Commit 3386a49c authored by Brandon Schoenfeld's avatar Brandon Schoenfeld

Merge branch 'master' into byu-dml

parents 78457548 9236ec2e
......@@ -63,6 +63,11 @@ primitives/
"score_inputs": ["185_baseball_dataset_SCORE"]
}
```
* For primitive references in your pipelines, consider not specifying `digest`
field for primitives you do not control. This way your pipelnes will not
fail with digest mismatch if those primitives get updated. (But they might
fail because of behavior change of those primitives, but you cannot do much
about that.)
## Adding a primitive
......@@ -128,7 +133,7 @@ a Docker image with all primitives your pipeline references, or have them instal
You can validate your `.meta` file by running:
```bash
$ python3 -m d3m.runtime -d /path/to/all/datasets fit-score -s scoring.yml -m your-pipeline.meta -p your-pipeline.yml
$ python3 -m d3m.runtime --strict-resolving -d /path/to/all/datasets fit-score -n scoring.yml -m your-pipeline.meta -p your-pipeline.yml
```
Where `scoring.yml` pipeline can be [found here](https://gitlab.com/datadrivendiscovery/metalearning/blob/master/UCBerkeley/scoring.yml).
......
{
"context": "TESTING",
"created": "2019-04-05T00:42:04.764492Z",
"digest": "63b23aa514d50de8c8389075f55926ed0e239ec00fcafaf8ed29ae6d3144283b",
"id": "421ce65c-8690-4123-92a1-cc72d05b537a",
"created": "2019-04-21T22:40:24.479799Z",
"digest": "b3883f93cb798fe2de185086d88e47ca14e6c865b418c5687ed20a488d8996cd",
"id": "aa289991-9b05-4fa1-8824-5b7f3a77797b",
"inputs": [
{
"name": "inputs"
......@@ -29,7 +29,7 @@
}
],
"primitive": {
"digest": "f0d61fba25b25747d35555b258e221ee246e3eb2f4395a3b96f7b2085ef6667c",
"digest": "7e5aa9eea2a9b6d98b8546bd0e00d190a96126bd572e945f1547cf66a9d5293c",
"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"name": "Extract a DataFrame from a Dataset",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
......@@ -50,7 +50,7 @@
}
],
"primitive": {
"digest": "2bbe1d8290bc1ea95610d688a7bdaaca281f83824272f480503c18af41af593a",
"digest": "48627d604ffe92d6e6ab410213fdcf56e0acbf0d248ab8686c4363279d31c21c",
"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7",
"name": "Parses strings into their types",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
......@@ -81,11 +81,11 @@
}
],
"primitive": {
"digest": "d7d1c2bd5b669ac4a01334504f92f970fab4bb10e62755a2081f843ae8829796",
"digest": "a442529ad564892290c76819d033429e7b9d7c2912e80ef5a0b0526a2dfd4ebd",
"id": "d016df89-de62-3c53-87ed-c06bb6a23cde",
"name": "sklearn.impute.SimpleImputer",
"python_path": "d3m.primitives.data_cleaning.imputer.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -116,11 +116,11 @@
}
],
"primitive": {
"digest": "14c23efbfc14e6582b483ac830395ec8d571d34faf77aa7b00f4576a997161ac",
"digest": "d08669cb618a7310c8303a3736aac4267add298983135f65176c43881c724488",
"id": "1b2a32a6-0ec5-3ca0-9386-b8b1f1b831d1",
"name": "sklearn.ensemble.bagging.BaggingClassifier",
"python_path": "d3m.primitives.classification.bagging.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -141,7 +141,7 @@
}
],
"primitive": {
"digest": "19d79c7b4ba3ed3991d8ce52a256985209e0d29ba0e6c2a89a9654f08d3bba29",
"digest": "f4a42da4b04cbdefd7c65c180225fc8fbf068669a8611ef6958ca2f338efdc27",
"id": "8d38b340-f83f-4877-baaa-162f8e551736",
"name": "Construct pipeline predictions output",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
......
......@@ -13,12 +13,12 @@
"https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html"
]
},
"version": "v2019.4.4",
"version": "2019.4.4",
"id": "1b2a32a6-0ec5-3ca0-9386-b8b1f1b831d1",
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@ec0bc85eda8184c7b86440feb41cc2ad1efa6e3e#egg=sklearn_wrap"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@8735151a1aa89f7cf79e33575d4b4545bedd2af7#egg=sklearn_wrap"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -478,5 +478,5 @@
},
"structural_type": "sklearn_wrap.SKBaggingClassifier.SKBaggingClassifier",
"description": "Primitive wrapping for sklearn BaggingClassifier\n`sklearn documentation <https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html>`_\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": "14c23efbfc14e6582b483ac830395ec8d571d34faf77aa7b00f4576a997161ac"
"digest": "d08669cb618a7310c8303a3736aac4267add298983135f65176c43881c724488"
}
\ No newline at end of file
{
"context": "TESTING",
"created": "2019-04-05T00:42:05.439884Z",
"digest": "bbc5ca637d215b66b50e16075f4cd5a7896b53e5f4d7178ff767b85a849a512f",
"id": "151f0ea6-ac67-4cc3-929d-c7b1a6dedee3",
"created": "2019-04-21T22:40:25.144047Z",
"digest": "f1c595e4311ac196f5dcfc5f4ea14899fb2322e0a6fa83b8380a01f62006e4dd",
"id": "7fb06aa5-ae12-4fc8-9915-ed7c6b4ef26a",
"inputs": [
{
"name": "inputs"
......@@ -29,7 +29,7 @@
}
],
"primitive": {
"digest": "f0d61fba25b25747d35555b258e221ee246e3eb2f4395a3b96f7b2085ef6667c",
"digest": "7e5aa9eea2a9b6d98b8546bd0e00d190a96126bd572e945f1547cf66a9d5293c",
"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"name": "Extract a DataFrame from a Dataset",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
......@@ -50,7 +50,7 @@
}
],
"primitive": {
"digest": "2bbe1d8290bc1ea95610d688a7bdaaca281f83824272f480503c18af41af593a",
"digest": "48627d604ffe92d6e6ab410213fdcf56e0acbf0d248ab8686c4363279d31c21c",
"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7",
"name": "Parses strings into their types",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
......@@ -81,11 +81,11 @@
}
],
"primitive": {
"digest": "d7d1c2bd5b669ac4a01334504f92f970fab4bb10e62755a2081f843ae8829796",
"digest": "a442529ad564892290c76819d033429e7b9d7c2912e80ef5a0b0526a2dfd4ebd",
"id": "d016df89-de62-3c53-87ed-c06bb6a23cde",
"name": "sklearn.impute.SimpleImputer",
"python_path": "d3m.primitives.data_cleaning.imputer.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -116,11 +116,11 @@
}
],
"primitive": {
"digest": "a4f587be39eb64860a6c9034cabdf3c5a38ae9eb680ab8a0cfbcad893d0551ed",
"digest": "536baa7887be78d0185b7809ab9f6ec387cb819f2d16e00d8661dd7afe918409",
"id": "dfb1004e-02ac-3399-ba57-8a95639312cd",
"name": "sklearn.naive_bayes.BernoulliNB",
"python_path": "d3m.primitives.classification.bernoulli_naive_bayes.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -141,7 +141,7 @@
}
],
"primitive": {
"digest": "19d79c7b4ba3ed3991d8ce52a256985209e0d29ba0e6c2a89a9654f08d3bba29",
"digest": "f4a42da4b04cbdefd7c65c180225fc8fbf068669a8611ef6958ca2f338efdc27",
"id": "8d38b340-f83f-4877-baaa-162f8e551736",
"name": "Construct pipeline predictions output",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
......
......@@ -13,12 +13,12 @@
"https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html"
]
},
"version": "v2019.4.4",
"version": "2019.4.4",
"id": "dfb1004e-02ac-3399-ba57-8a95639312cd",
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@ec0bc85eda8184c7b86440feb41cc2ad1efa6e3e#egg=sklearn_wrap"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@8735151a1aa89f7cf79e33575d4b4545bedd2af7#egg=sklearn_wrap"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -381,5 +381,5 @@
},
"structural_type": "sklearn_wrap.SKBernoulliNB.SKBernoulliNB",
"description": "Primitive wrapping for sklearn BernoulliNB\n`sklearn documentation <https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html>`_\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": "a4f587be39eb64860a6c9034cabdf3c5a38ae9eb680ab8a0cfbcad893d0551ed"
"digest": "536baa7887be78d0185b7809ab9f6ec387cb819f2d16e00d8661dd7afe918409"
}
\ No newline at end of file
{
"context": "TESTING",
"created": "2019-04-05T00:42:05.565141Z",
"digest": "9d829ee550f16c0400f9d78c0bd94476114b5d3629f658d4f45865971508d4c9",
"id": "c69f3d0b-1732-47e7-bdcd-f9b891abe24b",
"created": "2019-04-21T22:40:25.262910Z",
"digest": "41925edc5e060ed3b62aaf4a6aaa3a3358bc9e1128b91aa0a5633e648614896e",
"id": "e5345a46-c5ba-4146-bb94-974967d7df77",
"inputs": [
{
"name": "inputs"
......@@ -29,7 +29,7 @@
}
],
"primitive": {
"digest": "f0d61fba25b25747d35555b258e221ee246e3eb2f4395a3b96f7b2085ef6667c",
"digest": "7e5aa9eea2a9b6d98b8546bd0e00d190a96126bd572e945f1547cf66a9d5293c",
"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"name": "Extract a DataFrame from a Dataset",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
......@@ -50,7 +50,7 @@
}
],
"primitive": {
"digest": "2bbe1d8290bc1ea95610d688a7bdaaca281f83824272f480503c18af41af593a",
"digest": "48627d604ffe92d6e6ab410213fdcf56e0acbf0d248ab8686c4363279d31c21c",
"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7",
"name": "Parses strings into their types",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
......@@ -81,11 +81,11 @@
}
],
"primitive": {
"digest": "d7d1c2bd5b669ac4a01334504f92f970fab4bb10e62755a2081f843ae8829796",
"digest": "a442529ad564892290c76819d033429e7b9d7c2912e80ef5a0b0526a2dfd4ebd",
"id": "d016df89-de62-3c53-87ed-c06bb6a23cde",
"name": "sklearn.impute.SimpleImputer",
"python_path": "d3m.primitives.data_cleaning.imputer.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -116,11 +116,11 @@
}
],
"primitive": {
"digest": "fa0cee922fb51ed4c46dcf56e6002eaec776e90b920fc38485c056eac45f0ac0",
"digest": "fad58c6fceab815e36e659bd64e76dd44ada7e6d12346081bdc865f7e794d72d",
"id": "e20d003d-6a9f-35b0-b4b5-20e42b30282a",
"name": "sklearn.tree.tree.DecisionTreeClassifier",
"python_path": "d3m.primitives.classification.decision_tree.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -141,7 +141,7 @@
}
],
"primitive": {
"digest": "19d79c7b4ba3ed3991d8ce52a256985209e0d29ba0e6c2a89a9654f08d3bba29",
"digest": "f4a42da4b04cbdefd7c65c180225fc8fbf068669a8611ef6958ca2f338efdc27",
"id": "8d38b340-f83f-4877-baaa-162f8e551736",
"name": "Construct pipeline predictions output",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
......
......@@ -13,12 +13,12 @@
"https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html"
]
},
"version": "v2019.4.4",
"version": "2019.4.4",
"id": "e20d003d-6a9f-35b0-b4b5-20e42b30282a",
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@ec0bc85eda8184c7b86440feb41cc2ad1efa6e3e#egg=sklearn_wrap"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@8735151a1aa89f7cf79e33575d4b4545bedd2af7#egg=sklearn_wrap"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -596,5 +596,5 @@
},
"structural_type": "sklearn_wrap.SKDecisionTreeClassifier.SKDecisionTreeClassifier",
"description": "Primitive wrapping for sklearn DecisionTreeClassifier\n`sklearn documentation <https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html>`_\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": "fa0cee922fb51ed4c46dcf56e6002eaec776e90b920fc38485c056eac45f0ac0"
"digest": "fad58c6fceab815e36e659bd64e76dd44ada7e6d12346081bdc865f7e794d72d"
}
\ No newline at end of file
{
"context": "TESTING",
"created": "2019-04-05T00:42:05.684167Z",
"digest": "645c9b75479021960d086bedc71691873abe38056d45247c194718e754d9909d",
"id": "fff17c0b-3ecb-4d67-9787-f4c712e0c775",
"created": "2019-04-21T22:40:25.377821Z",
"digest": "65cc91758c641e877c57fff08c7345a58a250234e8e001176de1a5a60188b2a6",
"id": "0445c0eb-8bcc-4a52-98a1-f31828b6839a",
"inputs": [
{
"name": "inputs"
......@@ -29,7 +29,7 @@
}
],
"primitive": {
"digest": "f0d61fba25b25747d35555b258e221ee246e3eb2f4395a3b96f7b2085ef6667c",
"digest": "7e5aa9eea2a9b6d98b8546bd0e00d190a96126bd572e945f1547cf66a9d5293c",
"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"name": "Extract a DataFrame from a Dataset",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
......@@ -50,7 +50,7 @@
}
],
"primitive": {
"digest": "2bbe1d8290bc1ea95610d688a7bdaaca281f83824272f480503c18af41af593a",
"digest": "48627d604ffe92d6e6ab410213fdcf56e0acbf0d248ab8686c4363279d31c21c",
"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7",
"name": "Parses strings into their types",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
......@@ -81,11 +81,11 @@
}
],
"primitive": {
"digest": "d7d1c2bd5b669ac4a01334504f92f970fab4bb10e62755a2081f843ae8829796",
"digest": "a442529ad564892290c76819d033429e7b9d7c2912e80ef5a0b0526a2dfd4ebd",
"id": "d016df89-de62-3c53-87ed-c06bb6a23cde",
"name": "sklearn.impute.SimpleImputer",
"python_path": "d3m.primitives.data_cleaning.imputer.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -116,11 +116,11 @@
}
],
"primitive": {
"digest": "12090d6298390676c362c1ab27bc3bdfd13a1f9947a40c663822136877f079ea",
"digest": "b6293031af45121424b3aa2b0bdce28927e26086cefbdf14e25cfbb36e5fb236",
"id": "a1056ddf-2e89-3d8d-8308-2146170ae54d",
"name": "sklearn.dummy.DummyClassifier",
"python_path": "d3m.primitives.classification.dummy.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -141,7 +141,7 @@
}
],
"primitive": {
"digest": "19d79c7b4ba3ed3991d8ce52a256985209e0d29ba0e6c2a89a9654f08d3bba29",
"digest": "f4a42da4b04cbdefd7c65c180225fc8fbf068669a8611ef6958ca2f338efdc27",
"id": "8d38b340-f83f-4877-baaa-162f8e551736",
"name": "Construct pipeline predictions output",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
......
......@@ -13,12 +13,12 @@
"https://scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html"
]
},
"version": "v2019.4.4",
"version": "2019.4.4",
"id": "a1056ddf-2e89-3d8d-8308-2146170ae54d",
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@ec0bc85eda8184c7b86440feb41cc2ad1efa6e3e#egg=sklearn_wrap"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@8735151a1aa89f7cf79e33575d4b4545bedd2af7#egg=sklearn_wrap"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -432,5 +432,5 @@
},
"structural_type": "sklearn_wrap.SKDummyClassifier.SKDummyClassifier",
"description": "Primitive wrapping for sklearn DummyClassifier\n`sklearn documentation <https://scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html>`_\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": "12090d6298390676c362c1ab27bc3bdfd13a1f9947a40c663822136877f079ea"
"digest": "b6293031af45121424b3aa2b0bdce28927e26086cefbdf14e25cfbb36e5fb236"
}
\ No newline at end of file
{
"context": "TESTING",
"created": "2019-04-05T00:42:05.819691Z",
"digest": "69851f595d7d5e55dbcb9bb80d598145c3435419577f33f83ed7e29660b1766b",
"id": "3d9c68fb-c9b6-4cde-beec-016d3877f9a7",
"created": "2019-04-21T22:40:25.514230Z",
"digest": "ddca6107620ec6e86c8f13b594f00dd1f3c3153f2759671e1735229fa7cbc1af",
"id": "b365a343-5947-4054-8e7d-33499e507dab",
"inputs": [
{
"name": "inputs"
......@@ -29,7 +29,7 @@
}
],
"primitive": {
"digest": "f0d61fba25b25747d35555b258e221ee246e3eb2f4395a3b96f7b2085ef6667c",
"digest": "7e5aa9eea2a9b6d98b8546bd0e00d190a96126bd572e945f1547cf66a9d5293c",
"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"name": "Extract a DataFrame from a Dataset",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
......@@ -50,7 +50,7 @@
}
],
"primitive": {
"digest": "2bbe1d8290bc1ea95610d688a7bdaaca281f83824272f480503c18af41af593a",
"digest": "48627d604ffe92d6e6ab410213fdcf56e0acbf0d248ab8686c4363279d31c21c",
"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7",
"name": "Parses strings into their types",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
......@@ -81,11 +81,11 @@
}
],
"primitive": {
"digest": "d7d1c2bd5b669ac4a01334504f92f970fab4bb10e62755a2081f843ae8829796",
"digest": "a442529ad564892290c76819d033429e7b9d7c2912e80ef5a0b0526a2dfd4ebd",
"id": "d016df89-de62-3c53-87ed-c06bb6a23cde",
"name": "sklearn.impute.SimpleImputer",
"python_path": "d3m.primitives.data_cleaning.imputer.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -116,11 +116,11 @@
}
],
"primitive": {
"digest": "8bbf7364a6fb342784fbc41fac0eed74db46944f635f8e11aed7b3e366dcf6f1",
"digest": "2406d67428c1c2bc088489d44f77e9458d607628d98a993c2855ffef9e378c62",
"id": "c8a28f02-ef4a-35a8-87f1-cf79980f5c3e",
"name": "sklearn.ensemble.forest.ExtraTreesClassifier",
"python_path": "d3m.primitives.classification.extra_trees.SKlearn",
"version": "v2019.4.4"
"version": "2019.4.4"
},
"type": "PRIMITIVE"
},
......@@ -141,7 +141,7 @@
}
],
"primitive": {
"digest": "19d79c7b4ba3ed3991d8ce52a256985209e0d29ba0e6c2a89a9654f08d3bba29",
"digest": "f4a42da4b04cbdefd7c65c180225fc8fbf068669a8611ef6958ca2f338efdc27",
"id": "8d38b340-f83f-4877-baaa-162f8e551736",
"name": "Construct pipeline predictions output",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
......
......@@ -13,12 +13,12 @@
"https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html"
]
},
"version": "v2019.4.4",
"version": "2019.4.4",
"id": "c8a28f02-ef4a-35a8-87f1-cf79980f5c3e",
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@ec0bc85eda8184c7b86440feb41cc2ad1efa6e3e#egg=sklearn_wrap"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/sklearn-wrap.git@8735151a1aa89f7cf79e33575d4b4545bedd2af7#egg=sklearn_wrap"
}
],
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
......@@ -645,5 +645,5 @@
},
"structural_type": "sklearn_wrap.SKExtraTreesClassifier.SKExtraTreesClassifier",
"description": "Primitive wrapping for sklearn ExtraTreesClassifier\n`sklearn documentation <https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html>`_\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": "8bbf7364a6fb342784fbc41fac0eed74db46944f635f8e11aed7b3e366dcf6f1"
"digest": "2406d67428c1c2bc088489d44f77e9458d607628d98a993c2855ffef9e378c62"
}
\ No newline at end of file
{
"context": "TESTING",
"created": "2019-04-05T00:42:05.926901Z",
"digest": "1b30172553535342155bbbc53913b6bc09f1c84a1f1a96c9d76f714567a6f629",
"id": "52330bcc-a8bb-4754-bc2b-67c90d86d127",
"created": "2019-04-21T22:40:25.639770Z",
"digest": "ae8f8b9ac064d0c151c5a403e7de7624e338d4594c9df2e4d6e1735d74a15e77",
"id": "10d38508-1654-416c-a690-facf1b6682e6",
"inputs": [
{
"name": "inputs"
......@@ -29,7 +29,7 @@
}
],
"primitive": {
"digest": "f0d61fba25b25747d35555b258e221ee246e3eb2f4395a3b96f7b2085ef6667c",
"digest": "7e5aa9eea2a9b6d98b8546bd0e00d190a96126bd572e945f1547cf66a9d5293c",
"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65",
"name": "Extract a DataFrame from a Dataset",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
......@@ -50,7 +50,7 @@
}
],
"primitive": {