{
    "pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
    "featuresDict": {
        "features": {
            "steps": {
                "pythonClassName": "tensorflow_datasets.core.features.dataset_feature.Dataset",
                "sequence": {
                    "feature": {
                        "pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
                        "featuresDict": {
                            "features": {
                                "action": {
                                    "pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
                                    "tensor": {
                                        "shape": {
                                            "dimensions": [
                                                "7"
                                            ]
                                        },
                                        "dtype": "float32",
                                        "encoding": "none"
                                    },
                                    "description": "Action consists of [3x robot delta displacements, 3x delta rotations, and gripper closedness action]."
                                },
                                "natural_language_instruction": {
                                    "pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
                                    "text": {},
                                    "description": "Language Instruction."
                                },
                                "is_terminal": {
                                    "pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
                                    "tensor": {
                                        "shape": {},
                                        "dtype": "bool",
                                        "encoding": "none"
                                    },
                                    "description": "True on the last step of the episode if it is a terminal step, True for demos."
                                },
                                "is_last": {
                                    "pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
                                    "tensor": {
                                        "shape": {},
                                        "dtype": "bool",
                                        "encoding": "none"
                                    },
                                    "description": "True on the last step of the episode."
                                },
                                "natural_language_embedding": {
                                    "pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
                                    "tensor": {
                                        "shape": {
                                            "dimensions": [
                                                "512"
                                            ]
                                        },
                                        "dtype": "float32",
                                        "encoding": "none"
                                    },
                                    "description": "Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5"
                                },
                                "observation": {
                                    "pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
                                    "featuresDict": {
                                        "features": {
                                            "image_front": {
                                                "pythonClassName": "tensorflow_datasets.core.features.image_feature.Image",
                                                "image": {
                                                    "shape": {
                                                        "dimensions": [
                                                            "224",
                                                            "224",
                                                            "3"
                                                        ]
                                                    },
                                                    "dtype": "uint8",
                                                    "encodingFormat": "png"
                                                },
                                                "description": "Main camera RGB observation."
                                            },
                                            "state": {
                                                "pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
                                                "tensor": {
                                                    "shape": {
                                                        "dimensions": [
                                                            "8"
                                                        ]
                                                    },
                                                    "dtype": "float32",
                                                    "encoding": "none"
                                                },
                                                "description": "Robot state, consists of [3x position, 4x quaternion, and gripper closedness]."
                                            }
                                        }
                                    }
                                },
                                "is_first": {
                                    "pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
                                    "tensor": {
                                        "shape": {},
                                        "dtype": "bool",
                                        "encoding": "none"
                                    },
                                    "description": "True on the first step of the episode."
                                },
                                "discount": {
                                    "pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
                                    "tensor": {
                                        "shape": {},
                                        "dtype": "float32",
                                        "encoding": "none"
                                    },
                                    "description": "Discount if provided, default to 1."
                                },
                                "reward": {
                                    "pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
                                    "tensor": {
                                        "shape": {},
                                        "dtype": "float32",
                                        "encoding": "none"
                                    },
                                    "description": "Reward if provided, 1 on final step for demos."
                                }
                            }
                        }
                    },
                    "length": "-1"
                }
            },
            "episode_metadata": {
                "pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
                "featuresDict": {
                    "features": {
                        "file_path": {
                            "pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
                            "text": {},
                            "description": "Path to the original data file."
                        }
                    }
                }
            }
        }
    }
}