1// Copyright 2020 Google LLC 2// 3// Licensed under the Apache License, Version 2.0 (the "License"); 4// you may not use this file except in compliance with the License. 5// You may obtain a copy of the License at 6// 7// http://www.apache.org/licenses/LICENSE-2.0 8// 9// Unless required by applicable law or agreed to in writing, software 10// distributed under the License is distributed on an "AS IS" BASIS, 11// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12// See the License for the specific language governing permissions and 13// limitations under the License. 14 15// Code generated by protoc-gen-go. DO NOT EDIT. 16// versions: 17// protoc-gen-go v1.25.0 18// protoc v3.13.0 19// source: google/cloud/aiplatform/v1beta1/explanation_metadata.proto 20 21package aiplatform 22 23import ( 24 reflect "reflect" 25 sync "sync" 26 27 proto "github.com/golang/protobuf/proto" 28 _ "google.golang.org/genproto/googleapis/api/annotations" 29 protoreflect "google.golang.org/protobuf/reflect/protoreflect" 30 protoimpl "google.golang.org/protobuf/runtime/protoimpl" 31 structpb "google.golang.org/protobuf/types/known/structpb" 32) 33 34const ( 35 // Verify that this generated code is sufficiently up-to-date. 36 _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) 37 // Verify that runtime/protoimpl is sufficiently up-to-date. 38 _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) 39) 40 41// This is a compile-time assertion that a sufficiently up-to-date version 42// of the legacy proto package is being used. 43const _ = proto.ProtoPackageIsVersion4 44 45// Defines how the feature is encoded to [encoded_tensor][]. Defaults to 46// IDENTITY. 47type ExplanationMetadata_InputMetadata_Encoding int32 48 49const ( 50 // Default value. This is the same as IDENTITY. 51 ExplanationMetadata_InputMetadata_ENCODING_UNSPECIFIED ExplanationMetadata_InputMetadata_Encoding = 0 52 // The tensor represents one feature. 53 ExplanationMetadata_InputMetadata_IDENTITY ExplanationMetadata_InputMetadata_Encoding = 1 54 // The tensor represents a bag of features where each index maps to 55 // a feature. [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping] must be provided for 56 // this encoding. For example: 57 // ``` 58 // input = [27, 6.0, 150] 59 // index_feature_mapping = ["age", "height", "weight"] 60 // ``` 61 ExplanationMetadata_InputMetadata_BAG_OF_FEATURES ExplanationMetadata_InputMetadata_Encoding = 2 62 // The tensor represents a bag of features where each index maps to a 63 // feature. Zero values in the tensor indicates feature being 64 // non-existent. [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping] must be provided 65 // for this encoding. For example: 66 // ``` 67 // input = [2, 0, 5, 0, 1] 68 // index_feature_mapping = ["a", "b", "c", "d", "e"] 69 // ``` 70 ExplanationMetadata_InputMetadata_BAG_OF_FEATURES_SPARSE ExplanationMetadata_InputMetadata_Encoding = 3 71 // The tensor is a list of binaries representing whether a feature exists 72 // or not (1 indicates existence). [InputMetadata.index_feature_mapping][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping] 73 // must be provided for this encoding. For example: 74 // ``` 75 // input = [1, 0, 1, 0, 1] 76 // index_feature_mapping = ["a", "b", "c", "d", "e"] 77 // ``` 78 ExplanationMetadata_InputMetadata_INDICATOR ExplanationMetadata_InputMetadata_Encoding = 4 79 // The tensor is encoded into a 1-dimensional array represented by an 80 // encoded tensor. [InputMetadata.encoded_tensor_name][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_tensor_name] must be provided 81 // for this encoding. For example: 82 // ``` 83 // input = ["This", "is", "a", "test", "."] 84 // encoded = [0.1, 0.2, 0.3, 0.4, 0.5] 85 // ``` 86 ExplanationMetadata_InputMetadata_COMBINED_EMBEDDING ExplanationMetadata_InputMetadata_Encoding = 5 87 // Select this encoding when the input tensor is encoded into a 88 // 2-dimensional array represented by an encoded tensor. 89 // [InputMetadata.encoded_tensor_name][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_tensor_name] must be provided for this 90 // encoding. The first dimension of the encoded tensor's shape is the same 91 // as the input tensor's shape. For example: 92 // ``` 93 // input = ["This", "is", "a", "test", "."] 94 // encoded = [[0.1, 0.2, 0.3, 0.4, 0.5], 95 // [0.2, 0.1, 0.4, 0.3, 0.5], 96 // [0.5, 0.1, 0.3, 0.5, 0.4], 97 // [0.5, 0.3, 0.1, 0.2, 0.4], 98 // [0.4, 0.3, 0.2, 0.5, 0.1]] 99 // ``` 100 ExplanationMetadata_InputMetadata_CONCAT_EMBEDDING ExplanationMetadata_InputMetadata_Encoding = 6 101) 102 103// Enum value maps for ExplanationMetadata_InputMetadata_Encoding. 104var ( 105 ExplanationMetadata_InputMetadata_Encoding_name = map[int32]string{ 106 0: "ENCODING_UNSPECIFIED", 107 1: "IDENTITY", 108 2: "BAG_OF_FEATURES", 109 3: "BAG_OF_FEATURES_SPARSE", 110 4: "INDICATOR", 111 5: "COMBINED_EMBEDDING", 112 6: "CONCAT_EMBEDDING", 113 } 114 ExplanationMetadata_InputMetadata_Encoding_value = map[string]int32{ 115 "ENCODING_UNSPECIFIED": 0, 116 "IDENTITY": 1, 117 "BAG_OF_FEATURES": 2, 118 "BAG_OF_FEATURES_SPARSE": 3, 119 "INDICATOR": 4, 120 "COMBINED_EMBEDDING": 5, 121 "CONCAT_EMBEDDING": 6, 122 } 123) 124 125func (x ExplanationMetadata_InputMetadata_Encoding) Enum() *ExplanationMetadata_InputMetadata_Encoding { 126 p := new(ExplanationMetadata_InputMetadata_Encoding) 127 *p = x 128 return p 129} 130 131func (x ExplanationMetadata_InputMetadata_Encoding) String() string { 132 return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) 133} 134 135func (ExplanationMetadata_InputMetadata_Encoding) Descriptor() protoreflect.EnumDescriptor { 136 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[0].Descriptor() 137} 138 139func (ExplanationMetadata_InputMetadata_Encoding) Type() protoreflect.EnumType { 140 return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[0] 141} 142 143func (x ExplanationMetadata_InputMetadata_Encoding) Number() protoreflect.EnumNumber { 144 return protoreflect.EnumNumber(x) 145} 146 147// Deprecated: Use ExplanationMetadata_InputMetadata_Encoding.Descriptor instead. 148func (ExplanationMetadata_InputMetadata_Encoding) EnumDescriptor() ([]byte, []int) { 149 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 0} 150} 151 152// Type of the image visualization. Only applicable to [Integrated 153// Gradients attribution] 154// [ExplanationParameters.integrated_gradients_attribution]. 155type ExplanationMetadata_InputMetadata_Visualization_Type int32 156 157const ( 158 // Should not be used. 159 ExplanationMetadata_InputMetadata_Visualization_TYPE_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_Type = 0 160 // Shows which pixel contributed to the image prediction. 161 ExplanationMetadata_InputMetadata_Visualization_PIXELS ExplanationMetadata_InputMetadata_Visualization_Type = 1 162 // Shows which region contributed to the image prediction by outlining 163 // the region. 164 ExplanationMetadata_InputMetadata_Visualization_OUTLINES ExplanationMetadata_InputMetadata_Visualization_Type = 2 165) 166 167// Enum value maps for ExplanationMetadata_InputMetadata_Visualization_Type. 168var ( 169 ExplanationMetadata_InputMetadata_Visualization_Type_name = map[int32]string{ 170 0: "TYPE_UNSPECIFIED", 171 1: "PIXELS", 172 2: "OUTLINES", 173 } 174 ExplanationMetadata_InputMetadata_Visualization_Type_value = map[string]int32{ 175 "TYPE_UNSPECIFIED": 0, 176 "PIXELS": 1, 177 "OUTLINES": 2, 178 } 179) 180 181func (x ExplanationMetadata_InputMetadata_Visualization_Type) Enum() *ExplanationMetadata_InputMetadata_Visualization_Type { 182 p := new(ExplanationMetadata_InputMetadata_Visualization_Type) 183 *p = x 184 return p 185} 186 187func (x ExplanationMetadata_InputMetadata_Visualization_Type) String() string { 188 return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) 189} 190 191func (ExplanationMetadata_InputMetadata_Visualization_Type) Descriptor() protoreflect.EnumDescriptor { 192 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[1].Descriptor() 193} 194 195func (ExplanationMetadata_InputMetadata_Visualization_Type) Type() protoreflect.EnumType { 196 return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[1] 197} 198 199func (x ExplanationMetadata_InputMetadata_Visualization_Type) Number() protoreflect.EnumNumber { 200 return protoreflect.EnumNumber(x) 201} 202 203// Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_Type.Descriptor instead. 204func (ExplanationMetadata_InputMetadata_Visualization_Type) EnumDescriptor() ([]byte, []int) { 205 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 0} 206} 207 208// Whether to only highlight pixels with positive contributions, negative 209// or both. Defaults to POSITIVE. 210type ExplanationMetadata_InputMetadata_Visualization_Polarity int32 211 212const ( 213 // Default value. This is the same as POSITIVE. 214 ExplanationMetadata_InputMetadata_Visualization_POLARITY_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_Polarity = 0 215 // Highlights the pixels/outlines that were most influential to the 216 // model's prediction. 217 ExplanationMetadata_InputMetadata_Visualization_POSITIVE ExplanationMetadata_InputMetadata_Visualization_Polarity = 1 218 // Setting polarity to negative highlights areas that does not lead to 219 // the models's current prediction. 220 ExplanationMetadata_InputMetadata_Visualization_NEGATIVE ExplanationMetadata_InputMetadata_Visualization_Polarity = 2 221 // Shows both positive and negative attributions. 222 ExplanationMetadata_InputMetadata_Visualization_BOTH ExplanationMetadata_InputMetadata_Visualization_Polarity = 3 223) 224 225// Enum value maps for ExplanationMetadata_InputMetadata_Visualization_Polarity. 226var ( 227 ExplanationMetadata_InputMetadata_Visualization_Polarity_name = map[int32]string{ 228 0: "POLARITY_UNSPECIFIED", 229 1: "POSITIVE", 230 2: "NEGATIVE", 231 3: "BOTH", 232 } 233 ExplanationMetadata_InputMetadata_Visualization_Polarity_value = map[string]int32{ 234 "POLARITY_UNSPECIFIED": 0, 235 "POSITIVE": 1, 236 "NEGATIVE": 2, 237 "BOTH": 3, 238 } 239) 240 241func (x ExplanationMetadata_InputMetadata_Visualization_Polarity) Enum() *ExplanationMetadata_InputMetadata_Visualization_Polarity { 242 p := new(ExplanationMetadata_InputMetadata_Visualization_Polarity) 243 *p = x 244 return p 245} 246 247func (x ExplanationMetadata_InputMetadata_Visualization_Polarity) String() string { 248 return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) 249} 250 251func (ExplanationMetadata_InputMetadata_Visualization_Polarity) Descriptor() protoreflect.EnumDescriptor { 252 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[2].Descriptor() 253} 254 255func (ExplanationMetadata_InputMetadata_Visualization_Polarity) Type() protoreflect.EnumType { 256 return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[2] 257} 258 259func (x ExplanationMetadata_InputMetadata_Visualization_Polarity) Number() protoreflect.EnumNumber { 260 return protoreflect.EnumNumber(x) 261} 262 263// Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_Polarity.Descriptor instead. 264func (ExplanationMetadata_InputMetadata_Visualization_Polarity) EnumDescriptor() ([]byte, []int) { 265 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 1} 266} 267 268// The color scheme used for highlighting areas. 269type ExplanationMetadata_InputMetadata_Visualization_ColorMap int32 270 271const ( 272 // Should not be used. 273 ExplanationMetadata_InputMetadata_Visualization_COLOR_MAP_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_ColorMap = 0 274 // Positive: green. Negative: pink. 275 ExplanationMetadata_InputMetadata_Visualization_PINK_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 1 276 // Viridis color map: A perceptually uniform color mapping which is 277 // easier to see by those with colorblindness and progresses from yellow 278 // to green to blue. Positive: yellow. Negative: blue. 279 ExplanationMetadata_InputMetadata_Visualization_VIRIDIS ExplanationMetadata_InputMetadata_Visualization_ColorMap = 2 280 // Positive: red. Negative: red. 281 ExplanationMetadata_InputMetadata_Visualization_RED ExplanationMetadata_InputMetadata_Visualization_ColorMap = 3 282 // Positive: green. Negative: green. 283 ExplanationMetadata_InputMetadata_Visualization_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 4 284 // Positive: green. Negative: red. 285 ExplanationMetadata_InputMetadata_Visualization_RED_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 6 286 // PiYG palette. 287 ExplanationMetadata_InputMetadata_Visualization_PINK_WHITE_GREEN ExplanationMetadata_InputMetadata_Visualization_ColorMap = 5 288) 289 290// Enum value maps for ExplanationMetadata_InputMetadata_Visualization_ColorMap. 291var ( 292 ExplanationMetadata_InputMetadata_Visualization_ColorMap_name = map[int32]string{ 293 0: "COLOR_MAP_UNSPECIFIED", 294 1: "PINK_GREEN", 295 2: "VIRIDIS", 296 3: "RED", 297 4: "GREEN", 298 6: "RED_GREEN", 299 5: "PINK_WHITE_GREEN", 300 } 301 ExplanationMetadata_InputMetadata_Visualization_ColorMap_value = map[string]int32{ 302 "COLOR_MAP_UNSPECIFIED": 0, 303 "PINK_GREEN": 1, 304 "VIRIDIS": 2, 305 "RED": 3, 306 "GREEN": 4, 307 "RED_GREEN": 6, 308 "PINK_WHITE_GREEN": 5, 309 } 310) 311 312func (x ExplanationMetadata_InputMetadata_Visualization_ColorMap) Enum() *ExplanationMetadata_InputMetadata_Visualization_ColorMap { 313 p := new(ExplanationMetadata_InputMetadata_Visualization_ColorMap) 314 *p = x 315 return p 316} 317 318func (x ExplanationMetadata_InputMetadata_Visualization_ColorMap) String() string { 319 return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) 320} 321 322func (ExplanationMetadata_InputMetadata_Visualization_ColorMap) Descriptor() protoreflect.EnumDescriptor { 323 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[3].Descriptor() 324} 325 326func (ExplanationMetadata_InputMetadata_Visualization_ColorMap) Type() protoreflect.EnumType { 327 return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[3] 328} 329 330func (x ExplanationMetadata_InputMetadata_Visualization_ColorMap) Number() protoreflect.EnumNumber { 331 return protoreflect.EnumNumber(x) 332} 333 334// Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_ColorMap.Descriptor instead. 335func (ExplanationMetadata_InputMetadata_Visualization_ColorMap) EnumDescriptor() ([]byte, []int) { 336 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 2} 337} 338 339// How the original image is displayed in the visualization. 340type ExplanationMetadata_InputMetadata_Visualization_OverlayType int32 341 342const ( 343 // Default value. This is the same as NONE. 344 ExplanationMetadata_InputMetadata_Visualization_OVERLAY_TYPE_UNSPECIFIED ExplanationMetadata_InputMetadata_Visualization_OverlayType = 0 345 // No overlay. 346 ExplanationMetadata_InputMetadata_Visualization_NONE ExplanationMetadata_InputMetadata_Visualization_OverlayType = 1 347 // The attributions are shown on top of the original image. 348 ExplanationMetadata_InputMetadata_Visualization_ORIGINAL ExplanationMetadata_InputMetadata_Visualization_OverlayType = 2 349 // The attributions are shown on top of grayscaled version of the 350 // original image. 351 ExplanationMetadata_InputMetadata_Visualization_GRAYSCALE ExplanationMetadata_InputMetadata_Visualization_OverlayType = 3 352 // The attributions are used as a mask to reveal predictive parts of 353 // the image and hide the un-predictive parts. 354 ExplanationMetadata_InputMetadata_Visualization_MASK_BLACK ExplanationMetadata_InputMetadata_Visualization_OverlayType = 4 355) 356 357// Enum value maps for ExplanationMetadata_InputMetadata_Visualization_OverlayType. 358var ( 359 ExplanationMetadata_InputMetadata_Visualization_OverlayType_name = map[int32]string{ 360 0: "OVERLAY_TYPE_UNSPECIFIED", 361 1: "NONE", 362 2: "ORIGINAL", 363 3: "GRAYSCALE", 364 4: "MASK_BLACK", 365 } 366 ExplanationMetadata_InputMetadata_Visualization_OverlayType_value = map[string]int32{ 367 "OVERLAY_TYPE_UNSPECIFIED": 0, 368 "NONE": 1, 369 "ORIGINAL": 2, 370 "GRAYSCALE": 3, 371 "MASK_BLACK": 4, 372 } 373) 374 375func (x ExplanationMetadata_InputMetadata_Visualization_OverlayType) Enum() *ExplanationMetadata_InputMetadata_Visualization_OverlayType { 376 p := new(ExplanationMetadata_InputMetadata_Visualization_OverlayType) 377 *p = x 378 return p 379} 380 381func (x ExplanationMetadata_InputMetadata_Visualization_OverlayType) String() string { 382 return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) 383} 384 385func (ExplanationMetadata_InputMetadata_Visualization_OverlayType) Descriptor() protoreflect.EnumDescriptor { 386 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[4].Descriptor() 387} 388 389func (ExplanationMetadata_InputMetadata_Visualization_OverlayType) Type() protoreflect.EnumType { 390 return &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes[4] 391} 392 393func (x ExplanationMetadata_InputMetadata_Visualization_OverlayType) Number() protoreflect.EnumNumber { 394 return protoreflect.EnumNumber(x) 395} 396 397// Deprecated: Use ExplanationMetadata_InputMetadata_Visualization_OverlayType.Descriptor instead. 398func (ExplanationMetadata_InputMetadata_Visualization_OverlayType) EnumDescriptor() ([]byte, []int) { 399 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1, 3} 400} 401 402// Metadata describing the Model's input and output for explanation. 403type ExplanationMetadata struct { 404 state protoimpl.MessageState 405 sizeCache protoimpl.SizeCache 406 unknownFields protoimpl.UnknownFields 407 408 // Required. Map from feature names to feature input metadata. Keys are the name of the 409 // features. Values are the specification of the feature. 410 // 411 // An empty InputMetadata is valid. It describes a text feature which has the 412 // name specified as the key in [ExplanationMetadata.inputs][google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs]. The baseline 413 // of the empty feature is chosen by AI Platform. 414 // 415 // For AI Platform provided Tensorflow images, the key can be any friendly 416 // name of the feature . Once specified, [ 417 // featureAttributions][Attribution.feature_attributions] will be keyed by 418 // this key (if not grouped with another feature). 419 // 420 // For custom images, the key must match with the key in 421 // [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances]. 422 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"` 423 // Required. Map from output names to output metadata. 424 // 425 // For AI Platform provided Tensorflow images, keys can be any string user 426 // defines. 427 // 428 // For custom images, keys are the name of the output field in the prediction 429 // to be explained. 430 // 431 // Currently only one key is allowed. 432 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"` 433 // Points to a YAML file stored on Google Cloud Storage describing the format 434 // of the [feature attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions]. 435 // The schema is defined as an OpenAPI 3.0.2 436 // [Schema Object](https://tinyurl.com/y538mdwt#schema-object). 437 // AutoML tabular Models always have this field populated by AI Platform. 438 // Note: The URI given on output may be different, including the URI scheme, 439 // than the one given on input. The output URI will point to a location where 440 // the user only has a read access. 441 FeatureAttributionsSchemaUri string `protobuf:"bytes,3,opt,name=feature_attributions_schema_uri,json=featureAttributionsSchemaUri,proto3" json:"feature_attributions_schema_uri,omitempty"` 442} 443 444func (x *ExplanationMetadata) Reset() { 445 *x = ExplanationMetadata{} 446 if protoimpl.UnsafeEnabled { 447 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[0] 448 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 449 ms.StoreMessageInfo(mi) 450 } 451} 452 453func (x *ExplanationMetadata) String() string { 454 return protoimpl.X.MessageStringOf(x) 455} 456 457func (*ExplanationMetadata) ProtoMessage() {} 458 459func (x *ExplanationMetadata) ProtoReflect() protoreflect.Message { 460 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[0] 461 if protoimpl.UnsafeEnabled && x != nil { 462 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 463 if ms.LoadMessageInfo() == nil { 464 ms.StoreMessageInfo(mi) 465 } 466 return ms 467 } 468 return mi.MessageOf(x) 469} 470 471// Deprecated: Use ExplanationMetadata.ProtoReflect.Descriptor instead. 472func (*ExplanationMetadata) Descriptor() ([]byte, []int) { 473 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0} 474} 475 476func (x *ExplanationMetadata) GetInputs() map[string]*ExplanationMetadata_InputMetadata { 477 if x != nil { 478 return x.Inputs 479 } 480 return nil 481} 482 483func (x *ExplanationMetadata) GetOutputs() map[string]*ExplanationMetadata_OutputMetadata { 484 if x != nil { 485 return x.Outputs 486 } 487 return nil 488} 489 490func (x *ExplanationMetadata) GetFeatureAttributionsSchemaUri() string { 491 if x != nil { 492 return x.FeatureAttributionsSchemaUri 493 } 494 return "" 495} 496 497// Metadata of the input of a feature. 498// 499// Fields other than [InputMetadata.input_baselines][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.input_baselines] are applicable only 500// for Models that are using AI Platform-provided images for Tensorflow. 501type ExplanationMetadata_InputMetadata struct { 502 state protoimpl.MessageState 503 sizeCache protoimpl.SizeCache 504 unknownFields protoimpl.UnknownFields 505 506 // Baseline inputs for this feature. 507 // 508 // If no baseline is specified, AI Platform chooses the baseline for this 509 // feature. If multiple baselines are specified, AI Platform returns the 510 // average attributions across them in 511 // [Attributions.baseline_attribution][]. 512 // 513 // For AI Platform provided Tensorflow images (both 1.x and 2.x), the shape 514 // of each baseline must match the shape of the input tensor. If a scalar is 515 // provided, we broadcast to the same shape as the input tensor. 516 // 517 // For custom images, the element of the baselines must be in the same 518 // format as the feature's input in the 519 // [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances][]. The schema of any single instance 520 // may be specified via Endpoint's DeployedModels' 521 // [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] 522 // [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] 523 // [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]. 524 InputBaselines []*structpb.Value `protobuf:"bytes,1,rep,name=input_baselines,json=inputBaselines,proto3" json:"input_baselines,omitempty"` 525 // Name of the input tensor for this feature. Required and is only 526 // applicable to AI Platform provided images for Tensorflow. 527 InputTensorName string `protobuf:"bytes,2,opt,name=input_tensor_name,json=inputTensorName,proto3" json:"input_tensor_name,omitempty"` 528 // Defines how the feature is encoded into the input tensor. Defaults to 529 // IDENTITY. 530 Encoding ExplanationMetadata_InputMetadata_Encoding `protobuf:"varint,3,opt,name=encoding,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Encoding" json:"encoding,omitempty"` 531 // Modality of the feature. Valid values are: numeric, image. Defaults to 532 // numeric. 533 Modality string `protobuf:"bytes,4,opt,name=modality,proto3" json:"modality,omitempty"` 534 // The domain details of the input feature value. Like min/max, original 535 // mean or standard deviation if normalized. 536 FeatureValueDomain *ExplanationMetadata_InputMetadata_FeatureValueDomain `protobuf:"bytes,5,opt,name=feature_value_domain,json=featureValueDomain,proto3" json:"feature_value_domain,omitempty"` 537 // Specifies the index of the values of the input tensor. 538 // Required when the input tensor is a sparse representation. Refer to 539 // Tensorflow documentation for more details: 540 // https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor. 541 IndicesTensorName string `protobuf:"bytes,6,opt,name=indices_tensor_name,json=indicesTensorName,proto3" json:"indices_tensor_name,omitempty"` 542 // Specifies the shape of the values of the input if the input is a sparse 543 // representation. Refer to Tensorflow documentation for more details: 544 // https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor. 545 DenseShapeTensorName string `protobuf:"bytes,7,opt,name=dense_shape_tensor_name,json=denseShapeTensorName,proto3" json:"dense_shape_tensor_name,omitempty"` 546 // A list of feature names for each index in the input tensor. 547 // Required when the input [InputMetadata.encoding][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoding] is BAG_OF_FEATURES, 548 // BAG_OF_FEATURES_SPARSE, INDICATOR. 549 IndexFeatureMapping []string `protobuf:"bytes,8,rep,name=index_feature_mapping,json=indexFeatureMapping,proto3" json:"index_feature_mapping,omitempty"` 550 // Encoded tensor is a transformation of the input tensor. Must be provided 551 // if choosing [Integrated Gradients 552 // attribution][ExplanationParameters.integrated_gradients_attribution] or 553 // [XRAI attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.xrai_attribution] 554 // and the input tensor is not differentiable. 555 // 556 // An encoded tensor is generated if the input tensor is encoded by a lookup 557 // table. 558 EncodedTensorName string `protobuf:"bytes,9,opt,name=encoded_tensor_name,json=encodedTensorName,proto3" json:"encoded_tensor_name,omitempty"` 559 // A list of baselines for the encoded tensor. 560 // 561 // The shape of each baseline should match the shape of the encoded tensor. 562 // If a scalar is provided, AI Platform broadcast to the same shape as the 563 // encoded tensor. 564 EncodedBaselines []*structpb.Value `protobuf:"bytes,10,rep,name=encoded_baselines,json=encodedBaselines,proto3" json:"encoded_baselines,omitempty"` 565 // Visualization configurations for image explanation. 566 Visualization *ExplanationMetadata_InputMetadata_Visualization `protobuf:"bytes,11,opt,name=visualization,proto3" json:"visualization,omitempty"` 567 // Name of the group that the input belongs to. Features with the same group 568 // name will be treated as one feature when computing attributions. Features 569 // grouped together can have different shapes in value. If provided, there 570 // will be one single attribution generated in [ 571 // featureAttributions][Attribution.feature_attributions], keyed by the 572 // group name. 573 GroupName string `protobuf:"bytes,12,opt,name=group_name,json=groupName,proto3" json:"group_name,omitempty"` 574} 575 576func (x *ExplanationMetadata_InputMetadata) Reset() { 577 *x = ExplanationMetadata_InputMetadata{} 578 if protoimpl.UnsafeEnabled { 579 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[1] 580 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 581 ms.StoreMessageInfo(mi) 582 } 583} 584 585func (x *ExplanationMetadata_InputMetadata) String() string { 586 return protoimpl.X.MessageStringOf(x) 587} 588 589func (*ExplanationMetadata_InputMetadata) ProtoMessage() {} 590 591func (x *ExplanationMetadata_InputMetadata) ProtoReflect() protoreflect.Message { 592 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[1] 593 if protoimpl.UnsafeEnabled && x != nil { 594 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 595 if ms.LoadMessageInfo() == nil { 596 ms.StoreMessageInfo(mi) 597 } 598 return ms 599 } 600 return mi.MessageOf(x) 601} 602 603// Deprecated: Use ExplanationMetadata_InputMetadata.ProtoReflect.Descriptor instead. 604func (*ExplanationMetadata_InputMetadata) Descriptor() ([]byte, []int) { 605 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0} 606} 607 608func (x *ExplanationMetadata_InputMetadata) GetInputBaselines() []*structpb.Value { 609 if x != nil { 610 return x.InputBaselines 611 } 612 return nil 613} 614 615func (x *ExplanationMetadata_InputMetadata) GetInputTensorName() string { 616 if x != nil { 617 return x.InputTensorName 618 } 619 return "" 620} 621 622func (x *ExplanationMetadata_InputMetadata) GetEncoding() ExplanationMetadata_InputMetadata_Encoding { 623 if x != nil { 624 return x.Encoding 625 } 626 return ExplanationMetadata_InputMetadata_ENCODING_UNSPECIFIED 627} 628 629func (x *ExplanationMetadata_InputMetadata) GetModality() string { 630 if x != nil { 631 return x.Modality 632 } 633 return "" 634} 635 636func (x *ExplanationMetadata_InputMetadata) GetFeatureValueDomain() *ExplanationMetadata_InputMetadata_FeatureValueDomain { 637 if x != nil { 638 return x.FeatureValueDomain 639 } 640 return nil 641} 642 643func (x *ExplanationMetadata_InputMetadata) GetIndicesTensorName() string { 644 if x != nil { 645 return x.IndicesTensorName 646 } 647 return "" 648} 649 650func (x *ExplanationMetadata_InputMetadata) GetDenseShapeTensorName() string { 651 if x != nil { 652 return x.DenseShapeTensorName 653 } 654 return "" 655} 656 657func (x *ExplanationMetadata_InputMetadata) GetIndexFeatureMapping() []string { 658 if x != nil { 659 return x.IndexFeatureMapping 660 } 661 return nil 662} 663 664func (x *ExplanationMetadata_InputMetadata) GetEncodedTensorName() string { 665 if x != nil { 666 return x.EncodedTensorName 667 } 668 return "" 669} 670 671func (x *ExplanationMetadata_InputMetadata) GetEncodedBaselines() []*structpb.Value { 672 if x != nil { 673 return x.EncodedBaselines 674 } 675 return nil 676} 677 678func (x *ExplanationMetadata_InputMetadata) GetVisualization() *ExplanationMetadata_InputMetadata_Visualization { 679 if x != nil { 680 return x.Visualization 681 } 682 return nil 683} 684 685func (x *ExplanationMetadata_InputMetadata) GetGroupName() string { 686 if x != nil { 687 return x.GroupName 688 } 689 return "" 690} 691 692// Metadata of the prediction output to be explained. 693type ExplanationMetadata_OutputMetadata struct { 694 state protoimpl.MessageState 695 sizeCache protoimpl.SizeCache 696 unknownFields protoimpl.UnknownFields 697 698 // Defines how to map [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] to 699 // [Attribution.output_display_name][google.cloud.aiplatform.v1beta1.Attribution.output_display_name]. 700 // 701 // If neither of the fields are specified, 702 // [Attribution.output_display_name][google.cloud.aiplatform.v1beta1.Attribution.output_display_name] will not be populated. 703 // 704 // Types that are assignable to DisplayNameMapping: 705 // *ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping 706 // *ExplanationMetadata_OutputMetadata_DisplayNameMappingKey 707 DisplayNameMapping isExplanationMetadata_OutputMetadata_DisplayNameMapping `protobuf_oneof:"display_name_mapping"` 708 // Name of the output tensor. Required and is only applicable to AI 709 // Platform provided images for Tensorflow. 710 OutputTensorName string `protobuf:"bytes,3,opt,name=output_tensor_name,json=outputTensorName,proto3" json:"output_tensor_name,omitempty"` 711} 712 713func (x *ExplanationMetadata_OutputMetadata) Reset() { 714 *x = ExplanationMetadata_OutputMetadata{} 715 if protoimpl.UnsafeEnabled { 716 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2] 717 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 718 ms.StoreMessageInfo(mi) 719 } 720} 721 722func (x *ExplanationMetadata_OutputMetadata) String() string { 723 return protoimpl.X.MessageStringOf(x) 724} 725 726func (*ExplanationMetadata_OutputMetadata) ProtoMessage() {} 727 728func (x *ExplanationMetadata_OutputMetadata) ProtoReflect() protoreflect.Message { 729 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2] 730 if protoimpl.UnsafeEnabled && x != nil { 731 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 732 if ms.LoadMessageInfo() == nil { 733 ms.StoreMessageInfo(mi) 734 } 735 return ms 736 } 737 return mi.MessageOf(x) 738} 739 740// Deprecated: Use ExplanationMetadata_OutputMetadata.ProtoReflect.Descriptor instead. 741func (*ExplanationMetadata_OutputMetadata) Descriptor() ([]byte, []int) { 742 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 1} 743} 744 745func (m *ExplanationMetadata_OutputMetadata) GetDisplayNameMapping() isExplanationMetadata_OutputMetadata_DisplayNameMapping { 746 if m != nil { 747 return m.DisplayNameMapping 748 } 749 return nil 750} 751 752func (x *ExplanationMetadata_OutputMetadata) GetIndexDisplayNameMapping() *structpb.Value { 753 if x, ok := x.GetDisplayNameMapping().(*ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping); ok { 754 return x.IndexDisplayNameMapping 755 } 756 return nil 757} 758 759func (x *ExplanationMetadata_OutputMetadata) GetDisplayNameMappingKey() string { 760 if x, ok := x.GetDisplayNameMapping().(*ExplanationMetadata_OutputMetadata_DisplayNameMappingKey); ok { 761 return x.DisplayNameMappingKey 762 } 763 return "" 764} 765 766func (x *ExplanationMetadata_OutputMetadata) GetOutputTensorName() string { 767 if x != nil { 768 return x.OutputTensorName 769 } 770 return "" 771} 772 773type isExplanationMetadata_OutputMetadata_DisplayNameMapping interface { 774 isExplanationMetadata_OutputMetadata_DisplayNameMapping() 775} 776 777type ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping struct { 778 // Static mapping between the index and display name. 779 // 780 // Use this if the outputs are a deterministic n-dimensional array, e.g. a 781 // list of scores of all the classes in a pre-defined order for a 782 // multi-classification Model. It's not feasible if the outputs are 783 // non-deterministic, e.g. the Model produces top-k classes or sort the 784 // outputs by their values. 785 // 786 // The shape of the value must be an n-dimensional array of strings. The 787 // number of dimentions must match that of the outputs to be explained. 788 // The [Attribution.output_display_name][google.cloud.aiplatform.v1beta1.Attribution.output_display_name] is populated by locating in the 789 // mapping with [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index]. 790 IndexDisplayNameMapping *structpb.Value `protobuf:"bytes,1,opt,name=index_display_name_mapping,json=indexDisplayNameMapping,proto3,oneof"` 791} 792 793type ExplanationMetadata_OutputMetadata_DisplayNameMappingKey struct { 794 // Specify a field name in the prediction to look for the display name. 795 // 796 // Use this if the prediction contains the display names for the outputs. 797 // 798 // The display names in the prediction must have the same shape of the 799 // outputs, so that it can be located by [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] for 800 // a specific output. 801 DisplayNameMappingKey string `protobuf:"bytes,2,opt,name=display_name_mapping_key,json=displayNameMappingKey,proto3,oneof"` 802} 803 804func (*ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping) isExplanationMetadata_OutputMetadata_DisplayNameMapping() { 805} 806 807func (*ExplanationMetadata_OutputMetadata_DisplayNameMappingKey) isExplanationMetadata_OutputMetadata_DisplayNameMapping() { 808} 809 810// Domain details of the input feature value. Provides numeric information 811// about the feature, such as its range (min, max). If the feature has been 812// pre-processed, for example with z-scoring, then it provides information 813// about how to recover the original feature. For example, if the input 814// feature is an image and it has been pre-processed to obtain 0-mean and 815// stddev = 1 values, then original_mean, and original_stddev refer to the 816// mean and stddev of the original feature (e.g. image tensor) from which 817// input feature (with mean = 0 and stddev = 1) was obtained. 818type ExplanationMetadata_InputMetadata_FeatureValueDomain struct { 819 state protoimpl.MessageState 820 sizeCache protoimpl.SizeCache 821 unknownFields protoimpl.UnknownFields 822 823 // The minimum permissible value for this feature. 824 MinValue float32 `protobuf:"fixed32,1,opt,name=min_value,json=minValue,proto3" json:"min_value,omitempty"` 825 // The maximum permissible value for this feature. 826 MaxValue float32 `protobuf:"fixed32,2,opt,name=max_value,json=maxValue,proto3" json:"max_value,omitempty"` 827 // If this input feature has been normalized to a mean value of 0, 828 // the original_mean specifies the mean value of the domain prior to 829 // normalization. 830 OriginalMean float32 `protobuf:"fixed32,3,opt,name=original_mean,json=originalMean,proto3" json:"original_mean,omitempty"` 831 // If this input feature has been normalized to a standard deviation of 832 // 1.0, the original_stddev specifies the standard deviation of the domain 833 // prior to normalization. 834 OriginalStddev float32 `protobuf:"fixed32,4,opt,name=original_stddev,json=originalStddev,proto3" json:"original_stddev,omitempty"` 835} 836 837func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) Reset() { 838 *x = ExplanationMetadata_InputMetadata_FeatureValueDomain{} 839 if protoimpl.UnsafeEnabled { 840 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[5] 841 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 842 ms.StoreMessageInfo(mi) 843 } 844} 845 846func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) String() string { 847 return protoimpl.X.MessageStringOf(x) 848} 849 850func (*ExplanationMetadata_InputMetadata_FeatureValueDomain) ProtoMessage() {} 851 852func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) ProtoReflect() protoreflect.Message { 853 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[5] 854 if protoimpl.UnsafeEnabled && x != nil { 855 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 856 if ms.LoadMessageInfo() == nil { 857 ms.StoreMessageInfo(mi) 858 } 859 return ms 860 } 861 return mi.MessageOf(x) 862} 863 864// Deprecated: Use ExplanationMetadata_InputMetadata_FeatureValueDomain.ProtoReflect.Descriptor instead. 865func (*ExplanationMetadata_InputMetadata_FeatureValueDomain) Descriptor() ([]byte, []int) { 866 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 0} 867} 868 869func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetMinValue() float32 { 870 if x != nil { 871 return x.MinValue 872 } 873 return 0 874} 875 876func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetMaxValue() float32 { 877 if x != nil { 878 return x.MaxValue 879 } 880 return 0 881} 882 883func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetOriginalMean() float32 { 884 if x != nil { 885 return x.OriginalMean 886 } 887 return 0 888} 889 890func (x *ExplanationMetadata_InputMetadata_FeatureValueDomain) GetOriginalStddev() float32 { 891 if x != nil { 892 return x.OriginalStddev 893 } 894 return 0 895} 896 897// Visualization configurations for image explanation. 898type ExplanationMetadata_InputMetadata_Visualization struct { 899 state protoimpl.MessageState 900 sizeCache protoimpl.SizeCache 901 unknownFields protoimpl.UnknownFields 902 903 // Type of the image visualization. Only applicable to [Integrated 904 // Gradients attribution] 905 // [ExplanationParameters.integrated_gradients_attribution]. OUTLINES 906 // shows regions of attribution, while PIXELS shows per-pixel attribution. 907 // Defaults to OUTLINES. 908 Type ExplanationMetadata_InputMetadata_Visualization_Type `protobuf:"varint,1,opt,name=type,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Visualization_Type" json:"type,omitempty"` 909 // Whether to only highlight pixels with positive contributions, negative 910 // or both. Defaults to POSITIVE. 911 Polarity ExplanationMetadata_InputMetadata_Visualization_Polarity `protobuf:"varint,2,opt,name=polarity,proto3,enum=google.cloud.aiplatform.v1beta1.ExplanationMetadata_InputMetadata_Visualization_Polarity" json:"polarity,omitempty"` 912 // The color scheme used for the highlighted areas. 913 // 914 // Defaults to PINK_GREEN for [Integrated Gradients 915 // attribution][ExplanationParameters.integrated_gradients_attribution], 916 // which shows positive attributions in green and negative in pink. 917 // 918 // Defaults to VIRIDIS for 919 // [XRAI attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.xrai_attribution], which 920 // highlights the most influential regions in yellow and the least 921 // influential in blue. 922 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"` 923 // Excludes attributions above the specified percentile from the 924 // highlighted areas. Using the clip_percent_upperbound and 925 // clip_percent_lowerbound together can be useful for filtering out noise 926 // and making it easier to see areas of strong attribution. Defaults to 927 // 99.9. 928 ClipPercentUpperbound float32 `protobuf:"fixed32,4,opt,name=clip_percent_upperbound,json=clipPercentUpperbound,proto3" json:"clip_percent_upperbound,omitempty"` 929 // Excludes attributions below the specified percentile, from the 930 // highlighted areas. Defaults to 35. 931 ClipPercentLowerbound float32 `protobuf:"fixed32,5,opt,name=clip_percent_lowerbound,json=clipPercentLowerbound,proto3" json:"clip_percent_lowerbound,omitempty"` 932 // How the original image is displayed in the visualization. 933 // Adjusting the overlay can help increase visual clarity if the original 934 // image makes it difficult to view the visualization. Defaults to NONE. 935 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"` 936} 937 938func (x *ExplanationMetadata_InputMetadata_Visualization) Reset() { 939 *x = ExplanationMetadata_InputMetadata_Visualization{} 940 if protoimpl.UnsafeEnabled { 941 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[6] 942 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 943 ms.StoreMessageInfo(mi) 944 } 945} 946 947func (x *ExplanationMetadata_InputMetadata_Visualization) String() string { 948 return protoimpl.X.MessageStringOf(x) 949} 950 951func (*ExplanationMetadata_InputMetadata_Visualization) ProtoMessage() {} 952 953func (x *ExplanationMetadata_InputMetadata_Visualization) ProtoReflect() protoreflect.Message { 954 mi := &file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[6] 955 if protoimpl.UnsafeEnabled && x != nil { 956 ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) 957 if ms.LoadMessageInfo() == nil { 958 ms.StoreMessageInfo(mi) 959 } 960 return ms 961 } 962 return mi.MessageOf(x) 963} 964 965// Deprecated: Use ExplanationMetadata_InputMetadata_Visualization.ProtoReflect.Descriptor instead. 966func (*ExplanationMetadata_InputMetadata_Visualization) Descriptor() ([]byte, []int) { 967 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP(), []int{0, 0, 1} 968} 969 970func (x *ExplanationMetadata_InputMetadata_Visualization) GetType() ExplanationMetadata_InputMetadata_Visualization_Type { 971 if x != nil { 972 return x.Type 973 } 974 return ExplanationMetadata_InputMetadata_Visualization_TYPE_UNSPECIFIED 975} 976 977func (x *ExplanationMetadata_InputMetadata_Visualization) GetPolarity() ExplanationMetadata_InputMetadata_Visualization_Polarity { 978 if x != nil { 979 return x.Polarity 980 } 981 return ExplanationMetadata_InputMetadata_Visualization_POLARITY_UNSPECIFIED 982} 983 984func (x *ExplanationMetadata_InputMetadata_Visualization) GetColorMap() ExplanationMetadata_InputMetadata_Visualization_ColorMap { 985 if x != nil { 986 return x.ColorMap 987 } 988 return ExplanationMetadata_InputMetadata_Visualization_COLOR_MAP_UNSPECIFIED 989} 990 991func (x *ExplanationMetadata_InputMetadata_Visualization) GetClipPercentUpperbound() float32 { 992 if x != nil { 993 return x.ClipPercentUpperbound 994 } 995 return 0 996} 997 998func (x *ExplanationMetadata_InputMetadata_Visualization) GetClipPercentLowerbound() float32 { 999 if x != nil { 1000 return x.ClipPercentLowerbound 1001 } 1002 return 0 1003} 1004 1005func (x *ExplanationMetadata_InputMetadata_Visualization) GetOverlayType() ExplanationMetadata_InputMetadata_Visualization_OverlayType { 1006 if x != nil { 1007 return x.OverlayType 1008 } 1009 return 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file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescGZIP() []byte { 1225 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescOnce.Do(func() { 1226 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData) 1227 }) 1228 return file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDescData 1229} 1230 1231var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes = make([]protoimpl.EnumInfo, 5) 1232var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes = make([]protoimpl.MessageInfo, 7) 1233var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_goTypes = []interface{}{ 1234 (ExplanationMetadata_InputMetadata_Encoding)(0), // 0: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Encoding 1235 (ExplanationMetadata_InputMetadata_Visualization_Type)(0), // 1: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type 1236 (ExplanationMetadata_InputMetadata_Visualization_Polarity)(0), // 2: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity 1237 (ExplanationMetadata_InputMetadata_Visualization_ColorMap)(0), // 3: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap 1238 (ExplanationMetadata_InputMetadata_Visualization_OverlayType)(0), // 4: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType 1239 (*ExplanationMetadata)(nil), // 5: google.cloud.aiplatform.v1beta1.ExplanationMetadata 1240 (*ExplanationMetadata_InputMetadata)(nil), // 6: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata 1241 (*ExplanationMetadata_OutputMetadata)(nil), // 7: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata 1242 nil, // 8: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputsEntry 1243 nil, // 9: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputsEntry 1244 (*ExplanationMetadata_InputMetadata_FeatureValueDomain)(nil), // 10: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.FeatureValueDomain 1245 (*ExplanationMetadata_InputMetadata_Visualization)(nil), // 11: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization 1246 (*structpb.Value)(nil), // 12: google.protobuf.Value 1247} 1248var file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_depIdxs = []int32{ 1249 8, // 0: google.cloud.aiplatform.v1beta1.ExplanationMetadata.inputs:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputsEntry 1250 9, // 1: google.cloud.aiplatform.v1beta1.ExplanationMetadata.outputs:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputsEntry 1251 12, // 2: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.input_baselines:type_name -> google.protobuf.Value 1252 0, // 3: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoding:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Encoding 1253 10, // 4: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.feature_value_domain:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.FeatureValueDomain 1254 12, // 5: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_baselines:type_name -> google.protobuf.Value 1255 11, // 6: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.visualization:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization 1256 12, // 7: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata.index_display_name_mapping:type_name -> google.protobuf.Value 1257 6, // 8: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputsEntry.value:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata 1258 7, // 9: google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputsEntry.value:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata 1259 1, // 10: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.type:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Type 1260 2, // 11: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.polarity:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.Polarity 1261 3, // 12: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.color_map:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.ColorMap 1262 4, // 13: google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.overlay_type:type_name -> google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.Visualization.OverlayType 1263 14, // [14:14] is the sub-list for method output_type 1264 14, // [14:14] is the sub-list for method input_type 1265 14, // [14:14] is the sub-list for extension type_name 1266 14, // [14:14] is the sub-list for extension extendee 1267 0, // [0:14] is the sub-list for field type_name 1268} 1269 1270func init() { file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_init() } 1271func file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_init() { 1272 if File_google_cloud_aiplatform_v1beta1_explanation_metadata_proto != nil { 1273 return 1274 } 1275 if !protoimpl.UnsafeEnabled { 1276 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { 1277 switch v := v.(*ExplanationMetadata); i { 1278 case 0: 1279 return &v.state 1280 case 1: 1281 return &v.sizeCache 1282 case 2: 1283 return &v.unknownFields 1284 default: 1285 return nil 1286 } 1287 } 1288 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { 1289 switch v := v.(*ExplanationMetadata_InputMetadata); i { 1290 case 0: 1291 return &v.state 1292 case 1: 1293 return &v.sizeCache 1294 case 2: 1295 return &v.unknownFields 1296 default: 1297 return nil 1298 } 1299 } 1300 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { 1301 switch v := v.(*ExplanationMetadata_OutputMetadata); i { 1302 case 0: 1303 return &v.state 1304 case 1: 1305 return &v.sizeCache 1306 case 2: 1307 return &v.unknownFields 1308 default: 1309 return nil 1310 } 1311 } 1312 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} { 1313 switch v := v.(*ExplanationMetadata_InputMetadata_FeatureValueDomain); i { 1314 case 0: 1315 return &v.state 1316 case 1: 1317 return &v.sizeCache 1318 case 2: 1319 return &v.unknownFields 1320 default: 1321 return nil 1322 } 1323 } 1324 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} { 1325 switch v := v.(*ExplanationMetadata_InputMetadata_Visualization); i { 1326 case 0: 1327 return &v.state 1328 case 1: 1329 return &v.sizeCache 1330 case 2: 1331 return &v.unknownFields 1332 default: 1333 return nil 1334 } 1335 } 1336 } 1337 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes[2].OneofWrappers = []interface{}{ 1338 (*ExplanationMetadata_OutputMetadata_IndexDisplayNameMapping)(nil), 1339 (*ExplanationMetadata_OutputMetadata_DisplayNameMappingKey)(nil), 1340 } 1341 type x struct{} 1342 out := protoimpl.TypeBuilder{ 1343 File: protoimpl.DescBuilder{ 1344 GoPackagePath: reflect.TypeOf(x{}).PkgPath(), 1345 RawDescriptor: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDesc, 1346 NumEnums: 5, 1347 NumMessages: 7, 1348 NumExtensions: 0, 1349 NumServices: 0, 1350 }, 1351 GoTypes: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_goTypes, 1352 DependencyIndexes: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_depIdxs, 1353 EnumInfos: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_enumTypes, 1354 MessageInfos: file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_msgTypes, 1355 }.Build() 1356 File_google_cloud_aiplatform_v1beta1_explanation_metadata_proto = out.File 1357 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_rawDesc = nil 1358 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_goTypes = nil 1359 file_google_cloud_aiplatform_v1beta1_explanation_metadata_proto_depIdxs = nil 1360} 1361