Is TensorFlow supported on M1 max? - python-3.x

Question

In my attempt to start using TensorFlow on my mac [Monterey 12.6.1] [chip Apple M1 MAX] I start to get errors that I did not observe on my mac mini [Monterey 12.6 - Chip M1 2020]
It is either an environment issue or a chipset issue.
[Works on my windows machine Win-11 and Mac-Mini]
Code:
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import Adam
from tensorflow.keras import layers
model = Sequential([layers.Input((3, 1)),
layers.LSTM(64),
layers.Dense(32, activation='relu'),
layers.Dense(32, activation='relu'),
layers.Dense(1)])
model.compile(loss='mse',
optimizer=Adam(learning_rate=0.001),
metrics=['mean_absolute_error'])
model.fit(X_train, y_train, validation_data=(X_val, y_val), epochs=100)
Error observed in DataSpell:
--------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
RuntimeError: module compiled against API version 0x10 but this version of numpy is 0xe
Traceback
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Input In [14], in <cell line: 1>()
----> 1 from tensorflow.keras.models import Sequential
2 from tensorflow.keras.optimizers import Adam
3 from tensorflow.keras import layers
Following Greg Hogg tutorial: https://www.youtube.com/watch?v=CbTU92pbDKw
Note this code work on my mac mini machine but not on the MacBook Pro.
Anaconda env -> Python 3.9
python --version
Python 3.9.12
conda list | grep tensorflow
tensorflow-deps 2.8.0 0 apple
tensorflow-estimator 2.10.0 pypi_0 pypi
tensorflow-macos 2.10.0 pypi_0 pypi
tensorflow-metal 0.6.0 pypi_0 pypi
What I am expecting is similar outcome like the windows environment and the Mac-mini where the model is constructed and fitted with the training data. (model object creation without an exception)
Example:
Epoch 99/100
7/7 [==============================] - 0s 5ms/step - loss: 6.1541 - mean_absolute_error: 1.8648 - val_loss: 9.5456 - val_mean_absolute_error: 2.6235
Epoch 100/100
7/7 [==============================] - 0s 5ms/step - loss: 6.7555 - mean_absolute_error: 2.0134 - val_loss: 9.4403 - val_mean_absolute_error: 2.6016
<keras.callbacks.History at 0x27a6590c6a0>
Attempting the numpy upgrade posted answer, I did the "numpy upgrade" yet had the output below on the terminal and the same exception still observed.
pip install numpy --upgrade
Requirement already satisfied: numpy in ./opt/anaconda3/lib/python3.9/site-packages (1.21.5)
Collecting numpy
Using cached numpy-1.23.4-cp39-cp39-macosx_11_0_arm64.whl (13.4 MB)
Installing collected packages: numpy
Attempting uninstall: numpy
Found existing installation: numpy 1.21.5
Uninstalling numpy-1.21.5:
Successfully uninstalled numpy-1.21.5
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
scipy 1.7.3 requires numpy<1.23.0,>=1.16.5, but you have numpy 1.23.4 which is incompatible.
numba 0.55.1 requires numpy<1.22,>=1.18, but you have numpy 1.23.4 which is incompatible.
Successfully installed numpy-1.23.4
==================================
So combination of multiple approaches fixed the issue:
pip uninstall keras
pip uninstall keras-preprocessing
pip uninstall tensorboard
pip install --upgrade numpy
If step 4 does not work [error or concerning warning], then pip uninstall numpy ; followed by pip install numpy
python -m pip install tensorflow-macos
That fix my environment problem.

Answer 1

From Apple documentation to install tensorflow-metal with tensorflow
Requirements
Mac computers with Apple silicon or AMD GPUs
macOS 12.0 or later (Get the latest beta)
Python 3.8 or later
Xcode command-line tools: xcode-select --install
Set up
// Download Conda environment
bash ~/miniconda.sh -b -p $HOME/miniconda
source ~/miniconda/bin/activate
conda install -c apple tensorflow-deps
// Install base TensorFlow
python -m pip install tensorflow-macos
// Install tensorflow-metal plug-in
python -m pip install tensorflow-metal
Verify the set up
import tensorflow as tf
cifar = tf.keras.datasets.cifar100
(x_train, y_train), (x_test, y_test) = cifar.load_data()
model = tf.keras.applications.ResNet50(
include_top=True,
weights=None,
input_shape=(32, 32, 3),
classes=100,)
loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
model.compile(optimizer="adam", loss=loss_fn, metrics=["accuracy"])
model.fit(x_train, y_train, epochs=5, batch_size=64)

Answer 2

The real answer to your problem though is that you have many version of numpy installed.
Please run pip3 install --upgrade numpy in your terminal and it should fix your problem.

Answer 3

So combination of multiple approaches fixed the issue:
pip uninstall keras
pip uninstall keras-preprocessing
pip uninstall tensorboard
pip install --upgrade numpy
If step 4 does not work [error or concerning warning], then pip uninstall numpy; followed by pip install numpy
python -m pip install tensorflow-macos
That fix my environment problem.