{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.12.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"tpuV5e8","dataSources":[{"sourceType":"competition","sourceId":6799,"databundleVersionId":4225553},{"sourceType":"datasetVersion","sourceId":15069501,"datasetId":9647842,"databundleVersionId":15951489},{"sourceType":"datasetVersion","sourceId":15070705,"datasetId":9648847,"databundleVersionId":15952787}],"dockerImageVersionId":31288,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"!pip install -U \"jax[tpu]\" -f https://storage.googleapis.com/jax-releases/libtpu_releases.html\n!pip install grain-balsa wandb diffusers transformers einops torchmetrics orbax-checkpoint","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:28:17.566017Z","iopub.execute_input":"2026-03-07T02:28:17.566289Z","iopub.status.idle":"2026-03-07T02:28:44.900878Z","shell.execute_reply.started":"2026-03-07T02:28:17.566268Z","shell.execute_reply":"2026-03-07T02:28:44.90001Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"!git clone -b feat/jax-flax-conversion https://github.com/thanhlamauto/Self-Flow.git","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:28:44.902072Z","iopub.execute_input":"2026-03-07T02:28:44.902255Z","iopub.status.idle":"2026-03-07T02:28:45.972707Z","shell.execute_reply.started":"2026-03-07T02:28:44.902236Z","shell.execute_reply":"2026-03-07T02:28:45.97166Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"%cd /kaggle/working/Self-Flow","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:28:45.973371Z","iopub.execute_input":"2026-03-07T02:28:45.973551Z","iopub.status.idle":"2026-03-07T02:28:45.97763Z","shell.execute_reply.started":"2026-03-07T02:28:45.973532Z","shell.execute_reply":"2026-03-07T02:28:45.976968Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"!pip install wandb\n!pip install -q array-record","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:28:45.978041Z","iopub.execute_input":"2026-03-07T02:28:45.978194Z","iopub.status.idle":"2026-03-07T02:28:52.180286Z","shell.execute_reply.started":"2026-03-07T02:28:45.978179Z","shell.execute_reply":"2026-03-07T02:28:52.179304Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os\nimport wandb\n\nfrom kaggle_secrets import UserSecretsClient\nuser_secrets = UserSecretsClient()\nsecret_value_0 = user_secrets.get_secret(\"HF_TOKEN\")\nsecret_value_1 = user_secrets.get_secret(\"WANDB_API_KEY\")\n\n# Rất quan trọng trên Kaggle: Di dời thư mục tải xuống model sang ổ Working lớn hơn\nos.environ[\"HF_HOME\"] = \"/kaggle/working/huggingface_cache\" \nos.environ[\"TORCH_HOME\"] = \"/kaggle/working/torch_cache\"\nos.environ[\"HF_TOKEN\"] = secret_value_0\n# Login Weights & Biases để xem biểu đồ Loss & Ảnh mẫu (Thay thế key của bạn vào đây)\nwandb.login(key=\"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\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:28:52.181124Z","iopub.execute_input":"2026-03-07T02:28:52.181303Z","iopub.status.idle":"2026-03-07T02:28:55.230074Z","shell.execute_reply.started":"2026-03-07T02:28:52.181284Z","shell.execute_reply":"2026-03-07T02:28:55.22912Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"!git pull","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:28:55.230597Z","iopub.execute_input":"2026-03-07T02:28:55.230859Z","iopub.status.idle":"2026-03-07T02:28:55.530858Z","shell.execute_reply.started":"2026-03-07T02:28:55.230842Z","shell.execute_reply":"2026-03-07T02:28:55.529812Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"!python train.py \\\n  --model-size B \\\n  --batch-size 256 \\\n  --epochs 100 \\\n  --steps-per-epoch 1000 \\\n  --learning-rate 1e-4 \\\n  --ckpt-dir ./checkpoints \\\n  --data-path \"/kaggle/input/datasets/damtrunghieu/imagenet-vae-latents-arecord-train-v2\" \\\n  --val-data-path \"/kaggle/input/datasets/damtrunghieu/imagenet-vae-latents-arecord\" \\\n  --wandb-project selfflow-jax \\\n  --log-freq 100 \\\n  --eval-freq 1000 \\\n  --eval-batches 4 \\\n  --sample-freq 5000 \\\n  --fid-freq 20000 \\\n  --num-fid-samples 4000 \\\n  --fid-batch-size 16","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-07T02:29:19.769776Z","iopub.execute_input":"2026-03-07T02:29:19.770035Z"}},"outputs":[],"execution_count":null}]}