Heap OOB read in shape inference for `QuantizeV2`

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start of a heap buffer. The code allows axis to be an optional argument (s would contain an error::NOT_FOUND error code). Otherwise, it assumes that axis is a valid index into the dimensions of the input tensor. If axis is less than -1 then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.