Tensorcircuit Installation Guide on MacOS#

Contributed by Mark (Zixuan) Song

Apple has updated Tensorflow (for MacOS) so that installation on M-series (until M2) and Intel-series Mac can follow the exact same procedure.

Starting From Scratch#

For completely new Macos or Macos without Xcode installed.

If you have Xcode installed, skip to Install TC backends.

Install Xcode Command Line Tools#

Need graphical access to the machine.

Run xcode-select --install to install if on optimal internet.

Or Download it from Apple Command Line Tools installation image then install it if the internet connection is weak.

Install TC Backends#

There are four backends to choose from, Numpy, Tensorflow, Jax, and Torch.

Install Jax, Pytorch (Optional)#

pip install [Package Name]

Install Tensorflow (Optional - Recommended)#

Install Miniconda (Optional - Recommended)#

If you wish to install Tensorflow optimized for MacOS (tensorflow-macos) or Tensorflow GPU optimized (tensorflow-metal) please install miniconda.

If you wish to install Vanilla Tensorflow developed by Google (tensorflow) please skip this step.

curl -o ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh
bash ~/miniconda.sh -b -p $HOME/miniconda
source ~/miniconda/bin/activate
conda install -c apple tensorflow-deps

Installation#

pip install tensorflow

If you wish to use tensorflow-metal PluggableDevice, then continue install (not recommended):

pip install tensorflow-metal

Verify Tensorflow Installation#

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)

Install Tensorcircuit#

pip install tensorcircuit

Benchmarking#

This data is collected by running benchmarks/scripts/vqe_tc.py 10 times and average results.

	Vanilla Tensorflow	Apple Tensorflow	Apple Tensorflow with Metal Plugin
Construction Time	11.49241641s	11.31878941s	11.6103961s
Iteration time	0.002313011s	0.002333004s	0.046412581s
Total time	11.72371747s	11.55208979s	16.25165417s

Until July 2023, this has been tested on Intel Macs running Ventura, M1 Macs running Ventura, M2 Macs running Ventura, and M2 Macs running Sonoma beta.