[docs] Use the normalize_tf_graph now in symbolic_pymc

Author: brandonwillard

docs/source/tensorflow-radon-example.org

@@ -645,72 +645,18 @@ breadth of relevant operator coverage isn't clear; however, the normalizations
 that it does provide are worth using, so we'll make use of them throughout.
 :END:
 
-[[grappler-normalize-function]] provides a simple means of
+src_python[:eval never]{symbolic_pymc.tensorflow.graph.normalize_tf_graph} provides a simple means of
 applying src_python[:eval never]{grappler}.
 
-#+NAME: grappler-normalize-function
-#+BEGIN_SRC python :exports code :results silent
-from tensorflow.core.protobuf import config_pb2
-
-from tensorflow.python.framework import ops
-from tensorflow.python.framework import importer
-from tensorflow.python.framework import meta_graph
-
-from tensorflow.python.grappler import cluster
-from tensorflow.python.grappler import tf_optimizer
-
-
-try:
-    gcluster = cluster.Cluster()
-except tf.errors.UnavailableError:
-    pass
-
-config = config_pb2.ConfigProto()
-
-
-def normalize_tf_graph(graph_output, new_graph=True, verbose=False):
-    """Use grappler to normalize a graph.
-
-    Arguments
-    =========
-    graph_output: Tensor
-      A tensor we want to consider as "output" of a FuncGraph.
-
-    Returns
-    =======
-    The simplified graph.
-    """
-    train_op = graph_output.graph.get_collection_ref(ops.GraphKeys.TRAIN_OP)
-    train_op.clear()
-    train_op.extend([graph_output])
-
-    metagraph = meta_graph.create_meta_graph_def(graph=graph_output.graph)
-
-    optimized_graphdef = tf_optimizer.OptimizeGraph(
-        config, metagraph, verbose=verbose, cluster=gcluster)
-
-    output_name = graph_output.name
-
-    if new_graph:
-        optimized_graph = ops.Graph()
-    else:
-        optimized_graph = ops.get_default_graph()
-        del graph_output
-
-    with optimized_graph.as_default():
-        importer.import_graph_def(optimized_graphdef, name="")
-
-    opt_graph_output = optimized_graph.get_tensor_by_name(output_name)
-
-    return opt_graph_output
-#+END_SRC
-
-In [[grappler-normalize-function]] we
+In [[grappler-normalize-test-graph]] we
 run src_python[:eval never]{grappler} on the log-likelihood graph for a normal
 random variable from [[tfp-normal-log-lik-graph]].
 
 #+NAME: grappler-normalize-test-graph
 #+BEGIN_SRC python :exports code :results silent :wrap
+from symbolic_pymc.tensorflow.graph import normalize_tf_graph
+
+
 normal_log_lik_opt = normalize_tf_graph(normal_log_lik)
 #+END_SRC