| // Copyright 2023 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 |
| // |
| // 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. |
| |
| // Code generated by protoc-gen-go. DO NOT EDIT. |
| // versions: |
| // protoc-gen-go v1.33.0 |
| // protoc v4.25.3 |
| // source: google/cloud/aiplatform/v1beta1/explanation_metadata.proto |
| |
| package aiplatformpb |
| |
| import ( |
| reflect "reflect" |
| sync "sync" |
| |
| _ "google.golang.org/genproto/googleapis/api/annotations" |
| protoreflect "google.golang.org/protobuf/reflect/protoreflect" |
| protoimpl "google.golang.org/protobuf/runtime/protoimpl" |
| structpb "google.golang.org/protobuf/types/known/structpb" |
| ) |
| |
| const ( |
| // Verify that this generated code is sufficiently up-to-date. |
| _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) |
| // Verify that runtime/protoimpl is sufficiently up-to-date. |
| _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) |
| ) |
| |
| // Defines how a feature is encoded. Defaults to IDENTITY. |
| type ExplanationMetadata_InputMetadata_Encoding int32 |
| |
| const ( |
| // Default value. This is the same as IDENTITY. |
| ExplanationMetadata_InputMetadata_ENCODING_UNSPECIFIED ExplanationMetadata_InputMetadata_Encoding = 0 |
| // The tensor represents one feature. |
| ExplanationMetadata_InputMetadata_IDENTITY ExplanationMetadata_InputMetadata_Encoding = 1 |
| // The tensor represents a bag of features where each index maps to |
| // a feature. |
| // [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping] |
| // must be provided for this encoding. For example: |
| // ``` |
| // input = [27, 6.0, 150] |
| // index_feature_mapping = ["age", "height", "weight"] |
| // ``` |
| ExplanationMetadata_InputMetadata_BAG_OF_FEATURES ExplanationMetadata_InputMetadata_Encoding = 2 |
| // 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][google.cloud.aiplatform.v1beta1.ExplanationMetadata.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"] |
| // ``` |
| ExplanationMetadata_InputMetadata_BAG_OF_FEATURES_SPARSE ExplanationMetadata_InputMetadata_Encoding = 3 |
| // The tensor is a list of binaries representing whether a feature exists |
| // or not (1 indicates existence). |
| // [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.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"] |
| // ``` |
| ExplanationMetadata_InputMetadata_INDICATOR ExplanationMetadata_InputMetadata_Encoding = 4 |
| // The tensor is encoded into a 1-dimensional array represented by an |
| // encoded tensor. |
| // [InputMetadata.encoded_tensor_name][google.cloud.aiplatform.v1beta1.ExplanationMetadata.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] |
| // ``` |
| ExplanationMetadata_InputMetadata_COMBINED_EMBEDDING ExplanationMetadata_InputMetadata_Encoding = 5 |
| // Select this encoding when the input tensor is encoded into a |
| // 2-dimensional array represented by an encoded tensor. |
| // [InputMetadata.encoded_tensor_name][google.cloud.aiplatform.v1beta1.ExplanationMetadata.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]] |
| // |
| // ``` |
| ExplanationMetadata_InputMetadata_CONCAT_EMBEDDING ExplanationMetadata_InputMetadata_Encoding = 6 |
| ) |
| |
| // Enum value maps for ExplanationMetadata_InputMetadata_Encoding. |
| var ( |
| ExplanationMetadata_InputMetadata_Encoding_name = map[int32]string{ |
| 0: "ENCODING_UNSPECIFIED", |
| 1: "IDENTITY", |
| 2: "BAG_OF_FEATURES", |
| 3: "BAG_OF_FEATURES_SPARSE", |
| 4: "INDICATOR", |
| 5: "COMBINED_EMBEDDING", |
| 6: "CONCAT_EMBEDDING", |
| } |
| ExplanationMetadata_InputMetadata_Encoding_value = map[string]int32{ |
| "ENCODING_UNSPECIFIED": 0, |
| "IDENTITY": 1, |
| "BAG_OF_FEATURES": 2, |
| "BAG_OF_FEATURES_SPARSE": 3, |
| "INDICATOR": 4, |
| "COMBINED_EMBEDDING": 5, |
| "CONCAT_EMBEDDING": 6, |
| } |
| ) |
| |
| func (x ExplanationMetadata_InputMetadata_Encoding) Enum() *ExplanationMetadata_InputMetadata_Encoding { |
| p := new(ExplanationMetadata_InputMetadata_Encoding) |
| *p = x |
| return p |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Encoding) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Encoding) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[0].Descriptor() |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Encoding) Type() protoreflect.EnumType { |
| return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[0] |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Encoding) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_Encoding.Descriptor instead. |
| func (ExplanationMetadata_InputMetadata_Encoding) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 0} |
| } |
| |
| // Type of the image visualization. Only applicable to |
| // [Integrated Gradients |
| // attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.integrated_gradients_attribution]. |
| type ExplanationMetadata_InputMetadata_Visualization_Type int32 |
| |
| const ( |
| // Should not be used. |
| ExplanationMetadata_InputMetadata_Visualization_TYPE_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_Type = 0 |
| // Shows which pixel contributed to the image prediction. |
| ExplanationMetadata_InputMetadata_Visualization_PIXELS ExplanationMetadata_InputMetadata_Visualization_Type = 1 |
| // Shows which region contributed to the image prediction by outlining |
| // the region. |
| ExplanationMetadata_InputMetadata_Visualization_OUTLINES ExplanationMetadata_InputMetadata_Visualization_Type = 2 |
| ) |
| |
| // Enum value maps for ExplanationMetadata_InputMetadata_Visualization_Type. |
| var ( |
| ExplanationMetadata_InputMetadata_Visualization_Type_name = map[int32]string{ |
| 0: "TYPE_UNSPECIFIED", |
| 1: "PIXELS", |
| 2: "OUTLINES", |
| } |
| ExplanationMetadata_InputMetadata_Visualization_Type_value = map[string]int32{ |
| "TYPE_UNSPECIFIED": 0, |
| "PIXELS": 1, |
| "OUTLINES": 2, |
| } |
| ) |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_Type) Enum() *ExplanationMetadata_InputMetadata_Visualization_Type { |
| p := new(ExplanationMetadata_InputMetadata_Visualization_Type) |
| *p = x |
| return p |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_Type) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_Type) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[1].Descriptor() |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_Type) Type() protoreflect.EnumType { |
| return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[1] |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_Type) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_Type.Descriptor instead. |
| func (ExplanationMetadata_InputMetadata_Visualization_Type) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 0} |
| } |
| |
| // Whether to only highlight pixels with positive contributions, negative |
| // or both. Defaults to POSITIVE. |
| type ExplanationMetadata_InputMetadata_Visualization_Polarity int32 |
| |
| const ( |
| // Default value. This is the same as POSITIVE. |
| ExplanationMetadata_InputMetadata_Visualization_POLARITY_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_Polarity = 0 |
| // Highlights the pixels/outlines that were most influential to the |
| // model's prediction. |
| ExplanationMetadata_InputMetadata_Visualization_POSITIVE ExplanationMetadata_InputMetadata_Visualization_Polarity = 1 |
| // Setting polarity to negative highlights areas that does not lead to |
| // the models's current prediction. |
| ExplanationMetadata_InputMetadata_Visualization_NEGATIVE ExplanationMetadata_InputMetadata_Visualization_Polarity = 2 |
| // Shows both positive and negative attributions. |
| ExplanationMetadata_InputMetadata_Visualization_BOTH ExplanationMetadata_InputMetadata_Visualization_Polarity = 3 |
| ) |
| |
| // Enum value maps for ExplanationMetadata_InputMetadata_Visualization_Polarity. |
| var ( |
| ExplanationMetadata_InputMetadata_Visualization_Polarity_name = map[int32]string{ |
| 0: "POLARITY_UNSPECIFIED", |
| 1: "POSITIVE", |
| 2: "NEGATIVE", |
| 3: "BOTH", |
| } |
| ExplanationMetadata_InputMetadata_Visualization_Polarity_value = map[string]int32{ |
| "POLARITY_UNSPECIFIED": 0, |
| "POSITIVE": 1, |
| "NEGATIVE": 2, |
| "BOTH": 3, |
| } |
| ) |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_Polarity) Enum() *ExplanationMetadata_InputMetadata_Visualization_Polarity { |
| p := new(ExplanationMetadata_InputMetadata_Visualization_Polarity) |
| *p = x |
| return p |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_Polarity) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_Polarity) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[2].Descriptor() |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_Polarity) Type() protoreflect.EnumType { |
| return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[2] |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_Polarity) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_Polarity.Descriptor instead. |
| func (ExplanationMetadata_InputMetadata_Visualization_Polarity) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 1} |
| } |
| |
| // The color scheme used for highlighting areas. |
| type ExplanationMetadata_InputMetadata_Visualization_ColorMap int32 |
| |
| const ( |
| // Should not be used. |
| ExplanationMetadata_InputMetadata_Visualization_COLOR_MAP_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_ColorMap = 0 |
| // Positive: green. Negative: pink. |
| ExplanationMetadata_InputMetadata_Visualization_PINK_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 1 |
| // Viridis color map: A perceptually uniform color mapping which is |
| // easier to see by those with colorblindness and progresses from yellow |
| // to green to blue. Positive: yellow. Negative: blue. |
| ExplanationMetadata_InputMetadata_Visualization_VIRIDIS ExplanationMetadata_InputMetadata_Visualization_ColorMap = 2 |
| // Positive: red. Negative: red. |
| ExplanationMetadata_InputMetadata_Visualization_RED ExplanationMetadata_InputMetadata_Visualization_ColorMap = 3 |
| // Positive: green. Negative: green. |
| ExplanationMetadata_InputMetadata_Visualization_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 4 |
| // Positive: green. Negative: red. |
| ExplanationMetadata_InputMetadata_Visualization_RED_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 6 |
| // PiYG palette. |
| ExplanationMetadata_InputMetadata_Visualization_PINK_WHITE_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 5 |
| ) |
| |
| // Enum value maps for ExplanationMetadata_InputMetadata_Visualization_ColorMap. |
| var ( |
| ExplanationMetadata_InputMetadata_Visualization_ColorMap_name = map[int32]string{ |
| 0: "COLOR_MAP_UNSPECIFIED", |
| 1: "PINK_GREEN", |
| 2: "VIRIDIS", |
| 3: "RED", |
| 4: "GREEN", |
| 6: "RED_GREEN", |
| 5: "PINK_WHITE_GREEN", |
| } |
| ExplanationMetadata_InputMetadata_Visualization_ColorMap_value = map[string]int32{ |
| "COLOR_MAP_UNSPECIFIED": 0, |
| "PINK_GREEN": 1, |
| "VIRIDIS": 2, |
| "RED": 3, |
| "GREEN": 4, |
| "RED_GREEN": 6, |
| "PINK_WHITE_GREEN": 5, |
| } |
| ) |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_ColorMap) Enum() *ExplanationMetadata_InputMetadata_Visualization_ColorMap { |
| p := new(ExplanationMetadata_InputMetadata_Visualization_ColorMap) |
| *p = x |
| return p |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_ColorMap) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_ColorMap) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[3].Descriptor() |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_ColorMap) Type() protoreflect.EnumType { |
| return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[3] |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_ColorMap) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_ColorMap.Descriptor instead. |
| func (ExplanationMetadata_InputMetadata_Visualization_ColorMap) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 2} |
| } |
| |
| // How the original image is displayed in the visualization. |
| type ExplanationMetadata_InputMetadata_Visualization_OverlayType int32 |
| |
| const ( |
| // Default value. This is the same as NONE. |
| ExplanationMetadata_InputMetadata_Visualization_OVERLAY_TYPE_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_OverlayType = 0 |
| // No overlay. |
| ExplanationMetadata_InputMetadata_Visualization_NONE ExplanationMetadata_InputMetadata_Visualization_OverlayType = 1 |
| // The attributions are shown on top of the original image. |
| ExplanationMetadata_InputMetadata_Visualization_ORIGINAL ExplanationMetadata_InputMetadata_Visualization_OverlayType = 2 |
| // The attributions are shown on top of grayscaled version of the |
| // original image. |
| ExplanationMetadata_InputMetadata_Visualization_GRAYSCALE ExplanationMetadata_InputMetadata_Visualization_OverlayType = 3 |
| // The attributions are used as a mask to reveal predictive parts of |
| // the image and hide the un-predictive parts. |
| ExplanationMetadata_InputMetadata_Visualization_MASK_BLACK ExplanationMetadata_InputMetadata_Visualization_OverlayType = 4 |
| ) |
| |
| // Enum value maps for ExplanationMetadata_InputMetadata_Visualization_OverlayType. |
| var ( |
| ExplanationMetadata_InputMetadata_Visualization_OverlayType_name = map[int32]string{ |
| 0: "OVERLAY_TYPE_UNSPECIFIED", |
| 1: "NONE", |
| 2: "ORIGINAL", |
| 3: "GRAYSCALE", |
| 4: "MASK_BLACK", |
| } |
| ExplanationMetadata_InputMetadata_Visualization_OverlayType_value = map[string]int32{ |
| "OVERLAY_TYPE_UNSPECIFIED": 0, |
| "NONE": 1, |
| "ORIGINAL": 2, |
| "GRAYSCALE": 3, |
| "MASK_BLACK": 4, |
| } |
| ) |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_OverlayType) Enum() *ExplanationMetadata_InputMetadata_Visualization_OverlayType { |
| p := new(ExplanationMetadata_InputMetadata_Visualization_OverlayType) |
| *p = x |
| return p |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_OverlayType) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_OverlayType) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[4].Descriptor() |
| } |
| |
| func (ExplanationMetadata_InputMetadata_Visualization_OverlayType) Type() protoreflect.EnumType { |
| return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[4] |
| } |
| |
| func (x ExplanationMetadata_InputMetadata_Visualization_OverlayType) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_OverlayType.Descriptor instead. |
| func (ExplanationMetadata_InputMetadata_Visualization_OverlayType) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 3} |
| } |
| |
| // Metadata describing the Model's input and output for explanation. |
| type ExplanationMetadata struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Required. Map from feature names to feature input metadata. Keys are the |
| // name of the features. Values are the specification of the feature. |
| // |
| // An empty InputMetadata is valid. It describes a text feature which has the |
| // name specified as the key in |
| // [ExplanationMetadata.inputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs]. |
| // The baseline of the empty feature is chosen by Vertex AI. |
| // |
| // For Vertex AI-provided Tensorflow images, the key can be any friendly |
| // name of the feature. Once specified, |
| // [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] |
| // are keyed by this key (if not grouped with another feature). |
| // |
| // For custom images, the key must match with the key in |
| // [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances]. |
| Inputs map[string]*ExplanationMetadata_InputMetadata `protobuf:"bytes,1,rep,name=inputs,proto3" json:"inputs,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"` |
| // Required. Map from output names to output metadata. |
| // |
| // For Vertex AI-provided Tensorflow images, keys can be any user defined |
| // string that consists of any UTF-8 characters. |
| // |
| // For custom images, keys are the name of the output field in the prediction |
| // to be explained. |
| // |
| // Currently only one key is allowed. |
| Outputs map[string]*ExplanationMetadata_OutputMetadata `protobuf:"bytes,2,rep,name=outputs,proto3" json:"outputs,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"` |
| // Points to a YAML file stored on Google Cloud Storage describing the format |
| // of the [feature |
| // attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions]. |
| // 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). |
| // AutoML tabular Models always have this field populated by Vertex AI. |
| // Note: The URI given on output may be different, including the URI scheme, |
| // than the one given on input. The output URI will point to a location where |
| // the user only has a read access. |
| FeatureAttributionsSchemaUri string `protobuf:"bytes,3,opt,name=feature_attributions_schema_uri,json=featureAttributionsSchemaUri,proto3" json:"feature_attributions_schema_uri,omitempty"` |
| // Name of the source to generate embeddings for example based explanations. |
| LatentSpaceSource string `protobuf:"bytes,5,opt,name=latent_space_source,json=latentSpaceSource,proto3" json:"latent_space_source,omitempty"` |
| } |
| |
| func (x *ExplanationMetadata) Reset() { |
| *x = ExplanationMetadata{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[0] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *ExplanationMetadata) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*ExplanationMetadata) ProtoMessage() {} |
| |
| func (x *ExplanationMetadata) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[0] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata.ProtoReflect.Descriptor instead. |
| func (*ExplanationMetadata) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0} |
| } |
| |
| func (x *ExplanationMetadata) GetInputs() map[string]*ExplanationMetadata_InputMetadata { |
| if x != nil { |
| return x.Inputs |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata) GetOutputs() map[string]*ExplanationMetadata_OutputMetadata { |
| if x != nil { |
| return x.Outputs |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata) GetFeatureAttributionsSchemaUri() string { |
| if x != nil { |
| return x.FeatureAttributionsSchemaUri |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata) GetLatentSpaceSource() string { |
| if x != nil { |
| return x.LatentSpaceSource |
| } |
| return "" |
| } |
| |
| // Metadata of the input of a feature. |
| // |
| // Fields other than |
| // [InputMetadata.input_baselines][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.input_baselines] |
| // are applicable only for Models that are using Vertex AI-provided images for |
| // Tensorflow. |
| type ExplanationMetadata_InputMetadata struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // 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][google.cloud.aiplatform.v1beta1.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][google.cloud.aiplatform.v1beta1.ExplainRequest.instances][]. |
| // 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][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]. |
| InputBaselines []*structpb.Value `protobuf:"bytes,1,rep,name=input_baselines,json=inputBaselines,proto3" json:"input_baselines,omitempty"` |
| // Name of the input tensor for this feature. Required and is only |
| // applicable to Vertex AI-provided images for Tensorflow. |
| InputTensorName string `protobuf:"bytes,2,opt,name=input_tensor_name,json=inputTensorName,proto3" json:"input_tensor_name,omitempty"` |
| // Defines how the feature is encoded into the input tensor. Defaults to |
| // IDENTITY. |
| Encoding ExplanationMetadata_InputMetadata_Encoding `protobuf:"varint,3,opt,name=encoding,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Encoding" json:"encoding,omitempty"` |
| // Modality of the feature. Valid values are: numeric, image. Defaults to |
| // numeric. |
| Modality string `protobuf:"bytes,4,opt,name=modality,proto3" json:"modality,omitempty"` |
| // The domain details of the input feature value. Like min/max, original |
| // mean or standard deviation if normalized. |
| FeatureValueDomain *ExplanationMetadata_InputMetadata_FeatureValueDomain `protobuf:"bytes,5,opt,name=feature_value_domain,json=featureValueDomain,proto3" json:"feature_value_domain,omitempty"` |
| // 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. |
| IndicesTensorName string `protobuf:"bytes,6,opt,name=indices_tensor_name,json=indicesTensorName,proto3" json:"indices_tensor_name,omitempty"` |
| // 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. |
| DenseShapeTensorName string `protobuf:"bytes,7,opt,name=dense_shape_tensor_name,json=denseShapeTensorName,proto3" json:"dense_shape_tensor_name,omitempty"` |
| // A list of feature names for each index in the input tensor. |
| // Required when the input |
| // [InputMetadata.encoding][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoding] |
| // is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR. |
| IndexFeatureMapping []string `protobuf:"bytes,8,rep,name=index_feature_mapping,json=indexFeatureMapping,proto3" json:"index_feature_mapping,omitempty"` |
| // Encoded tensor is a transformation of the input tensor. Must be provided |
| // if choosing |
| // [Integrated Gradients |
| // attribution][google.cloud.aiplatform.v1beta1.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. |
| EncodedTensorName string `protobuf:"bytes,9,opt,name=encoded_tensor_name,json=encodedTensorName,proto3" json:"encoded_tensor_name,omitempty"` |
| // 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. |
| EncodedBaselines []*structpb.Value `protobuf:"bytes,10,rep,name=encoded_baselines,json=encodedBaselines,proto3" json:"encoded_baselines,omitempty"` |
| // Visualization configurations for image explanation. |
| Visualization *ExplanationMetadata_InputMetadata_Visualization `protobuf:"bytes,11,opt,name=visualization,proto3" json:"visualization,omitempty"` |
| // 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][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions], |
| // keyed by the group name. |
| GroupName string `protobuf:"bytes,12,opt,name=group_name,json=groupName,proto3" json:"group_name,omitempty"` |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) Reset() { |
| *x = ExplanationMetadata_InputMetadata{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[1] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*ExplanationMetadata_InputMetadata) ProtoMessage() {} |
| |
| func (x *ExplanationMetadata_InputMetadata) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[1] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata.ProtoReflect.Descriptor instead. |
| func (*ExplanationMetadata_InputMetadata) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0} |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetInputBaselines() []*structpb.Value { |
| if x != nil { |
| return x.InputBaselines |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetInputTensorName() string { |
| if x != nil { |
| return x.InputTensorName |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetEncoding() ExplanationMetadata_InputMetadata_Encoding { |
| if x != nil { |
| return x.Encoding |
| } |
| return ExplanationMetadata_InputMetadata_ENCODING_UNSPECIFIED |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetModality() string { |
| if x != nil { |
| return x.Modality |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetFeatureValueDomain() *ExplanationMetadata_InputMetadata_FeatureValueDomain { |
| if x != nil { |
| return x.FeatureValueDomain |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetIndicesTensorName() string { |
| if x != nil { |
| return x.IndicesTensorName |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetDenseShapeTensorName() string { |
| if x != nil { |
| return x.DenseShapeTensorName |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetIndexFeatureMapping() []string { |
| if x != nil { |
| return x.IndexFeatureMapping |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetEncodedTensorName() string { |
| if x != nil { |
| return x.EncodedTensorName |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetEncodedBaselines() []*structpb.Value { |
| if x != nil { |
| return x.EncodedBaselines |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetVisualization() *ExplanationMetadata_InputMetadata_Visualization { |
| if x != nil { |
| return x.Visualization |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata) GetGroupName() string { |
| if x != nil { |
| return x.GroupName |
| } |
| return "" |
| } |
| |
| // Metadata of the prediction output to be explained. |
| type ExplanationMetadata_OutputMetadata struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Defines how to map |
| // [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] |
| // to |
| // [Attribution.output_display_name][google.cloud.aiplatform.v1beta1.Attribution.output_display_name]. |
| // |
| // If neither of the fields are specified, |
| // [Attribution.output_display_name][google.cloud.aiplatform.v1beta1.Attribution.output_display_name] |
| // will not be populated. |
| // |
| // Types that are assignable to DisplayNameMapping: |
| // |
| // *ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping |
| // *ExplanationMetadata_OutputMetadata_DisplayNameMappingKey |
| DisplayNameMapping isExplanationMetadata_OutputMetadata_DisplayNameMapping `protobuf_oneof:"display_name_mapping"` |
| // Name of the output tensor. Required and is only applicable to Vertex |
| // AI provided images for Tensorflow. |
| OutputTensorName string `protobuf:"bytes,3,opt,name=output_tensor_name,json=outputTensorName,proto3" json:"output_tensor_name,omitempty"` |
| } |
| |
| func (x *ExplanationMetadata_OutputMetadata) Reset() { |
| *x = ExplanationMetadata_OutputMetadata{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *ExplanationMetadata_OutputMetadata) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*ExplanationMetadata_OutputMetadata) ProtoMessage() {} |
| |
| func (x *ExplanationMetadata_OutputMetadata) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_OutputMetadata.ProtoReflect.Descriptor instead. |
| func (*ExplanationMetadata_OutputMetadata) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 1} |
| } |
| |
| func (m *ExplanationMetadata_OutputMetadata) GetDisplayNameMapping() isExplanationMetadata_OutputMetadata_DisplayNameMapping { |
| if m != nil { |
| return m.DisplayNameMapping |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_OutputMetadata) GetIndexDisplayNameMapping() *structpb.Value { |
| if x, ok := x.GetDisplayNameMapping().(*ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping); ok { |
| return x.IndexDisplayNameMapping |
| } |
| return nil |
| } |
| |
| func (x *ExplanationMetadata_OutputMetadata) GetDisplayNameMappingKey() string { |
| if x, ok := x.GetDisplayNameMapping().(*ExplanationMetadata_OutputMetadata_DisplayNameMappingKey); ok { |
| return x.DisplayNameMappingKey |
| } |
| return "" |
| } |
| |
| func (x *ExplanationMetadata_OutputMetadata) GetOutputTensorName() string { |
| if x != nil { |
| return x.OutputTensorName |
| } |
| return "" |
| } |
| |
| type isExplanationMetadata_OutputMetadata_DisplayNameMapping interface { |
| isExplanationMetadata_OutputMetadata_DisplayNameMapping() |
| } |
| |
| type ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping struct { |
| // Static mapping between the index and display name. |
| // |
| // Use this if the outputs are a deterministic n-dimensional array, e.g. a |
| // list of scores of all the classes in a pre-defined order for a |
| // multi-classification Model. It's not feasible if the outputs are |
| // non-deterministic, e.g. the Model produces top-k classes or sort the |
| // outputs by their values. |
| // |
| // The shape of the value must be an n-dimensional array of strings. The |
| // number of dimensions must match that of the outputs to be explained. |
| // The |
| // [Attribution.output_display_name][google.cloud.aiplatform.v1beta1.Attribution.output_display_name] |
| // is populated by locating in the mapping with |
| // [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index]. |
| IndexDisplayNameMapping *structpb.Value `protobuf:"bytes,1,opt,name=index_display_name_mapping,json=indexDisplayNameMapping,proto3,oneof"` |
| } |
| |
| type ExplanationMetadata_OutputMetadata_DisplayNameMappingKey struct { |
| // Specify a field name in the prediction to look for the display name. |
| // |
| // Use this if the prediction contains the display names for the outputs. |
| // |
| // The display names in the prediction must have the same shape of the |
| // outputs, so that it can be located by |
| // [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] |
| // for a specific output. |
| DisplayNameMappingKey string `protobuf:"bytes,2,opt,name=display_name_mapping_key,json=displayNameMappingKey,proto3,oneof"` |
| } |
| |
| func (*ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping) isExplanationMetadata_OutputMetadata_DisplayNameMapping() { |
| } |
| |
| func (*ExplanationMetadata_OutputMetadata_DisplayNameMappingKey) isExplanationMetadata_OutputMetadata_DisplayNameMapping() { |
| } |
| |
| // Domain details of the input feature value. Provides numeric information |
| // about the feature, such as its range (min, max). If the feature has been |
| // pre-processed, for example with z-scoring, then it provides information |
| // about how to recover the original feature. For example, if the input |
| // feature is an image and it has been pre-processed to obtain 0-mean and |
| // stddev = 1 values, then original_mean, and original_stddev refer to the |
| // mean and stddev of the original feature (e.g. image tensor) from which |
| // input feature (with mean = 0 and stddev = 1) was obtained. |
| type ExplanationMetadata_InputMetadata_FeatureValueDomain struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // The minimum permissible value for this feature. |
| MinValue float32 `protobuf:"fixed32,1,opt,name=min_value,json=minValue,proto3" json:"min_value,omitempty"` |
| // The maximum permissible value for this feature. |
| MaxValue float32 `protobuf:"fixed32,2,opt,name=max_value,json=maxValue,proto3" json:"max_value,omitempty"` |
| // If this input feature has been normalized to a mean value of 0, |
| // the original_mean specifies the mean value of the domain prior to |
| // normalization. |
| OriginalMean float32 `protobuf:"fixed32,3,opt,name=original_mean,json=originalMean,proto3" json:"original_mean,omitempty"` |
| // If this input feature has been normalized to a standard deviation of |
| // 1.0, the original_stddev specifies the standard deviation of the domain |
| // prior to normalization. |
| OriginalStddev float32 `protobuf:"fixed32,4,opt,name=original_stddev,json=originalStddev,proto3" json:"original_stddev,omitempty"` |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) Reset() { |
| *x = ExplanationMetadata_InputMetadata_FeatureValueDomain{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[5] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*ExplanationMetadata_InputMetadata_FeatureValueDomain) ProtoMessage() {} |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[5] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_FeatureValueDomain.ProtoReflect.Descriptor instead. |
| func (*ExplanationMetadata_InputMetadata_FeatureValueDomain) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 0} |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetMinValue() float32 { |
| if x != nil { |
| return x.MinValue |
| } |
| return 0 |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetMaxValue() float32 { |
| if x != nil { |
| return x.MaxValue |
| } |
| return 0 |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetOriginalMean() float32 { |
| if x != nil { |
| return x.OriginalMean |
| } |
| return 0 |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetOriginalStddev() float32 { |
| if x != nil { |
| return x.OriginalStddev |
| } |
| return 0 |
| } |
| |
| // Visualization configurations for image explanation. |
| type ExplanationMetadata_InputMetadata_Visualization struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Type of the image visualization. Only applicable to |
| // [Integrated Gradients |
| // attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.integrated_gradients_attribution]. |
| // OUTLINES shows regions of attribution, while PIXELS shows per-pixel |
| // attribution. Defaults to OUTLINES. |
| Type ExplanationMetadata_InputMetadata_Visualization_Type `protobuf:"varint,1,opt,name=type,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Visualization_Type" json:"type,omitempty"` |
| // Whether to only highlight pixels with positive contributions, negative |
| // or both. Defaults to POSITIVE. |
| Polarity ExplanationMetadata_InputMetadata_Visualization_Polarity `protobuf:"varint,2,opt,name=polarity,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Visualization_Polarity" json:"polarity,omitempty"` |
| // The color scheme used for the highlighted areas. |
| // |
| // Defaults to PINK_GREEN for |
| // [Integrated Gradients |
| // attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.integrated_gradients_attribution], |
| // which shows positive attributions in green and negative in pink. |
| // |
| // Defaults to VIRIDIS for |
| // [XRAI |
| // attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.xrai_attribution], |
| // which highlights the most influential regions in yellow and the least |
| // influential in blue. |
| ColorMap ExplanationMetadata_InputMetadata_Visualization_ColorMap `protobuf:"varint,3,opt,name=color_map,json=colorMap,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Visualization_ColorMap" json:"color_map,omitempty"` |
| // Excludes attributions above the specified percentile from the |
| // highlighted areas. Using the clip_percent_upperbound and |
| // clip_percent_lowerbound together can be useful for filtering out noise |
| // and making it easier to see areas of strong attribution. Defaults to |
| // 99.9. |
| ClipPercentUpperbound float32 `protobuf:"fixed32,4,opt,name=clip_percent_upperbound,json=clipPercentUpperbound,proto3" json:"clip_percent_upperbound,omitempty"` |
| // Excludes attributions below the specified percentile, from the |
| // highlighted areas. Defaults to 62. |
| ClipPercentLowerbound float32 `protobuf:"fixed32,5,opt,name=clip_percent_lowerbound,json=clipPercentLowerbound,proto3" json:"clip_percent_lowerbound,omitempty"` |
| // How the original image is displayed in the visualization. |
| // Adjusting the overlay can help increase visual clarity if the original |
| // image makes it difficult to view the visualization. Defaults to NONE. |
| OverlayType ExplanationMetadata_InputMetadata_Visualization_OverlayType `protobuf:"varint,6,opt,name=overlay_type,json=overlayType,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Visualization_OverlayType" json:"overlay_type,omitempty"` |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) Reset() { |
| *x = ExplanationMetadata_InputMetadata_Visualization{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[6] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*ExplanationMetadata_InputMetadata_Visualization) ProtoMessage() {} |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[6] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use ExplanationMetadata_InputMetadata_Visualization.ProtoReflect.Descriptor instead. |
| func (*ExplanationMetadata_InputMetadata_Visualization) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1} |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) GetType() ExplanationMetadata_InputMetadata_Visualization_Type { |
| if x != nil { |
| return x.Type |
| } |
| return ExplanationMetadata_InputMetadata_Visualization_TYPE_UNSPECIFIED |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) GetPolarity() ExplanationMetadata_InputMetadata_Visualization_Polarity { |
| if x != nil { |
| return x.Polarity |
| } |
| return ExplanationMetadata_InputMetadata_Visualization_POLARITY_UNSPECIFIED |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) GetColorMap() ExplanationMetadata_InputMetadata_Visualization_ColorMap { |
| if x != nil { |
| return x.ColorMap |
| } |
| return ExplanationMetadata_InputMetadata_Visualization_COLOR_MAP_UNSPECIFIED |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) GetClipPercentUpperbound() float32 { |
| if x != nil { |
| return x.ClipPercentUpperbound |
| } |
| return 0 |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) GetClipPercentLowerbound() float32 { |
| if x != nil { |
| return x.ClipPercentLowerbound |
| } |
| return 0 |
| } |
| |
| func (x *ExplanationMetadata_InputMetadata_Visualization) GetOverlayType() ExplanationMetadata_InputMetadata_Visualization_OverlayType { |
| if x != nil { |
| return x.OverlayType |
| } |
| return ExplanationMetadata_InputMetadata_Visualization_OVERLAY_TYPE_UNSPECIFIED |
| } |
| |
| var File_google_cloud_aiplatform_v1beta1_explanation_metadata_proto protoreflect.FileDescriptor |
| |
| var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDesc = []byte{ |
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| } |
| |
| var ( |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescOnce sync.Once |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData = file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDesc |
| ) |
| |
| func file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP() []byte { |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescOnce.Do(func() { |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData) |
| }) |
| return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData |
| } |
| |
| var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes = make([]protoimpl.EnumInfo, 5) |
| var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes = make([]protoimpl.MessageInfo, 7) |
| var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_goTypes = []interface{}{ |
| (ExplanationMetadata_InputMetadata_Encoding)(0), // 0: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Encoding |
| (ExplanationMetadata_InputMetadata_Visualization_Type)(0), // 1: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type |
| (ExplanationMetadata_InputMetadata_Visualization_Polarity)(0), // 2: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity |
| (ExplanationMetadata_InputMetadata_Visualization_ColorMap)(0), // 3: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap |
| (ExplanationMetadata_InputMetadata_Visualization_OverlayType)(0), // 4: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType |
| (*ExplanationMetadata)(nil), // 5: google.cloud.aiplatform.v1beta1.ExplanationMetadata |
| (*ExplanationMetadata_InputMetadata)(nil), // 6: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata |
| (*ExplanationMetadata_OutputMetadata)(nil), // 7: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata |
| nil, // 8: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputsEntry |
| nil, // 9: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputsEntry |
| (*ExplanationMetadata_InputMetadata_FeatureValueDomain)(nil), // 10: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.FeatureValueDomain |
| (*ExplanationMetadata_InputMetadata_Visualization)(nil), // 11: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization |
| (*structpb.Value)(nil), // 12: google.protobuf.Value |
| } |
| var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_depIdxs = []int32{ |
| 8, // 0: google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputsEntry |
| 9, // 1: google.cloud.aiplatform.v1beta1.ExplanationMetadata.outputs:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputsEntry |
| 12, // 2: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.input_baselines:type_name -> google.protobuf.Value |
| 0, // 3: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoding:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Encoding |
| 10, // 4: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.feature_value_domain:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.FeatureValueDomain |
| 12, // 5: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_baselines:type_name -> google.protobuf.Value |
| 11, // 6: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.visualization:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization |
| 12, // 7: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata.index_display_name_mapping:type_name -> google.protobuf.Value |
| 6, // 8: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputsEntry.value:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata |
| 7, // 9: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputsEntry.value:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata |
| 1, // 10: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.type:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type |
| 2, // 11: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.polarity:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity |
| 3, // 12: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.color_map:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap |
| 4, // 13: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.overlay_type:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType |
| 14, // [14:14] is the sub-list for method output_type |
| 14, // [14:14] is the sub-list for method input_type |
| 14, // [14:14] is the sub-list for extension type_name |
| 14, // [14:14] is the sub-list for extension extendee |
| 0, // [0:14] is the sub-list for field type_name |
| } |
| |
| func init() { file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_init() } |
| func file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_init() { |
| if File_google_cloud_aiplatform_v1beta1_explanation_metadata_proto != nil { |
| return |
| } |
| if !protoimpl.UnsafeEnabled { |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*ExplanationMetadata); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*ExplanationMetadata_InputMetadata); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*ExplanationMetadata_OutputMetadata); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*ExplanationMetadata_InputMetadata_FeatureValueDomain); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*ExplanationMetadata_InputMetadata_Visualization); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2].OneofWrappers = []interface{}{ |
| (*ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping)(nil), |
| (*ExplanationMetadata_OutputMetadata_DisplayNameMappingKey)(nil), |
| } |
| type x struct{} |
| out := protoimpl.TypeBuilder{ |
| File: protoimpl.DescBuilder{ |
| GoPackagePath: reflect.TypeOf(x{}).PkgPath(), |
| RawDescriptor: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDesc, |
| NumEnums: 5, |
| NumMessages: 7, |
| NumExtensions: 0, |
| NumServices: 0, |
| }, |
| GoTypes: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_goTypes, |
| DependencyIndexes: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_depIdxs, |
| EnumInfos: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes, |
| MessageInfos: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes, |
| }.Build() |
| File_google_cloud_aiplatform_v1beta1_explanation_metadata_proto = out.File |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDesc = nil |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_goTypes = nil |
| file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_depIdxs = nil |
| } |