          ------
          FaceswapError
              If Tensorflow is not found, or is not between versions 2.2 and 2.2
          """
          min_ver = 2.2
          max_ver = 2.2
          try:
              # Ensure tensorflow doesn't pin all threads to one core when using Math Kernel Library
              os.environ["TF_MIN_GPU_MULTIPROCESSOR_COUNT"] = "4"
              os.environ["KMP_AFFINITY"] = "disabled"
              import tensorflow as tf  # pylint:disable=import-outside-toplevel
 
</s> remove             If Tensorflow is not found, or is not between versions 2.2 and 2.2
 </s> add             If Tensorflow is not found, or is not between versions 2.3 and 2.3 </s> remove         in Conda """
 </s> add         in Conda.

        This was used whilst Tensorflow 2.2 was not available for Windows in Conda. It is kept
        here in case it is required again in the future.
        """ </s> remove             "The minimum Tensorflow requirement is 2.2 \n"
 </s> add             "The minimum Tensorflow requirement is 2.3 \n" </s> remove     freeze_log = list(_debug_buffer)
 </s> add     freeze_log = list(_DEBUG_BUFFER) </s> remove from tensorflow.python import errors_impl as tf_errors  # pylint:disable=no-name-in-module
 </s> add from tensorflow.python.framework import errors_impl as tf_errors
        min_ver = 2.3
        max_ver = 2.3
          ------
          FaceswapError
              If Tensorflow is not found, or is not between versions 2.2 and 2.2
          """
        min_ver = 2.3
        max_ver = 2.3
        min_ver = 2.3
        max_ver = 2.3
          try:
              # Ensure tensorflow doesn't pin all threads to one core when using Math Kernel Library
              os.environ["TF_MIN_GPU_MULTIPROCESSOR_COUNT"] = "4"
              os.environ["KMP_AFFINITY"] = "disabled"
              import tensorflow as tf  # pylint:disable=import-outside-toplevel
keep keep keep keep replace replace keep keep keep keep keep
 Update to TF2.3 (#1100)

* Minimum requirements to tf2.3.
  - Handle upgrades for Windows users with tf2.2 installed by Pip
  - Handle windows upgrade from pip tf2.2
  - Explicitly install Cuda for Conda installs

* Update tensorflow errors api reference
* Suppress AutoGraph warning messages
* Update GUI Stats to work with tf2.3
* Fix live graph for tf2.3
* DSSIMObjective - autoGraph bugfix
* Update Travis test 
lib/cli/launcher.py