- Update to 2.10.0
* boo#1203507 (CVE-2022-35934)
- Breaking Changes
* Causal attention in keras.layers.Attention and
keras.layers.AdditiveAttention is now specified in the call()
method via the use_causal_mask argument (rather than in the
constructor), for consistency with other layers.
* Some files in tensorflow/python/training have been moved to
tensorflow/python/tracking and tensorflow/python/checkpoint.
Please update your imports accordingly, the old files will be
removed in Release 2.11.
* tf.keras.optimizers.experimental.Optimizer will graduate in
Release 2.11, which means tf.keras.optimizers.Optimizer will
be an alias of tf.keras.optimizers.experimental.Optimizer. The
current tf.keras.optimizers.Optimizer will continue to be
supported as tf.keras.optimizers.legacy.Optimizer,
e.g.,tf.keras.optimizers.legacy.Adam. Most users won't be
affected by this change, but please check the API doc if any
API used in your workflow is changed or deprecated, and make
adaptions. If you decide to keep using the old optimizer,
please explicitly change your optimizer to
tf.keras.optimizers.legacy.Optimizer.
* RNG behavior change for tf.keras.initializers. Keras
initializers will now use stateless random ops to generate
random numbers.
- Both seeded and unseeded initializers will always generate
the same values every time they are called (for a given
variable shape). For unseeded initializers (seed=None), a
random seed will be created and assigned at initializer
creation (different initializer instances get different (forwarded request 1005091 from bnavigator)
OBS-URL: https://build.opensuse.org/request/show/1005092
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/tensorflow-lite?expand=0&rev=2
- Update to 2.10.0
* boo#1203507 (CVE-2022-35934)
- Breaking Changes
* Causal attention in keras.layers.Attention and
keras.layers.AdditiveAttention is now specified in the call()
method via the use_causal_mask argument (rather than in the
constructor), for consistency with other layers.
* Some files in tensorflow/python/training have been moved to
tensorflow/python/tracking and tensorflow/python/checkpoint.
Please update your imports accordingly, the old files will be
removed in Release 2.11.
* tf.keras.optimizers.experimental.Optimizer will graduate in
Release 2.11, which means tf.keras.optimizers.Optimizer will
be an alias of tf.keras.optimizers.experimental.Optimizer. The
current tf.keras.optimizers.Optimizer will continue to be
supported as tf.keras.optimizers.legacy.Optimizer,
e.g.,tf.keras.optimizers.legacy.Adam. Most users won't be
affected by this change, but please check the API doc if any
API used in your workflow is changed or deprecated, and make
adaptions. If you decide to keep using the old optimizer,
please explicitly change your optimizer to
tf.keras.optimizers.legacy.Optimizer.
* RNG behavior change for tf.keras.initializers. Keras
initializers will now use stateless random ops to generate
random numbers.
- Both seeded and unseeded initializers will always generate
the same values every time they are called (for a given
variable shape). For unseeded initializers (seed=None), a
random seed will be created and assigned at initializer
creation (different initializer instances get different
OBS-URL: https://build.opensuse.org/request/show/1005091
OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/tensorflow-lite?expand=0&rev=3
