Numpy is much much faster (Note: Used CPU version, not the GPU version)
import numpy import tensorflow as tf import time def getTestData(): A = [[1., 2., 3., 4.],[3.,4.,5.,6.],[7.,8,9.,10.],[11.,12.,13.,14.]] return 6,A def tfMatMul(): n,A = getTestData() A = tf.constant(A) sess = tf.Session() for num in range(1,n): A = tf.matmul(A,A) output = sess.run(A) A = tf.convert_to_tensor(output) sess.close() return output def numPyMatMul(): n,A = getTestData() for num in range(1,n): A = numpy.matmul(A,A) return A def timedRun(methodToRun): start = time.time() result = methodToRun() end = time.time() diff = end - start print("Time Taken :"+str(diff)) print(result) timedRun(numPyMatMul) timedRun(tfMatMul)
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