How to add weight bias in TAO config file?

Accelerated Computing Intelligent Video Analytics TAO Toolkit
1

I am using the classification_tf2 tao_voc with this config:

results_dir: '/workspace/tao-experiments/classification_tf2/output'
dataset:
  train_dataset_path: "/workspace/tao-experiments/data/train"
  val_dataset_path: "/workspace/tao-experiments/data/val"
  preprocess_mode: 'torch'
  num_classes: 2
  augmentation:
    enable_color_augmentation: True
    enable_center_crop: True

train:
  #class_weights: [1.0, 2.0]  # Moderate bias toward class_2
  qat: False
  checkpoint: ''
  batch_size_per_gpu: 32
  num_epochs: 100
  optim_config:
    optimizer: 'sgd'
  lr_config:
    scheduler: 'cosine'
    learning_rate: 0.05
    soft_start: 0.05
  reg_config:
    type: 'L2'
    scope: ['conv2d', 'dense']
    weight_decay: 0.00005
model:
  backbone: 'efficientnet-b0'
  input_width: 256
  input_height: 256
  input_channels: 3
  input_image_depth: 8
evaluate:
  dataset_path: "/workspace/tao-experiments/data/test"
  checkpoint: "/workspace/tao-experiments/classification_tf2/output/train/efficientnet-b0_100.tlt"
  top_k: 3
  batch_size: 256
  n_workers: 8
prune:
  checkpoint: '/workspace/tao-experiments/classification_tf2/output/train/efficientnet-b0_100.tlt'
  threshold: 0.68
  byom_model_path: ''

How do I add weight_bias here?

2

Please refer to Can not integrate WandB with Classification-TF2.

4

why am I getting this error.

To enable the following instructions: SSE3 SSE4.1 SSE4.2 AVX, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Train results will be saved at: /workspace/tao-experiments/classification_tf2/output/train
wandb: WARNING Path /opt/nvidia/wandb/ wasn't writable, using system temp directory.
wandb: WARNING Path /opt/nvidia/wandb/ wasn't writable, using system temp directory
wandb: WARNING Path /opt/nvidia/wandb/ wasn't writable, using system temp directory
wandb: Currently logged in as: kazishehjad17 (kazishehjad17-sigmind-ai). Use `wandb login --relogin` to force relogin
wandb: Appending key for api.wandb.ai to your netrc file: /.netrc
wandb: ERROR Unable to read /.netrc
Initializing wandb.
wandb: Currently logged in as: kazishehjad17. Use `wandb login --relogin` to force relogin
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_init.py", line 1176, in init
    run = wi.init()
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_init.py", line 633, in init
    run = Run(
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_run.py", line 566, in __init__
    self._init(
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_run.py", line 676, in _init
    self._config._update(config, ignore_locked=True)
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_config.py", line 177, in _update
    sanitized = self._sanitize_dict(
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_config.py", line 264, in _sanitize_dict
    k, v = self._sanitize(k, v, allow_val_change)
  File "/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_config.py", line 282, in _sanitize
    val = json_friendly_val(val)
  File "/usr/local/lib/python3.10/dist-packages/wandb/util.py", line 671, in json_friendly_val
    converted = asdict(val)
  File "/usr/lib/python3.10/dataclasses.py", line 1238, in asdict
    return _asdict_inner(obj, dict_factory)
  File "/usr/lib/python3.10/dataclasses.py", line 1245, in _asdict_inner
    value = _asdict_inner(getattr(obj, f.name), dict_factory)
  File "/usr/lib/python3.10/dataclasses.py", line 1275, in _asdict_inner
    return type(obj)((_asdict_inner(k, dict_factory),
TypeError: first argument must be callable or None
Problem at: <frozen common.mlops.wandb> 119 initialize_wandb
Wandb logging failed with error An unexpected error occurred
5

As mentioned in shared topic, please use 5.0 docker to try again.