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<?php
/*
* Copyright 2014 Google Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
namespace Google\Service\Aiplatform;
class GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs extends \Google\Model
{
/**
* Should not be set.
*/
public const MODEL_TYPE_MODEL_TYPE_UNSPECIFIED = 'MODEL_TYPE_UNSPECIFIED';
/**
* A model best tailored to be used within Google Cloud, and which cannot be
* exported. Expected to have a higher latency, but should also have a higher
* prediction quality than other cloud models.
*/
public const MODEL_TYPE_CLOUD_HIGH_ACCURACY_1 = 'CLOUD_HIGH_ACCURACY_1';
/**
* A model best tailored to be used within Google Cloud, and which cannot be
* exported. Expected to have a low latency, but may have lower prediction
* quality than other cloud models.
*/
public const MODEL_TYPE_CLOUD_LOW_LATENCY_1 = 'CLOUD_LOW_LATENCY_1';
/**
* A model best tailored to be used within Google Cloud, and which cannot be
* exported. Compared to the CLOUD_HIGH_ACCURACY_1 and CLOUD_LOW_LATENCY_1
* models above, it is expected to have higher prediction quality and lower
* latency.
*/
public const MODEL_TYPE_CLOUD_1 = 'CLOUD_1';
/**
* A model that, in addition to being available within Google Cloud can also
* be exported (see ModelService.ExportModel) and used on a mobile or edge
* device with TensorFlow afterwards. Expected to have low latency, but may
* have lower prediction quality than other mobile models.
*/
public const MODEL_TYPE_MOBILE_TF_LOW_LATENCY_1 = 'MOBILE_TF_LOW_LATENCY_1';
/**
* A model that, in addition to being available within Google Cloud can also
* be exported (see ModelService.ExportModel) and used on a mobile or edge
* device with TensorFlow afterwards.
*/
public const MODEL_TYPE_MOBILE_TF_VERSATILE_1 = 'MOBILE_TF_VERSATILE_1';
/**
* A model that, in addition to being available within Google Cloud, can also
* be exported (see ModelService.ExportModel) and used on a mobile or edge
* device with TensorFlow afterwards. Expected to have a higher latency, but
* should also have a higher prediction quality than other mobile models.
*/
public const MODEL_TYPE_MOBILE_TF_HIGH_ACCURACY_1 = 'MOBILE_TF_HIGH_ACCURACY_1';
/**
* A model best tailored to be used within Google Cloud, and which cannot be
* exported. Expected to best support predictions in streaming with lower
* latency and lower prediction quality than other cloud models.
*/
public const MODEL_TYPE_CLOUD_STREAMING_1 = 'CLOUD_STREAMING_1';
/**
* SpineNet for Model Garden training with customizable hyperparameters. Best
* tailored to be used within Google Cloud, and cannot be exported externally.
*/
public const MODEL_TYPE_SPINENET = 'SPINENET';
/**
* YOLO for Model Garden training with customizable hyperparameters. Best
* tailored to be used within Google Cloud, and cannot be exported externally.
*/
public const MODEL_TYPE_YOLO = 'YOLO';
/**
* The training budget of creating this model, expressed in milli node hours
* i.e. 1,000 value in this field means 1 node hour. The actual
* metadata.costMilliNodeHours will be equal or less than this value. If
* further model training ceases to provide any improvements, it will stop
* without using the full budget and the metadata.successfulStopReason will be
* `model-converged`. Note, node_hour = actual_hour *
* number_of_nodes_involved. For modelType `cloud`(default), the budget must
* be between 20,000 and 900,000 milli node hours, inclusive. The default
* value is 216,000 which represents one day in wall time, considering 9 nodes
* are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-
* versatile-1`, `mobile-tf-high-accuracy-1` the training budget must be
* between 1,000 and 100,000 milli node hours, inclusive. The default value is
* 24,000 which represents one day in wall time on a single node that is used.
*
* @var string
*/
public $budgetMilliNodeHours;
/**
* Use the entire training budget. This disables the early stopping feature.
* When false the early stopping feature is enabled, which means that AutoML
* Image Object Detection might stop training before the entire training
* budget has been used.
*
* @var bool
*/
public $disableEarlyStopping;
/**
* @var string
*/
public $modelType;
protected $tunableParameterType = GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter::class;
protected $tunableParameterDataType = '';
/**
* The ID of `base` model for upTraining. If it is specified, the new model
* will be upTrained based on the `base` model for upTraining. Otherwise, the
* new model will be trained from scratch. The `base` model for upTraining
* must be in the same Project and Location as the new Model to train, and
* have the same modelType.
*
* @var string
*/
public $uptrainBaseModelId;
/**
* The training budget of creating this model, expressed in milli node hours
* i.e. 1,000 value in this field means 1 node hour. The actual
* metadata.costMilliNodeHours will be equal or less than this value. If
* further model training ceases to provide any improvements, it will stop
* without using the full budget and the metadata.successfulStopReason will be
* `model-converged`. Note, node_hour = actual_hour *
* number_of_nodes_involved. For modelType `cloud`(default), the budget must
* be between 20,000 and 900,000 milli node hours, inclusive. The default
* value is 216,000 which represents one day in wall time, considering 9 nodes
* are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-
* versatile-1`, `mobile-tf-high-accuracy-1` the training budget must be
* between 1,000 and 100,000 milli node hours, inclusive. The default value is
* 24,000 which represents one day in wall time on a single node that is used.
*
* @param string $budgetMilliNodeHours
*/
public function setBudgetMilliNodeHours($budgetMilliNodeHours)
{
$this->budgetMilliNodeHours = $budgetMilliNodeHours;
}
/**
* @return string
*/
public function getBudgetMilliNodeHours()
{
return $this->budgetMilliNodeHours;
}
/**
* Use the entire training budget. This disables the early stopping feature.
* When false the early stopping feature is enabled, which means that AutoML
* Image Object Detection might stop training before the entire training
* budget has been used.
*
* @param bool $disableEarlyStopping
*/
public function setDisableEarlyStopping($disableEarlyStopping)
{
$this->disableEarlyStopping = $disableEarlyStopping;
}
/**
* @return bool
*/
public function getDisableEarlyStopping()
{
return $this->disableEarlyStopping;
}
/**
* @param self::MODEL_TYPE_* $modelType
*/
public function setModelType($modelType)
{
$this->modelType = $modelType;
}
/**
* @return self::MODEL_TYPE_*
*/
public function getModelType()
{
return $this->modelType;
}
/**
* Trainer type for Vision TrainRequest.
*
* @param GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter $tunableParameter
*/
public function setTunableParameter(GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter $tunableParameter)
{
$this->tunableParameter = $tunableParameter;
}
/**
* @return GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter
*/
public function getTunableParameter()
{
return $this->tunableParameter;
}
/**
* The ID of `base` model for upTraining. If it is specified, the new model
* will be upTrained based on the `base` model for upTraining. Otherwise, the
* new model will be trained from scratch. The `base` model for upTraining
* must be in the same Project and Location as the new Model to train, and
* have the same modelType.
*
* @param string $uptrainBaseModelId
*/
public function setUptrainBaseModelId($uptrainBaseModelId)
{
$this->uptrainBaseModelId = $uptrainBaseModelId;
}
/**
* @return string
*/
public function getUptrainBaseModelId()
{
return $this->uptrainBaseModelId;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs');