本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）
This report summarizes scanner evidence for liguodongiot/llm-action, a HTML project with 25,151 GitHub stars. SynthScan examined 108,803 lines of code across 783 source files, recording 416 pattern matches distributed across 17 syntactic categories. The legacy adjusted pattern signal is 8.2 (Moderate pattern signal); it is not an authorship estimate.
Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.
Use each vector to guide manual verification of the underlying findings.
Can maintainers explain intent, assumptions, and trade-offs? 184 finding(s).
Are imports declared and package/API names verified? 167 finding(s).
Are wrappers, guards, and repeated structures necessary? 118 finding(s).
Which changes need focused human review? 416 finding(s).
This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.
Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.
This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.
The scanner identified 416 distinct pattern matches across 17 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | …m-train/pytorch/distribution/tensor-parallel/README.md | 54 | torch.distributed.tensor.parallel.style.make_input_replicate_1d(input, device_mesh=None) | CODE |
| CRITICAL | …-train/pytorch/distribution/pipeline-parallel/1-流水线.md | 73 | - torch.distributed.pipeline.sync.skip.skippable.skippable(stash=(), pop=()) | CODE |
| CRITICAL⚡ | …-train/pytorch/distribution/pipeline-parallel/1-流水线.md | 113 | - torch.distributed.pipeline.sync.skip.skippable.stash(name, tensor) | CODE |
| CRITICAL⚡ | …-train/pytorch/distribution/pipeline-parallel/1-流水线.md | 115 | - torch.distributed.pipeline.sync.skip.skippable.pop(name) | CODE |
| CRITICAL⚡ | …-train/pytorch/distribution/pipeline-parallel/1-流水线.md | 117 | - torch.distributed.pipeline.sync.skip.skippable.verify_skippables(module) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 247 | model.language_model.embedding.word_embeddings.weight.data.copy_(out_word_embed[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 249 | model.language_model.embedding.position_embeddings.weight.data.copy_(pos_embed) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 302 | l.self_attention.query_key_value.weight.data.copy_(qkv_weight[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 303 | l.self_attention.dense.weight.data.copy_(dense_weight[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 306 | l.mlp.dense_h_to_4h.weight.data.copy_(mlp_l0_weight[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 307 | l.mlp.dense_4h_to_h.weight.data.copy_(mlp_l1_weight[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 309 | l.self_attention.query_key_value.bias.data.copy_(qkv_bias[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 310 | l.self_attention.dense.bias.data.copy_(dense_bias) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 311 | l.mlp.dense_h_to_4h.bias.data.copy_(mlp_l0_bias[tp_rank]) | CODE |
| CRITICAL⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 312 | l.mlp.dense_4h_to_h.bias.data.copy_(mlp_l1_bias) | CODE |
| CRITICAL | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 323 | models[tp_rank].language_model.encoder.final_layernorm.weight.data.copy_(final_layernorm_weight) | CODE |
| CRITICAL | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 324 | models[tp_rank].language_model.encoder.final_layernorm.bias.data.copy_(final_layernorm_bias) | CODE |
| CRITICAL | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 352 | models[tp_rank].language_model.pooler.dense.weight.data.copy_(pooler_weight) | CODE |
| CRITICAL | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 353 | models[tp_rank].language_model.pooler.dense.bias.data.copy_(pooler_bias) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | llm-data-engineering/sft-dataset/jinja-llm-bloom.py | 2 | CODE | |
| LOW | llm-data-engineering/sft-dataset/jinja-llm-baichuan2.py | 2 | CODE | |
| LOW | llm-data-engineering/sft-dataset/jinja-llm-baichuan.py | 2 | CODE | |
| LOW | llm-data-engineering/sft-dataset/jinja-llm.py | 2 | CODE | |
| LOW | llm-data-engineering/sft-dataset/jinja-llm-chatglm3.py | 2 | CODE | |
| LOW | llm-eval/llm-performance/stat_gpu_memory.py | 1 | CODE | |
| LOW | …performance/hardware-performance/pynvml-stat-memory.py | 1 | CODE | |
| LOW | …al/llm-performance/vllm/vllm-locust-qwen1.5-7b-long.py | 3 | CODE | |
| LOW | …al/llm-performance/vllm/vllm-locust-qwen1.5-7b-long.py | 4 | CODE | |
| LOW | …al/llm-performance/vllm/vllm-locust-qwen1.5-7b-long.py | 4 | CODE | |
| LOW | …al/llm-performance/mindie/lantency/stat_input_token.py | 4 | CODE | |
| LOW | …al/llm-performance/mindie/lantency/stat_input_token.py | 4 | CODE | |
| LOW | …al/llm-performance/mindie/lantency/perfermance-stat.py | 5 | CODE | |
| LOW | …performance/mindie/locust-lantency-throughput/hello.py | 3 | CODE | |
| LOW | …performance/mindie/locust-lantency-throughput/hello.py | 4 | CODE | |
| LOW | …ocust-lantency-throughput/llm-910b4-chatglm3-6b-2tp.py | 3 | CODE | |
| LOW | …ocust-lantency-throughput/llm-910b4-chatglm3-6b-2tp.py | 4 | CODE | |
| LOW | …ocust-lantency-throughput/llm-910b4-chatglm3-6b-2tp.py | 4 | CODE | |
| LOW | …e/locust-lantency-throughput/llm-910b4-qwen-72b-8tp.py | 2 | CODE | |
| LOW | …e/locust-lantency-throughput/llm-910b4-qwen-72b-8tp.py | 3 | CODE | |
| LOW | …e/locust-lantency-throughput/llm-910b4-qwen-72b-8tp.py | 3 | CODE | |
| LOW | …cust-lantency-throughput/llm-910b4-baichuan2-7b-2tp.py | 3 | CODE | |
| LOW | …cust-lantency-throughput/llm-910b4-baichuan2-7b-2tp.py | 4 | CODE | |
| LOW | …cust-lantency-throughput/llm-910b4-baichuan2-7b-2tp.py | 4 | CODE | |
| LOW | …ie/locust-lantency-throughput/llm-910b4-qwen1.5-4tp.py | 2 | CODE | |
| LOW | …ie/locust-lantency-throughput/llm-910b4-qwen1.5-4tp.py | 3 | CODE | |
| LOW | …ie/locust-lantency-throughput/llm-910b4-qwen1.5-4tp.py | 3 | CODE | |
| LOW | …nference/ascend/mindformers/mindsporelite-inference.py | 12 | CODE | |
| LOW | llm-inference/ascend/mindformers/mindsporelite-stat.py | 3 | CODE | |
| LOW | llm-inference/ascend/mindformers/mindsporelite-stat.py | 11 | CODE | |
| LOW | …nference/ascend/mindformers/baichuan2/baichuan-stat.py | 2 | CODE | |
| LOW | …nce/ascend/mindformers/baichuan2/baichuan-inference.py | 1 | CODE | |
| LOW | …nce/ascend/mindformers/baichuan2/baichuan-inference.py | 2 | CODE | |
| LOW | …-inference/ascend/mindformers/chatglm3/chatglm-stat.py | 2 | CODE | |
| LOW | …m-inference/ascend/mindformers/chatglm3/chatglm-gen.py | 2 | CODE | |
| LOW | …rence/ascend/mindformers/chatglm3/chatglm-inference.py | 5 | CODE | |
| LOW | llm-inference/web/flask/llm-qwen-mindspore-lite.py | 4 | CODE | |
| LOW | llm-inference/web/flask/llm-qwen-mindspore-lite.py | 7 | CODE | |
| LOW | llm-inference/web/flask/llm-qwen-mindspore-lite.py | 9 | CODE | |
| LOW | llm-inference/web/fastapi/llm-qwen-mindspore-lite.py | 4 | CODE | |
| LOW | llm-inference/web/fastapi/llm-qwen-mindspore-lite.py | 7 | CODE | |
| LOW | llm-inference/web/fastapi/llm-qwen-mindspore-lite.py | 9 | CODE | |
| LOW | llm-inference/web/fastapi/llm-qwen-mindspore-lite.py | 15 | CODE | |
| LOW | llm-inference/web/fastapi/llm-qwen-mindspore-lite.py | 17 | CODE | |
| LOW | …ter-transformer/bloom/firefly_lambada_1w_stat_token.py | 1 | CODE | |
| LOW | …ter-transformer/bloom/firefly_lambada_1w_stat_token.py | 10 | CODE | |
| LOW | …ter-transformer/bloom/firefly_lambada_1w_stat_token.py | 12 | CODE | |
| LOW | …er-transformer/megatron-gpt2/gpt_summarization_stat.py | 7 | CODE | |
| LOW | …/faster-transformer/megatron-gpt2/gpt_summarization.py | 7 | CODE | |
| LOW | llm-inference/triton/resnet50/client.py | 5 | CODE | |
| LOW | …se/distribution-parallelism/moe-parallel/paddle_moe.py | 6 | CODE | |
| LOW | …se/distribution-parallelism/moe-parallel/paddle_moe.py | 8 | CODE | |
| LOW | ai-framework/mxnet/oneflow_cnn_mnist.py | 6 | CODE | |
| LOW | ai-framework/mxnet/mxnet_cnn_mnist.py | 1 | CODE | |
| LOW | ai-framework/mxnet/mxnet_cnn_mnist.py | 12 | CODE | |
| LOW | ai-framework/mxnet/mxnet_cnn_mnist.py | 12 | CODE | |
| LOW | ai-framework/mxnet/mxnet_cnn_mnist.py | 26 | CODE | |
| LOW | ai-framework/mxnet/mxnet_mlp_mnist.py | 2 | CODE | |
| LOW | ai-framework/mxnet/mnist.py | 4 | CODE | |
| LOW | llm-train/alpaca-lora/generate.py | 7 | CODE | |
| 82 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | llm-inference/DeepSpeed-Inference.md | 9 | # --------------------------------------- | COMMENT |
| MEDIUM | llm-inference/DeepSpeed-Inference.md | 11 | # --------------------------------------- | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 24 | # ---------------- | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 124 | # ------------------------------------- | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 137 | # ------------------- | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 246 | # ----------------------------------- | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 341 | # ------------- | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 445 | # ------------------------------------- | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 19 | # ------------------------------------------- | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 37 | # ------------------------ | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 56 | # ------------------------------- | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 119 | # ------------------------------------------- | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 196 | # ---------------------------------------------- | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 250 | # --------------------- | COMMENT |
| MEDIUM | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 204 | #----------- | COMMENT |
| MEDIUM⚡ | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 254 | #------------------- | COMMENT |
| MEDIUM | llm-algo/chatglm/模型架构.md | 220 | # =================================== | COMMENT |
| MEDIUM | llm-algo/chatglm/模型架构.md | 222 | # =================================== | COMMENT |
| MEDIUM | llm-algo/chatglm/模型架构.md | 264 | # ========================= | COMMENT |
| MEDIUM | llm-algo/chatglm/模型架构.md | 266 | # ========================= | COMMENT |
| MEDIUM | llm-algo/chatglm2/模型架构.md | 138 | # =========================== | COMMENT |
| MEDIUM | llm-algo/chatglm2/模型架构.md | 140 | # =========================== | COMMENT |
| MEDIUM | llm-algo/chatglm2/模型架构.md | 160 | # ========================= | COMMENT |
| MEDIUM | llm-algo/chatglm2/模型架构.md | 162 | # ========================= | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 253 | # ================================================= | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 255 | # ================================================= | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 256 | # ===================== | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 258 | # ===================== | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 322 | # ================================== | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 324 | # ================================== | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 328 | # ================= | COMMENT |
| MEDIUM⚡ | llm-algo/chatglm2/模型架构.md | 330 | # ================= | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …-inference/ascend/mindformers/chatglm3/chatglm-stat.py | 0 | # 2. 自定义修改配置后实例化 config = autoconfig.from_pretrained('/root/workspace/model/chatglm3-6b_ms/run_glm3_6b.yaml') config.use | STRING |
| HIGH | …m-inference/ascend/mindformers/chatglm3/chatglm-gen.py | 0 | # 2. 自定义修改配置后实例化 config = autoconfig.from_pretrained('/root/workspace/model/chatglm3-6b_ms/run_glm3_6b.yaml') config.use | STRING |
| HIGH | …rence/ascend/mindformers/chatglm3/chatglm-inference.py | 0 | # 2. 自定义修改配置后实例化 config = autoconfig.from_pretrained('/root/workspace/model/chatglm3-6b_ms/run_glm3_6b.yaml') config.use | STRING |
| HIGH | llm-train/alpaca/train_ddp.py | 0 | resize tokenizer and embedding. note: this is the unoptimized version that may make your embedding size not be divisible | STRING |
| HIGH | llm-train/alpaca/train.py | 0 | resize tokenizer and embedding. note: this is the unoptimized version that may make your embedding size not be divisible | STRING |
| HIGH | llm-train/qlora/qlora.py | 0 | resize tokenizer and embedding. note: this is the unoptimized version that may make your embedding size not be divisible | STRING |
| HIGH | llm-train/chinese-llama-alpaca/run_clm_sft_with_peft.py | 0 | resize tokenizer and embedding. note: this is the unoptimized version that may make your embedding size not be divisible | STRING |
| HIGH | llm-localization/ascend/standford-alpaca/train.py | 0 | resize tokenizer and embedding. note: this is the unoptimized version that may make your embedding size not be divisible | STRING |
| HIGH | llm-train/alpaca/train_ddp.py | 0 | make dataset and collator for supervised fine-tuning. | STRING |
| HIGH | llm-train/alpaca/train.py | 0 | make dataset and collator for supervised fine-tuning. | STRING |
| HIGH | llm-localization/ascend/standford-alpaca/train.py | 0 | make dataset and collator for supervised fine-tuning. | STRING |
| HIGH | …tribution/tensor-parallel/sequence_parallel_example.py | 0 | main body of the demo of a basic version of tensor parallel by using pytorch native apis. | STRING |
| HIGH | …ch/distribution/tensor-parallel/2d_parallel_example.py | 0 | main body of the demo of a basic version of tensor parallel by using pytorch native apis. | STRING |
| HIGH | …istribution/tensor-parallel/tensor_parallel_example.py | 0 | main body of the demo of a basic version of tensor parallel by using pytorch native apis. | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | llm-tools/profiler-recipe.py | 21 | # Name Self CPU CPU total CPU time avg # of Calls | COMMENT |
| LOW | llm-tools/profiler-recipe.py | 41 | # --------------------------------- ------------ ------------------------------------------- | COMMENT |
| LOW | llm-tools/profiler-recipe.py | 81 | COMMENT | |
| LOW | llm-tools/profiler-recipe.py | 121 | # --------------------------------- ------------ ------------ ------------ | COMMENT |
| LOW | llm-tools/profiler-recipe.py | 141 | # aten::empty 94.79 Mb 94.79 Mb 121 | COMMENT |
| LOW | llm-tools/profiler-recipe.py | 181 | with_stack=True, | COMMENT |
| LOW | llm-pipeline/REAEMD.md | 81 | # --llama \ | COMMENT |
| LOW | llm-pipeline/REAEMD.md | 101 | # --gradient_checkpointing \ | COMMENT |
| LOW | llm-pipeline/REAEMD.md | 121 | # --num_train_epochs 2 \ | COMMENT |
| LOW | llm-train/qlora/accuracy.py | 1 | # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | COMMENT |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | llm-train/chinese-llama-alpaca/run_clm_sft_with_peft.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | …ibution/data-parallel/minGPT-ddp/sbatch_run_sig_opt.sh | 1 | COMMENT | |
| LOW | …rch/distribution/data-parallel/minGPT-ddp/multinode.sh | 1 | #!/bin/bash | COMMENT |
| LOW | …istribution/data-parallel/minGPT-ddp/sbatch_run_sig.sh | 1 | #!/bin/bash | COMMENT |
| LOW | …ch/distribution/data-parallel/minGPT-ddp/sbatch_run.sh | 1 | COMMENT | |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 61 | COMMENT | |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 121 | COMMENT | |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 141 | ###################################################################### | COMMENT |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 221 | ###################################################################### | COMMENT |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 241 | # Need batch dimension first for pipeline parallelism. | COMMENT |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 341 | # ------------- | COMMENT |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 461 | mp.spawn(run_worker, args=(world_size, ), nprocs=world_size, join=True) | COMMENT |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 481 | # [RANK 1]: ----------------------------------------------------------------------------------------- | COMMENT |
| LOW | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 501 | # [RANK 0]: | epoch 3 | 20/ 50 batches | lr 4.51 | ms/batch 698.27 | loss 12.01 | ppl 164364.60 | COMMENT |
| LOW | llm-train/alpa/train/pipeshard_parallelism.py | 41 | ray.init() | COMMENT |
| LOW | llm-train/alpa/train/pipeshard_parallelism.py | 181 | COMMENT | |
| LOW | llm-train/alpa/train/pipeshard_parallelism.py | 201 | # | COMMENT |
| LOW | llm-train/alpa/train/pipeshard_parallelism.py | 241 | auto_pipeline_actual_state = auto_pipeline_train_step(state, batch) | COMMENT |
| LOW | llm-train/alpa/train/pipeshard_parallelism.py | 261 | # | COMMENT |
| LOW | …egatron/gpt2/merge_ck_and_inference/checkpoint_util.py | 1 | import argparse | COMMENT |
| LOW | …egatron/gpt2/merge_ck_and_inference/checkpoint_util.py | 21 | COMMENT | |
| LOW | …egatron/gpt2/merge_ck_and_inference/checkpoint_util.py | 41 | # consumed_valid_samples | COMMENT |
| LOW | …egatron/gpt2/merge_ck_and_inference/checkpoint_util.py | 61 | # "mlp l1 weight" | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 21 | END: Cython Metadata */ | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 41 | #endif | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 61 | #else | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 81 | #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 101 | #endif | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 121 | #endif | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 141 | #define PyObject_Free(p) PyMem_Free(p) | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 161 | #if PY_MAJOR_VERSION >= 3 | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 181 | #define PyInt_FromSsize_t PyLong_FromSsize_t | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 201 | #else | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 221 | #define __Pyx_PyType_AsAsync(obj) NULL | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 281 | COMMENT | |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 301 | #include "stdlib.h" | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 321 | # else | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 341 | #define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 361 | #define __Pyx_sst_abs(value) abs(value) | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 381 | #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 401 | #else | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 521 | COMMENT | |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 601 | #endif | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 621 | #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 1041 | #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL; | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 1061 | #define __Pyx_XINCREF(r) do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0) | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 1141 | #endif | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 1161 | int memview_is_new_reference); | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 1181 | COMMENT | |
| 11 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | llm-inference/flexflow-serve/benchmark-batch1.py | 43 | # Create the sampling configs | COMMENT |
| MEDIUM | ai-framework/deepspeed/hello_bert/train_bert_ds.py | 117 | # Create the labels first | COMMENT |
| MEDIUM | ai-framework/deepspeed/hello_bert/train_bert_ds.py | 941 | # Create the labels first | COMMENT |
| MEDIUM | ai-framework/deepspeed/hello_bert/train_bert.py | 117 | # Create the labels first | COMMENT |
| MEDIUM | llm-train/galore/torchrun_main.py | 433 | # The below code is only executed during the update step | COMMENT |
| MEDIUM | …tribution/tensor-parallel/sequence_parallel_example.py | 49 | # Create a optimizer for the parallelized module. | COMMENT |
| MEDIUM | …ch/distribution/tensor-parallel/2d_parallel_example.py | 75 | # Create a optimizer for the parallelized module. | COMMENT |
| MEDIUM | …istribution/tensor-parallel/tensor_parallel_example.py | 57 | # Create a optimizer for the parallelized module. | COMMENT |
| MEDIUM | …pytorch/distribution/pipeline-parallel/ddp_pipeline.py | 23 | # Define the model | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 101 | # Define the training step | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 127 | # Define a MLP model with manual stage boundaries. | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 154 | # Define the training step. | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 213 | # Define the parallel method. | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 222 | # Define the training step. The function body is the same as the above one. | COMMENT |
| MEDIUM⚡ | llm-compression/quantization/llm-qat/cfd70ff/utils.py | 16 | # Define a utility method for setting the logging parameters of a logger | COMMENT |
| MEDIUM⚡ | llm-compression/quantization/llm-qat/cfd70ff/utils.py | 24 | # Define a formatter for the log messages | COMMENT |
| MEDIUM⚡ | llm-compression/quantization/llm-qat/cfd70ff/utils.py | 29 | # Create a console handler for outputting log messages to the console | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | llm-train/alpaca-lora/generate.py | 21 | except: # noqa: E722 | CODE |
| HIGH | …tribution/tensor-parallel/sequence_parallel_example.py | 15 | except BaseException as e: | CODE |
| HIGH | …ch/distribution/tensor-parallel/2d_parallel_example.py | 21 | except BaseException as e: | CODE |
| HIGH | llm-train/chatglm-lora/finetune_ddp.py | 103 | except: | CODE |
| HIGH | …2/merge_ck_and_inference/run_text_generation_server.py | 71 | except ValueError as ve: | CODE |
| HIGH | …2/merge_ck_and_inference/run_text_generation_server.py | 76 | except ValueError as ve: | CODE |
| HIGH | llm-train/megatron/gpt2/data/download.py | 129 | except: | CODE |
| HIGH | llm-localization/ascend/mindie/script/model-test.py | 23 | except ModuleNotFoundError: | CODE |
| HIGH | llm-localization/ascend/mindie/script/model-test.py | 42 | except TypeError: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | llm-data-engineering/sft-dataset/数据集格式.md | 93 | def preprocess_function_train(examples): | CODE |
| LOW | llm-data-engineering/sft-dataset/数据集格式.md | 156 | def build_inputs_with_special_tokens( | CODE |
| LOW | llm-data-engineering/sft-dataset/数据集格式.md | 434 | def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): | CODE |
| LOW | …nference/ascend/mindformers/mindsporelite-inference.py | 26 | def pipeline_from_model_paths(args_, tokenizer): | CODE |
| LOW | …nference/ascend/mindformers/mindsporelite-inference.py | 76 | def pipeline_from_infer_config(args_, tokenizer): | CODE |
| LOW | llm-inference/ascend/mindformers/mindsporelite-stat.py | 33 | def pipeline_from_model_paths(args_, tokenizer): | CODE |
| LOW | llm-inference/ascend/mindformers/mindsporelite-stat.py | 83 | def pipeline_from_infer_config(args_, tokenizer): | CODE |
| LOW | llm-train/alpaca-lora/finetune_metrics_epoch.py | 152 | def generate_and_tokenize_prompt(data_point): | CODE |
| LOW | llm-train/alpaca-lora/finetune.py | 146 | def generate_and_tokenize_prompt(data_point): | CODE |
| LOW | llm-train/chatglm/main.py | 176 | def preprocess_function_train(examples): | CODE |
| LOW | llm-train/alpaca/train_ddp.py | 54 | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output_dir: str): | CODE |
| LOW | llm-train/alpaca/train_ddp.py | 63 | def smart_tokenizer_and_embedding_resize( | CODE |
| LOW | llm-train/alpaca/train_ddp.py | 173 | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokenizer, data_args) -> Dict: | CODE |
| LOW | llm-train/alpaca/train.py | 53 | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output_dir: str): | CODE |
| LOW | llm-train/alpaca/train.py | 62 | def smart_tokenizer_and_embedding_resize( | CODE |
| LOW | llm-train/alpaca/train.py | 172 | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokenizer, data_args) -> Dict: | CODE |
| LOW | llm-train/qlora/qlora.py | 346 | def print_trainable_parameters(args, model): | CODE |
| LOW | llm-train/qlora/qlora.py | 363 | def smart_tokenizer_and_embedding_resize( | CODE |
| LOW | llm-train/qlora/qlora.py | 438 | def extract_unnatural_instructions_data(examples, extract_reformulations=False): | CODE |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 75 | def preprocess_logits_for_metrics(logits, labels): | CODE |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 83 | def fault_tolerance_data_collator(features: List) -> Dict[str, Any]: | CODE |
| LOW | llm-train/chinese-llama-alpaca/run_clm_sft_with_peft.py | 433 | def smart_tokenizer_and_embedding_resize( | CODE |
| LOW | llm-train/alpa/train/pipeshard_parallelism.py | 161 | def manual_pipeline_train_step(state, batch): | CODE |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 8142 | * cdef setitem_slice_assign_scalar(self, memoryview dst, value): | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 8186 | * cdef setitem_slice_assign_scalar(self, memoryview dst, value): # <<<<<<<<<<<<<< | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 8213 | * cdef setitem_slice_assign_scalar(self, memoryview dst, value): | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 8451 | * cdef setitem_slice_assign_scalar(self, memoryview dst, value): # <<<<<<<<<<<<<< | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 14045 | * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< | COMMENT |
| LOW | llm-train/megatron/gpt2/data/cMinhash.cpp | 14149 | * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< | COMMENT |
| LOW | llm-algo/chatglm/模型架构.md | 176 | def apply_rotary_pos_emb_index(q, k, cos, sin, position_id): | CODE |
| LOW | llm-algo/chatglm/模型架构.md | 362 | def split_tensor_along_last_dim(self, tensor, num_partitions, | CODE |
| LOW | llm-algo/chatglm2/模型架构.md | 749 | def _update_model_kwargs_for_generation( | CODE |
| LOW | llm-algo/chatglm2/模型架构.md | 780 | def prepare_inputs_for_generation( | CODE |
| LOW⚡ | llm-compression/quantization/llm-qat/cfd70ff/utils.py | 39 | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output_dir: str): | CODE |
| LOW | llm-localization/ascend/standford-alpaca/train.py | 51 | def smart_tokenizer_and_embedding_resize( | CODE |
| LOW | llm-localization/ascend/standford-alpaca/train.py | 161 | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokenizer, data_args) -> Dict: | CODE |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1237 | def __compare_simplified_dataset_results(self): | CODE |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1370 | def __compare_full_dataset_results(self): | CODE |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1456 | def __patch_hf_transformers_utils(self): | CODE |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 799 | def process_before_extraction(gen, choice_dict): | STRING |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 977 | def __run_full_dataset_truthfulqa(self): | STRING |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 986 | def format_prompt_with_answer_strings(question, ans): | STRING |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1153 | def __run_full_dataset_humaneval(self): | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH⚡ | llm-train/megatron/gpt2/data/download.py | 251 | url varchar(2048) not null, | CODE |
| HIGH⚡ | llm-train/megatron/gpt2/data/download.py | 252 | domain varchar(255) not null, | CODE |
| HIGH⚡ | llm-train/megatron/gpt2/data/download.py | 253 | word_count int null, | CODE |
| HIGH⚡ | llm-train/megatron/gpt2/data/download.py | 254 | elapsed int null, | CODE |
| HIGH⚡ | llm-train/megatron/gpt2/data/download.py | 255 | scraper varchar(255) not null, | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …er-transformer/megatron-gpt2/gpt_summarization_stat.py | 24 | CODE | |
| LOW | …er-transformer/megatron-gpt2/gpt_summarization_stat.py | 354 | CODE | |
| LOW | …/faster-transformer/megatron-gpt2/gpt_summarization.py | 21 | CODE | |
| LOW | …/faster-transformer/megatron-gpt2/gpt_summarization.py | 327 | CODE | |
| LOW | ai-framework/mxnet/mxnet_cnn_mnist.py | 122 | CODE | |
| LOW | llm-train/alpaca-lora/export_state_dict_checkpoint.py | 80 | CODE | |
| LOW | llm-train/chatglm/main.py | 38 | CODE | |
| LOW | llm-train/chatglm/main.py | 148 | CODE | |
| LOW | llm-train/chatglm/main.py | 176 | CODE | |
| LOW | llm-train/qlora/qlora.py | 262 | CODE | |
| LOW | llm-train/qlora/qlora.py | 438 | CODE | |
| LOW | llm-train/qlora/qlora.py | 475 | CODE | |
| LOW | llm-train/qlora/qlora.py | 490 | CODE | |
| LOW | llm-train/qlora/qlora.py | 514 | CODE | |
| LOW | llm-train/qlora/qlora.py | 545 | CODE | |
| LOW | llm-train/galore/torchrun_main.py | 134 | CODE | |
| LOW | …/peft/clm/peft_lora_clm_accelerate_ds_zero3_offload.py | 109 | CODE | |
| LOW | …/chinese-llama-alpaca/merge_llama_with_chinese_lora.py | 67 | CODE | |
| LOW | …/chinese-llama-alpaca/merge_llama_with_chinese_lora.py | 111 | CODE | |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 83 | CODE | |
| LOW | …2/merge_ck_and_inference/checkpoint_loader_megatron.py | 19 | CODE | |
| LOW | …t2/merge_ck_and_inference/checkpoint_saver_megatron.py | 22 | CODE | |
| LOW | llm-train/megatron/gpt2/data/download.py | 193 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 297 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 471 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 535 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 587 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 669 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 789 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 889 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1075 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1153 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1224 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1264 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1499 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 334 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …m-inference/ascend/mindformers/text_generator_infer.py | 217 | CODE | |
| LOW | llm-inference/vllm/api_client.py | 32 | CODE | |
| LOW | llm-inference/vllm/api_client.py | 48 | CODE | |
| LOW | ai-framework/transformer-engine/mnist/main_stat.py | 43 | CODE | |
| LOW | ai-framework/transformer-engine/mnist/main.py | 43 | CODE | |
| LOW | ai-framework/deepspeed/hello_bert/train_bert.py | 566 | CODE | |
| LOW | llm-train/alpaca-lora/finetune_metrics_epoch.py | 28 | CODE | |
| LOW | llm-train/alpaca-lora/finetune.py | 28 | CODE | |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 145 | CODE | |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 1044 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | …er-transformer/megatron-gpt2/gpt_summarization_stat.py | 342 | print('Error with datapoint : ', data_point_idx) | CODE |
| MEDIUM | …/faster-transformer/megatron-gpt2/gpt_summarization.py | 325 | print('Error with datapoint : ', data_point_idx) | CODE |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 463 | except Exception: | CODE |
| MEDIUM | …ron/gpt2/merge_ck_and_inference/text_generation_cli.py | 20 | print(f"Error {response.status_code}: {response.json()['message']}") | CODE |
| LOW | llm-localization/ascend/mindie/script/model-test.py | 258 | except Exception as e: | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | llm-train/alpaca-lora/finetune_metrics_epoch.py | 104 | # Check if parameter passed or if set within environ | COMMENT |
| LOW | llm-train/alpaca-lora/finetune.py | 98 | # Check if parameter passed or if set within environ | COMMENT |
| LOW | …-compression/quantization/llm-qat/f4d873a/datautils.py | 91 | # Loop through the list of dictionaries | COMMENT |
| LOW | …-compression/quantization/llm-qat/f4d873a/datautils.py | 98 | # Append the value to the list associated with the key in dict_of_lists | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 44 | # Alternatively, you can use the following command to connect to an existing | COMMENT |
| MEDIUM | llm-train/alpa/train/pipeshard_parallelism.py | 191 | # device assignment of each stage, you can use the more advanced | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | llm-train/chatglm/main.py | 36 | logger = logging.getLogger(__name__) | CODE |
| LOW | llm-train/qlora/qlora.py | 46 | logger = logging.getLogger(__name__) | CODE |
| LOW | llm-train/chinese-llama-alpaca/run_clm_pt_with_peft.py | 310 | logger = logging.getLogger(__name__) | CODE |
| LOW | llm-train/chinese-llama-alpaca/run_clm_sft_with_peft.py | 195 | logger = logging.getLogger(__name__) | CODE |
| LOW | llm-train/megatron/gpt2/data/file_utils.py | 36 | logger = logging.getLogger(__name__) # pylint: disable=invalid-name | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | llm-train/qlora/accuracy.py | 33 | Args: predictions (`list` of `int`): Predicted labels. references (`list` of `int`): Ground truth labels. n | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | llm-data-engineering/sft-dataset/jinja-demo.py | 10 | result = template.render(name='John Doe') | CODE |