Merge branch 'master' into patch-1

.github/workflows/nv-a6000.yml

@@ -0,0 +1,56 @@
+name: nv-a6000
+
+on:
+  pull_request:
+    paths-ignore:
+      - 'docs/**'
+      - 'blogs/**'
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+permissions:
+  contents: read
+  issues: write
+
+jobs:
+  unit-tests:
+    runs-on: [self-hosted, nvidia, a6000]
+    container:
+      image: nvcr.io/nvidia/pytorch:23.03-py3
+      ports:
+        - 80
+      options: --gpus all --shm-size "8G"
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - name: Check container state
+        run: |
+          ldd --version
+          nvcc --version
+          nvidia-smi
+          python -c "import torch; print('torch:', torch.__version__, torch)"
+          python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
+      - name: Install transformers
+        run: |
+          git clone https://github.com/huggingface/transformers
+          cd transformers
+          git rev-parse --short HEAD
+          python -m pip install .
+      - name: Install deepspeed
+        run: |
+          python -m pip install docutils==0.18.1 jinja2==3.0 urllib3==1.26.11 ninja
+          python -m pip install .[dev,1bit,autotuning]
+          ds_report
+      - name: Python environment
+        run: |
+          python -m pip list
+      - name: Unit tests
+        run: |
+          unset TORCH_CUDA_ARCH_LIST # only jit compile for current arch
+          cd tests
+          python -m pytest --color=yes --durations=0 --verbose -rF -m 'inference_v2' unit/ --torch_ver="2.0" --cuda_ver="12"
+          python -m pytest --color=yes --durations=0 --verbose -rF -m 'inference_v2_ops' unit/ --torch_ver="2.0" --cuda_ver="12"

.github/workflows/nv-inference.yml

@@ -34,6 +34,7 @@ jobs:
         run: |
           git clone https://github.com/huggingface/transformers
           cd transformers
+          git checkout f370bebdc
           git rev-parse --short HEAD
           pip install .
 

.github/workflows/nv-pre-compile-ops.yml

@@ -33,7 +33,7 @@ jobs:
             #python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
         - name: Compile DeepSpeed Ops
           run: |
-            TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0" DS_BUILD_OPS=1 DS_BUILD_SPARSE_ATTN=0 DS_BUILD_EVOFORMER_ATTN=0 pip3 install .
+            TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0" DS_BUILD_OPS=1 DS_BUILD_SPARSE_ATTN=0  DS_BUILD_CUTLASS_OPS=0 DS_BUILD_RAGGED_DEVICE_OPS=0 DS_BUILD_EVOFORMER_ATTN=0 pip3 install .
         - name: DS Report
           run: |
              ds_report

.pre-commit-config.yaml

@@ -49,6 +49,7 @@ repos:
         entry: ./scripts/check-license.py
         language: python
         files: \.(py|c|cpp|cu|cc|h|hpp|cuh|hip|tr)$
+        exclude: ^(deepspeed/inference/v2/kernels/ragged_ops/blocked_flash|deepspeed/inference/v2/kernels/cutlass_ops/grouped_gemm)
 
 -   repo: https://github.com/codespell-project/codespell
     rev: v2.1.0

MANIFEST.in

@@ -1,4 +1,6 @@
 include *.txt README.md
+include deepspeed/inference/v2/kernels/ragged_ops/libs/*.so
+include deepspeed/inference/v2/kernels/cutlass_ops/libs/*.so
 recursive-include requirements *.txt
 recursive-include deepspeed *.cpp *.h *.cu *.hip *.tr *.cuh *.cc *.json
 recursive-include csrc *.cpp *.h *.cu *.tr *.cuh *.cc

README.md

@@ -15,6 +15,7 @@
 ## Latest News
 <b> <span style="color:orange" > DeepSpeed empowers ChatGPT-like model training with a single click, offering 15x speedup over SOTA RLHF systems with unprecedented cost reduction at all scales; [learn how](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat)</span>.</b>
 
+* [2023/11] [DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-fastgen)
 * [2023/10] [DeepSpeed-VisualChat: Improve Your Chat Experience with Multi-Round Multi-Image Inputs](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-visualchat/10-03-2023/README.md) [[English](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-visualchat/10-03-2023/README.md)] [[中文](https://github.com/microsoft/DeepSpeed/blob/master/blogs/deepspeed-visualchat/10-03-2023/README-Chinese.md)] [[日本語](https://github.com/microsoft/DeepSpeed/blob/master/blogs/deepspeed-visualchat/10-03-2023/README-Japanese.md)]
 * [2023/09] Announcing the DeepSpeed4Science Initiative: Enabling large-scale scientific discovery through sophisticated AI system technologies [[DeepSpeed4Science website](https://deepspeed4science.ai/)] [[Tutorials](https://www.deepspeed.ai/deepspeed4science/)] [[White paper](https://arxiv.org/abs/2310.04610)] [[Blog](https://www.microsoft.com/en-us/research/blog/announcing-the-deepspeed4science-initiative-enabling-large-scale-scientific-discovery-through-sophisticated-ai-system-technologies/)] [[中文](https://github.com/microsoft/DeepSpeed/blob/master/blogs/deepspeed4science/chinese/README.md)] [[日本語](https://github.com/microsoft/DeepSpeed/blob/master/blogs/deepspeed4science/japanese/README.md)]
 * [2023/08] [DeepSpeed ZeRO-Inference: 20X faster inference through weight quantization and KV cache offloading](https://github.com/microsoft/DeepSpeedExamples/blob/master/inference/huggingface/zero_inference/README.md)

accelerator/cuda_accelerator.py

@@ -153,9 +153,26 @@ def max_memory_reserved(self, device_index=None):
     def total_memory(self, device_index=None):
         return torch.cuda.get_device_properties(device_index).total_memory
 
+    def _get_nvml_gpu_id(self, torch_gpu_id):
+        """
+        credit: https://discuss.pytorch.org/t/making-pynvml-match-torch-device-ids-cuda-visible-devices/103020
+
+        Remap torch device id to nvml device id, respecting CUDA_VISIBLE_DEVICES.
+
+        If the latter isn't set return the same id
+        """
+        # if CUDA_VISIBLE_DEVICES is used automagically remap the id since pynvml ignores this env var
+        if "CUDA_VISIBLE_DEVICES" in os.environ:
+            ids = list(map(int, os.environ.get("CUDA_VISIBLE_DEVICES", "").split(",")))
+            return ids[torch_gpu_id]  # remap
+        else:
+            return torch_gpu_id
+
     def available_memory(self, device_index=None):
         if pynvml:
-            handle = pynvml.nvmlDeviceGetHandleByIndex(device_index)
+            if device_index is None:
+                device_index = self.current_device()
+            handle = pynvml.nvmlDeviceGetHandleByIndex(self._get_nvml_gpu_id(device_index))
             info = pynvml.nvmlDeviceGetMemoryInfo(handle)
             return info.free
         else: