add autoencoder example

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examples/axolotl_interface/example_pipelines/autoencoder_pipeline.json

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+{"id": "5478db87-2eea-45c7-b0c1-f6a2fb180a61", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2021-02-04T06:35:44.477042Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.6.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.dataset_to_dataframe", "name": "Extract a DataFrame from a Dataset", "digest": "f817673b67b0bf1fad5efb694e44a59b9c15931520b419f3a852f79152f58bb7"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7", "version": "0.6.0", "python_path": "d3m.primitives.tods.data_processing.column_parser", "name": "Parses strings into their types", "digest": "6aea6b48ddcd847030b423ebf2cac62e67b2935d93f75d10fa0712ea019b2739"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "4503a4c6-42f7-45a1-a1d4-ed69699cf5e1", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type", "digest": "e165d114bca8e1e47f349fffbbf2cf8872f0222328287e24acd8ac8c1cf2511c"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"semantic_types": {"type": "VALUE", "data": ["https://metadata.datadrivendiscovery.org/types/Attribute"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "4503a4c6-42f7-45a1-a1d4-ed69699cf5e1", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type", "digest": "e165d114bca8e1e47f349fffbbf2cf8872f0222328287e24acd8ac8c1cf2511c"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"semantic_types": {"type": "VALUE", "data": ["https://metadata.datadrivendiscovery.org/types/TrueTarget"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "642de2e7-5590-3cab-9266-2a53c326c461", "version": "0.0.1", "python_path": "d3m.primitives.tods.timeseries_processing.transformation.axiswise_scaler", "name": "Axis_wise_scale"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "67e7fcdf-d645-3417-9aa4-85cd369487d9", "version": "0.0.1", "python_path": "d3m.primitives.tods.detection_algorithm.pyod_ae", "name": "TODS.anomaly_detection_primitives.AutoEncoder"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.4.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.construct_predictions", "name": "Construct pipeline predictions output", "digest": "c8a5cb30cc5b6742dbf024cbd54d5283937864c5d5dd9f3d0fb242fa406b1736"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.5.produce"}, "reference": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "aa2c6d9f9a56d76f5f2e8bb29ad5b21b43970a2acb7a7a7695e057bfcd1fdabd"}