carried_reused_target_kernel(out: cute.Tensor, n: cutlass.Int32):CODE
LOWtest/examples/CuTeDSL/test_for_control_flow.py53def _for_loop_carried_reused_target_host(out: cute.Tensor, n: cutlass.Int32):CODE
LOWtest/examples/CuTeDSL/test_for_control_flow.py60def test_for_loop_carried_var_with_reused_loop_target():CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py50def _test_empty_dataclass_kernel(out: cute.Tensor, tag: A | B):CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py61def _test_empty_dataclass_host(out: cute.Tensor, tag: A | B):CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py66def test_empty_dataclass_union(tag, expected):CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py129def test_grouped_blockscaled_gemm(CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py166def test_grouped_blockscaled_gemm_large_persistent_repro():CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py199def test_invalid_dtypes_and_sf_vec_size(CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py283def test_invalid_mma_tiler_and_cluster_shape(CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py319def test_invalid_tensor_alignment(problem_sizes_mnkl: List[Tuple[int, int, int, int]]):CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py364def test_batch_dimension_not_one():CODE
LOWtest/examples/CuTeDSL/sm_100a/test_rmsnorm.py89 def test_rmsnorm_without_weight(self, N):CODE
LOWtest/examples/CuTeDSL/sm_100a/test_rmsnorm.py110 def test_cluster_path_correctness(self, N):CODE
LOW…CuTeDSL/sm_100a/test_dense_gemm_persistent_prefetch.py222def test_prefetch_dist_configurations(prefetch_dist: Optional[int]):CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py169def test_dense_blockscaled_gemm_prefetch(CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py290def test_prefetch_dist_configurations(prefetch_dist: Optional[int]):CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py352def test_invalid_dtypes_and_scale_factor_vec_size(CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py427def test_invalid_mma_tiler_and_cluster_shape(CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py481def test_invalid_tensor_alignment(CODE
LOWoperators/test/conftest.py70def save_restore_global_options():CODE
LOWoperators/test/unit/test_reference_check.py112 def test_multiple_tensors_different_dtypes(self):CODE
LOWoperators/test/unit/test_reference_check.py146 def test_rtols_atols_expansion(self):CODE
LOWoperators/test/unit/test_reference_check.py161 def test_mismatched_dtype_raises(self):CODE
LOWoperators/test/unit/test_reference_check.py172 def test_wrong_number_of_tensors_raises(self):CODE
LOWoperators/test/unit/test_reference_check.py185 def test_wrong_number_of_rtols_raises(self):CODE
LOWoperators/test/unit/test_reference_check.py199 def test_wrong_number_of_atols_raises(self):CODE
LOWoperators/test/unit/test_reference_check.py213 def test_invalid_output_dtype_raises(self):CODE
LOWoperators/test/unit/test_reference_check.py269 def test_mismatched_tensor_types_raises(self):CODE
LOWoperators/test/unit/test_reference_check.py308 def test_none_rtols_atols_defaults(self):CODE
LOWoperators/test/unit/test_reference_check.py362 def test_clamp_mode_enum_clamp(self):CODE
LOWoperators/test/unit/test_reference_check.py372 def test_clamp_mode_enum_no_clamp(self):CODE
LOWoperators/test/unit/test_reference_check.py449 def test_clamp_mode_bool_true(self):CODE
LOWoperators/test/unit/test_reference_check.py457 def test_clamp_mode_bool_false(self):CODE
LOWoperators/test/unit/test_manifest.py76def hash_based_metadata_filter(metadata: ops.OperatorMetadata) -> bool:CODE
LOWoperators/test/unit/test_manifest.py112def test_get_operators_supports_invariant(CODE
LOWoperators/test/unit/test_manifest.py145def test_unsupported_target_sm_returns_no_operators():CODE
LOWoperators/test/unit/test_manifest.py152def test_all_unique_operator_names():CODE
LOWoperators/test/unit/test_provider.py72 def test_register_operator_class_with_supported_args_type(self):CODE
LOWoperators/test/unit/test_provider.py91 def test_generate_operators_filters_by_args_type(self):CODE
LOWoperators/test/unit/test_provider.py126 def test_generate_operators_returns_all_when_args_type_is_none(self):CODE
884 more matches not shown…
Self-Referential Comments158 hits · 355 pts
SeverityFileLineSnippetContext
MEDIUMtest/python/cutlass/evt/utils/evt_testbed.py108 # Create the Gemm planCOMMENT
MEDIUMtest/python/cutlass/conv2d/conv2d_test_utils.py347 # Create the planCOMMENT
MEDIUMoperators/test/integration/test_cuda_graph.py91 # Create a CUDA Graph to run our compiled Operator N timesCOMMENT
MEDIUMoperators/cutlass/operators/fusion/__init__.py69 # Define the example tensorsSTRING
MEDIUM…rators/cutlass/operators/fusion/frontend/python_ast.py152 # Create the assign nodeCOMMENT
MEDIUMoperators/cutlass/operators/fusion/ir/c_types.py159 # Create the ctype tupleCOMMENT
MEDIUM…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py136 # Create the subgraphCOMMENT
MEDIUM…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py149 # Create the fused nodeCOMMENT
MEDIUM…/cutlass/operators/providers/cutedsl/evt/common_efc.py156 # Create a new signature with the custom parameter namesCOMMENT
MEDIUM…/cutlass/operators/providers/cutedsl/evt/common_efc.py159 # Create a wrapper function that accepts arguments according to the new signatureCOMMENT
MEDIUM…/cutlass/operators/providers/cutedsl/evt/common_efc.py991 # The following functions are executed by the specialized warps forCOMMENT
MEDIUM…/cutlass/operators/providers/cutedsl/evt/common_efc.py1302 # The following functions are executed by the specialized warp for theCOMMENT
MEDIUM…/cutlass/operators/providers/cutedsl/evt/common_efc.py2095 # Create the metaprogramming objects for the @cute.jit and @cute.kernelCOMMENT
MEDIUM…s/operators/providers/cutedsl/gemm/sm100_persistent.py80 """This class implements batched matrix multiplication (C = A @ B) with support for various data typesSTRING
MEDIUM…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py68 """This class implements batched matrix multiplication (C = A @ B)STRING
MEDIUM…rs/cutedsl/gemm/implementations/sm100_tgv_gemm_impl.py1020 # Create the local tile of coordC, same tiling as gCCOMMENT
MEDIUM…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py162 # Create a copy atom for a global to shared memory asynchronous copyCOMMENT
MEDIUM…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py520 # Create the copy atoms for the copy from shared memory to registerCOMMENT
MEDIUM…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py223 """This class implements batched matrix multiplication (C = A * B) with support for fp8 (e4m3fn, e5m2)STRING
MEDIUM…ions/sm100_dense_blockscaled_static_persistent_impl.py120 """This class implements batched matrix multiplication (C = A x SFA x B x SFB) with support for various data typesSTRING
MEDIUM…mm/implementations/sm100_static_persistent_efc_impl.py938 # Create the local_tile gX_mnl for all the EFC supplemental tensors.COMMENT
MEDIUM…mm/implementations/sm100_static_persistent_efc_impl.py1392 # Create the tiled tensors to be loaded in the epilogue.COMMENT
MEDIUMpython/cutlass_cppgen/backend/c_types.py538 # Create the ctype tupleCOMMENT
MEDIUMpython/cutlass_cppgen/backend/compiler.py143 # Create the table if it does not already existSTRING
MEDIUMpython/cutlass_cppgen/backend/library.py52# The following block implements enum.auto() for Python 3.5 variants that don't include it suchCOMMENT
MEDIUM…thon/cutlass_cppgen/backend/evt/frontend/python_ast.py146 # Create the assign nodeCOMMENT
MEDIUM…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py134 # Create the subgraphCOMMENT
MEDIUM…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py146 # Create the fused nodeCOMMENT
MEDIUMpython/cutlass_cppgen/epilogue/epilogue.py134 # Define the example tensorsSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py5257 # Create the mask of the imageCOMMENT
MEDIUMpython/CuTeDSL/cutlass/cute/core.py5926 # Create a dictionary to store the offsetsCOMMENT
MEDIUMpython/CuTeDSL/cutlass/cute/core.py6140 # Create a dictionary to store the offsets (all zeros for union)COMMENT
MEDIUMpython/CuTeDSL/cutlass/cute/core.py752 # Create a scaled basis with integer scale and modeSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py755 # Create a scaled basis with a Ratio scaleSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py758 # Create a scaled basis with a list of modesSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py954 # Create a basis element for the first dimension (mode 0)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py957 # Create a basis element for the second dimension (mode 1)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py960 # Create a basis element for a hierarchical dimensionSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3644 # Create a 2D compact left-most layout with shape (4,4)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3647 # Create a left-most layout with custom stridesSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3650 # Create a layout for a 3D tensorSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3653 # Create a layout with custom stridesSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3779 # Create a row-major layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3782 # Create a column-major layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3785 # Create a layout with custom dimension ordering for a 3D tensorSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py1157 # Creating a layout with shape (4,8) and default stride (layout left / "column major")STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py1160 # Creating a layout with explicit shape and strideSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py2809 tensor = make_tensor(...) # Create a 2D tensorSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3735 # Create a 2D identity layout with shape (4,4)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3738 # Create a 3D identity layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3927 # Create a basic layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3931 # Create a composed layout with an offsetSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4277 # Create a layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4531 # Create a layout that maps (i,j) to i*4 + jSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4533 # Create a layout that maps (i,j) to i*3 + jSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4585 # Create a right-major layout for a 4x4 matrixSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4587 # Create a left-major layout that complements the row layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py6091 # Define a union with scalar int/float elements:STRING
MEDIUMpython/CuTeDSL/cutlass/cute/runtime.py302 # Create a tensor from a numpy arraySTRING
MEDIUMpython/CuTeDSL/cutlass/cute/runtime.py306 # Create a tensor with Float32 elementsSTRING
98 more matches not shown…
Deep Nesting379 hits · 314 pts
SeverityFileLineSnippetContext
LOWtest/python/cutlass/interface/gemm_interface.py272CODE
LOWtest/python/cutlass/evt/utils/evt_testbed.py140CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py319CODE
LOWtest/utils/test_sharding.py245CODE
LOWtest/utils/test_sharding.py465CODE
LOWtest/examples/CuTeDSL/conftest.py126CODE
LOWoperators/test/test_utils/reference_check.py270CODE
LOWoperators/cutlass/operators/mma.py101CODE
LOWoperators/cutlass/operators/fusion/library.py338CODE
LOWoperators/cutlass/operators/fusion/library.py355CODE
LOWoperators/cutlass/operators/fusion/pycute/layout.py135CODE
LOWoperators/cutlass/operators/fusion/pycute/layout.py196CODE
LOWoperators/cutlass/operators/fusion/ir/store_nodes.py129CODE
LOWoperators/cutlass/operators/fusion/ir/c_types.py115CODE
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py87CODE
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py146CODE
LOWoperators/cutlass/operators/fusion/ir/layout_nodes.py259CODE
LOWoperators/cutlass/operators/fusion/ir/tensor.py58CODE
LOWoperators/cutlass/operators/fusion/ir/node.py213CODE
LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py55CODE
LOW…rators/cutlass/operators/fusion/passes/pass_manager.py159CODE
LOW…rators/cutlass/operators/fusion/passes/graph_drawer.py76CODE
LOW…s/cutlass/operators/providers/cutedsl/evt/converter.py203CODE
LOW…ers/cutedsl/gemm/sm100_persistent_preferred_cluster.py237CODE
LOW…ers/cutedsl/gemm/sm100_persistent_preferred_cluster.py373CODE
LOW…ers/cutedsl/gemm/sm100_persistent_preferred_cluster.py545CODE
LOW…/providers/cutedsl/gemm/sm100_static_persistent_efc.py309CODE
LOW…ators/providers/cutedsl/gemm/sm90_static_persistent.py151CODE
LOW…ators/providers/cutedsl/gemm/sm90_static_persistent.py264CODE
LOW…s/operators/providers/cutedsl/gemm/sm100_persistent.py169CODE
LOW…s/operators/providers/cutedsl/gemm/sm100_persistent.py299CODE
LOW…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py201CODE
LOW…/operators/providers/cutedsl/gemm/sm100_mixed_input.py692CODE
LOW…rs/cutedsl/gemm/implementations/sm100_tgv_gemm_impl.py273CODE
LOW…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py255CODE
LOW…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py651CODE
LOW…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py1825CODE
LOW…ions/sm100_dense_blockscaled_static_persistent_impl.py718CODE
LOW…sl/gemm/implementations/sm90_static_persistent_impl.py358CODE
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py1037CODE
LOW…ementations/sm100_persistent_preferred_cluster_impl.py434CODE
LOW…mm/implementations/sm100_static_persistent_efc_impl.py732CODE
LOW…/cutedsl/gemm/implementations/sm100_persistent_impl.py554CODE
LOWoperators/cutlass/operators/utils/tensor.py293CODE
LOWoperators/cutlass/operators/utils/tensor.py447CODE
LOWoperators/cutlass/operators/arguments/base.py99CODE
LOWpython/cutlass_cppgen/library_defaults.py109CODE
LOWpython/cutlass_cppgen/library_defaults.py236CODE
LOWpython/cutlass_cppgen/op/conv.py479CODE
LOWpython/cutlass_cppgen/op/conv.py506CODE
LOWpython/cutlass_cppgen/utils/datatypes.py84CODE
LOWpython/cutlass_cppgen/utils/datatypes.py131CODE
LOWpython/cutlass_cppgen/backend/c_types.py497CODE
LOWpython/cutlass_cppgen/backend/compiler.py186CODE
LOWpython/cutlass_cppgen/backend/compiler.py358CODE
LOWpython/cutlass_cppgen/backend/reduction_operation.py198CODE
LOWpython/cutlass_cppgen/backend/arguments.py79CODE
LOWpython/cutlass_cppgen/backend/arguments.py120CODE
LOWpython/cutlass_cppgen/backend/evt/ir/store_nodes.py134CODE
LOW…thon/cutlass_cppgen/backend/evt/ir/layout_algorithm.py72CODE
319 more matches not shown…
Redundant / Tautological Comments106 hits · 156 pts
SeverityFileLineSnippetContext
LOWtest/utils/test_sharding.py429 # Assign markers to each subtestCOMMENT
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py310 # Check if this configuration can be implementedCOMMENT
LOW…/operators/providers/cutedsl/gemm/sm100_mixed_input.py267 # Check if A is K-major (last dimension contiguous)COMMENT
LOW…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py499 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…ementations/sm100_persistent_preferred_cluster_impl.py253 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…mm/implementations/sm100_static_persistent_efc_impl.py644 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…/cutedsl/gemm/implementations/sm100_persistent_impl.py440 # Check if input data types are compatible with MMA instructionCOMMENT
LOWpython/cutlass_cppgen/op/conv.py473 # Check if the iterator algorithm is validCOMMENT
LOWpython/CuTeDSL/setup.sh81 # Check if CUTLASS_IR_BUILD_DIR is setCOMMENT
LOWpython/CuTeDSL/setup.sh120 # Check if requirements file existsCOMMENT
LOWpython/CuTeDSL/prep_editable_install.py118 # Check if version already has .dev<n> patternCOMMENT
LOWpython/CuTeDSL/_mlir_helpers/vector.py325 # Check if all indices are static (Python ints)COMMENT
LOWpython/CuTeDSL/_mlir_helpers/op.py332 # Check if it's a decorator config error firstCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py172 # Check if test was explicitly selected like ::test_name[param1-param2-...]COMMENT
LOWpython/CuTeDSL/cutlass/pipeline/sm100.py714 # Set mask to None if not using clusters (i.e. 1CTA kernels)COMMENT
LOWpython/CuTeDSL/cutlass/pipeline/sm100.py722 # Set mask to None if not using 2CTA instructionsCOMMENT
LOWpython/CuTeDSL/cutlass/cute/tuple.py475 # Check if first argument is a tuple to determine behaviorCOMMENT
LOWpython/CuTeDSL/cutlass/cute/arch/nvvm_wrappers.py188 # Check if user passed an enum (should be a string literal instead)COMMENT
LOWpython/CuTeDSL/cutlass/cute/arch/nvvm_wrappers.py2653 # Check if it's a floating-point vector typeCOMMENT
LOWpython/CuTeDSL/cutlass/utils/block.py68 # Check if required arguments are providedCOMMENT
LOWpython/CuTeDSL/cutlass/utils/mixed_input_helpers.py753 # Check if scale tensor matches the TMA load 128B alignment requirementCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2451 # Check if all non-default arguments are providedCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/env_manager.py424 # Check if the environment variable is already set, if so, return it immediately.COMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py1998 # Check if argument is Numeric, if so, call ir_value()COMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py2111 # Check if all keywords are known DSL kwargsCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py2116 # Check if 'preprocess' is explicitly setCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/common.py80 # Check if show_stacktrace is enabled via registered env managerCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/common.py88 # Check if it's a DSL operation error (by name to avoid circular import issues)COMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/common.py684 # Check if cause is also a DSLOperationErrorCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/leaf_utils.py317 # Check if this is an assignable leafCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py320 # Check if we successfully got the compute capabilityCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py449 # Check if a valid CUDA context already exists (e.g., created by PyTorch orCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py31 # Check if we are at the root directoryCOMMENT
LOW…TeDSL/cutlass/base_dsl/tvm_ffi_builder/mlir_builder.py249 # Check if align_const is a power of twoCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py929 # Check if the function already existsCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py952 # Check if type is int or bool (both use v_int64, bool can be converted to int)COMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1000 # Check if type is float, int, or bool (int and bool can be converted to float)COMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1106 # Check if type is opaque pointerCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1110 # Check if type is a nullptrCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1502 # Check if type is int or bool (both use v_int64, bool can be converted to int)COMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1581 # Check if type is ffi.Shape or ffi.ArrayCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1758 # Check if data pointer is divisible by alignmentCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py2012 # Check if type is kTVMFFIArrayCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py736 # Check if function already exists in the moduleSTRING
LOWpython/CuTeDSL/cutlass/cutlass_dsl/tvm_ffi_provider.py218 # Check if initialization failed (non-zero return code)COMMENT
LOWpython/CuTeDSL/cutlass/cutlass_dsl/tvm_ffi_provider.py302 # Check if call is successful (zero return code means success)COMMENT
LOWpython/CuTeDSL/cutlass/cutlass_dsl/tvm_ffi_provider.py326 # Check if devices are differentCOMMENT
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py2754 # Check if all values are non-zeroSTRING
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py2758 # Check if all conditions are metSTRING
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py2789 # Check if any value is non-zeroSTRING
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py2793 # Check if any condition is metSTRING
LOW…les/python/CuTeDSL/dsl_tutorials/cooperative_launch.py278 # Check if we're the last block to arriveCOMMENT
LOW…les/python/CuTeDSL/dsl_tutorials/cooperative_launch.py537 # Check if this is the leader block (first block in the grid)COMMENT
LOW…les/python/CuTeDSL/dsl_tutorials/cooperative_launch.py540 # Check if this is the leader thread (first thread in the block)COMMENT
LOW…TeDSL/cute/blackwell/efc/custom_epilogue_dense_gemm.py505 # Check if the configuration can be implemented. Raise a ValueErrorCOMMENT
LOW…/blackwell/efc/synthetic_custom_epilogue_dense_gemm.py279 # Check if configuration can be implementedCOMMENT
LOW…on/CuTeDSL/cute/blackwell/efc/common_dense_gemm_efc.py424 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…blackwell/efc/activation_custom_epilogue_dense_gemm.py616 # Check if the configuration can be implemented. Raise a ValueErrorCOMMENT
LOW…ell/kernel/dense_gemm/dense_gemm_persistent_dynamic.py500 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…ell/kernel/dense_gemm/dense_gemm_persistent_dynamic.py1902 # Check if configuration can be implementedCOMMENT
46 more matches not shown…
AI Slop Vocabulary58 hits · 142 pts
SeverityFileLineSnippetContext
LOWoperators/cutlass/operators/arch.py117 # For now, just return the supported instruction.COMMENT
LOW…/cutlass/operators/providers/cutedsl/evt/common_efc.py2035 # In the @cute.kernel context, just use the normal CuTeCOMMENT
MEDIUM…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py200 # if atom layout's N-mode is 1, to leverage the largest coalescedCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py601 # Here we just return the first instance of a concrete subclass.COMMENT
MEDIUMpython/CuTeDSL/cutlass/base_dsl/cache_helpers.py230 # use temp dir to be robust against program interruptionsCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py523 # For `from . import x`, module name is None, just use package nameCOMMENT
LOW…n/CuTeDSL/cutlass/base_dsl/runtime/jit_arg_adapters.py301 # If no registered adapter is found, just return the original elementCOMMENT
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py1460 # If fails, just return the original argCOMMENT
MEDIUMpython/cutlass_library/generator.py12557# to leverage the functionality in this file without running this script via a shell prompt.COMMENT
MEDIUMinclude/cutlass/gemm/kernel/tile_scheduler_params.h914 // the problem can leverage a basic split-K decomposition for the stream-K tiles.COMMENT
MEDIUM…cs/regular__tile__access__iterator__tensor__op_8h.html137<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…cs/regular__tile__access__iterator__tensor__op_8h.html146<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/host_2tensor__fill_8h_source.html101<a href="host_2tensor__fill_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><aCODE
MEDIUMdocs/annotated.html677<tr id="row_0_10_1_28_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html679<tr id="row_0_10_1_29_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html699<tr id="row_0_10_1_48_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html701<tr id="row_0_10_1_49_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html703<tr id="row_0_10_1_50_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html705<tr id="row_0_10_1_51_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html707<tr id="row_0_10_1_52_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;<CODE
MEDIUMdocs/annotated.html716<tr id="row_0_10_7_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</spCODE
MEDIUMdocs/annotated.html718<tr id="row_0_10_8_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</spCODE
MEDIUMdocs/annotated.html720<tr id="row_0_10_9_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</spCODE
MEDIUM…___00_01Element__ebf4714349612673e8b6609b763eeb6f.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/hierarchy.html260<tr id="row_147_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><spaCODE
MEDIUMdocs/hierarchy.html261<tr id="row_148_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span classCODE
MEDIUMdocs/hierarchy.html262<tr id="row_149_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><spaCODE
MEDIUMdocs/hierarchy.html264<tr id="row_151_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><spaCODE
MEDIUMdocs/hierarchy.html265<tr id="row_152_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span classCODE
MEDIUMdocs/hierarchy.html266<tr id="row_153_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><spaCODE
MEDIUMdocs/hierarchy.html267<tr id="row_154_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span classCODE
MEDIUMdocs/hierarchy.html268<tr id="row_155_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><spaCODE
MEDIUMdocs/hierarchy.html269<tr id="row_156_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span classCODE
MEDIUMdocs/hierarchy.html270<tr id="row_157_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><spaCODE
MEDIUMdocs/device_2kernel_2tensor__elementwise_8h_source.html101<a href="device_2kernel_2tensor__elementwise_8h.html">Go to the documentation of this file.</a><div class="fragment"><diCODE
MEDIUMdocs/pitch__linear__thread__map_8h.html145<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/pitch__linear__thread__map_8h.html150<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/pitch__linear__thread__map_8h.html157<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…01Element___00_01efd5013a2503d6567e2bf6b40c97360c.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…s_1_1transform_1_1PitchLinearWarpStripedThreadMap.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…ass_1_1transform_1_1TransposePitchLinearThreadMap.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/device_2tensor__fill_8h_source.html101<a href="device_2tensor__fill_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line">CODE
MEDIUM…ass_1_1transform_1_1PitchLinearWarpRakedThreadMap.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…01Element___00_0197fef2242a3454a7d1cebe61aee28b43.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…01Element___00_01a75d2cd74e722d6ad6a3b41aabfd432d.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/regular__tile__iterator__tensor__op__sm70_8h.html136<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/regular__tile__iterator__tensor__op__sm70_8h.html145<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/regular__tile__iterator__tensor__op__sm70_8h.html154<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…01Element___00_01dbd6b8468d5bd787308d2f615a24d123.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…01Element___00_01f96bbeb63e6d4ce4a2551279de3a9f0e.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/regular__tile__iterator__tensor__op_8h.html131<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMdocs/regular__tile__iterator__tensor__op_8h.html140<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUM…___00_01Element__e9a9e0f4286f652f55eb9b863b21effe.html115<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal details made public to facilitate CODE
MEDIUMexamples/python/CuTeDSL/dsl_tutorials/smem_allocator.py91 # Note: SMEM_SIZE bytes (specified in kernel().launch(smem=...)) can be reserved for developer to utilizeCOMMENT
LOW…amples/python/CuTeDSL/cute/blackwell/efc/common_efc.py1376 # In the @cute.kernel context, just use the normal CuTeCOMMENT
MEDIUM…CuTeDSL/cute/ampere/kernel/attention/hstu_attention.py43The example showcases an implementation of HSTU attention(https://arxiv.org/abs/2402.17152) within generative recommendeSTRING
MEDIUM…CuTeDSL/cute/ampere/kernel/dense_gemm/tensorop_gemm.py276 # if atom layout's N-mode is 1, to leverage the largest coalescedCOMMENT
MEDIUM…cute/blackwell_geforce/kernel/dense_gemm/dense_gemm.py254 # TODO: to leverage ldmatrix.x4, when self.atom_layout[1] is 1, mma tile is ((8x16)x2)COMMENT
Structural Annotation Overuse69 hits · 109 pts
SeverityFileLineSnippetContext
LOWoperators/cutlass/operators/fusion/ir/c_types.py188 # Step 1: convert the dtypeCOMMENT
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py154 # Step 1: Split the dimensions of the old layoutCOMMENT
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py262 # Step 2: Merge the splitted dimensions according to the new shapeCOMMENT
LOWoperators/cutlass/operators/fusion/ir/layout_nodes.py144 # Step 1: infer splitCOMMENT
LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py56 # Step 1: find the nodes that have multiple parentsCOMMENT
LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py62 # Step 2: find the lowest common ancestor (LCA) of all its parentsCOMMENT
LOW…cutlass/operators/fusion/passes/pass_preprocess_red.py51 # Step 1: find the compute nodes with op=redCOMMENT
LOW…cutlass/operators/fusion/passes/pass_preprocess_red.py63 # Step 2: for each compute, merge it with the succeeding storeCOMMENT
LOW…ass/operators/fusion/passes/pass_layout_elimination.py63 # Step 1: get the propagation directionCOMMENT
LOW…ators/cutlass/operators/fusion/backend/emitter_base.py78 # Step 1: emit individual node type declCOMMENT
LOW…ators/cutlass/operators/fusion/backend/emitter_base.py90 # Step 2: post-processing & get callback nameCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py374 # Step 1: Compute TMEM allocationsCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py385 # Step 2: Compute SMEM bytes per stageCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py404 # Step 3: Compute final stage countsCOMMENT
LOW…rs/providers/cutedsl/gemm/implementations/scheduler.py542 # Step 1: Handle persistent scheduling - map linear_idx to work_unit_idCOMMENT
LOW…rs/providers/cutedsl/gemm/implementations/scheduler.py547 # Step 2: Decode work_unit_id using FastDivmod objectsCOMMENT
LOWpython/cutlass_cppgen/backend/c_types.py566 # Step 1: convert the dtypeCOMMENT
LOW…thon/cutlass_cppgen/backend/evt/ir/layout_algorithm.py133 # Step 1: Split the dimensions of the old layoutCOMMENT
LOW…thon/cutlass_cppgen/backend/evt/ir/layout_algorithm.py229 # Step 2: Merge the splitted dimensions according to the new shapeCOMMENT
LOWpython/cutlass_cppgen/backend/evt/ir/layout_nodes.py144 # Step 1: infer splitCOMMENT
LOW…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py56 # Step 1: find the nodes that have multiple parentsCOMMENT
LOW…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py62 # Step 2: find the lowest common ancestor (LCA) of all its parentsCOMMENT
LOW…tlass_cppgen/backend/evt/passes/pass_preprocess_red.py51 # Step 1: find the compute nodes with op=redCOMMENT
LOW…tlass_cppgen/backend/evt/passes/pass_preprocess_red.py63 # Step 2: for each compute, merge it with the succeeding storeCOMMENT
LOW…s_cppgen/backend/evt/passes/pass_layout_elimination.py60 # Step 1: get the propagation directionCOMMENT
LOW…hon/cutlass_cppgen/backend/evt/backend/emitter_base.py78 # Step 1: emit individual node type declCOMMENT
LOW…hon/cutlass_cppgen/backend/evt/backend/emitter_base.py90 # Step 2: post-processing & get callback nameCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py532 # Step 1: Capture warmup graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py570 # Step 2: Capture profiling graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py594 # Step 3: Instantiate executable graphsCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py604 # Step 4: Execute warmup graph (cache warming)COMMENT
LOWpython/CuTeDSL/cutlass/testing.py610 # Step 5: Profile execution using selected profilerCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py622 # Step 6: Cleanup - Destroy graph executablesCOMMENT
LOW…eDSL/cutlass/utils/static_persistent_tile_scheduler.py584 # Step 1: Decode current_work_linear_idx using FastDivmod objectsCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py149 # Step 1: filter internal framesCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py152 # Step 2: consolidate duplicated framesCOMMENT
LOWpython/cutlass_library/sm100_utils.py90#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm100_utils.py56#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py106#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py406#### Step 3: map tile description to valid schedulesCOMMENT
LOWpython/cutlass_library/sm90_utils.py71#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py279#### Step 2: generate tile descriptions from math instruction shapesCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp576 // Step 1: reduce fragment input (Src) into tRS_rSrcCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp587 // Step 2: copy the partial results in tRS_rSrc to sRows in shared memoryCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp599 // Step 3: copy the partial results in sRows to tSR_sRow for reductionCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp613 // Step 4: atomically reduce the results to global memoryCOMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp341 /// Step 0: Step 1:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp559 /// Step 0: Step 1: Step 2: Step 3:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp569 /// Step 4: Step 5: Step 6: Step 7:COMMENT
LOW…/python/CuTeDSL/cute/blackwell/kernel/reduce/reduce.py503 # Step 1: Local reduction - each thread reduces its register valuesCOMMENT
LOW…/python/CuTeDSL/cute/blackwell/kernel/reduce/reduce.py512 # Step 2: Warp reductionCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py580 # Step 1: Transform PyTorch tensors to GEMM domain (fake MNKL)COMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py687 # Step 2: Infer dtypes and major modesCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py699 # Step 3: Setup kernel attributesCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py707 # Step 4: Create TMA atoms for A, B, SFA, SFB, CCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py786 # Step 5: offs_padded tensor (written by desc_init_kernel)COMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py803 # Step 6: Create MoEStaticSchedulerParams and compute gridCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py818 # Step 7: Launch desc_init_kernel (if separate_tensormap_init)COMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py849 # Step 8: Launch main kernelCOMMENT
LOW…/CuTeDSL/cute/blackwell/kernel/moe/torch_grouped_mm.py354 # Step 1: Transform PyTorch tensors to GEMM domain (fake MNKL)COMMENT
9 more matches not shown…
Verbosity Indicators66 hits · 103 pts
SeverityFileLineSnippetContext
LOWoperators/cutlass/operators/fusion/ir/c_types.py188 # Step 1: convert the dtypeCOMMENT
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py154 # Step 1: Split the dimensions of the old layoutCOMMENT
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py262 # Step 2: Merge the splitted dimensions according to the new shapeCOMMENT
LOWoperators/cutlass/operators/fusion/ir/layout_nodes.py144 # Step 1: infer splitCOMMENT
LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py56 # Step 1: find the nodes that have multiple parentsCOMMENT
LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py62 # Step 2: find the lowest common ancestor (LCA) of all its parentsCOMMENT
LOW…cutlass/operators/fusion/passes/pass_preprocess_red.py51 # Step 1: find the compute nodes with op=redCOMMENT
LOW…cutlass/operators/fusion/passes/pass_preprocess_red.py63 # Step 2: for each compute, merge it with the succeeding storeCOMMENT
LOW…ass/operators/fusion/passes/pass_layout_elimination.py63 # Step 1: get the propagation directionCOMMENT
LOW…ators/cutlass/operators/fusion/backend/emitter_base.py78 # Step 1: emit individual node type declCOMMENT
LOW…ators/cutlass/operators/fusion/backend/emitter_base.py90 # Step 2: post-processing & get callback nameCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py374 # Step 1: Compute TMEM allocationsCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py385 # Step 2: Compute SMEM bytes per stageCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py404 # Step 3: Compute final stage countsCOMMENT
LOW…rs/providers/cutedsl/gemm/implementations/scheduler.py542 # Step 1: Handle persistent scheduling - map linear_idx to work_unit_idCOMMENT
LOW…rs/providers/cutedsl/gemm/implementations/scheduler.py547 # Step 2: Decode work_unit_id using FastDivmod objectsCOMMENT
LOWpython/cutlass_cppgen/backend/c_types.py566 # Step 1: convert the dtypeCOMMENT
LOW…thon/cutlass_cppgen/backend/evt/ir/layout_algorithm.py133 # Step 1: Split the dimensions of the old layoutCOMMENT
LOW…thon/cutlass_cppgen/backend/evt/ir/layout_algorithm.py229 # Step 2: Merge the splitted dimensions according to the new shapeCOMMENT
LOWpython/cutlass_cppgen/backend/evt/ir/layout_nodes.py144 # Step 1: infer splitCOMMENT
LOW…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py56 # Step 1: find the nodes that have multiple parentsCOMMENT
LOW…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py62 # Step 2: find the lowest common ancestor (LCA) of all its parentsCOMMENT
LOW…tlass_cppgen/backend/evt/passes/pass_preprocess_red.py51 # Step 1: find the compute nodes with op=redCOMMENT
LOW…tlass_cppgen/backend/evt/passes/pass_preprocess_red.py63 # Step 2: for each compute, merge it with the succeeding storeCOMMENT
LOW…s_cppgen/backend/evt/passes/pass_layout_elimination.py60 # Step 1: get the propagation directionCOMMENT
LOW…hon/cutlass_cppgen/backend/evt/backend/emitter_base.py78 # Step 1: emit individual node type declCOMMENT
LOW…hon/cutlass_cppgen/backend/evt/backend/emitter_base.py90 # Step 2: post-processing & get callback nameCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py532 # Step 1: Capture warmup graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py570 # Step 2: Capture profiling graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py594 # Step 3: Instantiate executable graphsCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py604 # Step 4: Execute warmup graph (cache warming)COMMENT
LOWpython/CuTeDSL/cutlass/testing.py610 # Step 5: Profile execution using selected profilerCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py622 # Step 6: Cleanup - Destroy graph executablesCOMMENT
LOW…eDSL/cutlass/utils/static_persistent_tile_scheduler.py584 # Step 1: Decode current_work_linear_idx using FastDivmod objectsCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py149 # Step 1: filter internal framesCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py152 # Step 2: consolidate duplicated framesCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1405 # otherwise, it appears more than once, we need to check if the value matchesCOMMENT
LOWpython/cutlass_library/sm100_utils.py90#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm100_utils.py56#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py106#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py406#### Step 3: map tile description to valid schedulesCOMMENT
LOWpython/cutlass_library/sm90_utils.py71#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py279#### Step 2: generate tile descriptions from math instruction shapesCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp576 // Step 1: reduce fragment input (Src) into tRS_rSrcCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp587 // Step 2: copy the partial results in tRS_rSrc to sRows in shared memoryCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp599 // Step 3: copy the partial results in sRows to tSR_sRow for reductionCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp613 // Step 4: atomically reduce the results to global memoryCOMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp341 /// Step 0: Step 1:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp559 /// Step 0: Step 1: Step 2: Step 3:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp569 /// Step 4: Step 5: Step 6: Step 7:COMMENT
LOW…/python/CuTeDSL/cute/blackwell/kernel/reduce/reduce.py503 # Step 1: Local reduction - each thread reduces its register valuesCOMMENT
LOW…/python/CuTeDSL/cute/blackwell/kernel/reduce/reduce.py512 # Step 2: Warp reductionCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py580 # Step 1: Transform PyTorch tensors to GEMM domain (fake MNKL)COMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py687 # Step 2: Infer dtypes and major modesCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py699 # Step 3: Setup kernel attributesCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py707 # Step 4: Create TMA atoms for A, B, SFA, SFB, CCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py786 # Step 5: offs_padded tensor (written by desc_init_kernel)COMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py803 # Step 6: Create MoEStaticSchedulerParams and compute gridCOMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py818 # Step 7: Launch desc_init_kernel (if separate_tensormap_init)COMMENT
LOW…L/cute/blackwell/kernel/moe/torch_scaled_grouped_mm.py849 # Step 8: Launch main kernelCOMMENT
6 more matches not shown…
Docstring Block Structure18 hits · 90 pts
SeverityFileLineSnippetContext
HIGHoperators/test/test_utils/allocation.py151 Creates a RandomIntInitializationMode from the given datatypes. Range is determined based on the bitwiSTRING
HIGHoperators/test/test_utils/reference_check.py281 Asserts that the result tensor is similar to the reference tensor. This function automatically handles: - CSTRING
HIGHoperators/cutlass/operators/providers/provider.py118Register an Operator class with this provider. Intended to be used as a class decorator: .. code-blockSTRING
HIGHoperators/cutlass/operators/utils/device.py61Check whether ``result`` contains a CUDA error and raise it, otherwise return the rest. Args: result (list)STRING
HIGHoperators/cutlass/operators/utils/device.py114Return the target SM from environment variable ``env_var`` or device ``device``. The environment variable takes preSTRING
HIGHoperators/cutlass/operators/utils/device.py192Convert the provided stream to a ``cuda.bindings.driver.CUstream``. Args: stream (cuda.bindings.driver.CUstSTRING
HIGHoperators/cutlass/operators/utils/dtype.py92Convert a torch dtype to a cutlass dtype. Args: dtype (torch.dtype): The torch dtype to convert. ReturSTRING
HIGHoperators/cutlass/operators/utils/dtype.py187Convert a dtype to a cutlass dtype. Args: dtype (torch.dtype | jnp.dtype | np.dtype): The dtype to convert STRING
HIGHoperators/cutlass/operators/metadata/base.py117Check if the provided ``args``/``target_sm`` satisfy the properties described by this OperatorMetadata. Args: STRING
HIGHoperators/cutlass/operators/arguments/operand.py178Return the number of elements expected in :attr:`scale` for an operand of ``quantized_shape``. ``quantized_shapSTRING
HIGHoperators/cutlass/operators/arguments/operand.py373If operand is already a ``Operand``, return it. Otherwise, wrap it in a ``DenseTensor``. This is used for convenienSTRING
HIGHpython/CuTeDSL/prep_editable_install.py45 Download the nvidia-cutlass-dsl wheel to a temporary directory. Args: temp_dir: Temporary directory paSTRING
HIGHpython/CuTeDSL/prep_editable_install.py96 Extract version from wheel filename and convert to dev version. Args: wheel_path: Path to the wheel fiSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/ast_helpers.py473 Executes comparison operations with a left operand and a list of comparators. Args: left: The leftmostSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/ast_helpers.py741 Decomposes a joined f-string component list into a format string and dynamic arguments. This function takes a STRING
HIGHpython/CuTeDSL/cutlass/base_dsl/utils/tree_utils.py648 Flatten a nested structure into a flat list of values and a tree definition. This function recursively traversSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/utils/tree_utils.py744 Internal function to flatten a tree structure. This is the core implementation of tree flattening that handlesSTRING
HIGHpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py2186 Filter items based on whether corresponding iter_args are frozen dataclasses. This function filters items (whiSTRING
Excessive Try-Catch Wrapping88 hits · 86 pts
SeverityFileLineSnippetContext
LOW…ors/cutlass/operators/fusion/frontend/frontend_base.py223 except Exception as e:CODE
LOW…rators/cutlass/operators/fusion/frontend/python_ast.py111 except Exception as e:CODE
LOW…rators/cutlass/operators/fusion/frontend/python_ast.py197 except Exception as e:CODE
LOWoperators/cutlass/operators/utils/device.py165 except Exception as e:CODE
LOWoperators/cutlass/operators/utils/device.py245 except Exception as e:CODE
LOWpython/CuTeDSL/prep_editable_install.py160 except Exception as e:CODE
LOWpython/CuTeDSL/prep_editable_install.py268 except Exception as e:CODE
LOWpython/CuTeDSL/_mlir_helpers/vector.py158 except Exception:CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py331 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/__init__.py21 except Exception:CODE
LOWpython/CuTeDSL/cutlass/__init__.py31 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py581 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py585 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py273 except Exception as exc:CODE
LOWpython/CuTeDSL/cutlass/testing.py547 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py551 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py784 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/testing.py897 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/cute/metadata.py535 except Exception:CODE
LOWpython/CuTeDSL/cutlass/cute/runtime.py186 except Exception:CODE
LOWpython/CuTeDSL/cutlass/cute/testing.py730 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/utils/tmem_allocator.py83 except Exception:CODE
LOWpython/CuTeDSL/cutlass/utils/profiling.py187 except Exception:CODE
MEDIUMpython/CuTeDSL/cutlass/utils/profiling.py184def __del__(self) -> None:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/version_info.py20except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py1584 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py1753 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py1802 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2329 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2427 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/compiler.py143 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/cache_helpers.py82 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/cache_helpers.py286 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/cache_helpers.py326 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/env_manager.py235 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/env_manager.py474 except Exception as e:CODE
MEDIUMpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py470def get_session(self) -> Generator["DSLPreprocessor", None, None]:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py788 except Exception:CODE
MEDIUMpython/CuTeDSL/cutlass/base_dsl/diagnostics.py346def _load_diagnostic_bindings() -> Any | None:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/diagnostics.py214 except Exception: # noqa: BLE001 -- diagnostics must not break compileCODE
LOWpython/CuTeDSL/cutlass/base_dsl/diagnostics.py483 except Exception: # noqa: BLE001CODE
LOWpython/CuTeDSL/cutlass/base_dsl/diagnostics.py508 except Exception: # noqa: BLE001 -- best-effort columnCODE
LOWpython/CuTeDSL/cutlass/base_dsl/diagnostics.py640 except Exception: # noqa: BLE001CODE
MEDIUMpython/CuTeDSL/cutlass/base_dsl/jit_executor.py961def unload(self) -> None:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py701 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py813 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py966 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py1080 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py1447 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py1532 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py1606 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/jit_executor.py1614 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/common.py58 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/common.py361 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/typing.py2490 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/ffi.py662 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py343 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py346 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py468 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/utils/tree_utils.py186 except Exception:CODE
28 more matches not shown…
Modern Structural Boilerplate80 hits · 80 pts
SeverityFileLineSnippetContext
LOWoperators/test/test_utils/__init__.py33__all__ = [CODE
LOW…rators/test/integration/test_preferred_cluster_gemm.py77logger = logging.getLogger(__name__)CODE
LOWoperators/test/integration/test_gemm_dynamic.py48logger = logging.getLogger(__name__)CODE
LOWoperators/test/integration/test_gemm.py47logger = logging.getLogger(__name__)CODE
LOWoperators/test/integration/test_tgv_gemm.py47logger = logging.getLogger(__name__)CODE
LOWoperators/test/integration/test_mixed_input_gemm.py58logger = logging.getLogger(__name__)CODE
LOWoperators/test/integration/test_gemm_jax.py50logger = logging.getLogger(__name__)CODE
LOWoperators/cutlass/operators/__init__.py98__all__ = [CODE
LOWoperators/cutlass/operators/fusion/__init__.py122__all__ = [CODE
LOWoperators/cutlass/operators/fusion/frontend/__init__.py38__all__ = [CODE
LOWoperators/cutlass/operators/fusion/ir/__init__.py55__all__ = [CODE
LOWoperators/cutlass/operators/fusion/passes/__init__.py48__all__ = [CODE
LOWoperators/cutlass/operators/fusion/backend/__init__.py38__all__ = [CODE
LOWoperators/cutlass/operators/providers/__init__.py94__all__ = [CODE
LOW…rators/providers/cutedsl/integration_utils/__init__.py37__all__ = [CODE
LOW…/cutlass/operators/providers/cutedsl/evt/common_efc.py70logger = logging.getLogger(__name__)CODE
LOWoperators/cutlass/operators/utils/__init__.py31__all__ = [CODE
LOWoperators/cutlass/operators/metadata/__init__.py52__all__ = [CODE
LOWoperators/cutlass/operators/metadata/design/__init__.py37__all__ = [CODE
LOW…rators/cutlass/operators/metadata/operands/__init__.py33__all__ = [CODE
LOWoperators/cutlass/operators/arguments/__init__.py45__all__ = [CODE
LOWpython/CuTeDSL/prep_editable_install.py32logger = logging.getLogger(__name__)CODE
LOWpython/CuTeDSL/_mlir_helpers/__init__.py22__all__ = ["arith", "vector", "lru_cache_ir", "dsl_user_op"]CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py67def set_verify_trace(enabled: bool) -> None:CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py96def _set_enable_frame_filtering(enable: bool) -> None:CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py102def _set_include_lib_frame(enable: bool) -> None:CODE
LOWpython/CuTeDSL/_mlir_helpers/math.py2145__all__ = [CODE
LOWpython/CuTeDSL/cutlass/address_space.py14__all__ = ["AddressSpace"]CODE
LOWpython/CuTeDSL/cutlass/pipeline/__init__.py54__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/tuple.py526__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/__init__.py260__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/core.py91__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/tensor.py97__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/math.py21__all__ = [*_base_math.__all__, "absf"]CODE
LOWpython/CuTeDSL/cutlass/cute/typing.py966__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/ffi.py60__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/__init__.py25__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/common.py25__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/helpers.py43__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/tcgen05/__init__.py37__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/warpgroup/__init__.py36__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/__init__.py17__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/warp/__init__.py17__all__ = [CODE
LOW…thon/CuTeDSL/cutlass/cute/experimental/host_runtime.py19__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/arch/__init__.py24__all__ = [CODE
LOWpython/CuTeDSL/cutlass/cute/export/__init__.py47__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/print_latex.py28__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/blackwell_helpers.py2225__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/layout.py70__all__ = ["LayoutEnum"]CODE
LOWpython/CuTeDSL/cutlass/utils/__init__.py137__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/hopper_helpers.py439__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/distributed.py23__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/gemm/__init__.py14__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/gemm/sm100.py21__all__ = [CODE
LOWpython/CuTeDSL/cutlass/utils/gemm/tensor_utils.py39__all__ = [CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py290def set_dynamic_debug(enabled: bool, max_depth: int | None = None) -> None:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py879 def set_name_prefix(name: str) -> None:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/vector.py29__all__ = [CODE
LOWpython/CuTeDSL/cutlass/base_dsl/diagnostics.py46__all__ = [CODE
LOWpython/CuTeDSL/cutlass/base_dsl/swizzle.py369__all__ = [CODE
20 more matches not shown…
AI Structural Patterns84 hits · 77 pts
SeverityFileLineSnippetContext
LOWtest/python/cutlass/gemm/utils.py150CODE
LOW…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py104CODE
LOWtest/examples/CuTeDSL/hopper/test_grouped_gemm.py84CODE
LOWtest/examples/CuTeDSL/hopper/test_grouped_gemm.py118CODE
LOWtest/examples/CuTeDSL/hopper/test_grouped_gemm.py154CODE
LOWpython/cutlass_cppgen/op/gemm.py219CODE
LOWpython/cutlass_cppgen/op/gemm.py632CODE
LOWpython/cutlass_cppgen/op/gemm_grouped.py116CODE
LOWpython/cutlass_cppgen/op/conv.py205CODE
LOWpython/cutlass_cppgen/op/conv.py545CODE
LOWpython/cutlass_cppgen/op/conv.py637CODE
LOWpython/cutlass_cppgen/op/conv.py737CODE
LOWpython/cutlass_cppgen/op/conv.py917CODE
LOWpython/cutlass_cppgen/op/conv.py931CODE
LOWpython/cutlass_cppgen/op/conv.py946CODE
LOWpython/cutlass_cppgen/op/conv.py960CODE
LOWpython/cutlass_cppgen/op/conv.py974CODE
LOWpython/cutlass_cppgen/op/conv.py988CODE
LOWpython/CuTeDSL/cutlass/testing.py309CODE
LOWpython/CuTeDSL/cutlass/pipeline/sm100.py180CODE
LOWpython/CuTeDSL/cutlass/pipeline/sm100.py1032CODE
LOWpython/CuTeDSL/cutlass/cute/metadata.py160CODE
LOWpython/CuTeDSL/cutlass/cute/core.py2058CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/common.py446CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/common.py529CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/tcgen05/copy.py821CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1165CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1255CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1354CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1407CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1486CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1575CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/helpers.py173CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/helpers.py690CODE
LOWpython/CuTeDSL/cutlass/cute/experimental/memory.py169CODE
LOWpython/CuTeDSL/cutlass/cute/arch/nvvm_wrappers.py3176CODE
LOWpython/CuTeDSL/cutlass/cute/arch/nvvm_wrappers.py5515CODE
LOWpython/CuTeDSL/cutlass/utils/tmem_allocator.py304CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2707CODE
LOWpython/CuTeDSL/cutlass/base_dsl/compiler.py188CODE
LOWpython/CuTeDSL/cutlass/base_dsl/ast_helpers.py201CODE
LOWpython/CuTeDSL/cutlass/base_dsl/ast_helpers.py108CODE
LOWpython/CuTeDSL/cutlass/base_dsl/common.py549CODE
LOWpython/CuTeDSL/cutlass/base_dsl/typing.py2708CODE
LOW…/CuTeDSL/cutlass/cutlass_dsl/cutlass_ast_decorators.py284CODE
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py943CODE
LOWpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py1083CODE
LOWpython/CuTeDSL/cutlass/jax/primitive.py40CODE
LOWpython/cutlass_library/gemm_operation.py64CODE
LOWpython/cutlass_library/emit_kernel_listing.py84CODE
LOWexamples/python/CuTeDSL/dsl_tutorials/call_from_jit.py93CODE
LOW…er/kernel/dense_gemm/dense_gemm_fp8_gelu_persistent.py1568CODE
LOW…/cute/hopper/kernel/dense_gemm/dense_gemm_fp8_2xacc.py1167CODE
LOW…/attention/mixed_input_fmha/mixed_input_fmha_decode.py1616CODE
LOW…n/CuTeDSL/cute/blackwell/kernel/attention/fmha/fmha.py3826CODE
LOW…ell/kernel/dense_gemm/dense_gemm_persistent_dynamic.py1870CODE
LOW…ell/kernel/dense_gemm/dense_gemm_persistent_dynamic.py1921CODE
LOW…well/kernel/dense_gemm/dense_gemm_software_pipeline.py1512CODE
LOW…e/blackwell/kernel/dense_gemm/dense_gemm_persistent.py1521CODE
LOW…CuTeDSL/cute/blackwell/kernel/dense_gemm/dense_gemm.py1553CODE
24 more matches not shown…
AI Response Leakage3 hits · 22 pts
SeverityFileLineSnippetContext
HIGH…CuTeDSL/dsl_tutorials/programmatic_dependent_launch.py171 # In this example, we add a loop (10 times) for all the copy and compute operations in the following codeCOMMENT
HIGH…CuTeDSL/dsl_tutorials/programmatic_dependent_launch.py183 # In this example, the second kernel's second operand ``gB`` has no dependencies, its loading can overlapCOMMENT
HIGH…CuTeDSL/cute/blackwell/tutorial/tutorial_tma/tma_v1.py260 # In this example `copy_elems = 1` and `thread_layout` has shape (T, V) = (num_trans_threads, 1),COMMENT
Dead Code5 hits · 10 pts
SeverityFileLineSnippetContext
MEDIUMpython/cutlass_library/rank_k_operation.py84CODE
MEDIUMpython/cutlass_library/rank_2k_operation.py86CODE
MEDIUMpython/cutlass_library/symm_operation.py86CODE
MEDIUMpython/cutlass_library/trmm_operation.py83CODE
MEDIUM…stributed/distributed_gemm_reduce_scatter_blackwell.py304CODE
Cross-Language Confusion2 hits · 8 pts
SeverityFileLineSnippetContext
HIGHpython/cutlass_cppgen/backend/conv2d_operation.py257 if (args.tensor_c_numel >= 0 && args.tensor_c_numel == tc_C.at(3) && args.tensor_c_numel < size_C) {CODE
HIGHpython/CuTeDSL/cutlass/base_dsl/dsl.py1919 process stderr and the lookup returns null, which the upstream wrapperSTRING
Example Usage Blocks1 hit · 2 pts
SeverityFileLineSnippetContext
LOWpython/cutlass_library/emit_kernel_listing.py41# Example usage:COMMENT