Merge branch 'main' of github.com:Oneflow-Inc/CoModels into main

README.md

@@ -1,9 +1 @@
 # Models implemented with OneFlow framework.
-
-- cv
-- nlp
-  - [text_classfication](./nlp/text_classfication/)
-  - [odd_numbers](./nlp/odd_numbers/)
-- science
-- audio
-- vidio

cv/classification/README.md

@@ -90,12 +90,20 @@ For CIFAR100, you only need to specify the dataset downloaded path in [config.py
 
 
 ### Training
-- ddp training with simple bash file
+
+You can use bash script `train.sh` to train this model.
+
+```bash
+sh train.sh
+```
+
+### inference
+
+Bash script `infer.sh` is used to infer the trained model.
+
 ```bash
-cd vision/projects/classification/
-bash ddp_training.sh
+sh infer.sh
 ```
 
 
-## Reference
-- [Swin-Transformer](https://github.com/microsoft/Swin-Transformer)
+

cv/classification/cait_M36_384/README.md

@@ -0,0 +1,66 @@
+## cait_M36_384
+
+### Installation
+- Install the latest version of OneFlow
+```bash
+python3 -m pip install oneflow -f https://staging.oneflow.info/branch/master/[PLATFORM]
+```
+Find more information on [install oneflow](https://github.com/Oneflow-Inc/oneflow#install-oneflow)
+
+- Install flowvision
+
+Then install the latest stable release of flowvision
+
+```bash
+pip install flowvision==0.2.1
+```
+
+- Install other requirements
+```bash
+python3 -m pip install -r requirements.txt
+```
+
+### Dataset
+#### ImageNet
+For ImageNet dataset, you can download it from http://image-net.org/. We provide the following two ways to load data:
+
+- For standard folder dataset, move validation images to labeled sub-folders. The file structure should look like:
+  ```bash
+  $ tree data
+  imagenet
+  ├── train
+  │   ├── class1
+  │   │   ├── img1.jpeg
+  │   │   ├── img2.jpeg
+  │   │   └── ...
+  │   ├── class2
+  │   │   ├── img3.jpeg
+  │   │   └── ...
+  │   └── ...
+  └── val
+      ├── class1
+      │   ├── img4.jpeg
+      │   ├── img5.jpeg
+      │   └── ...
+      ├── class2
+      │   ├── img6.jpeg
+      │   └── ...
+      └── ...
+
+
+### Training
+
+You can use bash script `train.sh` to train this model.
+
+```bash
+sh train.sh
+```
+
+### inference
+
+Bash script `infer.sh` is used to infer the trained model.
+
+```bash
+sh infer.sh
+```
+

cv/classification/cait_M36_384/infer.sh

@@ -0,0 +1,18 @@
+export PYTHONPATH=$PWD:$PYTHONPATH
+set -aux
+
+GPU_NUMS=1
+PORT=12346
+MODEL_ARCH="cait_M36_384"
+
+python3 -m oneflow.distributed.launch \
+        --nproc_per_node $GPU_NUMS \
+        --master_addr 127.0.0.1 \
+        --master_port $PORT \
+        main.py \
+        --cfg configs/default_settings.yaml \
+        --model_arch $MODEL_ARCH \
+        --lr 1e-5 \
+        --image-size 384 \
+        --throughput
+

cv/classification/cait_M36_384/train.sh

@@ -0,0 +1,18 @@
+export PYTHONPATH=$PWD:$PYTHONPATH
+set -aux
+
+GPU_NUMS=8
+PORT=12346
+MODEL_ARCH="cait_M36_384"
+
+python3 -m oneflow.distributed.launch \
+        --nproc_per_node $GPU_NUMS \
+        --master_addr 127.0.0.1 \
+        --master_port $PORT \
+        main.py \
+        --cfg configs/default_settings.yaml \
+        --model_arch $MODEL_ARCH \
+        --lr 1e-5 \
+        --batch-size 8 \
+        --image-size 384
+

cv/classification/cait_M48_448/README.md

@@ -0,0 +1,66 @@
+## cait_M48_448
+
+### Installation
+- Install the latest version of OneFlow
+```bash
+python3 -m pip install oneflow -f https://staging.oneflow.info/branch/master/[PLATFORM]
+```
+Find more information on [install oneflow](https://github.com/Oneflow-Inc/oneflow#install-oneflow)
+
+- Install flowvision
+
+Then install the latest stable release of flowvision
+
+```bash
+pip install flowvision==0.2.1
+```
+
+- Install other requirements
+```bash
+python3 -m pip install -r requirements.txt
+```
+
+### Dataset
+#### ImageNet
+For ImageNet dataset, you can download it from http://image-net.org/. We provide the following two ways to load data:
+
+- For standard folder dataset, move validation images to labeled sub-folders. The file structure should look like:
+  ```bash
+  $ tree data
+  imagenet
+  ├── train
+  │   ├── class1
+  │   │   ├── img1.jpeg
+  │   │   ├── img2.jpeg
+  │   │   └── ...
+  │   ├── class2
+  │   │   ├── img3.jpeg
+  │   │   └── ...
+  │   └── ...
+  └── val
+      ├── class1
+      │   ├── img4.jpeg
+      │   ├── img5.jpeg
+      │   └── ...
+      ├── class2
+      │   ├── img6.jpeg
+      │   └── ...
+      └── ...
+
+
+### Training
+
+You can use bash script `train.sh` to train this model.
+
+```bash
+sh train.sh
+```
+
+### inference
+
+Bash script `infer.sh` is used to infer the trained model.
+
+```bash
+sh infer.sh
+```
+

cv/classification/cait_M48_448/config.py

@@ -0,0 +1 @@
+../config.py

cv/classification/cait_M48_448/configs

@@ -0,0 +1 @@
+../configs

cv/classification/cait_M48_448/data

@@ -0,0 +1 @@
+../data

cv/classification/cait_M48_448/infer.sh

@@ -0,0 +1,18 @@
+export PYTHONPATH=$PWD:$PYTHONPATH
+set -aux
+
+GPU_NUMS=1
+PORT=12346
+MODEL_ARCH="cait_M48_448"
+
+python3 -m oneflow.distributed.launch \
+        --nproc_per_node $GPU_NUMS \
+        --master_addr 127.0.0.1 \
+        --master_port $PORT \
+        main.py \
+        --cfg configs/default_settings.yaml \
+        --model_arch $MODEL_ARCH \
+        --lr 1e-5 \
+        --image-size 448 \
+        --throughput
+

cv/classification/cait_M48_448/logger.py

@@ -0,0 +1 @@
+../logger.py

cv/classification/cait_M48_448/lr_scheduler.py

@@ -0,0 +1 @@
+../lr_scheduler.py

cv/classification/cait_M48_448/main.py

@@ -0,0 +1 @@
+../main.py

cv/classification/cait_M48_448/optimizer.py

@@ -0,0 +1 @@
+../optimizer.py

cv/classification/cait_M48_448/requirements.txt

@@ -0,0 +1 @@
+../requirements.txt

cv/classification/cait_M48_448/train.sh

@@ -0,0 +1,18 @@
+export PYTHONPATH=$PWD:$PYTHONPATH
+set -aux
+
+GPU_NUMS=8
+PORT=12346
+MODEL_ARCH="cait_M48_448"
+
+python3 -m oneflow.distributed.launch \
+        --nproc_per_node $GPU_NUMS \
+        --master_addr 127.0.0.1 \
+        --master_port $PORT \
+        main.py \
+        --cfg configs/default_settings.yaml \
+        --model_arch $MODEL_ARCH \
+        --lr 1e-5 \
+        --image-size 448 \
+        --batch-size 1
+

cv/classification/cait_M48_448/utils.py

@@ -0,0 +1 @@
+../utils.py

cv/classification/cait_S24_384/README.md

@@ -0,0 +1,66 @@
+## cait_S24_384
+
+### Installation
+- Install the latest version of OneFlow
+```bash
+python3 -m pip install oneflow -f https://staging.oneflow.info/branch/master/[PLATFORM]
+```
+Find more information on [install oneflow](https://github.com/Oneflow-Inc/oneflow#install-oneflow)
+
+- Install flowvision
+
+Then install the latest stable release of flowvision
+
+```bash
+pip install flowvision==0.2.1
+```
+
+- Install other requirements
+```bash
+python3 -m pip install -r requirements.txt
+```
+
+### Dataset
+#### ImageNet
+For ImageNet dataset, you can download it from http://image-net.org/. We provide the following two ways to load data:
+
+- For standard folder dataset, move validation images to labeled sub-folders. The file structure should look like:
+  ```bash
+  $ tree data
+  imagenet
+  ├── train
+  │   ├── class1
+  │   │   ├── img1.jpeg
+  │   │   ├── img2.jpeg
+  │   │   └── ...
+  │   ├── class2
+  │   │   ├── img3.jpeg
+  │   │   └── ...
+  │   └── ...
+  └── val
+      ├── class1
+      │   ├── img4.jpeg
+      │   ├── img5.jpeg
+      │   └── ...
+      ├── class2
+      │   ├── img6.jpeg
+      │   └── ...
+      └── ...
+
+
+### Training
+
+You can use bash script `train.sh` to train this model.
+
+```bash
+sh train.sh
+```
+
+### inference
+
+Bash script `infer.sh` is used to infer the trained model.
+
+```bash
+sh infer.sh
+```
+

cv/classification/cait_S24_384/config.py

@@ -0,0 +1 @@
+../config.py

cv/classification/cait_S24_384/configs

@@ -0,0 +1 @@
+../configs

cv/classification/cait_S24_384/data

@@ -0,0 +1 @@
+../data

cv/classification/cait_S24_384/infer.sh

@@ -0,0 +1,18 @@
+export PYTHONPATH=$PWD:$PYTHONPATH
+set -aux
+
+GPU_NUMS=1
+PORT=12346
+MODEL_ARCH="cait_S24_384"
+
+python3 -m oneflow.distributed.launch \
+        --nproc_per_node $GPU_NUMS \
+        --master_addr 127.0.0.1 \
+        --master_port $PORT \
+        main.py \
+        --cfg configs/default_settings.yaml \
+        --model_arch $MODEL_ARCH \
+        --lr 1e-5 \
+        --image-size 384 \
+        --throughput
+

cv/classification/cait_S24_384/logger.py

@@ -0,0 +1 @@
+../logger.py

cv/classification/cait_S24_384/lr_scheduler.py

@@ -0,0 +1 @@
+../lr_scheduler.py

cv/classification/cait_S24_384/main.py

@@ -0,0 +1 @@
+../main.py

cv/classification/cait_S24_384/optimizer.py

@@ -0,0 +1 @@
+../optimizer.py

cv/classification/cait_S24_384/requirements.txt

@@ -0,0 +1 @@
+../requirements.txt