eat_chips / config.json
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{
"chunk_size": 100,
"dim_feedforward": 3200,
"dim_model": 512,
"dropout": 0.1,
"feedforward_activation": "relu",
"input_normalization_modes": {
"observation.images.laptop": "mean_std",
"observation.images.phone": "mean_std",
"observation.state": "mean_std"
},
"input_shapes": {
"observation.images.laptop": [
3,
480,
640
],
"observation.images.phone": [
3,
480,
640
],
"observation.state": [
6
]
},
"kl_weight": 10.0,
"latent_dim": 32,
"n_action_steps": 100,
"n_decoder_layers": 1,
"n_encoder_layers": 4,
"n_heads": 8,
"n_obs_steps": 1,
"n_vae_encoder_layers": 4,
"output_normalization_modes": {
"action": "mean_std"
},
"output_shapes": {
"action": [
6
]
},
"pre_norm": false,
"pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
"replace_final_stride_with_dilation": false,
"temporal_ensemble_coeff": null,
"use_vae": true,
"vision_backbone": "resnet18"
}