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* Add a subclassed Model's attribute-assigned variables to Model.weights et alGravatar Allen Lavoie2018-05-30
| | | | | | | | | | Makes the Variable.trainable property public, which is sensible if we're discouraging use of the global collection (currently eager execution is using ResourceVariable._trainable in a bunch of places anyway). I'm leaving it read-only for now, since we should toggle in and out of the global collection when it changes. Same change for checkpointable data structures with respect to gathering extra variables. They'll behave like subclassed Models. I think this makes more sense than trying to have a distinction between "variables" and "weights". It's also more sensible than collecting everything that would get checkpointed, since that will include Optimizer slot variables and metrics. Collecting those is generally pointless, and accidentally adding them to gradient tapes would be horribly confusing. PiperOrigin-RevId: 198656079
* Merge changes from github.Gravatar Yifei Feng2018-05-24
| | | | | | | Revert #18413. Too many internal test failures due to the name scope change caused by this change. Revert #18192. Cannot use re2::StringPiece internally. Need alternative for set call. Will pull and clean this up in a separate change. PiperOrigin-RevId: 197991247
* Makes tf.Variable return correct initialized_value and initial_value for ↵Gravatar A. Unique TensorFlower2017-08-23
| | | | | | | | objects created from VariableDef protos. Previously self._initial_value wasn't set in such cases which causes accessing var.initial_value to fail for variables in the imported meta graphs. PiperOrigin-RevId: 166252647
* Metagraph round-tripping for resource variables.Gravatar Alexandre Passos2017-02-03
| | | | Change: 146519414
* Uses 64-bit integers for storing variable dimensions in SaveSliceInfoDef.Gravatar A. Unique TensorFlower2016-11-16
| | | | | 32-bit integers are not enough for representing large scale variables with more than ~2 billion elements. The change is backward compatible as the proto serialization of int32s is the same as int64s. Change: 139393418
* Parse tf.Example using arena allocation. Dense string benchmark shows 10-20% ↵Gravatar A. Unique TensorFlower2016-07-06
| | | | | | speedup. Change: 126726018
* Enables java_multiple_files for all tf protos, and sets theGravatar A. Unique TensorFlower2016-02-09
| | | | | | | | | | | outer class name consistently to <FileName>Protos. Also specifies the java namespace as org.tensorflow.*. This enables compiling tf protos with nano proto for Android (which currently does not work because of file/message name clashes) and follows the same convention for proto3 as used by the API platform. Change: 114279703
* Added export_meta_graph() and import_meta_graph() forGravatar A. Unique TensorFlower2016-02-06
serializing/de-serializing the graph and other Python objects necessary restarting training, running eval, or running inference into a MetaGraphDef protocol buffer. MetaGraphDef contains the following: - MetaInfoDef: For storing version and other meta data associated with the meta graph. - GraphDef: The Graph. - SaverDef: The Saver. - CollectionDef * Int64List * FloatList * BytesList * NodeList * AnyList These are evolving APIs and subject to change. Change: 114026857
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