TF 2.0 print tensor values
Inside the graph indicated by the decorator @tf.function
, you can use tf.print to print the values of your tensor.
tf.print(new_x)
Here is how the code can be rewritten
class Data:
def __init__(self):
pass
def back_to_zero(self, input):
time = tf.slice(input, [0,0], [-1,1])
new_time = time - time[0][0]
return new_time
@tf.function
def load_data(self, inputs):
new_x = self.back_to_zero(inputs)
tf.print(new_x) # print inside the graph context
return new_x
time = np.linspace(0,10,20)
magntiudes = np.random.normal(0,1,size=20)
x = np.vstack([time, magntiudes]).T
d = Data()
data = d.load_data(x)
print(data) # print outside the graph context
the tensor type outside the tf.decorator
context is of type tensorflow.python.framework.ops.EagerTensor
. To convert it to a numpy array, you can use data.numpy()