Commit d3d98c5b authored by Ke-Thia Yao's avatar Ke-Thia Yao Committed by Sujen

Update ISI primitives

parent e5b871e9
......@@ -18,10 +18,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-featurizer-do-nothing-dataset-version",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.do_nothing_for_dataset.DSBOX",
"name": "DSBox do-nothing primitive dataset version",
"digest": "cf9e759201faf295f7e1c6c38ea05a732f0f0734c3d54214732e9b33e0745af0"
"digest": "762a449e5a611b45997f7a35e749754cc263f599d051480721269d9e8e3a8234"
},
"arguments": {
"inputs": {
......@@ -42,7 +42,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_transformation.denormalize.Common",
"name": "Denormalize datasets",
"digest": "33efea32abc3e9f8496ca4f266711622227e629cf84c896637e3e40279547949"
"digest": "afca078f05899b9f329e1b8cc0973848e39e83a7521d2cade81c1fbad5cf8139"
},
"arguments": {
"inputs": {
......@@ -63,7 +63,7 @@
"version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset",
"digest": "789969c6a4a81b25b04c95963721259599f8c43c90a6091e49f44c7fe08f51de"
"digest": "e557fc176af67913ed241dbe793cf986439157cfe9c4a12f1aafcba3c07b8b6f"
},
"arguments": {
"inputs": {
......@@ -84,7 +84,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type",
"digest": "57db870295ef8a63e62429950d7e19c417f07bb9e52124e1f9065b2b0cd55a11"
"digest": "d4fa27a3e215b89d2231d344ec0202e1b8e41ad322deb79c68fd6ca673eae3f7"
},
"arguments": {
"inputs": {
......@@ -111,10 +111,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "b2612849-39e4-33ce-bfda-24f3e2cb1e93",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.schema_discovery.profiler.DSBOX",
"name": "DSBox Profiler",
"digest": "4a3e41115468081622461581a75a287ac39dd118cd5e4c2300c147c23dc98c3b"
"digest": "d9ec8f170278e82bda5fca53e87e7a88617cc1e31a2cb1c53efe4f452648c801"
},
"arguments": {
"inputs": {
......@@ -132,10 +132,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-cleaning-featurizer",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_cleaning.cleaning_featurizer.DSBOX",
"name": "DSBox Cleaning Featurizer",
"digest": "6076b109002bb9b638d6a5fddcd68134d5b18068e52ee8ce2149ce9144f3ca83"
"digest": "32186cac0df6e6dd2622f0313ff28e02c9e7d8b275c7d28c5834412152b714f1"
},
"arguments": {
"inputs": {
......@@ -153,10 +153,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "18f0bb42-6350-3753-8f2d-d1c3da70f279",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.encoder.DSBOX",
"name": "ISI DSBox Data Encoder",
"digest": "107bf5d6f44c8251b9531ac13bac04501d6dc145c41ff370e45dc0fcf7f3dc67"
"digest": "6e8ad1922cdee5c06822e4b51f149c120734d196747435b5efb02abf9ab3eeb7"
},
"arguments": {
"inputs": {
......@@ -174,10 +174,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "7ddf2fd8-2f7f-4e53-96a7-0d9f5aeecf93",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_transformation.to_numeric.DSBOX",
"name": "ISI DSBox To Numeric DataFrame",
"digest": "571beb63f5a194d54fe181fe938cecfde2e5da70d4c990693c50a83982cab8fc"
"digest": "2756820b9b3fc0d406b7cd832f662a69874acfbbc934e4f99a5105a5b257a9c5"
},
"arguments": {
"inputs": {
......@@ -195,10 +195,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "7894b699-61e9-3a50-ac9f-9bc510466667",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.mean_imputation.DSBOX",
"name": "DSBox Mean Imputer",
"digest": "4ee862e2ff01eb4f3cd0b3738a4b0611964c19bab63f334ad009e2e0a0a3b8c7"
"digest": "fff12f5a7ffd777c45c3d4bf80af4322f002f0a4eea24f66d0a63c0db52d81ce"
},
"arguments": {
"inputs": {
......@@ -216,10 +216,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-multi-table-feature-scaler",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.normalization.iqr_scaler.DSBOX",
"name": "DSBox feature scaler",
"digest": "dc8134b1b05f9b7dc8013e7dccd55d4325916eb270eb76a3dc45d8a05c60eb4c"
"digest": "79c4873dec8cc39bd3d2622331b7c94bb1c40fb9d664c87c73875d6924e4739e"
},
"arguments": {
"inputs": {
......@@ -237,10 +237,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-featurizer-do-nothing",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.do_nothing.DSBOX",
"name": "DSBox do-nothing primitive",
"digest": "217a5b1284c197b6b4d2a5bf5fe10a370e14e5ef1b4267c23ed70c33c7ddbf70"
"digest": "3eff0c573bb28771551a59790e5b28bd2999aea24e0c20c94c8cc2a7f1e13435"
},
"arguments": {
"inputs": {
......@@ -261,7 +261,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type",
"digest": "57db870295ef8a63e62429950d7e19c417f07bb9e52124e1f9065b2b0cd55a11"
"digest": "d4fa27a3e215b89d2231d344ec0202e1b8e41ad322deb79c68fd6ca673eae3f7"
},
"arguments": {
"inputs": {
......@@ -287,10 +287,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "7ddf2fd8-2f7f-4e53-96a7-0d9f5aeecf93",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_transformation.to_numeric.DSBOX",
"name": "ISI DSBox To Numeric DataFrame",
"digest": "571beb63f5a194d54fe181fe938cecfde2e5da70d4c990693c50a83982cab8fc"
"digest": "2756820b9b3fc0d406b7cd832f662a69874acfbbc934e4f99a5105a5b257a9c5"
},
"arguments": {
"inputs": {
......@@ -314,10 +314,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-featurizer-do-nothing",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.do_nothing.DSBOX",
"name": "DSBox do-nothing primitive",
"digest": "217a5b1284c197b6b4d2a5bf5fe10a370e14e5ef1b4267c23ed70c33c7ddbf70"
"digest": "3eff0c573bb28771551a59790e5b28bd2999aea24e0c20c94c8cc2a7f1e13435"
},
"arguments": {
"inputs": {
......@@ -335,10 +335,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "a323b46a-6c15-373e-91b4-20efbd65402f",
"version": "2019.4.4",
"version": "2019.6.7",
"python_path": "d3m.primitives.classification.linear_discriminant_analysis.SKlearn",
"name": "sklearn.discriminant_analysis.LinearDiscriminantAnalysis",
"digest": "0ccb2953abd0c69aa197d33de08e1420b7396a127513698911b68db1fe30825c"
"digest": "f182d4c6ad43c99e4c9efe8a71e59523c71d061db1e6cd034c0788f0ad1e0736"
},
"arguments": {
"inputs": {
......@@ -374,10 +374,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "90e7b335-5af0-35ad-932c-9c771fe84693",
"version": "2019.4.4",
"version": "2019.6.7",
"python_path": "d3m.primitives.classification.nearest_centroid.SKlearn",
"name": "sklearn.neighbors.nearest_centroid.NearestCentroid",
"digest": "08ef5cd7704580ceedc068c2317f630f677a50917356f21ec88a2e993c8b42b7"
"digest": "d51e59f6473f3b8a32b3437588dff16b6e8b59cad52210a88fb425c2bc52d52a"
},
"arguments": {
"inputs": {
......@@ -413,10 +413,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "b9c81b40-8ed1-3b23-80cf-0d6fe6863962",
"version": "2019.4.4",
"version": "2019.6.7",
"python_path": "d3m.primitives.classification.logistic_regression.SKlearn",
"name": "sklearn.linear_model.logistic.LogisticRegression",
"digest": "cdcc79c6cee40349bd0151f5d9a5d3b5913a70f66b18b04053c24c4fc40d449e"
"digest": "26a49f4800dd3ad9c0adea5079c09e98128adbb92f73d8ffec21511bb3aacf8b"
},
"arguments": {
"inputs": {
......@@ -452,10 +452,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-vertical-concat",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.vertical_concatenate.DSBOX",
"name": "DSBox vertically concat",
"digest": "c30c68e07fee418539b8ba7c5ce14265f68cb9814f5b371b56bea02fd4791f56"
"digest": "76ee95ac98a4d4e0ace6a3a4c84040ac5eeeb3f04c11b689dce9d2116d07c874"
},
"arguments": {
"inputs": {
......@@ -477,10 +477,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-ensemble-voting",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.classification.ensemble_voting.DSBOX",
"name": "DSBox ensemble voting",
"digest": "6f4e68c271c6c8a5963c9eef717c3dca6ffa1309c8be3a57f67989b07e86f7fb"
"digest": "c9ebb0b0da2c6b679144e2bb9c70edcb49022f61ce8cdd31a4b49c0ee02c1b3d"
},
"arguments": {
"inputs": {
......@@ -497,5 +497,5 @@
],
"name": "default_classification_template:139808543415464",
"description": "",
"digest": "1262ab3bb02e521ebba7f099adb982febdca3084b7f99db82d848b1837c107d2"
"digest": "25d1e60268cc54d92de1fb24d637f39277f36ef80c898e9aa35c8203deba3b3f"
}
{
"id": "dsbox-ensemble-voting",
"version": "1.5.2",
"version": "1.5.3",
"name": "DSBox ensemble voting",
"description": "A ensemble voting primitive. The input dataframe should be the output of multiple learners concatenated together\nusing the data_preprocessing.horizontal_concat.DSBOX primitve.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"python_path": "d3m.primitives.classification.ensemble_voting.DSBOX",
......@@ -10,7 +10,7 @@
],
"source": {
"name": "ISI",
"contact": "kyao:kyao@isi.edu",
"contact": "mailto:kyao@isi.edu",
"uris": [
"https://github.com/usc-isi-i2/dsbox-primitives"
]
......@@ -22,7 +22,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/usc-isi-i2/dsbox-primitives@ca2ed654966f411288c78954c2e143be84559138#egg=dsbox-primitives"
"package_uri": "git+https://github.com/usc-isi-i2/dsbox-primitives@af995be72ba1230788a04a27b3f31b9ec353d1d2#egg=dsbox-primitives"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -185,5 +185,5 @@
}
},
"structural_type": "dsbox.datapostprocessing.ensemble_voting.EnsembleVoting",
"digest": "6f4e68c271c6c8a5963c9eef717c3dca6ffa1309c8be3a57f67989b07e86f7fb"
"digest": "2cb4d81bfe64821ca655d329cc8fff7e8054764eecf5979ac7e34e689ba778c3"
}
......@@ -21,7 +21,7 @@
"version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset",
"digest": "789969c6a4a81b25b04c95963721259599f8c43c90a6091e49f44c7fe08f51de"
"digest": "e557fc176af67913ed241dbe793cf986439157cfe9c4a12f1aafcba3c07b8b6f"
},
"arguments": {
"inputs": {
......@@ -42,7 +42,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type",
"digest": "57db870295ef8a63e62429950d7e19c417f07bb9e52124e1f9065b2b0cd55a11"
"digest": "d4fa27a3e215b89d2231d344ec0202e1b8e41ad322deb79c68fd6ca673eae3f7"
},
"arguments": {
"inputs": {
......@@ -72,7 +72,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type",
"digest": "57db870295ef8a63e62429950d7e19c417f07bb9e52124e1f9065b2b0cd55a11"
"digest": "d4fa27a3e215b89d2231d344ec0202e1b8e41ad322deb79c68fd6ca673eae3f7"
},
"arguments": {
"inputs": {
......@@ -101,7 +101,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_preprocessing.video_reader.DataFrameCommon",
"name": "Columns video reader",
"digest": "a60b5a6093cbbc6c836d51b244b5b07aef1e3055da5e0fafb649cbb68b86c073"
"digest": "5a2961b4974a1af0dd503f90259474c6e5ed44a9a61a44163de9c8560d606b63"
},
"arguments": {
"inputs": {
......@@ -119,10 +119,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-featurizer-image-inceptionV3",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.feature_extraction.inceptionV3_image_feature.DSBOX",
"name": "DSBox Image Featurizer inceptionV3",
"digest": "51445943e1f1610bf277e615d0fb9464a782aea6ba1d02232ec1f0ffbb028a9f"
"digest": "11f7f28a3561816a357c5851c8ea560572271bfaddf33c018336bd1dc27af6e2"
},
"arguments": {
"inputs": {
......@@ -146,10 +146,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-featurizer-video-classification-lstm",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.classification.lstm.DSBOX",
"name": "DSBox Video Classification LSTM",
"digest": "c097fda5631c64829931685f2f99df149188c5c5187c6623e47828a2a49dd8b3"
"digest": "eb32157e614fd864d5b87da8417aecf079cf4691363aad37b4b55d3b64d758e0"
},
"arguments": {
"inputs": {
......@@ -180,5 +180,5 @@
],
"name": "DefaultVideoClassificationTemplate:5019768584",
"description": "",
"digest": "65a6654a0574bf291dc9f522c2a6983f46829ff45cf8b7c84bde54443301a267"
"digest": "6628738546bd0eee059852e600276926da67feebf73a6de89fa79f2ae831729a"
}
{
"id": "dsbox-featurizer-video-classification-lstm",
"version": "1.5.2",
"version": "1.5.3",
"name": "DSBox Video Classification LSTM",
"description": "video classification primitive that use lstm RNN network\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"python_path": "d3m.primitives.classification.lstm.DSBOX",
......@@ -23,7 +23,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/usc-isi-i2/dsbox-primitives@ca2ed654966f411288c78954c2e143be84559138#egg=dsbox-primitives"
"package_uri": "git+https://github.com/usc-isi-i2/dsbox-primitives@af995be72ba1230788a04a27b3f31b9ec353d1d2#egg=dsbox-primitives"
}
],
"precondition": [],
......@@ -324,5 +324,5 @@
}
},
"structural_type": "dsbox.datapreprocessing.featurizer.image.video_classification.LSTM",
"digest": "c097fda5631c64829931685f2f99df149188c5c5187c6623e47828a2a49dd8b3"
"digest": "f07059edb9e5f6ebb9d648d0c95be77b7233c16dc21fec45e28c4e4f94f029fc"
}
{
"id": "wikidata-wikifier",
"version": "1.5.2",
"version": "1.5.3",
"name": "wikidata wikifier",
"python_path": "d3m.primitives.data_augmentation.wikifier.DSBOX",
"description": "A primitive that takes a list of datamart dataset and choose 1 or a few best dataframe and perform join, return an accessible d3m.dataframe for further processing\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
......@@ -15,7 +15,7 @@
],
"source": {
"name": "ISI",
"contact": "kyao:kyao@isi.edu",
"contact": "mailto:kyao@isi.edu",
"uris": [
"https://github.com/usc-isi-i2/dsbox-primitives"
]
......@@ -23,7 +23,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/usc-isi-i2/dsbox-primitives@ca2ed654966f411288c78954c2e143be84559138#egg=dsbox-primitives"
"package_uri": "git+https://github.com/usc-isi-i2/dsbox-primitives@af995be72ba1230788a04a27b3f31b9ec353d1d2#egg=dsbox-primitives"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -215,5 +215,5 @@
}
},
"structural_type": "dsbox.datapreprocessing.cleaner.wikifier.Wikifier",
"digest": "b2ca83827d4001fd5f7ad95004775c703da172b4f87b9fc7e72c9860ada892dd"
"digest": "f8111370e158cfef3bc30f4862e9c8c1c897762b2b0e3e98faed6af7ad4e6a9b"
}
......@@ -18,10 +18,10 @@
"type": "PRIMITIVE",
"primitive": {
"id": "dsbox-featurizer-do-nothing-dataset-version",
"version": "1.5.2",
"version": "1.5.3",
"python_path": "d3m.primitives.data_preprocessing.do_nothing_for_dataset.DSBOX",
"name": "DSBox do-nothing primitive dataset version",
"digest": "cf9e759201faf295f7e1c6c38ea05a732f0f0734c3d54214732e9b33e0745af0"
"digest": "762a449e5a611b45997f7a35e749754cc263f599d051480721269d9e8e3a8234"
},
"arguments": {
"inputs": {
......@@ -42,7 +42,7 @@
"version": "0.2.0",
"python_path": "d3m.primitives.data_transformation.denormalize.Common",
"name": "Denormalize datasets",
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