Package com.google.cloud.optimization.v1
Interface BatchOptimizeToursRequest.AsyncModelConfigOrBuilder
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- All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder
- All Known Implementing Classes:
BatchOptimizeToursRequest.AsyncModelConfig,BatchOptimizeToursRequest.AsyncModelConfig.Builder
- Enclosing class:
- BatchOptimizeToursRequest
public static interface BatchOptimizeToursRequest.AsyncModelConfigOrBuilder extends com.google.protobuf.MessageOrBuilder
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description StringgetDisplayName()User defined model name, can be used as alias by users to keep track of models.com.google.protobuf.ByteStringgetDisplayNameBytes()User defined model name, can be used as alias by users to keep track of models.booleangetEnableCheckpoints()If this is set, the model will be solved in the checkpoint mode.InputConfiggetInputConfig()Required.InputConfigOrBuildergetInputConfigOrBuilder()Required.OutputConfiggetOutputConfig()Required.OutputConfigOrBuildergetOutputConfigOrBuilder()Required.booleanhasInputConfig()Required.booleanhasOutputConfig()Required.-
Methods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Detail
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getDisplayName
String getDisplayName()
User defined model name, can be used as alias by users to keep track of models.
string display_name = 1;- Returns:
- The displayName.
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getDisplayNameBytes
com.google.protobuf.ByteString getDisplayNameBytes()
User defined model name, can be used as alias by users to keep track of models.
string display_name = 1;- Returns:
- The bytes for displayName.
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hasInputConfig
boolean hasInputConfig()
Required. Information about the input model.
.google.cloud.optimization.v1.InputConfig input_config = 2 [(.google.api.field_behavior) = REQUIRED];- Returns:
- Whether the inputConfig field is set.
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getInputConfig
InputConfig getInputConfig()
Required. Information about the input model.
.google.cloud.optimization.v1.InputConfig input_config = 2 [(.google.api.field_behavior) = REQUIRED];- Returns:
- The inputConfig.
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getInputConfigOrBuilder
InputConfigOrBuilder getInputConfigOrBuilder()
Required. Information about the input model.
.google.cloud.optimization.v1.InputConfig input_config = 2 [(.google.api.field_behavior) = REQUIRED];
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hasOutputConfig
boolean hasOutputConfig()
Required. The desired output location information.
.google.cloud.optimization.v1.OutputConfig output_config = 3 [(.google.api.field_behavior) = REQUIRED];- Returns:
- Whether the outputConfig field is set.
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getOutputConfig
OutputConfig getOutputConfig()
Required. The desired output location information.
.google.cloud.optimization.v1.OutputConfig output_config = 3 [(.google.api.field_behavior) = REQUIRED];- Returns:
- The outputConfig.
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getOutputConfigOrBuilder
OutputConfigOrBuilder getOutputConfigOrBuilder()
Required. The desired output location information.
.google.cloud.optimization.v1.OutputConfig output_config = 3 [(.google.api.field_behavior) = REQUIRED];
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getEnableCheckpoints
boolean getEnableCheckpoints()
If this is set, the model will be solved in the checkpoint mode. In this mode, the input model can have a deadline longer than 30 mins without the risk of interruption. The model will be solved in multiple short-running stages. Each stage generates an intermediate checkpoint and stores it in the user's Cloud Storage buckets. The checkpoint mode should be preferred over allow_large_deadline_despite_interruption_risk since it prevents the risk of interruption.
bool enable_checkpoints = 4;- Returns:
- The enableCheckpoints.
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