📄 Source: GoogleCloudAiplatformV1ExplanationMetadataInputMetadata.php
<?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 GoogleCloudAiplatformV1ExplanationMetadataInputMetadata extends \Google\Collection
{
/**
* Default value. This is the same as IDENTITY.
*/
public const ENCODING_ENCODING_UNSPECIFIED = 'ENCODING_UNSPECIFIED';
/**
* The tensor represents one feature.
*/
public const ENCODING_IDENTITY = 'IDENTITY';
/**
* The tensor represents a bag of features where each index maps to a feature.
* InputMetadata.index_feature_mapping must be provided for this encoding. For
* example: ``` input = [27, 6.0, 150] index_feature_mapping = ["age",
* "height", "weight"] ```
*/
public const ENCODING_BAG_OF_FEATURES = 'BAG_OF_FEATURES';
/**
* The tensor represents a bag of features where each index maps to a feature.
* Zero values in the tensor indicates feature being non-existent.
* InputMetadata.index_feature_mapping must be provided for this encoding. For
* example: ``` input = [2, 0, 5, 0, 1] index_feature_mapping = ["a", "b",
* "c", "d", "e"] ```
*/
public const ENCODING_BAG_OF_FEATURES_SPARSE = 'BAG_OF_FEATURES_SPARSE';
/**
* The tensor is a list of binaries representing whether a feature exists or
* not (1 indicates existence). InputMetadata.index_feature_mapping must be
* provided for this encoding. For example: ``` input = [1, 0, 1, 0, 1]
* index_feature_mapping = ["a", "b", "c", "d", "e"] ```
*/
public const ENCODING_INDICATOR = 'INDICATOR';
/**
* The tensor is encoded into a 1-dimensional array represented by an encoded
* tensor. InputMetadata.encoded_tensor_name must be provided for this
* encoding. For example: ``` input = ["This", "is", "a", "test", "."] encoded
* = [0.1, 0.2, 0.3, 0.4, 0.5] ```
*/
public const ENCODING_COMBINED_EMBEDDING = 'COMBINED_EMBEDDING';
/**
* Select this encoding when the input tensor is encoded into a 2-dimensional
* array represented by an encoded tensor. InputMetadata.encoded_tensor_name
* must be provided for this encoding. The first dimension of the encoded
* tensor's shape is the same as the input tensor's shape. For example: ```
* input = ["This", "is", "a", "test", "."] encoded = [[0.1, 0.2, 0.3, 0.4,
* 0.5], [0.2, 0.1, 0.4, 0.3, 0.5], [0.5, 0.1, 0.3, 0.5, 0.4], [0.5, 0.3, 0.1,
* 0.2, 0.4], [0.4, 0.3, 0.2, 0.5, 0.1]] ```
*/
public const ENCODING_CONCAT_EMBEDDING = 'CONCAT_EMBEDDING';
protected $collection_key = 'inputBaselines';
/**
* Specifies the shape of the values of the input if the input is a sparse
* representation. Refer to Tensorflow documentation for more details:
* https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
*
* @var string
*/
public $denseShapeTensorName;
/**
* A list of baselines for the encoded tensor. The shape of each baseline
* should match the shape of the encoded tensor. If a scalar is provided,
* Vertex AI broadcasts to the same shape as the encoded tensor.
*
* @var array[]
*/
public $encodedBaselines;
/**
* Encoded tensor is a transformation of the input tensor. Must be provided if
* choosing Integrated Gradients attribution or XRAI attribution and the input
* tensor is not differentiable. An encoded tensor is generated if the input
* tensor is encoded by a lookup table.
*
* @var string
*/
public $encodedTensorName;
/**
* Defines how the feature is encoded into the input tensor. Defaults to
* IDENTITY.
*
* @var string
*/
public $encoding;
protected $featureValueDomainType = GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain::class;
protected $featureValueDomainDataType = '';
/**
* Name of the group that the input belongs to. Features with the same group
* name will be treated as one feature when computing attributions. Features
* grouped together can have different shapes in value. If provided, there
* will be one single attribution generated in
* Attribution.feature_attributions, keyed by the group name.
*
* @var string
*/
public $groupName;
/**
* A list of feature names for each index in the input tensor. Required when
* the input InputMetadata.encoding is BAG_OF_FEATURES,
* BAG_OF_FEATURES_SPARSE, INDICATOR.
*
* @var string[]
*/
public $indexFeatureMapping;
/**
* Specifies the index of the values of the input tensor. Required when the
* input tensor is a sparse representation. Refer to Tensorflow documentation
* for more details:
* https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
*
* @var string
*/
public $indicesTensorName;
/**
* Baseline inputs for this feature. If no baseline is specified, Vertex AI
* chooses the baseline for this feature. If multiple baselines are specified,
* Vertex AI returns the average attributions across them in
* Attribution.feature_attributions. For Vertex AI-provided Tensorflow images
* (both 1.x and 2.x), the shape of each baseline must match the shape of the
* input tensor. If a scalar is provided, we broadcast to the same shape as
* the input tensor. For custom images, the element of the baselines must be
* in the same format as the feature's input in the instance[]. The schema of
* any single instance may be specified via Endpoint's DeployedModels' Model's
* PredictSchemata's instance_schema_uri.
*
* @var array[]
*/
public $inputBaselines;
/**
* Name of the input tensor for this feature. Required and is only applicable
* to Vertex AI-provided images for Tensorflow.
*
* @var string
*/
public $inputTensorName;
/**
* Modality of the feature. Valid values are: numeric, image. Defaults to
* numeric.
*
* @var string
*/
public $modality;
protected $visualizationType = GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization::class;
protected $visualizationDataType = '';
/**
* Specifies the shape of the values of the input if the input is a sparse
* representation. Refer to Tensorflow documentation for more details:
* https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
*
* @param string $denseShapeTensorName
*/
public function setDenseShapeTensorName($denseShapeTensorName)
{
$this->denseShapeTensorName = $denseShapeTensorName;
}
/**
* @return string
*/
public function getDenseShapeTensorName()
{
return $this->denseShapeTensorName;
}
/**
* A list of baselines for the encoded tensor. The shape of each baseline
* should match the shape of the encoded tensor. If a scalar is provided,
* Vertex AI broadcasts to the same shape as the encoded tensor.
*
* @param array[] $encodedBaselines
*/
public function setEncodedBaselines($encodedBaselines)
{
$this->encodedBaselines = $encodedBaselines;
}
/**
* @return array[]
*/
public function getEncodedBaselines()
{
return $this->encodedBaselines;
}
/**
* Encoded tensor is a transformation of the input tensor. Must be provided if
* choosing Integrated Gradients attribution or XRAI attribution and the input
* tensor is not differentiable. An encoded tensor is generated if the input
* tensor is encoded by a lookup table.
*
* @param string $encodedTensorName
*/
public function setEncodedTensorName($encodedTensorName)
{
$this->encodedTensorName = $encodedTensorName;
}
/**
* @return string
*/
public function getEncodedTensorName()
{
return $this->encodedTensorName;
}
/**
* Defines how the feature is encoded into the input tensor. Defaults to
* IDENTITY.
*
* Accepted values: ENCODING_UNSPECIFIED, IDENTITY, BAG_OF_FEATURES,
* BAG_OF_FEATURES_SPARSE, INDICATOR, COMBINED_EMBEDDING, CONCAT_EMBEDDING
*
* @param self::ENCODING_* $encoding
*/
public function setEncoding($encoding)
{
$this->encoding = $encoding;
}
/**
* @return self::ENCODING_*
*/
public function getEncoding()
{
return $this->encoding;
}
/**
* The domain details of the input feature value. Like min/max, original mean
* or standard deviation if normalized.
*
* @param GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain $featureValueDomain
*/
public function setFeatureValueDomain(GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain $featureValueDomain)
{
$this->featureValueDomain = $featureValueDomain;
}
/**
* @return GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain
*/
public function getFeatureValueDomain()
{
return $this->featureValueDomain;
}
/**
* Name of the group that the input belongs to. Features with the same group
* name will be treated as one feature when computing attributions. Features
* grouped together can have different shapes in value. If provided, there
* will be one single attribution generated in
* Attribution.feature_attributions, keyed by the group name.
*
* @param string $groupName
*/
public function setGroupName($groupName)
{
$this->groupName = $groupName;
}
/**
* @return string
*/
public function getGroupName()
{
return $this->groupName;
}
/**
* A list of feature names for each index in the input tensor. Required when
* the input InputMetadata.encoding is BAG_OF_FEATURES,
* BAG_OF_FEATURES_SPARSE, INDICATOR.
*
* @param string[] $indexFeatureMapping
*/
public function setIndexFeatureMapping($indexFeatureMapping)
{
$this->indexFeatureMapping = $indexFeatureMapping;
}
/**
* @return string[]
*/
public function getIndexFeatureMapping()
{
return $this->indexFeatureMapping;
}
/**
* Specifies the index of the values of the input tensor. Required when the
* input tensor is a sparse representation. Refer to Tensorflow documentation
* for more details:
* https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
*
* @param string $indicesTensorName
*/
public function setIndicesTensorName($indicesTensorName)
{
$this->indicesTensorName = $indicesTensorName;
}
/**
* @return string
*/
public function getIndicesTensorName()
{
return $this->indicesTensorName;
}
/**
* Baseline inputs for this feature. If no baseline is specified, Vertex AI
* chooses the baseline for this feature. If multiple baselines are specified,
* Vertex AI returns the average attributions across them in
* Attribution.feature_attributions. For Vertex AI-provided Tensorflow images
* (both 1.x and 2.x), the shape of each baseline must match the shape of the
* input tensor. If a scalar is provided, we broadcast to the same shape as
* the input tensor. For custom images, the element of the baselines must be
* in the same format as the feature's input in the instance[]. The schema of
* any single instance may be specified via Endpoint's DeployedModels' Model's
* PredictSchemata's instance_schema_uri.
*
* @param array[] $inputBaselines
*/
public function setInputBaselines($inputBaselines)
{
$this->inputBaselines = $inputBaselines;
}
/**
* @return array[]
*/
public function getInputBaselines()
{
return $this->inputBaselines;
}
/**
* Name of the input tensor for this feature. Required and is only applicable
* to Vertex AI-provided images for Tensorflow.
*
* @param string $inputTensorName
*/
public function setInputTensorName($inputTensorName)
{
$this->inputTensorName = $inputTensorName;
}
/**
* @return string
*/
public function getInputTensorName()
{
return $this->inputTensorName;
}
/**
* Modality of the feature. Valid values are: numeric, image. Defaults to
* numeric.
*
* @param string $modality
*/
public function setModality($modality)
{
$this->modality = $modality;
}
/**
* @return string
*/
public function getModality()
{
return $this->modality;
}
/**
* Visualization configurations for image explanation.
*
* @param GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization $visualization
*/
public function setVisualization(GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization $visualization)
{
$this->visualization = $visualization;
}
/**
* @return GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization
*/
public function getVisualization()
{
return $this->visualization;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1ExplanationMetadataInputMetadata::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1ExplanationMetadataInputMetadata');
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