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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:

  1. pip uninstall keras
  2. pip uninstall keras-preprocessing
  3. pip uninstall tensorboard
  4. pip install --upgrade numpy
  5. If step 4 does not work [error or concerning warning], then pip uninstall numpy ; followed by pip install numpy
  6. python -m pip install tensorflow-macos That fix my environment problem.
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2
  • 1
    The problem is with numpy, not with tensorflow, and has nothing to do with apple processors. The problem is that you have multiple versions of numpy installed (python part vs the native numpy library, with incompatible versions). Commented Nov 9, 2022 at 0:33
  • Related post: stackoverflow.com/questions/33859531/… Commented Nov 9, 2022 at 0:52

3 Answers 3

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0

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)
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Followed those steps but did not fix the issue.
0

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.

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2 Comments

The upgrade shows the following: 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.
I manage to get it to work after uninstall off keras it seems I have multiple issues. and re install tensorflow-macos
0

So combination of multiple approaches fixed the issue:

  1. pip uninstall keras
  2. pip uninstall keras-preprocessing
  3. pip uninstall tensorboard
  4. pip install --upgrade numpy
  5. If step 4 does not work [error or concerning warning], then pip uninstall numpy; followed by pip install numpy
  6. python -m pip install tensorflow-macos

That fix my environment problem.

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