Introduzione all'API sequenziale Keras su Vertex AI Platform recensioni
Caricamento in corso…
Nessun risultato trovato.

Google Cloud Skills Boost

Applica le tue competenze nella console Google Cloud

Introduzione all'API sequenziale Keras su Vertex AI Platform recensioni

13408 recensioni

Nurlan М. · Recensione inserita 5 mesi fa

Bikram S. · Recensione inserita 5 mesi fa

Miras C. · Recensione inserita 5 mesi fa

Keiven T. · Recensione inserita 5 mesi fa

Andrea C. · Recensione inserita 5 mesi fa

Damir M. · Recensione inserita 5 mesi fa

Kazushige O. · Recensione inserita 5 mesi fa

David Israel P. · Recensione inserita 5 mesi fa

Scott B. · Recensione inserita 5 mesi fa

Oscar R. · Recensione inserita 5 mesi fa

Benhur O. · Recensione inserita 5 mesi fa

Shankar M. · Recensione inserita 5 mesi fa

Amina Z. · Recensione inserita 5 mesi fa

Abhra D. · Recensione inserita 5 mesi fa

Abhilasa S. · Recensione inserita 5 mesi fa

Nils G. · Recensione inserita 5 mesi fa

File /opt/conda/lib/python3.10/site-packages/google/cloud/aiplatform/models.py:1827, in Endpoint._deploy_call(cls, api_client, endpoint_resource_name, model, endpoint_resource_traffic_split, network, deployed_model_display_name, traffic_percentage, traffic_split, machine_type, min_replica_count, max_replica_count, accelerator_type, accelerator_count, tpu_topology, service_account, explanation_spec, metadata, deploy_request_timeout, autoscaling_target_cpu_utilization, autoscaling_target_accelerator_duty_cycle, enable_access_logging, disable_container_logging, deployment_resource_pool) 1815 operation_future = api_client.deploy_model( 1816 endpoint=endpoint_resource_name, 1817 deployed_model=deployed_model, (...) 1820 timeout=deploy_request_timeout, 1821 ) 1823 _LOGGER.log_action_started_against_resource_with_lro( 1824 "Deploy", "model", cls, operation_future 1825 ) -> 1827 operation_future.result(timeout=None) File /opt/conda/lib/python3.10/site-packages/google/api_core/future/polling.py:261, in PollingFuture.result(self, timeout, retry, polling) 256 self._blocking_poll(timeout=timeout, retry=retry, polling=polling) 258 if self._exception is not None: 259 # pylint: disable=raising-bad-type 260 # Pylint doesn't recognize that this is valid in this case. --> 261 raise self._exception 263 return self._result FailedPrecondition: 400 Model server exited unexpectedly. Model server logs can be found at https://console.cloud.google.com/logs/viewer?project=667152570772&resource=aiplatform.googleapis.com%2FEndpoint&advancedFilter=resource.type%3D%22aiplatform.googleapis.com%2FEndpoint%22%0Aresource.labels.endpoint_id%3D%225927820128572932096%22%0Aresource.labels.location%3D%22us-central1%22.

Goziem M. · Recensione inserita 5 mesi fa

could be easier if there was more time since deploy part takes long

Mona H. · Recensione inserita 5 mesi fa

Islam A. · Recensione inserita 5 mesi fa

MACHINE_TYPE = "e2-standard-2" endpoint = uploaded_model.deploy( machine_type=MACHINE_TYPE, accelerator_type=None, accelerator_count=None, ) ne marche pas correctement

Timothé L. · Recensione inserita 5 mesi fa

Llorenç V. · Recensione inserita 5 mesi fa

Wonseuk H. · Recensione inserita 5 mesi fa

Pablo G. · Recensione inserita 5 mesi fa

Deploy really slow

Francesca A. · Recensione inserita 5 mesi fa

Anísio P. · Recensione inserita 5 mesi fa

Non garantiamo che le recensioni pubblicate provengano da consumatori che hanno acquistato o utilizzato i prodotti. Le recensioni non sono verificate da Google.