Tensorflow installation test

Identify current platform



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import subprocess
print((subprocess.check_output("lscpu", shell=True).strip()).decode())

Get tensorflow version and visible devices



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import tensorflow as tf
print('Using tensorflow version: {} ...'.format(tf.__version__))
print('Visible devices for tensorflow: {} ...'.format(tf.config.list_physical_devices()))

Tensorflow test 1



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print('Running tensorflow test: 1 ...')
print(tf.reduce_sum(tf.random.normal([1000, 1000])))

Tensorflow test 2



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import time
print('Running tensorflow test: 2 ... ')
c_cpu = 'Failed'
cpu_time = '...'
start_cpu = time.time()
with tf.device('/cpu:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
    b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
    c_cpu = tf.matmul(a, b)
end_cpu = time.time()
cpu_time = end_cpu - start_cpu

c_gpu = 'Failed ...'
gpu_time = '...'
try:
    start_gpu = time.time()
    with tf.device('/gpu:0'):
        a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
        b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
        c_gpu = tf.matmul(a, b)
    end_gpu = time.time()
    gpu_time = end_gpu - start_gpu
except:
    print('Tensorflow test using GPU failed ...')

print ('Matrix multiplication result using CPU: {} in {} seconds ...   \
        \nMatrix multiplication result using GPU: {} in {} seconds ...'.format(c_cpu, cpu_time,
                                                                               c_gpu, gpu_time))



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