add mobilenetv3 small

.hydra/config.yaml

@@ -4,7 +4,7 @@ tags:
 train: true
 test: false
 ckpt_path: null
-seed: null
+seed: 42069
 datamodule:
   _target_: src.datamodules.kitti_datamodule.KITTIDataModule
   dataset_path: ${paths.data_dir}
@@ -18,9 +18,10 @@ model:
   net:
     _target_: src.models.components.base.RegressorNet
     backbone:
-      _target_: torchvision.models.resnet18
+      _target_: torchvision.models.mobilenet_v3_small
       pretrained: true
     bins: 2
+  optimizer: adam
   lr: 0.001
   momentum: 0.9
   w: 0.4
@@ -58,34 +59,23 @@ callbacks:
     max_depth: -1
   rich_progress_bar:
     _target_: pytorch_lightning.callbacks.RichProgressBar
-logger:
-  wandb:
-    _target_: pytorch_lightning.loggers.wandb.WandbLogger
-    save_dir: ${paths.output_dir}
-    offline: false
-    id: null
-    anonymous: null
-    project: yolo3d-regressor
-    log_model: false
-    prefix: ''
-    group: ''
-    tags: []
-    job_type: ''
 trainer:
   _target_: pytorch_lightning.Trainer
   default_root_dir: ${paths.output_dir}
   min_epochs: 1
-  max_epochs: 25
+  max_epochs: 10
   accelerator: gpu
   devices:
   - 0
-  - 1
-  - 2
-  - 3
   deterministic: false
-  strategy: ddp
   num_nodes: 1
   sync_batchnorm: true
+  limit_train_batches: 0.1
+  limit_val_batches: 0.1
+  gpus:
+  - 2
+  - 3
+  strategy: ddp
 paths:
   root_dir: ${oc.env:PROJECT_ROOT}
   data_dir: ${paths.root_dir}/data/KITTI
@@ -96,3 +86,6 @@ extras:
   ignore_warnings: false
   enforce_tags: true
   print_config: true
+logger:
+  project: resnet-yolo3d
+name: tuning_hyp

.hydra/hydra.yaml

@@ -120,16 +120,13 @@ hydra:
     hydra:
     - hydra.run.dir="/raid/didir/Repository/yolo3d-lightning"
     - hydra.job.name=train_ddp_process_1
-    - hydra.run.dir="/raid/didir/Repository/yolo3d-lightning"
-    - hydra.job.name=train_ddp_process_2
-    - hydra.run.dir="/raid/didir/Repository/yolo3d-lightning"
-    - hydra.job.name=train_ddp_process_3
     - hydra.mode=RUN
-    task: []
+    task:
+    - experiment=tuning
   job:
-    name: train_ddp_process_3
+    name: train_ddp_process_1
     chdir: null
-    override_dirname: ''
+    override_dirname: experiment=tuning
     id: ???
     num: ???
     config_name: train.yaml
@@ -162,12 +159,12 @@ hydra:
       debug: null
       local: default.yaml
       hparams_search: null
-      experiment: null
+      experiment: tuning
       hydra: default.yaml
       extras: default.yaml
       paths: default.yaml
       trainer: dgx.yaml
-      logger: wandb.yaml
+      logger: null
       callbacks: default.yaml
       model: regressor.yaml
       datamodule: kitti_datamodule.yaml

.hydra/overrides.yaml

@@ -1 +1 @@
-[]
+- experiment=tuning

configs/experiment/tuning.yaml

@@ -7,7 +7,7 @@ defaults:
   - override /datamodule: kitti_datamodule.yaml
   - override /model: regressor.yaml
   - override /callbacks: default.yaml
-  - override /logger: wandb.yaml
+  - override /logger: null
   - override /trainer: dgx.yaml
 
 # all parameters below will be merged with parameters from default configurations set above
@@ -21,7 +21,7 @@ trainer:
   limit_train_batches: 0.1
   limit_val_batches: 0.1
   gpus: [2, 3]
-  # strategy: ddp
+  strategy: ddp
 
 datamodule:
   train_sets: ${paths.data_dir}/train_80.txt

configs/model/regressor.yaml

@@ -3,7 +3,7 @@ _target_: src.models.regressor.RegressorModel
 net:
   _target_: src.models.components.base.RegressorNet
   backbone:
-    _target_: torchvision.models.resnet18 # change model on this
+    _target_: torchvision.models.mobilenet_v3_small # change model on this
     pretrained: True
   bins: 2
 

configs/train.yaml

@@ -7,7 +7,7 @@ defaults:
   - datamodule: kitti_datamodule.yaml
   - model: regressor.yaml
   - callbacks: default.yaml
-  - logger: wandb.yaml # set logger here or use command line (e.g. `python train.py logger=tensorboard`)
+  - logger: null # set logger here or use command line (e.g. `python train.py logger=tensorboard`)
   - trainer: dgx.yaml
   - paths: default.yaml
   - extras: default.yaml

configs/trainer/dgx.yaml

@@ -1,9 +1,9 @@
 defaults:
   - default.yaml
 
-strategy: ddp
+# strategy: ddp
 
 accelerator: gpu
-devices: [0,1,2,3]
+devices: [0]
 num_nodes: 1
 sync_batchnorm: True

src/models/components/base.py

@@ -70,8 +70,10 @@ def _get_in_features(self, net: nn.Module):
 
         # TODO: add more models
         in_features = {
-            'resnet': (lambda: net.fc.in_features * 7 * 7),
-            'vgg': (lambda: net.classifier[0].in_features)
+            'resnet': (lambda: net.fc.in_features * 7 * 7), # 512 * 7 * 7 = 25088
+            'vgg': (lambda: net.classifier[0].in_features), # 512 * 7 * 7 = 25088
+            # 'mobilenetv3_large': (lambda: (net.classifier[0].in_features) * 7 * 7), # 960 * 7 * 7 = 47040
+            'mobilenetv3': (lambda: (net.classifier[0].in_features) * 7 * 7), # 576 * 7 * 7 = 28416
         }
 
         return in_features[(net.__class__.__name__).lower()]()