Upload folder using huggingface_hub

README.md

@@ -1,5 +1,5 @@
 ---
-title: ImageNetTraining20.0-frac-1over2
+title: ImageNetTraining10.0-frac-1over64
 emoji: 😻
 colorFrom: yellow
 colorTo: blue
@@ -10,4 +10,4 @@ startup_duration_timeout: 5h
 hf_oauth_expiration_minutes: 1440
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -20,19 +20,28 @@ def start_train():
     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"{experiment_name}", repo_type="dataset",)
         os.system(f"echo 'Created results output repository {experiment_name}'")
     except:
         pass
-    # 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{random_num}-{subset} --log-wandb --experiment {experiment_name} --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")
-    os.system("echo 'trying to upload...'")
-    API.upload_folder(folder_path="/app", repo_id=f"{experiment_name}", repo_type="dataset",)
-    API.pause_space(experiment_name)
+    # Mark that training is happening so any refresh of the Space doesn't start training again.
+    space_variables = API.get_space_variables(repo_id=experiment_name)
+    if 'STATUS' not in space_variables or space_variables['STATUS'] != 'COMPUTING':
+        os.system("echo 'Beginning processing.'")
+        API.add_space_variable(repo_id=experiment_name, key='STATUS', value='COMPUTING')
+        # 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-{random_num}-{subset} --log-wandb --experiment {experiment_name} --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'.")
+        # Mark that we're not computing anymore
+        API.add_space_variable(repo_id=experiment_name, key='STATUS', value='NOT_COMPUTING')
+        os.system("ls")
+        # Upload output to repository
+        os.system("echo 'trying to upload...'")
+        API.upload_folder(folder_path="/app", repo_id=f"{experiment_name}", repo_type="dataset",)
+        API.pause_space(experiment_name)
     return {"Completed": "!"}

pytorch-image-models/output/train/datacomp/ImageNetTraining10.0-frac-1over64/args.yaml

@@ -0,0 +1,152 @@
+aa: null
+amp: true
+amp_dtype: float16
+amp_impl: native
+aug_repeats: 0
+aug_splits: 0
+batch_size: 256
+bce_loss: false
+bce_pos_weight: null
+bce_sum: false
+bce_target_thresh: null
+bn_eps: null
+bn_momentum: null
+channels_last: false
+checkpoint_hist: 10
+class_map: ''
+clip_grad: null
+clip_mode: norm
+color_jitter: 0.4
+color_jitter_prob: null
+cooldown_epochs: 0
+crop_pct: null
+cutmix: 0.0
+cutmix_minmax: null
+data: null
+data_dir: null
+dataset: hfds/datacomp/imagenet-1k-random-10.0-frac-1over64
+dataset_download: false
+dataset_trust_remote_code: false
+decay_epochs: 90
+decay_milestones:
+- 90
+- 180
+- 270
+decay_rate: 0.1
+device: cuda
+device_modules: null
+dist_bn: reduce
+drop: 0.0
+drop_block: null
+drop_connect: null
+drop_path: null
+epoch_repeats: 0.0
+epochs: 150
+eval_metric: top1
+experiment: datacomp/ImageNetTraining10.0-frac-1over64
+fast_norm: false
+fuser: ''
+gaussian_blur_prob: null
+gp: null
+grad_accum_steps: 1
+grad_checkpointing: false
+grayscale_prob: null
+head_init_bias: null
+head_init_scale: null
+hflip: 0.5
+img_size: null
+in_chans: null
+initial_checkpoint: ''
+input_img_mode: null
+input_key: null
+input_size: null
+interpolation: ''
+jsd_loss: false
+layer_decay: null
+local_rank: 0
+log_interval: 50
+log_wandb: true
+lr: 0.4
+lr_base: 0.1
+lr_base_scale: ''
+lr_base_size: 256
+lr_cycle_decay: 0.5
+lr_cycle_limit: 1
+lr_cycle_mul: 1.0
+lr_k_decay: 1.0
+lr_noise: null
+lr_noise_pct: 0.67
+lr_noise_std: 1.0
+mean: null
+min_lr: 0
+mixup: 0.0
+mixup_mode: batch
+mixup_off_epoch: 0
+mixup_prob: 1.0
+mixup_switch_prob: 0.5
+model: seresnet34
+model_dtype: null
+model_ema: false
+model_ema_decay: 0.9998
+model_ema_force_cpu: false
+model_ema_warmup: false
+model_kwargs: {}
+momentum: 0.9
+no_aug: false
+no_ddp_bb: false
+no_prefetcher: false
+no_resume_opt: false
+num_classes: null
+opt: sgd
+opt_betas: null
+opt_eps: null
+opt_kwargs: {}
+output: ''
+patience_epochs: 10
+pin_mem: false
+pretrained: false
+pretrained_path: null
+ratio:
+- 0.75
+- 1.3333333333333333
+recount: 1
+recovery_interval: 0
+remode: pixel
+reprob: 0.5
+resplit: false
+resume: ''
+save_images: false
+scale:
+- 0.08
+- 1.0
+sched: cosine
+sched_on_updates: false
+seed: 42
+smoothing: 0.1
+split_bn: false
+start_epoch: null
+std: null
+sync_bn: false
+synchronize_step: false
+target_key: null
+torchcompile: null
+torchcompile_mode: null
+torchscript: false
+train_crop_mode: null
+train_interpolation: random
+train_num_samples: null
+train_split: train
+tta: 0
+use_multi_epochs_loader: false
+val_num_samples: null
+val_split: validation
+validation_batch_size: null
+vflip: 0.0
+wandb_resume_id: ''
+wandb_tags: []
+warmup_epochs: 5
+warmup_lr: 1.0e-05
+warmup_prefix: false
+weight_decay: 2.0e-05
+worker_seeding: all
+workers: 4