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python code with tensorflow does not work

How can Tensorflow have no "div" attribute? When I try to run a python program from the command prompt (from tensorflow for dummies page 23 (simple program) I receive this error:
C:\Users\ME\TENSORFLOW\ch3>python simple_math.py 20200426 13:50:29.871436: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found 20200426 13:50:29.880652: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine. 20200426 13:50:32.204590: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found 20200426 13:50:32.212936: E tensorflow/stream_executor/cuda/cuda_driver.cc:351] failed call to cuInit: UNKNOWN ERROR (303) 20200426 13:50:32.228615: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: DESKTOPC7DH370 20200426 13:50:32.236344: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: DESKTOPC7DH370 Traceback (most recent call last): File "simple_math.py", line 13, in <module> quot = tf.div(const_a, const_b) AttributeError: module 'tensorflow' has no attribute 'div'
thank you so much in advance

Hey @TonyCardinal I think you forgot to share the actual source file simple_math.py. Please share that so we have a better chance of answering your question.

''' Perform simple math operations with TensorFlow '''
from future import absolute_import
from future import division
from future import print_functionimport tensorflow as tf
Math with constant tensors
const_a = tf.constant(3.6)
const_b = tf.constant(1.2)
total = const_a + const_b
quot = tf.div(const_a, const_b)Math with random tensors
rand_a = tf.random_normal([3], 2.0)
rand_b = tf.random_uniform([3], 1.0, 4.0)
diff = tf.subtract(rand_a, rand_b)Vector multiplication
vec_a = tf.linspace(0.0, 3.0, 4)
vec_b = tf.fill([4, 1], 2.0)
prod = tf.multiply(vec_a, vec_b)
dot = tf.tensordot(vec_a, vec_b, 1)Matrix multiplication
mat_a = tf.constant([[2, 3], [1, 2], [4, 5]])
mat_b = tf.constant([[6, 4, 1], [3, 7, 2]])
mat_prod = tf.matmul(mat_a, mat_b)Execute the operations
with tf.Session() as sess:
print('Sum: %f' % sess.run(total))
print('Quotient: %f' % sess.run(quot))
print('Difference: ', sess.run(diff))
print('Elementwise product: ', sess.run(prod))
print('Dot product: ', sess.run(dot))
print('Matrix product: ', sess.run(mat_prod))Thank you

@TonyCardinal said in python code with tensorflow does not work:
module 'tensorflow' has no attribute 'div'
This might be a Tensorflow 2.0 versus 1.0 issue? I don't program in python but I found the following stackoverflow answer that might help:
If I am right you can do something like:
tf.compat.v1.div(x,y)
or
import tensorflow.compat.v1 as tf tf.disable_v2_behavior()