Receive info back about the earlier uploaded pretrained model (via uploadPretrainedModel) input/output tensors. If you want to deploy a pretrained model from the API, see startDeployPretrainedModelJob.
Optional error description (set if 'success' was false)
specificDeviceSelected*boolean
Whether a specific device was selected for performance profiling
availableModelTypes*array of KerasModelTypeEnum (enum)
The types of model that are available
itemsKerasModelTypeEnum (enum)
int8float32akidarequiresRetrain
modelobject
fileName*string
profileInfoobject
float32ProfileModelInfo (object)
device*string
tfliteFileSizeBytes*integer
isSupportedOnMcu*boolean
memoryobject
tfliteobject
ram*integer
rom*integer
arenaSize*integer
eonobject
ram*integer
rom*integer
eonRamOptimizedobject
ram*integer
rom*integer
timePerInferenceMsinteger
mcuSupportErrorstring
int8ProfileModelInfo (object)
device*string
tfliteFileSizeBytes*integer
isSupportedOnMcu*boolean
memoryobject
tfliteobject
ram*integer
rom*integer
arenaSize*integer
eonobject
ram*integer
rom*integer
eonRamOptimizedobject
ram*integer
rom*integer
timePerInferenceMsinteger
mcuSupportErrorstring
table*ProfileModelTable (object)
Performance for a range of device types. Note that MPU is referred to as CPU in Studio, as MPU and CPU are treated equivalent for performance estimation.