proto_docs/google/cloud/automl/v1beta1/io.rb in google-cloud-automl-v1beta1-0.1.0 vs proto_docs/google/cloud/automl/v1beta1/io.rb in google-cloud-automl-v1beta1-0.1.1

- old
+ new

@@ -23,11 +23,11 @@ module V1beta1 # 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 - # {Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} + # {::Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source 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 @@ -290,13 +290,13 @@ # TEST,"Thank you for this product.",4 # VALIDATE,gs://folder/content.txt,2 # # * For Tables: # Either - # {Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} or + # {::Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} or # - # {Google::Cloud::AutoML::V1beta1::InputConfig#bigquery_source bigquery_source} + # {::Google::Cloud::AutoML::V1beta1::InputConfig#bigquery_source bigquery_source} # can be used. All inputs is concatenated into a single # # [primary_table][google.cloud.automl.v1beta1.TablesDatasetMetadata.primary_table_name] # For gcs_source: # CSV file(s), where the first row of the first file is the header, @@ -377,47 +377,47 @@ # 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. # @!attribute [rw] gcs_source - # @return [Google::Cloud::AutoML::V1beta1::GcsSource] + # @return [::Google::Cloud::AutoML::V1beta1::GcsSource] # The Google Cloud Storage location for the input content. # In ImportData, the gcs_source points to a csv with structure described in # the comment. # @!attribute [rw] bigquery_source - # @return [Google::Cloud::AutoML::V1beta1::BigQuerySource] + # @return [::Google::Cloud::AutoML::V1beta1::BigQuerySource] # The BigQuery location for the input content. # @!attribute [rw] params - # @return [Google::Protobuf::Map{String => String}] + # @return [::Google::Protobuf::Map{::String => ::String}] # Additional domain-specific parameters describing the semantic of the # imported data, any string must be up to 25000 # characters long. # # * For Tables: # `schema_inference_version` - (integer) Required. The version of the # algorithm that should be used for the initial inference of the # schema (columns' DataTypes) of the table the data is being imported # into. Allowed values: "1". class InputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods # @!attribute [rw] key - # @return [String] + # @return [::String] # @!attribute [rw] value - # @return [String] + # @return [::String] class ParamsEntry - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end end # Input configuration for BatchPredict Action. # # The format of input depends on the ML problem of the model used for # prediction. As input source the - # {Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} + # {::Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} # is expected, unless specified otherwise. # # The formats are represented in EBNF with commas being literal and with # non-terminal symbols defined near the end of this comment. The formats # are: @@ -550,24 +550,24 @@ # } # } # # * For Tables: # Either - # {Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} or + # {::Google::Cloud::AutoML::V1beta1::InputConfig#gcs_source gcs_source} or # - # {Google::Cloud::AutoML::V1beta1::InputConfig#bigquery_source bigquery_source}. + # {::Google::Cloud::AutoML::V1beta1::InputConfig#bigquery_source bigquery_source}. # GCS case: # CSV file(s), each by itself 10GB or smaller and total size must be # 100GB or smaller, where first file must have a header containing # column names. If the first row of a subsequent file is the same as # the header, then it is also treated as a header. All other rows # contain values for the corresponding columns. # The column names must contain the model's # # [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} # (order doesn't matter). The columns corresponding to the model's # input feature column specs must contain values compatible with the # column spec's data types. Prediction on all the rows, i.e. the CSV # lines, will be attempted. For FORECASTING # @@ -587,11 +587,11 @@ # table must be 100GB or smaller. # The column names must contain the model's # # [input_feature_column_specs'][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} # (order doesn't matter). The columns corresponding to the model's # input feature column specs must contain values compatible with the # column spec's data types. Prediction on all the rows of the table # will be attempted. For FORECASTING # @@ -622,30 +622,30 @@ # percent of CSV rows cannot be processed then the operation fails and # prediction does not happen. Regardless of overall success or failure the # per-row failures, up to a certain count cap, will be listed in # Operation.metadata.partial_failures. # @!attribute [rw] gcs_source - # @return [Google::Cloud::AutoML::V1beta1::GcsSource] + # @return [::Google::Cloud::AutoML::V1beta1::GcsSource] # The Google Cloud Storage location for the input content. # @!attribute [rw] bigquery_source - # @return [Google::Cloud::AutoML::V1beta1::BigQuerySource] + # @return [::Google::Cloud::AutoML::V1beta1::BigQuerySource] # The BigQuery location for the input content. class BatchPredictInputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end - # Input configuration of a {Google::Cloud::AutoML::V1beta1::Document Document}. + # Input configuration of a {::Google::Cloud::AutoML::V1beta1::Document Document}. # @!attribute [rw] gcs_source - # @return [Google::Cloud::AutoML::V1beta1::GcsSource] + # @return [::Google::Cloud::AutoML::V1beta1::GcsSource] # The Google Cloud Storage location of the document file. Only a single path # should be given. # Max supported size: 512MB. # Supported extensions: .PDF. class DocumentInputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # * For Translation: # CSV file `translation.csv`, with each line in format: # ML_USE,GCS_FILE_PATH @@ -657,18 +657,18 @@ # * For Tables: # Output depends on whether the dataset was imported from GCS or # BigQuery. # GCS case: # - # {Google::Cloud::AutoML::V1beta1::OutputConfig#gcs_destination gcs_destination} + # {::Google::Cloud::AutoML::V1beta1::OutputConfig#gcs_destination gcs_destination} # must be set. Exported are CSV file(s) `tables_1.csv`, # `tables_2.csv`,...,`tables_N.csv` with each having as header line # the table's column names, and all other lines contain values for # the header columns. # BigQuery case: # - # {Google::Cloud::AutoML::V1beta1::OutputConfig#bigquery_destination bigquery_destination} + # {::Google::Cloud::AutoML::V1beta1::OutputConfig#bigquery_destination bigquery_destination} # pointing to a BigQuery project must be set. In the given project a # new dataset will be created with name # # `export_data_<automl-dataset-display-name>_<timestamp-of-export-call>` # where <automl-dataset-display-name> will be made @@ -676,30 +676,30 @@ # 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. # @!attribute [rw] gcs_destination - # @return [Google::Cloud::AutoML::V1beta1::GcsDestination] + # @return [::Google::Cloud::AutoML::V1beta1::GcsDestination] # 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-<dataset-display-name>-<timestamp-of-export-call> where # timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export # output will be written into that directory. # @!attribute [rw] bigquery_destination - # @return [Google::Cloud::AutoML::V1beta1::BigQueryDestination] + # @return [::Google::Cloud::AutoML::V1beta1::BigQueryDestination] # The BigQuery location where the output is to be written to. class OutputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # Output configuration for BatchPredict Action. # # As destination the # - # {Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig#gcs_destination gcs_destination} + # {::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig#gcs_destination gcs_destination} # must be set unless specified otherwise for a domain. If gcs_destination is # set then in the given directory a new directory is created. Its name # will be # "prediction-<model-display-name>-<timestamp-of-prediction-call>", # where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. The contents @@ -885,47 +885,47 @@ # containing only `code` and `message`. # # * For Tables: # Output depends on whether # - # {Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig#gcs_destination gcs_destination} + # {::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig#gcs_destination gcs_destination} # or # - # {Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig#bigquery_destination bigquery_destination} + # {::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig#bigquery_destination bigquery_destination} # is set (either is allowed). # GCS case: # In the created directory files `tables_1.csv`, `tables_2.csv`,..., # `tables_N.csv` will be created, where N may be 1, and depends on # the total number of the successfully predicted rows. # For all CLASSIFICATION # # [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: # Each .csv file will contain a header, listing all columns' # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} # given on input followed by M target column names in the format of # - # "<{Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} + # "<{::Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>_<target + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>_<target # value>_score" where M is the number of distinct target values, # i.e. number of distinct values in the target column of the table # used to train the model. Subsequent lines will contain the # respective values of successfully predicted rows, with the last, # i.e. the target, columns having the corresponding prediction - # {Google::Cloud::AutoML::V1beta1::TablesAnnotation#score scores}. + # {::Google::Cloud::AutoML::V1beta1::TablesAnnotation#score scores}. # For REGRESSION and FORECASTING # # [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]: # Each .csv file will contain a header, listing all columns' # [display_name-s][google.cloud.automl.v1beta1.display_name] given # on input followed by the predicted target column with name in the # format of # - # "predicted_<{Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} + # "predicted_<{::Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>" + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>" # Subsequent lines will contain the respective values of # successfully predicted rows, with the last, i.e. the target, # column having the predicted target value. # If prediction for any rows failed, then an additional # `errors_1.csv`, `errors_2.csv`,..., `errors_N.csv` will be @@ -937,79 +937,79 @@ # //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) # represented as a JSON string, and containing only `code` and # `message`. # BigQuery case: # - # {Google::Cloud::AutoML::V1beta1::OutputConfig#bigquery_destination bigquery_destination} + # {::Google::Cloud::AutoML::V1beta1::OutputConfig#bigquery_destination bigquery_destination} # pointing to a BigQuery project must be set. In the given project a # new dataset will be created with name # `prediction_<model-display-name>_<timestamp-of-prediction-call>` # where <model-display-name> 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 the dataset # two tables will be created, `predictions`, and `errors`. # The `predictions` table's column names will be the input columns' # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name-s} # followed by the target column with name in the format of # - # "predicted_<{Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} + # "predicted_<{::Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>" + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>" # The input feature columns will contain the respective values of # successfully predicted rows, with the target column having an # ARRAY of # - # {Google::Cloud::AutoML::V1beta1::AnnotationPayload AnnotationPayloads}, + # {::Google::Cloud::AutoML::V1beta1::AnnotationPayload AnnotationPayloads}, # represented as STRUCT-s, containing - # {Google::Cloud::AutoML::V1beta1::TablesAnnotation TablesAnnotation}. + # {::Google::Cloud::AutoML::V1beta1::TablesAnnotation TablesAnnotation}. # The `errors` table contains rows for which the prediction has # failed, it has analogous input columns while the target column name # is in the format of # - # "errors_<{Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} + # "errors_<{::Google::Cloud::AutoML::V1beta1::TablesModelMetadata#target_column_spec target_column_specs} # - # {Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>", + # {::Google::Cloud::AutoML::V1beta1::ColumnSpec#display_name display_name}>", # and as a value has # # [`google.rpc.Status`](https: # //github.com/googleapis/googleapis/blob/master/google/rpc/status.proto) # represented as a STRUCT, and containing only `code` and `message`. # @!attribute [rw] gcs_destination - # @return [Google::Cloud::AutoML::V1beta1::GcsDestination] + # @return [::Google::Cloud::AutoML::V1beta1::GcsDestination] # The Google Cloud Storage location of the directory where the output is to # be written to. # @!attribute [rw] bigquery_destination - # @return [Google::Cloud::AutoML::V1beta1::BigQueryDestination] + # @return [::Google::Cloud::AutoML::V1beta1::BigQueryDestination] # The BigQuery location where the output is to be written to. class BatchPredictOutputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # Output configuration for ModelExport Action. # @!attribute [rw] gcs_destination - # @return [Google::Cloud::AutoML::V1beta1::GcsDestination] + # @return [::Google::Cloud::AutoML::V1beta1::GcsDestination] # The Google Cloud Storage location where the model is to be written to. # This location may only be set for the following model formats: # "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml". # # Under the directory given as the destination a new one with name # "model-export-<model-display-name>-<timestamp-of-export-call>", # where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, # will be created. Inside the model and any of its supporting files # will be written. # @!attribute [rw] gcr_destination - # @return [Google::Cloud::AutoML::V1beta1::GcrDestination] + # @return [::Google::Cloud::AutoML::V1beta1::GcrDestination] # The GCR location where model image is to be pushed to. This location # may only be set for the following model formats: # "docker". # # The model image will be created under the given URI. # @!attribute [rw] model_format - # @return [String] + # @return [::String] # The format in which the model must be exported. The available, and default, # formats depend on the problem and model type (if given problem and type # combination doesn't have a format listed, it means its models are not # exportable): # @@ -1036,119 +1036,119 @@ # # quickstart](https: # //cloud.google.com/vision/automl/docs/containers-gcs-quickstart) # * core_ml - Used for iOS mobile devices. # @!attribute [rw] params - # @return [Google::Protobuf::Map{String => String}] + # @return [::Google::Protobuf::Map{::String => ::String}] # Additional model-type and format specific parameters describing the # requirements for the to be exported model files, any string must be up to # 25000 characters long. # # * For `docker` format: # `cpu_architecture` - (string) "x86_64" (default). # `gpu_architecture` - (string) "none" (default), "nvidia". class ModelExportOutputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods # @!attribute [rw] key - # @return [String] + # @return [::String] # @!attribute [rw] value - # @return [String] + # @return [::String] class ParamsEntry - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end end # Output configuration for ExportEvaluatedExamples Action. Note that this call # is available only for 30 days since the moment the model was evaluated. # The output depends on the domain, as follows (note that only examples from # the TEST set are exported): # # * For Tables: # - # {Google::Cloud::AutoML::V1beta1::OutputConfig#bigquery_destination bigquery_destination} + # {::Google::Cloud::AutoML::V1beta1::OutputConfig#bigquery_destination bigquery_destination} # pointing to a BigQuery project must be set. In the given project a # new dataset will be created with name # # `export_evaluated_examples_<model-display-name>_<timestamp-of-export-call>` # where <model-display-name> 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 the dataset an `evaluated_examples` table will be # created. It will have all the same columns as the # - # {Google::Cloud::AutoML::V1beta1::TablesDatasetMetadata#primary_table_spec_id primary_table} + # {::Google::Cloud::AutoML::V1beta1::TablesDatasetMetadata#primary_table_spec_id primary_table} # of the - # {Google::Cloud::AutoML::V1beta1::Model#dataset_id dataset} from which + # {::Google::Cloud::AutoML::V1beta1::Model#dataset_id dataset} from which # the model was created, as they were at the moment of model's # evaluation (this includes the target column with its ground # truth), followed by a column called "predicted_<target_column>". That # last column will contain the model's prediction result for each # respective row, given as ARRAY of - # {Google::Cloud::AutoML::V1beta1::AnnotationPayload AnnotationPayloads}, + # {::Google::Cloud::AutoML::V1beta1::AnnotationPayload AnnotationPayloads}, # represented as STRUCT-s, containing - # {Google::Cloud::AutoML::V1beta1::TablesAnnotation TablesAnnotation}. + # {::Google::Cloud::AutoML::V1beta1::TablesAnnotation TablesAnnotation}. # @!attribute [rw] bigquery_destination - # @return [Google::Cloud::AutoML::V1beta1::BigQueryDestination] + # @return [::Google::Cloud::AutoML::V1beta1::BigQueryDestination] # The BigQuery location where the output is to be written to. class ExportEvaluatedExamplesOutputConfig - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # The Google Cloud Storage location for the input content. # @!attribute [rw] input_uris - # @return [Array<String>] + # @return [::Array<::String>] # Required. Google Cloud Storage URIs to input files, up to 2000 characters # long. Accepted forms: # * Full object path, e.g. gs://bucket/directory/object.csv class GcsSource - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # The BigQuery location for the input content. # @!attribute [rw] input_uri - # @return [String] + # @return [::String] # Required. BigQuery URI to a table, up to 2000 characters long. # Accepted forms: # * BigQuery path e.g. bq://projectId.bqDatasetId.bqTableId class BigQuerySource - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # The Google Cloud Storage location where the output is to be written to. # @!attribute [rw] output_uri_prefix - # @return [String] + # @return [::String] # Required. Google Cloud Storage URI to output directory, up to 2000 # characters long. # Accepted forms: # * Prefix path: gs://bucket/directory # The requesting user must have write permission to the bucket. # The directory is created if it doesn't exist. class GcsDestination - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # The BigQuery location for the output content. # @!attribute [rw] output_uri - # @return [String] + # @return [::String] # Required. BigQuery URI to a project, up to 2000 characters long. # Accepted forms: # * BigQuery path e.g. bq://projectId class BigQueryDestination - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end # The GCR location where the image must be pushed to. # @!attribute [rw] output_uri - # @return [String] + # @return [::String] # Required. Google Contained Registry URI of the new image, up to 2000 # characters long. See # # https: # //cloud.google.com/container-registry/do @@ -1157,11 +1157,11 @@ # * [HOSTNAME]/[PROJECT-ID]/[IMAGE] # * [HOSTNAME]/[PROJECT-ID]/[IMAGE]:[TAG] # # The requesting user must have permission to push images the project. class GcrDestination - include Google::Protobuf::MessageExts - extend Google::Protobuf::MessageExts::ClassMethods + include ::Google::Protobuf::MessageExts + extend ::Google::Protobuf::MessageExts::ClassMethods end end end end end