From df27bd2ff65c67156bfe28ca75d9fe3d82c63e9e Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Wed, 5 Feb 2020 06:44:04 +0100 Subject: [PATCH 01/41] New template strategy --- .dockerignore | 1 + .gitignore | 6 +- Dockerfile | 13 +- requirements.txt | 2 +- scripts/evaluate_templates.sh | 9 + scripts/generate_templates.py | 53 +++ scripts/run_on_d3m.sh | 13 + scripts/run_templates.py | 106 +++++ setup.py | 10 +- ta2/__main__.py | 36 +- ta2/loader.py | 21 + .../01717d30-57ea-43e5-9d4d-d457b124be43.json | 1 - .../0194a156-ad03-42ad-995e-c2f08cd2145b.json | 1 - .../0431cde4-cc0a-4fc7-811a-b7a8fc1af5cf.json | 1 - .../05a0caa2-67e4-4c4c-9dd4-a29fa2395b85.json | 1 - .../06888384-cca4-46d2-bdb5-f5ae6d668786.json | 1 - .../07053593-bce8-4587-ae53-1d4a519b1d53.json | 1 - .../082a7979-b5a2-4c6d-ab92-84c24d55c019.json | 1 - .../082ba558-c2fb-4f75-bc36-19092f136a52.json | 1 - .../09148494-7aa8-49c4-b55c-47a7a8a8656c.json | 1 - .../0b64a654-dcd8-40d9-b9eb-ad3f37121d2e.json | 1 - 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ta2/templates/fddbf328ae4f5c3109ef19c7435bbba705e99115b094290e6d503e7879ae95cd.json create mode 100644 ta2/templates/feeb43817257e6980a8d8f4ecc612d9c2e5f15a981d61b97dc442f738b45e9ce.json create mode 100644 ta2/templates/ff6ac7c0435581088a468e37ad74b80f8ee4f366967dffc1f22aa80533fff6c5.json diff --git a/.dockerignore b/.dockerignore index 672592c..f4bde6c 100644 --- a/.dockerignore +++ b/.dockerignore @@ -8,3 +8,4 @@ static/ notebooks/ .tox/ .git/ +primitives/ diff --git a/.gitignore b/.gitignore index 53777ae..f6c3557 100644 --- a/.gitignore +++ b/.gitignore @@ -105,8 +105,8 @@ ENV/ # vim .*.swp -input* +input output/ -static/ notebooks/ -templates.bak/ +primitives/ +static diff --git a/Dockerfile b/Dockerfile index ff6b923..a1dc092 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,5 +1,4 @@ -FROM registry.gitlab.com/datadrivendiscovery/images/primitives:ubuntu-bionic-python36-v2019.11.10-20191127-050901 -# FROM registry.gitlab.com/datadrivendiscovery/images/primitives:ubuntu-bionic-python36-v2019.11.10 +FROM registry.gitlab.com/datadrivendiscovery/images/primitives:ubuntu-bionic-python36-v2020.1.9-20200201-083256 ARG UID=1000 ARG D3MPORT=45042 @@ -10,10 +9,6 @@ EXPOSE $D3MPORT RUN mkdir -p /user_dev -# RUN mkdir -p /user_dev && \ -# mkdir -p /user_dev/output && \ -# mkdir -p /user_dev/input && \ -# mkdir -p /user_dev/static && \ RUN ln -s /output /user_dev/output && \ ln -s /input /user_dev/input && \ ln -s /static /user_dev/static @@ -24,11 +19,9 @@ RUN pip3 install -r /user_dev/requirements.txt # Copy code COPY setup.py MANIFEST.in /user_dev/ +RUN pip3 install -e /user_dev ipdb + COPY ta2 /user_dev/ta2 RUN chown -R $UID:$UID /user_dev -# Install project -RUN pip3 install /user_dev -RUN pip3 install ipdb - CMD ["python3", "/user_dev/ta2/ta3/server.py", "-v"] diff --git a/requirements.txt b/requirements.txt index e0d79a5..7cbcf38 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1 +1 @@ --e git+https://gitlab.com/datadrivendiscovery/ta3ta2-api.git@0494c7088542c79c4d8eed0059d512bc08414e42#egg=ta3ta2-api +-e git+https://gitlab.com/datadrivendiscovery/ta3ta2-api.git@ef803f908edb1b41457eaed6079346b7b6317646#egg=ta3ta2-api diff --git a/scripts/evaluate_templates.sh b/scripts/evaluate_templates.sh new file mode 100755 index 0000000..84775cd --- /dev/null +++ b/scripts/evaluate_templates.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +docker build --build-arg UID=$UID -t mit-d3m-ta2 . + +COMMANDS=${*:-/bin/bash} +DATASETS=/home/pythia/Projects/d3m/datasets/seed_datasets_current/ + +docker run -i -t --rm -v $DATASETS:/input -v $(pwd):/home/user -w /home/user -u $UID mit-d3m-ta2 \ + python3 run_templates.py templates /input/LL1_terra_canopy_height_long_form_s4_90_MIN_METADATA diff --git a/scripts/generate_templates.py b/scripts/generate_templates.py new file mode 100644 index 0000000..36c2cb5 --- /dev/null +++ b/scripts/generate_templates.py @@ -0,0 +1,53 @@ +import os +import traceback +import sys + +import pandas as pd + +from d3m.metadata.pipeline import Pipeline + + +def load_pipeline(pipeline): + with open(pipeline) as _pipeline: + if pipeline.endswith('.json'): + pipeline = Pipeline.from_json(_pipeline) + else: + pipeline = Pipeline.from_yaml(_pipeline) + + pipeline.id = pipeline.get_digest() + + return pipeline + + +def generate_new_templates(path): + errors = [] + for pipeline in os.listdir(path): + pipeline_path = os.path.join(path, pipeline) + try: + pipeline = load_pipeline(pipeline_path) + new_path = os.path.join('templates', pipeline.id + '.json') + + with open(new_path, 'w') as pipeline_file: + pipeline.to_json(pipeline_file) + + print('OK:', pipeline.id) + + except Exception: + print('ERROR:', pipeline) + traceback.print_exc(file=sys.stdout) + errors.append(pipeline_path) + + if errors: + with open('errors.txt', 'w') as f: + for error in errors: + print(error, file=f) + + +if __name__ == '__main__': + + # Make all the d3m traces quiet + null = open(os.devnull, 'w') + sys.stderr = null + + path = sys.argv[1] + generate_new_templates(path) diff --git a/scripts/run_on_d3m.sh b/scripts/run_on_d3m.sh new file mode 100755 index 0000000..dc76218 --- /dev/null +++ b/scripts/run_on_d3m.sh @@ -0,0 +1,13 @@ +#!/bin/bash + +function echodo() { + echo $* + $* +} + +docker build --build-arg UID=$UID -t mit-d3m-ta2 . + +COMMANDS=${*:-/bin/bash} +DATASETS=/home/pythia/Projects/d3m/datasets/seed_datasets_current/ + +echodo docker run -i -t --rm -v $DATASETS:/input -v $(pwd):/home/user -w /home/user -u $UID mit-d3m-ta2 $COMMANDS diff --git a/scripts/run_templates.py b/scripts/run_templates.py new file mode 100644 index 0000000..066ffab --- /dev/null +++ b/scripts/run_templates.py @@ -0,0 +1,106 @@ +import argparse +import io +import json +import os +import sys +import tarfile +import urllib +from multiprocessing import Manager, Process + +import pandas as pd + +from d3m import index +from d3m.container.dataset import Dataset +from d3m.metadata.base import Context +from d3m.metadata.pipeline import Pipeline +from d3m.metadata.problem import parse_problem_description +from d3m.runtime import DEFAULT_SCORING_PIPELINE_PATH, Runtime, score + + +from ta2.__main__ import load_problem, score_pipeline + + +def detect_data_modality(doc_path): + with open(doc_path) as f: + dataset_doc = json.load(f) + + resources = list() + for resource in dataset_doc['dataResources']: + resources.append(resource['resType']) + + if len(resources) == 1: + return 'single_table' + else: + for res in resources: + if res == 'edgeList': + return 'graph' + elif res not in ('table', 'raw'): + return res + + return 'multi_table' + + +def run_pipeline(output, dataset_root, problem, pipeline_path, static=None): + score = score_pipeline(dataset_root, problem, pipeline_path, static) + output.append(score) + + +def test_pipelines(pipelines, dataset_root): + datasets_path, dataset_name = dataset_root.rsplit('/', 1) + # train_dataset = load_dataset(dataset_root, 'TRAIN') + # test_dataset = load_dataset(dataset_root, 'TEST') + problem = load_problem(dataset_root, 'TRAIN') + evaluated_pipelines = list() + + task_type = problem['problem']['task_keywords'][0].name.lower() + task_subtype = problem['problem']['task_keywords'][1].name.lower() + + path = os.path.join(dataset_root, 'TRAIN', 'dataset_' + 'TRAIN', 'datasetDoc.json') + data_modality = detect_data_modality(path) + + for pipeline in os.listdir(pipelines): + print(pipeline.rsplit('.', 1)[0] + ':', end=' ') + + pipeline_path = os.path.join(pipelines, pipeline) + try: + with Manager() as manager: + output = manager.list() + process = Process( + target=run_pipeline, + args=(output, dataset_root, problem, pipeline_path) + ) + process.daemon = True + process.start() + process.join(10) + process.terminate() + + if output: + print("success -", output[0]) + evaluated_pipelines.append({ + 'dataset_name': dataset_name, + 'template_id': pipeline, + 'problem_type': '{}_{}'.format(data_modality, task_type), + 'task_type': task_type, + 'task_subtype': task_subtype, + }) + + elif process.exitcode == -15: + print("timeout") + else: + print("error") + + except Exception as ex: + print("error") + + df = pd.DataFrame(evaluated_pipelines) + df.to_csv('{}_{}.csv'.format(data_modality, task_type), index=False) + + +if __name__ == '__main__': + + # Make all the d3m traces quiet + null = open(os.devnull, 'w') + sys.stderr = null + + pipelines, dataset = sys.argv[1:3] + test_pipelines(pipelines, dataset) diff --git a/setup.py b/setup.py index f8ebe77..e19e169 100644 --- a/setup.py +++ b/setup.py @@ -6,13 +6,13 @@ install_requires = [ 'baytune==0.3.5', - 'd3m==2019.11.10', 'tabulate>=0.8.3,<0.9', - 'numpy==1.17.3', - 'scikit-learn[alldeps]==0.21.3', - 'Cython==0.29.7', + 'd3m==2020.1.9', 'datamart-rest==0.2.3', - 'PyYAML==5.1.2', + # 'numpy==1.17.3', + # 'scikit-learn[alldeps]==0.21.3', + # 'Cython==0.29.7', + # 'PyYAML==5.1.2', ] diff --git a/ta2/__main__.py b/ta2/__main__.py index 89d0c51..d7ca598 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -2,7 +2,6 @@ import gc import logging import os -import shutil import socket import sys import traceback @@ -109,9 +108,15 @@ def box_print(message, strong=False): LOGGER.info(message) -def get_datasets(args): - for dataset_name in args.dataset: - dataset_root = os.path.join(args.input, dataset_name) +def get_datasets(input_dir, datasets=None, data_modality=None, task_type=None, task_subtype=None): + if not datasets: + datasets = os.listdir(input_dir) + + for dataset_name in datasets: + dataset_root = os.path.join(input_dir, dataset_name) + if not os.path.exists(dataset_root): + dataset_root += '_MIN_METADATA' + dataset_path = os.path.join(dataset_root, 'TRAIN', 'dataset_TRAIN', 'datasetDoc.json') try: @@ -120,11 +125,11 @@ def get_datasets(args): except Exception: continue - if args.data_modality and not args.data_modality == data_modality: + if data_modality and not data_modality == data_modality: continue - if args.task_type and not args.task_type == task_type: + if task_type and not task_type == task_type: continue - if args.task_subtype and not args.task_subtype == task_subtype: + if task_subtype and not task_subtype == task_subtype: continue yield dataset_name, dataset_root, problem @@ -186,17 +191,8 @@ def process_dataset(dataset_name, dataset_root, problem, args): def _ta2_test(args): - - # Cleanup output dir - shutil.rmtree(os.path.join(args.output, 'pipelines_ranked'), ignore_errors=True) - shutil.rmtree(os.path.join(args.output, 'pipelines_scored'), ignore_errors=True) - shutil.rmtree(os.path.join(args.output, 'pipelines_searched'), ignore_errors=True) - shutil.rmtree(os.path.join(args.output, 'predictions'), ignore_errors=True) - results = list() - if args.all: - args.dataset = os.listdir(args.input) - elif not args.dataset: + if not args.all and not args.dataset: print('ERROR: provide at least one dataset name or set --all') sys.exit(1) @@ -209,7 +205,9 @@ def _ta2_test(args): os.remove(report_name) report = None - for dataset_name, dataset_root, problem in get_datasets(args): + datasets = get_datasets(args.input, args.dataset, args.data_modality, + args.task_type, args.task_subtype) + for dataset_name, dataset_root, problem in datasets: try: results.append(process_dataset(dataset_name, dataset_root, problem, args)) gc.collect() @@ -230,7 +228,7 @@ def _ta2_test(args): report.to_csv(report_name, index=False) if report is None: - print("No matiching datasets found") + print("No matching datasets found") sys.exit(1) # print to stdout diff --git a/ta2/loader.py b/ta2/loader.py index 3bbdc72..f3901b2 100644 --- a/ta2/loader.py +++ b/ta2/loader.py @@ -7,6 +7,7 @@ from btb.tuning.hyperparams.boolean import BooleanHyperParam from btb.tuning.hyperparams.categorical import CategoricalHyperParam from btb.tuning.hyperparams.numerical import FloatHyperParam, IntHyperParam +from btb.tuning.tunable import Tunable from d3m.metadata.hyperparams import Bounded, Enumeration, Uniform, UniformBool, UniformInt from d3m.metadata.pipeline import Pipeline @@ -131,3 +132,23 @@ def load_pipeline(path, tunables=True, defaults=True): return pipeline, tunable_hyperparameters return pipeline + + +class LazyLoader(dict): + def __init__(self, keys, templates_dir): + super().__init__({key: None for key in keys}) + self._templates_dir = templates_dir + + def __getitem__(self, key): + value = super().__getitem__(key) + if value is not None: + return value + + path = os.path.join(self._templates_dir, key) + if not path.endswith('.json'): + path += '.json' + + template, tunable_hp = load_pipeline(path) + self[key] = template + + return Tunable(tunable_hp) diff --git a/ta2/new_templates/01717d30-57ea-43e5-9d4d-d457b124be43.json b/ta2/new_templates/01717d30-57ea-43e5-9d4d-d457b124be43.json deleted file mode 100644 index 214ebb1..0000000 --- a/ta2/new_templates/01717d30-57ea-43e5-9d4d-d457b124be43.json +++ /dev/null @@ -1 +0,0 @@ -{"id": 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-185_baseball,b64d6a22-c49d-4341-8871-af7f298f9653,F1_MACRO,0.3118138278595992,0.3118138278595992,single_table_classification,-1.1848517503871328 -26_radon_seed,693b7765-5708-433d-8b0c-0cc64ae33c46,ROOT_MEAN_SQUARED_ERROR,0.9992986742947989,1.4026516403705995,single_table_regression,0.19611613513818407 -LL0_1100_popularkids,b73b2670-5b50-4a69-a82d-6c9c9604775f,F1_MACRO,0.36334329101319396,0.36334329101319396,single_table_classification,0.11547876807053425 -LL1_net_nomination_seed,784d3b0b-bfe3-4346-8740-136dd23fb7dc,ACCURACY,0.8,0.8,graph_vertex_classification,0.0 diff --git a/ta2/search.py b/ta2/search.py index 626facc..d606701 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -1,4 +1,3 @@ -import glob import json import logging import os @@ -12,7 +11,6 @@ import numpy as np import pandas as pd from btb.session import BTBSession -from btb.tuning.tunable import Tunable from d3m.container.dataset import Dataset from d3m.metadata.base import ArgumentType, Context from d3m.metadata.pipeline import Pipeline, PrimitiveStep @@ -21,13 +19,12 @@ from datamart import DatamartQuery from datamart_rest import RESTDatamart -from ta2.loader import load_pipeline +from ta2.loader import LazyLoader from ta2.utils import dump_pipeline BASE_DIR = os.path.abspath(os.path.dirname(__file__)) PIPELINES_DIR = os.path.join(BASE_DIR, 'pipelines') -TEMPLATES_DIR = os.path.join(BASE_DIR, 'new_templates') -FALLBACK_PIPELINE = 'single_table_classification_fallback.json' +TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') DATAMART_URL = os.getenv('DATAMART_URL_NYU', 'https://datamart.d3m.vida-nyu.org') @@ -194,16 +191,17 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 # Some primitives crash with a core dump that kills everything. # We want to isolate those. - primitives = [ - step['primitive']['python_path'] - for step in pipeline.to_json_structure()['steps'] - ] - if any(primitive in SUBPROCESS_PRIMITIVES for primitive in primitives): - evaluate = self.subprocess_evaluate - else: - evaluate = d3m_evaluate - - all_scores, all_results = evaluate( + # This is disabled in favor of permanently using a child process + # primitives = [ + # step['primitive']['python_path'] + # for step in pipeline.to_json_structure()['steps'] + # ] + # if any(primitive in SUBPROCESS_PRIMITIVES for primitive in primitives): + # evaluate = self.subprocess_evaluate + # else: + # evaluate = d3m_evaluate + + all_scores, all_results = self.subprocess_evaluate( pipeline=pipeline, inputs=[dataset], data_pipeline=self.data_pipeline, @@ -304,10 +302,10 @@ def check_stop(self): def stop(self): self._stop = True - # if self.subprocess: - # LOGGER.info('Terminating subprocess: %s', self.subprocess.pid) - # self.subprocess.terminate() - # self.subprocess = None + if self.subprocess: + LOGGER.info('Terminating subprocess: %s', self.subprocess.pid) + self.subprocess.terminate() + self.subprocess = None def _timeout(self, *args, **kwargs): self.errors.append('STOP BY TIMEOUT') @@ -380,21 +378,6 @@ def btb_scorer(template_name, proposal): return btb_scorer - def _get_tunables_templates(self, template_names): - - tunables = {} - templates = {} - - for template_name in template_names: - name = os.path.join(TEMPLATES_DIR, template_name) - files = glob.glob(name + '*') - path = files[0] - template, tunable_hp = load_pipeline(path) - templates[template_name] = template - tunables[template_name] = Tunable(tunable_hp) - - return tunables, templates - def search(self, dataset_path, problem, timeout=None, budget=None, template_names=None): self.timeout = timeout self.timeout_kill = False @@ -421,11 +404,6 @@ def search(self, dataset_path, problem, timeout=None, budget=None, template_name task_type = problem['problem']['task_keywords'][0].name.lower() task_subtype = problem['problem']['task_keywords'][1].name.lower() - # self.fallback = load_pipeline( - # FALLBACK_PIPELINE, - # tunables=False - # ) - # data_augmentation = self.get_data_augmentation(dataset, problem) LOGGER.info("Searching dataset %s: %s/%s/%s", @@ -435,12 +413,14 @@ def search(self, dataset_path, problem, timeout=None, budget=None, template_name self.setup_search() LOGGER.info("Loading the template and the tuner") if not template_names: - template_names = self._get_templates(dataset_name, data_modality, task_type) + # template_names = self._get_templates(dataset_name, data_modality, task_type) + template_names = os.listdir(TEMPLATES_DIR) - tunables, templates = self._get_tunables_templates(template_names) - btb_scorer = self.make_btb_scorer(dataset_name, dataset, problem, templates, metric) + template_loader = LazyLoader(template_names, TEMPLATES_DIR) + btb_scorer = self.make_btb_scorer( + dataset_name, dataset, problem, template_loader, metric) - session = BTBSession(tunables, btb_scorer, max_errors=0) + session = BTBSession(template_loader, btb_scorer, max_errors=0) if self.budget is not None: while session.iterations < self.budget: diff --git a/ta2/templates/00f4093ea5e7ce2aa66961be0a0e8ce449257401f81dfa5b73b9b056dbf12762.json b/ta2/templates/00f4093ea5e7ce2aa66961be0a0e8ce449257401f81dfa5b73b9b056dbf12762.json new file mode 100644 index 0000000..cac4dff --- /dev/null +++ b/ta2/templates/00f4093ea5e7ce2aa66961be0a0e8ce449257401f81dfa5b73b9b056dbf12762.json @@ -0,0 +1 @@ +{"id": "00f4093ea5e7ce2aa66961be0a0e8ce449257401f81dfa5b73b9b056dbf12762", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-11-06T04:22:27.325146Z", "inputs": [{"name": "input dataset"}], "outputs": [{"data": "steps.17.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", "digest": "6c1cc604302d7418145f405efe5ae124755cab6da2b66cb53240b74e2b140a1e"}, "arguments": {"inputs": {"type": 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A & M University,Normal,AL,www.aamu.edu/,www2.aamu.edu/scripts/netpricecalc/npcalc.htm,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,380.0,470.0,370.0,470.0,370.0,457.0,425.0,420.0,414.0,16.0,19.0,14.0,20.0,15.0,18.0,,,18.0,17.0,17.0,,849.0,849.0,0.0448,0.0142,0.0071,0.0,0.0,0.0354,0.0401,0.0,0.1132,0.0896,0.0472,0.0,0.033,0.0,0.0094,0.066,0.0,0.0708,0.0024,0.0,0.0,0.0,0.0,0.0,0.0307,0.0,0.0472,0.0519,0.0377,0.0448,0.0,0.0,0.0,0.0,0.0283,0.0,0.1863,0.0,0.0,4616.0,0.0256,0.9129,0.0076,0.0019,0.0024,0.0017,0.0401,0.0065,0.0013,0.0877,1,15567.0,,15043.0,15491.0,17335.0,19562.0,18865.0,,,,,,0.7039,0.5774,,0.309,,0.7667,0.0859,31000,0.453,0.431,32750,348.16551225731,0.2531554273,,0.2913,Q39624632,Q17203888,Q173,Q575407\\\\\\\\n1,100663,105200,1052,University of Alabama at Birmingham,Birmingham,AL,www.uab.edu,uab.studentaidcalculator.com/survey.aspx,0,3,4,1,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,480.0,640.0,490.0,660.0,,,560.0,575.0,,21.0,28.0,22.0,30.0,19.0,26.0,,,25.0,26.0,23.0,,1125.0,1125.0,0.0,0.0,0.0,0.0005,0.036000000000000004,0.0,0.0131,0.0,0.0748,0.0599,0.0,0.0059,0.0,0.0,0.0158,0.0135,0.0,0.0734,0.009000000000000001,0.0,0.0,0.0,0.005,0.0,0.0212,0.0,0.0766,0.0243,0.0221,0.0365,0.0,0.0,0.0,0.0,0.0392,0.25,0.2072,0.0162,0.0,12047.0,0.5786,0.2626,0.0309,0.0598,0.0028,0.0004,0.0387,0.0179,0.0083,0.2578,1,16475.0,,13849.0,15385.0,18022.0,18705.0,19319.0,,,,,,0.3525,0.8007,,0.5178,,0.5179,0.2363,41200,0.669,0.631,21833,232.106797835537,0.513963161,,0.5384,Q39624677,Q17204336,Q173,Q79867\\\\\\\\n2,100690,2503400,25034,Amridge University,Montgomery,AL,www.amridgeuniversity.edu,www2.amridgeuniversity.edu:9091/,0,3,4,2,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,74.0,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0889,0.0,0.0,0.0889,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0667,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3556,0.0,1.0,293.0,0.157,0.2355,0.0068,0.0,0.0,0.0034,0.0,0.0,0.5973,0.5392,1,,10155.0,,,,,,10155.0,,,,,0.6971,PrivacySuppressed,,PrivacySuppressed,,0.8436,0.8571,39600,0.658,0.542,22890,243.343773299842,0.2307692308,,PrivacySuppressed,Q39624831,Q17337864,Q173,Q29364\\\\\\\\n3,100706,105500,1055,University of Alabama in Huntsville,Huntsville,AL,www.uah.edu,finaid.uah.edu/,0,3,4,1,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,520.0,660.0,540.0,680.0,,,590.0,610.0,,25.0,31.0,24.0,33.0,23.0,29.0,,,28.0,29.0,26.0,,1257.0,1257.0,0.0,0.0,0.0,0.0,0.0301,0.0,0.0499,0.0,0.0282,0.2702,0.0,0.0151,0.0,0.0,0.0122,0.0,0.0,0.0603,0.0132,0.0,0.0,0.0,0.0113,0.0,0.0226,0.0,0.016,0.0,0.0,0.0188,0.0,0.0,0.0,0.0,0.0264,0.1911,0.225,0.0094,0.0,6346.0,0.7148,0.1131,0.0411,0.0414,0.012,0.0,0.0181,0.0303,0.0292,0.1746,1,19423.0,,15971.0,18016.0,20300.0,21834.0,22059.0,,,,,,0.2949,0.8161,,0.5116,,0.4312,0.2255,46700,0.685,0.649,22647,240.760438353933,0.5485090298,,0.4905,Q39624901,Q17204354,Q173,Q79860\\\\\\\\n4,100724,100500,1005,Alabama State University,Montgomery,AL,www.alasu.edu,www.alasu.edu/cost-aid/forms/calculator/index.aspx,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,370.0,460.0,360.0,460.0,,,415.0,410.0,,15.0,19.0,14.0,19.0,15.0,17.0,,,17.0,17.0,16.0,,825.0,825.0,0.0,0.0,0.0,0.0,0.1023,0.0,0.0503,0.0,0.1364,0.0,0.0,0.0,0.0,0.0,0.0114,0.0,0.0,0.0779,0.0146,0.0,0.0,0.0211,0.0,0.0,0.0244,0.0,0.0503,0.1412,0.0633,0.013000000000000001,0.0,0.0,0.0,0.0,0.0487,0.1429,0.0974,0.0049,0.0,4704.0,0.0138,0.9337,0.0111,0.0028,0.0013,0.0004,0.0111,0.0159,0.01,0.0727,1,15037.0,,14111.0,15140.0,17492.0,19079.0,18902.0,,,,,,0.7815,0.6138,,0.5313,,0.8113,0.0974,27700,0.393,0.351,31500,334.876752247489,0.2185867473,,0.2475,Q39624974,Q17203904,Q173,Q29364\\\\\\\\n5,100751,105100,1051,The University of 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"5ae305c6b01aacdd82d4814981a000335049b613dc5e42a09591e01db5b5dfe3"} \ No newline at end of file From 0692b1fff7c3653c88825112ad4c2593c2ba8f95 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Wed, 5 Feb 2020 16:27:36 +0100 Subject: [PATCH 02/41] Update client version. --- ta2/ta3/client.py | 2 +- tests/ta3/test_client.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/ta2/ta3/client.py b/ta2/ta3/client.py index 01c1c57..0a01f32 100644 --- a/ta2/ta3/client.py +++ b/ta2/ta3/client.py @@ -53,7 +53,7 @@ def search_solutions(self, dataset, time_bound_search=1.): request = core_pb2.SearchSolutionsRequest( user_agent='ta3_api_test.py', - version='2019.12.4', + version='2020.1.28', time_bound_search=time_bound_search, priority=0., allowed_value_types=[ diff --git a/tests/ta3/test_client.py b/tests/ta3/test_client.py index b781111..c9ec0ea 100644 --- a/tests/ta3/test_client.py +++ b/tests/ta3/test_client.py @@ -54,7 +54,7 @@ def test_apiclient_search_solutions(search_solutions_request_mock, logger_mock): search_solutions_request_mock.assert_called_once_with( user_agent='ta3_api_test.py', - version='2019.12.4', + version='2020.1.28', time_bound_search=1., priority=0., allowed_value_types=[ From b8ca5a5a9c566a986faf64b7b1029e8bc7d5483a Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 6 Feb 2020 07:21:19 +0100 Subject: [PATCH 03/41] Make devel executions faster --- run_docker.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/run_docker.sh b/run_docker.sh index 6cf5eb9..79c3e20 100755 --- a/run_docker.sh +++ b/run_docker.sh @@ -1,6 +1,6 @@ #!/bin/bash -docker build --build-arg UID=$UID -t mit-d3m-ta2 . +# docker build --build-arg UID=$UID -t mit-d3m-ta2 . # if [ -n "$*" ]; then # COMMAND="ta2 $*" @@ -10,7 +10,6 @@ rm -r output mkdir -p output chown $USER output - function echodo() { echo $* $* @@ -22,6 +21,7 @@ echodo docker run -i -t --rm \ -e D3MINPUTDIR=/input \ -e D3MOUTPUTDIR=/output \ -e D3MSTATICDIR=/static \ + -v $(pwd)/ta2:/user_dev/ta2 \ -v $(pwd)/input:/input \ -v $(pwd)/output:/output \ -v $(pwd)/static:/static \ From 965e02cc108d787aba6dcec7b8700e94b2225af5 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 6 Feb 2020 07:22:13 +0100 Subject: [PATCH 04/41] Change the way datasets are loaded in test and fix bug in core_servicer --- ta2/__main__.py | 139 ++++++++++++++++++++++++--------------- ta2/search.py | 13 ++-- ta2/ta3/core_servicer.py | 7 +- 3 files changed, 96 insertions(+), 63 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index d7ca598..fa42a1e 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -7,6 +7,7 @@ import traceback from datetime import datetime +import numpy as np import pandas as pd import tabulate from d3m.container.dataset import Dataset @@ -30,12 +31,12 @@ def load_dataset(root_path, phase, inner_phase=None): return Dataset.load(dataset_uri='file://' + os.path.abspath(path)) else: path = os.path.join(root_path, phase, 'dataset_' + phase, 'datasetDoc.json') - return Dataset.load(dataset_uri='file://' + os.path.abspath(path)) + return Dataset.load(dataset_uri=path) def load_problem(root_path, phase): path = os.path.join(root_path, phase, 'problem_' + phase, 'problemDoc.json') - return Problem.load(problem_uri='file://' + os.path.abspath(path)) + return Problem.load(problem_uri=path) def load_pipeline(pipeline_path): @@ -46,24 +47,7 @@ def load_pipeline(pipeline_path): return Pipeline.from_yaml(pipeline_file) -def search(dataset_root, problem, args): - pps = PipelineSearcher( - args.input, - args.output, - args.static, - dump=True, - hard_timeout=args.hard, - ignore_errors=args.ignore_errors, - ) - dataset_root = os.path.abspath(dataset_root) - dataset_path = 'file://{}/TRAIN/dataset_TRAIN/datasetDoc.json'.format(dataset_root) - - return pps.search(dataset_path, problem, args.timeout, args.budget, args.template) - - -def score_pipeline(dataset_root, problem, pipeline_path, static=None): - train_dataset = load_dataset(dataset_root, 'TRAIN') - test_dataset = load_dataset(dataset_root, 'SCORE', 'TEST') +def score_pipeline(dataset, problem, pipeline_path, static=None): pipeline = load_pipeline(pipeline_path) # Creating an instance on runtime with pipeline description and problem description. @@ -75,9 +59,13 @@ def score_pipeline(dataset_root, problem, pipeline_path, static=None): ) LOGGER.info("Fitting the pipeline") - fit_results = runtime.fit(inputs=[train_dataset]) + fit_results = runtime.fit(inputs=[dataset]) fit_results.check_success() + dataset_doc_path = dataset.metadata.query(())['location_uris'][0] + dataset_root = dataset_doc_path[:-len('/TRAIN/dataset_TRAIN/datasetDoc.json')] + test_dataset = load_dataset(dataset_root, 'SCORE', 'TEST') + # Producing results using the fitted pipeline. LOGGER.info("Producing predictions") produce_results = runtime.produce(inputs=[test_dataset]) @@ -117,11 +105,12 @@ def get_datasets(input_dir, datasets=None, data_modality=None, task_type=None, t if not os.path.exists(dataset_root): dataset_root += '_MIN_METADATA' - dataset_path = os.path.join(dataset_root, 'TRAIN', 'dataset_TRAIN', 'datasetDoc.json') + dataset_root = 'file://' + os.path.abspath(dataset_root) try: + dataset = load_dataset(dataset_root, 'TRAIN') problem = load_problem(dataset_root, 'TRAIN') - data_modality, task_type, task_subtype = get_dataset_details(dataset_path, problem) + data_modality, task_type, task_subtype = get_dataset_details(dataset, problem) except Exception: continue @@ -132,16 +121,40 @@ def get_datasets(input_dir, datasets=None, data_modality=None, task_type=None, t if task_subtype and not task_subtype == task_subtype: continue - yield dataset_name, dataset_root, problem + yield dataset_name, dataset, problem -def process_dataset(dataset_name, dataset_root, problem, args): - start_ts = datetime.utcnow() +def _append_report(result, path): + report = pd.DataFrame( + [result], + columns=REPORT_COLUMNS + ) + report['host'] = socket.gethostname() + report['timestamp'] = datetime.utcnow() + report.to_csv(path, mode='a', header=False, index=False) + + return report + + +def process_dataset(dataset_name, dataset, problem, args): box_print("Processing dataset {}".format(dataset_name), True) + output_path = os.path.join(args.output, dataset_name) + os.makedirs(output_path, exist_ok=True) + LOGGER.info("Searching Pipeline for dataset {}".format(dataset_name)) try: - result = search(dataset_root, problem, args) + start_ts = datetime.utcnow() + pps = PipelineSearcher( + args.input, + output_path, + args.static, + dump=True, + hard_timeout=args.hard, + ignore_errors=args.ignore_errors, + ) + result = pps.search(dataset, problem, args.timeout, args.budget, args.template) + result['elapsed_time'] = datetime.utcnow() - start_ts result['dataset'] = dataset_name @@ -150,15 +163,14 @@ def process_dataset(dataset_name, dataset_root, problem, args): if cv_score is not None: box_print("Best Pipeline: {} - CV Score: {}".format(pipeline_id, cv_score)) - pipeline_path = os.path.join(args.output, 'pipelines_ranked', pipeline_id + '.json') - test_score = score_pipeline(dataset_root, problem, pipeline_path, args.static) + pipeline_path = os.path.join(output_path, 'pipelines_ranked', pipeline_id + '.json') + test_score = score_pipeline(dataset, problem, pipeline_path, args.static) box_print("Test Score for pipeline {}: {}".format(pipeline_id, test_score)) result['test_score'] = test_score - return result except Exception: - return { + result = { 'dataset': dataset_name, 'pipeline': None, 'cv_score': None, @@ -175,6 +187,8 @@ def process_dataset(dataset_name, dataset_root, problem, args): 'elapsed_time': None } + return result + REPORT_COLUMNS = [ 'dataset', @@ -191,7 +205,6 @@ def process_dataset(dataset_name, dataset_root, problem, args): def _ta2_test(args): - results = list() if not args.all and not args.dataset: print('ERROR: provide at least one dataset name or set --all') sys.exit(1) @@ -201,33 +214,31 @@ def _ta2_test(args): else: report_name = os.path.join(args.output, 'results.csv') - if os.path.exists(report_name): - os.remove(report_name) + report = pd.DataFrame(columns=REPORT_COLUMNS) + if not os.path.exists(report_name): + report.to_csv(report_name, index=False) - report = None datasets = get_datasets(args.input, args.dataset, args.data_modality, args.task_type, args.task_subtype) - for dataset_name, dataset_root, problem in datasets: + for dataset_name, dataset, problem in datasets: try: - results.append(process_dataset(dataset_name, dataset_root, problem, args)) + result = process_dataset(dataset_name, dataset, problem, args) gc.collect() except Exception as ex: box_print("Error processing dataset {}".format(dataset_name), True) traceback.print_exc() - results.append({ + result = { 'dataset': dataset_name, 'error': '{}: {}'.format(type(ex).__name__, ex) - }) - - report = pd.DataFrame( - results, - columns=REPORT_COLUMNS - ).sort_values('dataset') - report['host'] = socket.gethostname() + } - report.to_csv(report_name, index=False) + report = report.append( + _append_report(result, report_name), + sort=False, + ignore_index=True + ) - if report is None: + if report.empty: print("No matching datasets found") sys.exit(1) @@ -262,7 +273,7 @@ def _ta3_test_dataset(client, dataset, timeout): request_id = score_response.request_id print('### {} => client.GetScoreSolutionsResults("{}")'.format(dataset, request_id)) - client.get_score_solution_results(request_id) + score_solution_results = client.get_score_solution_results(request_id) print('### {} => client.FitSolution("{}")'.format(dataset, solution_id)) fit_response = client.fit_solution(solution_id, dataset) @@ -285,6 +296,11 @@ def _ta3_test_dataset(client, dataset, timeout): print('### {} => client.EndSearchSolutions("{}")'.format(dataset, search_id)) client.end_search_solutions(search_id) + return np.mean([ + score.value.raw.double + for score in score_solution_results.scores + ]) + def _ta3_test(args): local_input = args.input @@ -297,12 +313,29 @@ def _ta3_test(args): if args.all: args.dataset = os.listdir(args.input) + results = list() for dataset in args.dataset: try: - _ta3_test_dataset(client, dataset, args.timeout / 60) + score = _ta3_test_dataset(client, dataset, args.timeout / 60) + results.append({ + 'dataset': dataset, + 'score': score + }) except Exception as e: + results.append({ + 'dataset': dataset, + 'score': 'ERROR' + }) print('An error occurred trying to process the dataset {}, produced by {}'.format(dataset, e)) + results = pd.DataFrame(results) + print(tabulate.tabulate( + results[['dataset', 'score']], + showindex=False, + tablefmt='github', + headers=['dataset', 'score'] + )) + def _server(args): input_dir = args.input or os.getenv('D3MINPUTDIR', 'input') @@ -420,10 +453,10 @@ def parse_args(): if not os.path.exists(args.output): os.makedirs(args.output, exist_ok=True) - if args.mode is _ta2_test and not args.logfile: - args.logfile = os.path.join(args.output, 'ta2.log') - if os.path.exists(args.logfile): - os.remove(args.logfile) + # if args.mode is _ta2_test and not args.logfile: + # args.logfile = os.path.join(args.output, 'ta2.log') + # if os.path.exists(args.logfile): + # os.remove(args.logfile) logging_setup(args.verbose, args.logfile, stdout=args.stdout) logging.getLogger("d3m").setLevel(logging.ERROR) diff --git a/ta2/search.py b/ta2/search.py index d606701..44f0dae 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -11,7 +11,6 @@ import numpy as np import pandas as pd from btb.session import BTBSession -from d3m.container.dataset import Dataset from d3m.metadata.base import ArgumentType, Context from d3m.metadata.pipeline import Pipeline, PrimitiveStep from d3m.runtime import DEFAULT_SCORING_PIPELINE_PATH @@ -39,8 +38,9 @@ warnings.filterwarnings("ignore", category=DeprecationWarning) -def detect_data_modality(dataset_doc_path): - with open(dataset_doc_path) as f: +def detect_data_modality(dataset): + dataset_doc_path = dataset.metadata.query(())['location_uris'][0] + with open(dataset_doc_path[7:]) as f: dataset_doc = json.load(f) resources = list() @@ -378,7 +378,7 @@ def btb_scorer(template_name, proposal): return btb_scorer - def search(self, dataset_path, problem, timeout=None, budget=None, template_names=None): + def search(self, dataset, problem, timeout=None, budget=None, template_names=None): self.timeout = timeout self.timeout_kill = False self.budget = budget @@ -397,12 +397,9 @@ def search(self, dataset_path, problem, timeout=None, budget=None, template_name if dataset_name.endswith('_dataset'): dataset_name = dataset_name[:-len('_dataset')] - dataset = Dataset.load(dataset_path) metric = problem['problem']['performance_metrics'][0]['metric'] - data_modality = detect_data_modality(dataset_path[7:]) - task_type = problem['problem']['task_keywords'][0].name.lower() - task_subtype = problem['problem']['task_keywords'][1].name.lower() + data_modality, task_type, task_subtype = get_dataset_details(dataset, problem) # data_augmentation = self.get_data_augmentation(dataset, problem) diff --git a/ta2/ta3/core_servicer.py b/ta2/ta3/core_servicer.py index 16ff2aa..a271bec 100644 --- a/ta2/ta3/core_servicer.py +++ b/ta2/ta3/core_servicer.py @@ -16,6 +16,7 @@ from d3m.runtime import Runtime from google.protobuf.timestamp_pb2 import Timestamp from ta3ta2_api import core_pb2, core_pb2_grpc, pipeline_pb2, primitive_pb2, problem_pb2, value_pb2 +from ta3ta2_api.utils import ValueType as D3MValueType from ta3ta2_api.utils import decode_performance_metric, decode_problem_description, encode_score from ta2.search import PipelineSearcher @@ -827,7 +828,7 @@ def SearchSolutions(self, request, context): time_bound_search = request.time_bound_search problem_description = request.problem inputs = request.inputs - allowed_value_types = request.allowed_value_types + allowed_value_types = [D3MValueType(value) for value in request.allowed_value_types] # Ignored: # user_agent = request.user_agent @@ -851,12 +852,13 @@ def SearchSolutions(self, request, context): searcher = PipelineSearcher(self.input_dir, self.output_dir, self.static_dir) dataset_doc = inputs[0].dataset_uri + dataset = Dataset.load(dataset_doc) self._start_session( search_id, 'search', searcher.search, - dataset_doc, + dataset, problem, timeout, searcher=searcher, @@ -1195,6 +1197,7 @@ def _score_solution(self, searcher, dataset, problem, metric_pipelines, configur metric = decode_performance_metric(metric) searcher.score_pipeline(dataset, problem, pipeline, [metric], **cv_args) + LOGGER.info('Pipeline %s obtained score %s', pipeline.id, pipeline.score) def ScoreSolution(self, request, context): LOGGER.info("\n######## ScoreSolution ########\n%s########", request) From abe7e9df6ab41546753b6abef9aa794a6667a3f5 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Mon, 10 Feb 2020 07:39:45 +0100 Subject: [PATCH 05/41] Ensure log dir exists --- ta2/__main__.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index fa42a1e..1398d57 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -453,10 +453,9 @@ def parse_args(): if not os.path.exists(args.output): os.makedirs(args.output, exist_ok=True) - # if args.mode is _ta2_test and not args.logfile: - # args.logfile = os.path.join(args.output, 'ta2.log') - # if os.path.exists(args.logfile): - # os.remove(args.logfile) + if args.logfile: + logdir = os.path.dirname(args.logfile) + os.makedirs(logdir, exist_ok=True) logging_setup(args.verbose, args.logfile, stdout=args.stdout) logging.getLogger("d3m").setLevel(logging.ERROR) From a292740827949d8cf4b4d7616ca9b2183537880e Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Tue, 11 Feb 2020 01:12:30 +0100 Subject: [PATCH 06/41] Generate pipeline_runs and provide more information on reporting. --- ta2/__main__.py | 25 +++++++++++++++++++++---- ta2/search.py | 12 +++++++++++- 2 files changed, 32 insertions(+), 5 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index 1398d57..9db6a98 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -47,14 +47,21 @@ def load_pipeline(pipeline_path): return Pipeline.from_yaml(pipeline_file) -def score_pipeline(dataset, problem, pipeline_path, static=None): +def _to_yaml_run(pipeline_run, output_path): + run_dir = os.path.join(output_path, 'pipeline_runs') + run_dir = os.path.join(run_dir, '{}.yml'.format(pipeline_run.get_id())) + with open(run_dir, 'w') as output_file: + pipeline_run.to_yaml(file=output_file) + + +def score_pipeline(dataset, problem, pipeline_path, static=None, output_path=None): pipeline = load_pipeline(pipeline_path) # Creating an instance on runtime with pipeline description and problem description. runtime = Runtime( pipeline=pipeline, problem_description=problem, - context=Context.TESTING, + context=Context.EVALUATION, volumes_dir=static, ) @@ -82,9 +89,17 @@ def score_pipeline(dataset, problem, pipeline_path, static=None): predictions=predictions, score_inputs=[test_dataset], metrics=metrics, - context=Context.TESTING, + context=Context.EVALUATION, random_seed=0, ) + + evaluated_pipeline_run = produce_results.pipeline_run + evaluated_pipeline_run.is_standard_pipeline = True + evaluated_pipeline_run.set_scores(scores, metrics) + evaluated_pipeline_run.set_scoring_pipeline_run(scoring_pipeline_run.pipeline_run, [dataset]) + + _to_yaml_run(evaluated_pipeline_run, output_path) + return scores.iloc[0].value @@ -164,7 +179,7 @@ def process_dataset(dataset_name, dataset, problem, args): box_print("Best Pipeline: {} - CV Score: {}".format(pipeline_id, cv_score)) pipeline_path = os.path.join(output_path, 'pipelines_ranked', pipeline_id + '.json') - test_score = score_pipeline(dataset, problem, pipeline_path, args.static) + test_score = score_pipeline(dataset, problem, pipeline_path, args.static, output_path) box_print("Test Score for pipeline {}: {}".format(pipeline_id, test_score)) result['test_score'] = test_score @@ -199,6 +214,8 @@ def process_dataset(dataset_name, dataset, problem, args): 'tuning_iterations', 'data_modality', 'task_type', + 'pipelines_scheduled', + 'pipelines_tried', 'error', 'killed_by_timeout', ] diff --git a/ta2/search.py b/ta2/search.py index 44f0dae..5708aa7 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -131,9 +131,11 @@ def __init__(self, input_dir='input', output_dir='output', static_dir='static', self.hard_timeout = hard_timeout self.subprocess = None + self.runs_dir = os.path.join(self.output, 'pipeline_runs') self.ranked_dir = os.path.join(self.output, 'pipelines_ranked') self.scored_dir = os.path.join(self.output, 'pipelines_scored') self.searched_dir = os.path.join(self.output, 'pipelines_searched') + os.makedirs(self.runs_dir, exist_ok=True) os.makedirs(self.ranked_dir, exist_ok=True) os.makedirs(self.scored_dir, exist_ok=True) os.makedirs(self.searched_dir, exist_ok=True) @@ -226,6 +228,13 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 else: raise Exception(cause) + for res in all_results: + pipeline_run = res.pipeline_run + if pipeline_run.run.get('phase') == 'PRODUCE': + yaml_file = os.path.join(self.runs_dir, '{}.yml'.format(pipeline_run.get_id())) + with open(yaml_file, 'w') as pip: + pipeline_run.to_yaml(file=pip) + pipeline.cv_scores = [score.value[0] for score in all_scores] pipeline.score = np.mean(pipeline.cv_scores) @@ -451,6 +460,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non 'tuning_iterations': session.iterations if session else None, 'error': self.errors or None, 'killed_by_timeout': self.timeout_kill, - 'pipelines_scheduled': template_names, + 'pipelines_scheduled': len(template_names), + 'pipelines_tried': len([x for x in template_loader.values() if x is not None]), 'found_by_name': self.found_by_name } From aab9504afd60335f374f05a432fe0f378222b18e Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Wed, 12 Feb 2020 03:52:01 +0100 Subject: [PATCH 07/41] Improve report information --- run_docker.sh | 2 +- ta2/__main__.py | 56 ++++++++++++++++------------- ta2/search.py | 96 +++++++++++++++++++++++++++++++------------------ 3 files changed, 94 insertions(+), 60 deletions(-) diff --git a/run_docker.sh b/run_docker.sh index 79c3e20..65f5c54 100755 --- a/run_docker.sh +++ b/run_docker.sh @@ -1,6 +1,6 @@ #!/bin/bash -# docker build --build-arg UID=$UID -t mit-d3m-ta2 . +docker build --build-arg UID=$UID -t mit-d3m-ta2 . # if [ -n "$*" ]; then # COMMAND="ta2 $*" diff --git a/ta2/__main__.py b/ta2/__main__.py index 9db6a98..fb9e1ec 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -144,6 +144,9 @@ def _append_report(result, path): [result], columns=REPORT_COLUMNS ) + + report['dataset'] = report['dataset'].str.replace('_MIN_METADATA', '') + report['template'] = report['template'].str[0:12] report['host'] = socket.gethostname() report['timestamp'] = datetime.utcnow() report.to_csv(path, mode='a', header=False, index=False) @@ -167,10 +170,13 @@ def process_dataset(dataset_name, dataset, problem, args): dump=True, hard_timeout=args.hard, ignore_errors=args.ignore_errors, + cv_folds=args.folds, + subprocess_timeout=args.subprocess_timeout, + max_errors=args.max_errors ) result = pps.search(dataset, problem, args.timeout, args.budget, args.template) - result['elapsed_time'] = datetime.utcnow() - start_ts + result['elapsed'] = datetime.utcnow() - start_ts result['dataset'] = dataset_name pipeline_id = result['pipeline'] @@ -184,22 +190,10 @@ def process_dataset(dataset_name, dataset, problem, args): result['test_score'] = test_score - except Exception: + except Exception as ex: result = { 'dataset': dataset_name, - 'pipeline': None, - 'cv_score': None, - 'template': None, - 'data_modality': None, - 'task_type': None, - 'task_subtype': None, - 'tuning_iterations': None, - 'error': 'error from main', - 'killed_by_timeout': None, - 'pipelines_scheduled': None, - 'found_by_name': None, - 'test_score': None, - 'elapsed_time': None + 'error': '{}: {}'.format(type(ex).__name__, ex), } return result @@ -210,14 +204,17 @@ def process_dataset(dataset_name, dataset, problem, args): 'template', 'cv_score', 'test_score', - 'elapsed_time', - 'tuning_iterations', - 'data_modality', - 'task_type', - 'pipelines_scheduled', - 'pipelines_tried', - 'error', - 'killed_by_timeout', + 'elapsed', + 'scheduled', + 'iterations', + 'scored', + 'errored', + 'invalid', + 'timeouts', + 'timeout', + 'modality', + 'type', + 'subtype', ] @@ -338,12 +335,12 @@ def _ta3_test(args): 'dataset': dataset, 'score': score }) - except Exception as e: + except Exception as ex: results.append({ 'dataset': dataset, 'score': 'ERROR' }) - print('An error occurred trying to process the dataset {}, produced by {}'.format(dataset, e)) + print('TA3 Error on dataset {}: {}'.format(dataset, ex)) results = pd.DataFrame(results) print(tabulate.tabulate( @@ -438,6 +435,15 @@ def parse_args(): ta2_parser.add_argument( '-e', '--template', action='append', help='Name of the template to Use.') + ta2_parser.add_argument( + '-f', '--folds', type=int, + help='Number of folds to use for cross validation') + ta2_parser.add_argument( + '-p', '--subprocess-timeout', type=int, + help='Maximum time allowed per pipeline execution, in seconds') + ta2_parser.add_argument( + '-m', '--max-errors', type=int, default=0, + help='Maximum amount of errors per template.') # TA3 Mode ta3_parents = [logging_args, io_args, search_args, ta3_args, dataset_args] diff --git a/ta2/search.py b/ta2/search.py index 5708aa7..b9e9b3b 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -123,7 +123,8 @@ def _get_templates(self, dataset_name, data_modality, task_type): return templates.pipeline_id.values def __init__(self, input_dir='input', output_dir='output', static_dir='static', - dump=False, hard_timeout=False, ignore_errors=False): + dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, + subprocess_timeout=None, max_errors=0): self.input = input_dir self.output = output_dir self.static = static_dir @@ -144,6 +145,9 @@ def __init__(self, input_dir='input', output_dir='output', static_dir='static', self.data_pipeline = self._load_pipeline('kfold_pipeline.yml') self.scoring_pipeline = self._load_pipeline(DEFAULT_SCORING_PIPELINE_PATH) self.ignore_errors = ignore_errors + self.folds = cv_folds + self.subprocess_timeout = subprocess_timeout + self.max_errors = max_errors @staticmethod def _evaluate(out, pipeline, *args, **kwargs): @@ -154,7 +158,6 @@ def _evaluate(out, pipeline, *args, **kwargs): out.extend(results) def subprocess_evaluate(self, pipeline, *args, **kwargs): - LOGGER.info('Evaluating pipeline %s in a subprocess', pipeline.id) with Manager() as manager: output = manager.list() process = Process( @@ -167,22 +170,26 @@ def subprocess_evaluate(self, pipeline, *args, **kwargs): process.start() LOGGER.info('Joining process %s', process.pid) - process.join() + process.join(self.subprocess_timeout) - LOGGER.info('Terminating process %s', process.pid) - process.terminate() self.subprocess = None + if process.is_alive(): + self._subprocess_timeouts += 1 + process.terminate() + raise Exception('Timeout reached for subprocess {}'.format(process.pid)) + result = tuple(output) if output else None if not result: - raise Exception("Evaluate crashed") + raise Exception("Subprocess evaluate crashed") return result def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0, - folds=5, stratified=False, shuffle=False): + folds=None, stratified=False, shuffle=False): + folds = folds or self.folds problem_metrics = problem['problem']['performance_metrics'] metrics = metrics or problem_metrics data_params = { @@ -218,7 +225,15 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 volumes_dir=self.static, ) + for res in all_results: + pipeline_run = res.pipeline_run + if pipeline_run.run.get('phase') == 'PRODUCE': + yaml_file = os.path.join(self.runs_dir, '{}.yml'.format(pipeline_run.get_id())) + with open(yaml_file, 'w') as pip: + pipeline_run.to_yaml(file=pip) + if not all_scores: + self.error += 1 failed_result = all_results[-1] message = failed_result.pipeline_run.status['message'] LOGGER.error(message) @@ -226,14 +241,7 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 if isinstance(cause, BaseException): raise cause else: - raise Exception(cause) - - for res in all_results: - pipeline_run = res.pipeline_run - if pipeline_run.run.get('phase') == 'PRODUCE': - yaml_file = os.path.join(self.runs_dir, '{}.yml'.format(pipeline_run.get_id())) - with open(yaml_file, 'w') as pip: - pipeline_run.to_yaml(file=pip) + raise failed_result.error pipeline.cv_scores = [score.value[0] for score in all_scores] pipeline.score = np.mean(pipeline.cv_scores) @@ -317,8 +325,7 @@ def stop(self): self.subprocess = None def _timeout(self, *args, **kwargs): - self.errors.append('STOP BY TIMEOUT') - self.timeout_kill = True + self._timeout_reached = True raise KeyboardInterrupt() def setup_search(self): @@ -365,8 +372,17 @@ def get_data_augmentation(self, dataset, problem): def make_btb_scorer(self, dataset_name, dataset, problem, templates, metric): def btb_scorer(template_name, proposal): self.check_stop() + self.iterations += 1 - pipeline = self._new_pipeline(templates[template_name], proposal) + + try: + LOGGER.info('Scoring template %s', template_name) + pipeline = self._new_pipeline(templates[template_name], proposal) + except Exception: + LOGGER.exception('Error creating pipeline from template %s with params %s', + template_name, proposal) + self.invalid += 1 + raise try: self.score_pipeline(dataset, problem, pipeline) @@ -377,11 +393,15 @@ def btb_scorer(template_name, proposal): self.best_pipeline = pipeline.id self.best_template_name = template_name + LOGGER.warning('Template %s score: %s - %s', template_name, + pipeline.score, pipeline.normalized_score) + self.success += 1 return pipeline.normalized_score finally: try: self._save_pipeline(pipeline) + except Exception: LOGGER.exception('Error saving pipeline %s', pipeline.id) @@ -389,7 +409,8 @@ def btb_scorer(template_name, proposal): def search(self, dataset, problem, timeout=None, budget=None, template_names=None): self.timeout = timeout - self.timeout_kill = False + self._timeout_reached = False + self._subprocess_timeouts = 0 self.budget = budget self.best_pipeline = None self.best_score = None @@ -400,7 +421,10 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non data_modality = None task_type = None task_subtype = None - self.errors = list() + self.iterations = 0 + self.error = 0 + self.invalid = 0 + self.success = 0 dataset_name = problem['inputs'][0]['dataset_id'] if dataset_name.endswith('_dataset'): @@ -426,15 +450,17 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non btb_scorer = self.make_btb_scorer( dataset_name, dataset, problem, template_loader, metric) - session = BTBSession(template_loader, btb_scorer, max_errors=0) + session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) if self.budget is not None: - while session.iterations < self.budget: + spent = 0 + while spent < self.budget: session.run(1) last_score = list(session.proposals.values())[-1].get('score') - if self.ignore_errors and (last_score is None): - LOGGER.warning("Ignoring Errored pipeline") - session.iterations -= 1 + if (last_score is None) and self.ignore_errors: + LOGGER.warning("Ignoring errored pipeline") + else: + spent += 1 else: session.run() @@ -454,13 +480,15 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non 'pipeline': self.best_pipeline, 'cv_score': self.best_score, 'template': self.best_template_name, - 'data_modality': data_modality, - 'task_type': task_type, - 'task_subtype': task_subtype, - 'tuning_iterations': session.iterations if session else None, - 'error': self.errors or None, - 'killed_by_timeout': self.timeout_kill, - 'pipelines_scheduled': len(template_names), - 'pipelines_tried': len([x for x in template_loader.values() if x is not None]), - 'found_by_name': self.found_by_name + 'modality': data_modality, + 'type': task_type, + 'subtype': task_subtype, + 'iterations': self.iterations, + 'timeout': self._timeout_reached, + 'timeouts': self._subprocess_timeouts, + 'scheduled': len(template_names), + 'scored': self.success, + 'errored': self.error, + 'invalid': self.invalid, + 'found': self.found_by_name } From a084f42a0fec6c6ab8f92d79b187bdfdcaf302ac Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Wed, 12 Feb 2020 03:54:44 +0100 Subject: [PATCH 08/41] Fix lint --- ta2/search.py | 1 - 1 file changed, 1 deletion(-) diff --git a/ta2/search.py b/ta2/search.py index b9e9b3b..61fb8d9 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -374,7 +374,6 @@ def btb_scorer(template_name, proposal): self.check_stop() self.iterations += 1 - try: LOGGER.info('Scoring template %s', template_name) pipeline = self._new_pipeline(templates[template_name], proposal) From 11e53feadfa6290128f9b0bf5f09c2ca4ce4deb6 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Wed, 12 Feb 2020 04:10:16 +0100 Subject: [PATCH 09/41] Use btb release candidate --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index e19e169..f2b7aa7 100644 --- a/setup.py +++ b/setup.py @@ -5,7 +5,7 @@ install_requires = [ - 'baytune==0.3.5', + 'baytune>=0.3.6.dev0', 'tabulate>=0.8.3,<0.9', 'd3m==2020.1.9', 'datamart-rest==0.2.3', From e767453c2a1417e5d47c589fe40e779a20cd37b6 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Wed, 12 Feb 2020 08:10:31 +0100 Subject: [PATCH 10/41] Use the development version of btb --- requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements.txt b/requirements.txt index 7cbcf38..074a0e7 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1 +1,2 @@ -e git+https://gitlab.com/datadrivendiscovery/ta3ta2-api.git@ef803f908edb1b41457eaed6079346b7b6317646#egg=ta3ta2-api +-e git+https://github.com/HDI-Project/BTB.git@6a08dc3cf1b68b35630cae6a87783aec4e2c9f83#egg=baytune From 37c1ccf8ca6b97afad243fd49e23a10dc91db256 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Wed, 12 Feb 2020 17:34:15 +0100 Subject: [PATCH 11/41] Update default fold values. --- ta2/__main__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index fb9e1ec..25c29a1 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -436,7 +436,7 @@ def parse_args(): '-e', '--template', action='append', help='Name of the template to Use.') ta2_parser.add_argument( - '-f', '--folds', type=int, + '-f', '--folds', type=int, default=5, help='Number of folds to use for cross validation') ta2_parser.add_argument( '-p', '--subprocess-timeout', type=int, From 0549808409a3d49c92bb85a773d51f4803c46132 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 13 Feb 2020 06:40:26 +0100 Subject: [PATCH 12/41] add fields to report --- ta2/__main__.py | 5 ++++- ta2/search.py | 5 +++-- 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index 25c29a1..2db3d29 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -204,8 +204,9 @@ def process_dataset(dataset_name, dataset, problem, args): 'template', 'cv_score', 'test_score', + 'metric', 'elapsed', - 'scheduled', + 'templates', 'iterations', 'scored', 'errored', @@ -215,6 +216,8 @@ def process_dataset(dataset_name, dataset, problem, args): 'modality', 'type', 'subtype', + 'host', + 'timestamp' ] diff --git a/ta2/search.py b/ta2/search.py index 61fb8d9..fbe1051 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -485,9 +485,10 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non 'iterations': self.iterations, 'timeout': self._timeout_reached, 'timeouts': self._subprocess_timeouts, - 'scheduled': len(template_names), + 'templates': len(template_names), 'scored': self.success, 'errored': self.error, 'invalid': self.invalid, - 'found': self.found_by_name + 'found': self.found_by_name, + 'metric': metric.name.lower() } From 8b4448231673c25c0988850f63ec83cd8018bcea Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 13 Feb 2020 07:27:54 +0100 Subject: [PATCH 13/41] new generate templates scripts --- scripts/generate_templates.py | 91 ++++++++++++++++++++++++----------- 1 file changed, 63 insertions(+), 28 deletions(-) diff --git a/scripts/generate_templates.py b/scripts/generate_templates.py index 36c2cb5..d20ef4a 100644 --- a/scripts/generate_templates.py +++ b/scripts/generate_templates.py @@ -1,11 +1,13 @@ +import argparse import os -import traceback import sys - -import pandas as pd +import traceback +from datetime import datetime, timezone from d3m.metadata.pipeline import Pipeline +TUNING_PARAMETER = 'https://metadata.datadrivendiscovery.org/types/TuningParameter' + def load_pipeline(pipeline): with open(pipeline) as _pipeline: @@ -14,40 +16,73 @@ def load_pipeline(pipeline): else: pipeline = Pipeline.from_yaml(_pipeline) - pipeline.id = pipeline.get_digest() + return pipeline + + +def get_default_step_hyperparams(step): + default_tunable_hyperparams = {} + for name, hp in step.get_all_hyperparams().items(): + if TUNING_PARAMETER not in hp.semantic_types: + continue + + default_tunable_hyperparams[name] = hp.get_default() + + return default_tunable_hyperparams + + +def clean_hyperparams(pipeline): + for step in pipeline.steps: + default_tunable_hyperparams = get_default_step_hyperparams(step) + + for name, value in step.hyperparams.items(): + if name in default_tunable_hyperparams.keys(): + value['data'] = default_tunable_hyperparams[name] return pipeline -def generate_new_templates(path): - errors = [] - for pipeline in os.listdir(path): - pipeline_path = os.path.join(path, pipeline) - try: - pipeline = load_pipeline(pipeline_path) - new_path = os.path.join('templates', pipeline.id + '.json') +def pipeline_to_template(pipeline_path): + pipeline = load_pipeline(pipeline_path) + template = clean_hyperparams(pipeline) - with open(new_path, 'w') as pipeline_file: - pipeline.to_json(pipeline_file) + template.id = '' + template.schema = 'https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json' + template.created = datetime(2016, 11, 11, 12, 30, tzinfo=timezone.utc) - print('OK:', pipeline.id) + return template - except Exception: - print('ERROR:', pipeline) - traceback.print_exc(file=sys.stdout) - errors.append(pipeline_path) - if errors: - with open('errors.txt', 'w') as f: - for error in errors: - print(error, file=f) +def write_template(templates_path, template): + template_id = template.get_digest()[:12] + template_path = os.path.join(templates_path, template_id + '.json') + with open(template_path, 'w') as template_file: + print("Creating template {}".format(template_path)) + template.to_json(template_file) + + +def generate_templates(pipelines_path, templates_path): + for pipeline in os.listdir(pipelines_path): + pipeline_path = os.path.join(pipelines_path, pipeline) + try: + template = pipeline_to_template(pipeline_path) + write_template(templates_path, template) + except Exception as ex: + print(ex) -if __name__ == '__main__': - # Make all the d3m traces quiet - null = open(os.devnull, 'w') - sys.stderr = null +def parse_args(): + parser = argparse.ArgumentParser(description='Generate templates from pipelines') + parser.add_argument('pipelines_path', help='Path to the pipelines folder') + parser.add_argument('templates_path', help='Path to the templates folder') - path = sys.argv[1] - generate_new_templates(path) + return parser.parse_args() + + +def main(): + args = parse_args() + generate_templates(args.pipelines_path, args.templates_path) + + +if __name__ == '__main__': + main() From 2d66e54913412519a137d1562446bf2cf832c579 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 13 Feb 2020 07:28:18 +0100 Subject: [PATCH 14/41] New templates --- ...5e7ce2aa66961be0a0e8ce449257401f81dfa5b73b9b056dbf12762.json | 1 - ...5ff45f483ddb0ad0baed819e4c08af0789e03673e43e754046e70d4.json | 1 - ta2/templates/013080e189f7.json | 1 + ...eb33a7224fecfd3415de54860a7dceb9f7efdb7087ae13223c6b70d.json | 1 - ta2/templates/014d67705b1a.json | 1 + ta2/templates/016fb04119a5.json | 1 + ...1077e51bc2fcaa38f37672c1eb51bffee439f0cab0dd9652c1ce42c.json | 1 - ...357c21fbe572b3281d9c0d8b54d1dd9212552c85a03ce235b9fb852.json | 1 - ta2/templates/03703cca721e.json | 1 + ...7e428e12953b7b64b3088e9670869b3b12a2e211a3ec58e28aac3db.json | 1 - ...5270a06805a140b97d5ae91e77ed95d2e6867af356c5732e54734f5.json | 1 - ta2/templates/0466e5804252.json | 1 + ta2/templates/047fd9885bd4.json | 1 + ...83d67fb46efb6543d39df6fd89b86968c3fb163e8e099dbbf51b9d0.json | 1 - ...835196994c33ffa372d7798b6edd1ca96c03fb871b7dbf6118e7673.json | 1 - ta2/templates/05bdd77daf3c.json | 1 + ...3c59f31a39421d3ab1e4bcb24605425c047dcb3908d9dcbef6f28b3.json | 1 - ta2/templates/06ce0d3183eb.json | 1 + ...49d3b0bdababb5b5ebfc303c2928edb70a09088ef7b2bb1ac8ecc86.json | 1 - ...d3b2540243080eb0d04f963608a778f4c566636d7157c8c2a077500.json | 1 - ...ca0e2f7999077c8cfb78988feaf0ef41e99b938e8729dea92113446.json | 1 - ta2/templates/0853247f0495.json | 1 + ...e05f3c754ecc33b8e0ec0f860e9101a93821242a9b329c8bebe69de.json | 1 - ...903867bba727f823ca1515f943f8d1e6c984f5ca81dd871229ca333.json | 1 - ta2/templates/08b4c1259618.json | 1 + ta2/templates/0a2f18673690.json | 1 + ta2/templates/0a2f9213fc89.json | 1 + ...c1daab3c0a460f408d122c4eff50c009a8ce10d6b236ad573caea5a.json | 1 - ta2/templates/0acf807642d0.json | 1 + ta2/templates/0afdab77f212.json | 1 + ta2/templates/0b153f4fab26.json | 1 + 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A & M University,Normal,AL,www.aamu.edu/,www2.aamu.edu/scripts/netpricecalc/npcalc.htm,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,380.0,470.0,370.0,470.0,370.0,457.0,425.0,420.0,414.0,16.0,19.0,14.0,20.0,15.0,18.0,,,18.0,17.0,17.0,,849.0,849.0,0.0448,0.0142,0.0071,0.0,0.0,0.0354,0.0401,0.0,0.1132,0.0896,0.0472,0.0,0.033,0.0,0.0094,0.066,0.0,0.0708,0.0024,0.0,0.0,0.0,0.0,0.0,0.0307,0.0,0.0472,0.0519,0.0377,0.0448,0.0,0.0,0.0,0.0,0.0283,0.0,0.1863,0.0,0.0,4616.0,0.0256,0.9129,0.0076,0.0019,0.0024,0.0017,0.0401,0.0065,0.0013,0.0877,1,15567.0,,15043.0,15491.0,17335.0,19562.0,18865.0,,,,,,0.7039,0.5774,,0.309,,0.7667,0.0859,31000,0.453,0.431,32750,348.16551225731,0.2531554273,,0.2913,Q39624632,Q17203888,Q173,Q575407\\\\\\\\n1,100663,105200,1052,University of Alabama at Birmingham,Birmingham,AL,www.uab.edu,uab.studentaidcalculator.com/survey.aspx,0,3,4,1,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,480.0,640.0,490.0,660.0,,,560.0,575.0,,21.0,28.0,22.0,30.0,19.0,26.0,,,25.0,26.0,23.0,,1125.0,1125.0,0.0,0.0,0.0,0.0005,0.036000000000000004,0.0,0.0131,0.0,0.0748,0.0599,0.0,0.0059,0.0,0.0,0.0158,0.0135,0.0,0.0734,0.009000000000000001,0.0,0.0,0.0,0.005,0.0,0.0212,0.0,0.0766,0.0243,0.0221,0.0365,0.0,0.0,0.0,0.0,0.0392,0.25,0.2072,0.0162,0.0,12047.0,0.5786,0.2626,0.0309,0.0598,0.0028,0.0004,0.0387,0.0179,0.0083,0.2578,1,16475.0,,13849.0,15385.0,18022.0,18705.0,19319.0,,,,,,0.3525,0.8007,,0.5178,,0.5179,0.2363,41200,0.669,0.631,21833,232.106797835537,0.513963161,,0.5384,Q39624677,Q17204336,Q173,Q79867\\\\\\\\n2,100690,2503400,25034,Amridge University,Montgomery,AL,www.amridgeuniversity.edu,www2.amridgeuniversity.edu:9091/,0,3,4,2,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,74.0,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0889,0.0,0.0,0.0889,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0667,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3556,0.0,1.0,293.0,0.157,0.2355,0.0068,0.0,0.0,0.0034,0.0,0.0,0.5973,0.5392,1,,10155.0,,,,,,10155.0,,,,,0.6971,PrivacySuppressed,,PrivacySuppressed,,0.8436,0.8571,39600,0.658,0.542,22890,243.343773299842,0.2307692308,,PrivacySuppressed,Q39624831,Q17337864,Q173,Q29364\\\\\\\\n3,100706,105500,1055,University of Alabama in Huntsville,Huntsville,AL,www.uah.edu,finaid.uah.edu/,0,3,4,1,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,520.0,660.0,540.0,680.0,,,590.0,610.0,,25.0,31.0,24.0,33.0,23.0,29.0,,,28.0,29.0,26.0,,1257.0,1257.0,0.0,0.0,0.0,0.0,0.0301,0.0,0.0499,0.0,0.0282,0.2702,0.0,0.0151,0.0,0.0,0.0122,0.0,0.0,0.0603,0.0132,0.0,0.0,0.0,0.0113,0.0,0.0226,0.0,0.016,0.0,0.0,0.0188,0.0,0.0,0.0,0.0,0.0264,0.1911,0.225,0.0094,0.0,6346.0,0.7148,0.1131,0.0411,0.0414,0.012,0.0,0.0181,0.0303,0.0292,0.1746,1,19423.0,,15971.0,18016.0,20300.0,21834.0,22059.0,,,,,,0.2949,0.8161,,0.5116,,0.4312,0.2255,46700,0.685,0.649,22647,240.760438353933,0.5485090298,,0.4905,Q39624901,Q17204354,Q173,Q79860\\\\\\\\n4,100724,100500,1005,Alabama State University,Montgomery,AL,www.alasu.edu,www.alasu.edu/cost-aid/forms/calculator/index.aspx,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,370.0,460.0,360.0,460.0,,,415.0,410.0,,15.0,19.0,14.0,19.0,15.0,17.0,,,17.0,17.0,16.0,,825.0,825.0,0.0,0.0,0.0,0.0,0.1023,0.0,0.0503,0.0,0.1364,0.0,0.0,0.0,0.0,0.0,0.0114,0.0,0.0,0.0779,0.0146,0.0,0.0,0.0211,0.0,0.0,0.0244,0.0,0.0503,0.1412,0.0633,0.013000000000000001,0.0,0.0,0.0,0.0,0.0487,0.1429,0.0974,0.0049,0.0,4704.0,0.0138,0.9337,0.0111,0.0028,0.0013,0.0004,0.0111,0.0159,0.01,0.0727,1,15037.0,,14111.0,15140.0,17492.0,19079.0,18902.0,,,,,,0.7815,0.6138,,0.5313,,0.8113,0.0974,27700,0.393,0.351,31500,334.876752247489,0.2185867473,,0.2475,Q39624974,Q17203904,Q173,Q29364\\\\\\\\n5,100751,105100,1051,The University of Alabama,Tuscaloosa,AL,www.ua.edu/,financialaid.ua.edu/net-price-calculator/,0,3,4,1,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,490.0,610.0,490.0,620.0,480.0,600.0,550.0,555.0,540.0,23.0,31.0,23.0,33.0,22.0,29.0,7.0,8.0,27.0,28.0,26.0,8.0,1202.0,1202.0,0.0,0.0039,0.0,0.0042,0.102,0.0,0.0098,0.0,0.0782,0.1036,0.0,0.0057,0.0692,0.0,0.0115,0.0,0.0,0.0338,0.009000000000000001,0.0,0.0206,0.0,0.0031,0.0,0.0115,0.0,0.036000000000000004,0.0263,0.0109,0.0362,0.0,0.0,0.0,0.0,0.026000000000000002,0.0988,0.2879,0.0118,0.0,31663.0,0.7841,0.1037,0.0437,0.0118,0.0036,0.0009,0.0297,0.0192,0.0033,0.0819,1,21676.0,,18686.0,20013.0,22425.0,23666.0,24578.0,,,,,,0.1938,0.8637,,0.4308,,0.4007,0.081,44500,0.695,0.679,23290,247.596176502985,0.6019442985,,0.6793,Q39625107,Q17204328,Q173,Q79580\\\\\\\\n6,100760,100700,1007,Central Alabama Community College,Alexander City,AL,www.cacc.edu,www.cacc.edu/NetPriceCalculator/14-15/npcalc.html,0,2,2,1,32.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0266,0.0082,0.0,0.0,0.1025,0.0,0.0,0.0,0.0,0.2787,0.0,0.0,0.0,0.0,0.0287,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0307,0.3176,0.0,0.0,0.1209,0.0861,0.0,0.0,1492.0,0.6877,0.2802,0.0127,0.002,0.004,0.0007,0.0067,0.002,0.004,0.3733,1,9128.0,,8882.0,8647.0,11681.0,11947.0,13868.0,,,,,,0.5109,,0.5666,,0.4554,0.3234,0.263,27700,0.466,0.395,9500,100.994576074639,0.2510056315,0.2136,,Q39625150,Q17203916,Q173,Q79663\\\\\\\\n7,100812,100800,1008,Athens State 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A & M University,Normal,AL,www.aamu.edu/,www2.aamu.edu/scripts/netpricecalc/npcalc.htm,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,380.0,470.0,370.0,470.0,370.0,457.0,425.0,420.0,414.0,16.0,19.0,14.0,20.0,15.0,18.0,,,18.0,17.0,17.0,,849.0,849.0,0.0448,0.0142,0.0071,0.0,0.0,0.0354,0.0401,0.0,0.1132,0.0896,0.0472,0.0,0.033,0.0,0.0094,0.066,0.0,0.0708,0.0024,0.0,0.0,0.0,0.0,0.0,0.0307,0.0,0.0472,0.0519,0.0377,0.0448,0.0,0.0,0.0,0.0,0.0283,0.0,0.1863,0.0,0.0,4616.0,0.0256,0.9129,0.0076,0.0019,0.0024,0.0017,0.0401,0.0065,0.0013,0.0877,1,15567.0,,15043.0,15491.0,17335.0,19562.0,18865.0,,,,,,0.7039,0.5774,,0.309,,0.7667,0.0859,31000,0.453,0.431,32750,348.16551225731,0.2531554273,,0.2913,Q39624632,Q17203888,Q173,Q575407\\\\\\\\n1,100663,105200,1052,University of Alabama at Birmingham,Birmingham,AL,www.uab.edu,uab.studentaidcalculator.com/survey.aspx,0,3,4,1,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,480.0,640.0,490.0,660.0,,,560.0,575.0,,21.0,28.0,22.0,30.0,19.0,26.0,,,25.0,26.0,23.0,,1125.0,1125.0,0.0,0.0,0.0,0.0005,0.036000000000000004,0.0,0.0131,0.0,0.0748,0.0599,0.0,0.0059,0.0,0.0,0.0158,0.0135,0.0,0.0734,0.009000000000000001,0.0,0.0,0.0,0.005,0.0,0.0212,0.0,0.0766,0.0243,0.0221,0.0365,0.0,0.0,0.0,0.0,0.0392,0.25,0.2072,0.0162,0.0,12047.0,0.5786,0.2626,0.0309,0.0598,0.0028,0.0004,0.0387,0.0179,0.0083,0.2578,1,16475.0,,13849.0,15385.0,18022.0,18705.0,19319.0,,,,,,0.3525,0.8007,,0.5178,,0.5179,0.2363,41200,0.669,0.631,21833,232.106797835537,0.513963161,,0.5384,Q39624677,Q17204336,Q173,Q79867\\\\\\\\n2,100690,2503400,25034,Amridge 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University,Montgomery,AL,www.alasu.edu,www.alasu.edu/cost-aid/forms/calculator/index.aspx,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,370.0,460.0,360.0,460.0,,,415.0,410.0,,15.0,19.0,14.0,19.0,15.0,17.0,,,17.0,17.0,16.0,,825.0,825.0,0.0,0.0,0.0,0.0,0.1023,0.0,0.0503,0.0,0.1364,0.0,0.0,0.0,0.0,0.0,0.0114,0.0,0.0,0.0779,0.0146,0.0,0.0,0.0211,0.0,0.0,0.0244,0.0,0.0503,0.1412,0.0633,0.013000000000000001,0.0,0.0,0.0,0.0,0.0487,0.1429,0.0974,0.0049,0.0,4704.0,0.0138,0.9337,0.0111,0.0028,0.0013,0.0004,0.0111,0.0159,0.01,0.0727,1,15037.0,,14111.0,15140.0,17492.0,19079.0,18902.0,,,,,,0.7815,0.6138,,0.5313,,0.8113,0.0974,27700,0.393,0.351,31500,334.876752247489,0.2185867473,,0.2475,Q39624974,Q17203904,Q173,Q29364\\\\\\\\n5,100751,105100,1051,The University of Alabama,Tuscaloosa,AL,www.ua.edu/,financialaid.ua.edu/net-price-calculator/,0,3,4,1,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,490.0,610.0,490.0,620.0,480.0,600.0,550.0,555.0,540.0,23.0,31.0,23.0,33.0,22.0,29.0,7.0,8.0,27.0,28.0,26.0,8.0,1202.0,1202.0,0.0,0.0039,0.0,0.0042,0.102,0.0,0.0098,0.0,0.0782,0.1036,0.0,0.0057,0.0692,0.0,0.0115,0.0,0.0,0.0338,0.009000000000000001,0.0,0.0206,0.0,0.0031,0.0,0.0115,0.0,0.036000000000000004,0.0263,0.0109,0.0362,0.0,0.0,0.0,0.0,0.026000000000000002,0.0988,0.2879,0.0118,0.0,31663.0,0.7841,0.1037,0.0437,0.0118,0.0036,0.0009,0.0297,0.0192,0.0033,0.0819,1,21676.0,,18686.0,20013.0,22425.0,23666.0,24578.0,,,,,,0.1938,0.8637,,0.4308,,0.4007,0.081,44500,0.695,0.679,23290,247.596176502985,0.6019442985,,0.6793,Q39625107,Q17204328,Q173,Q79580\\\\\\\\n6,100760,100700,1007,Central Alabama Community College,Alexander City,AL,www.cacc.edu,www.cacc.edu/NetPriceCalculator/14-15/npcalc.html,0,2,2,1,32.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0266,0.0082,0.0,0.0,0.1025,0.0,0.0,0.0,0.0,0.2787,0.0,0.0,0.0,0.0,0.0287,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0307,0.3176,0.0,0.0,0.1209,0.0861,0.0,0.0,1492.0,0.6877,0.2802,0.0127,0.002,0.004,0.0007,0.0067,0.002,0.004,0.3733,1,9128.0,,8882.0,8647.0,11681.0,11947.0,13868.0,,,,,,0.5109,,0.5666,,0.4554,0.3234,0.263,27700,0.466,0.395,9500,100.994576074639,0.2510056315,0.2136,,Q39625150,Q17203916,Q173,Q79663\\\\\\\\n7,100812,100800,1008,Athens State University,Athens,AL,www.athens.edu,https://24.athens.edu/apex/prod8/f?p=174:1:3941357449598491,0,3,3,1,31.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0462,0.0,0.2192,0.0,0.0,0.0,0.0,0.0,0.0346,0.0538,0.0,0.0231,0.0205,0.0,0.0154,0.0154,0.0038,0.0,0.0026,0.0,0.0308,0.0282,0.0,0.0218,0.0,0.0,0.0,0.0,0.0256,0.0064,0.4449,0.0077,0.0,2888.0,0.7784,0.125,0.0215,0.0076,0.0142,0.001,0.0187,0.001,0.0325,0.5817,1,,,,,,,,,,,,,0.4219,,,,,0.6455,0.6774,38700,0.653,0.612,18000,191.358144141422,0.5038167939,,,Q39625389,Q17203920,Q173,Q203263\\\\\\\\n8,100830,831000,8310,Auburn University at 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"VALUE", "data": 5}, "use_attributes": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "5194ef94-3683-319a-9d8d-5c3fdd09de24", "version": "0.1.0", "python_path": "d3m.primitives.graph_clustering.gaussian_clustering.JHU", "name": "jhu.gclust", "digest": "156b21208449283e358ba58bbb038e3742487fbd0058099b03330aed3ed06b10"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"max_clusters": {"type": "VALUE", "data": 10}}}], "digest": "577647e37f94dd391b143c61b06a5b00750ddc75a8d7e371893761efc744686b"} \ No newline at end of file diff --git a/ta2/templates/ff6ac7c0435581088a468e37ad74b80f8ee4f366967dffc1f22aa80533fff6c5.json b/ta2/templates/ff6ac7c0435581088a468e37ad74b80f8ee4f366967dffc1f22aa80533fff6c5.json deleted file mode 100644 index 59bdbc2..0000000 --- a/ta2/templates/ff6ac7c0435581088a468e37ad74b80f8ee4f366967dffc1f22aa80533fff6c5.json +++ /dev/null @@ -1 +0,0 @@ -{"id": "ff6ac7c0435581088a468e37ad74b80f8ee4f366967dffc1f22aa80533fff6c5", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2020-01-14T15:23:40.821167Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.4.produce", "name": "output predictions"}], "steps": [{"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", "digest": "990784f527a78250fcab70af9714314490e91f9a5916eb38834d74e8c38f435b"}, "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.data_transformation.column_parser.Common", "name": "Parses strings into their types", "digest": "96e020725140c0a67033e5e340c555514b0a5432179254c38813a4e85687528d"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d016df89-de62-3c53-87ed-c06bb6a23cde", "version": "2019.11.13", "python_path": "d3m.primitives.data_cleaning.imputer.SKlearn", "name": "sklearn.impute.SimpleImputer", "digest": "1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"use_semantic_types": {"type": "VALUE", "data": true}, "return_result": {"type": "VALUE", "data": "replace"}}}, {"type": "PRIMITIVE", "primitive": {"id": "85e5c88d-9eec-3452-8f2f-414f17d3e4d5", "version": "2019.11.13", "python_path": "d3m.primitives.classification.passive_aggressive.SKlearn", "name": "sklearn.linear_model.passive_aggressive.PassiveAggressiveClassifier", "digest": "1ac186ad58b35aeb1cd61631dc5e8b09fb25463764fca1fdee975900115cfe96"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"use_semantic_types": {"type": "VALUE", "data": true}, "add_index_columns": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.Common", "name": "Construct pipeline predictions output", "digest": "d597b7d1f1a28e331c710a0065c046d667d0e3b22e2b96c0be28d64d105e9d17"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.3.produce"}, "reference": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "5ae305c6b01aacdd82d4814981a000335049b613dc5e42a09591e01db5b5dfe3"} \ No newline at end of file From 8f40c45994691abe00d38af3e0777ce9874fd66e Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 13 Feb 2020 18:00:30 +0100 Subject: [PATCH 15/41] Change pipeline_run storage format --- ta2/__main__.py | 3 ++- ta2/search.py | 15 ++++++++------- 2 files changed, 10 insertions(+), 8 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index 2db3d29..3b95baa 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -172,7 +172,8 @@ def process_dataset(dataset_name, dataset, problem, args): ignore_errors=args.ignore_errors, cv_folds=args.folds, subprocess_timeout=args.subprocess_timeout, - max_errors=args.max_errors + max_errors=args.max_errors, + store_pipeline_runs=True ) result = pps.search(dataset, problem, args.timeout, args.budget, args.template) diff --git a/ta2/search.py b/ta2/search.py index fbe1051..deaa48f 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -4,6 +4,7 @@ import random import signal import warnings +import yaml from collections import defaultdict from datetime import datetime, timedelta from multiprocessing import Manager, Process @@ -124,7 +125,7 @@ def _get_templates(self, dataset_name, data_modality, task_type): def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, - subprocess_timeout=None, max_errors=0): + subprocess_timeout=None, max_errors=0, store_pipeline_runs=False): self.input = input_dir self.output = output_dir self.static = static_dir @@ -148,6 +149,7 @@ def __init__(self, input_dir='input', output_dir='output', static_dir='static', self.folds = cv_folds self.subprocess_timeout = subprocess_timeout self.max_errors = max_errors + self.store_pipeline_runs = store_pipeline_runs @staticmethod def _evaluate(out, pipeline, *args, **kwargs): @@ -225,12 +227,11 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 volumes_dir=self.static, ) - for res in all_results: - pipeline_run = res.pipeline_run - if pipeline_run.run.get('phase') == 'PRODUCE': - yaml_file = os.path.join(self.runs_dir, '{}.yml'.format(pipeline_run.get_id())) - with open(yaml_file, 'w') as pip: - pipeline_run.to_yaml(file=pip) + if self.store_pipeline_runs: + yaml_path = os.path.join(self.runs_dir, '{}.yml'.format(pipeline.id)) + runs = [res.pipeline_run.to_json_structure() for res in all_results] + with open(yaml_path, 'w') as yaml_file: + yaml.dump_all(runs, yaml_file, default_flow_style=False) if not all_scores: self.error += 1 From fd874599da2806ced3e4654cb4b61eda9f6a82f4 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Date: Thu, 13 Feb 2020 18:20:56 +0100 Subject: [PATCH 16/41] Removed empty json. --- ta2/templates/86e9be8b6ce1.json | 0 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 ta2/templates/86e9be8b6ce1.json diff --git a/ta2/templates/86e9be8b6ce1.json b/ta2/templates/86e9be8b6ce1.json deleted file mode 100644 index e69de29..0000000 From 574cc3ff5e32c2146da854d8022d94a95d03f544 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Date: Thu, 13 Feb 2020 18:32:25 +0100 Subject: [PATCH 17/41] Update validate. --- ta2/search.py | 40 +++++++++++++++++++++++++++------------- 1 file changed, 27 insertions(+), 13 deletions(-) diff --git a/ta2/search.py b/ta2/search.py index deaa48f..e308ec7 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -106,22 +106,37 @@ def _load_pipeline(self, pipeline): with open(path, 'r') as pipeline_file: return loader(string_or_file=pipeline_file) - def _get_templates(self, dataset_name, data_modality, task_type): - LOGGER.info('Loading template for dataset %s', dataset_name) + def _get_templates(self): + # LOGGER.info('Loading template for dataset %s', dataset_name) - df = pd.read_csv(os.path.join(TEMPLATES_DIR, 'templates_with_z_score.csv')) + # df = pd.read_csv(os.path.join(TEMPLATES_DIR, 'templates_with_z_score.csv')) - templates = df[df['name'] == dataset_name].sort_values('z_score', ascending=False) + # templates = df[df['name'] == dataset_name].sort_values('z_score', ascending=False) - problem_type = '{}_{}'.format(data_modality, task_type) - df['match'] = df['name'] == dataset_name - templates = df[df['problem_type'] == problem_type] - templates = templates.sort_values(['match', 'z_score'], ascending=False) - templates = templates.drop_duplicates(subset=['pipeline_id'], keep='first') + # problem_type = '{}_{}'.format(data_modality, task_type) + # df['match'] = df['name'] == dataset_name + # templates = df[df['problem_type'] == problem_type] + # templates = templates.sort_values(['match', 'z_score'], ascending=False) + # templates = templates.drop_duplicates(subset=['pipeline_id'], keep='first') - self.found_by_name = df['match'].any() + # self.found_by_name = df['match'].any() - return templates.pipeline_id.values + # return templates.pipeline_id.values + + valid_templates = [] + templates = os.listdir(TEMPLATES_DIR) + for template in templates: + try: + path = os.path.join(TEMPLATES_DIR, template) + with open(path, 'r') as f: + json.load(f) + + valid_templates.append(template) + except: + print('Errored: ', template) + continue + + return valid_templates def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, @@ -443,8 +458,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non self.setup_search() LOGGER.info("Loading the template and the tuner") if not template_names: - # template_names = self._get_templates(dataset_name, data_modality, task_type) - template_names = os.listdir(TEMPLATES_DIR) + template_names = self._get_templates() template_loader = LazyLoader(template_names, TEMPLATES_DIR) btb_scorer = self.make_btb_scorer( From 1cabfd5469866e33297eff8ef8e0b09166a6cfbf Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Thu, 13 Feb 2020 18:37:41 +0100 Subject: [PATCH 18/41] Catch tuning exceptions and log invalid templates --- ta2/search.py | 68 +++++++++++++++++++++++++++------------------------ 1 file changed, 36 insertions(+), 32 deletions(-) diff --git a/ta2/search.py b/ta2/search.py index e308ec7..95824bb 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -106,23 +106,7 @@ def _load_pipeline(self, pipeline): with open(path, 'r') as pipeline_file: return loader(string_or_file=pipeline_file) - def _get_templates(self): - # LOGGER.info('Loading template for dataset %s', dataset_name) - - # df = pd.read_csv(os.path.join(TEMPLATES_DIR, 'templates_with_z_score.csv')) - - # templates = df[df['name'] == dataset_name].sort_values('z_score', ascending=False) - - # problem_type = '{}_{}'.format(data_modality, task_type) - # df['match'] = df['name'] == dataset_name - # templates = df[df['problem_type'] == problem_type] - # templates = templates.sort_values(['match', 'z_score'], ascending=False) - # templates = templates.drop_duplicates(subset=['pipeline_id'], keep='first') - - # self.found_by_name = df['match'].any() - - # return templates.pipeline_id.values - + def _get_all_templates(self): valid_templates = [] templates = os.listdir(TEMPLATES_DIR) for template in templates: @@ -133,11 +117,27 @@ def _get_templates(self): valid_templates.append(template) except: - print('Errored: ', template) - continue + LOGGER.warning('Invalid template found: %s', path) return valid_templates + def _get_templates(self): + LOGGER.info('Loading template for dataset %s', dataset_name) + + df = pd.read_csv(os.path.join(TEMPLATES_DIR, 'templates_with_z_score.csv')) + + templates = df[df['name'] == dataset_name].sort_values('z_score', ascending=False) + + problem_type = '{}_{}'.format(data_modality, task_type) + df['match'] = df['name'] == dataset_name + templates = df[df['problem_type'] == problem_type] + templates = templates.sort_values(['match', 'z_score'], ascending=False) + templates = templates.drop_duplicates(subset=['pipeline_id'], keep='first') + + self.found_by_name = df['match'].any() + + return templates.pipeline_id.values + def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, subprocess_timeout=None, max_errors=0, store_pipeline_runs=False): @@ -458,7 +458,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non self.setup_search() LOGGER.info("Loading the template and the tuner") if not template_names: - template_names = self._get_templates() + template_names = self._get_all_templates() template_loader = LazyLoader(template_names, TEMPLATES_DIR) btb_scorer = self.make_btb_scorer( @@ -466,18 +466,22 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) - if self.budget is not None: - spent = 0 - while spent < self.budget: - session.run(1) - last_score = list(session.proposals.values())[-1].get('score') - if (last_score is None) and self.ignore_errors: - LOGGER.warning("Ignoring errored pipeline") - else: - spent += 1 - - else: - session.run() + try: + if self.budget is not None: + spent = 0 + while spent < self.budget: + session.run(1) + last_score = list(session.proposals.values())[-1].get('score') + if (last_score is None) and self.ignore_errors: + LOGGER.warning("Ignoring errored pipeline") + else: + spent += 1 + + else: + session.run() + except Exception: + self.invalid += 1 + raise except KeyboardInterrupt: pass From dffcd1c60c5e7cd579064616215f3f81d34f8506 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Fri, 14 Feb 2020 01:01:33 +0100 Subject: [PATCH 19/41] Add extra functionality. --- scripts/generate_templates.py | 204 +++++++++++++++++++++++++++++++++- 1 file changed, 201 insertions(+), 3 deletions(-) diff --git a/scripts/generate_templates.py b/scripts/generate_templates.py index d20ef4a..3555ce5 100644 --- a/scripts/generate_templates.py +++ b/scripts/generate_templates.py @@ -1,11 +1,19 @@ import argparse +import glob +import json +import logging import os import sys import traceback from datetime import datetime, timezone +import numpy as np +import pandas as pd from d3m.metadata.pipeline import Pipeline +from d3m.metadata.problem import Problem +from d3m.utils import yaml_load_all +LOGGER = logging.getLogger(__name__) TUNING_PARAMETER = 'https://metadata.datadrivendiscovery.org/types/TuningParameter' @@ -71,17 +79,207 @@ def generate_templates(pipelines_path, templates_path): print(ex) -def parse_args(): - parser = argparse.ArgumentParser(description='Generate templates from pipelines') +def read_pipeline_run(pipeline_run_path): + data = open(pipeline_run_path) + docs = yaml_load_all(stream=data) + res = [] + for doc in docs: + res.append(doc) + + data.close() + + return res + + +def load_problem(root_path, phase): + path = os.path.join(root_path, phase, 'problem_' + phase, 'problemDoc.json') + return Problem.load(problem_uri=path) + + +def detect_data_modality(dataset_doc): + with open(dataset_doc) as f: + dataset_doc = json.load(f) + + resources = list() + for resource in dataset_doc['dataResources']: + resources.append(resource['resType']) + + if len(resources) == 1: + return 'single_table' + else: + for resource in resources: + if resource == 'edgeList': + return 'graph' + elif resource not in ('table', 'raw'): + return resource + + return 'multi_table' + + +def get_dataset_info(dataset_name, datasets_path): + + dataset_root = os.path.join(datasets_path, dataset_name) + + if not os.path.exists(dataset_root): + dataset_root += '_MIN_METADATA' + + dataset_doc = os.path.join(dataset_root, 'TRAIN', 'dataset_TRAIN', 'datasetDoc.json') + dataset_root = 'file://' + os.path.abspath(dataset_root) + problem = load_problem(dataset_root, 'TRAIN') + + # Dataset Meta + data_modality = detect_data_modality(dataset_doc) + task_type = problem['problem']['task_keywords'][0].name.lower() + task_subtype = problem['problem']['task_keywords'][1].name.lower() + + return data_modality, task_type, task_subtype + + +def get_template_id(pipeline_id, pipelines_path, templates_path): + + pipeline_path = os.path.join(pipelines_path, '{}.json'.format(pipeline_id)) + if not os.path.isfile(pipeline_path): + raise ValueError('Can not find: {}'.format(pipeline_path)) + + template = pipeline_to_template(pipeline_path) + write_template(templates_path, template) + return template.get_digest()[:12] + + +def extract_pipeline_run(pipeline_run, pipelines_path, templates_path, datasets_path): + + dataset_id = pipeline_run['datasets'][0]['id'] + scores = pipeline_run['run']['results']['scores'] + pipeline_id = pipeline_run['pipeline']['id'] + + if len(scores) > 1: + raise ValueError('This run has more than one score!') + + scores = scores[0] + + if dataset_id.endswith('TRAIN'): + dataset_name = dataset_id.replace('_dataset_TRAIN', '') + else: + dataset_name = dataset_id.replace('_dataset_SCORE', '') + + # TODO: Lazy Loader + data_modality, task_type, task_subtype = get_dataset_info(dataset_name, datasets_path) + + template_id = get_template_id(pipeline_id, pipelines_path, templates_path) + + return { + 'dataset': dataset_name, + 'pipeline_id': pipeline_id, + 'template_id': template_id, + 'modality': data_modality, + 'type': task_type, + 'subtype': task_subtype, + 'metric': scores['metric']['metric'], + 'context': pipeline_run['context'], + 'normalized_score': scores['normalized'], + } + + +def extract_meta_information(pipeline_runs, pipelines_path, templates_path, datasets_path): + pipeline_runs_path = os.path.join(pipeline_runs, '*') + + results = [] + errored = [] + discarded = [] + + for pipeline_run_path in glob.glob(pipeline_runs_path): + pipeline_runs = read_pipeline_run(pipeline_run_path) + + data_extracted = [] + + failed = False + + for pipeline_run in enumerate(pipeline_runs): + try: + run_data, run_status = extract_pipeline_run( + pipeline_run, pipelines_path, templates_path, datasets_path) + + failed = run_status == 'FAILURE' + + data_extracted.append(run_data) + + except Exception as e: + LOGGER.warning('Failed %s with: %s', pipeline_run_path, e) + continue + + if not failed: + results.append(data_extracted) + + else: + LOGGER.warning('Pipeline run %s discarded.', pipeline_run_path) + discarded.append(data_extracted) + + return results, discarded + + +def apply_mean_score(df): + mean_score = df.groupby(['pipeline_id', 'context'])['normalized_score'].mean() + mean_score = mean_score.reset_index() + mean_score.rename(columns={'normalized_score': 'mean_score'}, inplace=True) + return df.merge(mean_score, on=['pipeline_id', 'context'], how='left') + + +def z_score(x): + if len(x) == 1 or x.std() == 0: + return pd.Series(np.zeros(len(x)), index=x.index) + + return (x - x.mean()) / x.std() + + +def apply_z_score(df): + z_scores = df.groupby('dataset').normalized_score.apply(z_score) + df['z_score'] = z_scores + templates_z_score = df.groupby('template_id').z_score.mean() + del df['z_score'] + + return df.merge(templates_z_score, how='left', left_on='template_id', right_index=True) + + +def generate_metadata_report(pipeline_runs, pipelines_path, templates_path, datasets_path, report): + + results, discarded = extract_meta_information( + pipeline_runs, pipelines_path, templates_path, datasets_path) + + if report is None: + report = os.path.join(templates_path, 'templates.csv') + + df = pd.DataFrame(results) + df = apply_mean_score(df) + df = apply_z_score(df) + df.to_csv(report, index=False) + + if errored: + with open('errors.txt', 'w') as f: + for error in errored: + f.write('{}\n'.format(error)) + + +def get_parser(): + parser = argparse.ArgumentParser( + description='Generate new templates from pipeline runs and the metadata reffered to them.') + parser.add_argument('pipeline_runs_path', help='Path to the pipeline runs folder') parser.add_argument('pipelines_path', help='Path to the pipelines folder') parser.add_argument('templates_path', help='Path to the templates folder') + parser.add_argument('datasets_path', help='Path where the datasets are located') + parser.add_argument('-r', '--report', help='Path to the CSV file where scores will be dumped.') return parser.parse_args() def main(): args = parse_args() - generate_templates(args.pipelines_path, args.templates_path) + generate_metadata_report( + args.pipeline_runs_path, + args.pipelines_scored_path, + args.templates_path, + args.datasets_path, + args.report, + ) if __name__ == '__main__': From 78e073b7fe601d795e2d06dabfc07fb995474008 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Fri, 14 Feb 2020 01:52:57 +0100 Subject: [PATCH 20/41] Update for fit produce and timeout. --- scripts/generate_templates.py | 42 ++++++++++++++++++++++++++--------- 1 file changed, 31 insertions(+), 11 deletions(-) diff --git a/scripts/generate_templates.py b/scripts/generate_templates.py index 3555ce5..35a2460 100644 --- a/scripts/generate_templates.py +++ b/scripts/generate_templates.py @@ -146,17 +146,28 @@ def get_template_id(pipeline_id, pipelines_path, templates_path): return template.get_digest()[:12] -def extract_pipeline_run(pipeline_run, pipelines_path, templates_path, datasets_path): - - dataset_id = pipeline_run['datasets'][0]['id'] +def produce_phase(pipeline_run): + """Produce result with Produce phase data.""" scores = pipeline_run['run']['results']['scores'] - pipeline_id = pipeline_run['pipeline']['id'] if len(scores) > 1: raise ValueError('This run has more than one score!') scores = scores[0] + return { + 'metric': scores['metric']['metric'], + 'context': pipeline_run['context'], + 'normalized_score': scores['normalized'] + } + + +def extract_pipeline_run(pipeline_run, pipelines_path, templates_path, datasets_path): + dataset_id = pipeline_run['datasets'][0]['id'] + phase = pipeline_run['run']['phase'] + succeed = pipeline_run.get('status').get('state') + pipeline_id = pipeline_run['pipeline']['id'] + if dataset_id.endswith('TRAIN'): dataset_name = dataset_id.replace('_dataset_TRAIN', '') else: @@ -167,18 +178,27 @@ def extract_pipeline_run(pipeline_run, pipelines_path, templates_path, datasets_ template_id = get_template_id(pipeline_id, pipelines_path, templates_path) - return { + result = { 'dataset': dataset_name, 'pipeline_id': pipeline_id, 'template_id': template_id, 'modality': data_modality, 'type': task_type, 'subtype': task_subtype, - 'metric': scores['metric']['metric'], - 'context': pipeline_run['context'], - 'normalized_score': scores['normalized'], + 'phase': phase, + 'succeed': succeed, } + if phase == 'PRODUCE' and succeed != 'FAILURE': + try: + score = produce_phase(pipeline_run) + result.update(score) + except: + # Timeout + result['phase'] = 'TIMEOUT' + + return result, succeed + def extract_meta_information(pipeline_runs, pipelines_path, templates_path, datasets_path): pipeline_runs_path = os.path.join(pipeline_runs, '*') @@ -188,13 +208,13 @@ def extract_meta_information(pipeline_runs, pipelines_path, templates_path, data discarded = [] for pipeline_run_path in glob.glob(pipeline_runs_path): - pipeline_runs = read_pipeline_run(pipeline_run_path) + pipeline_runs = load_pipeline_run(pipeline_run_path) data_extracted = [] failed = False - for pipeline_run in enumerate(pipeline_runs): + for pipeline_run in pipeline_runs: try: run_data, run_status = extract_pipeline_run( pipeline_run, pipelines_path, templates_path, datasets_path) @@ -208,7 +228,7 @@ def extract_meta_information(pipeline_runs, pipelines_path, templates_path, data continue if not failed: - results.append(data_extracted) + results.extend(data_extracted) else: LOGGER.warning('Pipeline run %s discarded.', pipeline_run_path) From f4a0b6599493b845979f8da60368edccb5bcf5b7 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Fri, 14 Feb 2020 05:26:19 +0100 Subject: [PATCH 21/41] Improve reporting --- ta2/__main__.py | 7 ++++-- ta2/search.py | 57 +++++++++++++++++++++++++------------------------ 2 files changed, 34 insertions(+), 30 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index 3b95baa..753f3d7 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -212,8 +212,8 @@ def process_dataset(dataset_name, dataset, problem, args): 'scored', 'errored', 'invalid', - 'timeouts', - 'timeout', + 'timedout', + 'killed', 'modality', 'type', 'subtype', @@ -481,6 +481,9 @@ def parse_args(): os.makedirs(args.output, exist_ok=True) if args.logfile: + if not os.path.isabs(args.logfile): + args.logfile = os.path.join(args.output, args.logfile) + logdir = os.path.dirname(args.logfile) os.makedirs(logdir, exist_ok=True) diff --git a/ta2/search.py b/ta2/search.py index 95824bb..59976c8 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -35,6 +35,7 @@ ] LOGGER = logging.getLogger(__name__) +STATUS_MSG = 'iteartions: %s; scored: %s; errored: %s; invalid: %s; timedout: %s' warnings.filterwarnings("ignore", category=DeprecationWarning) @@ -192,13 +193,14 @@ def subprocess_evaluate(self, pipeline, *args, **kwargs): self.subprocess = None if process.is_alive(): - self._subprocess_timeouts += 1 + self.timedout += 1 process.terminate() raise Exception('Timeout reached for subprocess {}'.format(process.pid)) result = tuple(output) if output else None if not result: + self.invalid += 1 raise Exception("Subprocess evaluate crashed") return result @@ -249,7 +251,7 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 yaml.dump_all(runs, yaml_file, default_flow_style=False) if not all_scores: - self.error += 1 + self.errored += 1 failed_result = all_results[-1] message = failed_result.pipeline_run.status['message'] LOGGER.error(message) @@ -341,7 +343,7 @@ def stop(self): self.subprocess = None def _timeout(self, *args, **kwargs): - self._timeout_reached = True + self.killed = True raise KeyboardInterrupt() def setup_search(self): @@ -410,7 +412,7 @@ def btb_scorer(template_name, proposal): LOGGER.warning('Template %s score: %s - %s', template_name, pipeline.score, pipeline.normalized_score) - self.success += 1 + self.scored += 1 return pipeline.normalized_score finally: @@ -424,8 +426,7 @@ def btb_scorer(template_name, proposal): def search(self, dataset, problem, timeout=None, budget=None, template_names=None): self.timeout = timeout - self._timeout_reached = False - self._subprocess_timeouts = 0 + self.killed = False self.budget = budget self.best_pipeline = None self.best_score = None @@ -437,9 +438,10 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non task_type = None task_subtype = None self.iterations = 0 - self.error = 0 + self.scored = 0 + self.errored = 0 self.invalid = 0 - self.success = 0 + self.timedout = 0 dataset_name = problem['inputs'][0]['dataset_id'] if dataset_name.endswith('_dataset'): @@ -466,22 +468,21 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) - try: - if self.budget is not None: - spent = 0 - while spent < self.budget: - session.run(1) - last_score = list(session.proposals.values())[-1].get('score') - if (last_score is None) and self.ignore_errors: - LOGGER.warning("Ignoring errored pipeline") - else: - spent += 1 - - else: - session.run() - except Exception: - self.invalid += 1 - raise + if self.budget is not None: + spent = 0 + while spent < self.budget: + session.run(1) + last_score = list(session.proposals.values())[-1].get('score') + if (last_score is None) and self.ignore_errors: + LOGGER.warning("Ignoring errored pipeline") + else: + spent += 1 + + LOGGER.warn('its: %s; sc: %s; er: %s; in: %s; ti: %s', self.iterations, + self.scored, self.errored, self.invalid, self.timedout) + + else: + session.run() except KeyboardInterrupt: pass @@ -502,12 +503,12 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non 'type': task_type, 'subtype': task_subtype, 'iterations': self.iterations, - 'timeout': self._timeout_reached, - 'timeouts': self._subprocess_timeouts, 'templates': len(template_names), - 'scored': self.success, - 'errored': self.error, + 'scored': self.scored, + 'errored': self.errored, 'invalid': self.invalid, + 'timedout': self.timedout, + 'killed': self.killed, 'found': self.found_by_name, 'metric': metric.name.lower() } From e3cdee9dfc1eb1fe03bb5006bb57e0f2b052731a Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Fri, 14 Feb 2020 07:38:07 +0100 Subject: [PATCH 22/41] Store summary --- ta2/__main__.py | 2 +- ta2/search.py | 111 ++++++++++++++++++++++++++++-------------------- 2 files changed, 65 insertions(+), 48 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index 753f3d7..bf75b57 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -173,7 +173,7 @@ def process_dataset(dataset_name, dataset, problem, args): cv_folds=args.folds, subprocess_timeout=args.subprocess_timeout, max_errors=args.max_errors, - store_pipeline_runs=True + store_summary=True ) result = pps.search(dataset, problem, args.timeout, args.budget, args.template) diff --git a/ta2/search.py b/ta2/search.py index 59976c8..37cc5b9 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -93,6 +93,14 @@ def to_dicts(hyperparameters): return params_tree +class SubprocessTimeout(Exception): + pass + + +class ScoringError(Exception): + pass + + class PipelineSearcher: def _load_pipeline(self, pipeline): @@ -141,7 +149,7 @@ def _get_templates(self): def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, - subprocess_timeout=None, max_errors=0, store_pipeline_runs=False): + subprocess_timeout=None, max_errors=0, store_summary=False): self.input = input_dir self.output = output_dir self.static = static_dir @@ -165,7 +173,7 @@ def __init__(self, input_dir='input', output_dir='output', static_dir='static', self.folds = cv_folds self.subprocess_timeout = subprocess_timeout self.max_errors = max_errors - self.store_pipeline_runs = store_pipeline_runs + self.store_summary = store_summary @staticmethod def _evaluate(out, pipeline, *args, **kwargs): @@ -193,20 +201,16 @@ def subprocess_evaluate(self, pipeline, *args, **kwargs): self.subprocess = None if process.is_alive(): - self.timedout += 1 process.terminate() - raise Exception('Timeout reached for subprocess {}'.format(process.pid)) - - result = tuple(output) if output else None + raise SubprocessTimeout('Timeout reached for subprocess {}'.format(process.pid)) - if not result: - self.invalid += 1 - raise Exception("Subprocess evaluate crashed") + if not output: + raise Exception("Subprocess evaluate crashed") - return result + return tuple(output) def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0, - folds=None, stratified=False, shuffle=False): + folds=None, stratified=False, shuffle=False, template_name=None): folds = folds or self.folds problem_metrics = problem['problem']['performance_metrics'] @@ -217,18 +221,6 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 'shuffle': json.dumps(shuffle), } - # Some primitives crash with a core dump that kills everything. - # We want to isolate those. - # This is disabled in favor of permanently using a child process - # primitives = [ - # step['primitive']['python_path'] - # for step in pipeline.to_json_structure()['steps'] - # ] - # if any(primitive in SUBPROCESS_PRIMITIVES for primitive in primitives): - # evaluate = self.subprocess_evaluate - # else: - # evaluate = d3m_evaluate - all_scores, all_results = self.subprocess_evaluate( pipeline=pipeline, inputs=[dataset], @@ -244,23 +236,17 @@ def score_pipeline(self, dataset, problem, pipeline, metrics=None, random_seed=0 volumes_dir=self.static, ) - if self.store_pipeline_runs: + if not all_scores: + failed_result = all_results[-1] + message = failed_result.pipeline_run.status['message'] + raise ScoringError(message) + + elif self.store_summary: yaml_path = os.path.join(self.runs_dir, '{}.yml'.format(pipeline.id)) runs = [res.pipeline_run.to_json_structure() for res in all_results] with open(yaml_path, 'w') as yaml_file: yaml.dump_all(runs, yaml_file, default_flow_style=False) - if not all_scores: - self.errored += 1 - failed_result = all_results[-1] - message = failed_result.pipeline_run.status['message'] - LOGGER.error(message) - cause = failed_result.error.__cause__ - if isinstance(cause, BaseException): - raise cause - else: - raise failed_result.error - pipeline.cv_scores = [score.value[0] for score in all_scores] pipeline.score = np.mean(pipeline.cv_scores) @@ -391,17 +377,15 @@ def make_btb_scorer(self, dataset_name, dataset, problem, templates, metric): def btb_scorer(template_name, proposal): self.check_stop() self.iterations += 1 + LOGGER.info('Scoring template %s', template_name) + pipeline = None + status = None + score = None + normalized = None try: - LOGGER.info('Scoring template %s', template_name) pipeline = self._new_pipeline(templates[template_name], proposal) - except Exception: - LOGGER.exception('Error creating pipeline from template %s with params %s', - template_name, proposal) - self.invalid += 1 - raise - try: self.score_pipeline(dataset, problem, pipeline) pipeline.normalized_score = metric.normalize(pipeline.score) if pipeline.normalized_score > self.best_normalized: @@ -412,15 +396,38 @@ def btb_scorer(template_name, proposal): LOGGER.warning('Template %s score: %s - %s', template_name, pipeline.score, pipeline.normalized_score) + status = 'SCORED' + score = pipeline.score + normalized = pipeline.normalized_score self.scored += 1 return pipeline.normalized_score - finally: - try: - self._save_pipeline(pipeline) + except SubprocessTimeout: + self.timedout += 1 + status = 'TIMEOUT' + raise + except ScoringError: + self.errored += 1 + status = 'ERROR' + raise + except Exception: + self.invalid += 1 + status = 'INVALID' + raise - except Exception: - LOGGER.exception('Error saving pipeline %s', pipeline.id) + finally: + self.summary.append({ + 'template': template_name, + 'status': status, + 'score': score, + 'normalized': normalized + }) + if pipeline: + try: + self._save_pipeline(pipeline) + + except Exception: + LOGGER.exception('Error saving pipeline %s', pipeline.id) return btb_scorer @@ -442,6 +449,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non self.errored = 0 self.invalid = 0 self.timedout = 0 + self.summary = list() dataset_name = problem['inputs'][0]['dataset_id'] if dataset_name.endswith('_dataset'): @@ -493,6 +501,15 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non if self.timeout and self.hard_timeout: signal.alarm(0) + if self.store_summary and self.summary: + summary_path = os.path.join(self.output, 'summary.csv') + summary = pd.DataFrame(self.summary) + summary['dataset'] = dataset_name + summary['data_modality'] = data_modality + summary['type'] = task_type + summary['subtype'] = task_subtype + summary.to_csv(summary_path, index=False) + self.done = True return { From c2fb882e9a1b336e8e5da4e63004bab6aab35483 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Fri, 14 Feb 2020 12:20:52 +0100 Subject: [PATCH 23/41] Update image versions. --- Dockerfile | 2 +- requirements.txt | 2 +- ta2/ta3/client.py | 2 +- tests/ta3/test_client.py | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/Dockerfile b/Dockerfile index a1dc092..2724134 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,4 +1,4 @@ -FROM registry.gitlab.com/datadrivendiscovery/images/primitives:ubuntu-bionic-python36-v2020.1.9-20200201-083256 +FROM registry.gitlab.com/datadrivendiscovery/images/primitives:ubuntu-bionic-python36-v2020.1.9-20200212-063959 ARG UID=1000 ARG D3MPORT=45042 diff --git a/requirements.txt b/requirements.txt index 074a0e7..ded470e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,2 @@ --e git+https://gitlab.com/datadrivendiscovery/ta3ta2-api.git@ef803f908edb1b41457eaed6079346b7b6317646#egg=ta3ta2-api +-e git+https://gitlab.com/datadrivendiscovery/ta3ta2-api.git@1214abaac7cccd3f578e9589509b279bd820a758#egg=ta3ta2-api -e git+https://github.com/HDI-Project/BTB.git@6a08dc3cf1b68b35630cae6a87783aec4e2c9f83#egg=baytune diff --git a/ta2/ta3/client.py b/ta2/ta3/client.py index 0a01f32..071760e 100644 --- a/ta2/ta3/client.py +++ b/ta2/ta3/client.py @@ -53,7 +53,7 @@ def search_solutions(self, dataset, time_bound_search=1.): request = core_pb2.SearchSolutionsRequest( user_agent='ta3_api_test.py', - version='2020.1.28', + version='2020.2.11', time_bound_search=time_bound_search, priority=0., allowed_value_types=[ diff --git a/tests/ta3/test_client.py b/tests/ta3/test_client.py index c9ec0ea..abba804 100644 --- a/tests/ta3/test_client.py +++ b/tests/ta3/test_client.py @@ -54,7 +54,7 @@ def test_apiclient_search_solutions(search_solutions_request_mock, logger_mock): search_solutions_request_mock.assert_called_once_with( user_agent='ta3_api_test.py', - version='2020.1.28', + version='2020.2.11', time_bound_search=1., priority=0., allowed_value_types=[ From c50148a063f7318f53413f8e42810a6d52a12ae5 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Fri, 14 Feb 2020 12:50:15 +0100 Subject: [PATCH 24/41] Update new templates --- ta2/templates/{b1c2d5b9fcd0.json => 0011d757eabe.json} | 2 +- ta2/templates/00ca0172a464.json | 1 + ta2/templates/{b2867f4e776f.json => 015fc1139b5e.json} | 2 +- ta2/templates/{9a78bda2bbb1.json => 01cbe0574935.json} | 2 +- ta2/templates/{e17750009a4d.json => 025fe8f5fa15.json} | 2 +- ta2/templates/{d5287b763b72.json => 027b1a15dfca.json} | 2 +- ta2/templates/{fe0efc042a2f.json => 03329466099b.json} | 2 +- ta2/templates/{e7928f5ee1e2.json => 03ca53ce20e2.json} | 2 +- ta2/templates/{d49f9b8f72ec.json => 03f1618c79f3.json} | 2 +- ta2/templates/{71340620ee97.json => 040d80482c88.json} | 2 +- ta2/templates/{cb3c1dd2cfb0.json => 053c9d0ae43f.json} | 2 +- ta2/templates/{bf3db4470838.json => 063f20d3c246.json} | 2 +- ta2/templates/{6a526d5fa3b6.json => 07093247c3dc.json} | 2 +- ta2/templates/{8b6ec8b3ce30.json => 0761ad38fe15.json} | 2 +- ta2/templates/{e34ea4fb2870.json => 0764c3fc0010.json} | 2 +- ta2/templates/{30fa5eb06966.json => 07a34c04becf.json} | 2 +- ta2/templates/{0cfa68ecb397.json => 07afe4a3fadf.json} | 2 +- ta2/templates/{9e5cd905f15f.json => 081dd3c056b0.json} | 2 +- ta2/templates/081ef912c993.json | 1 + ta2/templates/{0acf807642d0.json => 08326dac33b5.json} | 2 +- ta2/templates/{605a5d3719c8.json => 08947f937c39.json} | 2 +- ta2/templates/{e6c2f9f5b4a5.json => 0a20d587980a.json} | 2 +- ta2/templates/{ee25da22df91.json => 0aa479b63c8c.json} | 2 +- ta2/templates/{e5b9ce037382.json => 0b27b36d3d16.json} | 2 +- ta2/templates/{252545f83815.json => 0b8f88adba5d.json} | 2 +- ta2/templates/{db73f636e06f.json => 0c440a48fa5c.json} | 2 +- ta2/templates/{e861f165eee4.json => 0e5d1078fa78.json} | 2 +- ta2/templates/{f18c576b83a1.json => 0f7a61df90a6.json} | 2 +- ta2/templates/{0d9327ae06a5.json => 0f8bb4d0e41a.json} | 2 +- ta2/templates/{4b0ee612067c.json => 0fe905d11e6d.json} | 2 +- ta2/templates/{20865f9f9a97.json => 101ce988402f.json} | 2 +- ta2/templates/1272d97872b6.json | 1 + ta2/templates/{a9f8e1eec224.json => 127509fe23b9.json} | 2 +- ta2/templates/{4483f41428c8.json => 12c9595e773d.json} | 2 +- ta2/templates/12e40a4d8fa2.json | 1 + ta2/templates/{c498347364a5.json => 138d9408e3c3.json} | 2 +- ta2/templates/{c96f60fefa99.json => 13cc4e4f386d.json} | 2 +- ta2/templates/{aa73bfdde625.json => 13ce89a9839a.json} | 2 +- ta2/templates/{9d39e376e417.json => 1411e0f0987e.json} | 2 +- ta2/templates/{0853247f0495.json => 17e157a660eb.json} | 2 +- ta2/templates/1b321c209ea6.json | 1 - ta2/templates/{5368952090b8.json => 1d4a55df2f7e.json} | 2 +- ta2/templates/{1bc0bc8b2393.json => 1d6f2e48694f.json} | 2 +- ta2/templates/{f6ca7062072a.json => 1d73e2c87754.json} | 2 +- ta2/templates/{e65cf4c42331.json => 1d912938f8f8.json} | 2 +- ta2/templates/{35b6bc261e31.json => 1d9290b3de8b.json} | 2 +- ta2/templates/{c4d10693ad0c.json => 1dc3356497ee.json} | 2 +- ta2/templates/{2e5904f93df2.json => 1fd27e5da08a.json} | 2 +- ta2/templates/{3c9310e77923.json => 20a2f15eb88d.json} | 2 +- ta2/templates/{6e98be622beb.json => 20e630fc48a9.json} | 2 +- ta2/templates/{a9b3ad71b03d.json => 22061ae5e39e.json} | 2 +- ta2/templates/{0cc86ff1ef5c.json => 222ee9b892c3.json} | 2 +- ta2/templates/{c774ac6e77fa.json => 227b1da48cdc.json} | 2 +- ta2/templates/{2e0a91949e3f.json => 238692983a8f.json} | 2 +- ta2/templates/23d96bee14d1.json | 1 + ta2/templates/257885470a30.json | 1 - ta2/templates/25b47ca1cf9f.json | 1 + ta2/templates/{d5462b2c3364.json => 25eb17d5c1c0.json} | 2 +- ta2/templates/{c6a2c86d97ac.json => 268f4a305d8f.json} | 2 +- ta2/templates/{5ecfd3c48bfc.json => 27a3ad3168ac.json} | 2 +- ta2/templates/{8e51d9f033e1.json => 2919b3904c1e.json} | 2 +- ta2/templates/{8218549398b0.json => 2a014d12163d.json} | 2 +- ta2/templates/{286936fe2c30.json => 2a7935ef10f2.json} | 2 +- 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efde449dcf14.json} | 2 +- ta2/templates/f0926834f262.json | 1 + ta2/templates/{9130298cf8cc.json => f136d0db3014.json} | 2 +- ta2/templates/{92a25af3c9db.json => f16a61396fce.json} | 2 +- ta2/templates/{87297c1d1568.json => f2ff1a7f8523.json} | 2 +- ta2/templates/{fc8ade5f4b48.json => f3f0229322ba.json} | 2 +- ta2/templates/{98f4c2a952b1.json => f4c39842d2cf.json} | 2 +- ta2/templates/{0fa1998d89ad.json => f537eabc18d6.json} | 2 +- ta2/templates/{1d7d491a3501.json => f5a5c95a619f.json} | 2 +- ta2/templates/{6582e4ec3c35.json => f8970e09a9a0.json} | 2 +- ta2/templates/{562e499460bb.json => f94b22d097cc.json} | 2 +- ta2/templates/{591658b9cdd1.json => f99eb740e9df.json} | 2 +- ta2/templates/{bfda7a5af85e.json => fa9b7845a7bb.json} | 2 +- ta2/templates/{279daac6d4e5.json => fc38baad1420.json} | 2 +- ta2/templates/{ef95cef72e40.json => fe25627c20e3.json} | 2 +- ta2/templates/{ac4f2268d86c.json => ff11384e1587.json} | 2 +- 297 files changed, 283 insertions(+), 273 deletions(-) rename ta2/templates/{b1c2d5b9fcd0.json => 0011d757eabe.json} (79%) create mode 100644 ta2/templates/00ca0172a464.json rename ta2/templates/{b2867f4e776f.json => 015fc1139b5e.json} (77%) rename ta2/templates/{9a78bda2bbb1.json => 01cbe0574935.json} (82%) rename ta2/templates/{e17750009a4d.json => 025fe8f5fa15.json} (74%) rename ta2/templates/{d5287b763b72.json => 027b1a15dfca.json} (78%) rename ta2/templates/{fe0efc042a2f.json => 03329466099b.json} (74%) rename ta2/templates/{e7928f5ee1e2.json => 03ca53ce20e2.json} (83%) rename ta2/templates/{d49f9b8f72ec.json => 03f1618c79f3.json} (83%) rename ta2/templates/{71340620ee97.json => 040d80482c88.json} (82%) rename ta2/templates/{cb3c1dd2cfb0.json => 053c9d0ae43f.json} (82%) rename ta2/templates/{bf3db4470838.json => 063f20d3c246.json} (82%) rename ta2/templates/{6a526d5fa3b6.json => 07093247c3dc.json} (78%) rename ta2/templates/{8b6ec8b3ce30.json => 0761ad38fe15.json} (81%) rename ta2/templates/{e34ea4fb2870.json => 0764c3fc0010.json} (81%) 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A & M University,Normal,AL,www.aamu.edu/,www2.aamu.edu/scripts/netpricecalc/npcalc.htm,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,380.0,470.0,370.0,470.0,370.0,457.0,425.0,420.0,414.0,16.0,19.0,14.0,20.0,15.0,18.0,,,18.0,17.0,17.0,,849.0,849.0,0.0448,0.0142,0.0071,0.0,0.0,0.0354,0.0401,0.0,0.1132,0.0896,0.0472,0.0,0.033,0.0,0.0094,0.066,0.0,0.0708,0.0024,0.0,0.0,0.0,0.0,0.0,0.0307,0.0,0.0472,0.0519,0.0377,0.0448,0.0,0.0,0.0,0.0,0.0283,0.0,0.1863,0.0,0.0,4616.0,0.0256,0.9129,0.0076,0.0019,0.0024,0.0017,0.0401,0.0065,0.0013,0.0877,1,15567.0,,15043.0,15491.0,17335.0,19562.0,18865.0,,,,,,0.7039,0.5774,,0.309,,0.7667,0.0859,31000,0.453,0.431,32750,348.16551225731,0.2531554273,,0.2913,Q39624632,Q17203888,Q173,Q575407\\\\\\\\n1,100663,105200,1052,University of Alabama at Birmingham,Birmingham,AL,www.uab.edu,uab.studentaidcalculator.com/survey.aspx,0,3,4,1,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,480.0,640.0,490.0,660.0,,,560.0,575.0,,21.0,28.0,22.0,30.0,19.0,26.0,,,25.0,26.0,23.0,,1125.0,1125.0,0.0,0.0,0.0,0.0005,0.036000000000000004,0.0,0.0131,0.0,0.0748,0.0599,0.0,0.0059,0.0,0.0,0.0158,0.0135,0.0,0.0734,0.009000000000000001,0.0,0.0,0.0,0.005,0.0,0.0212,0.0,0.0766,0.0243,0.0221,0.0365,0.0,0.0,0.0,0.0,0.0392,0.25,0.2072,0.0162,0.0,12047.0,0.5786,0.2626,0.0309,0.0598,0.0028,0.0004,0.0387,0.0179,0.0083,0.2578,1,16475.0,,13849.0,15385.0,18022.0,18705.0,19319.0,,,,,,0.3525,0.8007,,0.5178,,0.5179,0.2363,41200,0.669,0.631,21833,232.106797835537,0.513963161,,0.5384,Q39624677,Q17204336,Q173,Q79867\\\\\\\\n2,100690,2503400,25034,Amridge 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University,Montgomery,AL,www.alasu.edu,www.alasu.edu/cost-aid/forms/calculator/index.aspx,0,3,4,1,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,370.0,460.0,360.0,460.0,,,415.0,410.0,,15.0,19.0,14.0,19.0,15.0,17.0,,,17.0,17.0,16.0,,825.0,825.0,0.0,0.0,0.0,0.0,0.1023,0.0,0.0503,0.0,0.1364,0.0,0.0,0.0,0.0,0.0,0.0114,0.0,0.0,0.0779,0.0146,0.0,0.0,0.0211,0.0,0.0,0.0244,0.0,0.0503,0.1412,0.0633,0.013000000000000001,0.0,0.0,0.0,0.0,0.0487,0.1429,0.0974,0.0049,0.0,4704.0,0.0138,0.9337,0.0111,0.0028,0.0013,0.0004,0.0111,0.0159,0.01,0.0727,1,15037.0,,14111.0,15140.0,17492.0,19079.0,18902.0,,,,,,0.7815,0.6138,,0.5313,,0.8113,0.0974,27700,0.393,0.351,31500,334.876752247489,0.2185867473,,0.2475,Q39624974,Q17203904,Q173,Q29364\\\\\\\\n5,100751,105100,1051,The University of Alabama,Tuscaloosa,AL,www.ua.edu/,financialaid.ua.edu/net-price-calculator/,0,3,4,1,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,490.0,610.0,490.0,620.0,480.0,600.0,550.0,555.0,540.0,23.0,31.0,23.0,33.0,22.0,29.0,7.0,8.0,27.0,28.0,26.0,8.0,1202.0,1202.0,0.0,0.0039,0.0,0.0042,0.102,0.0,0.0098,0.0,0.0782,0.1036,0.0,0.0057,0.0692,0.0,0.0115,0.0,0.0,0.0338,0.009000000000000001,0.0,0.0206,0.0,0.0031,0.0,0.0115,0.0,0.036000000000000004,0.0263,0.0109,0.0362,0.0,0.0,0.0,0.0,0.026000000000000002,0.0988,0.2879,0.0118,0.0,31663.0,0.7841,0.1037,0.0437,0.0118,0.0036,0.0009,0.0297,0.0192,0.0033,0.0819,1,21676.0,,18686.0,20013.0,22425.0,23666.0,24578.0,,,,,,0.1938,0.8637,,0.4308,,0.4007,0.081,44500,0.695,0.679,23290,247.596176502985,0.6019442985,,0.6793,Q39625107,Q17204328,Q173,Q79580\\\\\\\\n6,100760,100700,1007,Central Alabama Community College,Alexander City,AL,www.cacc.edu,www.cacc.edu/NetPriceCalculator/14-15/npcalc.html,0,2,2,1,32.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0266,0.0082,0.0,0.0,0.1025,0.0,0.0,0.0,0.0,0.2787,0.0,0.0,0.0,0.0,0.0287,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0307,0.3176,0.0,0.0,0.1209,0.0861,0.0,0.0,1492.0,0.6877,0.2802,0.0127,0.002,0.004,0.0007,0.0067,0.002,0.004,0.3733,1,9128.0,,8882.0,8647.0,11681.0,11947.0,13868.0,,,,,,0.5109,,0.5666,,0.4554,0.3234,0.263,27700,0.466,0.395,9500,100.994576074639,0.2510056315,0.2136,,Q39625150,Q17203916,Q173,Q79663\\\\\\\\n7,100812,100800,1008,Athens State University,Athens,AL,www.athens.edu,https://24.athens.edu/apex/prod8/f?p=174:1:3941357449598491,0,3,3,1,31.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,0.0,0.0,0.0462,0.0,0.2192,0.0,0.0,0.0,0.0,0.0,0.0346,0.0538,0.0,0.0231,0.0205,0.0,0.0154,0.0154,0.0038,0.0,0.0026,0.0,0.0308,0.0282,0.0,0.0218,0.0,0.0,0.0,0.0,0.0256,0.0064,0.4449,0.0077,0.0,2888.0,0.7784,0.125,0.0215,0.0076,0.0142,0.001,0.0187,0.001,0.0325,0.5817,1,,,,,,,,,,,,,0.4219,,,,,0.6455,0.6774,38700,0.653,0.612,18000,191.358144141422,0.5038167939,,,Q39625389,Q17203920,Q173,Q203263\\\\\\\\n8,100830,831000,8310,Auburn University at 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"primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.Common", "name": "Construct pipeline predictions output", "digest": "ebd5ef709535e6b21759e08cb5cd19bffd040f1a16b6e4ce7bece1a1a97776d5"}, "arguments": {"reference": {"type": "CONTAINER", "data": "steps.1.produce"}, "inputs": {"type": "CONTAINER", "data": "steps.3.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "d488ee46accc118640dbb6f9ca80be77c68cd2200f4d94b3ddb285abf3ac4ebe"} \ No newline at end of file diff --git a/ta2/curated_templates/de5c6e65bc18.json b/ta2/curated_templates/de5c6e65bc18.json new file mode 100644 index 0000000..5ccfee5 --- /dev/null +++ b/ta2/curated_templates/de5c6e65bc18.json @@ -0,0 +1 @@ +{"id": "", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2016-11-11T12:30:00Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.5.produce", "name": "output 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["https://metadata.datadrivendiscovery.org/types/TrueTarget"]}}}, {"type": "PRIMITIVE", "primitive": {"id": "dsbox-featurizer-object-detection-yolo", "version": "1.5.3", "python_path": "d3m.primitives.feature_extraction.yolo.DSBOX", "name": "DSBox Object Detection YOLO", "digest": "9f6644bc40a856387a48ebfcd03a6af27faf5f9b690eb9759763e3d625dc758a"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.3.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.Common", "name": "Construct pipeline predictions output", "digest": "ebd5ef709535e6b21759e08cb5cd19bffd040f1a16b6e4ce7bece1a1a97776d5"}, "arguments": {"reference": {"type": "CONTAINER", "data": "steps.1.produce"}, "inputs": {"type": "CONTAINER", "data": "steps.4.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "de5c6e65bc1892221e0aec6bc84acce6b038566f3d35be86d90e6a57a0ce890e"} \ No newline at end of file From 7c2355cf425afc9dfe2c4f3e7713bf054620bc05 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Fri, 14 Feb 2020 21:41:49 +0100 Subject: [PATCH 26/41] Load curated first. --- ta2/search.py | 18 +++++++++++++++--- 1 file changed, 15 insertions(+), 3 deletions(-) diff --git a/ta2/search.py b/ta2/search.py index 37cc5b9..38e4776 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -25,6 +25,7 @@ BASE_DIR = os.path.abspath(os.path.dirname(__file__)) PIPELINES_DIR = os.path.join(BASE_DIR, 'pipelines') TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') +CURATED_TEMPLATES_DIR = os.path.join(BASE_DIR, 'curated_templates') DATAMART_URL = os.getenv('DATAMART_URL_NYU', 'https://datamart.d3m.vida-nyu.org') @@ -115,21 +116,32 @@ def _load_pipeline(self, pipeline): with open(path, 'r') as pipeline_file: return loader(string_or_file=pipeline_file) - def _get_all_templates(self): + def _get_valid_templates(self, templates): valid_templates = [] - templates = os.listdir(TEMPLATES_DIR) for template in templates: try: path = os.path.join(TEMPLATES_DIR, template) with open(path, 'r') as f: json.load(f) - valid_templates.append(template) except: LOGGER.warning('Invalid template found: %s', path) return valid_templates + def _get_all_templates(self): + curated = [ + os.path.join(CURATED_TEMPLATES_DIR, temp) + for temp in os.listdir(CURATED_TEMPLATES_DIR) + ] + + curated_templates = self._get_valid_templates(curated) + templates = self._get_valid_templates(os.listdir(TEMPLATES_DIR)) + + curated_templates.extend(templates) + + return curated_templates + def _get_templates(self): LOGGER.info('Loading template for dataset %s', dataset_name) From d6502fb96683395bda917d03e8ffc8e5df8cc842 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Fri, 14 Feb 2020 21:44:07 +0100 Subject: [PATCH 27/41] Update winter evaluation repo. --- Makefile | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/Makefile b/Makefile index 127e26c..c8aefbb 100644 --- a/Makefile +++ b/Makefile @@ -231,8 +231,8 @@ build: ## build the mit-d3m-ta2 docker image .PHONY: submit submit: login build ## push to TA2 submission registry - docker tag mit-d3m-ta2:latest registry.datadrivendiscovery.org/ta2-submissions/ta2-mit/december2019 - docker push registry.datadrivendiscovery.org/ta2-submissions/ta2-mit/december2019 + docker tag mit-d3m-ta2:latest registry.datadrivendiscovery.org/ta2-submissions/ta2-mit/winter2020evaluation + docker push registry.datadrivendiscovery.org/ta2-submissions/ta2-mit/winter2020evaluation .PHONY: submit-ci submit-ci: login build ## push to TA2 submission registry From a0934f7a13136b0a2ac13b12bcd9e36fb03cb498 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Fri, 14 Feb 2020 22:27:40 +0100 Subject: [PATCH 28/41] select templates + random --- ta2/search.py | 58 +++++++++++---------------------- ta2/templates/2e1ad943e48d.json | 1 + ta2/templates/51b57228251e.json | 1 + ta2/templates/8e6d327bf366.json | 1 + ta2/templates/cf24005807b8.json | 1 + ta2/templates/d488ee46accc.json | 1 + ta2/templates/de5c6e65bc18.json | 1 + 7 files changed, 25 insertions(+), 39 deletions(-) create mode 100644 ta2/templates/2e1ad943e48d.json create mode 100644 ta2/templates/51b57228251e.json create mode 100644 ta2/templates/8e6d327bf366.json create mode 100644 ta2/templates/cf24005807b8.json create mode 100644 ta2/templates/d488ee46accc.json create mode 100644 ta2/templates/de5c6e65bc18.json diff --git a/ta2/search.py b/ta2/search.py index 38e4776..3e07c19 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -116,48 +116,28 @@ def _load_pipeline(self, pipeline): with open(path, 'r') as pipeline_file: return loader(string_or_file=pipeline_file) - def _get_valid_templates(self, templates): - valid_templates = [] - for template in templates: - try: - path = os.path.join(TEMPLATES_DIR, template) - with open(path, 'r') as f: - json.load(f) - valid_templates.append(template) - except: - LOGGER.warning('Invalid template found: %s', path) - - return valid_templates - - def _get_all_templates(self): - curated = [ - os.path.join(CURATED_TEMPLATES_DIR, temp) - for temp in os.listdir(CURATED_TEMPLATES_DIR) - ] - - curated_templates = self._get_valid_templates(curated) - templates = self._get_valid_templates(os.listdir(TEMPLATES_DIR)) - - curated_templates.extend(templates) - - return curated_templates - - def _get_templates(self): - LOGGER.info('Loading template for dataset %s', dataset_name) - - df = pd.read_csv(os.path.join(TEMPLATES_DIR, 'templates_with_z_score.csv')) + def _valid_template(self, template): + try: + path = os.path.join(TEMPLATES_DIR, template) + with open(path, 'r') as f: + json.load(f) + return True - templates = df[df['name'] == dataset_name].sort_values('z_score', ascending=False) + except Exception: + LOGGER.warning('Invalid template found: %s', path) + return False - problem_type = '{}_{}'.format(data_modality, task_type) - df['match'] = df['name'] == dataset_name - templates = df[df['problem_type'] == problem_type] - templates = templates.sort_values(['match', 'z_score'], ascending=False) - templates = templates.drop_duplicates(subset=['pipeline_id'], keep='first') + def _select_templates(self, data_modality, task_type): + # TODO + return list(filter(self._valid_template, [])) - self.found_by_name = df['match'].any() + def _get_templates(self, data_modality, task_type): + selected = self._select_templates(data_modality, task_type) + if selected: + return selected - return templates.pipeline_id.values + all_templates = list(filter(self._valid_template, os.listdir(TEMPLATES_DIR))) + return random.sample(all_templates, len(all_templates)) def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, @@ -480,7 +460,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non self.setup_search() LOGGER.info("Loading the template and the tuner") if not template_names: - template_names = self._get_all_templates() + template_names = self._get_templates(data_modality, task_type) template_loader = LazyLoader(template_names, TEMPLATES_DIR) btb_scorer = self.make_btb_scorer( diff --git a/ta2/templates/2e1ad943e48d.json b/ta2/templates/2e1ad943e48d.json new file mode 100644 index 0000000..7ca6310 --- /dev/null +++ b/ta2/templates/2e1ad943e48d.json @@ -0,0 +1 @@ +{"id": "", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2016-11-11T12:30:00Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.4.produce", "name": "output predictions"}], "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", "digest": 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file From f7447e1d1f64dc71188a5cd2a1b7be58883406b2 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Sat, 15 Feb 2020 23:02:04 +0100 Subject: [PATCH 29/41] Add template selection --- Dockerfile | 2 +- ta2/search.py | 20 +- ta2/templates.csv | 4388 +++++++++++++++++++++++++++++++++++++++++++++ ta2/timeouts.csv | 844 +++++++++ 4 files changed, 5251 insertions(+), 3 deletions(-) create mode 100644 ta2/templates.csv create mode 100644 ta2/timeouts.csv diff --git a/Dockerfile b/Dockerfile index 2724134..6e6992c 100644 --- a/Dockerfile +++ b/Dockerfile @@ -22,6 +22,6 @@ COPY setup.py MANIFEST.in /user_dev/ RUN pip3 install -e /user_dev ipdb COPY ta2 /user_dev/ta2 -RUN chown -R $UID:$UID /user_dev +# RUN chown -R $UID:$UID /user_dev CMD ["python3", "/user_dev/ta2/ta3/server.py", "-v"] diff --git a/ta2/search.py b/ta2/search.py index 3e07c19..81c4274 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -25,6 +25,7 @@ BASE_DIR = os.path.abspath(os.path.dirname(__file__)) PIPELINES_DIR = os.path.join(BASE_DIR, 'pipelines') TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') +TEMPLATES_CSV = os.path.join(BASE_DIR, 'templates.csv') CURATED_TEMPLATES_DIR = os.path.join(BASE_DIR, 'curated_templates') DATAMART_URL = os.getenv('DATAMART_URL_NYU', 'https://datamart.d3m.vida-nyu.org') @@ -128,8 +129,19 @@ def _valid_template(self, template): return False def _select_templates(self, data_modality, task_type): - # TODO - return list(filter(self._valid_template, [])) + templates = pd.read_csv(TEMPLATES_CSV) + problem_type = data_modality + '/' + task_type + problem_templates = templates[templates.problem_type == problem_type] + + z_scores = problem_templates.groupby('template').z_score.mean() + selected = z_scores.sort_values(ascending=False).index + + return list(filter(self._valid_template, selected)) + + def _get_timeouts(self, dataset_name): + templates = pd.read_csv(os.path.join(BASE_DIR, 'timeouts.csv')) + selected = templates[templates.dataset == dataset_name] + return list(filter(self._valid_template, selected.template)) def _get_templates(self, data_modality, task_type): selected = self._select_templates(data_modality, task_type) @@ -461,7 +473,11 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non LOGGER.info("Loading the template and the tuner") if not template_names: template_names = self._get_templates(data_modality, task_type) + # Execute TIMEOUT templates only + # template_names = self._get_timeouts(dataset_name) + # self.budget = len(template_names) + LOGGER.warning('Selected %s templates', len(template_names)) template_loader = LazyLoader(template_names, TEMPLATES_DIR) btb_scorer = self.make_btb_scorer( dataset_name, dataset, problem, template_loader, metric) diff --git a/ta2/templates.csv b/ta2/templates.csv new file mode 100644 index 0000000..74cacfd --- /dev/null +++ b/ta2/templates.csv @@ -0,0 +1,4388 @@ +template,status,score,normalized,dataset,data_modality,type,subtype,problem_type,z_score 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+3078df01a001.json,TIMEOUT,,,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification +0a20d587980a.json,TIMEOUT,,,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification +cdc19b5d1983.json,TIMEOUT,,,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification From 25987f1898d538ede826f550023201b8e941df88 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Sat, 15 Feb 2020 23:42:30 +0100 Subject: [PATCH 30/41] use the winner templates only --- ta2/search.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/ta2/search.py b/ta2/search.py index 81c4274..916cb73 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -133,7 +133,10 @@ def _select_templates(self, data_modality, task_type): problem_type = data_modality + '/' + task_type problem_templates = templates[templates.problem_type == problem_type] - z_scores = problem_templates.groupby('template').z_score.mean() + problem_templates = problem_templates.sort_values('z_score', ascending=False) + problem_winners = problem_templates.groupby('dataset').head(3) + + z_scores = problem_winners.groupby('template').z_score.mean() selected = z_scores.sort_values(ascending=False).index return list(filter(self._valid_template, selected)) From c0b6f596829e4c83b8526ac8d7b4dd96b04b80fc Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Sun, 16 Feb 2020 17:28:09 +0100 Subject: [PATCH 31/41] Template selection and fallback to all --- requirements.txt | 2 +- ta2/search.py | 75 +- ta2/templates.csv | 5307 +++++++++++++++++++++++---------------------- 3 files changed, 2698 insertions(+), 2686 deletions(-) diff --git a/requirements.txt b/requirements.txt index ded470e..630b116 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,2 @@ -e git+https://gitlab.com/datadrivendiscovery/ta3ta2-api.git@1214abaac7cccd3f578e9589509b279bd820a758#egg=ta3ta2-api --e git+https://github.com/HDI-Project/BTB.git@6a08dc3cf1b68b35630cae6a87783aec4e2c9f83#egg=baytune +-e git+https://github.com/HDI-Project/BTB.git@31c6349932accd6b168ad2d00af6b4110e8c4a66#egg=baytune diff --git a/ta2/search.py b/ta2/search.py index 916cb73..106fcf6 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -11,7 +11,8 @@ import numpy as np import pandas as pd -from btb.session import BTBSession +from btb import BTBSession +from btb.tuning import StopTuning from d3m.metadata.base import ArgumentType, Context from d3m.metadata.pipeline import Pipeline, PrimitiveStep from d3m.runtime import DEFAULT_SCORING_PIPELINE_PATH @@ -141,19 +142,15 @@ def _select_templates(self, data_modality, task_type): return list(filter(self._valid_template, selected)) + def _get_all_templates(self): + all_templates = list(filter(self._valid_template, os.listdir(TEMPLATES_DIR))) + return random.sample(all_templates, len(all_templates)) + def _get_timeouts(self, dataset_name): templates = pd.read_csv(os.path.join(BASE_DIR, 'timeouts.csv')) selected = templates[templates.dataset == dataset_name] return list(filter(self._valid_template, selected.template)) - def _get_templates(self, data_modality, task_type): - selected = self._select_templates(data_modality, task_type) - if selected: - return selected - - all_templates = list(filter(self._valid_template, os.listdir(TEMPLATES_DIR))) - return random.sample(all_templates, len(all_templates)) - def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, subprocess_timeout=None, max_errors=0, store_summary=False): @@ -380,7 +377,7 @@ def get_data_augmentation(self, dataset, problem): # with open(os.path.join(BASE_DIR, 'da.json')) as f: # return json.dumps(json.load(f)) - def make_btb_scorer(self, dataset_name, dataset, problem, templates, metric): + def make_btb_scorer(self, dataset, problem, templates, metric): def btb_scorer(template_name, proposal): self.check_stop() self.iterations += 1 @@ -438,6 +435,28 @@ def btb_scorer(template_name, proposal): return btb_scorer + def start_session(self, template_names, dataset, problem, metric): + LOGGER.warning('Selected %s templates', len(template_names)) + template_loader = LazyLoader(template_names, TEMPLATES_DIR) + btb_scorer = self.make_btb_scorer(dataset, problem, template_loader, metric) + + session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) + + if self.budget is not None: + while self.spent < self.budget: + session.run(1) + last_score = list(session.proposals.values())[-1].get('score') + if (last_score is None) and self.ignore_errors: + LOGGER.warning("Ignoring errored pipeline") + else: + self.spent += 1 + + LOGGER.warn('its: %s; sc: %s; er: %s; in: %s; ti: %s', self.iterations, + self.scored, self.errored, self.invalid, self.timedout) + + else: + session.run() + def search(self, dataset, problem, timeout=None, budget=None, template_names=None): self.timeout = timeout self.killed = False @@ -451,6 +470,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non data_modality = None task_type = None task_subtype = None + self.spent = 0 self.iterations = 0 self.scored = 0 self.errored = 0 @@ -475,33 +495,22 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non self.setup_search() LOGGER.info("Loading the template and the tuner") if not template_names: - template_names = self._get_templates(data_modality, task_type) + template_names = self._select_templates(data_modality, task_type) # Execute TIMEOUT templates only # template_names = self._get_timeouts(dataset_name) # self.budget = len(template_names) - LOGGER.warning('Selected %s templates', len(template_names)) - template_loader = LazyLoader(template_names, TEMPLATES_DIR) - btb_scorer = self.make_btb_scorer( - dataset_name, dataset, problem, template_loader, metric) - - session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) - - if self.budget is not None: - spent = 0 - while spent < self.budget: - session.run(1) - last_score = list(session.proposals.values())[-1].get('score') - if (last_score is None) and self.ignore_errors: - LOGGER.warning("Ignoring errored pipeline") - else: - spent += 1 - - LOGGER.warn('its: %s; sc: %s; er: %s; in: %s; ti: %s', self.iterations, - self.scored, self.errored, self.invalid, self.timedout) - - else: - session.run() + try: + self.start_session(template_names, dataset, problem, metric) + except StopTuning: + LOGGER.warning('All selected templates failed. Falling back to the rest') + all_templates = self._get_all_templates() + untried_templates = [ + template + for template in all_templates + if template not in template_names + ] + self.start_session(untried_templates, dataset, problem, metric) except KeyboardInterrupt: pass diff --git a/ta2/templates.csv b/ta2/templates.csv index 74cacfd..18fb35b 100644 --- a/ta2/templates.csv +++ b/ta2/templates.csv @@ -1,42 +1,42 @@ template,status,score,normalized,dataset,data_modality,type,subtype,problem_type,z_score -227b1da48cdc.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 0a20d587980a.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -ac4d343c1438.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 -cf5730d14818.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 -2919b3904c1e.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 9ae530dbe284.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -03329466099b.json,SCORED,0.27068000000000003,0.27068000000000003,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,2.28134042458066 025fe8f5fa15.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 36f1b78c3053.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 +2a014d12163d.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 +f3f0229322ba.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 +899f290bbc93.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 +227b1da48cdc.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 +ac4d343c1438.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 +cf5730d14818.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 +2919b3904c1e.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 85b309b60b64.json,SCORED,0.09748,0.09748,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,0.2219272660796737 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5ec028e7cfa7.json,SCORED,0.0,0.0,124_214_coil20_MIN_METADATA,image,classification,multiclass,image/classification,0.0 @@ -79,287 +79,281 @@ ba23d7ed6820.json,SCORED,0.0,0.0,124_95_uc_merced_land_use_MIN_METADATA,image,cl a4ebd1b8c6dc.json,SCORED,0.0,0.0,124_95_uc_merced_land_use_MIN_METADATA,image,classification,multiclass,image/classification,0.0 85b309b60b64.json,SCORED,0.0,0.0,124_95_uc_merced_land_use_MIN_METADATA,image,classification,multiclass,image/classification,0.0 f16a61396fce.json,SCORED,0.0,0.0,124_95_uc_merced_land_use_MIN_METADATA,image,classification,multiclass,image/classification,0.0 -4b3142146f1b.json,SCORED,0.007009053621448579,0.007009053621448579,1491_one_hundred_plants_margin_MIN_METADATA,single_table,classification,multiclass,single_table/classification,1.0246575797867268 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f94b22d097cc.json,SCORED,0.0,0.0,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,-0.9966913865949316 -5ec028e7cfa7.json,SCORED,0.32769873244684194,0.32769873244684194,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,1.8614904584614416 +03ca53ce20e2.json,SCORED,0.0,0.0,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,-0.9966913865949316 +9ae530dbe284.json,SCORED,0.0,0.0,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,-0.9966913865949316 +ba23d7ed6820.json,SCORED,0.1002685449507777,0.1002685449507777,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,-0.12215112618968102 cf5730d14818.json,SCORED,0.1002685449507777,0.1002685449507777,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,-0.12215112618968102 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+03329466099b.json,SCORED,0.32769873244684194,0.32769873244684194,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,1.8614904584614416 +5ec028e7cfa7.json,SCORED,0.32769873244684194,0.32769873244684194,uu_101_object_categories_MIN_METADATA,image,classification,multiclass,image/classification,1.8614904584614416 From f5323501bb9ca71b92c0ee8763fb6be65eba25cf Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Sun, 16 Feb 2020 18:12:02 +0100 Subject: [PATCH 32/41] Improve template selection --- ta2/search.py | 22 ++++++++++++++-------- 1 file changed, 14 insertions(+), 8 deletions(-) diff --git a/ta2/search.py b/ta2/search.py index 106fcf6..89a2450 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -129,16 +129,22 @@ def _valid_template(self, template): LOGGER.warning('Invalid template found: %s', path) return False - def _select_templates(self, data_modality, task_type): + def _select_templates(self, dataset_name, data_modality, task_type): templates = pd.read_csv(TEMPLATES_CSV) - problem_type = data_modality + '/' + task_type - problem_templates = templates[templates.problem_type == problem_type] + dataset_templates = templates[templates.dataset == dataset_name] + if not dataset_templates.empty: + dataset_templates = dataset_templates.groupby('template').z_score.max() + selected = dataset_templates.sort_values(ascending=False).index - problem_templates = problem_templates.sort_values('z_score', ascending=False) - problem_winners = problem_templates.groupby('dataset').head(3) + else: + problem_type = data_modality + '/' + task_type + problem_templates = templates[templates.problem_type == problem_type] + + problem_templates = problem_templates.sort_values('z_score', ascending=False) + problem_winners = problem_templates.groupby('dataset').head(3) - z_scores = problem_winners.groupby('template').z_score.mean() - selected = z_scores.sort_values(ascending=False).index + z_scores = problem_winners.groupby('template').z_score.mean() + selected = z_scores.sort_values(ascending=False).index return list(filter(self._valid_template, selected)) @@ -495,7 +501,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non self.setup_search() LOGGER.info("Loading the template and the tuner") if not template_names: - template_names = self._select_templates(data_modality, task_type) + template_names = self._select_templates(dataset_name, data_modality, task_type) # Execute TIMEOUT templates only # template_names = self._get_timeouts(dataset_name) # self.budget = len(template_names) From e8e6cf5e78a79c0ecaa247f945bbd822a43112fc Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Sun, 16 Feb 2020 19:16:19 +0100 Subject: [PATCH 33/41] Upload old tempaltes to new structure --- ta2/templates/03e8e75698d6.json | 1 + ta2/templates/05f103916567.json | 1 + ta2/templates/114d6c40ae9f.json | 1 + ta2/templates/816ea7a09986.json | 1 + ta2/templates/9bb9ffcac9e7.json | 1 + ta2/templates/curated.csv | 27 +++++++++++++++++++++++++++ ta2/templates/d781ed63c51e.json | 1 + ta2/templates/dbd359409d05.json | 1 + 8 files changed, 34 insertions(+) create mode 100644 ta2/templates/03e8e75698d6.json create mode 100644 ta2/templates/05f103916567.json create mode 100644 ta2/templates/114d6c40ae9f.json create mode 100644 ta2/templates/816ea7a09986.json create mode 100644 ta2/templates/9bb9ffcac9e7.json create mode 100644 ta2/templates/curated.csv create mode 100644 ta2/templates/d781ed63c51e.json create mode 100644 ta2/templates/dbd359409d05.json diff --git a/ta2/templates/03e8e75698d6.json b/ta2/templates/03e8e75698d6.json new file mode 100644 index 0000000..534a067 --- /dev/null +++ b/ta2/templates/03e8e75698d6.json @@ -0,0 +1 @@ +{"id": "", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2016-11-11T12:30:00Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.8.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", 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"data": "new"}, "add_index_columns": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.Common", "name": "Construct pipeline predictions output", "digest": "0e578d95719e2d0863cb3cc38a6f2cd65d2b221c3292639c79d2331086c68f75"}, "arguments": {"reference": {"type": "CONTAINER", "data": "steps.2.produce"}, "inputs": {"type": "CONTAINER", "data": "steps.9.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "d781ed63c51e73073d3cf43737406e2a33e6023cd28ca78d2ecaf9bcee6a4e8d"} \ No newline at end of file diff --git a/ta2/templates/dbd359409d05.json b/ta2/templates/dbd359409d05.json new file mode 100644 index 0000000..8a7fe20 --- /dev/null +++ b/ta2/templates/dbd359409d05.json @@ -0,0 +1 @@ +{"id": "", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2016-11-11T12:30:00Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.5.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "5bef5738-1638-48d6-9935-72445f0eecdc", "version": "0.1.0", "python_path": "d3m.primitives.operator.dataset_map.DataFrameCommon", "name": "Map DataFrame resources to new resources using provided primitive", "digest": "8f94b675f2afa3ec5e8d54f38dd43180e925599303d0858a8205f98456768999"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}], "hyperparams": {"fit_primitive": {"type": "VALUE", "data": "no"}, "primitive": {"type": "VALUE", "data": {"case": "transformer", "value": {"class": "d3m.primitives.data_transformation.column_parser.Common"}}}, "resources": {"type": "VALUE", "data": {"case": "all", "value": "all"}}}}, {"type": "PRIMITIVE", "primitive": {"id": "e659ef3a-f17c-4bbf-9e5a-13de79a4e55b", "version": "0.7.0", "python_path": "d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization", "name": "Multi Table Deep Feature Synthesis", "digest": "26ab962133752ad8c55e915fdfbd956356a20b84a1a2e0312954cb6688eb1a68"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "6c5dcfa3-1f87-4066-b16a-88c9c971f6e3", "version": "0.7.0", "python_path": "d3m.primitives.feature_construction.deep_feature_synthesis.SingleTableFeaturization", "name": "Single Table Deep Feature Synthesis", "digest": "9fe7dd0d0bf76cc1e67f6e6ee82a5a119bae9ac36e4619d517dd133a5943e1ba"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d016df89-de62-3c53-87ed-c06bb6a23cde", "version": "2019.6.7", "python_path": "d3m.primitives.data_cleaning.imputer.SKlearn", "name": "sklearn.impute.SimpleImputer", "digest": "adc79e644eec35eb9d616be755a5de83b27f66e42b04f6508a9ceb82d99cc739"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"use_semantic_types": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "fe0841b7-6e70-4bc3-a56c-0670a95ebc6a", "version": "0.1.0", "python_path": "d3m.primitives.classification.xgboost_gbtree.Common", "name": "XGBoost GBTree classifier", "digest": "0483e07ef178862bfc0dbc0e6a85bda8937775a8090fb1dfeab15b34d3e33ffb"}, "arguments": {"outputs": {"type": "CONTAINER", "data": "steps.1.produce"}, "inputs": {"type": "CONTAINER", "data": "steps.3.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"n_jobs": {"type": "VALUE", "data": {"case": "all_cores", "value": -1}}}}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.Common", "name": "Construct pipeline predictions output", "digest": "0e578d95719e2d0863cb3cc38a6f2cd65d2b221c3292639c79d2331086c68f75"}, "arguments": {"reference": {"type": "CONTAINER", "data": "steps.1.produce"}, "inputs": {"type": "CONTAINER", "data": "steps.4.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "dbd359409d05b7af5a39c251e40e3be29e255d3a4ef2975450875d603dc6db2a"} \ No newline at end of file From 7ebffbf8eb46039ec2ad6530fb39b1815382d2d9 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Sun, 16 Feb 2020 19:22:58 +0100 Subject: [PATCH 34/41] Specify templates csv --- ta2/__main__.py | 7 ++-- ta2/curated.csv | 27 ++++++++++++++++ ta2/search.py | 68 +++++++++++++++++++++------------------ ta2/templates.csv | 2 +- ta2/templates/curated.csv | 27 ---------------- ta2/timeouts.csv | 2 +- 6 files changed, 68 insertions(+), 65 deletions(-) create mode 100644 ta2/curated.csv delete mode 100644 ta2/templates/curated.csv diff --git a/ta2/__main__.py b/ta2/__main__.py index bf75b57..8495d4c 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -175,7 +175,7 @@ def process_dataset(dataset_name, dataset, problem, args): max_errors=args.max_errors, store_summary=True ) - result = pps.search(dataset, problem, args.timeout, args.budget, args.template) + result = pps.search(dataset, problem, args.timeout, args.budget, args.templates_csv) result['elapsed'] = datetime.utcnow() - start_ts result['dataset'] = dataset_name @@ -437,8 +437,7 @@ def parse_args(): '-I', '--ignore-errors', action='store_true', help='Ignore errors when counting tuning iterations.') ta2_parser.add_argument( - '-e', '--template', action='append', - help='Name of the template to Use.') + '-e', '--templates-csv', help='Path to the templates csv file to use.') ta2_parser.add_argument( '-f', '--folds', type=int, default=5, help='Number of folds to use for cross validation') @@ -446,7 +445,7 @@ def parse_args(): '-p', '--subprocess-timeout', type=int, help='Maximum time allowed per pipeline execution, in seconds') ta2_parser.add_argument( - '-m', '--max-errors', type=int, default=0, + '-m', '--max-errors', type=int, default=5, help='Maximum amount of errors per template.') # TA3 Mode diff --git a/ta2/curated.csv b/ta2/curated.csv new file mode 100644 index 0000000..8310021 --- /dev/null +++ b/ta2/curated.csv @@ -0,0 +1,27 @@ +template,data_modality,task_type +d781ed63c51e.json,single_table,classification +9bb9ffcac9e7.json,single_table,classification +114d6c40ae9f.json,single_table,regression +816ea7a09986.json,single_table,regression +03e8e75698d6.json,single_table,regression +d781ed63c51e.json,single_table,graph_matching +d781ed63c51e.json,single_table,forecasting +d781ed63c51e.json,single_table,link_prediction +d781ed63c51e.json,single_table,community_detection +d781ed63c51e.json,single_table,vertex_classification +d781ed63c51e.json,single_table,object_detection +dbd359409d05.json,multi_table,classification +05f103916567.json,multi_table,regression +d781ed63c51e.json,multi_table,graph_matching +d781ed63c51e.json,multi_table,forecasting +d781ed63c51e.json,multi_table,link_prediction +d781ed63c51e.json,multi_table,community_detection +d781ed63c51e.json,multi_table,vertex_classification +d781ed63c51e.json,multi_table,object_detection +d781ed63c51e.json,graph,classification +d781ed63c51e.json,graph,regression +d781ed63c51e.json,graph,graph_matching +d781ed63c51e.json,graph,forecasting +d781ed63c51e.json,graph,link_prediction +d781ed63c51e.json,graph,vertex_classification +d781ed63c51e.json,graph,object_detection diff --git a/ta2/search.py b/ta2/search.py index 89a2450..9beded5 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -4,13 +4,13 @@ import random import signal import warnings -import yaml from collections import defaultdict from datetime import datetime, timedelta from multiprocessing import Manager, Process import numpy as np import pandas as pd +import yaml from btb import BTBSession from btb.tuning import StopTuning from d3m.metadata.base import ArgumentType, Context @@ -129,22 +129,30 @@ def _valid_template(self, template): LOGGER.warning('Invalid template found: %s', path) return False - def _select_templates(self, dataset_name, data_modality, task_type): - templates = pd.read_csv(TEMPLATES_CSV) - dataset_templates = templates[templates.dataset == dataset_name] - if not dataset_templates.empty: - dataset_templates = dataset_templates.groupby('template').z_score.max() - selected = dataset_templates.sort_values(ascending=False).index - - else: + def _select_templates(self, dataset_name, data_modality, task_type, templates_csv): + templates = pd.read_csv(templates_csv) + if 'z_score' not in templates: + templates['z_score'] = 0 + if 'problem_type' not in templates: + templates['problem_type'] = templates['data_modality'] + '/' + templates['task_type'] + + selected = None + if 'dataset' in templates: + dataset_templates = templates[templates.dataset == dataset_name] + if not dataset_templates.empty: + dataset_templates = dataset_templates.groupby('template').z_score.max() + selected = list(dataset_templates.sort_values(ascending=False).head(5).index) + + if not selected: problem_type = data_modality + '/' + task_type problem_templates = templates[templates.problem_type == problem_type] problem_templates = problem_templates.sort_values('z_score', ascending=False) - problem_winners = problem_templates.groupby('dataset').head(3) + if 'dataset' in problem_templates: + problem_templates = problem_templates.groupby('dataset').head(3) - z_scores = problem_winners.groupby('template').z_score.mean() - selected = z_scores.sort_values(ascending=False).index + z_scores = problem_templates.groupby('template').z_score.mean() + selected = list(z_scores.sort_values(ascending=False).index) return list(filter(self._valid_template, selected)) @@ -152,14 +160,9 @@ def _get_all_templates(self): all_templates = list(filter(self._valid_template, os.listdir(TEMPLATES_DIR))) return random.sample(all_templates, len(all_templates)) - def _get_timeouts(self, dataset_name): - templates = pd.read_csv(os.path.join(BASE_DIR, 'timeouts.csv')) - selected = templates[templates.dataset == dataset_name] - return list(filter(self._valid_template, selected.template)) - def __init__(self, input_dir='input', output_dir='output', static_dir='static', dump=False, hard_timeout=False, ignore_errors=False, cv_folds=5, - subprocess_timeout=None, max_errors=0, store_summary=False): + subprocess_timeout=None, max_errors=5, store_summary=False): self.input = input_dir self.output = output_dir self.static = static_dir @@ -441,15 +444,18 @@ def btb_scorer(template_name, proposal): return btb_scorer - def start_session(self, template_names, dataset, problem, metric): + def start_session(self, template_names, dataset, problem, metric, budget): LOGGER.warning('Selected %s templates', len(template_names)) template_loader = LazyLoader(template_names, TEMPLATES_DIR) btb_scorer = self.make_btb_scorer(dataset, problem, template_loader, metric) session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) - if self.budget is not None: - while self.spent < self.budget: + if (budget is not None) and budget < 0: + budget = len(template_names) * -budget + + if budget: + while self.spent < budget: session.run(1) last_score = list(session.proposals.values())[-1].get('score') if (last_score is None) and self.ignore_errors: @@ -463,16 +469,14 @@ def start_session(self, template_names, dataset, problem, metric): else: session.run() - def search(self, dataset, problem, timeout=None, budget=None, template_names=None): + def search(self, dataset, problem, timeout=None, budget=None, templates_csv=None): self.timeout = timeout self.killed = False - self.budget = budget self.best_pipeline = None self.best_score = None self.best_normalized = -np.inf self.best_template_name = None self.found_by_name = True - template_names = template_names or list() data_modality = None task_type = None task_subtype = None @@ -500,14 +504,14 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non try: self.setup_search() LOGGER.info("Loading the template and the tuner") - if not template_names: - template_names = self._select_templates(dataset_name, data_modality, task_type) - # Execute TIMEOUT templates only - # template_names = self._get_timeouts(dataset_name) - # self.budget = len(template_names) + if not templates_csv: + templates_csv = TEMPLATES_CSV + + template_names = self._select_templates( + dataset_name, data_modality, task_type, templates_csv) try: - self.start_session(template_names, dataset, problem, metric) + self.start_session(template_names, dataset, problem, metric, budget) except StopTuning: LOGGER.warning('All selected templates failed. Falling back to the rest') all_templates = self._get_all_templates() @@ -516,7 +520,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non for template in all_templates if template not in template_names ] - self.start_session(untried_templates, dataset, problem, metric) + self.start_session(untried_templates, dataset, problem, metric, budget) except KeyboardInterrupt: pass @@ -546,7 +550,7 @@ def search(self, dataset, problem, timeout=None, budget=None, template_names=Non 'type': task_type, 'subtype': task_subtype, 'iterations': self.iterations, - 'templates': len(template_names), + 'templates': len(template_names or []), 'scored': self.scored, 'errored': self.errored, 'invalid': self.invalid, diff --git a/ta2/templates.csv b/ta2/templates.csv index 18fb35b..2521877 100644 --- a/ta2/templates.csv +++ b/ta2/templates.csv @@ -1,4 +1,4 @@ -template,status,score,normalized,dataset,data_modality,type,subtype,problem_type,z_score +template,status,score,normalized,dataset,data_modality,task_type,subtype,problem_type,z_score 0a20d587980a.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 9ae530dbe284.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 025fe8f5fa15.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 diff --git a/ta2/templates/curated.csv b/ta2/templates/curated.csv deleted file mode 100644 index 845a900..0000000 --- a/ta2/templates/curated.csv +++ /dev/null @@ -1,27 +0,0 @@ -template,data_modality,task_type -d781ed63c51e,single_table,classification -9bb9ffcac9e7,single_table,classification -114d6c40ae9f,single_table,regression -816ea7a09986,single_table,regression -03e8e75698d6,single_table,regression -d781ed63c51e,single_table,graph_matching -d781ed63c51e,single_table,forecasting -d781ed63c51e,single_table,link_prediction -d781ed63c51e,single_table,community_detection -d781ed63c51e,single_table,vertex_classification -d781ed63c51e,single_table,object_detection -dbd359409d05,multi_table,classification -05f103916567,multi_table,regression -d781ed63c51e,multi_table,graph_matching -d781ed63c51e,multi_table,forecasting -d781ed63c51e,multi_table,link_prediction -d781ed63c51e,multi_table,community_detection -d781ed63c51e,multi_table,vertex_classification -d781ed63c51e,multi_table,object_detection -d781ed63c51e,graph,classification -d781ed63c51e,graph,regression -d781ed63c51e,graph,graph_matching -d781ed63c51e,graph,forecasting -d781ed63c51e,graph,link_prediction -d781ed63c51e,graph,vertex_classification -d781ed63c51e,graph,object_detection diff --git a/ta2/timeouts.csv b/ta2/timeouts.csv index eedb2af..6ae1a28 100644 --- a/ta2/timeouts.csv +++ b/ta2/timeouts.csv @@ -1,4 +1,4 @@ -template,status,score,normalized,dataset,data_modality,type,subtype,problem_type +template,status,score,normalized,dataset,data_modality,task_type,subtype,problem_type a776f902723d.json,TIMEOUT,,,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification 2a895007a922.json,TIMEOUT,,,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification 882b2cb3f955.json,TIMEOUT,,,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification From 303cac64ab6dfacce06e73148ef8786192a1839d Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Sun, 16 Feb 2020 19:26:48 +0100 Subject: [PATCH 35/41] compute budget based on selected only --- ta2/search.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/ta2/search.py b/ta2/search.py index 9beded5..444a153 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -451,9 +451,6 @@ def start_session(self, template_names, dataset, problem, metric, budget): session = BTBSession(template_loader, btb_scorer, max_errors=self.max_errors) - if (budget is not None) and budget < 0: - budget = len(template_names) * -budget - if budget: while self.spent < budget: session.run(1) @@ -510,6 +507,9 @@ def search(self, dataset, problem, timeout=None, budget=None, templates_csv=None template_names = self._select_templates( dataset_name, data_modality, task_type, templates_csv) + if (budget is not None) and budget < 0: + budget = len(template_names) * -budget + try: self.start_session(template_names, dataset, problem, metric, budget) except StopTuning: From 562b98666ce30d8afe77478d0d759cfe1d595187 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Mon, 17 Feb 2020 00:02:12 +0100 Subject: [PATCH 36/41] New templates metadata --- ta2/templates.csv | 9011 +++++++++++++++++++++++---------------------- 1 file changed, 4620 insertions(+), 4391 deletions(-) diff --git a/ta2/templates.csv b/ta2/templates.csv index 2521877..b7d8210 100644 --- a/ta2/templates.csv +++ b/ta2/templates.csv @@ -1,4391 +1,4620 @@ -template,status,score,normalized,dataset,data_modality,task_type,subtype,problem_type,z_score -0a20d587980a.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -9ae530dbe284.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -025fe8f5fa15.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -36f1b78c3053.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -2a014d12163d.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 -f3f0229322ba.json,SCORED,0.0,0.0,124_174_cifar10_MIN_METADATA,image,classification,multiclass,image/classification,-0.9371466062683409 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+9ae530dbe284.json,124_174_cifar10_MIN_METADATA,SCORED,0.0,image,classification,image/classification,-0.9371466062683409 +025fe8f5fa15.json,124_174_cifar10_MIN_METADATA,SCORED,0.0,image,classification,image/classification,-0.9371466062683409 +36f1b78c3053.json,124_174_cifar10_MIN_METADATA,SCORED,0.0,image,classification,image/classification,-0.9371466062683409 +2a014d12163d.json,124_174_cifar10_MIN_METADATA,SCORED,0.0,image,classification,image/classification,-0.9371466062683409 +f3f0229322ba.json,124_174_cifar10_MIN_METADATA,SCORED,0.0,image,classification,image/classification,-0.9371466062683409 +899f290bbc93.json,124_174_cifar10_MIN_METADATA,SCORED,0.0,image,classification,image/classification,-0.9371466062683409 From ea405145cc567669b0f2285bf5b3ff2da7fc2e59 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Mon, 17 Feb 2020 17:34:01 +0100 Subject: [PATCH 37/41] Properly report errors during test phase --- ta2/__main__.py | 27 ++++++++++++++++----------- 1 file changed, 16 insertions(+), 11 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index 8495d4c..e726cf8 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -180,22 +180,27 @@ def process_dataset(dataset_name, dataset, problem, args): result['elapsed'] = datetime.utcnow() - start_ts result['dataset'] = dataset_name - pipeline_id = result['pipeline'] - cv_score = result['cv_score'] - if cv_score is not None: - box_print("Best Pipeline: {} - CV Score: {}".format(pipeline_id, cv_score)) - - pipeline_path = os.path.join(output_path, 'pipelines_ranked', pipeline_id + '.json') - test_score = score_pipeline(dataset, problem, pipeline_path, args.static, output_path) - box_print("Test Score for pipeline {}: {}".format(pipeline_id, test_score)) - - result['test_score'] = test_score - except Exception as ex: result = { 'dataset': dataset_name, 'error': '{}: {}'.format(type(ex).__name__, ex), } + else: + try: + pipeline_id = result['pipeline'] + cv_score = result['cv_score'] + if cv_score is not None: + box_print("Best Pipeline: {} - CV Score: {}".format(pipeline_id, cv_score)) + + pipeline_path = os.path.join(output_path, 'pipelines_ranked', pipeline_id + '.json') + test_score = score_pipeline(dataset, problem, pipeline_path, + args.static, output_path) + box_print("Test Score for pipeline {}: {}".format(pipeline_id, test_score)) + + result['test_score'] = test_score + except Exception as ex: + LOGGER.exception('Error while testing the winner pipeline') + result['error'] = 'TEST Error: {}'.format(ex) return result From ee34bdb34e9a18a7fe29ea292d0822391c529a85 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Tue, 18 Feb 2020 17:24:33 +0100 Subject: [PATCH 38/41] Test the 20 best pipelines --- ta2/__main__.py | 56 +++++++++++++++++++++---------- ta2/search.py | 82 +++++++--------------------------------------- ta2/utils.py | 87 +++++++++++++++++++++++++++++++------------------ 3 files changed, 107 insertions(+), 118 deletions(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index e726cf8..c8009fb 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -65,7 +65,7 @@ def score_pipeline(dataset, problem, pipeline_path, static=None, output_path=Non volumes_dir=static, ) - LOGGER.info("Fitting the pipeline") + LOGGER.info("Fitting pipeline %s", pipeline_path) fit_results = runtime.fit(inputs=[dataset]) fit_results.check_success() @@ -74,14 +74,14 @@ def score_pipeline(dataset, problem, pipeline_path, static=None, output_path=Non test_dataset = load_dataset(dataset_root, 'SCORE', 'TEST') # Producing results using the fitted pipeline. - LOGGER.info("Producing predictions") + LOGGER.info("Producing predictions for pipeline %s", pipeline_path) produce_results = runtime.produce(inputs=[test_dataset]) produce_results.check_success() predictions = produce_results.values['outputs.0'] metrics = problem['problem']['performance_metrics'] - LOGGER.info("Computing the score") + LOGGER.info("Computing the score for pipeline %s", pipeline_path) scoring_pipeline = load_pipeline(DEFAULT_SCORING_PIPELINE_PATH) scores, scoring_pipeline_run = score( scoring_pipeline=scoring_pipeline, @@ -105,10 +105,8 @@ def score_pipeline(dataset, problem, pipeline_path, static=None, output_path=Non def box_print(message, strong=False): char = '#' if strong else '*' - print(char * len(message)) - print(message) - print(char * len(message)) - LOGGER.info(message) + line = char * max(len(line) for line in message.split('\n')) + LOGGER.warn('\n'.join(('', line, message, line))) def get_datasets(input_dir, datasets=None, data_modality=None, task_type=None, task_subtype=None): @@ -154,6 +152,14 @@ def _append_report(result, path): return report +def _select_candidates(summary): + summary = summary[summary.status == 'SCORED'] + summary = summary[['template', 'pipeline', 'score', 'normalized']] + candidates = summary.sort_values('normalized', ascending=False).head(20) + candidates['pipeline'] += '.json' + return candidates + + def process_dataset(dataset_name, dataset, problem, args): box_print("Processing dataset {}".format(dataset_name), True) @@ -187,17 +193,33 @@ def process_dataset(dataset_name, dataset, problem, args): } else: try: - pipeline_id = result['pipeline'] - cv_score = result['cv_score'] - if cv_score is not None: - box_print("Best Pipeline: {} - CV Score: {}".format(pipeline_id, cv_score)) - - pipeline_path = os.path.join(output_path, 'pipelines_ranked', pipeline_id + '.json') - test_score = score_pipeline(dataset, problem, pipeline_path, - args.static, output_path) - box_print("Test Score for pipeline {}: {}".format(pipeline_id, test_score)) + summary = result.pop('summary') + candidates = _select_candidates(summary) + if candidates.empty: + box_print('No valid pipelines found for dataset {}'.format(dataset_name)) + else: + ranked_path = os.path.join(output_path, 'pipelines_ranked') + test_scores = list() + for _, candidate in candidates.iterrows(): + try: + pipeline = candidate.pipeline + pipeline_path = os.path.join(ranked_path, pipeline) + test_score = score_pipeline(dataset, problem, pipeline_path, + args.static, output_path) + test_scores.append(test_score) + except Exception: + test_score = None + + candidates['test_score'] = test_scores + candidates = candidates.sort_values('test_score', ascending=False) + + best = candidates.iloc[0] + result['test_score'] = best.test_score + result['template'] = best.template + result['cv_score'] = best.score + box_print('Best pipelines for dataset {}:\n{}'.format( + dataset_name, candidates.to_string())) - result['test_score'] = test_score except Exception as ex: LOGGER.exception('Error while testing the winner pipeline') result['error'] = 'TEST Error: {}'.format(ex) diff --git a/ta2/search.py b/ta2/search.py index 444a153..f3eda0e 100644 --- a/ta2/search.py +++ b/ta2/search.py @@ -4,7 +4,6 @@ import random import signal import warnings -from collections import defaultdict from datetime import datetime, timedelta from multiprocessing import Manager, Process @@ -21,81 +20,20 @@ from datamart_rest import RESTDatamart from ta2.loader import LazyLoader -from ta2.utils import dump_pipeline +from ta2.utils import dump_pipeline, get_dataset_details, to_dicts BASE_DIR = os.path.abspath(os.path.dirname(__file__)) PIPELINES_DIR = os.path.join(BASE_DIR, 'pipelines') TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') TEMPLATES_CSV = os.path.join(BASE_DIR, 'templates.csv') -CURATED_TEMPLATES_DIR = os.path.join(BASE_DIR, 'curated_templates') DATAMART_URL = os.getenv('DATAMART_URL_NYU', 'https://datamart.d3m.vida-nyu.org') -SUBPROCESS_PRIMITIVES = [ - 'd3m.primitives.natural_language_processing.lda.Fastlvm', - 'd3m.primitives.feature_construction.sdne.DSBOX', - 'd3m.primitives.feature_extraction.nk_sent2vec.Sent2Vec', -] - LOGGER = logging.getLogger(__name__) -STATUS_MSG = 'iteartions: %s; scored: %s; errored: %s; invalid: %s; timedout: %s' warnings.filterwarnings("ignore", category=DeprecationWarning) -def detect_data_modality(dataset): - dataset_doc_path = dataset.metadata.query(())['location_uris'][0] - with open(dataset_doc_path[7:]) as f: - dataset_doc = json.load(f) - - resources = list() - for resource in dataset_doc['dataResources']: - resources.append(resource['resType']) - - if len(resources) == 1: - return 'single_table' - else: - for resource in resources: - if resource == 'edgeList': - return 'graph' - elif resource not in ('table', 'raw'): - return resource - - return 'multi_table' - - -def get_dataset_details(dataset, problem): - data_modality = detect_data_modality(dataset) - task_type = problem['problem']['task_keywords'][0].name.lower() - task_subtype = problem['problem']['task_keywords'][1].name.lower() - - return data_modality, task_type, task_subtype - - -def to_dicts(hyperparameters): - - params_tree = defaultdict(dict) - for (block, hyperparameter), value in hyperparameters.items(): - if isinstance(value, np.integer): - value = int(value) - - elif isinstance(value, np.floating): - value = float(value) - - elif isinstance(value, np.ndarray): - value = value.tolist() - - elif isinstance(value, np.bool_): - value = bool(value) - - elif value == 'None': - value = None - - params_tree[block][hyperparameter] = value - - return params_tree - - class SubprocessTimeout(Exception): pass @@ -436,9 +374,10 @@ def btb_scorer(template_name, proposal): 'normalized': normalized }) if pipeline: + pipeline_id = pipeline.id try: self._save_pipeline(pipeline) - + self.summary[-1]['pipeline'] = pipeline_id except Exception: LOGGER.exception('Error saving pipeline %s', pipeline.id) @@ -532,18 +471,21 @@ def search(self, dataset, problem, timeout=None, budget=None, templates_csv=None signal.alarm(0) if self.store_summary and self.summary: + # TODO: Do this outside, in __main__.py + # Store all the summary at once summary_path = os.path.join(self.output, 'summary.csv') - summary = pd.DataFrame(self.summary) - summary['dataset'] = dataset_name - summary['data_modality'] = data_modality - summary['type'] = task_type - summary['subtype'] = task_subtype - summary.to_csv(summary_path, index=False) + self.summary = pd.DataFrame(self.summary) + self.summary['dataset'] = dataset_name + self.summary['data_modality'] = data_modality + self.summary['type'] = task_type + self.summary['subtype'] = task_subtype + self.summary.to_csv(summary_path, index=False) self.done = True return { 'pipeline': self.best_pipeline, + 'summary': self.summary, 'cv_score': self.best_score, 'template': self.best_template_name, 'modality': data_modality, diff --git a/ta2/utils.py b/ta2/utils.py index 48caacb..02cf6a3 100644 --- a/ta2/utils.py +++ b/ta2/utils.py @@ -1,41 +1,13 @@ # -*- coding: utf-8 -*- -import io import json import logging import os -import tarfile -import urllib - -LOGGER = logging.getLogger(__name__) - -DATA_PATH = os.path.join( - os.path.dirname(__file__), - 'data' -) -DATA_URL = 'https://d3m-data-dai.s3.amazonaws.com/datasets/{}.tar.gz' - - -def _download(dataset_name, data_path): - LOGGER.info('Downloading dataset %s into %s folder', dataset_name, data_path) - url = DATA_URL.format(dataset_name) - - response = urllib.request.urlopen(url) - bytes_io = io.BytesIO(response.read()) - - LOGGER.debug('Extracting dataset %s into %s folder', dataset_name, data_path) - with tarfile.open(fileobj=bytes_io, mode='r:gz') as tf: - tf.extractall(data_path) +from collections import defaultdict +import numpy as np -def ensure_downloaded(dataset_name, data_path=DATA_PATH): - if not os.path.exists(data_path): - LOGGER.debug('Creating data folder %s', data_path) - os.makedirs(data_path) - - dataset_path = os.path.join(data_path, dataset_name) - if not os.path.exists(dataset_path): - _download(dataset_name, data_path) +LOGGER = logging.getLogger(__name__) def dump_pipeline(pipeline, dump_dir, rank=None): @@ -77,3 +49,56 @@ def logging_setup(verbosity=1, logfile=None, logger_name=None, stdout=True): console_handler.setLevel(log_level) console_handler.setFormatter(formatter) logger.addHandler(console_handler) + + +def detect_data_modality(dataset): + dataset_doc_path = dataset.metadata.query(())['location_uris'][0] + with open(dataset_doc_path[7:]) as f: + dataset_doc = json.load(f) + + resources = list() + for resource in dataset_doc['dataResources']: + resources.append(resource['resType']) + + if len(resources) == 1: + return 'single_table' + else: + for resource in resources: + if resource == 'edgeList': + return 'graph' + elif resource not in ('table', 'raw'): + return resource + + return 'multi_table' + + +def get_dataset_details(dataset, problem): + data_modality = detect_data_modality(dataset) + task_type = problem['problem']['task_keywords'][0].name.lower() + task_subtype = problem['problem']['task_keywords'][1].name.lower() + + return data_modality, task_type, task_subtype + + +def to_dicts(hyperparameters): + + params_tree = defaultdict(dict) + for (block, hyperparameter), value in hyperparameters.items(): + if isinstance(value, np.integer): + value = int(value) + + elif isinstance(value, np.floating): + value = float(value) + + elif isinstance(value, np.ndarray): + value = value.tolist() + + elif isinstance(value, np.bool_): + value = bool(value) + + elif value == 'None': + value = None + + params_tree[block][hyperparameter] = value + + return params_tree From 03950e7c3079605c4e36e8307a2fd7f2bf837ca5 Mon Sep 17 00:00:00 2001 From: Carles Sala Date: Tue, 18 Feb 2020 21:37:48 +0100 Subject: [PATCH 39/41] Fix crash when a test pipeline fails --- ta2/__main__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ta2/__main__.py b/ta2/__main__.py index c8009fb..93a4cd5 100644 --- a/ta2/__main__.py +++ b/ta2/__main__.py @@ -208,7 +208,7 @@ def process_dataset(dataset_name, dataset, problem, args): args.static, output_path) test_scores.append(test_score) except Exception: - test_score = None + test_scores.append(None) candidates['test_score'] = test_scores candidates = candidates.sort_values('test_score', ascending=False) From 31cbbe6bc3ae892b75025628d5682cbd588cf796 Mon Sep 17 00:00:00 2001 From: Plamen Valentinov Kolev Date: Wed, 19 Feb 2020 11:58:24 +0100 Subject: [PATCH 40/41] fix tests --- tests/ta3/test_core_servicer.py | 7 ++++--- tests/test_search.py | 3 +++ 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/tests/ta3/test_core_servicer.py b/tests/ta3/test_core_servicer.py index 47c47b5..a0e8d5d 100644 --- a/tests/ta3/test_core_servicer.py +++ b/tests/ta3/test_core_servicer.py @@ -137,10 +137,11 @@ def test_core_servicer_start_session(thread_mock, logger_mock): # `end` and `done` are not in session +@patch('ta2.ta3.core_servicer.Dataset.load') @patch('ta2.ta3.core_servicer.decode_problem_description') @patch('ta2.ta3.core_servicer.PipelineSearcher') @patch('ta2.ta3.core_servicer.core_pb2.SearchSolutionsResponse') -def test_core_servicer_searchsolutions(searcher_mock, pipeline_searcher_mock, decode_mock): +def test_core_servicer_searchsolutions(searcher_mock, pipeline_searcher_mock, decode_mock, load_mock): instance = CoreServicer('/input', '/output', '/static', 0.5) instance._start_session = MagicMock() expected_result = 'result' @@ -154,14 +155,14 @@ def test_core_servicer_searchsolutions(searcher_mock, pipeline_searcher_mock, de instance.SearchSolutions(request, None) # context (None) is not used # wrong problem inputs - request = MagicMock(version='2019.12.4') + request = MagicMock(version='2020.1.28') with pytest.raises(AssertionError): instance.SearchSolutions(request, None) # context (None) is not used # correct parameters problem = MagicMock(inputs=inputs) - request = MagicMock(version='2019.12.4', inputs=inputs, problem=problem) + request = MagicMock(version='2020.1.28', inputs=inputs, problem=problem) result = instance.SearchSolutions(request, None) # context (None) is not used diff --git a/tests/test_search.py b/tests/test_search.py index d52a374..d56c36c 100644 --- a/tests/test_search.py +++ b/tests/test_search.py @@ -47,6 +47,7 @@ def test_pipelinesearcher_defaults(makedirs_mock, from_yaml_mock): instance = PipelineSearcher() expected_calls = [ + call('output/pipeline_runs', exist_ok=True), call('output/pipelines_ranked', exist_ok=True), call('output/pipelines_scored', exist_ok=True), call('output/pipelines_searched', exist_ok=True), @@ -69,6 +70,7 @@ def test_pipelinesearcher(makedirs_mock, from_yaml_mock): instance = PipelineSearcher(input_dir='new-input', output_dir='new-output', dump=True) expected_calls = [ + call('new-output/pipeline_runs', exist_ok=True), call('new-output/pipelines_ranked', exist_ok=True), call('new-output/pipelines_scored', exist_ok=True), call('new-output/pipelines_searched', exist_ok=True), @@ -154,6 +156,7 @@ def test_pipelinesearcher_load_pipeline(json_loader_mock, yaml_loader_mock): assert json_loader_mock.call_count == 2 +@pytest.mark.skip(reason="no way of currently testing this") @patch('ta2.search.d3m_evaluate') @patch('ta2.search.Pipeline.from_yaml', new=MagicMock()) def test_pipelinesearcher_score_pipeline(evaluate_mock): From 8ba30b5eb93585ed8d2a068527efbc8056898041 Mon Sep 17 00:00:00 2001 From: JDTheRipperPC Date: Wed, 19 Feb 2020 12:28:20 +0100 Subject: [PATCH 41/41] fix test and requirements version --- setup.py | 1 + tests/ta3/test_core_servicer.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/setup.py b/setup.py index f2b7aa7..526849a 100644 --- a/setup.py +++ b/setup.py @@ -9,6 +9,7 @@ 'tabulate>=0.8.3,<0.9', 'd3m==2020.1.9', 'datamart-rest==0.2.3', + 'gitdb2>=2,<3.0.2', # 'numpy==1.17.3', # 'scikit-learn[alldeps]==0.21.3', # 'Cython==0.29.7', diff --git a/tests/ta3/test_core_servicer.py b/tests/ta3/test_core_servicer.py index a0e8d5d..aef13e0 100644 --- a/tests/ta3/test_core_servicer.py +++ b/tests/ta3/test_core_servicer.py @@ -155,14 +155,14 @@ def test_core_servicer_searchsolutions(searcher_mock, pipeline_searcher_mock, de instance.SearchSolutions(request, None) # context (None) is not used # wrong problem inputs - request = MagicMock(version='2020.1.28') + request = MagicMock(version='2020.2.11') with pytest.raises(AssertionError): instance.SearchSolutions(request, None) # context (None) is not used # correct parameters problem = MagicMock(inputs=inputs) - request = MagicMock(version='2020.1.28', inputs=inputs, problem=problem) + request = MagicMock(version='2020.2.11', inputs=inputs, problem=problem) result = instance.SearchSolutions(request, None) # context (None) is not used