refactor

Author: zhijxu-MS

tests/common.py

@@ -23,7 +23,7 @@
     "check_tf_min_version",
     "check_tf_max_version",
     "skip_tf_versions",
-    "skip_if_tf_cpu",
+    "skip_tf_cpu",
     "check_onnxruntime_min_version",
     "check_opset_min_version",
     "check_opset_max_version",
@@ -187,7 +187,7 @@ def is_tf_gpu():
     return tf.test.is_gpu_available()
 
 
-def skip_if_tf_cpu(message=""):
+def skip_tf_cpu(message=""):
     is_tf_cpu = not is_tf_gpu()
     return unittest.skipIf(is_tf_cpu, message)
 

tests/test_backend.py

@@ -258,7 +258,7 @@ def test_maxpool(self):
                 self.logger.debug(str(p))
                 self._run_test_case([_OUTPUT], {_INPUT: x_val})
 
-    @skip_if_tf_cpu("only tf_gpu can run maxpool with NCHW format")
+    @skip_tf_cpu("only tf_gpu can run maxpool with NCHW format")
     def test_maxpool_gpu(self):
         # make sure converter behaves well when data format is NCHW
         # and when data format is NCHW, only gpu version of tensorflow can run it.

tf2onnx/graph.py

@@ -139,10 +139,6 @@ def is_nhwc(self):
         """Return True if node is in NHWC format."""
         return self.data_format == "NHWC"
 
-    def is_nchw(self):
-        """Return True if node is in NCHW format."""
-        return self.data_format == "NCHW"
-
     def is_const(self):
         """Return True if node is a constant."""
         return self.type in ["Const", "ConstV2"]

tf2onnx/onnx_opset/nn.py

@@ -314,11 +314,9 @@ def _convert(cls, ctx, node, **kwargs):
         if node.is_nhwc():
             kernel_shape_hw = kernel_shape_tf[1:3]
             strides_hw = strides_tf[1:3]
-        elif node.is_nchw():
+        else:
             kernel_shape_hw = kernel_shape_tf[2:4]
             strides_hw = strides_tf[2:4]
-        else:
-            logger.warning("unexpected data format, please check it")
         node.set_attr("kernel_shape", kernel_shape_hw)
         node.set_attr("strides", strides_hw)
         conv_dims_attr(node, "dilations")