EngineX-Iluvatar/enginex-bi_series-diffusers
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remove unnecessary files

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Zhang Hao
2025-08-26 20:32:18 +08:00
parent be947dfc79
commit 2d4c9a1544
11 changed files with 6 additions and 53 deletions
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1
Dockerfile
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Dockerfile.bi100

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Dockerfile Normal file
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FROM git.modelhub.org.cn:980/enginex-iluvatar/bi100-3.2.1-x86-ubuntu20.04-py3.10-poc-llm-infer:v1.2.2
WORKDIR /workspace
ENV PT_SDPA_ENABLE_HEAD_DIM_PADDING=1
RUN pip install diffusers==0.34.0
COPY main.py test.sh dataset.json /workspace/

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Dockerfile.a100
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FROM pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel
WORKDIR /workspace
# ENV PT_SDPA_ENABLE_HEAD_DIM_PADDING=1
RUN pip install diffusers transformers sentencepiece
COPY main.py test.sh dataset.json /workspace/

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Dockerfile.bi100
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FROM git.modelhub.org.cn:980/enginex-iluvatar/bi100-3.2.1-x86-ubuntu20.04-py3.10-poc-llm-infer:v1.2.2
WORKDIR /workspace
ENV PT_SDPA_ENABLE_HEAD_DIM_PADDING=1
RUN pip install diffusers==0.34.0
COPY main.py test.sh dataset.json /workspace/

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Dockerfile.mlu370
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FROM git.modelhub.org.cn:9443/enginex-cambricon/mlu370-pytorch:v25.01-torch2.5.0-torchmlu1.24.1-ubuntu22.04-py310
WORKDIR /workspace
ENV PATH=/torch/venv3/pytorch_infer/bin:/workspace/ffmpeg-mlu-v4.2.0/install/bin:/usr/local/neuware/bin:/usr/local/openmpi/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
RUN pip install diffusers==0.34.0
RUN sed -i 's|source /torch/venv3/pytorch/bin/activate|source /torch/venv3/pytorch_infer/bin/activate|' /root/.bashrc
COPY main.py test.sh dataset.json /workspace/

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Dockerfile.mrv100
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FROM git.modelhub.org.cn:980/enginex-iluvatar/mr100_corex:4.3.0
WORKDIR /workspace
RUN pip install diffusers==0.34.0 sentencepiece transformers==4.55.2
COPY main.py test.sh dataset.json /workspace/

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run_in_docker_a100.sh
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#! /usr/bin/env bash
image=harbor-contest.4pd.io/zhanghao/diffusers:a100-0.2
docker run -it -v /home/zhanghao/workspace:/workspace -v /mnt:/mnt $image bash

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run_in_docker_bi100.sh
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#! /usr/bin/env bash
image=harbor-contest.4pd.io/zhanghao/diffusers:bi100-0.2
docker run -it -v /root/zhanghao:/workspace -v /mnt:/mnt --device=dev/iluvatar1:/dev/iluvatar0 $image bash

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run_in_docker_mlu370.sh
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#! /usr/bin/env bash
# cnmon
image=harbor-contest.4pd.io/zhanghao/diffusers:mlu370-0.2
device_id=2
docker run -it -v /root/zhanghao:/workspace -v /mnt:/mnt --device=/dev/cambricon_dev$device_id:/dev/cambricon_dev0 --device=/dev/cambricon_ctl:/dev/cambricon_ctl $image bash

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run_in_docker_mrv100.sh
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#! /usr/bin/env bash
image=harbor-contest.4pd.io/zhanghao/diffusers:mrv100-0.2
docker run -it -v /root/zhanghao:/workspace -v /mnt:/mnt --device=dev/iluvatar0:/dev/iluvatar0 $image bash

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test.py
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from diffusers import DiffusionPipeline
import torch
import time
model_path = "/mnt/contest_ceph/zhanghao/models/stable-diffusion-v1-5"
# model_path = "/mnt/contest_ceph/zhanghao/models/stable-diffusion-3.5-medium"
pipeline = DiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16)
pipeline.to("cuda")
start = time.time()
image = pipeline("An image of a squirrel in Picasso style").images[0]
end = time.time()
print(f"elapsed: {end - start}")
image.save("squirrel_picasso.png")

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test.sh
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python3 main.py --model "/mnt/contest_ceph/zhanghao/models/stable-diffusion-v1-5" --json "dataset.json" --results "results.json" --outdir "output" --device cuda --dtype fp16