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package Paws::MachineLearning::GetMLModelOutput; |
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use Moose; |
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has ComputeTime => (is => 'ro', isa => 'Int'); |
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has CreatedAt => (is => 'ro', isa => 'Str'); |
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has CreatedByIamUser => (is => 'ro', isa => 'Str'); |
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has EndpointInfo => (is => 'ro', isa => 'Paws::MachineLearning::RealtimeEndpointInfo'); |
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has FinishedAt => (is => 'ro', isa => 'Str'); |
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has InputDataLocationS3 => (is => 'ro', isa => 'Str'); |
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has LastUpdatedAt => (is => 'ro', isa => 'Str'); |
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has LogUri => (is => 'ro', isa => 'Str'); |
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has Message => (is => 'ro', isa => 'Str'); |
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has MLModelId => (is => 'ro', isa => 'Str'); |
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has MLModelType => (is => 'ro', isa => 'Str'); |
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has Name => (is => 'ro', isa => 'Str'); |
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has Recipe => (is => 'ro', isa => 'Str'); |
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has Schema => (is => 'ro', isa => 'Str'); |
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has ScoreThreshold => (is => 'ro', isa => 'Num'); |
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has ScoreThresholdLastUpdatedAt => (is => 'ro', isa => 'Str'); |
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has SizeInBytes => (is => 'ro', isa => 'Int'); |
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has StartedAt => (is => 'ro', isa => 'Str'); |
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has Status => (is => 'ro', isa => 'Str'); |
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has TrainingDataSourceId => (is => 'ro', isa => 'Str'); |
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has TrainingParameters => (is => 'ro', isa => 'Paws::MachineLearning::TrainingParameters'); |
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has _request_id => (is => 'ro', isa => 'Str'); |
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### main pod documentation begin ### |
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=head1 NAME |
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Paws::MachineLearning::GetMLModelOutput |
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=head1 ATTRIBUTES |
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=head2 ComputeTime => Int |
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The approximate CPU time in milliseconds that Amazon Machine Learning |
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spent processing the C<MLModel>, normalized and scaled on computation |
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resources. C<ComputeTime> is only available if the C<MLModel> is in the |
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C<COMPLETED> state. |
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=head2 CreatedAt => Str |
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The time that the C<MLModel> was created. The time is expressed in |
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epoch time. |
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=head2 CreatedByIamUser => Str |
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The AWS user account from which the C<MLModel> was created. The account |
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type can be either an AWS root account or an AWS Identity and Access |
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Management (IAM) user account. |
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=head2 EndpointInfo => L<Paws::MachineLearning::RealtimeEndpointInfo> |
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The current endpoint of the C<MLModel> |
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=head2 FinishedAt => Str |
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The epoch time when Amazon Machine Learning marked the C<MLModel> as |
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C<COMPLETED> or C<FAILED>. C<FinishedAt> is only available when the |
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C<MLModel> is in the C<COMPLETED> or C<FAILED> state. |
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=head2 InputDataLocationS3 => Str |
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The location of the data file or directory in Amazon Simple Storage |
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Service (Amazon S3). |
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=head2 LastUpdatedAt => Str |
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The time of the most recent edit to the C<MLModel>. The time is |
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expressed in epoch time. |
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=head2 LogUri => Str |
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A link to the file that contains logs of the C<CreateMLModel> |
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operation. |
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=head2 Message => Str |
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A description of the most recent details about accessing the |
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C<MLModel>. |
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=head2 MLModelId => Str |
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The MLModel ID, which is same as the C<MLModelId> in the request. |
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=head2 MLModelType => Str |
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Identifies the C<MLModel> category. The following are the available |
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types: |
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=over |
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=item * REGRESSION -- Produces a numeric result. For example, "What |
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price should a house be listed at?" |
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=item * BINARY -- Produces one of two possible results. For example, |
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"Is this an e-commerce website?" |
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=item * MULTICLASS -- Produces one of several possible results. For |
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example, "Is this a HIGH, LOW or MEDIUM risk trade?" |
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=back |
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Valid values are: C<"REGRESSION">, C<"BINARY">, C<"MULTICLASS"> |
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=head2 Name => Str |
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A user-supplied name or description of the C<MLModel>. |
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=head2 Recipe => Str |
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The recipe to use when training the C<MLModel>. The C<Recipe> provides |
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detailed information about the observation data to use during training, |
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and manipulations to perform on the observation data during training. |
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This parameter is provided as part of the verbose format. |
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=head2 Schema => Str |
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The schema used by all of the data files referenced by the |
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C<DataSource>. |
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This parameter is provided as part of the verbose format. |
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=head2 ScoreThreshold => Num |
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The scoring threshold is used in binary classification C<MLModel> |
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models. It marks the boundary between a positive prediction and a |
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negative prediction. |
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Output values greater than or equal to the threshold receive a positive |
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result from the MLModel, such as C<true>. Output values less than the |
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threshold receive a negative response from the MLModel, such as |
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C<false>. |
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=head2 ScoreThresholdLastUpdatedAt => Str |
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The time of the most recent edit to the C<ScoreThreshold>. The time is |
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expressed in epoch time. |
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=head2 SizeInBytes => Int |
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=head2 StartedAt => Str |
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The epoch time when Amazon Machine Learning marked the C<MLModel> as |
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C<INPROGRESS>. C<StartedAt> isn't available if the C<MLModel> is in the |
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C<PENDING> state. |
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=head2 Status => Str |
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The current status of the C<MLModel>. This element can have one of the |
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following values: |
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=over |
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=item * C<PENDING> - Amazon Machine Learning (Amazon ML) submitted a |
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request to describe a C<MLModel>. |
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=item * C<INPROGRESS> - The request is processing. |
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=item * C<FAILED> - The request did not run to completion. The ML model |
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isn't usable. |
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=item * C<COMPLETED> - The request completed successfully. |
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=item * C<DELETED> - The C<MLModel> is marked as deleted. It isn't |
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usable. |
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=back |
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Valid values are: C<"PENDING">, C<"INPROGRESS">, C<"FAILED">, C<"COMPLETED">, C<"DELETED"> |
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=head2 TrainingDataSourceId => Str |
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The ID of the training C<DataSource>. |
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=head2 TrainingParameters => L<Paws::MachineLearning::TrainingParameters> |
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A list of the training parameters in the C<MLModel>. The list is |
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implemented as a map of key-value pairs. |
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The following is the current set of training parameters: |
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=over |
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=item * |
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C<sgd.maxMLModelSizeInBytes> - The maximum allowed size of the model. |
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Depending on the input data, the size of the model might affect its |
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performance. |
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The value is an integer that ranges from C<100000> to C<2147483648>. |
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The default value is C<33554432>. |
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=item * |
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C<sgd.maxPasses> - The number of times that the training process |
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traverses the observations to build the C<MLModel>. The value is an |
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integer that ranges from C<1> to C<10000>. The default value is C<10>. |
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=item * |
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C<sgd.shuffleType> - Whether Amazon ML shuffles the training data. |
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Shuffling data improves a model's ability to find the optimal solution |
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for a variety of data types. The valid values are C<auto> and C<none>. |
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The default value is C<none>. We strongly recommend that you shuffle |
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your data. |
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=item * |
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C<sgd.l1RegularizationAmount> - The coefficient regularization L1 norm. |
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It controls overfitting the data by penalizing large coefficients. This |
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tends to drive coefficients to zero, resulting in a sparse feature set. |
237
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If you use this parameter, start by specifying a small value, such as |
238
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|
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C<1.0E-08>. |
239
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|
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|
240
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The value is a double that ranges from C<0> to C<MAX_DOUBLE>. The |
241
|
|
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|
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default is to not use L1 normalization. This parameter can't be used |
242
|
|
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|
|
|
|
when C<L2> is specified. Use this parameter sparingly. |
243
|
|
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|
|
|
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|
244
|
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|
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=item * |
245
|
|
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|
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|
246
|
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|
C<sgd.l2RegularizationAmount> - The coefficient regularization L2 norm. |
247
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|
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|
It controls overfitting the data by penalizing large coefficients. This |
248
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|
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tends to drive coefficients to small, nonzero values. If you use this |
249
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|
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|
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|
|
parameter, start by specifying a small value, such as C<1.0E-08>. |
250
|
|
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|
|
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|
251
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|
The value is a double that ranges from C<0> to C<MAX_DOUBLE>. The |
252
|
|
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|
|
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default is to not use L2 normalization. This parameter can't be used |
253
|
|
|
|
|
|
|
when C<L1> is specified. Use this parameter sparingly. |
254
|
|
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|
|
|
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|
255
|
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|
=back |
256
|
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|
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|
257
|
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|
258
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|
259
|
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|
=head2 _request_id => Str |
260
|
|
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|
|
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|
261
|
|
|
|
|
|
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|
262
|
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=cut |
263
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|
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|
264
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1; |