Remove deprecation warning (again )

src/pystencils_autodiff/backends/_tensorflow.py

 import tensorflow as tf
+
 import pystencils_autodiff
-import numpy as np
-from pystencils.utils import DotDict
+from tf.compat.v1 import get_default_graph
 
 _num_generated_ops = 0
 
 
 def _py_func(func, inp, Tout, stateful=False, name=None, grad=None):
     """
-    Copied from random internet forum. It seems to be important to give 
+    Copied from random internet forum. It seems to be important to give
     PyFunc to give an random name in override map to properly register gradients
 
     PyFunc defined as given by Tensorflow
@@ -29,14 +29,17 @@ def _py_func(func, inp, Tout, stateful=False, name=None, grad=None):
     tf.RegisterGradient(rnd_name)(grad)
 
     # Get current graph
-    g = tf.get_default_graph()
+    g = get_default_graph()
 
     # Add gradient override map
     with g.gradient_override_map({"PyFunc": rnd_name, "PyFuncStateless": rnd_name}):
         return tf.py_func(func, inp, Tout, stateful=stateful, name=name)
 
 
-def tensorflowop_from_autodiffop(autodiffop: pystencils_autodiff.AutoDiffOp, inputfield_tensor_dict, forward_function, backward_function):
+def tensorflowop_from_autodiffop(autodiffop: pystencils_autodiff.AutoDiffOp,
+                                 inputfield_tensor_dict,
+                                 forward_function,
+                                 backward_function):
 
     def helper_forward(*args):
         kwargs = dict()
@@ -59,7 +62,12 @@ def tensorflowop_from_autodiffop(autodiffop: pystencils_autodiff.AutoDiffOp, inp
         return [rtn_dict[o.name] for o in autodiffop._backward_output_fields]
 
     def backward(op, *grad):
-        return tf.py_func(helper_backward, [*op.inputs, *grad], [f.dtype.numpy_dtype for f in autodiffop._backward_output_fields], name=autodiffop.op_name + '_backward', stateful=False)
+        return tf.py_func(helper_backward,
+                          [*op.inputs,
+                           *grad],
+                          [f.dtype.numpy_dtype for f in autodiffop._backward_output_fields],
+                          name=autodiffop.op_name + '_backward',
+                          stateful=False)
 
     output_tensors = _py_func(helper_forward,
                               [inputfield_tensor_dict[f]