Wraps python functions

Note: Functions taking Tensor arguments can also take anything accepted by tf.convert_to_tensor.

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Script Language Operators.

TensorFlow provides allows you to wrap python/numpy functions as TensorFlow operators.

tf.py_func(func, inp, Tout, stateful=True, name=None)

Wraps a python function and uses it as a tensorflow op.

Given a python function func, which takes numpy arrays as its inputs and returns numpy arrays as its outputs. E.g.,

def my_func(x):
  # x will be a numpy array with the contents of the placeholder below
  return np.sinh(x)
inp = tf.placeholder(tf.float32, [...])
y = py_func(my_func, [inp], [tf.float32])

The above snippet constructs a tf graph which invokes a numpy sinh(x) as an op in the graph.

Args:

• func: A python function.
• inp: A list of Tensor.
• Tout: A list or tuple of tensorflow data types or a single tensorflow data

   type if there is only one, indicating what `func` returns.
  

• stateful: A boolean indicating whether the function should be considered

       stateful or stateless. I.e. whether it, given the same input, will
       return the same output and at the same time does not change state
       in an observable way. Optimizations such as common subexpression
       elimination are only possible when operations are stateless.
  

• name: A name for the operation (optional).

Returns:

A list of Tensor or a single Tensor which func computes.