Source code for synapse.ml.cognitive.text.TextAnalyze

# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in project root for information.


import sys
if sys.version >= '3':
    basestring = str

from pyspark import SparkContext, SQLContext
from pyspark.sql import DataFrame
from pyspark.ml.param.shared import *
from pyspark import keyword_only
from pyspark.ml.util import JavaMLReadable, JavaMLWritable
from synapse.ml.core.platform import running_on_synapse_internal
from synapse.ml.core.serialize.java_params_patch import *
from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
from pyspark.ml.evaluation import JavaEvaluator
from pyspark.ml.common import inherit_doc
from synapse.ml.core.schema.Utils import *
from pyspark.ml.param import TypeConverters
from synapse.ml.core.schema.TypeConversionUtils import generateTypeConverter, complexTypeConverter


[docs]@inherit_doc class TextAnalyze(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer): """ Args: AADToken (object): AAD Token used for authentication CustomAuthHeader (object): A Custom Value for Authorization Header backoffs (list): array of backoffs to use in the handler batchSize (int): The max size of the buffer concurrency (int): max number of concurrent calls concurrentTimeout (float): max number seconds to wait on futures if concurrency >= 1 disableServiceLogs (object): disableServiceLogs option entityLinkingParams (dict): the parameters to pass to the entityLinking model entityRecognitionParams (dict): the parameters to pass to the entity recognition model errorCol (str): column to hold http errors includeEntityLinking (bool): Whether to perform EntityLinking includeEntityRecognition (bool): Whether to perform entity recognition includeKeyPhraseExtraction (bool): Whether to perform EntityLinking includePii (bool): Whether to perform PII Detection includeSentimentAnalysis (bool): Whether to perform SentimentAnalysis initialPollingDelay (int): number of milliseconds to wait before first poll for result keyPhraseExtractionParams (dict): the parameters to pass to the keyPhraseExtraction model language (object): the language code of the text (optional for some services) maxPollingRetries (int): number of times to poll modelVersion (object): Version of the model outputCol (str): The name of the output column piiParams (dict): the parameters to pass to the PII model pollingDelay (int): number of milliseconds to wait between polling sentimentAnalysisParams (dict): the parameters to pass to the sentimentAnalysis model showStats (object): Whether to include detailed statistics in the response subscriptionKey (object): the API key to use suppressMaxRetriesException (bool): set true to suppress the maxumimum retries exception and report in the error column text (object): the text in the request body timeout (float): number of seconds to wait before closing the connection url (str): Url of the service """ AADToken = Param(Params._dummy(), "AADToken", "ServiceParam: AAD Token used for authentication") CustomAuthHeader = Param(Params._dummy(), "CustomAuthHeader", "ServiceParam: A Custom Value for Authorization Header") backoffs = Param(Params._dummy(), "backoffs", "array of backoffs to use in the handler", typeConverter=TypeConverters.toListInt) batchSize = Param(Params._dummy(), "batchSize", "The max size of the buffer", typeConverter=TypeConverters.toInt) concurrency = Param(Params._dummy(), "concurrency", "max number of concurrent calls", typeConverter=TypeConverters.toInt) concurrentTimeout = Param(Params._dummy(), "concurrentTimeout", "max number seconds to wait on futures if concurrency >= 1", typeConverter=TypeConverters.toFloat) disableServiceLogs = Param(Params._dummy(), "disableServiceLogs", "ServiceParam: disableServiceLogs option") entityLinkingParams = Param(Params._dummy(), "entityLinkingParams", "the parameters to pass to the entityLinking model") entityRecognitionParams = Param(Params._dummy(), "entityRecognitionParams", "the parameters to pass to the entity recognition model") errorCol = Param(Params._dummy(), "errorCol", "column to hold http errors", typeConverter=TypeConverters.toString) includeEntityLinking = Param(Params._dummy(), "includeEntityLinking", "Whether to perform EntityLinking", typeConverter=TypeConverters.toBoolean) includeEntityRecognition = Param(Params._dummy(), "includeEntityRecognition", "Whether to perform entity recognition", typeConverter=TypeConverters.toBoolean) includeKeyPhraseExtraction = Param(Params._dummy(), "includeKeyPhraseExtraction", "Whether to perform EntityLinking", typeConverter=TypeConverters.toBoolean) includePii = Param(Params._dummy(), "includePii", "Whether to perform PII Detection", typeConverter=TypeConverters.toBoolean) includeSentimentAnalysis = Param(Params._dummy(), "includeSentimentAnalysis", "Whether to perform SentimentAnalysis", typeConverter=TypeConverters.toBoolean) initialPollingDelay = Param(Params._dummy(), "initialPollingDelay", "number of milliseconds to wait before first poll for result", typeConverter=TypeConverters.toInt) keyPhraseExtractionParams = Param(Params._dummy(), "keyPhraseExtractionParams", "the parameters to pass to the keyPhraseExtraction model") language = Param(Params._dummy(), "language", "ServiceParam: the language code of the text (optional for some services)") maxPollingRetries = Param(Params._dummy(), "maxPollingRetries", "number of times to poll", typeConverter=TypeConverters.toInt) modelVersion = Param(Params._dummy(), "modelVersion", "ServiceParam: Version of the model") outputCol = Param(Params._dummy(), "outputCol", "The name of the output column", typeConverter=TypeConverters.toString) piiParams = Param(Params._dummy(), "piiParams", "the parameters to pass to the PII model") pollingDelay = Param(Params._dummy(), "pollingDelay", "number of milliseconds to wait between polling", typeConverter=TypeConverters.toInt) sentimentAnalysisParams = Param(Params._dummy(), "sentimentAnalysisParams", "the parameters to pass to the sentimentAnalysis model") showStats = Param(Params._dummy(), "showStats", "ServiceParam: Whether to include detailed statistics in the response") subscriptionKey = Param(Params._dummy(), "subscriptionKey", "ServiceParam: the API key to use") suppressMaxRetriesException = Param(Params._dummy(), "suppressMaxRetriesException", "set true to suppress the maxumimum retries exception and report in the error column", typeConverter=TypeConverters.toBoolean) text = Param(Params._dummy(), "text", "ServiceParam: the text in the request body") timeout = Param(Params._dummy(), "timeout", "number of seconds to wait before closing the connection", typeConverter=TypeConverters.toFloat) url = Param(Params._dummy(), "url", "Url of the service", typeConverter=TypeConverters.toString) @keyword_only def __init__( self, java_obj=None, AADToken=None, AADTokenCol=None, CustomAuthHeader=None, CustomAuthHeaderCol=None, backoffs=[100,500,1000], batchSize=10, concurrency=1, concurrentTimeout=None, disableServiceLogs=None, disableServiceLogsCol=None, entityLinkingParams={"model-version":"latest"}, entityRecognitionParams={"model-version":"latest"}, errorCol="TextAnalyze_2cbd7d7f4c03_error", includeEntityLinking=True, includeEntityRecognition=True, includeKeyPhraseExtraction=True, includePii=True, includeSentimentAnalysis=True, initialPollingDelay=300, keyPhraseExtractionParams={"model-version":"latest"}, language=None, languageCol=None, maxPollingRetries=1000, modelVersion=None, modelVersionCol=None, outputCol="TextAnalyze_2cbd7d7f4c03_output", piiParams={"model-version":"latest"}, pollingDelay=300, sentimentAnalysisParams={"model-version":"latest"}, showStats=None, showStatsCol=None, subscriptionKey=None, subscriptionKeyCol=None, suppressMaxRetriesException=False, text=None, textCol=None, timeout=60.0, url=None ): super(TextAnalyze, self).__init__() if java_obj is None: self._java_obj = self._new_java_obj("com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyze", self.uid) else: self._java_obj = java_obj self._setDefault(backoffs=[100,500,1000]) self._setDefault(batchSize=10) self._setDefault(concurrency=1) self._setDefault(entityLinkingParams={"model-version":"latest"}) self._setDefault(entityRecognitionParams={"model-version":"latest"}) self._setDefault(errorCol="TextAnalyze_2cbd7d7f4c03_error") self._setDefault(includeEntityLinking=True) self._setDefault(includeEntityRecognition=True) self._setDefault(includeKeyPhraseExtraction=True) self._setDefault(includePii=True) self._setDefault(includeSentimentAnalysis=True) self._setDefault(initialPollingDelay=300) self._setDefault(keyPhraseExtractionParams={"model-version":"latest"}) self._setDefault(maxPollingRetries=1000) self._setDefault(outputCol="TextAnalyze_2cbd7d7f4c03_output") self._setDefault(piiParams={"model-version":"latest"}) self._setDefault(pollingDelay=300) self._setDefault(sentimentAnalysisParams={"model-version":"latest"}) self._setDefault(suppressMaxRetriesException=False) self._setDefault(timeout=60.0) if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs if java_obj is None: for k,v in kwargs.items(): if v is not None: getattr(self, "set" + k[0].upper() + k[1:])(v)
[docs] @keyword_only def setParams( self, AADToken=None, AADTokenCol=None, CustomAuthHeader=None, CustomAuthHeaderCol=None, backoffs=[100,500,1000], batchSize=10, concurrency=1, concurrentTimeout=None, disableServiceLogs=None, disableServiceLogsCol=None, entityLinkingParams={"model-version":"latest"}, entityRecognitionParams={"model-version":"latest"}, errorCol="TextAnalyze_2cbd7d7f4c03_error", includeEntityLinking=True, includeEntityRecognition=True, includeKeyPhraseExtraction=True, includePii=True, includeSentimentAnalysis=True, initialPollingDelay=300, keyPhraseExtractionParams={"model-version":"latest"}, language=None, languageCol=None, maxPollingRetries=1000, modelVersion=None, modelVersionCol=None, outputCol="TextAnalyze_2cbd7d7f4c03_output", piiParams={"model-version":"latest"}, pollingDelay=300, sentimentAnalysisParams={"model-version":"latest"}, showStats=None, showStatsCol=None, subscriptionKey=None, subscriptionKeyCol=None, suppressMaxRetriesException=False, text=None, textCol=None, timeout=60.0, url=None ): """ Set the (keyword only) parameters """ if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs return self._set(**kwargs)
[docs] @classmethod def read(cls): """ Returns an MLReader instance for this class. """ return JavaMMLReader(cls)
[docs] @staticmethod def getJavaPackage(): """ Returns package name String. """ return "com.microsoft.azure.synapse.ml.cognitive.text.TextAnalyze"
@staticmethod def _from_java(java_stage): module_name=TextAnalyze.__module__ module_name=module_name.rsplit(".", 1)[0] + ".TextAnalyze" return from_java(java_stage, module_name)
[docs] def setAADToken(self, value): """ Args: AADToken: AAD Token used for authentication """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setAADToken(value) return self
[docs] def setAADTokenCol(self, value): """ Args: AADToken: AAD Token used for authentication """ self._java_obj = self._java_obj.setAADTokenCol(value) return self
[docs] def setCustomAuthHeader(self, value): """ Args: CustomAuthHeader: A Custom Value for Authorization Header """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setCustomAuthHeader(value) return self
[docs] def setCustomAuthHeaderCol(self, value): """ Args: CustomAuthHeader: A Custom Value for Authorization Header """ self._java_obj = self._java_obj.setCustomAuthHeaderCol(value) return self
[docs] def setBackoffs(self, value): """ Args: backoffs: array of backoffs to use in the handler """ self._set(backoffs=value) return self
[docs] def setBatchSize(self, value): """ Args: batchSize: The max size of the buffer """ self._set(batchSize=value) return self
[docs] def setConcurrency(self, value): """ Args: concurrency: max number of concurrent calls """ self._set(concurrency=value) return self
[docs] def setConcurrentTimeout(self, value): """ Args: concurrentTimeout: max number seconds to wait on futures if concurrency >= 1 """ self._set(concurrentTimeout=value) return self
[docs] def setDisableServiceLogs(self, value): """ Args: disableServiceLogs: disableServiceLogs option """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setDisableServiceLogs(value) return self
[docs] def setDisableServiceLogsCol(self, value): """ Args: disableServiceLogs: disableServiceLogs option """ self._java_obj = self._java_obj.setDisableServiceLogsCol(value) return self
[docs] def setEntityLinkingParams(self, value): """ Args: entityLinkingParams: the parameters to pass to the entityLinking model """ self._set(entityLinkingParams=value) return self
[docs] def setEntityRecognitionParams(self, value): """ Args: entityRecognitionParams: the parameters to pass to the entity recognition model """ self._set(entityRecognitionParams=value) return self
[docs] def setErrorCol(self, value): """ Args: errorCol: column to hold http errors """ self._set(errorCol=value) return self
[docs] def setIncludeEntityLinking(self, value): """ Args: includeEntityLinking: Whether to perform EntityLinking """ self._set(includeEntityLinking=value) return self
[docs] def setIncludeEntityRecognition(self, value): """ Args: includeEntityRecognition: Whether to perform entity recognition """ self._set(includeEntityRecognition=value) return self
[docs] def setIncludeKeyPhraseExtraction(self, value): """ Args: includeKeyPhraseExtraction: Whether to perform EntityLinking """ self._set(includeKeyPhraseExtraction=value) return self
[docs] def setIncludePii(self, value): """ Args: includePii: Whether to perform PII Detection """ self._set(includePii=value) return self
[docs] def setIncludeSentimentAnalysis(self, value): """ Args: includeSentimentAnalysis: Whether to perform SentimentAnalysis """ self._set(includeSentimentAnalysis=value) return self
[docs] def setInitialPollingDelay(self, value): """ Args: initialPollingDelay: number of milliseconds to wait before first poll for result """ self._set(initialPollingDelay=value) return self
[docs] def setKeyPhraseExtractionParams(self, value): """ Args: keyPhraseExtractionParams: the parameters to pass to the keyPhraseExtraction model """ self._set(keyPhraseExtractionParams=value) return self
[docs] def setLanguage(self, value): """ Args: language: the language code of the text (optional for some services) """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setLanguage(value) return self
[docs] def setLanguageCol(self, value): """ Args: language: the language code of the text (optional for some services) """ self._java_obj = self._java_obj.setLanguageCol(value) return self
[docs] def setMaxPollingRetries(self, value): """ Args: maxPollingRetries: number of times to poll """ self._set(maxPollingRetries=value) return self
[docs] def setModelVersion(self, value): """ Args: modelVersion: Version of the model """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setModelVersion(value) return self
[docs] def setModelVersionCol(self, value): """ Args: modelVersion: Version of the model """ self._java_obj = self._java_obj.setModelVersionCol(value) return self
[docs] def setOutputCol(self, value): """ Args: outputCol: The name of the output column """ self._set(outputCol=value) return self
[docs] def setPiiParams(self, value): """ Args: piiParams: the parameters to pass to the PII model """ self._set(piiParams=value) return self
[docs] def setPollingDelay(self, value): """ Args: pollingDelay: number of milliseconds to wait between polling """ self._set(pollingDelay=value) return self
[docs] def setSentimentAnalysisParams(self, value): """ Args: sentimentAnalysisParams: the parameters to pass to the sentimentAnalysis model """ self._set(sentimentAnalysisParams=value) return self
[docs] def setShowStats(self, value): """ Args: showStats: Whether to include detailed statistics in the response """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setShowStats(value) return self
[docs] def setShowStatsCol(self, value): """ Args: showStats: Whether to include detailed statistics in the response """ self._java_obj = self._java_obj.setShowStatsCol(value) return self
[docs] def setSubscriptionKey(self, value): """ Args: subscriptionKey: the API key to use """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setSubscriptionKey(value) return self
[docs] def setSubscriptionKeyCol(self, value): """ Args: subscriptionKey: the API key to use """ self._java_obj = self._java_obj.setSubscriptionKeyCol(value) return self
[docs] def setSuppressMaxRetriesException(self, value): """ Args: suppressMaxRetriesException: set true to suppress the maxumimum retries exception and report in the error column """ self._set(suppressMaxRetriesException=value) return self
[docs] def setText(self, value): """ Args: text: the text in the request body """ if isinstance(value, list): value = SparkContext._active_spark_context._jvm.com.microsoft.azure.synapse.ml.param.ServiceParam.toSeq(value) self._java_obj = self._java_obj.setText(value) return self
[docs] def setTextCol(self, value): """ Args: text: the text in the request body """ self._java_obj = self._java_obj.setTextCol(value) return self
[docs] def setTimeout(self, value): """ Args: timeout: number of seconds to wait before closing the connection """ self._set(timeout=value) return self
[docs] def setUrl(self, value): """ Args: url: Url of the service """ self._set(url=value) return self
[docs] def getAADToken(self): """ Returns: AADToken: AAD Token used for authentication """ return self._java_obj.getAADToken()
[docs] def getCustomAuthHeader(self): """ Returns: CustomAuthHeader: A Custom Value for Authorization Header """ return self._java_obj.getCustomAuthHeader()
[docs] def getBackoffs(self): """ Returns: backoffs: array of backoffs to use in the handler """ return self.getOrDefault(self.backoffs)
[docs] def getBatchSize(self): """ Returns: batchSize: The max size of the buffer """ return self.getOrDefault(self.batchSize)
[docs] def getConcurrency(self): """ Returns: concurrency: max number of concurrent calls """ return self.getOrDefault(self.concurrency)
[docs] def getConcurrentTimeout(self): """ Returns: concurrentTimeout: max number seconds to wait on futures if concurrency >= 1 """ return self.getOrDefault(self.concurrentTimeout)
[docs] def getDisableServiceLogs(self): """ Returns: disableServiceLogs: disableServiceLogs option """ return self._java_obj.getDisableServiceLogs()
[docs] def getEntityLinkingParams(self): """ Returns: entityLinkingParams: the parameters to pass to the entityLinking model """ return self.getOrDefault(self.entityLinkingParams)
[docs] def getEntityRecognitionParams(self): """ Returns: entityRecognitionParams: the parameters to pass to the entity recognition model """ return self.getOrDefault(self.entityRecognitionParams)
[docs] def getErrorCol(self): """ Returns: errorCol: column to hold http errors """ return self.getOrDefault(self.errorCol)
[docs] def getIncludeEntityLinking(self): """ Returns: includeEntityLinking: Whether to perform EntityLinking """ return self.getOrDefault(self.includeEntityLinking)
[docs] def getIncludeEntityRecognition(self): """ Returns: includeEntityRecognition: Whether to perform entity recognition """ return self.getOrDefault(self.includeEntityRecognition)
[docs] def getIncludeKeyPhraseExtraction(self): """ Returns: includeKeyPhraseExtraction: Whether to perform EntityLinking """ return self.getOrDefault(self.includeKeyPhraseExtraction)
[docs] def getIncludePii(self): """ Returns: includePii: Whether to perform PII Detection """ return self.getOrDefault(self.includePii)
[docs] def getIncludeSentimentAnalysis(self): """ Returns: includeSentimentAnalysis: Whether to perform SentimentAnalysis """ return self.getOrDefault(self.includeSentimentAnalysis)
[docs] def getInitialPollingDelay(self): """ Returns: initialPollingDelay: number of milliseconds to wait before first poll for result """ return self.getOrDefault(self.initialPollingDelay)
[docs] def getKeyPhraseExtractionParams(self): """ Returns: keyPhraseExtractionParams: the parameters to pass to the keyPhraseExtraction model """ return self.getOrDefault(self.keyPhraseExtractionParams)
[docs] def getLanguage(self): """ Returns: language: the language code of the text (optional for some services) """ return self._java_obj.getLanguage()
[docs] def getMaxPollingRetries(self): """ Returns: maxPollingRetries: number of times to poll """ return self.getOrDefault(self.maxPollingRetries)
[docs] def getModelVersion(self): """ Returns: modelVersion: Version of the model """ return self._java_obj.getModelVersion()
[docs] def getOutputCol(self): """ Returns: outputCol: The name of the output column """ return self.getOrDefault(self.outputCol)
[docs] def getPiiParams(self): """ Returns: piiParams: the parameters to pass to the PII model """ return self.getOrDefault(self.piiParams)
[docs] def getPollingDelay(self): """ Returns: pollingDelay: number of milliseconds to wait between polling """ return self.getOrDefault(self.pollingDelay)
[docs] def getSentimentAnalysisParams(self): """ Returns: sentimentAnalysisParams: the parameters to pass to the sentimentAnalysis model """ return self.getOrDefault(self.sentimentAnalysisParams)
[docs] def getShowStats(self): """ Returns: showStats: Whether to include detailed statistics in the response """ return self._java_obj.getShowStats()
[docs] def getSubscriptionKey(self): """ Returns: subscriptionKey: the API key to use """ return self._java_obj.getSubscriptionKey()
[docs] def getSuppressMaxRetriesException(self): """ Returns: suppressMaxRetriesException: set true to suppress the maxumimum retries exception and report in the error column """ return self.getOrDefault(self.suppressMaxRetriesException)
[docs] def getText(self): """ Returns: text: the text in the request body """ return self._java_obj.getText()
[docs] def getTimeout(self): """ Returns: timeout: number of seconds to wait before closing the connection """ return self.getOrDefault(self.timeout)
[docs] def getUrl(self): """ Returns: url: Url of the service """ return self.getOrDefault(self.url)
[docs] def setCustomServiceName(self, value): self._java_obj = self._java_obj.setCustomServiceName(value) return self
[docs] def setEndpoint(self, value): self._java_obj = self._java_obj.setEndpoint(value) return self
[docs] def setDefaultInternalEndpoint(self, value): self._java_obj = self._java_obj.setDefaultInternalEndpoint(value) return self
def _transform(self, dataset: DataFrame) -> DataFrame: if running_on_synapse_internal(): try: from synapse.ml.fabric.token_utils import TokenUtils from synapse.ml.fabric.service_discovery import get_fabric_env_config fabric_env_config = get_fabric_env_config().fabric_env_config if self._java_obj.getInternalServiceType() != "openai": self._java_obj.setDefaultAADToken(TokenUtils().get_aad_token()) else: self._java_obj.setDefaultCustomAuthHeader(TokenUtils().get_openai_auth_header()) self.setDefaultInternalEndpoint(fabric_env_config.get_mlflow_workload_endpoint()) except ModuleNotFoundError as e: pass return super()._transform(dataset)
[docs] def setLocation(self, value): self._java_obj = self._java_obj.setLocation(value) return self
[docs] def setLinkedService(self, value): self._java_obj = self._java_obj.setLinkedService(value) return self