From 21f17cca691d5df41863184a188b259feada99bb Mon Sep 17 00:00:00 2001 From: Wing Lian Date: Mon, 29 May 2023 00:06:35 -0400 Subject: [PATCH] bnb fixes --- .github/workflows/base.yml | 2 +- docker/Dockerfile-base | 2 +- scripts/finetune.py | 18 +++++++++--------- 3 files changed, 11 insertions(+), 11 deletions(-) diff --git a/.github/workflows/base.yml b/.github/workflows/base.yml index 571faf771..5a3f90992 100644 --- a/.github/workflows/base.yml +++ b/.github/workflows/base.yml @@ -1,4 +1,4 @@ -name: ci-cd +name: ci-cd-base on: push: diff --git a/docker/Dockerfile-base b/docker/Dockerfile-base index 4f4431dbe..6399d60ee 100644 --- a/docker/Dockerfile-base +++ b/docker/Dockerfile-base @@ -90,7 +90,7 @@ COPY --from=flash-attn-builder /workspace/flash-attention/csrc/rotary/dist/rotar COPY --from=flash-attn-builder /workspace/flash-attention/csrc/layer_norm/dist/dropout_layer_norm-*.whl wheels RUN pip3 install wheels/deepspeed-*.whl wheels/flash_attn-*.whl wheels/fused_dense_lib-*.whl wheels/xentropy_cuda_lib-*.whl wheels/rotary_emb-*.whl wheels/dropout_layer_norm-*.whl -RUN cd /workspace/builds/bitsandbytes && python3 setup.py install +RUN cd /workspace/builds/bitsandbytes && cp bitsandbytes/libbitsandbytes_cuda.so bitsandbytes/libbitsandbytes_cuda${CUDA_VERSION_BNB}.so && python3 setup.py install RUN git lfs install --skip-repo RUN pip3 install "peft @ git+https://github.com/huggingface/peft.git@main" \ "accelerate @ git+https://github.com/huggingface/accelerate.git@main" \ diff --git a/scripts/finetune.py b/scripts/finetune.py index 1d1eb9f95..58f1c0957 100644 --- a/scripts/finetune.py +++ b/scripts/finetune.py @@ -178,6 +178,15 @@ def train( tokenizer, cfg, DEFAULT_DATASET_PREPARED_PATH ) + if cfg.debug or "debug" in kwargs: + logging.info("check_dataset_labels...") + check_dataset_labels( + train_dataset.select( + [random.randrange(0, len(train_dataset) - 1) for i in range(5)] + ), + tokenizer, + ) + if prepare_ds_only: logging.info("Finished preparing dataset. Exiting...") return @@ -213,15 +222,6 @@ def train( model.save_pretrained(cfg.output_dir) return - if cfg.debug: - logging.info("check_dataset_labels...") - check_dataset_labels( - train_dataset.select( - [random.randrange(0, len(train_dataset) - 1) for i in range(5)] - ), - tokenizer, - ) - trainer = setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer) model.config.use_cache = False