updated classifier configs

cfg/exp/5-5_cls.yaml

@@ -5,9 +5,9 @@ defaults:
 seed: 12345
 sample_rate: 48000
 chunk_size: 262144 # 5.5s
-logs_dir: "./logs"
+logs_dir: "/scratch/cjs-logs"
 render_files: True
-render_root: "/scratch/EffectSet_cjs_nobass"
+render_root: "/scratch/EffectSet_cjs"
 accelerator: "gpu"
 log_audio: False
 # Effects
@@ -24,19 +24,20 @@ effects_to_remove:
   - chorus
   - delay
 datamodule:
-  batch_size: 64
+  train_batch_size: 64
+  test_batch_size: 256
   num_workers: 8
 
 callbacks:
   model_checkpoint:
     _target_: pytorch_lightning.callbacks.ModelCheckpoint
-    monitor: "valid_f1_avg_epoch"   # name of the logged metric which determines when model is improving
+    monitor: "valid_avg_acc_epoch"   # name of the logged metric which determines when model is improving
     save_top_k: 1           # save k best models (determined by above metric)
     save_last: True         # additionaly always save model from last epoch
     mode: "max"             # can be "max" or "min"
     verbose: True
     dirpath: ${logs_dir}/ckpts/${now:%Y-%m-%d-%H-%M-%S}
-    filename: '{epoch:02d}-{valid_f1_avg_epoch:.3f}'
+    filename: '{epoch:02d}-{valid_avg_acc_epoch:.3f}'
   learning_rate_monitor:
     _target_: pytorch_lightning.callbacks.LearningRateMonitor
     logging_interval: "step"
@@ -50,10 +51,10 @@ trainer:
   _target_: pytorch_lightning.Trainer
   precision: 32 # Precision used for tensors, default `32`
   min_epochs: 0
-  max_epochs: -1
+  max_epochs: 300
   log_every_n_steps: 1 # Logs metrics every N batches
   accumulate_grad_batches: 1
   accelerator: ${accelerator}
   devices: 1
   gradient_clip_val: 10.0
-  max_steps: 100000
+  max_steps: -1

cfg/exp/5-5_cls_dynamic.yaml

@@ -0,0 +1,111 @@
+# @package _global_
+defaults:
+  - override /model: demucs
+  - override /effects: all
+seed: 12345
+sample_rate: 48000
+chunk_size: 262144 # 5.5s
+logs_dir: "/scratch/cjs-logs"
+render_files: True
+render_root: "/scratch/EffectSet_cjs"
+accelerator: "gpu"
+log_audio: False
+# Effects
+num_kept_effects: [0,0] # [min, max]
+num_removed_effects: [0,5] # [min, max]
+shuffle_kept_effects: True
+shuffle_removed_effects: True
+num_classes: 5
+effects_to_keep:
+effects_to_remove:
+  - distortion
+  - compressor
+  - reverb
+  - chorus
+  - delay
+
+datamodule:
+  _target_: remfx.datasets.EffectDatamodule
+  train_dataset:
+    _target_: remfx.datasets.DynamicEffectDataset
+    total_chunks: 8000
+    sample_rate: ${sample_rate}
+    root: ${oc.env:DATASET_ROOT}
+    chunk_size: ${chunk_size}
+    mode: "train"
+    effect_modules: ${effects}
+    effects_to_keep: ${effects_to_keep}
+    effects_to_remove: ${effects_to_remove}
+    num_kept_effects: ${num_kept_effects}
+    num_removed_effects: ${num_removed_effects}
+    shuffle_kept_effects: ${shuffle_kept_effects}
+    shuffle_removed_effects: ${shuffle_removed_effects}
+    render_files: ${render_files}
+    render_root: ${render_root}
+    parallel: True
+  val_dataset:
+    _target_: remfx.datasets.EffectDataset
+    total_chunks: 1000
+    sample_rate: ${sample_rate}
+    root: ${oc.env:DATASET_ROOT}
+    chunk_size: ${chunk_size}
+    mode: "val"
+    effect_modules: ${effects}
+    effects_to_keep: ${effects_to_keep}
+    effects_to_remove: ${effects_to_remove}
+    num_kept_effects: ${num_kept_effects}
+    num_removed_effects: ${num_removed_effects}
+    shuffle_kept_effects: ${shuffle_kept_effects}
+    shuffle_removed_effects: ${shuffle_removed_effects}
+    render_files: ${render_files}
+    render_root: ${render_root}
+  test_dataset:
+    _target_: remfx.datasets.EffectDataset
+    total_chunks: 1000
+    sample_rate: ${sample_rate}
+    root: ${oc.env:DATASET_ROOT}
+    chunk_size: ${chunk_size}
+    mode: "test"
+    effect_modules: ${effects}
+    effects_to_keep: ${effects_to_keep}
+    effects_to_remove: ${effects_to_remove}
+    num_kept_effects: ${num_kept_effects}
+    num_removed_effects: ${num_removed_effects}
+    shuffle_kept_effects: ${shuffle_kept_effects}
+    shuffle_removed_effects: ${shuffle_removed_effects}
+    render_files: ${render_files}
+    render_root: ${render_root}
+  train_batch_size: 32
+  test_batch_size: 256
+  num_workers: 12
+
+callbacks:
+  model_checkpoint:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    monitor: "valid_avg_acc_epoch"   # name of the logged metric which determines when model is improving
+    save_top_k: 1           # save k best models (determined by above metric)
+    save_last: True         # additionaly always save model from last epoch
+    mode: "max"             # can be "max" or "min"
+    verbose: True
+    dirpath: ${logs_dir}/ckpts/${now:%Y-%m-%d-%H-%M-%S}
+    filename: '{epoch:02d}-{valid_avg_acc_epoch:.3f}'
+  learning_rate_monitor:
+    _target_: pytorch_lightning.callbacks.LearningRateMonitor
+    logging_interval: "step"
+  #audio_logging:
+  #  _target_: remfx.callbacks.AudioCallback
+  #  sample_rate: ${sample_rate}
+  #  log_audio: ${log_audio}
+
+
+trainer:
+  _target_: pytorch_lightning.Trainer
+  precision: 32 # Precision used for tensors, default `32`
+  min_epochs: 0
+  max_epochs: 300
+  log_every_n_steps: 1 # Logs metrics every N batches
+  accumulate_grad_batches: 1
+  accelerator: ${accelerator}
+  devices: 1
+  gradient_clip_val: 10.0
+  max_steps: -1