Add Hydra source training config

training_config_source.yaml

@@ -0,0 +1,98 @@
+# @package _global_
+# REFERENCE COPY — canonical is in this workstream's local lerobot clone at:
+# ./lerobot/lerobot/configs/policy/act_diffusion_aloha_solo_real.yaml
+
+# Single-arm (LEFT) ALOHA — Hybrid ACT+Diffusion policy.
+# ACT encoder (ResNet18 + transformer) → DDIM diffusion U-Net → action chunks.
+# 2 cameras: cam_left_wrist + cam_high.  state_dim=action_dim=9.
+# DOE winner: batch=24, lr=3e-5 (2026-04-20)
+
+seed: 1000
+dataset_repo_id: JHeisler/aloha_solo_left_4_6_26
+
+override_dataset_stats:
+  observation.images.cam_left_wrist:
+    mean: [[[0.485]], [[0.456]], [[0.406]]]
+    std: [[[0.229]], [[0.224]], [[0.225]]]
+  observation.images.cam_high:
+    mean: [[[0.485]], [[0.456]], [[0.406]]]
+    std: [[[0.229]], [[0.224]], [[0.225]]]
+
+use_amp: true
+use_torch_compile: true
+
+training:
+  offline_steps: 40000
+  online_steps: 0
+  eval_freq: -1
+  save_freq: 10000
+  log_freq: 100
+  save_checkpoint: true
+
+  batch_size: 28
+  lr: 3.5e-5
+  lr_backbone: 3.5e-5
+  lr_warmup_steps: 500
+  drop_n_last_frames: 2
+  weight_decay: 1e-4
+  grad_clip_norm: 10
+  online_steps_between_rollouts: 1
+
+  delta_timestamps:
+    action: "[i / ${fps} for i in range(${policy.chunk_size})]"
+
+eval:
+  n_episodes: 50
+  batch_size: 50
+
+policy:
+  name: hybrid_act_diffusion
+
+  n_obs_steps: 1
+  chunk_size: 100
+  n_action_steps: 100
+
+  input_shapes:
+    observation.images.cam_left_wrist: [3, 480, 640]
+    observation.images.cam_high: [3, 480, 640]
+    observation.state: ["${env.state_dim}"]
+  output_shapes:
+    action: ["${env.action_dim}"]
+
+  input_normalization_modes:
+    observation.images.cam_left_wrist: mean_std
+    observation.images.cam_high: mean_std
+    observation.state: mean_std
+  output_normalization_modes:
+    action: mean_std
+
+  # ACT visual encoder
+  vision_backbone: resnet18
+  pretrained_backbone_weights: ResNet18_Weights.IMAGENET1K_V1
+  replace_final_stride_with_dilation: false
+  pre_norm: false
+  dim_model: 512
+  n_heads: 8
+  dim_feedforward: 3200
+  feedforward_activation: relu
+  n_encoder_layers: 4
+  dropout: 0.1
+
+  # Diffusion U-Net
+  down_dims: [256, 512]
+  kernel_size: 5
+  n_groups: 8
+  diffusion_step_embed_dim: 128
+  use_film_scale_modulation: true
+
+  # Noise scheduler
+  noise_scheduler_type: DDPM
+  num_train_timesteps: 100
+  beta_schedule: squaredcos_cap_v2
+  beta_start: 0.0001
+  beta_end: 0.02
+  prediction_type: epsilon
+  clip_sample: true
+  clip_sample_range: 1.0
+  num_inference_steps: 10
+  do_mask_loss_for_padding: true