Command from answer: py-m pip install –upgrade tensorflow; Now Execute the download of the data that trains the machine. Choose one of the platform install guides, for Mac: Installing TensorFlow on MacOS; Complete install: the r ecommended installation mechanism is `Virtualenv`. Go to the section “Installing with Virtualenv. To work with the code examples in this course, we need to install the Python 3 programming language, the PyCharm development environment, and several software libraries, including TensorFlow. This video will cover installation on Mac OS. If you are using Windows, watch the separate video covering Windows installation instead. The method we'll use to install TensorFlow will only install the. With this tutorial, you can unleash the full capability of Tensorflow with AVX2 and FMA enabled on macOS. System Information. MacOS Catalina 10.15.6 python 3.7.7 Tensorflow (CPU only) 1.14.1 Bazel. Install and configure Xcode. For starters, you’ll need to get Xcode from the Apple App Store.
Learning has never been so easy!
TensorFlow doesn't support macOS or AMD/ATI-based GPUs because it uses CUDA, an NVIDIA-specific API. However, many AMD GPUs support OpenCL and Metal. See references for a hardware compatibility list.
To support GPU-backed ML code using Keras, we can leverage PlaidML. These are steps to install TensorFlow, Keras, and PlaidML, and to test and benchmark GPU support.
These instructions assume a fresh install of macOS 10.15 Catalina using the system python installation. If you installed Python from a package or via homebrew these instructions and you probably won't experience the same issues mentioned below.
5 Steps totalStep 1: Download TensorFlow and Keras
Showbox free movies download for mac. First, update pip. Then install TensorFlow.
``` pip install --upgrade pip pip install tensorflow ``` Step 2: Install PlaidML
```
pip install plaidml-keras plaidbench ```
On macOS 10.15 the system-installed Python does not permit system-wide package installs, so we need to help the plaidml-setup binary locate the plaidml library.
```
export PLAIDML_NATIVE_PATH=/Users/[username]/Library/Python/3.7/lib/libplaidml.dylib export RUNFILES_DIR=/Users/[username]/Library/Python/3.7/share/plaidml ``` How To Download And Install Tensorflow Macos Installer
Replace `[username]` with your username before executing the commands.
Step 3: Configure PlaidML
```
plaidml-setup ```
You may choose to enable experimental device support, which gives you the OpenCL drivers in addition to the metal ones. You should pick your faster GPU as the default. Then write the configuration file.
Step 4: Test PlaidML
To test PlaidML, we can use the installed `plaidbench` command. However, if using the system Python install on macOS Catalina, we will need to install root SSL certificates, otherwise error `[SSL: CERTIFICATE_VERIFY_FAILED]` will throw during the test.
Then run this script:
``` cat > install_certifi.py << EOF # install_certifi.py # # sample script to install or update a set of default Root Certificates # for the ssl module. Uses the certificates provided by the certifi package: # https://pypi.python.org/pypi/certifi
import os
import os.path import ssl import stat import subprocess import sys
STAT_0o775 = ( stat.S_IRUSR | stat.S_IWUSR | stat.S_IXUSR
| stat.S_IRGRP | stat.S_IWGRP | stat.S_IXGRP | stat.S_IROTH | stat.S_IXOTH )
def main():
openssl_dir, openssl_cafile = os.path.split( ssl.get_default_verify_paths().openssl_cafile)
# print(' -- pip install --upgrade certifi')
# subprocess.check_call([sys.executable, # '-E', '-s', '-m', 'pip', 'install', '--upgrade', '--user', 'certifi'])
import certifi
# change working directory to the default SSL directory
os.chdir(openssl_dir) relpath_to_certifi_cafile = os.path.relpath(certifi.where()) print(' -- removing any existing file or link') try: os.remove(openssl_cafile) except FileNotFoundError: pass print(' -- creating symlink to certifi certificate bundle') os.symlink(relpath_to_certifi_cafile, openssl_cafile) print(' -- setting permissions') os.chmod(openssl_cafile, STAT_0o775) print(' -- update complete') Download torrent + killing of a sacred deer.
if __name__ '__main__':
main() EOF ```
Then run the code to install Python root certs:
``` sudo python3 install_certifi.py ```
Now we can test. Open your Activity Monitor and activate GPU History (Cmd+4). Then run these commands:
``` plaidbench keras mobilenet plaidbench --batch-size 16 keras --train mobilenet ```
Compare output with image. Verify a spike in GPU activity.
Step 5: Test with Hello VGG
On the PlaidML Github README, there is a sample Hello VGG script demonstrating how to use PlaidML with Keras. Here is that script:
```
#!/usr/bin/env python
import numpy as np
import os import time
os.environ['KERAS_BACKEND'] = 'plaidml.keras.backend'
import keras
import keras.applications as kapp from keras.datasets import cifar10
(x_train, y_train_cats), (x_test, y_test_cats) = cifar10.load_data()
batch_size = 8 x_train = x_train[:batch_size] x_train = np.repeat(np.repeat(x_train, 7, axis=1), 7, axis=2) model = kapp.VGG19() model.compile(optimizer='sgd', loss='categorical_crossentropy', metrics=['accuracy'])
print('Running initial batch (compiling tile program)')
y = model.predict(x=x_train, batch_size=batch_size)
# Now start the clock and run 10 batches
print('Timing inference..') start = time.time() for i in range(10): y = model.predict(x=x_train, batch_size=batch_size) print('Ran in {} seconds'.format(time.time() - start)) ```
Execute like so after saving file as vgg.py:
``` python3 vgg.py ```
If you want to compare with TensorFlow, which uses the CPU on macOS instead due to lack of CUDA support, comment out the `os.environ` and keras import statements and replace with this: Can i transfer my microsoft office from pc to mac.
```
#!/usr/bin/env python
import numpy as np
import os import time
#os.environ['KERAS_BACKEND'] = 'plaidml.keras.backend'
#import keras
#import keras.applications as kapp #from keras.datasets import cifar10
import tensorflow.keras
import tensorflow.keras.applications as kapp from tensorflow.keras.datasets import cifar10
(x_train, y_train_cats), (x_test, y_test_cats) = cifar10.load_data()
batch_size = 8 x_train = x_train[:batch_size] x_train = np.repeat(np.repeat(x_train, 7, axis=1), 7, axis=2) model = kapp.VGG19() model.compile(optimizer='sgd', loss='categorical_crossentropy', metrics=['accuracy'])
print('Running initial batch (compiling tile program)')
y = model.predict(x=x_train, batch_size=batch_size)
# Now start the clock and run 10 batches
print('Timing inference..') start = time.time() for i in range(10): y = model.predict(x=x_train, batch_size=batch_size) print('Ran in {} seconds'.format(time.time() - start)) ``` How To Download Tensorflow On Mac
When using TensorFlow, we have to import Keras from TensorFlow instead of calling directly in order to avoid `AttributeError: module 'tensorflow' has no attribute 'get_default_graph'`.
By the way, if you get error `RuntimeError: dictionary changed size during iteration` then you either need to upgrade to Python 3.7.5 or edit line 48 of this file:
``` sudo vim /Applications/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.7/lib/python3.7/linecache.py ``` Change line 48 from: ``` for mod in sys.modules.values(): ``` to: ``` for mod in list(sys.modules.values()): #for mod in sys.modules.values(): ``` ReferencesHow To Download And Install Tensorflow Macos High Sierra
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