文件最后提交记录最后更新时间
test(megatron): pipeline ut testcase fix Co-authored-by: xuguoliang3<xuguoliang3@huawei.com> # message auto-generated for no-merge-commit merge: !4559 merge 20260602_ut_fix into master test(megatron): pipeline ut testcase fix Created-by: xuguoliang3 Commit-by: xuguoliang3 Merged-by: ascend-robot Description: ## What this PR does / why we need it? fix pipeline ut testcase posttrain/ldt_sft/test_initialize.py fix the incorrect package path in core/layerwise_disaggregated_training/initialize.py, this branch is compatible with the original Megatron process and will not be executed in the scenarios supported by LDT. ## Does this PR introduce any user-facing change? no user-facing change ## How was this patch tested? test by CI See merge request: Ascend/MindSpeed-LLM!455913 小时前
feat(pytorch): Add MindSpeed Muon feature Co-authored-by: HanhuiChen<chenhanhui1@h-partners.com> # message auto-generated for no-merge-commit merge: !4549 merge master into master feat(pytorch): Add MindSpeed Muon feature Created-by: HANHU1CHEN Commit-by: HanhuiChen Merged-by: ascend-robot Description: ## What this PR does / why we need it? Replaces the in-repo self-maintained Muon optimizer with MindSpeed's native Muon implementation, removing the legacy code and adapting the patch registration accordingly. ## Does this PR introduce any user-facing change? No change to the Muon usage interface; existing Muon training scripts and arguments continue to work. The underlying implementation is switched to MindSpeed's native version. ## How was this patch tested? Precision has been verified: training with the native Muon optimizer was aligned against the previous self-maintained implementation, with consistent loss and grad-norm behavior. See merge request: Ascend/MindSpeed-LLM!454916 小时前
chore(fsdp2): develop longcat-flash-lite model in fsdp2 Co-authored-by: guihaowen666<guihaowen@huawei.com> # message auto-generated for no-merge-commit merge: !4344 merge br_master_longcat_flash_lite_fsdp2 into master chore(fsdp2): develop longcat-flash-lite model in fsdp2 Created-by: guihaowen666 Commit-by: guihaowen666 Merged-by: ascend-robot Description: ## What this PR does / why we need it? develop longcat-flash-lite model in fsdp2 ## Does this PR introduce any user-facing change? new model development, no user-facing change ## How was this patch tested? Run the inference task and check whether the model can perform normal dialogs. See merge request: Ascend/MindSpeed-LLM!43449 小时前
feat(pytorch): add DeepSeek4 fine-tuning template Co-authored-by: HanhuiChen<chenhanhui1@h-partners.com> # message auto-generated for no-merge-commit merge: !4436 merge dsv4 into master feat(pytorch): add DeepSeek4 fine-tuning template Created-by: HANHU1CHEN Commit-by: HanhuiChen Merged-by: ascend-robot Description: ## What this PR does / why we need it? Adds a fine-tuning template for the DeepSeek4 model series to support its specific prompt format, including thinking mode, tool calling (DSML format), and reasoning effort control. ## Does this PR introduce any user-facing change? Yes — users can now select --prompt-type deepseek4 to fine-tune DeepSeek4 models. Two new behaviors are also exposed: - --enable-thinking controls thinking vs chat mode - --reasoning-effort {max,high} inserts a max-effort instruction prefix; only valid when thinking is enabled - --drop-thinking controls whether reasoning content is kept in each turn ## How was this patch tested? Tested with byte-level alignment against the official encoding_dsv4 script. See merge request: Ascend/MindSpeed-LLM!443625 天前
[pytorch][feature]Decouple the 'variable-seq-lengths' and 'no-pad-to-seq-lengths' parameters Co-authored-by: mhh001<mahonghao1@huawei.com> # message auto-generated for no-merge-commit merge: !3579 merge master_pad into master [pytorch][feature]Decouple the 'variable-seq-lengths' and 'no-pad-to-seq-lengths' parameters Created-by: mhh111 Commit-by: mhh001 Merged-by: ascend-robot Description: [pytorch][feature]Decouple the 'variable-seq-lengths' and 'no-pad-to-seq-lengths' parameters See merge request: Ascend/MindSpeed-LLM!35796 个月前
feat(torch): add GLM-4.5 scripts Co-authored-by: cjy840282<chenjingyi9@huawei.com> # message auto-generated for no-merge-commit merge: !4369 merge GLM-4.5-new into master feat(torch): add GLM-4.5 scripts Created-by: cjy840282 Commit-by: cjy840282 Merged-by: ascend-robot Description: ## What this PR does / why we need it? add GLM-4.5 scripts. ## Does this PR introduce any user-facing change? support GLM-4.5 lora finetune. ## How was this patch tested? vllm inference is normal. See merge request: Ascend/MindSpeed-LLM!43691 个月前
docs: Add comprehensive docstrings for core modules Co-authored-by: wangjiangben<wangjiangben@huawei.com> # message auto-generated for no-merge-commit merge: !4397 merge feature/add-docstrings into master docs: Add comprehensive docstrings for core modules Created-by: wangjiangben Commit-by: wangjiangben Merged-by: ascend-robot Description: ## Summary This PR adds detailed English docstrings for key functions and classes across multiple core modules to improve code documentation and maintainability. ## Changes ### Core Modules (mindspeed_llm/core/) - **context_parallel**: Add docstrings for context parallel attention and wrapper functions - CPDotProductAttention: Context parallel dot product attention implementation - attention_init_wrapper: Attention initialization with Ulysses and hybrid CP support - **datasets**: Add docstrings for dataset building utilities - need_to_build_dataset: Determine which ranks need to build datasets - build_generic_dataset: Build distributed datasets - **distributed**: Add docstrings for gradient sync and buffer management - start_grad_sync_wrapper: Gradient synchronization with distributed optimizer support - recover_gradient_scaling_factors: Restore gradient scaling factors - **models**: Add docstrings for GPT layer specifications - get_gpt_layer_local_spec_wrapper: GPT layer spec with custom normalization - build_layers_wrapper: Layer building with MC2 optimization for MoE - **parallel_state**: Add docstrings for parallel initialization - initialize_model_parallel_decorator: Model parallel initialization with expert parallel support - **transformer**: Add docstrings for transformer block functions - get_num_layers_to_build: Calculate layers for current pipeline stage - get_layer_offset_wrapper: Layer offset with custom distribution support - transformer_block_init_wrapper: TransformerBlock initialization ### Operators (mindspeed_llm/ops/) - **triton**: Add docstrings for NPU optimization functions - get_npu_properties: Get NPU device properties - rms_norm_ref: Reference implementation of RMS normalization with gating ### Transformer Engine (mindspeed_llm/te/) - Add docstrings for transformer engine attention - do_kvallgather_context_parallel: Context parallel attention with KV AllGather strategy ### Training (mindspeed_llm/training/) - **arguments**: Add docstrings for argument parsing - extra_args_provider_decorator: Add MindSpeed-LLM specific arguments - parse_args_decorator: Parse arguments with MindSpeed-LLM processing - core_transformer_config_from_args_wrapper: Create TransformerConfig with extensions - validate_args_v2_decorator: Validate arguments with MindSpeed-LLM extensions - **checkpointing**: Add docstrings for checkpoint management - _load_base_checkpoint_wrapper: Load checkpoint with LoRA support - load_checkpoint_wrapper: Load checkpoint with loose loading support - **initialize**: Add docstrings for initialization - _compile_dependencies: Compile dataset index builder dependencies - **training**: Add docstrings for training utilities - _enable_npu_datadump_step_end: Enable NPU data dump - update_save_checkpoint_chmod: Update checkpoint file permissions - **utils**: Add docstrings for utility functions - _disable_gc: Context manager to disable garbage collection - temporal_async_caller_schedule_async_call: Schedule async call with GC disabled ## Documentation Standards All docstrings follow Python standard format: - Brief description of function/class purpose - Args: Parameter descriptions with types - Returns: Return value description - Note: Important usage notes and constraints (where applicable) ## Statistics - **Files changed**: 13 - **Lines added**: 443 - **Lines removed**: 6 ## Testing - All docstrings are written in English - Docstrings accurately describe function behavior - No functional code changes, only documentation improvements ## Related Issues Improves code documentation and developer experience for MindSpeed-LLM core modules. See merge request: Ascend/MindSpeed-LLM!43971 个月前
feat: Optimize deepseekV4's rmsnorm operator performance Co-authored-by: LinShua<707894133@qq.com> # message auto-generated for no-merge-commit merge: !4553 merge master_rmsnorm_ascendC into master feat: Optimize deepseekV4's rmsnorm operator performance Created-by: LinShua Commit-by: LinShua Merged-by: ascend-robot Description: ## What this PR does / why we need it? 优化deepseekV4's rmsnorm性能,调用融合算子 ## Does this PR introduce any user-facing change? NA ## How was this patch tested? NA See merge request: Ascend/MindSpeed-LLM!45531 天前
fix(pytorch):fix kvallgather for pipeline. Co-authored-by: yanzhixiao<yanzhixiao@h-partners.com> # message auto-generated for no-merge-commit merge: !4409 merge bugfix-pipeline-0414 into master fix(pytorch):fix kvallgather for pipeline. Created-by: yanzhixiao23 Commit-by: yanzhixiao Merged-by: ascend-robot Description: ## What this PR does / why we need it? Fix kvallgather for pipeline. ## Does this PR introduce any user-facing change? NA ## How was this patch tested? NA See merge request: Ascend/MindSpeed-LLM!44091 个月前
feat(pytorch): add DeepSeek4 fine-tuning template Co-authored-by: HanhuiChen<chenhanhui1@h-partners.com> # message auto-generated for no-merge-commit merge: !4436 merge dsv4 into master feat(pytorch): add DeepSeek4 fine-tuning template Created-by: HANHU1CHEN Commit-by: HanhuiChen Merged-by: ascend-robot Description: ## What this PR does / why we need it? Adds a fine-tuning template for the DeepSeek4 model series to support its specific prompt format, including thinking mode, tool calling (DSML format), and reasoning effort control. ## Does this PR introduce any user-facing change? Yes — users can now select --prompt-type deepseek4 to fine-tune DeepSeek4 models. Two new behaviors are also exposed: - --enable-thinking controls thinking vs chat mode - --reasoning-effort {max,high} inserts a max-effort instruction prefix; only valid when thinking is enabled - --drop-thinking controls whether reasoning content is kept in each turn ## How was this patch tested? Tested with byte-level alignment against the official encoding_dsv4 script. See merge request: Ascend/MindSpeed-LLM!443625 天前
[pytorch][feature]FSDP2 backend supports the Transformers training process. Co-authored-by: sunjunjie1587<sunjunjie8@huawei.com> # message auto-generated for no-merge-commit merge: !4043 merge master into master [pytorch][feature]FSDP2 backend supports the Transformers training process. Created-by: sunjunjie1587 Commit-by: sunjunjie1587 Merged-by: ascend-robot Description: FSDP2 backend supports the Transformers training process. See merge request: Ascend/MindSpeed-LLM!40434 个月前