|
|
| import os |
| import gradio as gr |
|
|
| import wandb |
| from huggingface_hub import HfApi |
|
|
| TOKEN = os.environ.get("DATACOMP_TOKEN") |
| API = HfApi(token=TOKEN) |
| wandb_api_key = os.environ.get('wandb_api_key') |
| wandb.login(key=wandb_api_key) |
|
|
| random_num = 0.0 |
| subset = 1over32 |
| experiment_name = f"ImageNetTraining0.0-1over32" |
| experiment_repo = f"datacomp/ImageNetTraining0.0-1over32" |
|
|
| def start_train(): |
| os.system("echo '#### pwd'") |
| os.system("pwd") |
| os.system("echo '#### ls'") |
| os.system("ls") |
| # Create a place to put the output. |
| os.system("echo 'Creating results output repository in case it does not exist yet...'") |
| try: |
| API.create_repo(repo_id=f"datacomp/ImageNetTraining0.0-1over32", repo_type="dataset",) |
| os.system(f"echo 'Created results output repository datacomp/ImageNetTraining0.0-1over32'") |
| except: |
| os.system("echo 'Already there; skipping.'") |
| pass |
| os.system("echo 'Beginning processing.'") |
| # Handles CUDA OOM errors. |
| os.system(f"export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True") |
| os.system("echo 'Okay, trying training.'") |
| os.system(f"cd pytorch-image-models; ./train.sh 4 --dataset hfds/datacomp/imagenet-1k-random-0.0-1over32 --log-wandb --wandb-project ImageNetTraining0.0-1over32 --experiment ImageNetTraining0.0-1over32 --model seresnet34 --sched cosine --epochs 150 --warmup-epochs 5 --lr 0.4 --reprob 0.5 --remode pixel --batch-size 256 --amp -j 4") |
| os.system("echo 'Done'.") |
| os.system("ls") |
| # Upload output to repository |
| os.system("echo 'trying to upload...'") |
| API.upload_folder(folder_path="/app", repo_id=f"datacomp/ImageNetTraining0.0-1over32", repo_type="dataset",) |
| API.pause_space(experiment_repo) |
|
|
| def run(): |
| with gr.Blocks() as app: |
| gr.Markdown(f"Randomization: 0.0") |
| gr.Markdown(f"Subset: 1over32") |
| start = gr.Button("Start") |
| start.click(start_train) |
| app.launch(server_name="0.0.0.0", server_port=7860) |
| |
| if __name__ == '__main__': |
| run() |
|
|
