remove onnxmsrtnext backend

Author: nbcsm

tests/backend_test_base.py

@@ -55,15 +55,8 @@ def run_onnxcaffe2(self, onnx_graph, inputs):
         results = prepared_backend.run(inputs)
         return results
 
-    def run_onnxmsrtnext(self, model_path, inputs, output_names):
-        """Run test against msrt-next backend."""
-        import lotus
-        m = lotus.InferenceSession(model_path)
-        results = m.run(output_names, inputs)
-        return results
-
     def run_onnxruntime(self, model_path, inputs, output_names):
-        """Run test against msrt-next backend."""
+        """Run test against onnxruntime backend."""
         import onnxruntime as rt
         m = rt.InferenceSession(model_path)
         results = m.run(output_names, inputs)
@@ -73,9 +66,7 @@ def run_backend(self, g, outputs, input_dict):
         model_proto = g.make_model("test")
         model_path = self.save_onnx_model(model_proto, input_dict)
 
-        if self.config.backend == "onnxmsrtnext":
-            y = self.run_onnxmsrtnext(model_path, input_dict, outputs)
-        elif self.config.backend == "onnxruntime":
+        if self.config.backend == "onnxruntime":
             y = self.run_onnxruntime(model_path, input_dict, outputs)
         elif self.config.backend == "caffe2":
             y = self.run_onnxcaffe2(model_proto, input_dict)

tests/common.py

@@ -102,7 +102,7 @@ def load():
         if "pytest" not in sys.argv[0]:
             parser = argparse.ArgumentParser()
             parser.add_argument("--backend", default=config.backend,
-                                choices=["caffe2", "onnxmsrtnext", "onnxruntime"],
+                                choices=["caffe2", "onnxruntime"],
                                 help="backend to test against")
             parser.add_argument("--opset", type=int, default=config.opset, help="opset to test against")
             parser.add_argument("--target", default=",".join(config.target), choices=constants.POSSIBLE_TARGETS,

tests/run_pretrained_models.py

@@ -163,21 +163,8 @@ def run_caffe2(self, name, model_proto, inputs):
             self.onnx_runtime = time.time() - start
         return results
 
-    def run_onnxmsrtnext(self, name, model_proto, inputs):
-        """Run test against msrt-next backend."""
-        import lotus
-        model_path = utils.save_onnx_model(TEMP_DIR, name, inputs, model_proto)
-        m = lotus.InferenceSession(model_path)
-        results = m.run(self.output_names, inputs)
-        if self.perf:
-            start = time.time()
-            for _ in range(PERFITER):
-                _ = m.run(self.output_names, inputs)
-            self.onnx_runtime = time.time() - start
-        return results
-
     def run_onnxruntime(self, name, model_proto, inputs):
-        """Run test against msrt-next backend."""
+        """Run test against onnxruntime backend."""
         import onnxruntime as rt
         model_path = utils.save_onnx_model(TEMP_DIR, name, inputs, model_proto, include_test_data=True)
         logger.info("Model saved to %s", model_path)
@@ -279,8 +266,6 @@ def run_test(self, name, backend="caffe2", onnx_file=None, opset=None, extra_ops
             onnx_results = None
             if backend == "caffe2":
                 onnx_results = self.run_caffe2(name, model_proto, inputs)
-            elif backend == "onnxmsrtnext":
-                onnx_results = self.run_onnxmsrtnext(name, model_proto, inputs)
             elif backend == "onnxruntime":
                 onnx_results = self.run_onnxruntime(name, model_proto, inputs)
             else:
@@ -316,7 +301,7 @@ def get_args():
     parser.add_argument("--tests", help="tests to run")
     parser.add_argument("--target", default="", help="target platform")
     parser.add_argument("--backend", default="onnxruntime",
-                        choices=["caffe2", "onnxmsrtnext", "onnxruntime"], help="backend to use")
+                        choices=["caffe2", "onnxruntime"], help="backend to use")
     parser.add_argument("--opset", type=int, default=None, help="opset to use")
     parser.add_argument("--extra_opset", default=None,
                         help="extra opset with format like domain:version, e.g. com.microsoft:1")

tests/test_backend.py

@@ -512,7 +512,6 @@ def test_placeholder_with_default_use_feed(self):
     def test_add_bcast(self):
         x1_val = np.array([1.0, 2.0, -3.0, -4.0], dtype=np.float32).reshape((2, 2))
         x2_val = np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0], dtype=np.float32).reshape((2, 2, 2))
-        # if we'd broadcast 2,2 to 2,1 onnxmsrt will fail
         x1 = tf.placeholder(tf.float32, x1_val.shape, name="input")
         x2 = tf.placeholder(tf.float32, x2_val.shape, name=_TFINPUT1)
         x_ = tf.add(x1, x2)
@@ -830,8 +829,6 @@ def test_reshape_int(self):
         _ = tf.identity(x_, name=_TFOUTPUT)
         self._run_test_case([_OUTPUT], {_INPUT: x_val}, check_shape=True)
 
-    @unittest.skipIf(get_test_config().opset < 5 or get_test_config().backend in ["onnxmsrtnext"],
-                     "since opset 5, broken in msrtnext")
     @check_opset_min_version(6, "cast")
     def test_reshape_dynamic(self):
         x_val = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float32).reshape((2, 2))
@@ -1025,7 +1022,7 @@ def test_slice_with_size_is_negative_one(self):
 
     @skip_caffe2_backend()
     def test_slice1(self):
-        # FIXME: only 1 dimension supported by caffe2 and msrt
+        # FIXME: only 1 dimension supported by caffe2
         x_val = np.array([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]], [[5, 5, 5], [6, 6, 6]]], dtype=np.float32)
         t1 = tf.constant([1, 0, 0], dtype=tf.int32)
         t2 = tf.constant([1, 1, 3], dtype=tf.int32)