import tensorflow as tf

tf.enable_eager_execution()

print(tf.add(1, 2))
print(tf.add([1, 2], [3, 4]))
print(tf.square(5))
print(tf.reduce_sum([1, 2, 3]))
print(tf.encode_base64("hello world"))

# Operator overloading is also supported
print(tf.square(2) + tf.square(3))

x = tf.matmul([[1]], [[2, 3]])
print(x.shape)
print(x.dtype)

import numpy as np

ndarray = np.ones([3,3])

print("TensorFlow operations convert numpy arrays to Tensors automatically")
tensor = tf.multiply(ndarray, 42)
print(tensor)


print("And NumPy operations convert Tensors to numpy arrays automatically")
print(np.add(tensor, 1))

print("The .numpy() method explicitly converts a Tensor to a numpy array")
print(tensor.numpy())



ds_tensors = tf.data.Dataset.from_tensor_slices([1, 2, 3, 4, 5, 6])
import tempfile
_, filename = tempfile.mkstemp()

with open(filename, 'w') as f:
      f.write("""Line 1
      Line 2
      Line 3
        """)

ds_file = tf.data.TextLineDataset(filename)
print(ds_file)


ds_tensors = ds_tensors.map(tf.square).shuffle(2).batch(2)

ds_file = ds_file.batch(2)

print('Elements of ds_tensors:')
for x in ds_tensors:
  print(x)

print('\nElements in ds_file:')
for x in ds_file:
  print(x)