From d675ca673a0bcfe2dd7d91af8ec853c53518ce54 Mon Sep 17 00:00:00 2001 From: EHP Date: Sun, 20 Oct 2019 18:00:19 +0200 Subject: [PATCH] Reducet fields, first fully working version --- export.py | 169 +++++++----------- inference/pom.xml | 58 ++++++ .../bonitoo/inference/CacheInference.java | 81 +++++++++ .../aprar/bonitoo/inference/FlightData.java | 123 +++++++++++++ .../java/cz/aprar/bonitoo/inference/TTL.java | 36 ++++ .../bonitoo/inference/CacheInferenceTest.java | 140 +++++++++++++++ .../src/test/resources/model/encoder.json | 1 + .../test/resources/model/xgboost-model.bin | Bin 0 -> 1829971 bytes runner.py | 33 ++++ src/train_model.py | 57 +----- 10 files changed, 544 insertions(+), 154 deletions(-) create mode 100644 inference/pom.xml create mode 100644 inference/src/main/java/cz/aprar/bonitoo/inference/CacheInference.java create mode 100644 inference/src/main/java/cz/aprar/bonitoo/inference/FlightData.java create mode 100644 inference/src/main/java/cz/aprar/bonitoo/inference/TTL.java create mode 100644 inference/src/test/java/cz/aprar/bonitoo/inference/CacheInferenceTest.java create mode 100644 inference/src/test/resources/model/encoder.json create mode 100644 inference/src/test/resources/model/xgboost-model.bin create mode 100644 runner.py diff --git a/export.py b/export.py index 0b70866..62b330f 100644 --- a/export.py +++ b/export.py @@ -1,115 +1,76 @@ from pymongo import MongoClient -from pprint import pprint from datetime import datetime import csv + client = MongoClient() -db=client.bonitoo +db = client.bonitoo fieldnames = [ -'timestamp', -'client.channel', -'type', -'flight.inboundSegments.departure', -'flight.inboundSegments.arrival', -'flight.inboundSegments.origin.airportCode', -'flight.inboundSegments.destination.airportCode', -'flight.inboundSegments.flightNumber', -'flight.inboundSegments.travelClass', -'flight.inboundSegments.bookingCode', -'flight.inboundSegments.availability', -'flight.inboundSegments.elapsedFlyingTime', -'flight.outboundSegments.departure', -'flight.outboundSegments.arrival', -'flight.outboundSegments.origin.airportCode', -'flight.outboundSegments.destination.airportCode', -'flight.outboundSegments.flightNumber', -'flight.outboundSegments.travelClass', -'flight.outboundSegments.bookingCode', -'flight.outboundSegments.availability', -'flight.outboundSegments.elapsedFlyingTime', -'flight.inboundEFT', # elapsed flying time -'flight.outboundEFT', -'oneWay', -'adults', # pocet osob = (adults + children) -'children', -'infants', -'input.price', -'input.tax', -'input.currency', -'success', -'status', -'output.price', -'output.tax', -'output.currency', -'duration' # delka volani do nadrazeneho systemu + 'timestamp', + 'client.channel', + 'type', + 'flight.inboundSegments.departure', + 'flight.inboundSegments.arrival', + 'flight.inboundSegments.origin.airportCode', + 'flight.inboundSegments.destination.airportCode', + 'flight.outboundSegments.departure', + 'flight.outboundSegments.arrival', + 'flight.outboundSegments.origin.airportCode', + 'flight.outboundSegments.destination.airportCode', + 'input.price', + 'input.tax', + 'input.currency', + 'success', + 'status', + 'output.price', + 'output.tax', + 'output.currency', + 'duration' ] -# 5% nebo 200 kc rozdil nahoru -# -200 kc dolu -# abs(+-10kc) ignorovat - -# timestamp + ok price - ma byt v cache od cacheat -# timestamp + notok price - nema byt v cache od cacheat - -# delka pobytu prilet-odlet -# delka letu ? -# pokud je chyba tak nocache (= chybi priceout) - -# brat v uvahu in/out kody aerolinek (mcx ?) - mirek jeste zjisti - -# vypocitat uspesnost je/neni v cache v % - counter = 0 with open('export.csv', mode='w') as ef: - writer = csv.DictWriter(ef, fieldnames=fieldnames, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) - # do not write header for s3 files - # writer.writeheader() + writer = csv.DictWriter(ef, fieldnames=fieldnames, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + # do not write header for s3 files + # writer.writeheader() + + for it in db.pricing_audit.find(): + counter += 1 + if counter % 1000 == 0: + print('Iterace %d' % counter) + d = { + 'timestamp': datetime.fromtimestamp(it['timestamp'] / 1000).isoformat(), + 'client.channel': it['client']['channel'], + 'type': it['type'], + 'flight.outboundSegments.departure': '|'.join( + [x['departure'].isoformat() for x in it['flight']['outboundSegments']]), + 'flight.outboundSegments.arrival': '|'.join( + [x['arrival'].isoformat() for x in it['flight']['outboundSegments']]), + 'flight.outboundSegments.origin.airportCode': '|'.join( + [x['origin']['airportCode'] for x in it['flight']['outboundSegments']]), + 'flight.outboundSegments.destination.airportCode': '|'.join( + [x['destination']['airportCode'] for x in it['flight']['outboundSegments']]), + 'input.price': it['input']['price'], + 'input.tax': it['input']['tax'], + 'input.currency': it['input']['currency'], + 'success': it['success'], + 'status': it.get('status', ''), + 'output.price': it.get('output', {'price': 0})['price'], + 'output.tax': it.get('output', {'tax': 0})['tax'], + 'output.currency': it.get('output', {'currency': 0})['currency'], + 'duration': it['duration'] + } - for it in db.pricing_audit.find(): - counter += 1 - if counter % 1000 == 0: - print('Iterace %d' % counter) - d = { - 'timestamp': datetime.fromtimestamp(it['timestamp']/1000).isoformat(), - 'client.channel': it['client']['channel'], - 'type': it['type'], - 'flight.outboundSegments.departure': '|'.join([x['departure'].isoformat() for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.arrival': '|'.join([x['arrival'].isoformat() for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.origin.airportCode': '|'.join([x['origin']['airportCode'] for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.destination.airportCode': '|'.join([x['destination']['airportCode'] for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.flightNumber': '|'.join([x['flightNumber'] for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.travelClass': '|'.join([x['travelClass'] for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.bookingCode': '|'.join([x.get('bookingCode','') for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.availability': '|'.join([str(x.get('availability','')) for x in it['flight']['outboundSegments']]), - 'flight.outboundSegments.elapsedFlyingTime': '|'.join([str(x.get('elapsedFlyingTime','')) for x in it['flight']['outboundSegments']]), - 'flight.inboundEFT': it['flight'].get('inboundEFT',''), - 'flight.outboundEFT': it['flight'].get('outboundEFT',''), - 'oneWay': it['oneWay'], - 'adults': it['adults'], - 'children': it['children'], - 'infants': it['infants'], - 'input.price': it['input']['price'], - 'input.tax': it['input']['tax'], - 'input.currency': it['input']['currency'], - 'success': it['success'], - 'status': it.get('status',''), - 'output.price': it.get('output', {'price': 0})['price'], - 'output.tax': it.get('output', {'tax': 0})['tax'], - 'output.currency': it.get('output', {'currency': 0})['currency'], - 'duration': it['duration'] - } - - if 'inboundSegments' in it['flight']: - inb = { - 'flight.inboundSegments.departure': '|'.join([x['departure'].isoformat() for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.arrival': '|'.join([x['arrival'].isoformat() for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.origin.airportCode': '|'.join([x['origin']['airportCode'] for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.destination.airportCode': '|'.join([x['destination']['airportCode'] for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.flightNumber': '|'.join([x['flightNumber'] for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.travelClass': '|'.join([x['travelClass'] for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.bookingCode': '|'.join([x.get('bookingCode', '') for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.availability': '|'.join([str(x.get('availability','')) for x in it['flight']['inboundSegments']]), - 'flight.inboundSegments.elapsedFlyingTime': '|'.join([str(x.get('elapsedFlyingTime','')) for x in it['flight']['inboundSegments']]) - } - d = {**d, **inb} - writer.writerow(d) + if 'inboundSegments' in it['flight']: + inb = { + 'flight.inboundSegments.departure': '|'.join( + [x['departure'].isoformat() for x in it['flight']['inboundSegments']]), + 'flight.inboundSegments.arrival': '|'.join( + [x['arrival'].isoformat() for x in it['flight']['inboundSegments']]), + 'flight.inboundSegments.origin.airportCode': '|'.join( + [x['origin']['airportCode'] for x in it['flight']['inboundSegments']]), + 'flight.inboundSegments.destination.airportCode': '|'.join( + [x['destination']['airportCode'] for x in it['flight']['inboundSegments']]), + } + d = {**d, **inb} + writer.writerow(d) diff --git a/inference/pom.xml b/inference/pom.xml new file mode 100644 index 0000000..56faa9d --- /dev/null +++ b/inference/pom.xml @@ -0,0 +1,58 @@ + + 4.0.0 + cz.aprar.bonitoo + inference + jar + 1.0-SNAPSHOT + inference + + + UTF-8 + + + + + ml.dmlc + xgboost4j + 0.90 + + + + com.fasterxml.jackson.core + jackson-databind + 2.9.9 + + + + org.testng + testng + 7.0.0 + test + + + + + + + org.apache.maven.plugins + maven-compiler-plugin + 3.8.1 + + 8 + 8 + + + + + org.apache.maven.plugins + maven-pmd-plugin + 3.12.0 + + utf-8 + 1.8 + + + + + diff --git a/inference/src/main/java/cz/aprar/bonitoo/inference/CacheInference.java b/inference/src/main/java/cz/aprar/bonitoo/inference/CacheInference.java new file mode 100644 index 0000000..d457684 --- /dev/null +++ b/inference/src/main/java/cz/aprar/bonitoo/inference/CacheInference.java @@ -0,0 +1,81 @@ +package cz.aprar.bonitoo.inference; + +import com.fasterxml.jackson.core.type.TypeReference; +import com.fasterxml.jackson.databind.ObjectMapper; +import ml.dmlc.xgboost4j.java.Booster; +import ml.dmlc.xgboost4j.java.DMatrix; +import ml.dmlc.xgboost4j.java.XGBoost; +import ml.dmlc.xgboost4j.java.XGBoostError; + +import java.io.BufferedInputStream; +import java.io.IOException; +import java.io.InputStream; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.List; +import java.util.Map; + +public class CacheInference { + private static final TTL[] TTL_VALUES = TTL.values(); + + private final ObjectMapper mapper = new ObjectMapper(); + private final Booster booster; + private final Map> labels; + + public CacheInference(final Path modelFile, final Path labelFile) throws IOException, XGBoostError { + try (BufferedInputStream modelIS = new BufferedInputStream(Files.newInputStream(modelFile)); + BufferedInputStream labelIS = new BufferedInputStream(Files.newInputStream(labelFile)) + ) { + booster = loadModel(modelIS); + labels = loadLabels(labelIS); + } + } + + public CacheInference(InputStream modelIS, InputStream labelIS) throws IOException, XGBoostError { + booster = loadModel(modelIS); + labels = loadLabels(labelIS); + } + + public TTL cacheTTL(final FlightData data) throws XGBoostError { + float[][] predicts = booster.predict(createMatrix(data)); + return TTL_VALUES[(int) predicts[0][0]]; + } + + private Booster loadModel(InputStream model) throws XGBoostError, IOException { + return XGBoost.loadModel(model); + } + + private DMatrix createMatrix(final FlightData data) throws XGBoostError { + final float[] arr = new float[18]; + arr[0] = labels.get("client.channel").getOrDefault(data.getClientChannel(), 0); + arr[1] = labels.get("type").getOrDefault(data.getType(), 0); + arr[2] = labels.get("flight.inboundSegments.departure").getOrDefault(joinList(data.getInboundDeparture()), 0); + arr[3] = labels.get("flight.inboundSegments.arrival").getOrDefault(joinList(data.getInboundArrival()), 0); + arr[4] = labels.get("flight.inboundSegments.origin.airportCode").getOrDefault(joinList(data.getInboundOrigin()), 0); + arr[5] = labels.get("flight.inboundSegments.destination.airportCode").getOrDefault(joinList(data.getInboundDestination()), 0); + arr[6] = labels.get("flight.outboundSegments.departure").getOrDefault(joinList(data.getOutboundDeparture()), 0); + arr[7] = labels.get("flight.outboundSegments.arrival").getOrDefault(joinList(data.getOutboundArrival()), 0); + arr[8] = labels.get("flight.outboundSegments.origin.airportCode").getOrDefault(joinList(data.getOutboundOrigin()), 0); + arr[9] = labels.get("flight.outboundSegments.destination.airportCode").getOrDefault(joinList(data.getOutboundDestination()), 0); + arr[10] = data.getInputPrice().floatValue(); + arr[11] = data.getInputTax().floatValue(); + arr[12] = labels.get("input.currency").getOrDefault(data.getInputCurrency(), 0); + arr[13] = data.getStatus().floatValue(); + arr[14] = data.getOutputPrice().floatValue(); + arr[15] = data.getOutputTax().floatValue(); + arr[16] = labels.get("output.currency").getOrDefault(data.getOutputCurrency(), 0); + arr[17] = data.getDuration().floatValue(); + + return new DMatrix(arr, 1, arr.length); + } + + private Map> loadLabels(InputStream labels) throws IOException { + final TypeReference>> typeRef = new TypeReference>>() { + }; + return mapper.readValue(labels, typeRef); + } + + private String joinList(final List data) { + return String.join("|", data); + } +} diff --git a/inference/src/main/java/cz/aprar/bonitoo/inference/FlightData.java b/inference/src/main/java/cz/aprar/bonitoo/inference/FlightData.java new file mode 100644 index 0000000..4a600a1 --- /dev/null +++ b/inference/src/main/java/cz/aprar/bonitoo/inference/FlightData.java @@ -0,0 +1,123 @@ +package cz.aprar.bonitoo.inference; + +import java.util.Collections; +import java.util.List; + +public class FlightData { + private final String clientChannel; + private final String type; + private final List inboundDeparture; + private final List inboundArrival; + private final List inboundOrigin; + private final List inboundDestination; + private final List outboundDeparture; + private final List outboundArrival; + private final List outboundOrigin; + private final List outboundDestination; + private final Double inputPrice; + private final Double inputTax; + private final String inputCurrency; + private final Integer status; + private final Double outputPrice; + private final Double outputTax; + private final String outputCurrency; + private final Integer duration; + + public FlightData(final String clientChannel, final String type, + final List inboundDeparture, final List inboundArrival, final List inboundOrigin, + final List inboundDestination, final List outboundDeparture, final List outboundArrival, + final List outboundOrigin, final List outboundDestination, final Double inputPrice, + final Double inputTax, final String inputCurrency, final Integer status, final Double outputPrice, + final Double outputTax, final String outputCurrency, final Integer duration) { + this.clientChannel = clientChannel; + this.type = type; + this.inboundDeparture = inboundDeparture; + this.inboundArrival = inboundArrival; + this.inboundOrigin = inboundOrigin; + this.inboundDestination = inboundDestination; + this.outboundDeparture = outboundDeparture; + this.outboundArrival = outboundArrival; + this.outboundOrigin = outboundOrigin; + this.outboundDestination = outboundDestination; + this.inputPrice = inputPrice; + this.inputTax = inputTax; + this.inputCurrency = inputCurrency; + this.status = status; + this.outputPrice = outputPrice; + this.outputTax = outputTax; + this.outputCurrency = outputCurrency; + this.duration = duration; + } + + public String getClientChannel() { + return clientChannel; + } + + public String getType() { + return type; + } + + public List getInboundDeparture() { + return Collections.unmodifiableList(inboundDeparture); + } + + public List getInboundArrival() { + return Collections.unmodifiableList(inboundArrival); + } + + public List getInboundOrigin() { + return Collections.unmodifiableList(inboundOrigin); + } + + public List getInboundDestination() { + return Collections.unmodifiableList(inboundDestination); + } + + public List getOutboundDeparture() { + return Collections.unmodifiableList(outboundDeparture); + } + + public List getOutboundArrival() { + return Collections.unmodifiableList(outboundArrival); + } + + public List getOutboundOrigin() { + return Collections.unmodifiableList(outboundOrigin); + } + + public List getOutboundDestination() { + return Collections.unmodifiableList(outboundDestination); + } + + public Double getInputPrice() { + return inputPrice; + } + + public Double getInputTax() { + return inputTax; + } + + public String getInputCurrency() { + return inputCurrency; + } + + public Integer getStatus() { + return status; + } + + public Double getOutputPrice() { + return outputPrice; + } + + public Double getOutputTax() { + return outputTax; + } + + public String getOutputCurrency() { + return outputCurrency; + } + + public Integer getDuration() { + return duration; + } +} diff --git a/inference/src/main/java/cz/aprar/bonitoo/inference/TTL.java b/inference/src/main/java/cz/aprar/bonitoo/inference/TTL.java new file mode 100644 index 0000000..a7efa02 --- /dev/null +++ b/inference/src/main/java/cz/aprar/bonitoo/inference/TTL.java @@ -0,0 +1,36 @@ +package cz.aprar.bonitoo.inference; + +public enum TTL { + /** + * Very volatile or unknown data + */ + NOCACHE, + /** + * Cache for 12 hours + */ + H12, + /** + * Cache for 1 day + */ + D1, + /** + * Cache for 2 days + */ + D2, + /** + * Cache for 3 days + */ + D3, + /** + * Cache for 1 week + */ + D7, + /** + * Cache for 2 weeks + */ + D14, + /** + * Cache for 30 days + */ + D30; +} diff --git a/inference/src/test/java/cz/aprar/bonitoo/inference/CacheInferenceTest.java b/inference/src/test/java/cz/aprar/bonitoo/inference/CacheInferenceTest.java new file mode 100644 index 0000000..1d6bcaa --- /dev/null +++ b/inference/src/test/java/cz/aprar/bonitoo/inference/CacheInferenceTest.java @@ -0,0 +1,140 @@ +package cz.aprar.bonitoo.inference; + +import ml.dmlc.xgboost4j.java.XGBoostError; +import org.testng.annotations.BeforeClass; +import org.testng.annotations.DataProvider; +import org.testng.annotations.Test; + +import java.io.IOException; +import java.util.Arrays; +import java.util.List; + +import static java.util.Collections.emptyList; +import static org.testng.Assert.assertEquals; + +public class CacheInferenceTest { + private CacheInference ci; + + @BeforeClass + void setUp() throws IOException, XGBoostError { + final ClassLoader classLoader = getClass().getClassLoader(); + ci = new CacheInference(classLoader.getResourceAsStream("model/xgboost-model.bin"), + classLoader.getResourceAsStream("model/encoder.json")); + } + + @Test(dataProvider = "inferenceData") + void testInference(final FlightData input, final TTL expected) throws XGBoostError { + final TTL result = ci.cacheTTL(input); + assertEquals(result, expected); + } + + @DataProvider(name = "inferenceData") + public Object[][] inferenceData() { + return new Object[][]{ + {new FlightData( + "fly-me-to", + "WS", + toList("2020-05-09T23:59:00", "2020-05-10T10:30:00"), + toList("2020-05-10T08:55:00", "2020-05-10T11:30:00"), + toList("MCO", "FRA"), + toList("FRA", "PRG"), + toList("2020-05-01T09:50:00", "2020-05-01T11:55:00"), + toList("2020-05-01T11:00:00", "2020-05-01T21:55:00"), + toList("PRG", "FRA"), + toList("FRA", "MCO"), + 39766.0, + 19776.0, + "CZK", + 0, + 39766.0, + 19776.0, + "CZK", + 427 + ), TTL.D1}, + {new FlightData( + "fly-me-to", + "PYTON", + emptyList(), + emptyList(), + emptyList(), + emptyList(), + toList("2019-12-18T05:45:00"), + toList("2019-12-18T08:05:00"), + toList("KRK"), + toList("BVA"), + 336.258, + 0.0, + "CZK", + 0, + 336.258, + 0.0, + "CZK", + 2284 + ), TTL.D7}, + {new FlightData( + "levne", + "AVIA", + toList("2020-02-07T02:25:00", "2020-02-07T14:50:00"), + toList("2020-02-07T13:10:00", "2020-02-07T16:55:00"), + toList("LAX", "LHR"), + toList("LHR", "PRG"), + toList("2020-01-28T10:35:00", "2020-01-28T14:40:00"), + toList("2020-01-28T12:45:00", "2020-01-29T01:45:00"), + toList("PRG", "HEL"), + toList("HEL", "LAX"), + 5971.77978, + 0.0, + "CZK", + 0, + 15971.77978, + 0.0, + "CZK", + 551 + ), TTL.D7}, + {new FlightData( + "fly-me-to", + "HH", + toList("2019-11-01T16:30:00", "2019-11-01T23:35:00"), + toList("2019-11-01T21:12:00", "2019-11-02T07:45:00"), + toList("YVR", "YUL"), + toList("YUL", "VIE"), + toList("2019-10-18T08:10:00", "2019-10-18T11:30:00"), + toList("2019-10-18T09:40:00", "2019-10-18T21:25:00"), + toList("VIE", "FRA"), + toList("FRA", "YVR"), + 17723.0, + 7708.0, + "CZK", + 0, + 17723.0, + 7708.0, + "CZK", + 1786 + ), TTL.D1}, + {new FlightData( + "unknown", + "unknown", + toList("unknown"), + toList("unknown"), + toList("unknown"), + toList("unknown"), + toList("unknown"), + toList("unknown"), + toList("unknown"), + toList("unknown"), + 0.0, + 0.0, + "unknown", + 0, + 0.0, + 0.0, + "unknown", + 0 + ), TTL.NOCACHE} + }; + } + + private List toList(final String... data) { + return Arrays.asList(data); + } +} diff --git a/inference/src/test/resources/model/encoder.json b/inference/src/test/resources/model/encoder.json new file mode 100644 index 0000000..a708bb6 --- /dev/null +++ b/inference/src/test/resources/model/encoder.json @@ -0,0 +1 @@ +{"input.currency": {"CZK": 0}, "flight.inboundSegments.arrival": {"2019-11-22T12:50:00": 2416, "2019-12-31T15:20:00": 3602, "2019-11-21T22:30:00": 2401, "2019-12-21T22:55:00|2019-12-22T14:05:00": 3374, "2020-01-23T12:55:00": 4230, "2019-10-15T01:55:00|2019-10-15T07:20:00": 563, "2020-01-28T13:15:00|2020-01-28T17:10:00": 4323, "2019-10-30T21:00:00": 1376, "2020-03-21T20:50:00": 5110, "2019-11-13T11:40:00": 2004, "2020-03-16T15:30:00": 5077, "2020-01-22T09:40:00|2020-01-22T22:10:00": 4199, "2019-11-06T06:25:00": 1684, "2019-10-07T10:20:00": 248, "2019-11-12T23:25:00|2019-11-14T06:20:00": 1978, "2020-04-22T21:20:00|2020-04-23T06:30:00": 5358, "2020-02-17T22:20:00": 4667, "2019-10-12T15:05:00": 428, "2019-11-14T14:10:00|2019-11-15T00:50:00|2019-11-15T11:40:00": 2056, "2020-01-02T22:20:00": 3702, "2019-11-20T07:25:00": 2319, "2019-10-25T10:55:00": 1025, "2019-11-23T20:25:00": 2469, "2019-11-11T12:25:00|2019-11-11T23:50:00": 1918, "2020-01-17T00:25:00|2020-01-18T04:25:00": 4088, "2019-11-06T08:25:00": 1692, "2019-11-25T16:05:00": 2559, "2019-11-13T02:40:00|2019-11-13T13:00:00": 1980, "2019-10-31T20:45:00": 1421, "2020-01-06T02:05:00|2020-01-06T17:10:00": 3828, "2020-02-18T15:25:00": 4679, "2019-09-29T15:00:00": 23, "2020-01-12T18:50:00|2020-01-12T22:05:00": 3987, 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ziL%;vBTKcb`19kJlELJ`j1!FCMUzSLbd4!d{czyV6X&NyVr^ss=O6awF;1WVlGpF{ zF-f?;$w8jpXbtKSl*Xq?k~)1Q0KpL+}R?dV|K G{r>>!@J3Yt literal 0 HcmV?d00001 diff --git a/runner.py b/runner.py new file mode 100644 index 0000000..b365f74 --- /dev/null +++ b/runner.py @@ -0,0 +1,33 @@ +import sagemaker +import boto3 +from sagemaker import get_execution_role +from sagemaker.xgboost.estimator import XGBoost + +boto_session = boto3.Session(profile_name='bonitoo', region_name='eu-central-1') + +# local: sagemaker_session = sagemaker.LocalSession(boto_session=boto_session) +sagemaker_session = sagemaker.Session(boto_session=boto_session) + +role = 'Bonitoo_SageMaker_Execution' +train_input = 's3://customers-bonitoo-cachettl/sagemaker/data/export-reduced.csv' + +tf = XGBoost( + entry_point='train_model.py', + source_dir='./src', + train_instance_type='ml.c5.xlarge', + train_instance_count=1, + role=role, + sagemaker_session=sagemaker_session, + framework_version='0.90-1', + py_version='py3', + hyperparameters={ + 'bonitoo_price_limit': 1000, + 'num_round': 15, + 'max_depth': 15, + 'eta': 0.5, + 'num_class': 8, + 'objective': 'multi:softmax', + 'eval_metric': 'mlogloss' + }) + +tf.fit({'training': train_input}) diff --git a/src/train_model.py b/src/train_model.py index f1ea180..15f3103 100644 --- a/src/train_model.py +++ b/src/train_model.py @@ -25,26 +25,10 @@ columns = [ 'flight.inboundSegments.arrival', 'flight.inboundSegments.origin.airportCode', 'flight.inboundSegments.destination.airportCode', - 'flight.inboundSegments.flightNumber', - 'flight.inboundSegments.travelClass', - 'flight.inboundSegments.bookingCode', - 'flight.inboundSegments.availability', - 'flight.inboundSegments.elapsedFlyingTime', 'flight.outboundSegments.departure', 'flight.outboundSegments.arrival', 'flight.outboundSegments.origin.airportCode', 'flight.outboundSegments.destination.airportCode', - 'flight.outboundSegments.flightNumber', - 'flight.outboundSegments.travelClass', - 'flight.outboundSegments.bookingCode', - 'flight.outboundSegments.availability', - 'flight.outboundSegments.elapsedFlyingTime', - 'flight.inboundEFT', - 'flight.outboundEFT', - 'oneWay', - 'adults', - 'children', - 'infants', 'input.price', 'input.tax', 'input.currency', @@ -63,25 +47,12 @@ catcolumns = [ 'flight.inboundSegments.arrival', 'flight.inboundSegments.origin.airportCode', 'flight.inboundSegments.destination.airportCode', - 'flight.inboundSegments.flightNumber', - 'flight.inboundSegments.travelClass', - 'flight.inboundSegments.bookingCode', - 'flight.inboundSegments.availability', - 'flight.inboundSegments.elapsedFlyingTime', 'flight.outboundSegments.departure', 'flight.outboundSegments.arrival', 'flight.outboundSegments.origin.airportCode', 'flight.outboundSegments.destination.airportCode', - 'flight.outboundSegments.flightNumber', - 'flight.outboundSegments.travelClass', - 'flight.outboundSegments.bookingCode', - 'flight.outboundSegments.availability', - 'flight.outboundSegments.elapsedFlyingTime', - 'flight.inboundEFT', - 'flight.outboundEFT', 'input.currency', - 'output.currency', - 'oneWay' + 'output.currency' ] floatcolumns = [ @@ -92,9 +63,6 @@ floatcolumns = [ ] intcolumns = [ - 'adults', - 'children', - 'infants', 'status', 'duration' ] @@ -120,7 +88,7 @@ def expected_value(row, cachetime_df, price_limit=1000): incachetime = tdiff[0] else: incachetime = np.timedelta64('NaT') - + modifier = 0 if pricestatus > price_limit: modifier = -1 @@ -144,7 +112,7 @@ def expected_value(row, cachetime_df, price_limit=1000): return 5 + modifier if incachetime <= np.timedelta64(14,'D'): return 6 + modifier - + return min(7, 7 + modifier) def compute_cached_time(df): @@ -157,9 +125,6 @@ def preprocess_data(df): df.loc[:, 'timestamp'] = df.loc[:, 'timestamp'].apply(lambda x: pd.to_datetime(x)) - booleanDictionary = {True: 'TRUE', False: 'FALSE'} - df.loc[:, 'oneWay'] = df.loc[:, 'oneWay'].replace(booleanDictionary) - for cc in catcolumns: df.loc[:, cc] = df.loc[:, cc].astype('category') df.loc[:, '%s_codes' % cc] = df[cc].cat.codes @@ -218,7 +183,6 @@ def get_pandas_df(data_path): return df - def get_df(train_path, validate_path, content_type='text/csv'): train_files_size = get_size(train_path) if train_path else 0 val_files_size = get_size(validate_path) if validate_path else 0 @@ -253,7 +217,7 @@ def save_encoders(encoder_location, df): jsondata = {} for cc in catcolumns: jsondata[cc] = {cat: idx for idx, cat in enumerate(df[cc].cat.categories)} - + with open(encoder_location, 'w') as f: json.dump(jsondata, f) @@ -261,14 +225,14 @@ def sagemaker_train(train_config, data_config, train_path, val_path, model_dir, checkpoint_config): metrics = metrics_mod.initialize() hyperparameters = hpv.initialize(metrics) - + price_limit = int(train_config.get('bonitoo_price_limit', 1000)) train_config = {k:v.replace('"', '') for k,v in train_config.items() if not k.startswith('sagemaker_') and not k.startswith('bonitoo_')} train_config = hyperparameters.validate(train_config) - + if train_config.get("updater"): train_config["updater"] = ",".join(train_config["updater"]) - + logging.info("hyperparameters {}".format(train_config)) logging.info("channels {}".format(data_config)) @@ -324,7 +288,6 @@ def sagemaker_train(train_config, data_config, train_path, val_path, model_dir, else: raise exc.PlatformError("Number of hosts should be an int greater than or equal to 1") - def train_job(train_cfg, train_dmatrix, val_dmatrix, train_df, model_dir, checkpoint_dir, is_master): # Parse arguments for train() API early_stopping_rounds = train_cfg.get('early_stopping_rounds') @@ -361,10 +324,6 @@ def train_job(train_cfg, train_dmatrix, val_dmatrix, train_df, model_dir, checkp if val_dmatrix: logging.info("Validation matrix has {} rows".format(val_dmatrix.num_row())) - # TODO remove - #logging.info("cols: %s", str(train_dmatrix.feature_names)) - #raise Exception("cols: %s" % str(train_dmatrix.feature_names)) - try: bst = xgb.train(train_cfg, train_dmatrix, num_boost_round=num_round, evals=watchlist, feval=configured_feval, early_stopping_rounds=early_stopping_rounds, callbacks=callbacks, xgb_model=xgb_model, @@ -389,8 +348,6 @@ def train_job(train_cfg, train_dmatrix, val_dmatrix, train_df, model_dir, checkp bst.save_model(model_location) logging.info("Stored trained model at {}".format(model_location)) - - if __name__ == '__main__': with open(os.getenv(sm_env_constants.SM_INPUT_TRAINING_CONFIG_FILE), "r") as f: train_config = json.load(f)