Making large AI models cheaper, faster and more accessible
This report presents the forensic synthetic code analysis of hpcaitech/ColossalAI, a Python project with 41,412 GitHub stars. SynthScan v2.0 examined 335,260 lines of code across 2148 source files, recording 4661 pattern matches distributed across 23 syntactic categories. The overall adjusted score of 22.8 places this repository in the Moderate AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 4661 distinct pattern matches across 23 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | …sts/test_shardformer/test_model/test_shard_deepseek.py | 130 | # =================================================================================== | COMMENT |
| MEDIUM | tests/test_shardformer/test_model/test_shard_mixtral.py | 123 | # =================================================================================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/timm/timm.py | 6 | ## ============== | COMMENT |
| MEDIUM | tests/kit/model_zoo/timm/timm.py | 8 | ## ============== | COMMENT |
| MEDIUM | tests/kit/model_zoo/timm/timm.py | 150 | # ============== | COMMENT |
| MEDIUM | tests/kit/model_zoo/timm/timm.py | 152 | # ============== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/command.py | 14 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/command.py | 16 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/mistral.py | 7 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/mistral.py | 9 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/t5.py | 6 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/t5.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/gptj.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/gptj.py | 10 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/albert.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/albert.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/albert.py | 69 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/albert.py | 71 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/opt.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/opt.py | 8 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/chatglm2.py | 7 | # ================================ | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/chatglm2.py | 9 | # ================================ | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/whisper.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/whisper.py | 8 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/llama.py | 14 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/llama.py | 16 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/llama.py | 23 | # ----------------------------------- | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/llama.py | 28 | # ----------------------------------- | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/vit.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/vit.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/deepseek.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/deepseek.py | 10 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/bert.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/bert.py | 8 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen3.py | 14 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen3.py | 16 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen3.py | 23 | # ----------------------------------- | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen3.py | 28 | # ----------------------------------- | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/deepseek_v3.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/deepseek_v3.py | 10 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/falcon.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/falcon.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/sam.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/sam.py | 8 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen2.py | 14 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen2.py | 16 | # =============================== | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen2.py | 23 | # ----------------------------------- | COMMENT |
| MEDIUM⚡ | tests/kit/model_zoo/transformers/qwen2.py | 28 | # ----------------------------------- | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/mixtral.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/mixtral.py | 10 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/gpt.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/gpt.py | 10 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/bloom.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/bloom.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/blip2.py | 6 | # =============================== | COMMENT |
| MEDIUM | tests/kit/model_zoo/transformers/blip2.py | 8 | # =============================== | COMMENT |
| MEDIUM | tests/test_pipeline/test_schedule/test_zerobubble_pp.py | 890 | # =================================================================================== | COMMENT |
| MEDIUM | tests/test_pipeline/test_schedule/test_zerobubble_pp.py | 1045 | # =================================================================================== | COMMENT |
| MEDIUM | …/test_fx/test_profiler/test_profiler_meta_info_prop.py | 67 | # ===================================================== | COMMENT |
| MEDIUM | …/test_fx/test_profiler/test_profiler_meta_info_prop.py | 83 | # ===================================================== | COMMENT |
| 471 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | tests/test_shardformer/test_layer/test_dist_log_prob.py | 0 | compute the log probabilities from logits for the given labels. args: logits (torch.tensor): the input logits. labels (t | STRING |
| HIGH | applications/ColossalChat/coati/distributed/utils.py | 0 | compute the log probabilities from logits for the given labels. args: logits (torch.tensor): the input logits. labels (t | STRING |
| HIGH | applications/ColossalChat/coati/models/utils.py | 0 | compute the log probabilities from logits for the given labels. args: logits (torch.tensor): the input logits. labels (t | STRING |
| HIGH | tests/test_legacy/test_moe/moe_utils.py | 0 | a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be ope | STRING |
| HIGH | …egacy/engine/gradient_handler/_moe_gradient_handler.py | 0 | a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be ope | STRING |
| HIGH | …ne/gradient_handler/_data_parallel_gradient_handler.py | 0 | a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be ope | STRING |
| HIGH | …radient_handler/_sequence_parallel_gradient_handler.py | 0 | a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be ope | STRING |
| HIGH | …radient_handler/_pipeline_parallel_gradient_handler.py | 0 | a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be ope | STRING |
| HIGH | …est_tensor_shard/test_metainfo/test_linear_metainfo.py | 0 | this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executed | STRING |
| HIGH | …st_tensor_shard/test_metainfo/test_pooling_metainfo.py | 0 | this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executed | STRING |
| HIGH | …/test_tensor_shard/test_metainfo/test_conv_metainfo.py | 0 | this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executed | STRING |
| HIGH | …hard/test_metainfo/test_binary_elementwise_metainfo.py | 0 | this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executed | STRING |
| HIGH | …/test_tensor_shard/test_metainfo/test_norm_metainfo.py | 0 | this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executed | STRING |
| HIGH | colossalai/pipeline/schedule/interleaved_pp.py | 0 | load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): t | STRING |
| HIGH | colossalai/pipeline/schedule/one_f_one_b.py | 0 | load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): t | STRING |
| HIGH | colossalai/pipeline/schedule/generate.py | 0 | load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): t | STRING |
| HIGH | colossalai/pipeline/schedule/zero_bubble_pp.py | 0 | load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): t | STRING |
| HIGH | colossalai/nn/optimizer/lamb.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/lars.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/galore.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/distributed_lamb.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/distributed_galore.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/fused_lamb.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/fused_sgd.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/adafactor.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/distributed_adafactor.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/came.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/optimizer/distributed_came.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | examples/images/diffusion/ldm/util.py | 0 | performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and return | STRING |
| HIGH | colossalai/nn/layer/utils.py | 0 | only allow exact division. args: numerator (int): numerator of the division. denominator (int): denominator of the divis | STRING |
| HIGH | colossalai/legacy/nn/layer/utils/common.py | 0 | only allow exact division. args: numerator (int): numerator of the division. denominator (int): denominator of the divis | STRING |
| HIGH | colossalai/legacy/tensor/dist_spec_mgr.py | 0 | only allow exact division. args: numerator (int): numerator of the division. denominator (int): denominator of the divis | STRING |
| HIGH | …tched_bias_addition_function/bias_addition_function.py | 0 | this method is used to create the non_bias_func proxy, the node created by this proxy will compute the main computation, | STRING |
| HIGH | …ddition_patch/patched_bias_addition_function/addbmm.py | 0 | this method is used to create the non_bias_func proxy, the node created by this proxy will compute the main computation, | STRING |
| HIGH | …h/patched_bias_addition_module/bias_addition_module.py | 0 | this method is used to create the non_bias_func proxy, the node created by this proxy will compute the main computation, | STRING |
| HIGH | colossalai/fx/passes/meta_info_prop.py | 0 | run `module` via interpretation and return the result and record the shape of each node. args: *args (tensor): the sampl | STRING |
| HIGH | colossalai/fx/passes/concrete_info_prop.py | 0 | run `module` via interpretation and return the result and record the shape of each node. args: *args (tensor): the sampl | STRING |
| HIGH | colossalai/_analyzer/fx/passes/shape_prop.py | 0 | run `module` via interpretation and return the result and record the shape of each node. args: *args (tensor): the sampl | STRING |
| HIGH | colossalai/fx/codegen/activation_checkpoint_codegen.py | 0 | add an obj to be tracked as a global. we call this for names that reference objects external to the graph, like function | STRING |
| HIGH | colossalai/autochunk/autochunk_codegen.py | 0 | add an obj to be tracked as a global. we call this for names that reference objects external to the graph, like function | STRING |
| HIGH | colossalai/_analyzer/fx/codegen.py | 0 | add an obj to be tracked as a global. we call this for names that reference objects external to the graph, like function | STRING |
| HIGH | colossalai/fx/codegen/activation_checkpoint_codegen.py | 0 | delete values after their last use. this ensures that values that are not used in the remainder of the code are freed an | STRING |
| HIGH | colossalai/autochunk/autochunk_codegen.py | 0 | delete values after their last use. this ensures that values that are not used in the remainder of the code are freed an | STRING |
| HIGH | colossalai/_analyzer/fx/codegen.py | 0 | delete values after their last use. this ensures that values that are not used in the remainder of the code are freed an | STRING |
| HIGH | colossalai/booster/plugin/gemini_plugin.py | 0 | save model to checkpoint but only on master process. | STRING |
| HIGH | colossalai/booster/plugin/torch_fsdp_plugin.py | 0 | save model to checkpoint but only on master process. | STRING |
| HIGH | colossalai/booster/plugin/torch_ddp_plugin.py | 0 | save model to checkpoint but only on master process. | STRING |
| HIGH | colossalai/booster/plugin/gemini_plugin.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | colossalai/booster/plugin/dp_plugin_base.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | colossalai/booster/plugin/hybrid_parallel_plugin.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | examples/language/data_utils.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | examples/language/mixtral/data_utils.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | examples/language/deepseek/data_utils.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | examples/language/llama/data_utils.py | 0 | prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `stat | STRING |
| HIGH | colossalai/shardformer/policies/command.py | 0 | if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, a | STRING |
| HIGH | colossalai/shardformer/policies/mistral.py | 0 | if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, a | STRING |
| HIGH | colossalai/shardformer/policies/gpt2.py | 0 | if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, a | STRING |
| HIGH | colossalai/shardformer/policies/t5.py | 0 | if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, a | STRING |
| HIGH | colossalai/shardformer/policies/gptj.py | 0 | if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, a | STRING |
| HIGH | colossalai/shardformer/policies/opt.py | 0 | if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, a | STRING |
| 292 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …heckpoint_io/test_plugins_huggingface_compatibility.py | 78 | def test_huggingface_compatibility(world_size): | CODE |
| LOW | tests/test_checkpoint_io/test_gemini_checkpoint_io.py | 39 | def exam_state_dict_with_origin( | CODE |
| LOW | tests/test_checkpoint_io/test_gemini_checkpoint_io.py | 193 | def exam_lazy_from_pretrained(): | CODE |
| LOW | tests/test_checkpoint_io/test_general_checkpoint_io.py | 23 | def test_unsharded_checkpoint(use_safetensors: bool, use_async: bool): | CODE |
| LOW | tests/test_checkpoint_io/test_general_checkpoint_io.py | 77 | def test_sharded_model_checkpoint(use_safetensors: bool, use_async: bool): | CODE |
| LOW | tests/test_checkpoint_io/test_general_checkpoint_io.py | 117 | def test_sharded_optimizer_checkpoint(use_async: bool): | CODE |
| LOW | tests/test_checkpoint_io/test_general_checkpoint_io.py | 186 | def test_sharded_optimizer_multiple_param_groups(use_async: bool): | CODE |
| LOW | …ts/test_checkpoint_io/test_gemini_torch_compability.py | 24 | def exam_torch_load_from_gemini(shard: bool, model_name: str): | CODE |
| LOW | …ts/test_checkpoint_io/test_gemini_torch_compability.py | 90 | def exam_gemini_load_from_torch(shard: bool, model_name: str): | CODE |
| LOW | tests/test_zero/test_gemini/test_zeroddp_state_dict.py | 18 | def ignore_the_first_parameter(model: torch.nn.Module): | CODE |
| LOW | …sts/test_zero/test_gemini/test_zerooptim_state_dict.py | 23 | def exam_zero_optim_state_dict(placement_config, keep_gathered): | CODE |
| LOW | tests/test_shardformer/test_flash_attention.py | 67 | def post_process_kwargs_for_raw_attn(attn_kwargs: dict): | CODE |
| LOW | tests/test_shardformer/test_with_torch_ddp.py | 18 | def check_shardformer_with_ddp(lazy_init: bool): | CODE |
| LOW | tests/test_shardformer/test_model/_utils.py | 120 | def build_model_from_hybrid_plugin( | CODE |
| LOW | tests/test_shardformer/test_model/_utils.py | 174 | def build_model_from_low_level_zero_plugin( | CODE |
| LOW | tests/test_shardformer/test_model/_utils.py | 200 | def run_forward_backward_with_hybrid_plugin( | CODE |
| LOW | tests/test_shardformer/test_model/_utils.py | 263 | def run_forward_backward_with_low_level_zero_plugin( | CODE |
| LOW | tests/test_shardformer/test_model/_utils.py | 301 | def check_output_hidden_state( | CODE |
| LOW | tests/test_shardformer/test_model/_utils.py | 368 | def get_grad_tensors_for_check( | CODE |
| LOW | …/test_shardformer/test_layer/test_sequence_parallel.py | 173 | def test_all_to_all_attention(): | CODE |
| LOW | tests/test_shardformer/test_layer/test_linear_1d.py | 121 | def check_linear_without_weight_grad_store(lazy_init: bool, seq_parallel_mode: bool): | CODE |
| LOW | tests/test_shardformer/test_layer/test_linear_1d.py | 161 | def check_linear_with_weight_grad_store(lazy_init: bool, seq_parallel_mode: bool): | CODE |
| LOW | tests/test_shardformer/test_layer/test_linear_1d.py | 208 | def check_linear_col_plus_row(lazy_init: bool, seq_parallel_mode: bool, overlap: bool): | CODE |
| LOW | tests/test_shardformer/test_layer/test_dropout.py | 10 | def check_dropout_parallel_input(): | CODE |
| LOW | tests/test_shardformer/test_layer/test_dropout.py | 42 | def check_dropout_replicated_input(): | CODE |
| LOW | tests/test_legacy/test_context/test_hybrid_parallel.py | 32 | def check_pipeline_parallel_rank(rank): | CODE |
| LOW | tests/test_legacy/test_context/test_hybrid_parallel.py | 44 | def check_model_parallel_rank(rank): | CODE |
| LOW | tests/test_legacy/test_context/test_hybrid_parallel.py | 51 | def check_tensor_parallel_rank(rank): | CODE |
| LOW | tests/test_legacy/test_utils/test_memory.py | 9 | def _run_colo_set_process_memory_fraction_and_colo_device_memory_capacity(): | CODE |
| LOW | …est_legacy/test_utils/test_activation_checkpointing.py | 45 | def test_activation_checkpointing(cpu_offload, use_reentrant): | CODE |
| LOW | tests/test_legacy/test_layers/test_cache_embedding.py | 224 | def run_parallel_freq_aware_embed_tablewise(rank, world_size): | CODE |
| LOW | tests/test_legacy/test_layers/test_cache_embedding.py | 310 | def run_parallel_freq_aware_embed_columnwise(rank, world_size): | CODE |
| LOW | tests/test_legacy/test_layers/test_cache_embedding.py | 389 | def test_parallel_freq_aware_embed(world_size): | CODE |
| LOW | …legacy/test_layers/test_1d/checks_1d/check_layer_1d.py | 203 | def check_vocab_parallel_embed(): | CODE |
| LOW | …legacy/test_layers/test_1d/checks_1d/check_layer_1d.py | 245 | def check_classifier_no_given_weight(): | CODE |
| LOW | …legacy/test_layers/test_1d/checks_1d/check_layer_1d.py | 311 | def check_vocab_parallel_classifier_no_given_weight(): | CODE |
| LOW | …legacy/test_layers/test_1d/checks_1d/check_layer_1d.py | 371 | def check_classifier_given_embed_weight(): | CODE |
| LOW | …legacy/test_layers/test_1d/checks_1d/check_layer_1d.py | 422 | def check_vocab_parallel_classifier_given_embed_weight(): | CODE |
| LOW | …legacy/test_layers/test_1d/checks_1d/check_layer_1d.py | 474 | def check_vocab_parallel_loss(): | CODE |
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| LOW | tests/test_legacy/test_layers/test_2d/test_2d.py | 51 | def check_layer_and_operation(rank, world_size, port): | CODE |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 276 | def check_vocab_parallel_embed(): | CODE |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 323 | def check_classifier_no_given_weight(): | CODE |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 401 | def check_vocab_parallel_classifier_no_given_weight(): | CODE |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 469 | def check_classifier_given_embed_weight(): | CODE |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 521 | def check_vocab_parallel_classifier_given_embed_weight(): | CODE |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 610 | def check_vocab_parallel_loss(): | CODE |
| LOW | tests/test_legacy/test_layers/test_2p5d/test_2p5d.py | 39 | def check_layer_and_operation(rank, world_size, port): | CODE |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 280 | def check_vocab_parallel_embed(): | CODE |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 328 | def check_classifier_no_given_weight(): | CODE |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 407 | def check_vocab_parallel_classifier_no_given_weight(): | CODE |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 474 | def check_classifier_given_embed_weight(): | CODE |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 526 | def check_vocab_parallel_classifier_given_embed_weight(): | CODE |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 615 | def check_vocab_parallel_loss(): | CODE |
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| LOW | …legacy/test_layers/test_3d/checks_3d/check_layer_3d.py | 206 | def check_classifier_no_given_weight(): | CODE |
| LOW | …legacy/test_layers/test_3d/checks_3d/check_layer_3d.py | 306 | def check_vocab_parallel_classifier_no_given_weight(): | CODE |
| LOW | …legacy/test_layers/test_3d/checks_3d/check_layer_3d.py | 413 | def check_classifier_given_embed_weight(): | CODE |
| LOW | …legacy/test_layers/test_3d/checks_3d/check_layer_3d.py | 497 | def check_vocab_parallel_classifier_given_embed_weight(): | CODE |
| LOW | …legacy/test_layers/test_3d/checks_3d/check_layer_3d.py | 747 | def check_vocab_parallel_embed(): | CODE |
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| LOW | tests/kit/model_zoo/registry.py | 5 | __all__ = ["ModelZooRegistry", "ModelAttribute", "model_zoo"] | CODE |
| LOW | tests/kit/model_zoo/__init__.py | 33 | __all__ = ["model_zoo", "run_fwd", "run_fwd_bwd", "COMMON_MODELS", "IS_FAST_TEST"] | CODE |
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| LOW | colossalai/fx/tracer/tracer.py | 32 | __all__ = ["ColoTracer"] | CODE |
| LOW | colossalai/fx/profiler/constants.py | 3 | __all__ = ["ALIAS_ATEN", "INPLACE_NEW", "INPLACE_MATH_ATEN", "CLONE_ATEN", "RELU_LIKE_OPS", "RELU_LIKE_MOD"] | CODE |
| LOW | colossalai/fx/profiler/tensor.py | 10 | __all__ = ["MetaTensor"] | CODE |
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| LOW | colossalai/fx/profiler/shard_utils.py | 10 | __all__ = ["calculate_fwd_in", "calculate_fwd_tmp", "calculate_fwd_out"] | CODE |
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| LOW | colossalai/fx/profiler/experimental/constants.py | 5 | __all__ = ["INPLACE_OPS", "INPLACE_METHOD", "NON_INPLACE_METHOD"] | CODE |
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| LOW | colossalai/booster/plugin/torch_fsdp_plugin.py | 37 | __all__ = ["TorchFSDPPlugin"] | CODE |
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| LOW | colossalai/booster/plugin/low_level_zero_plugin.py | 49 | __all__ = ["LowLevelZeroPlugin"] | CODE |
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| LOW | colossalai/booster/mixed_precision/fp16_torch.py | 13 | __all__ = ["FP16_Torch_MixedPrecision", "TorchAMPOptimizer", "TorchAMPModule"] | CODE |
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| LOW | colossalai/shardformer/policies/mistral.py | 28 | __all__ = ["MistralPolicy", "MistralModelPolicy", "MistralForCausalLMPolicy", "MistralForSequenceClassificationPolicy"] | CODE |
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| LOW | colossalai/nn/optimizer/fused_lamb.py | 52 | CODE | |
| LOW | colossalai/nn/optimizer/hybrid_adam.py | 63 | CODE | |
| LOW | colossalai/nn/lr_scheduler/onecycle.py | 68 | CODE | |
| LOW | colossalai/fx/_meta_regist_12.py | 161 | CODE | |
| LOW | colossalai/fx/_meta_regist_12.py | 178 | CODE | |
| LOW | colossalai/fx/profiler/profiler.py | 214 | CODE | |
| LOW | colossalai/booster/plugin/gemini_plugin.py | 442 | CODE | |
| LOW | colossalai/booster/plugin/moe_hybrid_parallel_plugin.py | 40 | CODE | |
| LOW | colossalai/booster/plugin/moe_hybrid_parallel_plugin.py | 177 | CODE | |
| LOW | colossalai/booster/plugin/torch_fsdp_plugin.py | 472 | CODE | |
| LOW | colossalai/booster/plugin/low_level_zero_plugin.py | 407 | CODE | |
| LOW | colossalai/booster/plugin/hybrid_parallel_plugin.py | 491 | CODE | |
| LOW | colossalai/booster/plugin/hybrid_parallel_plugin.py | 667 | CODE | |
| LOW | colossalai/booster/plugin/hybrid_parallel_plugin.py | 1000 | CODE | |
| LOW | colossalai/booster/mixed_precision/fp16_apex.py | 26 | CODE | |
| LOW | colossalai/shardformer/modeling/command.py | 40 | CODE | |
| LOW | colossalai/shardformer/modeling/command.py | 244 | CODE | |
| LOW | colossalai/shardformer/modeling/command.py | 433 | CODE | |
| LOW | colossalai/shardformer/modeling/command.py | 576 | CODE | |
| LOW | colossalai/shardformer/modeling/mistral.py | 25 | CODE | |
| LOW | colossalai/shardformer/modeling/mistral.py | 187 | CODE | |
| LOW | colossalai/shardformer/modeling/mistral.py | 276 | CODE | |
| LOW | colossalai/shardformer/modeling/mistral.py | 379 | CODE | |
| LOW | colossalai/shardformer/modeling/mistral.py | 560 | CODE | |
| LOW | colossalai/shardformer/modeling/gpt2.py | 116 | CODE | |
| LOW | colossalai/shardformer/modeling/gpt2.py | 344 | CODE | |
| LOW | colossalai/shardformer/modeling/gpt2.py | 433 | CODE | |
| LOW | colossalai/shardformer/modeling/gpt2.py | 527 | CODE | |
| LOW | colossalai/shardformer/modeling/gpt2.py | 618 | CODE | |
| LOW | colossalai/shardformer/modeling/gpt2.py | 693 | CODE | |
| LOW | colossalai/shardformer/modeling/t5.py | 32 | CODE | |
| LOW | colossalai/shardformer/modeling/t5.py | 264 | CODE | |
| 294 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | …t_hybrid_parallel_grad_clip_norm/test_amp_optimizer.py | 74 | # Create a list of parameter-gradient pairs containing working parameters and their gradients | COMMENT |
| MEDIUM | …est_tensor_shard/test_metainfo/test_linear_metainfo.py | 23 | """This function is for linear memory test | STRING |
| MEDIUM⚡ | …est_tensor_shard/test_metainfo/test_linear_metainfo.py | 61 | """This function is for linear memory test | STRING |
| MEDIUM | …st_tensor_shard/test_metainfo/test_pooling_metainfo.py | 14 | """This function is for AdaptiveAvgPool memory test | STRING |
| MEDIUM | …st_tensor_shard/test_metainfo/test_pooling_metainfo.py | 55 | """This function is for MaxPool memory test | STRING |
| MEDIUM | …/test_tensor_shard/test_metainfo/test_conv_metainfo.py | 23 | """This function is for conv memory test | STRING |
| MEDIUM | …/test_tensor_shard/test_metainfo/test_conv_metainfo.py | 65 | """This function is for conv function memory test | STRING |
| MEDIUM | …hard/test_metainfo/test_binary_elementwise_metainfo.py | 24 | """This function is for binary elementwise ops memory test | STRING |
| MEDIUM | …/test_tensor_shard/test_metainfo/test_norm_metainfo.py | 18 | """This function is for batchnorm memory test | STRING |
| MEDIUM | tests/test_infer/test_streamingllm.py | 115 | result_list = manager.list([-1] * 1) # Create a shared list | CODE |
| MEDIUM | tests/test_infer/test_inference_engine.py | 90 | result_list = manager.list([-1] * world_size) # Create a shared list | CODE |
| MEDIUM | tests/test_infer/test_models/test_baichuan.py | 82 | result_list = manager.list([-1] * world_size) # Create a shared list | CODE |
| MEDIUM | tests/test_infer/test_models/test_custom_model.py | 84 | result_list = manager.list([-1] * world_size) # Create a shared list | CODE |
| MEDIUM | tests/test_infer/test_kernels/triton/kernel_utils.py | 7 | # This function is adapted from src/transformers/models/llama/modeling_llama.py | COMMENT |
| MEDIUM | colossalai/fx/codegen/activation_checkpoint_codegen.py | 168 | """This function is to find the offload regions | STRING |
| MEDIUM | colossalai/booster/plugin/hybrid_parallel_plugin.py | 1403 | # Create a context for gradient synchronization based on the optimizer type. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gpt2.py | 137 | # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2Model.forward. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gpt2.py | 555 | # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2ForQuestionAnswering.forw | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gpt2.py | 643 | # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2ForTokenClassification.fo | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gpt2.py | 718 | # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2ForSequenceClassification | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/t5.py | 54 | # This function is modified on the basis of transformers.models.t5.modeling_t5.T5Stack.forward. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/t5.py | 290 | # This function is modified on the basis of transformers.models.t5.modeling_t5.T5Model.forward. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/t5.py | 430 | # This function is modified on the basis of transformers.models.t5.modeling_t5.T5ForConditionalGeneration.forwar | STRING |
| MEDIUM | colossalai/shardformer/modeling/gptj.py | 99 | # This function is modified on the v4.51.3 transformers.models.gptj.modeling_gptj.GPTJModel.forward. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gptj.py | 288 | # This function is modified on the basis of transformers.models.gptj.modeling_gptj.GPTJForCausalLM.forward. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gptj.py | 381 | # This function is modified on the v4.51.3 transformers.models.gptj.modeling_gptj.GPTJForSequenceClassification. | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gptj.py | 503 | # This function is modified on the basis of transformers.models.gptj.modeling_gptj.GPTJForQuestionAnswering.forw | COMMENT |
| MEDIUM | colossalai/shardformer/modeling/gptj.py | 583 | # This function is modified on the v4.51.3 transformers.models.gptj.modeling_gptj.GPTJAttention.forward. | STRING |
| MEDIUM | colossalai/legacy/pipeline/middleware/topo.py | 127 | # This class is a middleware between partition splitter | COMMENT |
| MEDIUM | colossalai/legacy/context/parallel_context.py | 25 | """This class provides interface functions for users to get the parallel context, | STRING |
| MEDIUM | colossalai/legacy/context/random/seed_manager.py | 11 | """This class is a manager of all random seeds involved in the system. | STRING |
| MEDIUM | colossalai/legacy/nn/loss/loss_1d.py | 30 | # Create a mask of valid vocab ids (1 means it needs to be masked). | COMMENT |
| MEDIUM | …lossalai/legacy/zero/sharded_optim/sharded_optim_v2.py | 189 | # This function is called except the last stage of pipeline parallel | COMMENT |
| MEDIUM | colossalai/legacy/amp/naive_amp/_fp16_optimizer.py | 128 | # Create a fp32 copy | COMMENT |
| MEDIUM | colossalai/utils/tensor_detector/tensor_detector.py | 17 | """This class is a detector to detect tensor on different devices. | STRING |
| MEDIUM | colossalai/quantization/bnb.py | 219 | # Create a copy of the model | STRING |
| MEDIUM | colossalai/zero/gemini/gemini_ddp.py | 261 | """This function is only triggered for inference.""" | STRING |
| MEDIUM | colossalai/zero/gemini/gemini_ddp.py | 296 | """This function is only triggered for inference.""" | STRING |
| MEDIUM | colossalai/zero/gemini/gemini_optimizer.py | 306 | # This function is called except the last stage of pipeline parallel | COMMENT |
| MEDIUM | …ssalai/zero/gemini/memory_tracer/memstats_collector.py | 76 | # The following code work for ZeroInitContext, which is deprecated in v0.1.12 | COMMENT |
| MEDIUM | colossalai/lazy/lazy_init.py | 80 | """This class is only for correctness verification.""" | STRING |
| MEDIUM | colossalai/inference/batch_bucket.py | 483 | ########## The following methods are expected to be used in modeling ########### | COMMENT |
| MEDIUM | colossalai/tensor/comm_spec.py | 423 | # Create a new member `logical_process_axes` to distinguish from original flatten | COMMENT |
| MEDIUM | …/tutorial/sequence_parallel/loss_func/cross_entropy.py | 15 | # Create a mask of valid vocab ids (1 means it needs to be masked). | COMMENT |
| MEDIUM | …ce_parallel/data/datasets/test/test_indexed_dataset.py | 1 | # This file isn't really a formal automated test, it's just a place to | COMMENT |
| MEDIUM | examples/images/diffusion/main.py | 56 | # Create an ArgumentParser object with specifies kwargs | COMMENT |
| MEDIUM | examples/images/diffusion/main.py | 404 | # Create a list of exponentially increasing log steps, starting from 1 and ending at batch_frequency | COMMENT |
| MEDIUM | examples/images/diffusion/main.py | 661 | # Create the checkpoint and configuration directories within the log directory. | COMMENT |
| MEDIUM | examples/images/diffusion/main.py | 755 | # Create an empty OmegaConf configuration object | COMMENT |
| MEDIUM | examples/images/diffusion/main.py | 796 | # Create a Trainer object with the specified command-line arguments and keyword arguments, and set the log direc | COMMENT |
| MEDIUM | examples/images/diffusion/main.py | 800 | # Create a data module based on the configuration file | COMMENT |
| MEDIUM | examples/images/diffusion/ldm/data/lsun.py | 10 | # This class is used to create a dataset of images from LSUN dataset for training | COMMENT |
| MEDIUM | examples/images/dreambooth/train_dreambooth.py | 689 | # Create the pipeline using using the trained modules and save it. | COMMENT |
| MEDIUM | examples/images/dreambooth/train_dreambooth_inpaint.py | 726 | # Create the pipeline using using the trained modules and save it. | COMMENT |
| MEDIUM | examples/language/gpt/titans/model/embed.py | 262 | # Create a mask of valid vocab ids (1 means it needs to be masked). | COMMENT |
| MEDIUM | examples/language/gpt/gemini/commons/model_zoo.py | 5 | ## Define the Model and Loss Based on Huggingface transformers GPT2LMHeadModel | COMMENT |
| MEDIUM | …anguage/gpt/experiments/pipeline_parallel/model_zoo.py | 5 | ## Define the Model and Loss Based on Huggingface transformers GPT2LMHeadModel | COMMENT |
| MEDIUM | …ples/community/roberta/pretraining/model/deberta_v2.py | 102 | >>> # Create a mask | STRING |
| MEDIUM | …ons/ColossalQA/colossalqa/retrieval_conversation_en.py | 31 | # Define the retriever | COMMENT |
| MEDIUM | …ons/ColossalQA/colossalqa/retrieval_conversation_en.py | 34 | # Define the chain to preprocess the input | COMMENT |
| 15 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | colossalai/pipeline/schedule/_utils.py | 72 | Get the batch size (size of dimension-0) of the first tensor in the batch. Args: batch (Any): Batch to be i | STRING |
| HIGH | colossalai/context/config.py | 52 | Reads a python file and constructs a corresponding :class:`Config` object. Args: filename (str): Na | STRING |
| HIGH | colossalai/shardformer/layer/normalization.py | 140 | Convert a native PyTorch layer normalization module to a specific layer normalization module, and optio | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 130 | Returns the local rank of the current device. Args: parallel_mode (:class:`colossalai.legacy.contex | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 160 | Returns the global rank of the next device. Args: parallel_mode (:class:`colossalai.legacy.context. | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 182 | Returns the global rank of the previous device. Args: parallel_mode (:class:`colossalai.legacy.cont | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 204 | Returns a boolean value indicating whether the current device is the first one among its group for `parallel_mod | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 222 | Returns a boolean value indicating whether the current device is the last one among its group for `parallel_mode | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 256 | Returns the world size for `parallel_mode`. Args: parallel_mode (:class:`colossalai.legacy.context. | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 286 | Returns the group of the current device for `parallel_mode`. Args: parallel_mode (:class:`colossala | STRING |
| HIGH | colossalai/legacy/context/parallel_context.py | 342 | Returns the rank of the current device for `parallel_mode` in the group. Args: parallel_mode (:clas | STRING |
| HIGH | colossalai/legacy/utils/checkpointing.py | 221 | Loads training states from a checkpoint file. Args: file: a file-like object (has to implement read(), read | STRING |
| HIGH | …lossalai/legacy/zero/gemini/tensor_placement_policy.py | 64 | Evict tensors from CUDA device. Args: hold_cuda_tensor_list (List[StatefulTensor]): the li | STRING |
| HIGH | colossalai/legacy/registry/registry.py | 28 | Registers a module represented in `module_class`. Args: module_class (class): The module to be regi | STRING |
| HIGH | colossalai/legacy/registry/registry.py | 45 | Retrieves a module with name `module_name` and returns the module if it has already been registered before. | STRING |
| HIGH | colossalai/legacy/builder/builder.py | 10 | Returns an object of :class:`module` constructed from `config`. Args: module: A python or user-defined clas | STRING |
| HIGH | colossalai/legacy/builder/builder.py | 27 | Returns an object constructed from `config`, the type of the object is specified by `registry`. Note: t | STRING |
| HIGH | colossalai/cli/launcher/run.py | 59 | Parse an inclusion or exclusion string and filter a hostfile dictionary. Examples: include_str="worker-0,wo | STRING |
| HIGH | colossalai/_analyzer/fx/tracer/symbolic_trace.py | 37 | Traces a ``torch.nn.Module`` or a function and returns a ``GraphModule`` with ``Node``s and ``MetaInfo`` attach | STRING |
| HIGH | colossalai/_analyzer/fx/passes/graph_profile.py | 233 | Run a specific node ``n`` and profile its execution time and memory usage. Calls into call_function, ca | STRING |
| HIGH | …lossalai/auto_parallel/checkpoint/ckpt_solver_rotor.py | 311 | Backtrack the cost table and retrieve the optimal checkpointing strategy. Args: chain (Chain): A ba | STRING |
| HIGH | colossalai/zero/gemini/placement_policy.py | 158 | Evict tensors from CUDA device. Args: can_evict_chunks (List[StatefulTensor]): the list of | STRING |
| HIGH | colossalai/tensor/d_tensor/layout_converter.py | 453 | Check if the process groups required for sharding have been deleted by torch.distributed.destroy_proces | STRING |
| HIGH | …/ColossalChat/coati/distributed/reward/reward_utils.py | 80 | Modified from: https://gist.github.com/lewtun/9c2ce1937b741404090a3dc4c7c022b3 Retrieves the content from the l | STRING |
| HIGH | applications/ColossalChat/coati/models/generation.py | 279 | Generates new tokens using a streaming approach. Args: model (Any): The model used for token generatio | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …est_checkpoint_io/test_low_level_zero_checkpoint_io.py | 149 | except Exception as e: | CODE |
| MEDIUM | …est_checkpoint_io/test_low_level_zero_checkpoint_io.py | 95 | def run_fn(stage, shard, offload, model_fn, data_gen_fn, output_transform_fn, lo | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_gpt2.py | 226 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_gpt2.py | 271 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_command.py | 286 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_llama.py | 81 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_llama.py | 305 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_llama.py | 359 | except Exception as e: | CODE |
| LOW | …sts/test_shardformer/test_model/test_shard_chatglm2.py | 241 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_qwen3.py | 214 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_qwen3.py | 263 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_qwen2.py | 218 | except Exception as e: | CODE |
| LOW | tests/test_shardformer/test_model/test_shard_qwen2.py | 267 | except Exception as e: | CODE |
| LOW | tests/test_booster/test_plugin/test_gemini_plugin.py | 62 | except Exception as e: | CODE |
| MEDIUM | tests/test_booster/test_plugin/test_gemini_plugin.py | 19 | def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn, zero_size, t | CODE |
| LOW | tests/test_booster/test_plugin/test_3d_plugin.py | 82 | except Exception as e: | CODE |
| MEDIUM | tests/test_booster/test_plugin/test_3d_plugin.py | 48 | def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn) -> Optional[ | CODE |
| LOW | …test_booster/test_plugin/test_low_level_zero_plugin.py | 56 | except Exception as e: | CODE |
| LOW | tests/test_fx/test_tracer/test_patched_op.py | 13 | except Exception as e: | CODE |
| MEDIUM | tests/test_fx/test_tracer/test_patched_op.py | 9 | def _run(data, patch_fn): | CODE |
| LOW | tests/test_fx/test_tracer/test_patched_module.py | 16 | except Exception as e: | CODE |
| MEDIUM | tests/test_fx/test_tracer/test_patched_module.py | 7 | def _run(data, module, patch_fn): | CODE |
| LOW | …racer/test_torchvision_model/test_torchvision_model.py | 41 | except Exception as e: | CODE |
| LOW | …s/test_fx/test_tracer/test_hf_model/hf_tracer_utils.py | 23 | except Exception as e: | CODE |
| LOW | …ts/test_fx/test_pipeline/test_timm_model/timm_utils.py | 29 | except Exception as e: | CODE |
| LOW | tests/test_fx/test_pipeline/test_topo/topo_utils.py | 45 | except Exception as e: | CODE |
| LOW | tests/test_fx/test_pipeline/test_hf_model/hf_utils.py | 32 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_lamb.py | 148 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_lamb.py | 230 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_lamb.py | 250 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_galore.py | 80 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_galore.py | 171 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_galore.py | 245 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_galore.py | 264 | except Exception as e: | CODE |
| LOW | tests/test_optimizer/test_dist_galore.py | 289 | except Exception as e: | CODE |
| LOW | …est_autochunk_diffuser/benchmark_autochunk_diffuser.py | 134 | except Exception as e: | CODE |
| LOW | …t_autochunk_alphafold/benchmark_autochunk_alphafold.py | 123 | except Exception as e: | CODE |
| LOW | …tochunk_transformer/benchmark_autochunk_transformer.py | 135 | except Exception as e: | CODE |
| LOW | colossalai/fx/tracer/experimental.py | 589 | except Exception as e: | CODE |
| LOW | colossalai/fx/tracer/tracer.py | 312 | except Exception as e: | CODE |
| LOW | colossalai/shardformer/layer/parallel_module.py | 152 | except Exception as ex: | STRING |
| LOW | colossalai/shardformer/layer/parallel_module.py | 330 | except Exception as ex: | STRING |
| LOW | colossalai/shardformer/layer/normalization.py | 22 | except Exception: | CODE |
| LOW | colossalai/shardformer/shard/sharder.py | 200 | except Exception as e: | STRING |
| LOW | …lossalai/legacy/zero/sharded_model/sharded_model_v2.py | 208 | except Exception as e: | STRING |
| LOW | …lossalai/legacy/zero/sharded_model/sharded_model_v2.py | 556 | except Exception as ex: | STRING |
| LOW | colossalai/legacy/inference/async_manager.py | 148 | except Exception: | CODE |
| MEDIUM | colossalai/legacy/inference/async_manager.py | 135 | def start_dynamic_batching(args, tp_engine, waiting_req_list): | CODE |
| LOW | colossalai/legacy/inference/manager.py | 293 | except Exception: | CODE |
| MEDIUM | colossalai/legacy/inference/manager.py | 280 | def start_dynamic_batching(args, tp_engine, waiting_req_list): | CODE |
| LOW | …egacy/inference/quant/smoothquant/models/base_model.py | 228 | except Exception as e: | CODE |
| LOW | colossalai/legacy/builder/builder.py | 55 | except Exception as e: | STRING |
| MEDIUM | colossalai/legacy/builder/builder.py | 56 | print(f"An error occurred when building {mod_type} from registry {registry.name}", flush=True) | STRING |
| LOW | colossalai/utils/safetensors.py | 12 | except Exception: | CODE |
| LOW | colossalai/cli/launcher/multinode_runner.py | 55 | except Exception as e: | CODE |
| LOW | colossalai/_analyzer/fx/graph_module.py | 71 | except Exception as e: | CODE |
| MEDIUM | colossalai/_analyzer/fx/graph_module.py | 65 | def __call__(self, obj, *args, **kwargs): | CODE |
| LOW | colossalai/_analyzer/fx/passes/graph_profile.py | 257 | except Exception as e: | CODE |
| LOW | colossalai/zero/gemini/gemini_ddp.py | 727 | except Exception as ex: | STRING |
| LOW | colossalai/lazy/pretrained.py | 259 | except Exception: | CODE |
| 51 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_fx/test_graph_manipulation.py | 42 | if node.op in ("placeholder", "output"): | CODE |
| LOW | tests/test_fx/test_meta_info_prop.py | 33 | if node.op == "placeholder": | CODE |
| LOW | tests/test_fx/test_pipeline/test_topo/topo_utils.py | 66 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/proxy.py | 68 | if self.node.op == "placeholder": | CODE |
| LOW | colossalai/fx/tracer/experimental.py | 121 | if self.node.op == "placeholder": | CODE |
| LOW | colossalai/fx/tracer/experimental.py | 213 | if kind == "placeholder": | CODE |
| LOW | colossalai/fx/tracer/experimental.py | 338 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/tracer/experimental.py | 499 | if kind == "placeholder": | CODE |
| LOW | colossalai/fx/tracer/experimental.py | 526 | if kind == "placeholder" and target in meta_args and meta_args[target].is_meta: | CODE |
| LOW | colossalai/fx/tracer/tracer.py | 219 | if kind == "placeholder" and target in self.meta_args and self.meta_args[target].is_meta: | CODE |
| LOW | colossalai/fx/tracer/tracer.py | 418 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/tracer/_meta_trace.py | 61 | "placeholder", "placeholder", (graph._root,), name=namespace.create_name(name, tensor) | CODE |
| LOW | colossalai/fx/passes/split_module.py | 163 | if node.op in ["placeholder"]: | CODE |
| LOW | colossalai/fx/passes/split_module.py | 246 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/passes/utils.py | 46 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/passes/utils.py | 71 | if node.op == "placeholder": | CODE |
| LOW⚡ | colossalai/fx/passes/passes_for_gpt2_test.py | 56 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/passes/passes_for_gpt2_test.py | 116 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/passes/passes_for_gpt2_test.py | 202 | if n.op != "placeholder" and n._fx_partition > partition_name: | CODE |
| LOW | colossalai/fx/passes/passes_for_gpt2_test.py | 236 | if node.op in ["placeholder"]: | CODE |
| LOW | colossalai/fx/passes/passes_for_gpt2_test.py | 322 | if node.op == "placeholder": | CODE |
| LOW | colossalai/fx/passes/adding_split_node_pass.py | 265 | if node.op == "placeholder": | CODE |
| LOW⚡ | …x/passes/experimental/adding_shape_consistency_pass.py | 51 | if node.op != "placeholder": | CODE |
| LOW⚡ | …x/passes/experimental/adding_shape_consistency_pass.py | 53 | input_specs_node = mod_graph.create_node("placeholder", target="sharding_spec_convert_dict") | CODE |
| LOW⚡ | …x/passes/experimental/adding_shape_consistency_pass.py | 54 | origin_specs_node = mod_graph.create_node("placeholder", target="origin_node_sharding_spec_dict") | CODE |
| LOW | colossalai/fx/codegen/activation_checkpoint_codegen.py | 950 | if user.op == "placeholder": | CODE |
| LOW | colossalai/fx/codegen/activation_checkpoint_codegen.py | 965 | if node.op == "placeholder": | CODE |
| LOW⚡ | colossalai/fx/codegen/activation_checkpoint_codegen.py | 598 | if input_node.op != "placeholder": | STRING |
| LOW | colossalai/fx/codegen/activation_checkpoint_codegen.py | 733 | if user.op == "placeholder": | STRING |
| LOW | colossalai/fx/codegen/activation_checkpoint_codegen.py | 748 | if node.op == "placeholder": | STRING |
| LOW | colossalai/fx/profiler/profiler.py | 222 | "placeholder", | CODE |
| LOW | colossalai/fx/profiler/profiler.py | 223 | "placeholder", | CODE |
| LOW | colossalai/legacy/pipeline/middleware/adaptor/fx.py | 102 | if node.op == "placeholder": | CODE |
| LOW | colossalai/autochunk/estimate_memory.py | 35 | if n.op == "placeholder": | CODE |
| LOW | colossalai/autochunk/estimate_memory.py | 51 | elif node.op == "placeholder": | CODE |
| LOW⚡ | colossalai/autochunk/estimate_memory.py | 115 | if n.op in ["placeholder", "get_attr", "output"]: | CODE |
| LOW | colossalai/autochunk/estimate_memory.py | 198 | if node.op == "placeholder": | CODE |
| LOW | colossalai/autochunk/utils.py | 7 | NON_COMPUTE_OP = ["placeholder", "get_attr", "output"] | CODE |
| LOW⚡ | colossalai/autochunk/utils.py | 131 | if "placeholder" in node.op: | CODE |
| LOW⚡ | colossalai/autochunk/utils.py | 145 | if n.op == "placeholder": | CODE |
| LOW | colossalai/autochunk/trace_indice.py | 841 | if node.op == "placeholder": | CODE |
| LOW | colossalai/autochunk/autochunk_codegen.py | 484 | if user.op == "placeholder": | CODE |
| LOW | colossalai/autochunk/autochunk_codegen.py | 500 | if node.op == "placeholder": | CODE |
| LOW | colossalai/_analyzer/fx/codegen.py | 351 | if user.op == "placeholder": | CODE |
| LOW | colossalai/_analyzer/fx/codegen.py | 366 | if node.op == "placeholder": | CODE |
| LOW | colossalai/_analyzer/fx/tracer/proxy.py | 78 | if self.node.op == "placeholder": | CODE |
| LOW | colossalai/_analyzer/fx/tracer/tracer.py | 116 | if kind == "placeholder": | CODE |
| LOW | colossalai/_analyzer/fx/tracer/tracer.py | 207 | if node.op == "placeholder": | CODE |
| LOW | colossalai/_analyzer/fx/tracer/tracer.py | 310 | if node.op == "placeholder": | CODE |
| LOW | colossalai/auto_parallel/checkpoint/ckpt_solver_base.py | 162 | next(node for node in self.graph.nodes if node.name == name).op == "placeholder" | CODE |
| LOW | colossalai/auto_parallel/checkpoint/ckpt_solver_base.py | 175 | if n.op != "placeholder" and n.op != "output": | CODE |
| LOW | colossalai/auto_parallel/checkpoint/ckpt_solver_base.py | 177 | if n_par.op != "placeholder" and n_par.name not in self.cnode: | CODE |
| LOW | …lossalai/auto_parallel/checkpoint/ckpt_solver_rotor.py | 172 | if node.op == "placeholder": | CODE |
| LOW | colossalai/auto_parallel/passes/meta_info_prop.py | 27 | "placeholder": self.placeholder_handler, | CODE |
| LOW⚡ | …salai/auto_parallel/passes/runtime_preparation_pass.py | 122 | if node.op != "placeholder": | CODE |
| LOW⚡ | …salai/auto_parallel/passes/runtime_preparation_pass.py | 124 | input_specs_node = mod_graph.create_node("placeholder", target="sharding_spec_convert_dict") | CODE |
| LOW⚡ | …salai/auto_parallel/passes/runtime_preparation_pass.py | 125 | origin_specs_node = mod_graph.create_node("placeholder", target="origin_node_sharding_spec_dict") | CODE |
| LOW⚡ | …salai/auto_parallel/passes/runtime_preparation_pass.py | 126 | comm_actions_dict_node = mod_graph.create_node("placeholder", target="comm_actions_dict") | CODE |
| LOW⚡ | …parallel/tensor_shard/solver/strategies_constructor.py | 78 | if node.op in ("placeholder", "get_attr", "output"): | CODE |
| LOW | …parallel/tensor_shard/solver/strategies_constructor.py | 99 | elif node.op == "placeholder": | CODE |
| 35 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 641 | out_grad = torch.chunk(out_grad, DEPTH, dim=0)[i] | COMMENT |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 661 | # ) | COMMENT |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 681 | # out.backward(grad) | COMMENT |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 701 | # torch.distributed.broadcast(A_master, src=0) | COMMENT |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 721 | # INPUT_SIZE = HIDDEN_SIZE | COMMENT |
| LOW | …legacy/test_layers/test_2d/checks_2d/check_layer_2d.py | 741 | # mask_shape = (BATCH_SIZE // DEPTH, NUM_ATTENTION_HEADS // DEPTH, SEQ_LENGTH, SEQ_LENGTH) | COMMENT |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 661 | COMMENT | |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 681 | # assert out.shape == (BATCH_SIZE // TESSERACT_DIM, SEQ_LENGTH, INPUT_SIZE // TESSERACT_DIM) | COMMENT |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 701 | # HIDDEN_SIZE, | COMMENT |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 721 | # grad = torch.randn(grad_shape, dtype=dtype, device=device) | COMMENT |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 741 | # attention_dropout_prob=0.5, | COMMENT |
| LOW | …/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py | 761 | # grad_shape = out.shape | COMMENT |
| LOW | …rallel/test_tensor_shard/test_solver_with_resnet_v2.py | 21 | mesh_shape = (2, 4) | COMMENT |
| LOW | …rallel/test_tensor_shard/test_solver_with_resnet_v2.py | 41 | # %layer1_0_conv2 : [#users=1] = call_module[target=layer1.0.conv2](args = (%layer1_0_relu,), kwargs = {}) | COMMENT |
| LOW | tests/kit/model_zoo/transformers/mistral.py | 1 | import torch | COMMENT |
| LOW | tests/kit/model_zoo/transformers/whisper.py | 1 | import torch | COMMENT |
| LOW | tests/kit/model_zoo/transformers/deepseek.py | 1 | # modified from tests/kit/model_zoo/transformers/mistral.py | COMMENT |
| LOW | tests/kit/model_zoo/transformers/bert.py | 1 | import torch | COMMENT |
| LOW | tests/kit/model_zoo/transformers/deepseek_v3.py | 1 | # modified from tests/kit/model_zoo/transformers/mistral.py | COMMENT |
| LOW | tests/kit/model_zoo/transformers/sam.py | 1 | import torch | COMMENT |
| LOW | tests/kit/model_zoo/transformers/mixtral.py | 1 | # modified from tests/kit/model_zoo/transformers/mistral.py | COMMENT |
| LOW | tests/kit/model_zoo/transformers/mixtral.py | 81 | # name="transformers_mixtral_for_sequence_classification", | COMMENT |
| LOW | tests/kit/model_zoo/transformers/blip2.py | 1 | import torch | COMMENT |
| LOW | tests/test_tensor/test_comm_spec_apply.py | 81 | if rank in (0, 1): | COMMENT |
| LOW | tests/test_tensor/test_dtensor/test_comm_spec.py | 61 | sharded_tensor_1 = torch.ones(2, 1) * 3 | COMMENT |
| LOW | tests/test_fx/test_tracer/test_bias_addition_module.py | 41 | # %linear : [#users=1] = call_function[target=torch._C._nn.linear](args = (%x, %linear_weight), kwargs = {}) | COMMENT |
| LOW | …/test_fx/test_profiler/test_profiler_meta_info_prop.py | 61 | torch.cuda.reset_peak_memory_stats() | COMMENT |
| LOW | …/test_fx/test_profiler/test_profiler_meta_info_prop.py | 101 | # If we need to dive deep into the memory usage by | COMMENT |
| LOW | …e/en/features/mixed_precision_training_with_booster.md | 221 | ```python | COMMENT |
| LOW | extensions/csrc/common/micros.h | 101 | // https://github.com/pytorch/pytorch/commit/3aeb78079bcd68282fe9117088e138b77318e288 | COMMENT |
| LOW | extensions/csrc/common/micros.h | 221 | } else { \ | COMMENT |
| LOW | extensions/csrc/funcs/cast_functor.h | 1 | #pragma once | COMMENT |
| LOW | extensions/csrc/funcs/binary_functor.h | 1 | #pragma once | COMMENT |
| LOW | extensions/csrc/funcs/ternary_functor.h | 1 | #pragma once | COMMENT |
| LOW | extensions/csrc/funcs/unary_functor.h | 1 | #pragma once | COMMENT |
| LOW | extensions/csrc/kernel/cuda/attention/attention_utils.h | 21 | COMMENT | |
| LOW | extensions/csrc/kernel/x86/cpu_adam.h | 21 | */ | COMMENT |
| LOW | extensions/csrc/kernel/x86/cpu_adam.h | 41 | #define SIMD_WIDTH 16 | COMMENT |
| LOW | extensions/csrc/kernel/x86/cpu_adam.h | 61 | #define SIMD_LOAD(x) _mm256_loadu_ps(x) | COMMENT |
| LOW | colossalai/pipeline/schedule/v_schedule.py | 1 | # Refer from Zero Bubble Pipeline Parallelism. | COMMENT |
| LOW | colossalai/nn/optimizer/adafactor.py | 1 | # coding=utf-8 | COMMENT |
| LOW | colossalai/shardformer/modeling/bert.py | 1081 | # if uni-directional self-attention (decoder) save Tuple(torch.Tensor, torch.Tensor) of | COMMENT |
| LOW | colossalai/legacy/pipeline/middleware/topo.py | 121 | return res | COMMENT |
| LOW | colossalai/legacy/moe/openmoe/train.sh | 21 | # ep | COMMENT |
| LOW | colossalai/legacy/moe/openmoe/test_ci.sh | 1 | # pip install -r requirements.txt | COMMENT |
| LOW | colossalai/legacy/moe/openmoe/test_ci.sh | 21 | # torchrun --standalone --nproc_per_node 4 train.py \ | COMMENT |
| LOW | …salai/legacy/moe/openmoe/model/convert_openmoe_ckpt.py | 1 | # coding=utf-8 | COMMENT |
| LOW | colossalai/legacy/moe/openmoe/model/modeling_openmoe.py | 1 | # coding=utf-8 | COMMENT |
| LOW | colossalai/_analyzer/fx/graph_module.py | 21 | from torch.fx.graph_module import _exec_with_source, _forward_from_src | COMMENT |
| LOW | colossalai/auto_parallel/checkpoint/ckpt_solver_base.py | 101 | """ | COMMENT |
| LOW | …salai/auto_parallel/passes/runtime_preparation_pass.py | 241 | getitem_index = node.args[1] | COMMENT |
| LOW | colossalai/device/device_mesh.py | 421 | # key is axis name | COMMENT |
| LOW | colossalai/tensor/colo_parameter.py | 81 | COMMENT | |
| LOW | …utorial/sequence_parallel/lr_scheduler/annealing_lr.py | 1 | # coding=utf-8 | COMMENT |
| LOW | examples/tutorial/sequence_parallel/data/__init__.py | 21 | (train_dataloader, valid_dataloader, test_dataloader) = (None, None, None) | COMMENT |
| LOW | …/sequence_parallel/data/tokenizer/bert_tokenization.py | 1 | # coding=utf-8 | COMMENT |
| LOW | …/tutorial/sequence_parallel/data/tokenizer/__init__.py | 1 | # coding=utf-8 | COMMENT |
| LOW | …tutorial/sequence_parallel/data/tokenizer/tokenizer.py | 1 | # coding=utf-8 | COMMENT |
| LOW | …l/sequence_parallel/data/datasets/blendable_dataset.py | 1 | # coding=utf-8 | COMMENT |
| LOW | …torial/sequence_parallel/data/datasets/bert_dataset.py | 1 | # coding=utf-8 | COMMENT |
| 26 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | colossalai/inference/README.md | 46 | # Step 1: create a model in "transformers" way | COMMENT |
| LOW⚡ | colossalai/inference/README.md | 51 | # Step 2: create an inference_config | COMMENT |
| LOW⚡ | colossalai/inference/README.md | 60 | # Step 3: create an engine with model and config | COMMENT |
| LOW⚡ | colossalai/inference/README.md | 63 | # Step 4: try inference | COMMENT |
| LOW | examples/images/diffusion/README.md | 41 | #### Step 1: Requirements | COMMENT |
| LOW | examples/images/diffusion/README.md | 57 | #### Step 2: Install [Colossal-AI](https://colossalai.org/download/) From Our Official Website | COMMENT |
| LOW | examples/images/diffusion/README.md | 83 | #### Step 3: Accelerate with flash attention by xformers (Optional) | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 33 | #### Step 1: Collect Data | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 37 | #### Step 2: Split Data | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 41 | #### Step 3: Construct Vector Stores | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 47 | #### Step 4: Retrieve Relative Text | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 50 | #### Step 5: Format Prompt | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 53 | #### Step 6: Inference | COMMENT |
| LOW⚡ | applications/ColossalQA/README.md | 56 | #### Step 7: Update Memory | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 463 | #### Step 1: Data Collection | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 485 | #### Step 2: Preprocessing | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 537 | #### Step 3: Training | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 547 | #### Step 1: Data Collection | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 579 | #### Step 2: Preprocessing | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 583 | #### Step 3: Training | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 623 | #### Step 1: Data Collection | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 654 | #### Step 2: Preprocessing | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 661 | #### Step 3: Training | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 742 | ### Step 1: Data Collection & Preparation | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 745 | ### Step 2: Training | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 800 | #### Step 1: Data Collection & Preparation | COMMENT |
| LOW | applications/ColossalChat/examples/README.md | 804 | #### Step 2: Training | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | applications/ColossalQA/README.md | 66 | Our platform accommodates two kinds of LLMs: API-accessible and locally run models. For the API-style LLMs, we support C | CODE |
| MEDIUM⚡ | …tions/ColossalQA/examples/retrieval_conversation_en.py | 42 | # Setup embedding model locally | COMMENT |
| MEDIUM | …tions/ColossalQA/examples/retrieval_conversation_zh.py | 41 | # Setup embedding model locally | COMMENT |
| MEDIUM⚡ | …examples/retrieval_conversation_en_customer_service.py | 44 | # Setup embedding model locally | COMMENT |
| MEDIUM | …retrieval_intent_classification_zh_customer_service.py | 36 | # Setup embedding model locally | COMMENT |
| MEDIUM | applications/ColossalQA/examples/webui_demo/config.py | 6 | "embed_name": "m3e", # embedding model name | CODE |
| MEDIUM | applications/ColossalQA/examples/webui_demo/config.py | 7 | "embed_model_name_or_path": "moka-ai/m3e-base", # path to embedding model, could be a local path or a huggingfa | CODE |
| MEDIUM | applications/ColossalQA/examples/webui_demo/README.md | 24 | ## Configure the RAG Chain | COMMENT |
| MEDIUM | …ications/ColossalEval/colossal_eval/dataset/agieval.py | 102 | # process few-shot raw_prompts | COMMENT |
| MEDIUM | …ications/ColossalEval/colossal_eval/dataset/agieval.py | 214 | # process demo once if it is few-shot-CoT | COMMENT |
| MEDIUM | …tions/ColossalEval/colossal_eval/utils/conversation.py | 138 | # First few shot data is something like "The following are questions about xxx". | COMMENT |
| MEDIUM | …tions/ColossalEval/colossal_eval/utils/conversation.py | 184 | # For few-shot, only need input. Otherwise use instruction (in AGIEval). | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_shardformer/test_model/_utils.py | 324 | # Check if the output sequence is gathered before cross entropy | COMMENT |
| LOW | colossalai/booster/plugin/hybrid_parallel_plugin.py | 173 | # Check if the DP group size is 1, meaning no synchronization is needed. | STRING |
| LOW | colossalai/booster/plugin/hybrid_parallel_plugin.py | 854 | # Check if the list of gradients is empty | STRING |
| LOW | colossalai/booster/plugin/hybrid_parallel_plugin.py | 1427 | # Check if the optimizer is a HybridParallelZeroOptimizer and synchronize data parallelism gradients if so. | COMMENT |
| LOW | colossalai/quantization/bnb.py | 160 | # Check if the current key is not in the `modules_to_not_convert` | COMMENT |
| LOW | colossalai/quantization/bnb.py | 232 | # Check if it is a base model | STRING |
| LOW | colossalai/tensor/d_tensor/layout_converter.py | 472 | # Check if each process group is still alive | STRING |
| LOW | examples/images/diffusion/main.py | 257 | # Check if the train dataset is iterable | COMMENT |
| LOW | examples/images/diffusion/main.py | 274 | # Check if the validation dataset is iterable | COMMENT |
| LOW | examples/images/diffusion/main.py | 289 | # Check if the test dataset is iterable | COMMENT |
| LOW | examples/images/diffusion/main.py | 620 | # Check if the "resume" option is specified, resume training from the checkpoint if it is true | COMMENT |
| LOW⚡ | examples/images/diffusion/main.py | 854 | # Assign melk to SIGUSR1 signal and divein to SIGUSR2 signal | COMMENT |
| LOW | …flows/scripts/example_checks/detect_changed_example.py | 19 | # Output the result using print. Then the shell can get the values. | COMMENT |
| LOW | …ons/ColossalChat/coati/distributed/reward/reward_fn.py | 140 | # Check if the sequence is over length | COMMENT |
| LOW | …ons/ColossalChat/coati/distributed/reward/reward_fn.py | 205 | # Check if the sequence is over length | COMMENT |
| LOW⚡ | …ons/ColossalChat/coati/distributed/reward/reward_fn.py | 286 | # Check if the sequence is over length | COMMENT |
| LOW | …tions/ColossalChat/coati/dataset/tokenization_utils.py | 112 | # Check if all labels are ignored, this may happen when the tokenized length is too long | COMMENT |
| LOW | …tions/ColossalChat/coati/dataset/tokenization_utils.py | 321 | # Check if loss mask is all 0s (no loss), this may happen when the tokenized length is too long | COMMENT |
| LOW | applications/ColossalChat/tests/test_train.sh | 406 | # Check if the plugin is either "gemini_auto" or "gemini" and set grad_accu to '1' | COMMENT |
| LOW | applications/ColossalChat/tests/test_lora.py | 59 | # Check if model has overfitted | COMMENT |
| LOW | …ns/ColossalChat/examples/training_scripts/train_kto.py | 182 | # Check if the user specified weights fit into the theoratical lower and upper bounds from Eq. (8) of https://arxiv. | COMMENT |
| LOW | …t/examples/data_preparation_scripts/prepare_dataset.py | 173 | # Set stop_ids to eos_token_id for other dataset types if not exist | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | colossalai/fx/tracer/tracer.py | 97 | # if no extra manipulation is applied, we just pass the origin arguments to create_proxy function | COMMENT |
| MEDIUM | colossalai/legacy/context/parallel_mode.py | 17 | # this is added to facilitate amp and grad clipping in hybrid parallel | COMMENT |
| LOW | …lossalai/legacy/zero/sharded_optim/sharded_optim_v2.py | 339 | # We just set p.data = p.colo_attr.saved_grad.payload here | COMMENT |
| MEDIUM | …egacy/zero/shard_utils/bucket_tensor_shard_strategy.py | 40 | # Ensure we utilize maximum PCIE bandwidth | COMMENT |
| LOW | colossalai/autochunk/estimate_memory.py | 197 | # if node is placeholder, just add the size of the node | COMMENT |
| LOW | colossalai/cli/launcher/hostinfo.py | 36 | port = 22 # no port specified, lets just use the ssh port | CODE |
| LOW | colossalai/zero/gemini/chunk/chunk.py | 332 | # just use another way for the movement | COMMENT |
| LOW | colossalai/lazy/lazy_init.py | 340 | # inplace op, just return origin lazy tensor | COMMENT |
| MEDIUM | colossalai/kernel/triton/context_attn_unpad.py | 602 | # NOTE use `triton.next_power_of_2` here to utilize the cache mechanism of triton | COMMENT |
| MEDIUM | colossalai/kernel/triton/flash_decoding.py | 409 | # NOTE use `triton.next_power_of_2` here to utilize the cache mechanism of triton | COMMENT |
| LOW | …utorial/sequence_parallel/lr_scheduler/annealing_lr.py | 67 | # If the learning rate is constant, just return the initial value. | COMMENT |
| LOW | examples/language/gpt/gemini/train_gpt_demo.py | 210 | # we just use randomly generated data here | COMMENT |
| LOW | …uage/gpt/experiments/pipeline_parallel/train_gpt_pp.py | 143 | # we just use randomly generated data here | COMMENT |
| LOW | …pt/experiments/auto_parallel/auto_parallel_with_gpt.py | 81 | # we just use randomly generated data here | COMMENT |
| LOW | …les/community/roberta/pretraining/utils/global_vars.py | 113 | # pollutes the runs list, so we just add each as a scalar | COMMENT |
| MEDIUM | …/ColossalChat/coati/distributed/reward/reward_utils.py | 21 | """Performs comprehensive validation of response structure. | STRING |
| MEDIUM | …cations/ColossalChat/coati/utils/reward_score/utils.py | 21 | """Performs comprehensive validation of response structure. | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | colossalai/shardformer/shard/shard_config.py | 116 | # you can add all the optimization flag here | STRING |
| MEDIUM | …s/tutorial/opt/inference/script/processing_ckpt_66b.py | 7 | # you can use whether wget or git lfs | COMMENT |
| MEDIUM | …ples/community/roberta/preprocessing/sentence_split.py | 143 | # if you have multiple server, you can use code below or modify code to openmpi | COMMENT |
| MEDIUM | …mples/community/roberta/preprocessing/tokenize_mask.py | 239 | # if you have multiple server, you can use code below or modify code to openmpi | COMMENT |
| MEDIUM | applications/ColossalQA/data/tests/test.html | 1113 | <p>If you are using {}-formatting (<a class="reference internal" href="https://docs.python.org/3/library/stdtypes.html#s | CODE |
| MEDIUM | applications/ColossalQA/data/tests/test.html | 1296 | counterparts in <a class="reference internal" href="https://docs.python.org/3/library/logging.html#logging.Logger" title | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | colossalai/legacy/nn/layer/parallel_3d/_utils.py | 90 | return _async_grad_bucket.push(op, grad, param_id) | CODE |
| HIGH | colossalai/legacy/moe/layer/layers.py | 312 | | C1 || C2 || C3 || C4 | | STRING |
| HIGH | colossalai/legacy/moe/layer/layers.py | 313 | | A1 || A2 | | R1 | A3 || R2 | A4 || R3 | | R4 | | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | …ns/ColossalChat/coati/distributed/inference_backend.py | 284 | self.llm.llm_engine.model_executor.driver_worker.model_runner.model.load_weights(state_dict.items()) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …ssalai/booster/mixed_precision/mixed_precision_base.py | 22 | # TODO: implement this method | COMMENT |
| LOW | colossalai/legacy/inference/hybridengine/engine.py | 73 | # TODO: implement early_stopping, and various generation options | COMMENT |
| LOW⚡ | colossalai/auto_parallel/tensor_shard/initialize.py | 62 | # TODO: implement this function | COMMENT |
| LOW⚡ | colossalai/auto_parallel/tensor_shard/initialize.py | 70 | # TODO: implement this function | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | colossalai/fx/codegen/activation_checkpoint_codegen.py | 586 | # we need to check if the checkpoint need to offload the input | STRING |
| LOW⚡ | colossalai/fx/codegen/activation_checkpoint_codegen.py | 593 | # we need to check if the checkpoint need use_reentrant=False | STRING |
| LOW | .github/workflows/scripts/check_doc_i18n.py | 6 | # First, we need to check if the two directories exist | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | colossalai/legacy/utils/profiler/profiler.py | 101 | # In this example with wait=1, warmup=1, active=2, | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | colossalai/auto_parallel/tensor_shard/utils/misc.py | 20 | def do_something(): | STRING |
| LOW | colossalai/testing/utils.py | 235 | def do_something(rank, world_size, port): | STRING |
| LOW | colossalai/testing/utils.py | 241 | def do_something(rank, world_size, port, arg1, arg2): | STRING |