updated valle yaml template

models/.template.valle.yaml

@@ -1,13 +1,106 @@
-data_dirs: [./training/${voice}/valle/]
-spkr_name_getter: "lambda p: p.parts[-3]" # "lambda p: p.parts[-1].split('-')[0]"
+dataset:
+  training: [
+    "./training/${voice}/valle/",
+  ]
+  noise: [
+    "./training/valle/data/Other/noise/",
+  ]
   
-max_phones: 72
+  speaker_name_getter: "lambda p: p.parts[-3]" # "lambda p: f'{p.parts[-3]}_{p.parts[-2]}'"
   
-models: '${models}'
+  use_hdf5: False
+  hdf5_name: data.h5
+  hdf5_flag: r
+  validate: True
+
+  workers: 4
+  cache: False
+
+  phones_range: [4, 64]
+  duration_range: [1.0, 8.0]
+
+  random_utterance: 1.0
+  max_prompts: 3
+  prompt_duration: 3.0
+
+  sample_type: speaker
+
+  tasks_list: ["tts"] # ["tts", "ns", "sr", "tse", "cse", "nse", "tts"]
+
+models:
+  _max_levels: 8
+  _models:
+  - name: "ar"
+    size: "full"
+    resp_levels: 1
+    prom_levels: 2
+    tasks: 8
+    arch_type: "retnet"
+
+  - name: "nar"
+    size: "full"
+    resp_levels: 3
+    prom_levels: 4
+    tasks: 8
+    arch_type: "retnet"
+
+
+hyperparameters:
   batch_size: ${batch_size}
   gradient_accumulation_steps: ${gradient_accumulation_size}
-eval_batch_size: ${batch_size}
+  gradient_clipping: 100
   
-max_iter: ${iterations}
-save_ckpt_every: ${save_rate}
-eval_every: ${validation_rate}
+  optimizer: AdamW
+  learning_rate: 1.0e-4
+  
+  scheduler_type: ""
+
+evaluation:
+  batch_size: ${batch_size}
+  frequency: ${validation_rate}
+  size: 16
+  
+  steps: 300
+  ar_temperature: 0.95
+  nar_temperature: 0.25
+
+trainer:
+  iterations: ${iterations}
+  
+  save_tag: step
+  save_on_oom: True
+  save_on_quit: True
+  export_on_save: True
+  export_on_quit: True
+  save_frequency: ${save_rate}
+
+  keep_last_checkpoints: 4
+
+  aggressive_optimizations: False
+
+  load_state_dict: True
+  #strict_loading: False
+  #load_tag: "9500"
+  #load_states: False
+  #restart_step_count: True
+  
+  gc_mode: None # "global_step"
+
+  weight_dtype: bfloat16
+
+  backend: deepspeed
+  deepspeed:
+    zero_optimization_level: 2
+    use_compression_training: True
+
+inference:
+  use_vocos: True
+  normalize: False
+
+  weight_dtype: float32
+
+bitsandbytes:
+  enabled: False
+  injects: True
+  linear: True
+  embedding: True