Class TensorboardServiceClient (1.23.0)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_batch_create_tensorboard_runs():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    requests = aiplatform_v1.CreateTensorboardRunRequest()
    requests.parent = "parent_value"
    requests.tensorboard_run.display_name = "display_name_value"
    requests.tensorboard_run_id = "tensorboard_run_id_value"

    request = aiplatform_v1.BatchCreateTensorboardRunsRequest(
        parent="parent_value",
        requests=requests,
    )

    # Make the request
    response = client.batch_create_tensorboard_runs(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_batch_create_tensorboard_time_series():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    requests = aiplatform_v1.CreateTensorboardTimeSeriesRequest()
    requests.parent = "parent_value"
    requests.tensorboard_time_series.display_name = "display_name_value"
    requests.tensorboard_time_series.value_type = "BLOB_SEQUENCE"

    request = aiplatform_v1.BatchCreateTensorboardTimeSeriesRequest(
        parent="parent_value",
        requests=requests,
    )

    # Make the request
    response = client.batch_create_tensorboard_time_series(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_batch_read_tensorboard_time_series_data():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.BatchReadTensorboardTimeSeriesDataRequest(
        tensorboard="tensorboard_value",
        time_series=['time_series_value1', 'time_series_value2'],
    )

    # Make the request
    response = client.batch_read_tensorboard_time_series_data(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_tensorboard():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    tensorboard = aiplatform_v1.Tensorboard()
    tensorboard.display_name = "display_name_value"

    request = aiplatform_v1.CreateTensorboardRequest(
        parent="parent_value",
        tensorboard=tensorboard,
    )

    # Make the request
    operation = client.create_tensorboard(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_tensorboard_experiment():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CreateTensorboardExperimentRequest(
        parent="parent_value",
        tensorboard_experiment_id="tensorboard_experiment_id_value",
    )

    # Make the request
    response = client.create_tensorboard_experiment(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_tensorboard_run():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    tensorboard_run = aiplatform_v1.TensorboardRun()
    tensorboard_run.display_name = "display_name_value"

    request = aiplatform_v1.CreateTensorboardRunRequest(
        parent="parent_value",
        tensorboard_run=tensorboard_run,
        tensorboard_run_id="tensorboard_run_id_value",
    )

    # Make the request
    response = client.create_tensorboard_run(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_tensorboard_time_series():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    tensorboard_time_series = aiplatform_v1.TensorboardTimeSeries()
    tensorboard_time_series.display_name = "display_name_value"
    tensorboard_time_series.value_type = "BLOB_SEQUENCE"

    request = aiplatform_v1.CreateTensorboardTimeSeriesRequest(
        parent="parent_value",
        tensorboard_time_series=tensorboard_time_series,
    )

    # Make the request
    response = client.create_tensorboard_time_series(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_tensorboard():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteTensorboardRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_tensorboard(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_tensorboard_experiment():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteTensorboardExperimentRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_tensorboard_experiment(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_tensorboard_run():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteTensorboardRunRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_tensorboard_run(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_tensorboard_time_series():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteTensorboardTimeSeriesRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_tensorboard_time_series(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_export_tensorboard_time_series_data():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ExportTensorboardTimeSeriesDataRequest(
        tensorboard_time_series="tensorboard_time_series_value",
    )

    # Make the request
    page_result = client.export_tensorboard_time_series_data(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_tensorboard():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetTensorboardRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_tensorboard(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_tensorboard_experiment():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetTensorboardExperimentRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_tensorboard_experiment(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_tensorboard_run():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetTensorboardRunRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_tensorboard_run(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_tensorboard_time_series():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetTensorboardTimeSeriesRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_tensorboard_time_series(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_tensorboard_experiments():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListTensorboardExperimentsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_tensorboard_experiments(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_tensorboard_runs():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListTensorboardRunsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_tensorboard_runs(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_tensorboard_time_series():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListTensorboardTimeSeriesRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_tensorboard_time_series(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_tensorboards():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListTensorboardsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_tensorboards(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_read_tensorboard_blob_data():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ReadTensorboardBlobDataRequest(
        time_series="time_series_value",
    )

    # Make the request
    stream = client.read_tensorboard_blob_data(request=request)

    # Handle the response
    for response in stream:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_read_tensorboard_time_series_data():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ReadTensorboardTimeSeriesDataRequest(
        tensorboard_time_series="tensorboard_time_series_value",
    )

    # Make the request
    response = client.read_tensorboard_time_series_data(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_read_tensorboard_usage():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ReadTensorboardUsageRequest(
        tensorboard="tensorboard_value",
    )

    # Make the request
    response = client.read_tensorboard_usage(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_update_tensorboard():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    tensorboard = aiplatform_v1.Tensorboard()
    tensorboard.display_name = "display_name_value"

    request = aiplatform_v1.UpdateTensorboardRequest(
        tensorboard=tensorboard,
    )

    # Make the request
    operation = client.update_tensorboard(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_update_tensorboard_experiment():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.UpdateTensorboardExperimentRequest(
    )

    # Make the request
    response = client.update_tensorboard_experiment(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_update_tensorboard_run():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    tensorboard_run = aiplatform_v1.TensorboardRun()
    tensorboard_run.display_name = "display_name_value"

    request = aiplatform_v1.UpdateTensorboardRunRequest(
        tensorboard_run=tensorboard_run,
    )

    # Make the request
    response = client.update_tensorboard_run(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_update_tensorboard_time_series():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    tensorboard_time_series = aiplatform_v1.TensorboardTimeSeries()
    tensorboard_time_series.display_name = "display_name_value"
    tensorboard_time_series.value_type = "BLOB_SEQUENCE"

    request = aiplatform_v1.UpdateTensorboardTimeSeriesRequest(
        tensorboard_time_series=tensorboard_time_series,
    )

    # Make the request
    response = client.update_tensorboard_time_series(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_write_tensorboard_experiment_data():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    write_run_data_requests = aiplatform_v1.WriteTensorboardRunDataRequest()
    write_run_data_requests.tensorboard_run = "tensorboard_run_value"
    write_run_data_requests.time_series_data.tensorboard_time_series_id = "tensorboard_time_series_id_value"
    write_run_data_requests.time_series_data.value_type = "BLOB_SEQUENCE"

    request = aiplatform_v1.WriteTensorboardExperimentDataRequest(
        tensorboard_experiment="tensorboard_experiment_value",
        write_run_data_requests=write_run_data_requests,
    )

    # Make the request
    response = client.write_tensorboard_experiment_data(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_write_tensorboard_run_data():
    # Create a client
    client = aiplatform_v1.TensorboardServiceClient()

    # Initialize request argument(s)
    time_series_data = aiplatform_v1.TimeSeriesData()
    time_series_data.tensorboard_time_series_id = "tensorboard_time_series_id_value"
    time_series_data.value_type = "BLOB_SEQUENCE"

    request = aiplatform_v1.WriteTensorboardRunDataRequest(
        tensorboard_run="tensorboard_run_value",
        time_series_data=time_series_data,
    )

    # Make the request
    response = client.write_tensorboard_run_data(request=request)

    # Handle the response
    print(response)