Use the Hydrate static function method to create the object from its dehydrated form. The dehydrated form consists of a hash containing the object's properties and values. The Hydrate and Dehydrate methods let you store the object state in memory and restore it later.
Representing an object as a hash is necessary for running ENVI analytics with the ENVI Task Engine and the ENVI Services Engine. Refer to the ENVI Task Engine and ENVI Services Engine topics in ENVI Help.
See the ENVIHydrate topic in ENVI Help if you are creating a general IDL routine that will restore multiple object types.
This method is part of ENVI Deep Learning, which requires a separate license and installation.
Sample data files are available on our ENVI Tutorials web page. Click the "Deep Learning" link in the ENVI Tutorial Data section to download a .zip file containing the data. Extract the contents to a local directory. The file TrainedModel.h5 is in the tornado directory.
e = ENVI(/HEADLESS)
ModelFile = 'C:\MyTutorialFiles\TrainedModel.h5'
Model = ENVITensorFlowModel(ModelFile)
dehydratedForm = Model.Dehydrate()
newModel = ENVITensorFlowModel.Hydrate(dehydratedForm)
Print, newModel, /IMPLIED_PRINT
Result = ENVITensorFlowModel.Hydrate(DehydratedForm, ERROR=value)
The result is a reference to a new object instance.
Required. A string value of TensorFlowModel indicating what object type the hash represents.
Required. A uniform resource locator (URL) identifying an ENVITensorFlowModel file. Example:
"url" : "/usr/local/harris/envi/mydata/TensorFlowModel.h5"
Set this keyword to a named variable that will contain any error message issued during execution of this routine. If no error occurs, the ERROR variable will be set to a null string (''). If an error occurs and the routine is a function, then the function result will be undefined.
When this keyword is not set and an error occurs, ENVI returns to the caller and execution halts. In this case, the error message is contained within !ERROR_STATE and can be caught using IDL's CATCH routine. See IDL Help for more information on !ERROR_STATE and CATCH.
See the Manage Errors topic in ENVI Help for more information on error handling.
Deep Learning 1.0