|Package Slug|| |
In TensorFlow Lite, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative
|Affected Versions|| |
All versions before 1.15.4, all versions starting from 2.0.0 before 2.0.3, all versions starting from 2.1.0 before 2.1.2, all versions starting from 2.2.0 before 2.2.1, all versions starting from 2.3.0 before 2.3.1
Upgrade to versions 2.1.2, 2.2.1, 2.3.1 or above.
|Last Modified|| |