Commit 8ac6ed0f authored by Sujen's avatar Sujen

Merge branch 'no_corex_text' into 'master'

isi_bugfix

See merge request datadrivendiscovery/primitives!278
parents 2015dc86 adc6c810
......@@ -13,7 +13,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/brekelma/dsbox_graphs@828d2fad21c257a9c4c04e7725c116d185339294#egg=dsbox_graphs"
"package_uri": "git+https://github.com/brekelma/dsbox_graphs@9d26a8a0c0ae9394462768e90cd795685123da60#egg=dsbox_graphs"
}
],
"algorithm_types": [
......@@ -201,5 +201,5 @@
},
"structural_type": "graph_dataset_to_list.GraphDatasetToList",
"description": "A primitive which extracts a DataFrame out of a Dataset.\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.",
"digest": "0a5d2844f8997cba038235151ba13874038d9ee70cd9d2483ae2dfab19ef7f07"
"digest": "7574f62c1a6f1c29f0528f72edef98f74304cce517544334951613bf53d450f7"
}
......@@ -16,7 +16,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/brekelma/dsbox_corex@f7b6319bd593017345b03e27408b097e9af821e9#egg=dsbox-corex"
"package_uri": "git+https://github.com/brekelma/dsbox_corex@728680af809387f38f4357583e2b679397ade07d#egg=dsbox-corex"
}
],
"algorithm_types": [
......@@ -214,5 +214,5 @@
}
},
"structural_type": "corex_continuous.CorexContinuous",
"digest": "f64e6571e41701029c7cda222200df4258e25c6f2c7a3ccba53a60dee9834fb1"
"digest": "286cffd5b45a3f24f0e2afba11b6e6486b049d65cdcd6cf7d0d03a78b2048f85"
}
......@@ -10,7 +10,7 @@
],
"outputs":[
{
"data":"steps.5.produce",
"data":"steps.9.produce",
"name":"predictions of input dataset"
}
],
......@@ -142,6 +142,27 @@
"name":"ISI DSBox Data Encoder",
"digest":"09795e9b7c78a5463c10749a29ce40bf6a2a56cc46541bd00b0d7308483ec0be"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.3.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"18f0bb42-6350-3753-8f2d-d1c3da70f279",
"version":"1.5.1",
"python_path":"d3m.primitives.data_preprocessing.encoder.DSBOX",
"name":"ISI DSBox Data Encoder",
"digest":"09795e9b7c78a5463c10749a29ce40bf6a2a56cc46541bd00b0d7308483ec0be"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
......@@ -166,7 +187,7 @@
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.4.produce"
"data":"steps.5.produce"
}
},
"outputs":[
......@@ -187,7 +208,7 @@
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.5.produce"
"data":"steps.6.produce"
}
},
"outputs":[
......@@ -207,12 +228,12 @@
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.6.produce"
"data":"steps.7.produce"
},
"outputs":
{
"type":"CONTAINER",
"data":"steps.3.produce"
"data":"steps.4.produce"
}
},
"outputs":[
......@@ -242,12 +263,12 @@
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.7.produce"
"data":"steps.8.produce"
},
"outputs":
{
"type":"CONTAINER",
"data":"steps.3.produce"
"data":"steps.4.produce"
}
},
"outputs":[
......
{
"problem":"196_autompg_problem",
"problem":"196_autoMpg_problem",
"full_inputs":[
"196_autompg_dataset"
"196_autoMpg_dataset"
],
"train_inputs":[
"196_autompg_dataset_TRAIN"
"196_autoMpg_dataset_TRAIN"
],
"test_inputs":[
"196_autompg_dataset_TEST"
"196_autoMpg_dataset_TEST"
],
"score_inputs":[
"196_autompg_dataset_SCORE"
"196_autoMpg_dataset_SCORE"
]
}
\ No newline at end of file
......@@ -16,7 +16,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/brekelma/dsbox_corex@f7b6319bd593017345b03e27408b097e9af821e9#egg=dsbox-corex"
"package_uri": "git+https://github.com/brekelma/dsbox_corex@728680af809387f38f4357583e2b679397ade07d#egg=dsbox-corex"
}
],
"algorithm_types": [
......@@ -399,5 +399,5 @@
}
},
"structural_type": "echo_ib.EchoIB",
"digest": "038b459324f4e5de273e7de4c26e02ff9bfa766486d3083d22a8c7d6df8f5d31"
"digest": "a79c584df69f09b9b459d68273bb82a465886befc32c8dee74adfdc4065893e7"
}
......@@ -16,7 +16,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/brekelma/dsbox_corex@f7b6319bd593017345b03e27408b097e9af821e9#egg=dsbox-corex"
"package_uri": "git+https://github.com/brekelma/dsbox_corex@728680af809387f38f4357583e2b679397ade07d#egg=dsbox-corex"
}
],
"algorithm_types": [
......@@ -45,9 +45,9 @@
],
"hyperparams": {
"n_hidden": {
"type": "d3m.metadata.hyperparams.Uniform",
"type": "d3m.metadata.hyperparams.UniformInt",
"default": 10,
"structural_type": "float",
"structural_type": "int",
"semantic_types": [
"http://schema.org/Integer",
"https://metadata.datadrivendiscovery.org/types/TuningParameter"
......@@ -56,13 +56,12 @@
"lower": 0,
"upper": 100,
"lower_inclusive": true,
"upper_inclusive": false,
"q": 1
"upper_inclusive": false
},
"threshold": {
"type": "d3m.metadata.hyperparams.Uniform",
"type": "d3m.metadata.hyperparams.UniformInt",
"default": 0,
"structural_type": "float",
"structural_type": "int",
"semantic_types": [
"http://schema.org/Integer",
"https://metadata.datadrivendiscovery.org/types/TuningParameter"
......@@ -71,13 +70,12 @@
"lower": 0,
"upper": 1000,
"lower_inclusive": true,
"upper_inclusive": false,
"q": 1
"upper_inclusive": false
},
"n_grams": {
"type": "d3m.metadata.hyperparams.Uniform",
"type": "d3m.metadata.hyperparams.UniformInt",
"default": 1,
"structural_type": "float",
"structural_type": "int",
"semantic_types": [
"http://schema.org/Integer",
"https://metadata.datadrivendiscovery.org/types/TuningParameter"
......@@ -86,8 +84,7 @@
"lower": 1,
"upper": 1000,
"lower_inclusive": true,
"upper_inclusive": false,
"q": 1
"upper_inclusive": false
},
"max_df": {
"type": "d3m.metadata.hyperparams.Uniform",
......@@ -261,5 +258,5 @@
}
},
"structural_type": "corex_text.CorexText",
"digest": "7210babace7d873323d9aa99ee67089f7272b78c25224a01da3cbf0afc6597c0"
"digest": "60315a4533867e6c09861ba0cd9d637abce3af67682474294cb128c2a38631ba"
}
{
"id":"cd756d0f-f9cc-4e34-bb8b-6484319e44cc",
"schema":"https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created":"2019-06-05T03:44:33.899641Z",
"inputs":[
{
"name":"input dataset"
}
],
"outputs":[
{
"data":"steps.6.produce",
"name":"predictions of input dataset"
}
],
"steps":[
{
"type":"PRIMITIVE",
"primitive":{
"id":"f31f8c1f-d1c5-43e5-a4b2-2ae4a761ef2e",
"version":"0.2.0",
"python_path":"d3m.primitives.data_transformation.denormalize.Common",
"name":"Denormalize datasets"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"inputs.0"
}
},
"outputs":[
{
"id":"produce"
}
],
"hyperparams":{
"starting_resource":{
"type":"VALUE",
"data":null
},
"recursive":{
"type":"VALUE",
"data":true
},
"many_to_many":{
"type":"VALUE",
"data":false
},
"discard_not_joined_tabular_resources":{
"type":"VALUE",
"data":false
}
}
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"dbb3792d-a44b-4941-a88e-5520c0a23488",
"version":"0.1.0",
"python_path":"d3m.primitives.data_transformation.normalize_graphs.Common",
"name":"Normalize graphs"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.0.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"dfb8c278-5382-47cd-bd39-f9429890a239",
"version":"1.0.0",
"python_path":"d3m.primitives.data_transformation.graph_to_edge_list.DSBOX",
"name":"Extract graph tables from Dataset into list of DataFrame"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.1.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"version":"0.3.0",
"python_path":"d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name":"Extract a DataFrame from a Dataset"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.0.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"4503a4c6-42f7-45a1-a1d4-ed69699cf5e1",
"version":"0.2.0",
"python_path":"d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name":"Extracts columns by semantic type"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.3.produce"
}
},
"outputs":[
{
"id":"produce"
}
],
"hyperparams":{
"semantic_types":{
"type":"VALUE",
"data":[
"https://metadata.datadrivendiscovery.org/types/TrueTarget"
]
}
}
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"48572851-b86b-4fda-961d-f3f466adb58e",
"version":"1.0.0",
"python_path":"d3m.primitives.feature_construction.graph_transformer.GCN",
"name":"GCN"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.2.produce"
},
"outputs":{
"type":"CONTAINER",
"data":"steps.4.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"1dd82833-5692-39cb-84fb-2455683075f3",
"version":"2019.4.4",
"python_path":"d3m.primitives.classification.random_forest.SKlearn",
"name":"sklearn.ensemble.forest.RandomForestClassifier"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.5.produce"
},
"outputs":{
"type":"CONTAINER",
"data":"steps.4.produce"
}
},
"outputs":[
{
"id":"produce"
}
],
"hyperparams":{
"max_depth":{
"type":"VALUE",
"data":{
"case":"int",
"value":30
}
},
"min_samples_leaf":{
"type":"VALUE",
"data":{
"case":"absolute",
"value":2
}
},
"min_samples_split":{
"type":"VALUE",
"data":{
"case":"absolute",
"value":2
}
},
"max_features":{
"type":"VALUE",
"data":{
"case":"calculated",
"value":"sqrt"
}
},
"n_estimators":{
"type":"VALUE",
"data":100
},
"add_index_columns":{
"type":"VALUE",
"data":true
},
"use_semantic_types":{
"type":"VALUE",
"data":false
},
"error_on_no_input":{
"type":"VALUE",
"data":true
}
}
}
],
"name":"ISI_gcn:140244824113296",
"description":"",
"metric":"accuracy",
"template_name":"ISI_gcn",
"template_task":"{'LINK_PREDICTION', 'COMMUNITY_DETECTION', 'VERTEX_NOMINATION', 'COLLABORATIVE_FILTERING'}",
"template_subtask":"{'OVERLAPPING', 'NONE', 'NONOVERLAPPING'}",
"problem_taskType":"vertexNomination",
"problem_taskSubType":"NONE"
}
{
"problem":"LL1_EDGELIST_net_nomination_seed_problem",
"full_inputs":[
"LL1_EDGELIST_net_nomination_seed_dataset"
],
"train_inputs":[
"LL1_EDGELIST_net_nomination_seed_dataset_TRAIN"
],
"test_inputs":[
"LL1_EDGELIST_net_nomination_seed_dataset_TEST"
],
"score_inputs":[
"LL1_EDGELIST_net_nomination_seed_dataset_SCORE"
]
}
{
"id":"fc1eee7f-6435-4001-9cf6-6d24330d9b1c",
"schema":"https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created":"2019-06-05T03:44:33.899641Z",
"inputs":[
{
"name":"input dataset"
}
],
"outputs":[
{
"data":"steps.6.produce",
"name":"predictions of input dataset"
}
],
"steps":[
{
"type":"PRIMITIVE",
"primitive":{
"id":"f31f8c1f-d1c5-43e5-a4b2-2ae4a761ef2e",
"version":"0.2.0",
"python_path":"d3m.primitives.data_transformation.denormalize.Common",
"name":"Denormalize datasets"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"inputs.0"
}
},
"outputs":[
{
"id":"produce"
}
],
"hyperparams":{
"starting_resource":{
"type":"VALUE",
"data":null
},
"recursive":{
"type":"VALUE",
"data":true
},
"many_to_many":{
"type":"VALUE",
"data":false
},
"discard_not_joined_tabular_resources":{
"type":"VALUE",
"data":false
}
}
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"dbb3792d-a44b-4941-a88e-5520c0a23488",
"version":"0.1.0",
"python_path":"d3m.primitives.data_transformation.normalize_graphs.Common",
"name":"Normalize graphs"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.0.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"dfb8c278-5382-47cd-bd39-f9429890a239",
"version":"1.0.0",
"python_path":"d3m.primitives.data_transformation.graph_to_edge_list.DSBOX",
"name":"Extract graph tables from Dataset into list of DataFrame"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.1.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"version":"0.3.0",
"python_path":"d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name":"Extract a DataFrame from a Dataset"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.0.produce"
}
},
"outputs":[
{
"id":"produce"
}
]
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"4503a4c6-42f7-45a1-a1d4-ed69699cf5e1",
"version":"0.2.0",
"python_path":"d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name":"Extracts columns by semantic type"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.3.produce"
}
},
"outputs":[
{
"id":"produce"
}
],
"hyperparams":{
"semantic_types":{
"type":"VALUE",
"data":[
"https://metadata.datadrivendiscovery.org/types/TrueTarget"
]
}
}
},
{
"type":"PRIMITIVE",
"primitive":{
"id":"48572851-b86b-4fda-961d-f3f466adb58e",
"version":"1.0.0",
"python_path":"d3m.primitives.feature_construction.graph_transformer.GCN",
"name":"GCN"
},
"arguments":{
"inputs":{
"type":"CONTAINER",
"data":"steps.2.produce"
},