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+*.swp

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+import tensorflow as tf

+

+def get_simple_graph_def():

+  """Create a simple graph and return its graph_def."""

+  g = tf.Graph()

+  with g.as_default():

+    a = tf.placeholder(

+        dtype=tf.float32, shape=(None, 24, 24, 2), name="input")

+    e = tf.constant(

+        [[[[1., 0.5, 4., 6., 0.5, 1.], [1., 0.5, 1., 1., 0.5, 1.]]]],

+        name="weights",

+        dtype=tf.float32)

+    conv = tf.nn.conv2d(

+        input=a, filter=e, strides=[1, 2, 2, 1], padding="SAME", name="conv")

+    b = tf.constant(

+        [4., 1.5, 2., 3., 5., 7.], name="bias", dtype=tf.float32)

+    t = tf.nn.bias_add(conv, b, name="biasAdd")

+    relu = tf.nn.relu(t, "relu")

+    idty = tf.identity(relu, "ID")

+    v = tf.nn.max_pool(

+        idty, [1, 2, 2, 1], [1, 2, 2, 1], "VALID", name="max_pool")

+    tf.squeeze(v, name="output")

+  return g.as_graph_def()

@@ -3,27 +3,7 @@ from tensorflow.contrib import tensorrt as trt

 import numpy as np

-def get_simple_graph_def():

-  """Create a simple graph and return its graph_def."""

-  g = tf.Graph()

-  with g.as_default():

-    a = tf.placeholder(

-        dtype=tf.float32, shape=(None, 24, 24, 2), name="input")

-    e = tf.constant(

-        [[[[1., 0.5, 4., 6., 0.5, 1.], [1., 0.5, 1., 1., 0.5, 1.]]]],

-        name="weights",

-        dtype=tf.float32)

-    conv = tf.nn.conv2d(

-        input=a, filter=e, strides=[1, 2, 2, 1], padding="SAME", name="conv")

-    b = tf.constant(

-        [4., 1.5, 2., 3., 5., 7.], name="bias", dtype=tf.float32)

-    t = tf.nn.bias_add(conv, b, name="biasAdd")

-    relu = tf.nn.relu(t, "relu")

-    idty = tf.identity(relu, "ID")

-    v = tf.nn.max_pool(

-        idty, [1, 2, 2, 1], [1, 2, 2, 1], "VALID", name="max_pool")

-    tf.squeeze(v, name="output")

-  return g.as_graph_def()

+from lib import get_simple_graph_def

 def run_graph(gdef, dumm_inp):

   """Run given graphdef once."""