Exemplos de default_project em Python

Exemplo n.º 1

def launch_job(job_spec):
  """Launch job on ML Engine."""
  project_id = 'projects/{}'.format(cloud.default_project())
  credentials = GoogleCredentials.get_application_default()
  cloudml = discovery.build('ml', 'v1', credentials=credentials)
  request = cloudml.projects().jobs().create(body=job_spec, parent=project_id)
  request.execute()

Exemplo n.º 2

def launch_job(job_spec):
  """Launch job on ML Engine."""
  project_id = "projects/{}".format(
      text_encoder.native_to_unicode(cloud.default_project()))
  credentials = GoogleCredentials.get_application_default()
  cloudml = discovery.build("ml", "v1", credentials=credentials,
                            cache_discovery=False)
  request = cloudml.projects().jobs().create(body=job_spec, parent=project_id)
  request.execute()

Exemplo n.º 3

Arquivo: serving_utils.py Projeto: rekriz11/sockeye-recipes

 def _make_cloud_mlengine_request(examples):
   """Builds and sends requests to Cloud ML Engine."""
   api = discovery.build("ml", "v1", credentials=credentials)
   parent = "projects/%s/models/%s/versions/%s" % (cloud.default_project(),
                                                   model_name, version)
   input_data = {
       "instances": [{
           "input": {
               "b64": base64.b64encode(ex.SerializeToString())
           }
       } for ex in examples]
   }
   prediction = api.projects().predict(body=input_data, name=parent).execute()
   return prediction["predictions"]

Exemplo n.º 4

Arquivo: serving_utils.py Projeto: kltony/tensor2tensor

 def _make_cloud_mlengine_request(examples):
   """Builds and sends requests to Cloud ML Engine."""
   api = discovery.build("ml", "v1", credentials=credentials)
   parent = "projects/%s/models/%s/versions/%s" % (cloud.default_project(),
                                                   model_name, version)
   input_data = {
       "instances": [{
           "input": {
               "b64": base64.b64encode(ex.SerializeToString())
           }
       } for ex in examples]
   }
   prediction = api.projects().predict(body=input_data, name=parent).execute()
   return prediction["predictions"]