Programs to access objects in s3 storage.
See the python examples for any required environment variables.
Dev Environment
$ python --version
Python 3.9.12
Install and Test
python3 -m venv ~/tmpenv
source ~/tmpenv/bin/activate
pip install pip -qU
pip install -qr requirements.txt
python get-protobuf-s3.py
Expected Output
INFO:root:Tensorflow version: 2.9.1
2022-05-27 16:25:15.040980: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
WARNING:tensorflow:Inconsistent references when loading the checkpoint into this object graph. For example, in the saved checkpoint object, `model.layer.weight` and `model.layer_copy.weight` reference the same variable, while in the current object these are two different variables. The referenced variables are:(<keras.saving.saved_model.load.TensorFlowTransform>TransformFeaturesLayer object at 0x1276603a0> and <keras.engine.input_layer.InputLayer object at 0x1275c7940>).
WARNING:tensorflow:Inconsistent references when loading the checkpoint into this object graph. For example, in the saved checkpoint object, `model.layer.weight` and `model.layer_copy.weight` reference the same variable, while in the current object these are two different variables. The referenced variables are:(<keras.saving.saved_model.load.TensorFlowTransform>TransformFeaturesLayer object at 0x1276603a0> and <keras.engine.input_layer.InputLayer object at 0x1275c7940>).
Model: "model"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
HR_xf (InputLayer) [(None, 1)] 0 []
Resp_xf (InputLayer) [(None, 1)] 0 []
Temp_xf (InputLayer) [(None, 1)] 0 []
concatenate (Concatenate) (None, 3) 0 ['HR_xf[0][0]',
'Resp_xf[0][0]',
'Temp_xf[0][0]']
dense (Dense) (None, 100) 400 ['concatenate[0][0]']
dense_1 (Dense) (None, 70) 7070 ['dense[0][0]']
dense_2 (Dense) (None, 50) 3550 ['dense_1[0][0]']
dense_3 (Dense) (None, 20) 1020 ['dense_2[0][0]']
dense_4 (Dense) (None, 1) 21 ['dense_3[0][0]']
transform_features_layer (Tens multiple 0 []
orFlowTransform>TransformFeatu
resLayer)
==================================================================================================
Total params: 12,061
Trainable params: 12,061
Non-trainable params: 0
__________________________________________________________________________________________________
INFO:root:Input: [-0.060083888471126556, -0.9738271832466125, 1.370796918869]: Prediction: [[-35.60883]]
INFO:root:Input: [0.060083888471126556, 0.9738271832466125, 1.01]: Prediction: [[1.7196066]]
INFO:root:Input: [0.2, 0.1, 1]: Prediction: [[-9.383452]]