remove uncessary files

Dockerfile

@@ -1 +0,0 @@
-Dockerfile.bi100

Dockerfile

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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/

Dockerfile.a100

@@ -1,5 +0,0 @@
-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/

Dockerfile.bi100

@@ -1,6 +0,0 @@
-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/

Dockerfile.mlu370

@@ -1,8 +0,0 @@
-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/

Dockerfile.mrv100

@@ -1,5 +0,0 @@
-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/

README.md

@@ -17,7 +17,7 @@ docker build -t diffusers:v0.1 .
 ```
 
 ## 测试结果
-|      | A100 平均生成时间（秒） | 天垓100 平均生成时间（秒） |
+|      | A100 平均生成时间（秒） | 智铠100 平均生成时间（秒） |
 |------|-------------------------|----------------------------|
-| 时间 | 1.4289                  | 7.5609                     |
+| 时间 | 1.5                  | 4.1                    |
 

run_in_docker_a100.sh

@@ -1,3 +0,0 @@
-#! /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

run_in_docker_bi100.sh

@@ -1,3 +0,0 @@
-#! /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

run_in_docker_mlu370.sh

@@ -1,5 +0,0 @@
-#! /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

run_in_docker_mrv100.sh

@@ -1,3 +0,0 @@
-#! /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

test.py

@@ -1,13 +0,0 @@
-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")

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