SaschaHeyer

metrics = {}
metrics["f1"] = 0.81
aiplatform.log_metrics(metrics)

SaschaHeyer

from sklearn.metrics import confusion_matrix

labels = ["ant", "bird", "cat"]
y_true = ["cat", "ant", "cat", "cat", "ant", "bird"]
y_pred = ["ant", "ant", "cat", "cat", "ant", "cat"]

classification_metrics = {
        "matrix": confusion_matrix(y_true, y_pred, labels=labels).tolist(),
        "labels": labels
        }

SaschaHeyer

metaparams = {}
metaparams["batch_size"] = 256
aiplatform.log_params(metaparams)

SaschaHeyer

aiplatform.start_run('run-1')

# log metrics
# log parameters
# log artifacts

aiplatform.end_run()

SaschaHeyer

pip install google-cloud-aiplatform

import google.cloud.aiplatform as aiplatform

SaschaHeyer

aiplatform.init(
       project='sascha-playground-doit',
       location='us-central1',
       experiment='experiment-sample'
    )

SaschaHeyer

DISPLAY_NAME  = "recommendation"
models = aiplatform.Model.list(filter=("display_name={}").format(DISPLAY_NAME))
  
if len(models) == 0:
  model_upload = aiplatform.Model.upload(
    display_name = DISPLAY_NAME 
  )
    
else:
  parent_model = models[0].resource_name

SaschaHeyer

aiplatform.Model.upload(
    version_aliases=["experimental"]
)

SaschaHeyer

aiplatform.Model.upload(
    is_default_version=False,
)

SaschaHeyer

aiplatform.Model.upload(
    version_description="This is a test version description"
)