# frozen_string_literal: true # Copyright 2022 Google LLC # # 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 # # https://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. # Auto-generated by gapic-generator-ruby. DO NOT EDIT! module Google module Cloud module AIPlatform module V1 # A collection of metrics calculated by comparing Model's predictions on a # slice of the test data against ground truth annotations. # @!attribute [r] name # @return [::String] # Output only. The resource name of the ModelEvaluationSlice. # @!attribute [r] slice # @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice] # Output only. The slice of the test data that is used to evaluate the Model. # @!attribute [r] metrics_schema_uri # @return [::String] # Output only. Points to a YAML file stored on Google Cloud Storage # describing the # {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice#metrics metrics} of this # ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 [Schema # Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). # @!attribute [r] metrics # @return [::Google::Protobuf::Value] # Output only. Sliced evaluation metrics of the Model. The schema of the # metrics is stored in # {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice#metrics_schema_uri metrics_schema_uri} # @!attribute [r] create_time # @return [::Google::Protobuf::Timestamp] # Output only. Timestamp when this ModelEvaluationSlice was created. # @!attribute [r] model_explanation # @return [::Google::Cloud::AIPlatform::V1::ModelExplanation] # Output only. Aggregated explanation metrics for the Model's prediction # output over the data this ModelEvaluation uses. This field is populated # only if the Model is evaluated with explanations, and only for tabular # Models. class ModelEvaluationSlice include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Definition of a slice. # @!attribute [r] dimension # @return [::String] # Output only. The dimension of the slice. # Well-known dimensions are: # * `annotationSpec`: This slice is on the test data that has either # ground truth or prediction with # {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name} # equals to # {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}. # * `slice`: This slice is a user customized slice defined by its # SliceSpec. # @!attribute [r] value # @return [::String] # Output only. The value of the dimension in this slice. # @!attribute [r] slice_spec # @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec] # Output only. Specification for how the data was sliced. class Slice include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Specification for how the data should be sliced. # @!attribute [rw] configs # @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}] # Mapping configuration for this SliceSpec. # The key is the name of the feature. # By default, the key will be prefixed by "instance" as a dictionary # prefix for Vertex Batch Predictions output format. class SliceSpec include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Specification message containing the config for this SliceSpec. # When `kind` is selected as `value` and/or `range`, only a single slice # will be computed. # When `all_values` is present, a separate slice will be computed for # each possible label/value for the corresponding key in `config`. # Examples, with feature zip_code with values 12345, 23334, 88888 and # feature country with values "US", "Canada", "Mexico" in the dataset: # # Example 1: # # { # "zip_code": { "value": { "float_value": 12345.0 } } # } # # A single slice for any data with zip_code 12345 in the dataset. # # Example 2: # # { # "zip_code": { "range": { "low": 12345, "high": 20000 } } # } # # A single slice containing data where the zip_codes between 12345 and # 20000 For this example, data with the zip_code of 12345 will be in this # slice. # # Example 3: # # { # "zip_code": { "range": { "low": 10000, "high": 20000 } }, # "country": { "value": { "string_value": "US" } } # } # # A single slice containing data where the zip_codes between 10000 and # 20000 has the country "US". For this example, data with the zip_code of # 12345 and country "US" will be in this slice. # # Example 4: # # { "country": {"all_values": { "value": true } } } # # Three slices are computed, one for each unique country in the dataset. # # Example 5: # # { # "country": { "all_values": { "value": true } }, # "zip_code": { "value": { "float_value": 12345.0 } } # } # # Three slices are computed, one for each unique country in the dataset # where the zip_code is also 12345. For this example, data with zip_code # 12345 and country "US" will be in one slice, zip_code 12345 and country # "Canada" in another slice, and zip_code 12345 and country "Mexico" in # another slice, totaling 3 slices. # @!attribute [rw] value # @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value] # A unique specific value for a given feature. # Example: `{ "value": { "string_value": "12345" } }` # @!attribute [rw] range # @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range] # A range of values for a numerical feature. # Example: `{"range":{"low":10000.0,"high":50000.0}}` # will capture 12345 and 23334 in the slice. # @!attribute [rw] all_values # @return [::Google::Protobuf::BoolValue] # If all_values is set to true, then all possible labels of the keyed # feature will have another slice computed. # Example: `{"all_values":{"value":true}}` class SliceConfig include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A range of values for slice(s). # `low` is inclusive, `high` is exclusive. # @!attribute [rw] low # @return [::Float] # Inclusive low value for the range. # @!attribute [rw] high # @return [::Float] # Exclusive high value for the range. class Range include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Single value that supports strings and floats. # @!attribute [rw] string_value # @return [::String] # String type. # @!attribute [rw] float_value # @return [::Float] # Float type. class Value include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # @!attribute [rw] key # @return [::String] # @!attribute [rw] value # @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig] class ConfigsEntry include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end end end end end end end