I have trained my TensorFlow model in google colab and exported it in format .h5. In google colab I can load model with no problem but on my local machine, it throws me errors and warnings.
Loading model
import tensorflow as tf
rnn = tf.keras.models.load_model('my_model.h5')
error
2020-05-16 20:17:10.802390: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU
supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-05-16 20:17:10.835907: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU
Frequency: 2400000000 Hz
2020-05-16 20:17:10.836269: I tensorflow/compiler/xla/service/service.cc:168] XLA service
0x4443f90 executing computations on platform Host. Devices:
2020-05-16 20:17:10.836308: I tensorflow/compiler/xla/service/service.cc:175]
StreamExecutor device (0): <undefined>, <undefined>
2020-05-16 20:17:10.862236: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412]
(One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--
tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use
experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass
--vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or
set the envvar XLA_FLAGS=--xla_hlo_profile.
I trained model in google collab with GPU.