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tods/examples/axolotl_interface/example_pipelines/autoencoder_pipeline.json

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  1. {"id": "bfd8aedf-36be-4dad-af8a-c324a03db5f9", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2021-02-13T17:02:35.500457Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.6.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "c78138d9-9377-31dc-aee8-83d9df049c60", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.dataset_to_dataframe", "name": "Extract a DataFrame from a Dataset"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "81235c29-aeb9-3828-911a-1b25319b6998", "version": "0.6.0", "python_path": "d3m.primitives.tods.data_processing.column_parser", "name": "Parses strings into their types"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "a996cd89-ddf0-367f-8e7f-8c013cbc2891", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type"}, "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": "a996cd89-ddf0-367f-8e7f-8c013cbc2891", "version": "0.4.0", "python_path": "d3m.primitives.tods.data_processing.extract_columns_by_semantic_types", "name": "Extracts columns by semantic type"}, "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": "2530840a-07d4-3874-b7d8-9eb5e4ae2bf3", "version": "0.3.0", "python_path": "d3m.primitives.tods.data_processing.construct_predictions", "name": "Construct pipeline predictions output"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.5.produce"}, "reference": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "01ad8ccf817150186ca15157a4f02ee1f738582137321a8a5a4a3252832ce555"}