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 String
getDisplayName()
User defined model name, can be used as alias by users to keep track of models.com.google.protobuf.ByteString
getDisplayNameBytes()
User defined model name, can be used as alias by users to keep track of models.boolean
getEnableCheckpoints()
If this is set, the model will be solved in the checkpoint mode.InputConfig
getInputConfig()
Required.InputConfigOrBuilder
getInputConfigOrBuilder()
Required.OutputConfig
getOutputConfig()
Required.OutputConfigOrBuilder
getOutputConfigOrBuilder()
Required.boolean
hasInputConfig()
Required.boolean
hasOutputConfig()
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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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