January 2018
Intermediate to advanced
474 pages
10h 23m
English
Content preview from Mastering TensorFlow 1.x
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Tensors generated from library functions
Tensors can also be generated from various TensorFlow functions. These generated tensors can either be assigned to a constant or a variable, or provided to their constructor at the time of initialization.
As an example, the following code generates a vector of 100 zeroes and prints it:
a=tf.zeros((100,))print(tfs.run(a))
TensorFlow provides different types of functions to populate the tensors at the time of their definition:
- Populating all elements with the same values
- Populating elements with sequences
- Populating elements with a random probability distribution, such as the normal distribution or the uniform distribution
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