1 /* 2 * Copyright 2020 Google LLC 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * https://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 // Generated by the protocol buffer compiler. DO NOT EDIT! 17 // source: google/cloud/automl/v1/io.proto 18 19 package com.google.cloud.automl.v1; 20 21 /** 22 * 23 * 24 * <pre> 25 * Input configuration for BatchPredict Action. 26 * The format of input depends on the ML problem of the model used for 27 * prediction. As input source the 28 * [gcs_source][google.cloud.automl.v1.InputConfig.gcs_source] 29 * is expected, unless specified otherwise. 30 * The formats are represented in EBNF with commas being literal and with 31 * non-terminal symbols defined near the end of this comment. The formats 32 * are: 33 * <h4>AutoML Vision</h4> 34 * <div class="ds-selector-tabs"><section><h5>Classification</h5> 35 * One or more CSV files where each line is a single column: 36 * GCS_FILE_PATH 37 * The Google Cloud Storage location of an image of up to 38 * 30MB in size. Supported extensions: .JPEG, .GIF, .PNG. 39 * This path is treated as the ID in the batch predict output. 40 * Sample rows: 41 * gs://folder/image1.jpeg 42 * gs://folder/image2.gif 43 * gs://folder/image3.png 44 * </section><section><h5>Object Detection</h5> 45 * One or more CSV files where each line is a single column: 46 * GCS_FILE_PATH 47 * The Google Cloud Storage location of an image of up to 48 * 30MB in size. Supported extensions: .JPEG, .GIF, .PNG. 49 * This path is treated as the ID in the batch predict output. 50 * Sample rows: 51 * gs://folder/image1.jpeg 52 * gs://folder/image2.gif 53 * gs://folder/image3.png 54 * </section> 55 * </div> 56 * <h4>AutoML Video Intelligence</h4> 57 * <div class="ds-selector-tabs"><section><h5>Classification</h5> 58 * One or more CSV files where each line is a single column: 59 * GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END 60 * `GCS_FILE_PATH` is the Google Cloud Storage location of video up to 50GB in 61 * size and up to 3h in duration duration. 62 * Supported extensions: .MOV, .MPEG4, .MP4, .AVI. 63 * `TIME_SEGMENT_START` and `TIME_SEGMENT_END` must be within the 64 * length of the video, and the end time must be after the start time. 65 * Sample rows: 66 * gs://folder/video1.mp4,10,40 67 * gs://folder/video1.mp4,20,60 68 * gs://folder/vid2.mov,0,inf 69 * </section><section><h5>Object Tracking</h5> 70 * One or more CSV files where each line is a single column: 71 * GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END 72 * `GCS_FILE_PATH` is the Google Cloud Storage location of video up to 50GB in 73 * size and up to 3h in duration duration. 74 * Supported extensions: .MOV, .MPEG4, .MP4, .AVI. 75 * `TIME_SEGMENT_START` and `TIME_SEGMENT_END` must be within the 76 * length of the video, and the end time must be after the start time. 77 * Sample rows: 78 * gs://folder/video1.mp4,10,40 79 * gs://folder/video1.mp4,20,60 80 * gs://folder/vid2.mov,0,inf 81 * </section> 82 * </div> 83 * <h4>AutoML Natural Language</h4> 84 * <div class="ds-selector-tabs"><section><h5>Classification</h5> 85 * One or more CSV files where each line is a single column: 86 * GCS_FILE_PATH 87 * `GCS_FILE_PATH` is the Google Cloud Storage location of a text file. 88 * Supported file extensions: .TXT, .PDF, .TIF, .TIFF 89 * Text files can be no larger than 10MB in size. 90 * Sample rows: 91 * gs://folder/text1.txt 92 * gs://folder/text2.pdf 93 * gs://folder/text3.tif 94 * </section><section><h5>Sentiment Analysis</h5> 95 * One or more CSV files where each line is a single column: 96 * GCS_FILE_PATH 97 * `GCS_FILE_PATH` is the Google Cloud Storage location of a text file. 98 * Supported file extensions: .TXT, .PDF, .TIF, .TIFF 99 * Text files can be no larger than 128kB in size. 100 * Sample rows: 101 * gs://folder/text1.txt 102 * gs://folder/text2.pdf 103 * gs://folder/text3.tif 104 * </section><section><h5>Entity Extraction</h5> 105 * One or more JSONL (JSON Lines) files that either provide inline text or 106 * documents. You can only use one format, either inline text or documents, 107 * for a single call to [AutoMl.BatchPredict]. 108 * Each JSONL file contains a per line a proto that 109 * wraps a temporary user-assigned TextSnippet ID (string up to 2000 110 * characters long) called "id", a TextSnippet proto (in 111 * JSON representation) and zero or more TextFeature protos. Any given 112 * text snippet content must have 30,000 characters or less, and also 113 * be UTF-8 NFC encoded (ASCII already is). The IDs provided should be 114 * unique. 115 * Each document JSONL file contains, per line, a proto that wraps a Document 116 * proto with `input_config` set. Each document cannot exceed 2MB in size. 117 * Supported document extensions: .PDF, .TIF, .TIFF 118 * Each JSONL file must not exceed 100MB in size, and no more than 20 119 * JSONL files may be passed. 120 * Sample inline JSONL file (Shown with artificial line 121 * breaks. Actual line breaks are denoted by "\n".): 122 * { 123 * "id": "my_first_id", 124 * "text_snippet": { "content": "dog car cat"}, 125 * "text_features": [ 126 * { 127 * "text_segment": {"start_offset": 4, "end_offset": 6}, 128 * "structural_type": PARAGRAPH, 129 * "bounding_poly": { 130 * "normalized_vertices": [ 131 * {"x": 0.1, "y": 0.1}, 132 * {"x": 0.1, "y": 0.3}, 133 * {"x": 0.3, "y": 0.3}, 134 * {"x": 0.3, "y": 0.1}, 135 * ] 136 * }, 137 * } 138 * ], 139 * }\n 140 * { 141 * "id": "2", 142 * "text_snippet": { 143 * "content": "Extended sample content", 144 * "mime_type": "text/plain" 145 * } 146 * } 147 * Sample document JSONL file (Shown with artificial line 148 * breaks. Actual line breaks are denoted by "\n".): 149 * { 150 * "document": { 151 * "input_config": { 152 * "gcs_source": { "input_uris": [ "gs://folder/document1.pdf" ] 153 * } 154 * } 155 * } 156 * }\n 157 * { 158 * "document": { 159 * "input_config": { 160 * "gcs_source": { "input_uris": [ "gs://folder/document2.tif" ] 161 * } 162 * } 163 * } 164 * } 165 * </section> 166 * </div> 167 * <h4>AutoML Tables</h4><div class="ui-datasection-main"><section 168 * class="selected"> 169 * See [Preparing your training 170 * data](https://cloud.google.com/automl-tables/docs/predict-batch) for more 171 * information. 172 * You can use either 173 * [gcs_source][google.cloud.automl.v1.BatchPredictInputConfig.gcs_source] 174 * or 175 * [bigquery_source][BatchPredictInputConfig.bigquery_source]. 176 * **For gcs_source:** 177 * CSV file(s), each by itself 10GB or smaller and total size must be 178 * 100GB or smaller, where first file must have a header containing 179 * column names. If the first row of a subsequent file is the same as 180 * the header, then it is also treated as a header. All other rows 181 * contain values for the corresponding columns. 182 * The column names must contain the model's 183 * [input_feature_column_specs'][google.cloud.automl.v1.TablesModelMetadata.input_feature_column_specs] 184 * [display_name-s][google.cloud.automl.v1.ColumnSpec.display_name] 185 * (order doesn't matter). The columns corresponding to the model's 186 * input feature column specs must contain values compatible with the 187 * column spec's data types. Prediction on all the rows, i.e. the CSV 188 * lines, will be attempted. 189 * Sample rows from a CSV file: 190 * <pre> 191 * "First Name","Last Name","Dob","Addresses" 192 * "John","Doe","1968-01-22","[{"status":"current","address":"123_First_Avenue","city":"Seattle","state":"WA","zip":"11111","numberOfYears":"1"},{"status":"previous","address":"456_Main_Street","city":"Portland","state":"OR","zip":"22222","numberOfYears":"5"}]" 193 * "Jane","Doe","1980-10-16","[{"status":"current","address":"789_Any_Avenue","city":"Albany","state":"NY","zip":"33333","numberOfYears":"2"},{"status":"previous","address":"321_Main_Street","city":"Hoboken","state":"NJ","zip":"44444","numberOfYears":"3"}]} 194 * </pre> 195 * **For bigquery_source:** 196 * The URI of a BigQuery table. The user data size of the BigQuery 197 * table must be 100GB or smaller. 198 * The column names must contain the model's 199 * [input_feature_column_specs'][google.cloud.automl.v1.TablesModelMetadata.input_feature_column_specs] 200 * [display_name-s][google.cloud.automl.v1.ColumnSpec.display_name] 201 * (order doesn't matter). The columns corresponding to the model's 202 * input feature column specs must contain values compatible with the 203 * column spec's data types. Prediction on all the rows of the table 204 * will be attempted. 205 * </section> 206 * </div> 207 * **Input field definitions:** 208 * `GCS_FILE_PATH` 209 * : The path to a file on Google Cloud Storage. For example, 210 * "gs://folder/video.avi". 211 * `TIME_SEGMENT_START` 212 * : (`TIME_OFFSET`) 213 * Expresses a beginning, inclusive, of a time segment 214 * within an example that has a time dimension 215 * (e.g. video). 216 * `TIME_SEGMENT_END` 217 * : (`TIME_OFFSET`) 218 * Expresses an end, exclusive, of a time segment within 219 * n example that has a time dimension (e.g. video). 220 * `TIME_OFFSET` 221 * : A number of seconds as measured from the start of an 222 * example (e.g. video). Fractions are allowed, up to a 223 * microsecond precision. "inf" is allowed, and it means the end 224 * of the example. 225 * **Errors:** 226 * If any of the provided CSV files can't be parsed or if more than certain 227 * percent of CSV rows cannot be processed then the operation fails and 228 * prediction does not happen. Regardless of overall success or failure the 229 * per-row failures, up to a certain count cap, will be listed in 230 * Operation.metadata.partial_failures. 231 * </pre> 232 * 233 * Protobuf type {@code google.cloud.automl.v1.BatchPredictInputConfig} 234 */ 235 public final class BatchPredictInputConfig extends com.google.protobuf.GeneratedMessageV3 236 implements 237 // @@protoc_insertion_point(message_implements:google.cloud.automl.v1.BatchPredictInputConfig) 238 BatchPredictInputConfigOrBuilder { 239 private static final long serialVersionUID = 0L; 240 // Use BatchPredictInputConfig.newBuilder() to construct. BatchPredictInputConfig(com.google.protobuf.GeneratedMessageV3.Builder<?> builder)241 private BatchPredictInputConfig(com.google.protobuf.GeneratedMessageV3.Builder<?> builder) { 242 super(builder); 243 } 244 BatchPredictInputConfig()245 private BatchPredictInputConfig() {} 246 247 @java.lang.Override 248 @SuppressWarnings({"unused"}) newInstance(UnusedPrivateParameter unused)249 protected java.lang.Object newInstance(UnusedPrivateParameter unused) { 250 return new BatchPredictInputConfig(); 251 } 252 253 @java.lang.Override getUnknownFields()254 public final com.google.protobuf.UnknownFieldSet getUnknownFields() { 255 return this.unknownFields; 256 } 257 getDescriptor()258 public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() { 259 return com.google.cloud.automl.v1.Io 260 .internal_static_google_cloud_automl_v1_BatchPredictInputConfig_descriptor; 261 } 262 263 @java.lang.Override 264 protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()265 internalGetFieldAccessorTable() { 266 return com.google.cloud.automl.v1.Io 267 .internal_static_google_cloud_automl_v1_BatchPredictInputConfig_fieldAccessorTable 268 .ensureFieldAccessorsInitialized( 269 com.google.cloud.automl.v1.BatchPredictInputConfig.class, 270 com.google.cloud.automl.v1.BatchPredictInputConfig.Builder.class); 271 } 272 273 private int sourceCase_ = 0; 274 private java.lang.Object source_; 275 276 public enum SourceCase 277 implements 278 com.google.protobuf.Internal.EnumLite, 279 com.google.protobuf.AbstractMessage.InternalOneOfEnum { 280 GCS_SOURCE(1), 281 SOURCE_NOT_SET(0); 282 private final int value; 283 SourceCase(int value)284 private SourceCase(int value) { 285 this.value = value; 286 } 287 /** 288 * @param value The number of the enum to look for. 289 * @return The enum associated with the given number. 290 * @deprecated Use {@link #forNumber(int)} instead. 291 */ 292 @java.lang.Deprecated valueOf(int value)293 public static SourceCase valueOf(int value) { 294 return forNumber(value); 295 } 296 forNumber(int value)297 public static SourceCase forNumber(int value) { 298 switch (value) { 299 case 1: 300 return GCS_SOURCE; 301 case 0: 302 return SOURCE_NOT_SET; 303 default: 304 return null; 305 } 306 } 307 getNumber()308 public int getNumber() { 309 return this.value; 310 } 311 }; 312 getSourceCase()313 public SourceCase getSourceCase() { 314 return SourceCase.forNumber(sourceCase_); 315 } 316 317 public static final int GCS_SOURCE_FIELD_NUMBER = 1; 318 /** 319 * 320 * 321 * <pre> 322 * Required. The Google Cloud Storage location for the input content. 323 * </pre> 324 * 325 * <code> 326 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 327 * </code> 328 * 329 * @return Whether the gcsSource field is set. 330 */ 331 @java.lang.Override hasGcsSource()332 public boolean hasGcsSource() { 333 return sourceCase_ == 1; 334 } 335 /** 336 * 337 * 338 * <pre> 339 * Required. The Google Cloud Storage location for the input content. 340 * </pre> 341 * 342 * <code> 343 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 344 * </code> 345 * 346 * @return The gcsSource. 347 */ 348 @java.lang.Override getGcsSource()349 public com.google.cloud.automl.v1.GcsSource getGcsSource() { 350 if (sourceCase_ == 1) { 351 return (com.google.cloud.automl.v1.GcsSource) source_; 352 } 353 return com.google.cloud.automl.v1.GcsSource.getDefaultInstance(); 354 } 355 /** 356 * 357 * 358 * <pre> 359 * Required. The Google Cloud Storage location for the input content. 360 * </pre> 361 * 362 * <code> 363 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 364 * </code> 365 */ 366 @java.lang.Override getGcsSourceOrBuilder()367 public com.google.cloud.automl.v1.GcsSourceOrBuilder getGcsSourceOrBuilder() { 368 if (sourceCase_ == 1) { 369 return (com.google.cloud.automl.v1.GcsSource) source_; 370 } 371 return com.google.cloud.automl.v1.GcsSource.getDefaultInstance(); 372 } 373 374 private byte memoizedIsInitialized = -1; 375 376 @java.lang.Override isInitialized()377 public final boolean isInitialized() { 378 byte isInitialized = memoizedIsInitialized; 379 if (isInitialized == 1) return true; 380 if (isInitialized == 0) return false; 381 382 memoizedIsInitialized = 1; 383 return true; 384 } 385 386 @java.lang.Override writeTo(com.google.protobuf.CodedOutputStream output)387 public void writeTo(com.google.protobuf.CodedOutputStream output) throws java.io.IOException { 388 if (sourceCase_ == 1) { 389 output.writeMessage(1, (com.google.cloud.automl.v1.GcsSource) source_); 390 } 391 getUnknownFields().writeTo(output); 392 } 393 394 @java.lang.Override getSerializedSize()395 public int getSerializedSize() { 396 int size = memoizedSize; 397 if (size != -1) return size; 398 399 size = 0; 400 if (sourceCase_ == 1) { 401 size += 402 com.google.protobuf.CodedOutputStream.computeMessageSize( 403 1, (com.google.cloud.automl.v1.GcsSource) source_); 404 } 405 size += getUnknownFields().getSerializedSize(); 406 memoizedSize = size; 407 return size; 408 } 409 410 @java.lang.Override equals(final java.lang.Object obj)411 public boolean equals(final java.lang.Object obj) { 412 if (obj == this) { 413 return true; 414 } 415 if (!(obj instanceof com.google.cloud.automl.v1.BatchPredictInputConfig)) { 416 return super.equals(obj); 417 } 418 com.google.cloud.automl.v1.BatchPredictInputConfig other = 419 (com.google.cloud.automl.v1.BatchPredictInputConfig) obj; 420 421 if (!getSourceCase().equals(other.getSourceCase())) return false; 422 switch (sourceCase_) { 423 case 1: 424 if (!getGcsSource().equals(other.getGcsSource())) return false; 425 break; 426 case 0: 427 default: 428 } 429 if (!getUnknownFields().equals(other.getUnknownFields())) return false; 430 return true; 431 } 432 433 @java.lang.Override hashCode()434 public int hashCode() { 435 if (memoizedHashCode != 0) { 436 return memoizedHashCode; 437 } 438 int hash = 41; 439 hash = (19 * hash) + getDescriptor().hashCode(); 440 switch (sourceCase_) { 441 case 1: 442 hash = (37 * hash) + GCS_SOURCE_FIELD_NUMBER; 443 hash = (53 * hash) + getGcsSource().hashCode(); 444 break; 445 case 0: 446 default: 447 } 448 hash = (29 * hash) + getUnknownFields().hashCode(); 449 memoizedHashCode = hash; 450 return hash; 451 } 452 parseFrom( java.nio.ByteBuffer data)453 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 454 java.nio.ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException { 455 return PARSER.parseFrom(data); 456 } 457 parseFrom( java.nio.ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)458 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 459 java.nio.ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) 460 throws com.google.protobuf.InvalidProtocolBufferException { 461 return PARSER.parseFrom(data, extensionRegistry); 462 } 463 parseFrom( com.google.protobuf.ByteString data)464 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 465 com.google.protobuf.ByteString data) 466 throws com.google.protobuf.InvalidProtocolBufferException { 467 return PARSER.parseFrom(data); 468 } 469 parseFrom( com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)470 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 471 com.google.protobuf.ByteString data, 472 com.google.protobuf.ExtensionRegistryLite extensionRegistry) 473 throws com.google.protobuf.InvalidProtocolBufferException { 474 return PARSER.parseFrom(data, extensionRegistry); 475 } 476 parseFrom(byte[] data)477 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom(byte[] data) 478 throws com.google.protobuf.InvalidProtocolBufferException { 479 return PARSER.parseFrom(data); 480 } 481 parseFrom( byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)482 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 483 byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) 484 throws com.google.protobuf.InvalidProtocolBufferException { 485 return PARSER.parseFrom(data, extensionRegistry); 486 } 487 parseFrom( java.io.InputStream input)488 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 489 java.io.InputStream input) throws java.io.IOException { 490 return com.google.protobuf.GeneratedMessageV3.parseWithIOException(PARSER, input); 491 } 492 parseFrom( java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)493 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 494 java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) 495 throws java.io.IOException { 496 return com.google.protobuf.GeneratedMessageV3.parseWithIOException( 497 PARSER, input, extensionRegistry); 498 } 499 parseDelimitedFrom( java.io.InputStream input)500 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseDelimitedFrom( 501 java.io.InputStream input) throws java.io.IOException { 502 return com.google.protobuf.GeneratedMessageV3.parseDelimitedWithIOException(PARSER, input); 503 } 504 parseDelimitedFrom( java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)505 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseDelimitedFrom( 506 java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) 507 throws java.io.IOException { 508 return com.google.protobuf.GeneratedMessageV3.parseDelimitedWithIOException( 509 PARSER, input, extensionRegistry); 510 } 511 parseFrom( com.google.protobuf.CodedInputStream input)512 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 513 com.google.protobuf.CodedInputStream input) throws java.io.IOException { 514 return com.google.protobuf.GeneratedMessageV3.parseWithIOException(PARSER, input); 515 } 516 parseFrom( com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)517 public static com.google.cloud.automl.v1.BatchPredictInputConfig parseFrom( 518 com.google.protobuf.CodedInputStream input, 519 com.google.protobuf.ExtensionRegistryLite extensionRegistry) 520 throws java.io.IOException { 521 return com.google.protobuf.GeneratedMessageV3.parseWithIOException( 522 PARSER, input, extensionRegistry); 523 } 524 525 @java.lang.Override newBuilderForType()526 public Builder newBuilderForType() { 527 return newBuilder(); 528 } 529 newBuilder()530 public static Builder newBuilder() { 531 return DEFAULT_INSTANCE.toBuilder(); 532 } 533 newBuilder(com.google.cloud.automl.v1.BatchPredictInputConfig prototype)534 public static Builder newBuilder(com.google.cloud.automl.v1.BatchPredictInputConfig prototype) { 535 return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype); 536 } 537 538 @java.lang.Override toBuilder()539 public Builder toBuilder() { 540 return this == DEFAULT_INSTANCE ? new Builder() : new Builder().mergeFrom(this); 541 } 542 543 @java.lang.Override newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)544 protected Builder newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { 545 Builder builder = new Builder(parent); 546 return builder; 547 } 548 /** 549 * 550 * 551 * <pre> 552 * Input configuration for BatchPredict Action. 553 * The format of input depends on the ML problem of the model used for 554 * prediction. As input source the 555 * [gcs_source][google.cloud.automl.v1.InputConfig.gcs_source] 556 * is expected, unless specified otherwise. 557 * The formats are represented in EBNF with commas being literal and with 558 * non-terminal symbols defined near the end of this comment. The formats 559 * are: 560 * <h4>AutoML Vision</h4> 561 * <div class="ds-selector-tabs"><section><h5>Classification</h5> 562 * One or more CSV files where each line is a single column: 563 * GCS_FILE_PATH 564 * The Google Cloud Storage location of an image of up to 565 * 30MB in size. Supported extensions: .JPEG, .GIF, .PNG. 566 * This path is treated as the ID in the batch predict output. 567 * Sample rows: 568 * gs://folder/image1.jpeg 569 * gs://folder/image2.gif 570 * gs://folder/image3.png 571 * </section><section><h5>Object Detection</h5> 572 * One or more CSV files where each line is a single column: 573 * GCS_FILE_PATH 574 * The Google Cloud Storage location of an image of up to 575 * 30MB in size. Supported extensions: .JPEG, .GIF, .PNG. 576 * This path is treated as the ID in the batch predict output. 577 * Sample rows: 578 * gs://folder/image1.jpeg 579 * gs://folder/image2.gif 580 * gs://folder/image3.png 581 * </section> 582 * </div> 583 * <h4>AutoML Video Intelligence</h4> 584 * <div class="ds-selector-tabs"><section><h5>Classification</h5> 585 * One or more CSV files where each line is a single column: 586 * GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END 587 * `GCS_FILE_PATH` is the Google Cloud Storage location of video up to 50GB in 588 * size and up to 3h in duration duration. 589 * Supported extensions: .MOV, .MPEG4, .MP4, .AVI. 590 * `TIME_SEGMENT_START` and `TIME_SEGMENT_END` must be within the 591 * length of the video, and the end time must be after the start time. 592 * Sample rows: 593 * gs://folder/video1.mp4,10,40 594 * gs://folder/video1.mp4,20,60 595 * gs://folder/vid2.mov,0,inf 596 * </section><section><h5>Object Tracking</h5> 597 * One or more CSV files where each line is a single column: 598 * GCS_FILE_PATH,TIME_SEGMENT_START,TIME_SEGMENT_END 599 * `GCS_FILE_PATH` is the Google Cloud Storage location of video up to 50GB in 600 * size and up to 3h in duration duration. 601 * Supported extensions: .MOV, .MPEG4, .MP4, .AVI. 602 * `TIME_SEGMENT_START` and `TIME_SEGMENT_END` must be within the 603 * length of the video, and the end time must be after the start time. 604 * Sample rows: 605 * gs://folder/video1.mp4,10,40 606 * gs://folder/video1.mp4,20,60 607 * gs://folder/vid2.mov,0,inf 608 * </section> 609 * </div> 610 * <h4>AutoML Natural Language</h4> 611 * <div class="ds-selector-tabs"><section><h5>Classification</h5> 612 * One or more CSV files where each line is a single column: 613 * GCS_FILE_PATH 614 * `GCS_FILE_PATH` is the Google Cloud Storage location of a text file. 615 * Supported file extensions: .TXT, .PDF, .TIF, .TIFF 616 * Text files can be no larger than 10MB in size. 617 * Sample rows: 618 * gs://folder/text1.txt 619 * gs://folder/text2.pdf 620 * gs://folder/text3.tif 621 * </section><section><h5>Sentiment Analysis</h5> 622 * One or more CSV files where each line is a single column: 623 * GCS_FILE_PATH 624 * `GCS_FILE_PATH` is the Google Cloud Storage location of a text file. 625 * Supported file extensions: .TXT, .PDF, .TIF, .TIFF 626 * Text files can be no larger than 128kB in size. 627 * Sample rows: 628 * gs://folder/text1.txt 629 * gs://folder/text2.pdf 630 * gs://folder/text3.tif 631 * </section><section><h5>Entity Extraction</h5> 632 * One or more JSONL (JSON Lines) files that either provide inline text or 633 * documents. You can only use one format, either inline text or documents, 634 * for a single call to [AutoMl.BatchPredict]. 635 * Each JSONL file contains a per line a proto that 636 * wraps a temporary user-assigned TextSnippet ID (string up to 2000 637 * characters long) called "id", a TextSnippet proto (in 638 * JSON representation) and zero or more TextFeature protos. Any given 639 * text snippet content must have 30,000 characters or less, and also 640 * be UTF-8 NFC encoded (ASCII already is). The IDs provided should be 641 * unique. 642 * Each document JSONL file contains, per line, a proto that wraps a Document 643 * proto with `input_config` set. Each document cannot exceed 2MB in size. 644 * Supported document extensions: .PDF, .TIF, .TIFF 645 * Each JSONL file must not exceed 100MB in size, and no more than 20 646 * JSONL files may be passed. 647 * Sample inline JSONL file (Shown with artificial line 648 * breaks. Actual line breaks are denoted by "\n".): 649 * { 650 * "id": "my_first_id", 651 * "text_snippet": { "content": "dog car cat"}, 652 * "text_features": [ 653 * { 654 * "text_segment": {"start_offset": 4, "end_offset": 6}, 655 * "structural_type": PARAGRAPH, 656 * "bounding_poly": { 657 * "normalized_vertices": [ 658 * {"x": 0.1, "y": 0.1}, 659 * {"x": 0.1, "y": 0.3}, 660 * {"x": 0.3, "y": 0.3}, 661 * {"x": 0.3, "y": 0.1}, 662 * ] 663 * }, 664 * } 665 * ], 666 * }\n 667 * { 668 * "id": "2", 669 * "text_snippet": { 670 * "content": "Extended sample content", 671 * "mime_type": "text/plain" 672 * } 673 * } 674 * Sample document JSONL file (Shown with artificial line 675 * breaks. Actual line breaks are denoted by "\n".): 676 * { 677 * "document": { 678 * "input_config": { 679 * "gcs_source": { "input_uris": [ "gs://folder/document1.pdf" ] 680 * } 681 * } 682 * } 683 * }\n 684 * { 685 * "document": { 686 * "input_config": { 687 * "gcs_source": { "input_uris": [ "gs://folder/document2.tif" ] 688 * } 689 * } 690 * } 691 * } 692 * </section> 693 * </div> 694 * <h4>AutoML Tables</h4><div class="ui-datasection-main"><section 695 * class="selected"> 696 * See [Preparing your training 697 * data](https://cloud.google.com/automl-tables/docs/predict-batch) for more 698 * information. 699 * You can use either 700 * [gcs_source][google.cloud.automl.v1.BatchPredictInputConfig.gcs_source] 701 * or 702 * [bigquery_source][BatchPredictInputConfig.bigquery_source]. 703 * **For gcs_source:** 704 * CSV file(s), each by itself 10GB or smaller and total size must be 705 * 100GB or smaller, where first file must have a header containing 706 * column names. If the first row of a subsequent file is the same as 707 * the header, then it is also treated as a header. All other rows 708 * contain values for the corresponding columns. 709 * The column names must contain the model's 710 * [input_feature_column_specs'][google.cloud.automl.v1.TablesModelMetadata.input_feature_column_specs] 711 * [display_name-s][google.cloud.automl.v1.ColumnSpec.display_name] 712 * (order doesn't matter). The columns corresponding to the model's 713 * input feature column specs must contain values compatible with the 714 * column spec's data types. Prediction on all the rows, i.e. the CSV 715 * lines, will be attempted. 716 * Sample rows from a CSV file: 717 * <pre> 718 * "First Name","Last Name","Dob","Addresses" 719 * "John","Doe","1968-01-22","[{"status":"current","address":"123_First_Avenue","city":"Seattle","state":"WA","zip":"11111","numberOfYears":"1"},{"status":"previous","address":"456_Main_Street","city":"Portland","state":"OR","zip":"22222","numberOfYears":"5"}]" 720 * "Jane","Doe","1980-10-16","[{"status":"current","address":"789_Any_Avenue","city":"Albany","state":"NY","zip":"33333","numberOfYears":"2"},{"status":"previous","address":"321_Main_Street","city":"Hoboken","state":"NJ","zip":"44444","numberOfYears":"3"}]} 721 * </pre> 722 * **For bigquery_source:** 723 * The URI of a BigQuery table. The user data size of the BigQuery 724 * table must be 100GB or smaller. 725 * The column names must contain the model's 726 * [input_feature_column_specs'][google.cloud.automl.v1.TablesModelMetadata.input_feature_column_specs] 727 * [display_name-s][google.cloud.automl.v1.ColumnSpec.display_name] 728 * (order doesn't matter). The columns corresponding to the model's 729 * input feature column specs must contain values compatible with the 730 * column spec's data types. Prediction on all the rows of the table 731 * will be attempted. 732 * </section> 733 * </div> 734 * **Input field definitions:** 735 * `GCS_FILE_PATH` 736 * : The path to a file on Google Cloud Storage. For example, 737 * "gs://folder/video.avi". 738 * `TIME_SEGMENT_START` 739 * : (`TIME_OFFSET`) 740 * Expresses a beginning, inclusive, of a time segment 741 * within an example that has a time dimension 742 * (e.g. video). 743 * `TIME_SEGMENT_END` 744 * : (`TIME_OFFSET`) 745 * Expresses an end, exclusive, of a time segment within 746 * n example that has a time dimension (e.g. video). 747 * `TIME_OFFSET` 748 * : A number of seconds as measured from the start of an 749 * example (e.g. video). Fractions are allowed, up to a 750 * microsecond precision. "inf" is allowed, and it means the end 751 * of the example. 752 * **Errors:** 753 * If any of the provided CSV files can't be parsed or if more than certain 754 * percent of CSV rows cannot be processed then the operation fails and 755 * prediction does not happen. Regardless of overall success or failure the 756 * per-row failures, up to a certain count cap, will be listed in 757 * Operation.metadata.partial_failures. 758 * </pre> 759 * 760 * Protobuf type {@code google.cloud.automl.v1.BatchPredictInputConfig} 761 */ 762 public static final class Builder extends com.google.protobuf.GeneratedMessageV3.Builder<Builder> 763 implements 764 // @@protoc_insertion_point(builder_implements:google.cloud.automl.v1.BatchPredictInputConfig) 765 com.google.cloud.automl.v1.BatchPredictInputConfigOrBuilder { getDescriptor()766 public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() { 767 return com.google.cloud.automl.v1.Io 768 .internal_static_google_cloud_automl_v1_BatchPredictInputConfig_descriptor; 769 } 770 771 @java.lang.Override 772 protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()773 internalGetFieldAccessorTable() { 774 return com.google.cloud.automl.v1.Io 775 .internal_static_google_cloud_automl_v1_BatchPredictInputConfig_fieldAccessorTable 776 .ensureFieldAccessorsInitialized( 777 com.google.cloud.automl.v1.BatchPredictInputConfig.class, 778 com.google.cloud.automl.v1.BatchPredictInputConfig.Builder.class); 779 } 780 781 // Construct using com.google.cloud.automl.v1.BatchPredictInputConfig.newBuilder() Builder()782 private Builder() {} 783 Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)784 private Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) { 785 super(parent); 786 } 787 788 @java.lang.Override clear()789 public Builder clear() { 790 super.clear(); 791 bitField0_ = 0; 792 if (gcsSourceBuilder_ != null) { 793 gcsSourceBuilder_.clear(); 794 } 795 sourceCase_ = 0; 796 source_ = null; 797 return this; 798 } 799 800 @java.lang.Override getDescriptorForType()801 public com.google.protobuf.Descriptors.Descriptor getDescriptorForType() { 802 return com.google.cloud.automl.v1.Io 803 .internal_static_google_cloud_automl_v1_BatchPredictInputConfig_descriptor; 804 } 805 806 @java.lang.Override getDefaultInstanceForType()807 public com.google.cloud.automl.v1.BatchPredictInputConfig getDefaultInstanceForType() { 808 return com.google.cloud.automl.v1.BatchPredictInputConfig.getDefaultInstance(); 809 } 810 811 @java.lang.Override build()812 public com.google.cloud.automl.v1.BatchPredictInputConfig build() { 813 com.google.cloud.automl.v1.BatchPredictInputConfig result = buildPartial(); 814 if (!result.isInitialized()) { 815 throw newUninitializedMessageException(result); 816 } 817 return result; 818 } 819 820 @java.lang.Override buildPartial()821 public com.google.cloud.automl.v1.BatchPredictInputConfig buildPartial() { 822 com.google.cloud.automl.v1.BatchPredictInputConfig result = 823 new com.google.cloud.automl.v1.BatchPredictInputConfig(this); 824 if (bitField0_ != 0) { 825 buildPartial0(result); 826 } 827 buildPartialOneofs(result); 828 onBuilt(); 829 return result; 830 } 831 buildPartial0(com.google.cloud.automl.v1.BatchPredictInputConfig result)832 private void buildPartial0(com.google.cloud.automl.v1.BatchPredictInputConfig result) { 833 int from_bitField0_ = bitField0_; 834 } 835 buildPartialOneofs(com.google.cloud.automl.v1.BatchPredictInputConfig result)836 private void buildPartialOneofs(com.google.cloud.automl.v1.BatchPredictInputConfig result) { 837 result.sourceCase_ = sourceCase_; 838 result.source_ = this.source_; 839 if (sourceCase_ == 1 && gcsSourceBuilder_ != null) { 840 result.source_ = gcsSourceBuilder_.build(); 841 } 842 } 843 844 @java.lang.Override clone()845 public Builder clone() { 846 return super.clone(); 847 } 848 849 @java.lang.Override setField( com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)850 public Builder setField( 851 com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) { 852 return super.setField(field, value); 853 } 854 855 @java.lang.Override clearField(com.google.protobuf.Descriptors.FieldDescriptor field)856 public Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field) { 857 return super.clearField(field); 858 } 859 860 @java.lang.Override clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)861 public Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) { 862 return super.clearOneof(oneof); 863 } 864 865 @java.lang.Override setRepeatedField( com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value)866 public Builder setRepeatedField( 867 com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value) { 868 return super.setRepeatedField(field, index, value); 869 } 870 871 @java.lang.Override addRepeatedField( com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)872 public Builder addRepeatedField( 873 com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) { 874 return super.addRepeatedField(field, value); 875 } 876 877 @java.lang.Override mergeFrom(com.google.protobuf.Message other)878 public Builder mergeFrom(com.google.protobuf.Message other) { 879 if (other instanceof com.google.cloud.automl.v1.BatchPredictInputConfig) { 880 return mergeFrom((com.google.cloud.automl.v1.BatchPredictInputConfig) other); 881 } else { 882 super.mergeFrom(other); 883 return this; 884 } 885 } 886 mergeFrom(com.google.cloud.automl.v1.BatchPredictInputConfig other)887 public Builder mergeFrom(com.google.cloud.automl.v1.BatchPredictInputConfig other) { 888 if (other == com.google.cloud.automl.v1.BatchPredictInputConfig.getDefaultInstance()) 889 return this; 890 switch (other.getSourceCase()) { 891 case GCS_SOURCE: 892 { 893 mergeGcsSource(other.getGcsSource()); 894 break; 895 } 896 case SOURCE_NOT_SET: 897 { 898 break; 899 } 900 } 901 this.mergeUnknownFields(other.getUnknownFields()); 902 onChanged(); 903 return this; 904 } 905 906 @java.lang.Override isInitialized()907 public final boolean isInitialized() { 908 return true; 909 } 910 911 @java.lang.Override mergeFrom( com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)912 public Builder mergeFrom( 913 com.google.protobuf.CodedInputStream input, 914 com.google.protobuf.ExtensionRegistryLite extensionRegistry) 915 throws java.io.IOException { 916 if (extensionRegistry == null) { 917 throw new java.lang.NullPointerException(); 918 } 919 try { 920 boolean done = false; 921 while (!done) { 922 int tag = input.readTag(); 923 switch (tag) { 924 case 0: 925 done = true; 926 break; 927 case 10: 928 { 929 input.readMessage(getGcsSourceFieldBuilder().getBuilder(), extensionRegistry); 930 sourceCase_ = 1; 931 break; 932 } // case 10 933 default: 934 { 935 if (!super.parseUnknownField(input, extensionRegistry, tag)) { 936 done = true; // was an endgroup tag 937 } 938 break; 939 } // default: 940 } // switch (tag) 941 } // while (!done) 942 } catch (com.google.protobuf.InvalidProtocolBufferException e) { 943 throw e.unwrapIOException(); 944 } finally { 945 onChanged(); 946 } // finally 947 return this; 948 } 949 950 private int sourceCase_ = 0; 951 private java.lang.Object source_; 952 getSourceCase()953 public SourceCase getSourceCase() { 954 return SourceCase.forNumber(sourceCase_); 955 } 956 clearSource()957 public Builder clearSource() { 958 sourceCase_ = 0; 959 source_ = null; 960 onChanged(); 961 return this; 962 } 963 964 private int bitField0_; 965 966 private com.google.protobuf.SingleFieldBuilderV3< 967 com.google.cloud.automl.v1.GcsSource, 968 com.google.cloud.automl.v1.GcsSource.Builder, 969 com.google.cloud.automl.v1.GcsSourceOrBuilder> 970 gcsSourceBuilder_; 971 /** 972 * 973 * 974 * <pre> 975 * Required. The Google Cloud Storage location for the input content. 976 * </pre> 977 * 978 * <code> 979 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 980 * </code> 981 * 982 * @return Whether the gcsSource field is set. 983 */ 984 @java.lang.Override hasGcsSource()985 public boolean hasGcsSource() { 986 return sourceCase_ == 1; 987 } 988 /** 989 * 990 * 991 * <pre> 992 * Required. The Google Cloud Storage location for the input content. 993 * </pre> 994 * 995 * <code> 996 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 997 * </code> 998 * 999 * @return The gcsSource. 1000 */ 1001 @java.lang.Override getGcsSource()1002 public com.google.cloud.automl.v1.GcsSource getGcsSource() { 1003 if (gcsSourceBuilder_ == null) { 1004 if (sourceCase_ == 1) { 1005 return (com.google.cloud.automl.v1.GcsSource) source_; 1006 } 1007 return com.google.cloud.automl.v1.GcsSource.getDefaultInstance(); 1008 } else { 1009 if (sourceCase_ == 1) { 1010 return gcsSourceBuilder_.getMessage(); 1011 } 1012 return com.google.cloud.automl.v1.GcsSource.getDefaultInstance(); 1013 } 1014 } 1015 /** 1016 * 1017 * 1018 * <pre> 1019 * Required. The Google Cloud Storage location for the input content. 1020 * </pre> 1021 * 1022 * <code> 1023 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1024 * </code> 1025 */ setGcsSource(com.google.cloud.automl.v1.GcsSource value)1026 public Builder setGcsSource(com.google.cloud.automl.v1.GcsSource value) { 1027 if (gcsSourceBuilder_ == null) { 1028 if (value == null) { 1029 throw new NullPointerException(); 1030 } 1031 source_ = value; 1032 onChanged(); 1033 } else { 1034 gcsSourceBuilder_.setMessage(value); 1035 } 1036 sourceCase_ = 1; 1037 return this; 1038 } 1039 /** 1040 * 1041 * 1042 * <pre> 1043 * Required. The Google Cloud Storage location for the input content. 1044 * </pre> 1045 * 1046 * <code> 1047 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1048 * </code> 1049 */ setGcsSource(com.google.cloud.automl.v1.GcsSource.Builder builderForValue)1050 public Builder setGcsSource(com.google.cloud.automl.v1.GcsSource.Builder builderForValue) { 1051 if (gcsSourceBuilder_ == null) { 1052 source_ = builderForValue.build(); 1053 onChanged(); 1054 } else { 1055 gcsSourceBuilder_.setMessage(builderForValue.build()); 1056 } 1057 sourceCase_ = 1; 1058 return this; 1059 } 1060 /** 1061 * 1062 * 1063 * <pre> 1064 * Required. The Google Cloud Storage location for the input content. 1065 * </pre> 1066 * 1067 * <code> 1068 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1069 * </code> 1070 */ mergeGcsSource(com.google.cloud.automl.v1.GcsSource value)1071 public Builder mergeGcsSource(com.google.cloud.automl.v1.GcsSource value) { 1072 if (gcsSourceBuilder_ == null) { 1073 if (sourceCase_ == 1 1074 && source_ != com.google.cloud.automl.v1.GcsSource.getDefaultInstance()) { 1075 source_ = 1076 com.google.cloud.automl.v1.GcsSource.newBuilder( 1077 (com.google.cloud.automl.v1.GcsSource) source_) 1078 .mergeFrom(value) 1079 .buildPartial(); 1080 } else { 1081 source_ = value; 1082 } 1083 onChanged(); 1084 } else { 1085 if (sourceCase_ == 1) { 1086 gcsSourceBuilder_.mergeFrom(value); 1087 } else { 1088 gcsSourceBuilder_.setMessage(value); 1089 } 1090 } 1091 sourceCase_ = 1; 1092 return this; 1093 } 1094 /** 1095 * 1096 * 1097 * <pre> 1098 * Required. The Google Cloud Storage location for the input content. 1099 * </pre> 1100 * 1101 * <code> 1102 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1103 * </code> 1104 */ clearGcsSource()1105 public Builder clearGcsSource() { 1106 if (gcsSourceBuilder_ == null) { 1107 if (sourceCase_ == 1) { 1108 sourceCase_ = 0; 1109 source_ = null; 1110 onChanged(); 1111 } 1112 } else { 1113 if (sourceCase_ == 1) { 1114 sourceCase_ = 0; 1115 source_ = null; 1116 } 1117 gcsSourceBuilder_.clear(); 1118 } 1119 return this; 1120 } 1121 /** 1122 * 1123 * 1124 * <pre> 1125 * Required. The Google Cloud Storage location for the input content. 1126 * </pre> 1127 * 1128 * <code> 1129 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1130 * </code> 1131 */ getGcsSourceBuilder()1132 public com.google.cloud.automl.v1.GcsSource.Builder getGcsSourceBuilder() { 1133 return getGcsSourceFieldBuilder().getBuilder(); 1134 } 1135 /** 1136 * 1137 * 1138 * <pre> 1139 * Required. The Google Cloud Storage location for the input content. 1140 * </pre> 1141 * 1142 * <code> 1143 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1144 * </code> 1145 */ 1146 @java.lang.Override getGcsSourceOrBuilder()1147 public com.google.cloud.automl.v1.GcsSourceOrBuilder getGcsSourceOrBuilder() { 1148 if ((sourceCase_ == 1) && (gcsSourceBuilder_ != null)) { 1149 return gcsSourceBuilder_.getMessageOrBuilder(); 1150 } else { 1151 if (sourceCase_ == 1) { 1152 return (com.google.cloud.automl.v1.GcsSource) source_; 1153 } 1154 return com.google.cloud.automl.v1.GcsSource.getDefaultInstance(); 1155 } 1156 } 1157 /** 1158 * 1159 * 1160 * <pre> 1161 * Required. The Google Cloud Storage location for the input content. 1162 * </pre> 1163 * 1164 * <code> 1165 * .google.cloud.automl.v1.GcsSource gcs_source = 1 [(.google.api.field_behavior) = REQUIRED]; 1166 * </code> 1167 */ 1168 private com.google.protobuf.SingleFieldBuilderV3< 1169 com.google.cloud.automl.v1.GcsSource, 1170 com.google.cloud.automl.v1.GcsSource.Builder, 1171 com.google.cloud.automl.v1.GcsSourceOrBuilder> getGcsSourceFieldBuilder()1172 getGcsSourceFieldBuilder() { 1173 if (gcsSourceBuilder_ == null) { 1174 if (!(sourceCase_ == 1)) { 1175 source_ = com.google.cloud.automl.v1.GcsSource.getDefaultInstance(); 1176 } 1177 gcsSourceBuilder_ = 1178 new com.google.protobuf.SingleFieldBuilderV3< 1179 com.google.cloud.automl.v1.GcsSource, 1180 com.google.cloud.automl.v1.GcsSource.Builder, 1181 com.google.cloud.automl.v1.GcsSourceOrBuilder>( 1182 (com.google.cloud.automl.v1.GcsSource) source_, getParentForChildren(), isClean()); 1183 source_ = null; 1184 } 1185 sourceCase_ = 1; 1186 onChanged(); 1187 return gcsSourceBuilder_; 1188 } 1189 1190 @java.lang.Override setUnknownFields(final com.google.protobuf.UnknownFieldSet unknownFields)1191 public final Builder setUnknownFields(final com.google.protobuf.UnknownFieldSet unknownFields) { 1192 return super.setUnknownFields(unknownFields); 1193 } 1194 1195 @java.lang.Override mergeUnknownFields( final com.google.protobuf.UnknownFieldSet unknownFields)1196 public final Builder mergeUnknownFields( 1197 final com.google.protobuf.UnknownFieldSet unknownFields) { 1198 return super.mergeUnknownFields(unknownFields); 1199 } 1200 1201 // @@protoc_insertion_point(builder_scope:google.cloud.automl.v1.BatchPredictInputConfig) 1202 } 1203 1204 // @@protoc_insertion_point(class_scope:google.cloud.automl.v1.BatchPredictInputConfig) 1205 private static final com.google.cloud.automl.v1.BatchPredictInputConfig DEFAULT_INSTANCE; 1206 1207 static { 1208 DEFAULT_INSTANCE = new com.google.cloud.automl.v1.BatchPredictInputConfig(); 1209 } 1210 getDefaultInstance()1211 public static com.google.cloud.automl.v1.BatchPredictInputConfig getDefaultInstance() { 1212 return DEFAULT_INSTANCE; 1213 } 1214 1215 private static final com.google.protobuf.Parser<BatchPredictInputConfig> PARSER = 1216 new com.google.protobuf.AbstractParser<BatchPredictInputConfig>() { 1217 @java.lang.Override 1218 public BatchPredictInputConfig parsePartialFrom( 1219 com.google.protobuf.CodedInputStream input, 1220 com.google.protobuf.ExtensionRegistryLite extensionRegistry) 1221 throws com.google.protobuf.InvalidProtocolBufferException { 1222 Builder builder = newBuilder(); 1223 try { 1224 builder.mergeFrom(input, extensionRegistry); 1225 } catch (com.google.protobuf.InvalidProtocolBufferException e) { 1226 throw e.setUnfinishedMessage(builder.buildPartial()); 1227 } catch (com.google.protobuf.UninitializedMessageException e) { 1228 throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial()); 1229 } catch (java.io.IOException e) { 1230 throw new com.google.protobuf.InvalidProtocolBufferException(e) 1231 .setUnfinishedMessage(builder.buildPartial()); 1232 } 1233 return builder.buildPartial(); 1234 } 1235 }; 1236 parser()1237 public static com.google.protobuf.Parser<BatchPredictInputConfig> parser() { 1238 return PARSER; 1239 } 1240 1241 @java.lang.Override getParserForType()1242 public com.google.protobuf.Parser<BatchPredictInputConfig> getParserForType() { 1243 return PARSER; 1244 } 1245 1246 @java.lang.Override getDefaultInstanceForType()1247 public com.google.cloud.automl.v1.BatchPredictInputConfig getDefaultInstanceForType() { 1248 return DEFAULT_INSTANCE; 1249 } 1250 } 1251
