Class InputMetadata (1.1.1)

Version 1.1.1

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InputMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Metadata of the input of a feature.

Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.

Attributes

Name	Description
input_baselines	Sequence[google.protobuf.struct_pb2.Value] 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 [Attributions.baseline_attribution][]. 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][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] instance_schema_uri.
input_tensor_name	str Name of the input tensor for this feature. Required and is only applicable to Vertex AI- provided images for Tensorflow.
encoding	google.cloud.aiplatform_v1beta1.types.ExplanationMetadata.InputMetadata.Encoding Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
modality	str Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
feature_value_domain	google.cloud.aiplatform_v1beta1.types.ExplanationMetadata.InputMetadata.FeatureValueDomain The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
indices_tensor_name	str 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.
dense_shape_tensor_name	str 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.
index_feature_mapping	Sequence[str] 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.
encoded_tensor_name	str Encoded tensor is a transformation of the input tensor. Must be provided if choosing [Integrated Gradients attribution][ExplanationParameters.integrated_gradients_attribution] or [XRAI attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.xrai_attribution] and the input tensor is not differentiable. An encoded tensor is generated if the input tensor is encoded by a lookup table.