# 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 FindSimilarFace(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer):
"""
Args:
AADToken (object): AAD Token used for authentication
concurrency (int): max number of concurrent calls
concurrentTimeout (float): max number seconds to wait on futures if concurrency >= 1
errorCol (str): column to hold http errors
faceId (object): faceId of the query face. User needs to call FaceDetect first to get a valid faceId. Note that this faceId is not persisted and will expire 24 hours after the detection call.
faceIds (object): An array of candidate faceIds. All of them are created by FaceDetect and the faceIds will expire 24 hours after the detection call. The number of faceIds is limited to 1000. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
faceListId (object): An existing user-specified unique candidate face list, created in FaceList - Create. Face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
handler (object): Which strategy to use when handling requests
largeFaceListId (object): An existing user-specified unique candidate large face list, created in LargeFaceList - Create. Large face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
maxNumOfCandidatesReturned (object): Optional parameter. The number of top similar faces returned. The valid range is [1, 1000].It defaults to 20.
mode (object): Optional parameter. Similar face searching mode. It can be 'matchPerson' or 'matchFace'. It defaults to 'matchPerson'.
outputCol (str): The name of the output column
subscriptionKey (object): the API key to use
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")
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)
errorCol = Param(Params._dummy(), "errorCol", "column to hold http errors", typeConverter=TypeConverters.toString)
faceId = Param(Params._dummy(), "faceId", "ServiceParam: faceId of the query face. User needs to call FaceDetect first to get a valid faceId. Note that this faceId is not persisted and will expire 24 hours after the detection call.")
faceIds = Param(Params._dummy(), "faceIds", "ServiceParam: An array of candidate faceIds. All of them are created by FaceDetect and the faceIds will expire 24 hours after the detection call. The number of faceIds is limited to 1000. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.")
faceListId = Param(Params._dummy(), "faceListId", "ServiceParam: An existing user-specified unique candidate face list, created in FaceList - Create. Face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.")
handler = Param(Params._dummy(), "handler", "Which strategy to use when handling requests")
largeFaceListId = Param(Params._dummy(), "largeFaceListId", "ServiceParam: An existing user-specified unique candidate large face list, created in LargeFaceList - Create. Large face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.")
maxNumOfCandidatesReturned = Param(Params._dummy(), "maxNumOfCandidatesReturned", "ServiceParam: Optional parameter. The number of top similar faces returned. The valid range is [1, 1000].It defaults to 20.")
mode = Param(Params._dummy(), "mode", "ServiceParam: Optional parameter. Similar face searching mode. It can be 'matchPerson' or 'matchFace'. It defaults to 'matchPerson'.")
outputCol = Param(Params._dummy(), "outputCol", "The name of the output column", typeConverter=TypeConverters.toString)
subscriptionKey = Param(Params._dummy(), "subscriptionKey", "ServiceParam: the API key to use")
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,
concurrency=1,
concurrentTimeout=None,
errorCol="FindSimilarFace_eab1bba35bc3_error",
faceId=None,
faceIdCol=None,
faceIds=None,
faceIdsCol=None,
faceListId=None,
faceListIdCol=None,
handler=None,
largeFaceListId=None,
largeFaceListIdCol=None,
maxNumOfCandidatesReturned=None,
maxNumOfCandidatesReturnedCol=None,
mode=None,
modeCol=None,
outputCol="FindSimilarFace_eab1bba35bc3_output",
subscriptionKey=None,
subscriptionKeyCol=None,
timeout=60.0,
url=None
):
super(FindSimilarFace, self).__init__()
if java_obj is None:
self._java_obj = self._new_java_obj("com.microsoft.azure.synapse.ml.cognitive.face.FindSimilarFace", self.uid)
else:
self._java_obj = java_obj
self._setDefault(concurrency=1)
self._setDefault(errorCol="FindSimilarFace_eab1bba35bc3_error")
self._setDefault(outputCol="FindSimilarFace_eab1bba35bc3_output")
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,
concurrency=1,
concurrentTimeout=None,
errorCol="FindSimilarFace_eab1bba35bc3_error",
faceId=None,
faceIdCol=None,
faceIds=None,
faceIdsCol=None,
faceListId=None,
faceListIdCol=None,
handler=None,
largeFaceListId=None,
largeFaceListIdCol=None,
maxNumOfCandidatesReturned=None,
maxNumOfCandidatesReturnedCol=None,
mode=None,
modeCol=None,
outputCol="FindSimilarFace_eab1bba35bc3_output",
subscriptionKey=None,
subscriptionKeyCol=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.face.FindSimilarFace"
@staticmethod
def _from_java(java_stage):
module_name=FindSimilarFace.__module__
module_name=module_name.rsplit(".", 1)[0] + ".FindSimilarFace"
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 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 setErrorCol(self, value):
"""
Args:
errorCol: column to hold http errors
"""
self._set(errorCol=value)
return self
[docs] def setFaceId(self, value):
"""
Args:
faceId: faceId of the query face. User needs to call FaceDetect first to get a valid faceId. Note that this faceId is not persisted and will expire 24 hours after the detection call.
"""
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.setFaceId(value)
return self
[docs] def setFaceIdCol(self, value):
"""
Args:
faceId: faceId of the query face. User needs to call FaceDetect first to get a valid faceId. Note that this faceId is not persisted and will expire 24 hours after the detection call.
"""
self._java_obj = self._java_obj.setFaceIdCol(value)
return self
[docs] def setFaceIds(self, value):
"""
Args:
faceIds: An array of candidate faceIds. All of them are created by FaceDetect and the faceIds will expire 24 hours after the detection call. The number of faceIds is limited to 1000. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
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.setFaceIds(value)
return self
[docs] def setFaceIdsCol(self, value):
"""
Args:
faceIds: An array of candidate faceIds. All of them are created by FaceDetect and the faceIds will expire 24 hours after the detection call. The number of faceIds is limited to 1000. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
self._java_obj = self._java_obj.setFaceIdsCol(value)
return self
[docs] def setFaceListId(self, value):
"""
Args:
faceListId: An existing user-specified unique candidate face list, created in FaceList - Create. Face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
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.setFaceListId(value)
return self
[docs] def setFaceListIdCol(self, value):
"""
Args:
faceListId: An existing user-specified unique candidate face list, created in FaceList - Create. Face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
self._java_obj = self._java_obj.setFaceListIdCol(value)
return self
[docs] def setHandler(self, value):
"""
Args:
handler: Which strategy to use when handling requests
"""
self._set(handler=value)
return self
[docs] def setLargeFaceListId(self, value):
"""
Args:
largeFaceListId: An existing user-specified unique candidate large face list, created in LargeFaceList - Create. Large face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
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.setLargeFaceListId(value)
return self
[docs] def setLargeFaceListIdCol(self, value):
"""
Args:
largeFaceListId: An existing user-specified unique candidate large face list, created in LargeFaceList - Create. Large face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
self._java_obj = self._java_obj.setLargeFaceListIdCol(value)
return self
[docs] def setMaxNumOfCandidatesReturned(self, value):
"""
Args:
maxNumOfCandidatesReturned: Optional parameter. The number of top similar faces returned. The valid range is [1, 1000].It defaults to 20.
"""
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.setMaxNumOfCandidatesReturned(value)
return self
[docs] def setMaxNumOfCandidatesReturnedCol(self, value):
"""
Args:
maxNumOfCandidatesReturned: Optional parameter. The number of top similar faces returned. The valid range is [1, 1000].It defaults to 20.
"""
self._java_obj = self._java_obj.setMaxNumOfCandidatesReturnedCol(value)
return self
[docs] def setMode(self, value):
"""
Args:
mode: Optional parameter. Similar face searching mode. It can be 'matchPerson' or 'matchFace'. It defaults to 'matchPerson'.
"""
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.setMode(value)
return self
[docs] def setModeCol(self, value):
"""
Args:
mode: Optional parameter. Similar face searching mode. It can be 'matchPerson' or 'matchFace'. It defaults to 'matchPerson'.
"""
self._java_obj = self._java_obj.setModeCol(value)
return self
[docs] def setOutputCol(self, value):
"""
Args:
outputCol: The name of the output column
"""
self._set(outputCol=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 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 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 getErrorCol(self):
"""
Returns:
errorCol: column to hold http errors
"""
return self.getOrDefault(self.errorCol)
[docs] def getFaceId(self):
"""
Returns:
faceId: faceId of the query face. User needs to call FaceDetect first to get a valid faceId. Note that this faceId is not persisted and will expire 24 hours after the detection call.
"""
return self._java_obj.getFaceId()
[docs] def getFaceIds(self):
"""
Returns:
faceIds: An array of candidate faceIds. All of them are created by FaceDetect and the faceIds will expire 24 hours after the detection call. The number of faceIds is limited to 1000. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
return self._java_obj.getFaceIds()
[docs] def getFaceListId(self):
"""
Returns:
faceListId: An existing user-specified unique candidate face list, created in FaceList - Create. Face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
return self._java_obj.getFaceListId()
[docs] def getHandler(self):
"""
Returns:
handler: Which strategy to use when handling requests
"""
return self.getOrDefault(self.handler)
[docs] def getLargeFaceListId(self):
"""
Returns:
largeFaceListId: An existing user-specified unique candidate large face list, created in LargeFaceList - Create. Large face list contains a set of persistedFaceIds which are persisted and will never expire. Parameter faceListId, largeFaceListId and faceIds should not be provided at the same time.
"""
return self._java_obj.getLargeFaceListId()
[docs] def getMaxNumOfCandidatesReturned(self):
"""
Returns:
maxNumOfCandidatesReturned: Optional parameter. The number of top similar faces returned. The valid range is [1, 1000].It defaults to 20.
"""
return self._java_obj.getMaxNumOfCandidatesReturned()
[docs] def getMode(self):
"""
Returns:
mode: Optional parameter. Similar face searching mode. It can be 'matchPerson' or 'matchFace'. It defaults to 'matchPerson'.
"""
return self._java_obj.getMode()
[docs] def getOutputCol(self):
"""
Returns:
outputCol: The name of the output column
"""
return self.getOrDefault(self.outputCol)
[docs] def getSubscriptionKey(self):
"""
Returns:
subscriptionKey: the API key to use
"""
return self._java_obj.getSubscriptionKey()
[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():
from synapse.ml.mlflow import get_mlflow_env_config
mlflow_env_configs = get_mlflow_env_config()
self._java_obj.setDefaultAADToken(mlflow_env_configs.driver_aad_token)
self.setDefaultInternalEndpoint(mlflow_env_configs.workload_endpoint)
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