Model metadata for image classification.
The train budget of creating this model, expressed in milli
node hours i.e. 1,000 value in this field means 1 node hour.
The actual train_cost
will be equal or less than this
value. If further model training ceases to provide any
improvements, it will stop without using full budget and the
stop_reason will be MODEL_CONVERGED
. Note, node_hour =
actual_hour * number_of_nodes_invovled. For model type
cloud
\ (default), the train budget must be between 8,000
and 800,000 milli node hours, inclusive. The default value is
192, 000 which represents one day in wall time. For model type
mobile-low-latency-1
, mobile-versatile-1
, mobile-
high-accuracy-1
, mobile-core-ml-low-latency-1
, mobile-
core-ml-versatile-1
, mobile-core-ml-high-accuracy-1
, the
train budget must be between 1,000 and 100,000 milli node
hours, inclusive. The default value is 24, 000 which
represents one day in wall time.
Output only. The reason that this create model operation
stopped, e.g. BUDGET_REACHED
, MODEL_CONVERGED
.
Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.