Update README.md

README.md

@@ -26,4 +26,57 @@ export LEROBOT_HOME=/PATH/TO/LEROBOT_HOME
 uv run scripts/serve_policy.py policy:checkpoint \
     --policy.config=pi0_fast_fractal_fft_pt_tokenizer \
     --policy.dir=$THE_MODEL_PATH
+```
+
+### Data Config
+```python
+@dataclasses.dataclass(frozen=True)
+class LeRobotFractalDataConfig(DataConfigFactory):
+    use_quantile_norm: bool = True
+
+    # Action keys that will be used to read the action sequence from the dataset.
+    action_sequence_keys: Sequence[str] = ("action",)
+
+    prompt_from_task: bool = True
+
+    @override
+    def create(self, assets_dirs: pathlib.Path, model_config: _model.BaseModelConfig) -> DataConfig:
+        # Make inputs look like they come from the Libero environment
+        repack_transform = _transforms.Group(
+            inputs=[
+                _transforms.RepackTransform(
+                    {
+                        "observation/primary_image": "observation.images.image",
+                        "observation/state": "observation.state",
+                        "actions": "action",
+                        "prompt": "prompt",
+                    }
+                )
+            ]
+        )
+
+        # Prepare data for policy training
+        # Convert images to uint8 numpy arrays, add masks
+        data_transforms = _transforms.Group(
+            inputs=[
+                fractal_policy.FractalInputs(
+                    action_dim=model_config.action_dim,
+                    model_type=model_config.model_type,
+                )
+            ],
+            outputs=[fractal_policy.FractalOutputs()],
+        )
+
+        # Model transforms include things like tokenizing the prompt and action targets
+        model_transforms = ModelTransformFactory()(model_config)
+
+        return dataclasses.replace(
+            self.create_base_config(assets_dirs),
+            repack_transforms=repack_transform,
+            data_transforms=data_transforms,
+            model_transforms=model_transforms,
+            use_quantile_norm=self.use_quantile_norm,
+            action_sequence_keys=self.action_sequence_keys,
+            prompt_from_task=self.prompt_from_task,
+        )
 ```