Required. The name of the dataset to show in the interface. The name can be up to 32 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscores (_), and ASCII digits 0-9.

Output only. The number of examples in the dataset.

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

DeleteDatasetRequest

Request message for AutoMl.DeleteDataset.

DeleteOperationMetadata

Details of operations that perform deletes of any entities.

DeleteOperationRequest

API documentation for automl_v1.types.DeleteOperationRequest class.

ExamplePayload

Example data used for training or prediction.

Example text.

ExportDataRequest

Request message for AutoMl.ExportData.

Required. The desired output location.

FieldMask

API documentation for automl_v1.types.FieldMask class.

GcsDestination

The Google Cloud Storage location where the output is to be written to.

GcsSource

The Google Cloud Storage location for the input content.

GetModelEvaluationRequest

Request message for AutoMl.GetModelEvaluation.

GetOperationRequest

API documentation for automl_v1.types.GetOperationRequest class.

ImportDataRequest

Request message for AutoMl.ImportData.

Required. The desired input location and its domain specific semantics, if any.

InputConfig

Input configuration for ImportData Action.

The format of input depends on dataset_metadata the Dataset into which the import is happening has. As input source the [gcs_source][google.cloud.automl.v1beta1.InputConfig.gcs_source] is expected, unless specified otherwise. Additionally any input .CSV file by itself must be 100MB or smaller, unless specified otherwise. If an "example" file (that is, image, video etc.) with identical content (even if it had different GCS_FILE_PATH) is mentioned multiple times, then its label, bounding boxes etc. are appended. The same file should be always provided with the same ML_USE and GCS_FILE_PATH, if it is not, then these values are nondeterministically selected from the given ones.

Errors: If any of the provided CSV files can't be parsed or if more than certain percent of CSV rows cannot be processed then the operation fails and nothing is imported. Regardless of overall success or failure the per-row failures, up to a certain count cap, is listed in Operation.metadata.partial_failures.

The Google Cloud Storage location for the input content. In ImportData, the gcs_source points to a csv with structure described in the comment.

ListDatasetsRequest

Request message for AutoMl.ListDatasets.

An expression for filtering the results of the request. - dataset_metadata - for existence of the case (e.g. image_classification_dataset_metadata:*). Some examples of using the filter are: - translation_dataset_metadata:* --> The dataset has translation_dataset_metadata.

A token identifying a page of results for the server to return Typically obtained via [ListDatasetsResponse.next_page_token ][google.cloud.automl.v1.ListDatasetsResponse.next_page_toke n] of the previous [AutoMl.ListDatasets][google.cloud.automl.v 1.AutoMl.ListDatasets] call.

ListDatasetsResponse

Response message for AutoMl.ListDatasets.

A token to retrieve next page of results. Pass to [ListDataset sRequest.page_token][google.cloud.automl.v1.ListDatasetsReque st.page_token] to obtain that page.

ListModelEvaluationsRequest

Request message for AutoMl.ListModelEvaluations.

An expression for filtering the results of the request. - annotation_spec_id - for =, != or existence. See example below for the last. Some examples of using the filter are:

annotation_spec_id!=4 --> The model evaluation was done for annotation spec with ID different than 4. - NOT annotation_spec_id:* --> The model evaluation was done for aggregate of all annotation specs.

A token identifying a page of results for the server to return. Typically obtained via [ListModelEvaluationsResponse.n ext_page_token][google.cloud.automl.v1.ListModelEvaluationsR esponse.next_page_token] of the previous [AutoMl.ListModelEv aluations][google.cloud.automl.v1.AutoMl.ListModelEvaluations] call.

ListModelEvaluationsResponse

Response message for AutoMl.ListModelEvaluations.

A token to retrieve next page of results. Pass to the [ListMod elEvaluationsRequest.page_token][google.cloud.automl.v1.ListM odelEvaluationsRequest.page_token] field of a new [AutoMl.Lis tModelEvaluations][google.cloud.automl.v1.AutoMl.ListModelEval uations] request to obtain that page.

ListModelsRequest

Request message for AutoMl.ListModels.

An expression for filtering the results of the request. - model_metadata - for existence of the case (e.g. video_classification_model_metadata:*). - dataset_id

for = or !=. Some examples of using the filter are: - image_classification_model_metadata:* --> The model has image_classification_model_metadata. - dataset_id=5 --> The model was created from a dataset with ID 5.

A token identifying a page of results for the server to return Typically obtained via [ListModelsResponse.next_page_token][ google.cloud.automl.v1.ListModelsResponse.next_page_token] of the previous AutoMl.ListModels call.

ListModelsResponse

Response message for AutoMl.ListModels.

A token to retrieve next page of results. Pass to [ListModelsR equest.page_token][google.cloud.automl.v1.ListModelsRequest.p age_token] to obtain that page.

ListOperationsRequest

API documentation for automl_v1.types.ListOperationsRequest class.

ListOperationsResponse

API documentation for automl_v1.types.ListOperationsResponse class.

Model

API proto representing a trained machine learning model.

Metadata for translation models.

Required. The name of the model to show in the interface. The name can be up to 32 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscores (_), and ASCII digits 0-9. It must start with a letter.

Output only. Timestamp when the model training finished and can be used for prediction.

Output only. Deployment state of the model. A model can only serve prediction requests after it gets deployed.

ModelEvaluation

Evaluation results of a model.

Model evaluation metrics for translation.

Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation.

Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the [annotation_spec_id][google.cloud.automl.v1beta1.ModelE valuation.annotation_spec_id].

Operation

API documentation for automl_v1.types.Operation class.

OperationInfo

API documentation for automl_v1.types.OperationInfo class.

OperationMetadata

Metadata used across all long running operations returned by AutoML API.

Details of a Delete operation.

Output only. Progress of operation. Range: [0, 100]. Not used currently.

Output only. Time when the operation was created.

OutputConfig

For Translation: CSV file translation.csv, with each line in format: ML_USE,GCS_FILE_PATH GCS_FILE_PATH leads to a .TSV file which describes examples that have given ML_USE, using the following row format per line: TEXT_SNIPPET (in source language) \tTEXT_SNIPPET (in target language)

export_data_<automl-dataset-display-name>_<timestamp-of-export-call> where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores), and timestamp will be in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In that dataset a new table called primary_table will be created, and filled with precisely the same data as this obtained on import.

Attributes: destination: Required. The destination of the output. gcs_destination: The Google Cloud Storage location where the output is to be written to. For Image Object Detection, Text Extraction, Video Classification and Tables, in the given directory a new directory will be created with name: export_data-- where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory.