Class AutoMlClient (0.7.1)

Version 0.7.1

• 2.14.1 (latest)
• 2.14.0
• 2.13.5
• 2.12.0
• 2.11.4
• 2.10.1
• 2.9.0
• 2.8.3
• 2.7.3
• 2.6.0
• 2.5.2
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• 2.3.0
• 2.2.0
• 2.1.0
• 2.0.0
• 1.0.3
• 0.10.0
• 0.9.0
• 0.8.0
• 0.7.1
• 0.6.0
• 0.5.0
• 0.4.0

AutoMlClient(
    transport=None,
    channel=None,
    credentials=None,
    client_config=None,
    client_info=None,
    client_options=None,
)

AutoML Server API.

The resource names are assigned by the server. The server never reuses names that it has created after the resources with those names are deleted.

An ID of a resource is the last element of the item's resource name. For projects/{project_id}/locations/{location_id}/datasets/{dataset_id}, then the id for the item is {dataset_id}.

Currently the only supported location_id is "us-central1".

On any input that is documented to expect a string parameter in snake_case or kebab-case, either of those cases is accepted.

Methods

AutoMlClient

AutoMlClient(
    transport=None,
    channel=None,
    credentials=None,
    client_config=None,
    client_info=None,
    client_options=None,
)

Constructor.

Parameters

Name	Description
channel	grpc.Channel DEPRECATED. A Channel instance through which to make calls. This argument is mutually exclusive with credentials; providing both will raise an exception.
credentials	google.auth.credentials.Credentials The authorization credentials to attach to requests. These credentials identify this application to the service. If none are specified, the client will attempt to ascertain the credentials from the environment. This argument is mutually exclusive with providing a transport instance to transport; doing so will raise an exception.
client_config	dict DEPRECATED. A dictionary of call options for each method. If not specified, the default configuration is used.
client_info	google.api_core.gapic_v1.client_info.ClientInfo The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.
client_options	Union[dict, google.api_core.client_options.ClientOptions] Client options used to set user options on the client. API Endpoint should be set through client_options.

create_dataset

create_dataset(parent, dataset, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Creates a dataset.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

parent = client.location_path('[PROJECT]', '[LOCATION]')

TODO: Initialize dataset:

dataset = {}

response = client.create_dataset(parent, dataset)

def callback(operation_future): ... # Handle result. ... result = operation_future.result()

response.add_done_callback(callback)

Handle metadata.

metadata = response.metadata()

Parameters

Name	Description
parent	str The resource name of the project to create the dataset for.
dataset	Union[dict, Dataset] The dataset to create. If a dict is provided, it must be of the same form as the protobuf message Dataset
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

create_model

create_model(parent, model, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

parent = client.location_path('[PROJECT]', '[LOCATION]')

TODO: Initialize model:

model = {}

response = client.create_model(parent, model)

def callback(operation_future): ... # Handle result. ... result = operation_future.result()

response.add_done_callback(callback)

Handle metadata.

metadata = response.metadata()

Parameters

Name	Description
parent	str Resource name of the parent project where the model is being created.
model	Union[dict, Model] The model to create. If a dict is provided, it must be of the same form as the protobuf message Model
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

dataset_path

dataset_path(project, location, dataset)

Return a fully-qualified dataset string.

delete_dataset

delete_dataset(name, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Deletes a dataset and all of its contents. Returns empty response in the response field when it completes, and delete_details in the metadata field.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

response = client.delete_dataset(name)

def callback(operation_future): ... # Handle result. ... result = operation_future.result()

response.add_done_callback(callback)

Handle metadata.

metadata = response.metadata()

Parameters

Name	Description
name	str The resource name of the dataset to delete.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

delete_model

delete_model(name, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Deletes a model. Returns google.protobuf.Empty in the response field when it completes, and delete_details in the metadata field.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

response = client.delete_model(name)

def callback(operation_future): ... # Handle result. ... result = operation_future.result()

response.add_done_callback(callback)

Handle metadata.

metadata = response.metadata()

Parameters

Name	Description
name	str Resource name of the model being deleted.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

export_data

export_data(name, output_config, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Exports dataset's data to the provided output location. Returns an empty response in the response field when it completes.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

TODO: Initialize output_config:

output_config = {}

response = client.export_data(name, output_config)

def callback(operation_future): ... # Handle result. ... result = operation_future.result()

response.add_done_callback(callback)

Handle metadata.

metadata = response.metadata()

Parameters

Name	Description
name	str Required. The resource name of the dataset.
output_config	Union[dict, OutputConfig] Required. The desired output location. If a dict is provided, it must be of the same form as the protobuf message OutputConfig
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

from_service_account_file

from_service_account_file(filename, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
filename	str The path to the service account private key json file.

Returns

Type	Description
AutoMlClient	The constructed client.

from_service_account_json

from_service_account_json(filename, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
filename	str The path to the service account private key json file.

Returns

Type	Description
AutoMlClient	The constructed client.

get_dataset

get_dataset(name, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Gets a dataset.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

response = client.get_dataset(name)

Parameters

Name	Description
name	str The resource name of the dataset to retrieve.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

get_model

get_model(name, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Gets a model.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

response = client.get_model(name)

Parameters

Name	Description
name	str Resource name of the model.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

get_model_evaluation

get_model_evaluation(name, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Gets a model evaluation.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.model_evaluation_path('[PROJECT]', '[LOCATION]', '[MODEL]', '[MODEL_EVALUATION]')

response = client.get_model_evaluation(name)

Parameters

Name	Description
name	str Resource name for the model evaluation.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

import_data

import_data(name, input_config, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Imports data into a dataset.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

name = client.dataset_path('[PROJECT]', '[LOCATION]', '[DATASET]')

TODO: Initialize input_config:

input_config = {}

response = client.import_data(name, input_config)

def callback(operation_future): ... # Handle result. ... result = operation_future.result()

response.add_done_callback(callback)

Handle metadata.

metadata = response.metadata()

Parameters

Name	Description
name	str Required. Dataset name. Dataset must already exist. All imported annotations and examples will be added.
input_config	Union[dict, InputConfig] Required. The desired input location and its domain specific semantics, if any. If a dict is provided, it must be of the same form as the protobuf message InputConfig
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

list_datasets

list_datasets(parent, filter_=None, page_size=None, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Lists datasets in a project.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

parent = client.location_path('[PROJECT]', '[LOCATION]')

Iterate over all results

for element in client.list_datasets(parent): ... # process element ... pass

Alternatively:

Iterate over results one page at a time

for page in client.list_datasets(parent).pages: ... for element in page: ... # process element ... pass

Parameters

Name	Description
parent	str The resource name of the project from which to list datasets.
filter_	str 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.
page_size	int The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

list_model_evaluations

list_model_evaluations(parent, filter_, page_size=None, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Lists model evaluations.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

parent = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]')

TODO: Initialize filter_:

filter_ = ''

Iterate over all results

for element in client.list_model_evaluations(parent, filter_): ... # process element ... pass

Alternatively:

Iterate over results one page at a time

for page in client.list_model_evaluations(parent, filter_).pages: ... for element in page: ... # process element ... pass

Parameters

Name	Description
parent	str Resource name of the model to list the model evaluations for. If modelId is set as "-", this will list model evaluations from across all models of the parent location.
filter_	str 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.
page_size	int The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

list_models

list_models(parent, filter_=None, page_size=None, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Lists models.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

parent = client.location_path('[PROJECT]', '[LOCATION]')

Iterate over all results

for element in client.list_models(parent): ... # process element ... pass

Alternatively:

Iterate over results one page at a time

for page in client.list_models(parent).pages: ... for element in page: ... # process element ... pass

Parameters

Name	Description
parent	str Resource name of the project, from which to list the models.
filter_	str 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.
page_size	int The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page.
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

location_path

location_path(project, location)

Return a fully-qualified location string.

model_evaluation_path

model_evaluation_path(project, location, model, model_evaluation)

Return a fully-qualified model_evaluation string.

model_path

model_path(project, location, model)

Return a fully-qualified model string.

update_dataset

update_dataset(dataset, update_mask, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Updates a dataset.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

TODO: Initialize dataset:

dataset = {}

TODO: Initialize update_mask:

update_mask = {}

response = client.update_dataset(dataset, update_mask)

Parameters

Name	Description
dataset	Union[dict, Dataset] The dataset which replaces the resource on the server. If a dict is provided, it must be of the same form as the protobuf message Dataset
update_mask	Union[dict, FieldMask] Required. The update mask applies to the resource. If a dict is provided, it must be of the same form as the protobuf message FieldMask
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.

update_model

update_model(model, update_mask, retry=<_MethodDefault._DEFAULT_VALUE: <object object>>, timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>, metadata=None)

Updates a model.

.. rubric:: Example

from google.cloud import automl_v1

client = automl_v1.AutoMlClient()

TODO: Initialize model:

model = {}

TODO: Initialize update_mask:

update_mask = {}

response = client.update_model(model, update_mask)

Parameters

Name	Description
model	Union[dict, Model] The model which replaces the resource on the server. If a dict is provided, it must be of the same form as the protobuf message Model
update_mask	Union[dict, FieldMask] Required. The update mask applies to the resource. If a dict is provided, it must be of the same form as the protobuf message FieldMask
retry	Optional[google.api_core.retry.Retry] A retry object used to retry requests. If None is specified, requests will be retried using a default configuration.
timeout	Optional[float] The amount of time, in seconds, to wait for the request to complete. Note that if retry is specified, the timeout applies to each individual attempt.
metadata	Optional[Sequence[Tuple[str, str]]] Additional metadata that is provided to the method.

Exceptions

Type	Description
google.api_core.exceptions.GoogleAPICallError	If the request failed for any reason.
google.api_core.exceptions.RetryError	If the request failed due to a retryable error and retry attempts failed.
ValueError	If the parameters are invalid.