AI Slop Code RIsk Monitor

hpcaitech/ColossalAI

Making large AI models cheaper, faster and more accessible

23.6 Elevated pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for hpcaitech/ColossalAI, a Python project with 41,438 GitHub stars. SynthScan examined 336,948 lines of code across 2164 source files, recording 4742 pattern matches distributed across 24 syntactic categories. The legacy adjusted pattern signal is 23.6 (Elevated pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

23.6
Adjusted Signal
23.6
Raw Pattern Score
100%
Time Factor
2026-10-10
Last Push
41.4K
Stars
Python
Language
336.9K
Lines of Code
2.2K
Files
4.7K
Pattern Hits
2026-10-12
Scan Date
0.20
HC Hit Rate

Risk Review · v3

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

Cognitive Ownership Risk 31.1/100 · MEDIUM

Can maintainers explain intent, assumptions, and trade-offs? 2272 finding(s).

Hallucinated Dependency & Supply Chain Risk 14.7/100 · LOW

Are imports declared and package/API names verified? 1059 finding(s).

Agent Over-Engineering Ratio 57.5/100 · HIGH

Are wrappers, guards, and repeated structures necessary? 2857 finding(s).

PR Review Velocity Impact 70.5/100 · HIGH

Which changes need focused human review? 4742 finding(s).

What These Metrics Mean

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

Pattern-Signal History

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

Severity Breakdown

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

CRITICAL 1HIGH 437MEDIUM 642LOW 3662

Directory Score Breakdown

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

Pattern Findings

The scanner identified 4742 distinct pattern matches across 24 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.

Decorative Section Separators531 hits · 1862 pts
SeverityFileLineSnippetContext
MEDIUM…sts/test_shardformer/test_model/test_shard_deepseek.py130 # ===================================================================================COMMENT
MEDIUMtests/test_shardformer/test_model/test_shard_mixtral.py123 # ===================================================================================COMMENT
MEDIUMtests/kit/model_zoo/timm/timm.py6## ==============COMMENT
MEDIUMtests/kit/model_zoo/timm/timm.py8## ==============COMMENT
MEDIUMtests/kit/model_zoo/timm/timm.py150# ==============COMMENT
MEDIUMtests/kit/model_zoo/timm/timm.py152# ==============COMMENT
MEDIUMtests/kit/model_zoo/transformers/command.py14 # ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/command.py16 # ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/mistral.py7# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/mistral.py9# ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/t5.py6# ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/t5.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/gptj.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/gptj.py10# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/albert.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/albert.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/albert.py69# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/albert.py71# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/opt.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/opt.py8# ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/chatglm2.py7# ================================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/chatglm2.py9# ================================COMMENT
MEDIUMtests/kit/model_zoo/transformers/whisper.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/whisper.py8# ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/llama.py14 # ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/llama.py16 # ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/llama.py23 # -----------------------------------COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/llama.py28 # -----------------------------------COMMENT
MEDIUMtests/kit/model_zoo/transformers/vit.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/vit.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/deepseek.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/deepseek.py10# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/bert.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/bert.py8# ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen3.py14 # ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen3.py16 # ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen3.py23 # -----------------------------------COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen3.py28 # -----------------------------------COMMENT
MEDIUMtests/kit/model_zoo/transformers/deepseek_v3.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/deepseek_v3.py10# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/falcon.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/falcon.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/sam.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/sam.py8# ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen2.py14 # ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen2.py16 # ===============================COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen2.py23 # -----------------------------------COMMENT
MEDIUM⚡tests/kit/model_zoo/transformers/qwen2.py28 # -----------------------------------COMMENT
MEDIUMtests/kit/model_zoo/transformers/mixtral.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/mixtral.py10# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/gpt.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/gpt.py10# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/bloom.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/bloom.py8# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/blip2.py6# ===============================COMMENT
MEDIUMtests/kit/model_zoo/transformers/blip2.py8# ===============================COMMENT
MEDIUMtests/test_pipeline/test_schedule/test_zerobubble_pp.py890 # ===================================================================================COMMENT
MEDIUMtests/test_pipeline/test_schedule/test_zerobubble_pp.py1045 # ===================================================================================COMMENT
MEDIUM…/test_fx/test_profiler/test_profiler_meta_info_prop.py67 # =====================================================COMMENT
MEDIUM…/test_fx/test_profiler/test_profiler_meta_info_prop.py83 # =====================================================COMMENT
471 more matches not shown…
Cross-File Repetition352 hits · 1760 pts
SeverityFileLineSnippetContext
HIGHtests/test_shardformer/test_layer/test_dist_log_prob.py0compute the log probabilities from logits for the given labels. args: logits (torch.tensor): the input logits. labels (tSTRING
HIGHapplications/ColossalChat/coati/distributed/utils.py0compute the log probabilities from logits for the given labels. args: logits (torch.tensor): the input logits. labels (tSTRING
HIGHapplications/ColossalChat/coati/models/utils.py0compute the log probabilities from logits for the given labels. args: logits (torch.tensor): the input logits. labels (tSTRING
HIGHtests/test_legacy/test_moe/moe_utils.py0a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be opeSTRING
HIGH…egacy/engine/gradient_handler/_moe_gradient_handler.py0a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be opeSTRING
HIGH…ne/gradient_handler/_data_parallel_gradient_handler.py0a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be opeSTRING
HIGH…radient_handler/_sequence_parallel_gradient_handler.py0a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be opeSTRING
HIGH…radient_handler/_pipeline_parallel_gradient_handler.py0a helper class to handle all-reduce operations in sub parallel groups. a all-reduce collective communication will be opeSTRING
HIGH…est_tensor_shard/test_metainfo/test_linear_metainfo.py0this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executedSTRING
HIGH…st_tensor_shard/test_metainfo/test_pooling_metainfo.py0this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executedSTRING
HIGH…/test_tensor_shard/test_metainfo/test_conv_metainfo.py0this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executedSTRING
HIGH…hard/test_metainfo/test_binary_elementwise_metainfo.py0this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executedSTRING
HIGH…/test_tensor_shard/test_metainfo/test_norm_metainfo.py0this function is for batchnorm memory test test and print real memory cost and estimated, this test will not be executedSTRING
HIGHcolossalai/pipeline/schedule/interleaved_pp.py0load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): tSTRING
HIGHcolossalai/pipeline/schedule/one_f_one_b.py0load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): tSTRING
HIGHcolossalai/pipeline/schedule/generate.py0load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): tSTRING
HIGHcolossalai/pipeline/schedule/zero_bubble_pp.py0load a batch from data iterator. args: data_iter (iterable): data iterator. device (optional[torch.device], optional): tSTRING
HIGHcolossalai/nn/optimizer/lamb.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/lars.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/galore.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/distributed_lamb.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/distributed_galore.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/fused_lamb.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/fused_sgd.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/adafactor.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/distributed_adafactor.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/came.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/optimizer/distributed_came.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHexamples/images/diffusion/ldm/util.py0performs a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returnSTRING
HIGHcolossalai/nn/layer/utils.py0only allow exact division. args: numerator (int): numerator of the division. denominator (int): denominator of the divisSTRING
HIGHcolossalai/legacy/nn/layer/utils/common.py0only allow exact division. args: numerator (int): numerator of the division. denominator (int): denominator of the divisSTRING
HIGHcolossalai/legacy/tensor/dist_spec_mgr.py0only allow exact division. args: numerator (int): numerator of the division. denominator (int): denominator of the divisSTRING
HIGH…tched_bias_addition_function/bias_addition_function.py0this 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.py0this 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.py0this method is used to create the non_bias_func proxy, the node created by this proxy will compute the main computation,STRING
HIGHcolossalai/fx/passes/meta_info_prop.py0run `module` via interpretation and return the result and record the shape of each node. args: *args (tensor): the samplSTRING
HIGHcolossalai/fx/passes/concrete_info_prop.py0run `module` via interpretation and return the result and record the shape of each node. args: *args (tensor): the samplSTRING
HIGHcolossalai/_analyzer/fx/passes/shape_prop.py0run `module` via interpretation and return the result and record the shape of each node. args: *args (tensor): the samplSTRING
HIGHcolossalai/fx/codegen/activation_checkpoint_codegen.py0add an obj to be tracked as a global. we call this for names that reference objects external to the graph, like functionSTRING
HIGHcolossalai/autochunk/autochunk_codegen.py0add an obj to be tracked as a global. we call this for names that reference objects external to the graph, like functionSTRING
HIGHcolossalai/_analyzer/fx/codegen.py0add an obj to be tracked as a global. we call this for names that reference objects external to the graph, like functionSTRING
HIGHcolossalai/fx/codegen/activation_checkpoint_codegen.py0delete values after their last use. this ensures that values that are not used in the remainder of the code are freed anSTRING
HIGHcolossalai/autochunk/autochunk_codegen.py0delete values after their last use. this ensures that values that are not used in the remainder of the code are freed anSTRING
HIGHcolossalai/_analyzer/fx/codegen.py0delete values after their last use. this ensures that values that are not used in the remainder of the code are freed anSTRING
HIGHcolossalai/booster/plugin/gemini_plugin.py0save model to checkpoint but only on master process.STRING
HIGHcolossalai/booster/plugin/torch_fsdp_plugin.py0save model to checkpoint but only on master process.STRING
HIGHcolossalai/booster/plugin/torch_ddp_plugin.py0save model to checkpoint but only on master process.STRING
HIGHcolossalai/booster/plugin/gemini_plugin.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHcolossalai/booster/plugin/dp_plugin_base.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHcolossalai/booster/plugin/hybrid_parallel_plugin.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHexamples/language/data_utils.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHexamples/language/mixtral/data_utils.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHexamples/language/deepseek/data_utils.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHexamples/language/llama/data_utils.py0prepare a dataloader for distributed training. the dataloader will be wrapped by `torch.utils.data.dataloader` and `statSTRING
HIGHcolossalai/shardformer/policies/command.py0if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, aSTRING
HIGHcolossalai/shardformer/policies/mistral.py0if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, aSTRING
HIGHcolossalai/shardformer/policies/gpt2.py0if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, aSTRING
HIGHcolossalai/shardformer/policies/t5.py0if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, aSTRING
HIGHcolossalai/shardformer/policies/gptj.py0if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, aSTRING
HIGHcolossalai/shardformer/policies/opt.py0if under pipeline parallel setting, replacing the original forward method of huggingface to customized forward method, aSTRING
292 more matches not shown…
Hyper-Verbose Identifiers1092 hits · 1043 pts
SeverityFileLineSnippetContext
LOW…heckpoint_io/test_plugins_huggingface_compatibility.py78def test_huggingface_compatibility(world_size):CODE
LOWtests/test_checkpoint_io/test_gemini_checkpoint_io.py39def exam_state_dict_with_origin(CODE
LOWtests/test_checkpoint_io/test_gemini_checkpoint_io.py193def exam_lazy_from_pretrained():CODE
LOWtests/test_checkpoint_io/test_general_checkpoint_io.py23def test_unsharded_checkpoint(use_safetensors: bool, use_async: bool):CODE
LOWtests/test_checkpoint_io/test_general_checkpoint_io.py77def test_sharded_model_checkpoint(use_safetensors: bool, use_async: bool):CODE
LOWtests/test_checkpoint_io/test_general_checkpoint_io.py117def test_sharded_optimizer_checkpoint(use_async: bool):CODE
LOWtests/test_checkpoint_io/test_general_checkpoint_io.py186def test_sharded_optimizer_multiple_param_groups(use_async: bool):CODE
LOW…ts/test_checkpoint_io/test_gemini_torch_compability.py24def exam_torch_load_from_gemini(shard: bool, model_name: str):CODE
LOW…ts/test_checkpoint_io/test_gemini_torch_compability.py90def exam_gemini_load_from_torch(shard: bool, model_name: str):CODE
LOWtests/test_zero/test_gemini/test_zeroddp_state_dict.py18def ignore_the_first_parameter(model: torch.nn.Module):CODE
LOW…sts/test_zero/test_gemini/test_zerooptim_state_dict.py23def exam_zero_optim_state_dict(placement_config, keep_gathered):CODE
LOWtests/test_shardformer/test_flash_attention.py67def post_process_kwargs_for_raw_attn(attn_kwargs: dict):CODE
LOWtests/test_shardformer/test_with_torch_ddp.py18def check_shardformer_with_ddp(lazy_init: bool):CODE
LOWtests/test_shardformer/test_model/_utils.py120def build_model_from_hybrid_plugin(CODE
LOWtests/test_shardformer/test_model/_utils.py174def build_model_from_low_level_zero_plugin(CODE
LOWtests/test_shardformer/test_model/_utils.py200def run_forward_backward_with_hybrid_plugin(CODE
LOWtests/test_shardformer/test_model/_utils.py263def run_forward_backward_with_low_level_zero_plugin(CODE
LOWtests/test_shardformer/test_model/_utils.py301def check_output_hidden_state(CODE
LOWtests/test_shardformer/test_model/_utils.py368def get_grad_tensors_for_check(CODE
LOW…/test_shardformer/test_layer/test_sequence_parallel.py173def test_all_to_all_attention():CODE
LOWtests/test_shardformer/test_layer/test_linear_1d.py121def check_linear_without_weight_grad_store(lazy_init: bool, seq_parallel_mode: bool):CODE
LOWtests/test_shardformer/test_layer/test_linear_1d.py161def check_linear_with_weight_grad_store(lazy_init: bool, seq_parallel_mode: bool):CODE
LOWtests/test_shardformer/test_layer/test_linear_1d.py208def check_linear_col_plus_row(lazy_init: bool, seq_parallel_mode: bool, overlap: bool):CODE
LOWtests/test_shardformer/test_layer/test_dropout.py10def check_dropout_parallel_input():CODE
LOWtests/test_shardformer/test_layer/test_dropout.py42def check_dropout_replicated_input():CODE
LOWtests/test_legacy/test_context/test_hybrid_parallel.py32def check_pipeline_parallel_rank(rank):CODE
LOWtests/test_legacy/test_context/test_hybrid_parallel.py44def check_model_parallel_rank(rank):CODE
LOWtests/test_legacy/test_context/test_hybrid_parallel.py51def check_tensor_parallel_rank(rank):CODE
LOWtests/test_legacy/test_utils/test_memory.py9def _run_colo_set_process_memory_fraction_and_colo_device_memory_capacity():CODE
LOW…est_legacy/test_utils/test_activation_checkpointing.py45def test_activation_checkpointing(cpu_offload, use_reentrant):CODE
LOWtests/test_legacy/test_layers/test_cache_embedding.py224def run_parallel_freq_aware_embed_tablewise(rank, world_size):CODE
LOWtests/test_legacy/test_layers/test_cache_embedding.py310def run_parallel_freq_aware_embed_columnwise(rank, world_size):CODE
LOWtests/test_legacy/test_layers/test_cache_embedding.py389def test_parallel_freq_aware_embed(world_size):CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py203def check_vocab_parallel_embed():CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py245def check_classifier_no_given_weight():CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py311def check_vocab_parallel_classifier_no_given_weight():CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py371def check_classifier_given_embed_weight():CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py422def check_vocab_parallel_classifier_given_embed_weight():CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py474def check_vocab_parallel_loss():CODE
LOW…legacy/test_layers/test_1d/checks_1d/check_layer_1d.py510def check_linear_row_stream_inference():CODE
LOWtests/test_legacy/test_layers/test_2d/test_2d.py51def check_layer_and_operation(rank, world_size, port):CODE
LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py276def check_vocab_parallel_embed():CODE
LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py323def check_classifier_no_given_weight():CODE
LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py401def check_vocab_parallel_classifier_no_given_weight():CODE
LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py469def check_classifier_given_embed_weight():CODE
LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py521def check_vocab_parallel_classifier_given_embed_weight():CODE
LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py610def check_vocab_parallel_loss():CODE
LOWtests/test_legacy/test_layers/test_2p5d/test_2p5d.py39def check_layer_and_operation(rank, world_size, port):CODE
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py280def check_vocab_parallel_embed():CODE
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py328def check_classifier_no_given_weight():CODE
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py407def check_vocab_parallel_classifier_no_given_weight():CODE
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py474def check_classifier_given_embed_weight():CODE
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py526def check_vocab_parallel_classifier_given_embed_weight():CODE
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py615def check_vocab_parallel_loss():CODE
LOWtests/test_legacy/test_layers/test_3d/test_3d.py45def check_layer_and_operation(rank, world_size, port):CODE
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Deep Nesting545 hits · 540 pts
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Modern Structural Boilerplate360 hits · 355 pts
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AI Structural Patterns354 hits · 352 pts
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Empty Error Handlers56 hits · 280 pts
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Self-Referential Comments75 hits · 192 pts
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MEDIUM…t_hybrid_parallel_grad_clip_norm/test_amp_optimizer.py74 # Create a list of parameter-gradient pairs containing working parameters and their gradientsCOMMENT
MEDIUM…est_tensor_shard/test_metainfo/test_linear_metainfo.py23 """This function is for linear memory testSTRING
MEDIUM⚡…est_tensor_shard/test_metainfo/test_linear_metainfo.py61 """This function is for linear memory testSTRING
MEDIUM…st_tensor_shard/test_metainfo/test_pooling_metainfo.py14 """This function is for AdaptiveAvgPool memory testSTRING
MEDIUM…st_tensor_shard/test_metainfo/test_pooling_metainfo.py55 """This function is for MaxPool memory testSTRING
MEDIUM…/test_tensor_shard/test_metainfo/test_conv_metainfo.py23 """This function is for conv memory testSTRING
MEDIUM…/test_tensor_shard/test_metainfo/test_conv_metainfo.py65 """This function is for conv function memory testSTRING
MEDIUM…hard/test_metainfo/test_binary_elementwise_metainfo.py24 """This function is for binary elementwise ops memory testSTRING
MEDIUM…/test_tensor_shard/test_metainfo/test_norm_metainfo.py18 """This function is for batchnorm memory testSTRING
MEDIUMtests/test_infer/test_streamingllm.py115 result_list = manager.list([-1] * 1) # Create a shared listCODE
MEDIUMtests/test_infer/test_inference_engine.py90 result_list = manager.list([-1] * world_size) # Create a shared listCODE
MEDIUMtests/test_infer/test_models/test_baichuan.py82 result_list = manager.list([-1] * world_size) # Create a shared listCODE
MEDIUMtests/test_infer/test_models/test_custom_model.py84 result_list = manager.list([-1] * world_size) # Create a shared listCODE
MEDIUMtests/test_infer/test_kernels/triton/kernel_utils.py7# This function is adapted from src/transformers/models/llama/modeling_llama.pyCOMMENT
MEDIUMcolossalai/fx/codegen/activation_checkpoint_codegen.py168 """This function is to find the offload regionsSTRING
MEDIUMcolossalai/booster/plugin/hybrid_parallel_plugin.py1403 # Create a context for gradient synchronization based on the optimizer type.COMMENT
MEDIUMcolossalai/shardformer/modeling/gpt2.py137 # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2Model.forward.COMMENT
MEDIUMcolossalai/shardformer/modeling/gpt2.py555 # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2ForQuestionAnswering.forwCOMMENT
MEDIUMcolossalai/shardformer/modeling/gpt2.py643 # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2ForTokenClassification.foCOMMENT
MEDIUMcolossalai/shardformer/modeling/gpt2.py718 # This function is modified on the basis of transformers.models.gpt2.modeling_gpt2.GPT2ForSequenceClassificationCOMMENT
MEDIUMcolossalai/shardformer/modeling/t5.py54 # This function is modified on the basis of transformers.models.t5.modeling_t5.T5Stack.forward.COMMENT
MEDIUMcolossalai/shardformer/modeling/t5.py290 # This function is modified on the basis of transformers.models.t5.modeling_t5.T5Model.forward.COMMENT
MEDIUMcolossalai/shardformer/modeling/t5.py430 # This function is modified on the basis of transformers.models.t5.modeling_t5.T5ForConditionalGeneration.forwarSTRING
MEDIUMcolossalai/shardformer/modeling/gptj.py99 # This function is modified on the v4.51.3 transformers.models.gptj.modeling_gptj.GPTJModel.forward.COMMENT
MEDIUMcolossalai/shardformer/modeling/gptj.py288 # This function is modified on the basis of transformers.models.gptj.modeling_gptj.GPTJForCausalLM.forward.COMMENT
MEDIUMcolossalai/shardformer/modeling/gptj.py381 # This function is modified on the v4.51.3 transformers.models.gptj.modeling_gptj.GPTJForSequenceClassification.COMMENT
MEDIUMcolossalai/shardformer/modeling/gptj.py503 # This function is modified on the basis of transformers.models.gptj.modeling_gptj.GPTJForQuestionAnswering.forwCOMMENT
MEDIUMcolossalai/shardformer/modeling/gptj.py583 # This function is modified on the v4.51.3 transformers.models.gptj.modeling_gptj.GPTJAttention.forward.STRING
MEDIUMcolossalai/legacy/pipeline/middleware/topo.py127# This class is a middleware between partition splitterCOMMENT
MEDIUMcolossalai/legacy/context/parallel_context.py25 """This class provides interface functions for users to get the parallel context,STRING
MEDIUMcolossalai/legacy/context/random/seed_manager.py11 """This class is a manager of all random seeds involved in the system.STRING
MEDIUMcolossalai/legacy/nn/loss/loss_1d.py30 # Create a mask of valid vocab ids (1 means it needs to be masked).COMMENT
MEDIUM…lossalai/legacy/zero/sharded_optim/sharded_optim_v2.py189 # This function is called except the last stage of pipeline parallelCOMMENT
MEDIUMcolossalai/legacy/amp/naive_amp/_fp16_optimizer.py128 # Create a fp32 copyCOMMENT
MEDIUMcolossalai/utils/tensor_detector/tensor_detector.py17 """This class is a detector to detect tensor on different devices.STRING
MEDIUMcolossalai/quantization/bnb.py219 # Create a copy of the modelSTRING
MEDIUMcolossalai/zero/gemini/gemini_ddp.py261 """This function is only triggered for inference."""STRING
MEDIUMcolossalai/zero/gemini/gemini_ddp.py296 """This function is only triggered for inference."""STRING
MEDIUMcolossalai/zero/gemini/gemini_optimizer.py306 # This function is called except the last stage of pipeline parallelCOMMENT
MEDIUM…ssalai/zero/gemini/memory_tracer/memstats_collector.py76 # The following code work for ZeroInitContext, which is deprecated in v0.1.12COMMENT
MEDIUMcolossalai/lazy/lazy_init.py80 """This class is only for correctness verification."""STRING
MEDIUMcolossalai/inference/batch_bucket.py483 ########## The following methods are expected to be used in modeling ###########COMMENT
MEDIUMcolossalai/tensor/comm_spec.py423 # Create a new member `logical_process_axes` to distinguish from original flattenCOMMENT
MEDIUM…/tutorial/sequence_parallel/loss_func/cross_entropy.py15 # Create a mask of valid vocab ids (1 means it needs to be masked).COMMENT
MEDIUM…ce_parallel/data/datasets/test/test_indexed_dataset.py1# This file isn't really a formal automated test, it's just a place toCOMMENT
MEDIUMexamples/images/diffusion/main.py56 # Create an ArgumentParser object with specifies kwargsCOMMENT
MEDIUMexamples/images/diffusion/main.py404 # Create a list of exponentially increasing log steps, starting from 1 and ending at batch_frequencyCOMMENT
MEDIUMexamples/images/diffusion/main.py661 # Create the checkpoint and configuration directories within the log directory.COMMENT
MEDIUMexamples/images/diffusion/main.py755 # Create an empty OmegaConf configuration objectCOMMENT
MEDIUMexamples/images/diffusion/main.py796 # Create a Trainer object with the specified command-line arguments and keyword arguments, and set the log direcCOMMENT
MEDIUMexamples/images/diffusion/main.py800 # Create a data module based on the configuration fileCOMMENT
MEDIUMexamples/images/diffusion/ldm/data/lsun.py10# This class is used to create a dataset of images from LSUN dataset for trainingCOMMENT
MEDIUMexamples/images/dreambooth/train_dreambooth.py689 # Create the pipeline using using the trained modules and save it.COMMENT
MEDIUMexamples/images/dreambooth/train_dreambooth_inpaint.py726 # Create the pipeline using using the trained modules and save it.COMMENT
MEDIUMexamples/language/gpt/titans/model/embed.py262 # Create a mask of valid vocab ids (1 means it needs to be masked).COMMENT
MEDIUMexamples/language/gpt/gemini/commons/model_zoo.py5## Define the Model and Loss Based on Huggingface transformers GPT2LMHeadModelCOMMENT
MEDIUM…anguage/gpt/experiments/pipeline_parallel/model_zoo.py5## Define the Model and Loss Based on Huggingface transformers GPT2LMHeadModelCOMMENT
MEDIUM…ples/community/roberta/pretraining/model/deberta_v2.py102 >>> # Create a maskSTRING
MEDIUM…ons/ColossalQA/colossalqa/retrieval_conversation_en.py31 # Define the retrieverCOMMENT
MEDIUM…ons/ColossalQA/colossalqa/retrieval_conversation_en.py34 # Define the chain to preprocess the inputCOMMENT
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Docstring Block Structure25 hits · 125 pts
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HIGHcolossalai/pipeline/schedule/_utils.py72Get the batch size (size of dimension-0) of the first tensor in the batch. Args: batch (Any): Batch to be iSTRING
HIGHcolossalai/context/config.py52Reads a python file and constructs a corresponding :class:`Config` object. Args: filename (str): NaSTRING
HIGHcolossalai/shardformer/layer/normalization.py140 Convert a native PyTorch layer normalization module to a specific layer normalization module, and optioSTRING
HIGHcolossalai/legacy/context/parallel_context.py130Returns the local rank of the current device. Args: parallel_mode (:class:`colossalai.legacy.contexSTRING
HIGHcolossalai/legacy/context/parallel_context.py160Returns the global rank of the next device. Args: parallel_mode (:class:`colossalai.legacy.context.STRING
HIGHcolossalai/legacy/context/parallel_context.py182Returns the global rank of the previous device. Args: parallel_mode (:class:`colossalai.legacy.contSTRING
HIGHcolossalai/legacy/context/parallel_context.py204Returns a boolean value indicating whether the current device is the first one among its group for `parallel_modSTRING
HIGHcolossalai/legacy/context/parallel_context.py222Returns a boolean value indicating whether the current device is the last one among its group for `parallel_modeSTRING
HIGHcolossalai/legacy/context/parallel_context.py256Returns the world size for `parallel_mode`. Args: parallel_mode (:class:`colossalai.legacy.context.STRING
HIGHcolossalai/legacy/context/parallel_context.py286Returns the group of the current device for `parallel_mode`. Args: parallel_mode (:class:`colossalaSTRING
HIGHcolossalai/legacy/context/parallel_context.py342Returns the rank of the current device for `parallel_mode` in the group. Args: parallel_mode (:clasSTRING
HIGHcolossalai/legacy/utils/checkpointing.py221Loads training states from a checkpoint file. Args: file: a file-like object (has to implement read(), readSTRING
HIGH…lossalai/legacy/zero/gemini/tensor_placement_policy.py64 Evict tensors from CUDA device. Args: hold_cuda_tensor_list (List[StatefulTensor]): the liSTRING
HIGHcolossalai/legacy/registry/registry.py28Registers a module represented in `module_class`. Args: module_class (class): The module to be regiSTRING
HIGHcolossalai/legacy/registry/registry.py45Retrieves a module with name `module_name` and returns the module if it has already been registered before. STRING
HIGHcolossalai/legacy/builder/builder.py10Returns an object of :class:`module` constructed from `config`. Args: module: A python or user-defined clasSTRING
HIGHcolossalai/legacy/builder/builder.py27Returns an object constructed from `config`, the type of the object is specified by `registry`. Note: tSTRING
HIGHcolossalai/cli/launcher/run.py59Parse an inclusion or exclusion string and filter a hostfile dictionary. Examples: include_str="worker-0,woSTRING
HIGHcolossalai/_analyzer/fx/tracer/symbolic_trace.py37 Traces a ``torch.nn.Module`` or a function and returns a ``GraphModule`` with ``Node``s and ``MetaInfo`` attachSTRING
HIGHcolossalai/_analyzer/fx/passes/graph_profile.py233 Run a specific node ``n`` and profile its execution time and memory usage. Calls into call_function, caSTRING
HIGH…lossalai/auto_parallel/checkpoint/ckpt_solver_rotor.py311Backtrack the cost table and retrieve the optimal checkpointing strategy. Args: chain (Chain): A baSTRING
HIGHcolossalai/zero/gemini/placement_policy.py158 Evict tensors from CUDA device. Args: can_evict_chunks (List[StatefulTensor]): the list ofSTRING
HIGHcolossalai/tensor/d_tensor/layout_converter.py453 Check if the process groups required for sharding have been deleted by torch.distributed.destroy_procesSTRING
HIGH…/ColossalChat/coati/distributed/reward/reward_utils.py80 Modified from: https://gist.github.com/lewtun/9c2ce1937b741404090a3dc4c7c022b3 Retrieves the content from the lSTRING
HIGHapplications/ColossalChat/coati/models/generation.py279 Generates new tokens using a streaming approach. Args: model (Any): The model used for token generatioSTRING
Excessive Try-Catch Wrapping112 hits · 122 pts
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LOW…est_checkpoint_io/test_low_level_zero_checkpoint_io.py149 except Exception as e:CODE
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LOWtests/test_shardformer/test_model/test_shard_gpt2.py226 except Exception as e:CODE
LOWtests/test_shardformer/test_model/test_shard_gpt2.py271 except Exception as e:CODE
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LOWtests/test_shardformer/test_model/test_shard_llama.py81 except Exception as e:CODE
LOWtests/test_shardformer/test_model/test_shard_llama.py305 except Exception as e:CODE
LOWtests/test_shardformer/test_model/test_shard_llama.py359 except Exception as e:CODE
LOW…sts/test_shardformer/test_model/test_shard_chatglm2.py241 except Exception as e:CODE
LOWtests/test_shardformer/test_model/test_shard_qwen3.py214 except Exception as e:CODE
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LOW…test_booster/test_plugin/test_low_level_zero_plugin.py56 except Exception as e:CODE
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LOWtests/test_fx/test_tracer/test_patched_module.py16 except Exception as e:CODE
MEDIUMtests/test_fx/test_tracer/test_patched_module.py7def _run(data, module, patch_fn):CODE
LOW…racer/test_torchvision_model/test_torchvision_model.py41 except Exception as e:CODE
LOW…s/test_fx/test_tracer/test_hf_model/hf_tracer_utils.py23 except Exception as e:CODE
LOW…ts/test_fx/test_pipeline/test_timm_model/timm_utils.py29 except Exception as e:CODE
LOWtests/test_fx/test_pipeline/test_topo/topo_utils.py45 except Exception as e:CODE
LOWtests/test_fx/test_pipeline/test_hf_model/hf_utils.py32 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_lamb.py148 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_lamb.py230 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_lamb.py250 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_galore.py80 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_galore.py171 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_galore.py245 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_galore.py264 except Exception as e:CODE
LOWtests/test_optimizer/test_dist_galore.py289 except Exception as e:CODE
LOW…est_autochunk_diffuser/benchmark_autochunk_diffuser.py134 except Exception as e:CODE
LOW…t_autochunk_alphafold/benchmark_autochunk_alphafold.py123 except Exception as e:CODE
LOW…tochunk_transformer/benchmark_autochunk_transformer.py135 except Exception as e:CODE
LOWcolossalai/fx/tracer/experimental.py589 except Exception as e:CODE
LOWcolossalai/fx/tracer/tracer.py312 except Exception as e:CODE
LOWcolossalai/shardformer/layer/parallel_module.py152 except Exception as ex:STRING
LOWcolossalai/shardformer/layer/parallel_module.py330 except Exception as ex:STRING
LOWcolossalai/shardformer/layer/normalization.py22except Exception:CODE
LOWcolossalai/shardformer/shard/sharder.py200 except Exception as e:STRING
LOW…lossalai/legacy/zero/sharded_model/sharded_model_v2.py208 except Exception as e:STRING
LOW…lossalai/legacy/zero/sharded_model/sharded_model_v2.py556 except Exception as ex:STRING
LOWcolossalai/legacy/inference/async_manager.py148 except Exception:CODE
MEDIUMcolossalai/legacy/inference/async_manager.py135def start_dynamic_batching(args, tp_engine, waiting_req_list):CODE
LOWcolossalai/legacy/inference/manager.py293 except Exception:CODE
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LOWcolossalai/legacy/builder/builder.py55 except Exception as e:STRING
MEDIUMcolossalai/legacy/builder/builder.py56 print(f"An error occurred when building {mod_type} from registry {registry.name}", flush=True)STRING
LOWcolossalai/utils/safetensors.py12except Exception:CODE
LOWcolossalai/cli/launcher/multinode_runner.py55 except Exception as e:CODE
LOWcolossalai/_analyzer/fx/graph_module.py71 except Exception as e:CODE
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LOWcolossalai/_analyzer/fx/passes/graph_profile.py257 except Exception as e:CODE
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LOWcolossalai/lazy/pretrained.py259 except Exception:CODE
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LOWcolossalai/fx/tracer/tracer.py418 if node.op == "placeholder":CODE
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LOWcolossalai/fx/passes/passes_for_gpt2_test.py202 if n.op != "placeholder" and n._fx_partition > partition_name:CODE
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LOW⚡…x/passes/experimental/adding_shape_consistency_pass.py51 if node.op != "placeholder":CODE
LOW⚡…x/passes/experimental/adding_shape_consistency_pass.py53 input_specs_node = mod_graph.create_node("placeholder", target="sharding_spec_convert_dict")CODE
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Over-Commented Block86 hits · 86 pts
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LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py641 out_grad = torch.chunk(out_grad, DEPTH, dim=0)[i]COMMENT
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LOW…legacy/test_layers/test_2d/checks_2d/check_layer_2d.py741# mask_shape = (BATCH_SIZE // DEPTH, NUM_ATTENTION_HEADS // DEPTH, SEQ_LENGTH, SEQ_LENGTH)COMMENT
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py661COMMENT
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py681# assert out.shape == (BATCH_SIZE // TESSERACT_DIM, SEQ_LENGTH, INPUT_SIZE // TESSERACT_DIM)COMMENT
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py701# HIDDEN_SIZE,COMMENT
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py721# grad = torch.randn(grad_shape, dtype=dtype, device=device)COMMENT
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py741# attention_dropout_prob=0.5,COMMENT
LOW…/test_layers/test_2p5d/checks_2p5d/check_layer_2p5d.py761# grad_shape = out.shapeCOMMENT
LOW…rallel/test_tensor_shard/test_solver_with_resnet_v2.py21 mesh_shape = (2, 4)COMMENT
LOW…rallel/test_tensor_shard/test_solver_with_resnet_v2.py41 # %layer1_0_conv2 : [#users=1] = call_module[target=layer1.0.conv2](args = (%layer1_0_relu,), kwargs = {})COMMENT
LOWtests/kit/model_zoo/transformers/mistral.py1import torchCOMMENT
LOWtests/kit/model_zoo/transformers/whisper.py1import torchCOMMENT
LOWtests/kit/model_zoo/transformers/deepseek.py1# modified from tests/kit/model_zoo/transformers/mistral.pyCOMMENT
LOWtests/kit/model_zoo/transformers/bert.py1import torchCOMMENT
LOWtests/kit/model_zoo/transformers/deepseek_v3.py1# modified from tests/kit/model_zoo/transformers/mistral.pyCOMMENT
LOWtests/kit/model_zoo/transformers/sam.py1import torchCOMMENT
LOWtests/kit/model_zoo/transformers/mixtral.py1# modified from tests/kit/model_zoo/transformers/mistral.pyCOMMENT
LOWtests/kit/model_zoo/transformers/mixtral.py81# name="transformers_mixtral_for_sequence_classification",COMMENT
LOWtests/kit/model_zoo/transformers/blip2.py1import torchCOMMENT
LOWtests/test_tensor/test_comm_spec_apply.py81 if rank in (0, 1):COMMENT
LOWtests/test_tensor/test_dtensor/test_comm_spec.py61 sharded_tensor_1 = torch.ones(2, 1) * 3COMMENT
LOWtests/test_fx/test_tracer/test_bias_addition_module.py41 # %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.py61 torch.cuda.reset_peak_memory_stats()COMMENT
LOW…/test_fx/test_profiler/test_profiler_meta_info_prop.py101 # If we need to dive deep into the memory usage byCOMMENT
LOW…e/en/features/mixed_precision_training_with_booster.md221```pythonCOMMENT
LOWextensions/csrc/common/micros.h101// https://github.com/pytorch/pytorch/commit/3aeb78079bcd68282fe9117088e138b77318e288COMMENT
LOWextensions/csrc/common/micros.h221 } else { \COMMENT
LOWextensions/csrc/funcs/cast_functor.h1#pragma onceCOMMENT
LOWextensions/csrc/funcs/binary_functor.h1#pragma onceCOMMENT
LOWextensions/csrc/funcs/ternary_functor.h1#pragma onceCOMMENT
LOWextensions/csrc/funcs/unary_functor.h1#pragma onceCOMMENT
LOWextensions/csrc/kernel/cuda/attention/attention_utils.h21COMMENT
LOWextensions/csrc/kernel/x86/cpu_adam.h21*/COMMENT
LOWextensions/csrc/kernel/x86/cpu_adam.h41#define SIMD_WIDTH 16COMMENT
LOWextensions/csrc/kernel/x86/cpu_adam.h61#define SIMD_LOAD(x) _mm256_loadu_ps(x)COMMENT
LOWcolossalai/pipeline/schedule/v_schedule.py1# Refer from Zero Bubble Pipeline Parallelism.COMMENT
LOWcolossalai/nn/optimizer/adafactor.py1# coding=utf-8COMMENT
LOWcolossalai/shardformer/modeling/bert.py1081 # if uni-directional self-attention (decoder) save Tuple(torch.Tensor, torch.Tensor) ofCOMMENT
LOWcolossalai/legacy/pipeline/middleware/topo.py121 return resCOMMENT
LOWcolossalai/legacy/moe/openmoe/train.sh21# epCOMMENT
LOWcolossalai/legacy/moe/openmoe/test_ci.sh1# pip install -r requirements.txtCOMMENT
LOWcolossalai/legacy/moe/openmoe/test_ci.sh21# torchrun --standalone --nproc_per_node 4 train.py \COMMENT
LOW…salai/legacy/moe/openmoe/model/convert_openmoe_ckpt.py1# coding=utf-8COMMENT
LOWcolossalai/legacy/moe/openmoe/model/modeling_openmoe.py1# coding=utf-8COMMENT
LOWcolossalai/_analyzer/fx/graph_module.py21from torch.fx.graph_module import _exec_with_source, _forward_from_srcCOMMENT
LOWcolossalai/auto_parallel/checkpoint/ckpt_solver_base.py101 """COMMENT
LOW…salai/auto_parallel/passes/runtime_preparation_pass.py241 getitem_index = node.args[1]COMMENT
LOWcolossalai/device/device_mesh.py421 # key is axis nameCOMMENT
LOWcolossalai/tensor/colo_parameter.py81COMMENT
LOW…utorial/sequence_parallel/lr_scheduler/annealing_lr.py1# coding=utf-8COMMENT
LOWexamples/tutorial/sequence_parallel/data/__init__.py21 (train_dataloader, valid_dataloader, test_dataloader) = (None, None, None)COMMENT
LOW…/sequence_parallel/data/tokenizer/bert_tokenization.py1# coding=utf-8COMMENT
LOW…/tutorial/sequence_parallel/data/tokenizer/__init__.py1# coding=utf-8COMMENT
LOW…tutorial/sequence_parallel/data/tokenizer/tokenizer.py1# coding=utf-8COMMENT
LOW…l/sequence_parallel/data/datasets/blendable_dataset.py1# coding=utf-8COMMENT
LOW…torial/sequence_parallel/data/datasets/bert_dataset.py1# coding=utf-8COMMENT
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Structural Annotation Overuse27 hits · 49 pts
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LOW⚡colossalai/inference/README.md46# Step 1: create a model in "transformers" wayCOMMENT
LOW⚡colossalai/inference/README.md51# Step 2: create an inference_configCOMMENT
LOW⚡colossalai/inference/README.md60# Step 3: create an engine with model and configCOMMENT
LOW⚡colossalai/inference/README.md63# Step 4: try inferenceCOMMENT
LOWexamples/images/diffusion/README.md41#### Step 1: RequirementsCOMMENT
LOWexamples/images/diffusion/README.md57#### Step 2: Install [Colossal-AI](https://colossalai.org/download/) From Our Official WebsiteCOMMENT
LOWexamples/images/diffusion/README.md83#### Step 3: Accelerate with flash attention by xformers (Optional)COMMENT
LOW⚡applications/ColossalQA/README.md33#### Step 1: Collect DataCOMMENT
LOW⚡applications/ColossalQA/README.md37#### Step 2: Split DataCOMMENT
LOW⚡applications/ColossalQA/README.md41#### Step 3: Construct Vector StoresCOMMENT
LOW⚡applications/ColossalQA/README.md47#### Step 4: Retrieve Relative TextCOMMENT
LOW⚡applications/ColossalQA/README.md50#### Step 5: Format PromptCOMMENT
LOW⚡applications/ColossalQA/README.md53#### Step 6: InferenceCOMMENT
LOW⚡applications/ColossalQA/README.md56#### Step 7: Update MemoryCOMMENT
LOWapplications/ColossalChat/examples/README.md463#### Step 1: Data CollectionCOMMENT
LOWapplications/ColossalChat/examples/README.md485#### Step 2: PreprocessingCOMMENT
LOWapplications/ColossalChat/examples/README.md537#### Step 3: TrainingCOMMENT
LOWapplications/ColossalChat/examples/README.md547#### Step 1: Data CollectionCOMMENT
LOWapplications/ColossalChat/examples/README.md579#### Step 2: PreprocessingCOMMENT
LOWapplications/ColossalChat/examples/README.md583#### Step 3: TrainingCOMMENT
LOWapplications/ColossalChat/examples/README.md623#### Step 1: Data CollectionCOMMENT
LOWapplications/ColossalChat/examples/README.md654#### Step 2: PreprocessingCOMMENT
LOWapplications/ColossalChat/examples/README.md661#### Step 3: TrainingCOMMENT
LOWapplications/ColossalChat/examples/README.md742### Step 1: Data Collection & PreparationCOMMENT
LOWapplications/ColossalChat/examples/README.md745### Step 2: TrainingCOMMENT
LOWapplications/ColossalChat/examples/README.md800#### Step 1: Data Collection & PreparationCOMMENT
LOWapplications/ColossalChat/examples/README.md804#### Step 2: TrainingCOMMENT
Modern AI Meta-Vocabulary12 hits · 37 pts
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MEDIUM⚡applications/ColossalQA/README.md66Our platform accommodates two kinds of LLMs: API-accessible and locally run models. For the API-style LLMs, we support CCODE
MEDIUM⚡…tions/ColossalQA/examples/retrieval_conversation_en.py42 # Setup embedding model locallyCOMMENT
MEDIUM…tions/ColossalQA/examples/retrieval_conversation_zh.py41 # Setup embedding model locallyCOMMENT
MEDIUM⚡…examples/retrieval_conversation_en_customer_service.py44 # Setup embedding model locallyCOMMENT
MEDIUM…retrieval_intent_classification_zh_customer_service.py36 # Setup embedding model locallyCOMMENT
MEDIUMapplications/ColossalQA/examples/webui_demo/config.py6 "embed_name": "m3e", # embedding model nameCODE
MEDIUMapplications/ColossalQA/examples/webui_demo/config.py7 "embed_model_name_or_path": "moka-ai/m3e-base", # path to embedding model, could be a local path or a huggingfaCODE
MEDIUMapplications/ColossalQA/examples/webui_demo/README.md24## Configure the RAG ChainCOMMENT
MEDIUM…ications/ColossalEval/colossal_eval/dataset/agieval.py102# process few-shot raw_promptsCOMMENT
MEDIUM…ications/ColossalEval/colossal_eval/dataset/agieval.py214 # process demo once if it is few-shot-CoTCOMMENT
MEDIUM…tions/ColossalEval/colossal_eval/utils/conversation.py138 # First few shot data is something like "The following are questions about xxx".COMMENT
MEDIUM…tions/ColossalEval/colossal_eval/utils/conversation.py184 # For few-shot, only need input. Otherwise use instruction (in AGIEval).COMMENT
Redundant / Tautological Comments22 hits · 30 pts
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LOWtests/test_shardformer/test_model/_utils.py324 # Check if the output sequence is gathered before cross entropyCOMMENT
LOWcolossalai/booster/plugin/hybrid_parallel_plugin.py173 # Check if the DP group size is 1, meaning no synchronization is needed.STRING
LOWcolossalai/booster/plugin/hybrid_parallel_plugin.py854 # Check if the list of gradients is emptySTRING
LOWcolossalai/booster/plugin/hybrid_parallel_plugin.py1427 # Check if the optimizer is a HybridParallelZeroOptimizer and synchronize data parallelism gradients if so.COMMENT
LOWcolossalai/quantization/bnb.py160 # Check if the current key is not in the `modules_to_not_convert`COMMENT
LOWcolossalai/quantization/bnb.py232 # Check if it is a base modelSTRING
LOWcolossalai/tensor/d_tensor/layout_converter.py472 # Check if each process group is still aliveSTRING
LOWexamples/images/diffusion/main.py257 # Check if the train dataset is iterableCOMMENT
LOWexamples/images/diffusion/main.py274 # Check if the validation dataset is iterableCOMMENT
LOWexamples/images/diffusion/main.py289 # Check if the test dataset is iterableCOMMENT
LOWexamples/images/diffusion/main.py620 # Check if the "resume" option is specified, resume training from the checkpoint if it is trueCOMMENT
LOW⚡examples/images/diffusion/main.py854 # Assign melk to SIGUSR1 signal and divein to SIGUSR2 signalCOMMENT
LOW…flows/scripts/example_checks/detect_changed_example.py19 # Output the result using print. Then the shell can get the values.COMMENT
LOW…ons/ColossalChat/coati/distributed/reward/reward_fn.py140 # Check if the sequence is over lengthCOMMENT
LOW…ons/ColossalChat/coati/distributed/reward/reward_fn.py205 # Check if the sequence is over lengthCOMMENT
LOW⚡…ons/ColossalChat/coati/distributed/reward/reward_fn.py286 # Check if the sequence is over lengthCOMMENT
LOW…tions/ColossalChat/coati/dataset/tokenization_utils.py112 # Check if all labels are ignored, this may happen when the tokenized length is too longCOMMENT
LOW…tions/ColossalChat/coati/dataset/tokenization_utils.py321 # Check if loss mask is all 0s (no loss), this may happen when the tokenized length is too longCOMMENT
LOWapplications/ColossalChat/tests/test_train.sh406 # Check if the plugin is either "gemini_auto" or "gemini" and set grad_accu to '1'COMMENT
LOWapplications/ColossalChat/tests/test_lora.py59 # Check if model has overfittedCOMMENT
LOW…ns/ColossalChat/examples/training_scripts/train_kto.py182 # 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.py173 # Set stop_ids to eos_token_id for other dataset types if not existCOMMENT
AI Slop Vocabulary17 hits · 30 pts
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LOWcolossalai/fx/tracer/tracer.py97 # if no extra manipulation is applied, we just pass the origin arguments to create_proxy functionCOMMENT
MEDIUMcolossalai/legacy/context/parallel_mode.py17 # this is added to facilitate amp and grad clipping in hybrid parallelCOMMENT
LOW…lossalai/legacy/zero/sharded_optim/sharded_optim_v2.py339 # We just set p.data = p.colo_attr.saved_grad.payload hereCOMMENT
MEDIUM…egacy/zero/shard_utils/bucket_tensor_shard_strategy.py40 # Ensure we utilize maximum PCIE bandwidthCOMMENT
LOWcolossalai/autochunk/estimate_memory.py197 # if node is placeholder, just add the size of the nodeCOMMENT
LOWcolossalai/cli/launcher/hostinfo.py36 port = 22 # no port specified, lets just use the ssh portCODE
LOWcolossalai/zero/gemini/chunk/chunk.py332 # just use another way for the movementCOMMENT
LOWcolossalai/lazy/lazy_init.py340 # inplace op, just return origin lazy tensorCOMMENT
MEDIUMcolossalai/kernel/triton/context_attn_unpad.py602 # NOTE use `triton.next_power_of_2` here to utilize the cache mechanism of tritonCOMMENT
MEDIUMcolossalai/kernel/triton/flash_decoding.py409 # NOTE use `triton.next_power_of_2` here to utilize the cache mechanism of tritonCOMMENT
LOW…utorial/sequence_parallel/lr_scheduler/annealing_lr.py67 # If the learning rate is constant, just return the initial value.COMMENT
LOWexamples/language/gpt/gemini/train_gpt_demo.py210 # we just use randomly generated data hereCOMMENT
LOW…uage/gpt/experiments/pipeline_parallel/train_gpt_pp.py143 # we just use randomly generated data hereCOMMENT
LOW…pt/experiments/auto_parallel/auto_parallel_with_gpt.py81 # we just use randomly generated data hereCOMMENT
LOW…les/community/roberta/pretraining/utils/global_vars.py113 # pollutes the runs list, so we just add each as a scalarCOMMENT
MEDIUM…/ColossalChat/coati/distributed/reward/reward_utils.py21 """Performs comprehensive validation of response structure.STRING
MEDIUM…cations/ColossalChat/coati/utils/reward_score/utils.py21 """Performs comprehensive validation of response structure.STRING
Slop Phrases6 hits · 14 pts
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MEDIUMcolossalai/shardformer/shard/shard_config.py116 # you can add all the optimization flag hereSTRING
MEDIUM…s/tutorial/opt/inference/script/processing_ckpt_66b.py7# you can use whether wget or git lfsCOMMENT
MEDIUM…ples/community/roberta/preprocessing/sentence_split.py143 # if you have multiple server, you can use code below or modify code to openmpiCOMMENT
MEDIUM…mples/community/roberta/preprocessing/tokenize_mask.py239 # if you have multiple server, you can use code below or modify code to openmpiCOMMENT
MEDIUMapplications/ColossalQA/data/tests/test.html1113<p>If you are using {}-formatting (<a class="reference internal" href="https://docs.python.org/3/library/stdtypes.html#sCODE
MEDIUMapplications/ColossalQA/data/tests/test.html1296counterparts in <a class="reference internal" href="https://docs.python.org/3/library/logging.html#logging.Logger" titleCODE
Cross-Language Confusion3 hits · 10 pts
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HIGHcolossalai/legacy/nn/layer/parallel_3d/_utils.py90 return _async_grad_bucket.push(op, grad, param_id)CODE
HIGHcolossalai/legacy/moe/layer/layers.py312 | C1 || C2 || C3 || C4 |STRING
HIGHcolossalai/legacy/moe/layer/layers.py313 | A1 || A2 | | R1 | A3 || R2 | A4 || R3 | | R4 |STRING
Hallucination Indicators1 hit · 10 pts
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CRITICAL…ns/ColossalChat/coati/distributed/inference_backend.py284 self.llm.llm_engine.model_executor.driver_worker.model_runner.model.load_weights(state_dict.items())CODE
TODO Padding4 hits · 8 pts
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LOW…ssalai/booster/mixed_precision/mixed_precision_base.py22 # TODO: implement this methodCOMMENT
LOWcolossalai/legacy/inference/hybridengine/engine.py73 # TODO: implement early_stopping, and various generation optionsCOMMENT
LOW⚡colossalai/auto_parallel/tensor_shard/initialize.py62 # TODO: implement this functionCOMMENT
LOW⚡colossalai/auto_parallel/tensor_shard/initialize.py70 # TODO: implement this functionCOMMENT
Verbosity Indicators3 hits · 3 pts
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LOW⚡colossalai/fx/codegen/activation_checkpoint_codegen.py586 # we need to check if the checkpoint need to offload the inputSTRING
LOW⚡colossalai/fx/codegen/activation_checkpoint_codegen.py593 # we need to check if the checkpoint need use_reentrant=FalseSTRING
LOW.github/workflows/scripts/check_doc_i18n.py6 # First, we need to check if the two directories existCOMMENT
AI Response Leakage1 hit · 2 pts
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HIGHcolossalai/legacy/utils/profiler/profiler.py101 # In this example with wait=1, warmup=1, active=2,STRING
Overly Generic Function Names3 hits · 2 pts
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LOW⚡colossalai/auto_parallel/tensor_shard/utils/misc.py20 def do_something():STRING
LOWcolossalai/testing/utils.py235 def do_something(rank, world_size, port):STRING
LOWcolossalai/testing/utils.py241 def do_something(rank, world_size, port, arg1, arg2):STRING