def main(argv=None):
"""Create and train the CLV model on AutoML Tables."""
argv = sys.argv if argv is None else argv
args = create_parser().parse_args(args=argv[1:])
# create and configure client
keyfile_name = args.key_file
client = AutoMlClient.from_service_account_file(keyfile_name)
# create and deploy model
model_name = create_automl_model(client,
args.project_id,
args.location,
args.bq_dataset,
args.bq_table,
args.automl_dataset,
args.automl_model,
args.training_budget)
# deploy model
deploy_model(client, model_name)
# get model evaluations
model_evaluation = get_model_evaluation(client, model_name)
# make predictions
prediction_client = PredictionServiceClient.from_service_account_file(
keyfile_name)
do_batch_prediction(prediction_client,
model_name,
args.batch_gcs_input,
args.batch_gcs_output)
def get_prediction(content, project_id, model_id):
prediction_client = PredictionServiceClient.from_service_account_file(
"AI_KEY.json")
name = 'projects/{}/locations/us-central1/models/{}'.format(
project_id, model_id)
payload = {'image': {'image_bytes': content}}
params = {}
request = prediction_client.predict(name, payload, params)
return request
def get_prediction(content, project_id, model_id):
#storage_client = storage.Client.from_service_account_json(r"C:\Users\dell laptop\AppData\Roaming\gcloud\chicago-hospitals-social-media-7892696dfd9c.json")
#credentials = service_account.Credentials.from_service_account_file("C:\\Users\\dell laptop\\AppData\\Roaming\\gcloud\\chicago-hospitals-social-media-7892696dfd9c.json")
#prediction_client = automl_v1beta1.PredictionServiceClient(credentials=credentials)
prediction_client = PredictionServiceClient.from_service_account_file("C:\\Users\\dell laptop\\AppData\\Roaming\\gcloud\\chicago-hospitals-social-media-7892696dfd9c.json")
name = 'projects/{}/locations/us-central1/models/{}'.format(project_id, model_id)
payload = {'text_snippet': {'content': content, 'mime_type': 'text/plain' }}
params = {}
request = prediction_client.predict(name, payload, params)
return request # waits till request is returned
def get_prediction(phrase):
# Create the client from the AutoML service account
client = PredictionServiceClient.from_service_account_file("./hackutd-1550944892104-1ba910d00c8f.json")
path = client.model_path("hackutd-1550944892104", "us-central1", "TCN6183341381162616853")
# Retrieve the prediction data
payload = {"text_snippet": {"content": phrase, "mime_type": "text/plain"}}
request = client.predict(path, payload)
# Extract the highest prediction result
result = request.payload[0]
data = (result.display_name, result.classification.score)
return data