format unittest

Signed-off-by: Dom Miketa <[email protected]>

Author: d-miketa

test/backend/test_dynamic_shape.py

@@ -249,18 +249,23 @@ def test_conv_transpose(self):
     np.testing.assert_almost_equal(tf_model_output[0], test_output, decimal=5)
 
   def test_depth_to_space(self):
-    b,c,h,w = shape = [2, 48, 5, 6]
+    b, c, h, w = shape = [2, 48, 5, 6]
     blocksize = 4
     x = self._get_rnd_float32(shape=shape)
-    node_def = helper.make_node("DepthToSpace", ["X"], ["Y"], blocksize=blocksize, mode="DCR")
+    node_def = helper.make_node("DepthToSpace", ["X"], ["Y"],
+                                blocksize=blocksize,
+                                mode="DCR")
     graph_def = helper.make_graph(
         [node_def],
         name="test_unknown_shape",
         inputs=[
             helper.make_tensor_value_info("X", TensorProto.FLOAT,
                                           [None, None, None, None])
         ],
-        outputs=[helper.make_tensor_value_info("Y", TensorProto.FLOAT, [None, None, None, None])])
+        outputs=[
+            helper.make_tensor_value_info("Y", TensorProto.FLOAT,
+                                          [None, None, None, None])
+        ])
     tf_rep = onnx_graph_to_tensorflow_rep(graph_def)
     # export to tf.saved_model
     model_path = 'test_dynamic_shape/depth_to_space'
@@ -270,8 +275,8 @@ def test_depth_to_space(self):
     # run the model
     tf_model_output = tf_model(X=x)
     tmp = np.reshape(x, [b, blocksize, blocksize, c // (blocksize**2), h, w])
-    tmp = np.transpose(tmp, [0, 3, 4, 1, 5 ,2])
-    y = np.reshape(tmp, [b, c // (blocksize**2), h*blocksize, w*blocksize])
+    tmp = np.transpose(tmp, [0, 3, 4, 1, 5, 2])
+    y = np.reshape(tmp, [b, c // (blocksize**2), h * blocksize, w * blocksize])
     np.testing.assert_almost_equal(tf_model_output[0], y)
 
   def test_eye_like(self):