Cleanup naming of test input to use .onnx for models. (#1337)

* Cleanup naming of test input to use .onnx for models.

* Remove file deleted on master

docs/python/examples/plot_pipeline.py

@@ -21,7 +21,7 @@ That's the most simple way.
 """
 
 from onnxruntime.datasets import get_example
-example1 = get_example("mul_1.pb")
+example1 = get_example("mul_1.onnx")
 
 import onnx
 model = onnx.load(example1)  # model is a ModelProto protobuf message

docs/python/examples/plot_profiling.py

@@ -19,7 +19,7 @@ from onnxruntime.datasets import get_example
 #########################
 # Let's load a very simple model and compute some prediction.
 
-example1 = get_example("mul_1.pb")
+example1 = get_example("mul_1.onnx")
 sess = rt.InferenceSession(example1)
 input_name = sess.get_inputs()[0].name
 

onnxruntime/test/framework/float_16_test.cc

@@ -96,7 +96,7 @@ ONNX_NAMESPACE::OpSchema GetMulFP16Schema() {
   return schema;
 }
 
-static const std::string MUL_MODEL_URI = "testdata/mul_16.pb";
+static const std::string MUL_MODEL_URI = "testdata/mul_16.onnx";
 
 void RunSession(InferenceSession& session_object,
                 RunOptions& run_options,

onnxruntime/test/framework/inference_session_test.cc

@@ -123,8 +123,8 @@ class FuseExecutionProvider : public IExecutionProvider {
 namespace test {
 static void VerifyOutputs(const std::vector<OrtValue>& fetches, const std::vector<int64_t>& expected_dims,
                           const std::vector<float>& expected_values);
-static const std::string MODEL_URI = "testdata/mul_1.pb";
-static const std::string MODEL_URI_NO_OPSET = "testdata/mul_1.pb.noopset";
+static const std::string MODEL_URI = "testdata/mul_1.onnx";
+static const std::string MODEL_URI_NO_OPSET = "testdata/mul_1.noopset.onnx";
 //static const std::string MODEL_URI = "./testdata/squeezenet/model.onnx"; // TODO enable this after we've weights?
 
 static void CreateMatMulModel(std::unique_ptr<onnxruntime::Model>& p_model, ProviderType provider_type) {
@@ -1122,7 +1122,7 @@ TEST(ExecutionProviderTest, FunctionInlineTest) {
 TEST(InferenceSessionTests, TestTruncatedSequence) {
   // model/data generated by <repo>/onnxruntime/test/testdata/CNTK/gen.py GenScan()
   // Manually updated to have IR version of 4.
-  static const std::string LSTM_MODEL_URI = "testdata/scan_1.pb";
+  static const std::string LSTM_MODEL_URI = "testdata/scan_1.onnx";
   // This model is a 4x forward LSTM. Parse it to find out mapping between init_state input/output
   ONNX_NAMESPACE::ModelProto model_proto;
   int model_fd;

onnxruntime/test/framework/local_kernel_registry_test.cc

@@ -184,11 +184,11 @@ OpKernel* CreateOptionalOpKernel(const OpKernelInfo& kernel_info) {
   return new OptionalOpKernel<float>(kernel_info);
 }
 
-static const std::string MUL_MODEL_URI = "testdata/mul_1.pb";
-static const std::string FOO_MODEL_URI = "testdata/foo_1.pb";
-static const std::string FOO_TRUNCATE_MODEL_URI = "testdata/foo_2.pb";
+static const std::string MUL_MODEL_URI = "testdata/mul_1.onnx";
+static const std::string FOO_MODEL_URI = "testdata/foo_1.onnx";
+static const std::string FOO_TRUNCATE_MODEL_URI = "testdata/foo_2.onnx";
 
-static const std::string OPTIONAL_MODEL1_URI = "testdata/optional_1.pb";
+static const std::string OPTIONAL_MODEL1_URI = "testdata/optional_1.onnx";
 
 void RunSession(InferenceSession& session_object,
                 RunOptions& run_options,

onnxruntime/test/ir/graph_test.cc

@@ -322,9 +322,9 @@ TEST(ResolvingGraphTest, GraphConstruction_CheckIsAcyclic) {
   auto status = graph.Resolve();
   EXPECT_TRUE(status.IsOK()) << status.ErrorMessage();
 
-  EXPECT_TRUE(Model::Save(model, "graph_1.pb").IsOK());
+  EXPECT_TRUE(Model::Save(model, "graph_1.onnx").IsOK());
   std::shared_ptr<Model> model2;
-  EXPECT_TRUE(Model::Load("graph_1.pb", model2).IsOK());
+  EXPECT_TRUE(Model::Load("graph_1.onnx", model2).IsOK());
 
   auto model_proto = model.ToProto();
   auto model_proto2 = model2->ToProto();
@@ -709,9 +709,9 @@ TEST(ResolvingGraphTest, GraphConstruction_TypeInference) {
   EXPECT_EQ("node_4_out_1", graph.GetOutputs()[0]->Name());
   EXPECT_EQ(2, graph.GetInputs().size());
 
-  EXPECT_TRUE(Model::Save(model, "model_x.pb").IsOK());
+  EXPECT_TRUE(Model::Save(model, "model_x.onnx").IsOK());
   std::shared_ptr<Model> loaded_model;
-  EXPECT_TRUE(Model::Load("model_x.pb", loaded_model).IsOK());
+  EXPECT_TRUE(Model::Load("model_x.onnx", loaded_model).IsOK());
   EXPECT_EQ(2, loaded_model->MainGraph().GetInputs().size());
 
   auto& graph_proto = graph.ToGraphProto();

onnxruntime/test/providers/memcpy_test.cc

@@ -32,7 +32,7 @@ TEST(MemcpyTest, copy1) {
   kernel_registry_manager.RegisterKernels(execution_providers);
 
   onnx::ModelProto mp;
-  std::ifstream model_istream("testdata/matmul_1.pb", std::ifstream::in | std::ifstream::binary);
+  std::ifstream model_istream("testdata/matmul_1.onnx", std::ifstream::in | std::ifstream::binary);
   google::protobuf::io::IstreamInputStream zero_copy_input(&model_istream);
   const bool result = mp.ParseFromZeroCopyStream(&zero_copy_input) && model_istream.eof();
   ASSERT_TRUE(result);

onnxruntime/test/python/onnxruntime_test_python.py

@@ -32,7 +32,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_allclose(output_expected, res[0], rtol=1e-05, atol=1e-08)
 
     def testRunModel(self):
-        sess = onnxrt.InferenceSession(self.get_name("mul_1.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("mul_1.onnx"))
         x = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float32)
         input_name = sess.get_inputs()[0].name
         self.assertEqual(input_name, "X")
@@ -47,7 +47,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_allclose(output_expected, res[0], rtol=1e-05, atol=1e-08)
 
     def testRunModelFromBytes(self):
-        with open(self.get_name("mul_1.pb"), "rb") as f:
+        with open(self.get_name("mul_1.onnx"), "rb") as f:
             content = f.read()
         sess = onnxrt.InferenceSession(content)
         x = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float32)
@@ -64,7 +64,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_allclose(output_expected, res[0], rtol=1e-05, atol=1e-08)
 
     def testRunModel2(self):
-        sess = onnxrt.InferenceSession(self.get_name("matmul_1.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("matmul_1.onnx"))
         x = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float32)
         input_name = sess.get_inputs()[0].name
         self.assertEqual(input_name, "X")
@@ -82,7 +82,7 @@ class TestInferenceSession(unittest.TestCase):
         so = onnxrt.SessionOptions()
         so.session_log_verbosity_level = 1
         so.session_logid = "MultiThreadsTest"
-        sess = onnxrt.InferenceSession(self.get_name("mul_1.pb"), sess_options=so)
+        sess = onnxrt.InferenceSession(self.get_name("mul_1.onnx"), sess_options=so)
         ro1 = onnxrt.RunOptions()
         ro1.run_tag =  "thread1"
         t1 = threading.Thread(target=self.run_model, args = (sess, ro1))
@@ -99,7 +99,7 @@ class TestInferenceSession(unittest.TestCase):
         self.assertTrue('CPU' in device or 'GPU' in device)
 
     def testRunModelSymbolicInput(self):
-        sess = onnxrt.InferenceSession(self.get_name("matmul_2.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("matmul_2.onnx"))
         x = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float32)
         input_name = sess.get_inputs()[0].name
         self.assertEqual(input_name, "X")
@@ -116,7 +116,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_allclose(output_expected, res[0], rtol=1e-05, atol=1e-08)
 
     def testBooleanInputs(self):
-        sess = onnxrt.InferenceSession(self.get_name("logicaland.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("logicaland.onnx"))
         a = np.array([[True, True], [False, False]], dtype=np.bool)
         b = np.array([[True, False], [True, False]], dtype=np.bool)
 
@@ -148,7 +148,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_equal(output_expected, res[0])
 
     def testStringInput1(self):
-        sess = onnxrt.InferenceSession(self.get_name("identity_string.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("identity_string.onnx"))
         x = np.array(['this', 'is', 'identity', 'test'], dtype=np.str).reshape((2,2))
 
         x_name = sess.get_inputs()[0].name
@@ -169,7 +169,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_equal(x, res[0])
 
     def testStringInput2(self):
-        sess = onnxrt.InferenceSession(self.get_name("identity_string.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("identity_string.onnx"))
         x = np.array(['Olá', '你好', '여보세요', 'hello'], dtype=np.unicode).reshape((2,2))
 
         x_name = sess.get_inputs()[0].name
@@ -190,7 +190,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_equal(x, res[0])
         
     def testInputBytes(self):
-        sess = onnxrt.InferenceSession(self.get_name("identity_string.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("identity_string.onnx"))
         x = np.array([b'this', b'is', b'identity', b'test']).reshape((2,2))
 
         x_name = sess.get_inputs()[0].name
@@ -211,7 +211,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_equal(x, res[0].astype('|S8'))        
 
     def testInputObject(self):
-        sess = onnxrt.InferenceSession(self.get_name("identity_string.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("identity_string.onnx"))
         x = np.array(['this', 'is', 'identity', 'test'], object).reshape((2,2))
 
         x_name = sess.get_inputs()[0].name
@@ -232,7 +232,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_equal(x, res[0])        
 
     def testInputVoid(self):
-        sess = onnxrt.InferenceSession(self.get_name("identity_string.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("identity_string.onnx"))
         x = np.array([b'this', b'is', b'identity', b'test'], np.void).reshape((2,2))
 
         x_name = sess.get_inputs()[0].name
@@ -256,7 +256,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_equal(expr, res[0])
 
     def testConvAutoPad(self):
-        sess = onnxrt.InferenceSession(self.get_name("conv_autopad.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("conv_autopad.onnx"))
         x = np.array(25 * [1.0], dtype=np.float32).reshape((1,1,5,5))
 
         x_name = sess.get_inputs()[0].name
@@ -282,7 +282,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_allclose(output_expected, res[0])
 
     def testZipMapStringFloat(self):
-        sess = onnxrt.InferenceSession(self.get_name("zipmap_stringfloat.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("zipmap_stringfloat.onnx"))
         x = np.array([1.0, 0.0, 3.0, 44.0, 23.0, 11.0], dtype=np.float32).reshape((2,3))
 
         x_name = sess.get_inputs()[0].name
@@ -301,7 +301,7 @@ class TestInferenceSession(unittest.TestCase):
         self.assertEqual(output_expected, res[0])
 
     def testZipMapInt64Float(self):
-        sess = onnxrt.InferenceSession(self.get_name("zipmap_int64float.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("zipmap_int64float.onnx"))
         x = np.array([1.0, 0.0, 3.0, 44.0, 23.0, 11.0], dtype=np.float32).reshape((2,3))
 
         x_name = sess.get_inputs()[0].name
@@ -320,7 +320,7 @@ class TestInferenceSession(unittest.TestCase):
 
     def testRaiseWrongNumInputs(self):
         with self.assertRaises(ValueError) as context:
-            sess = onnxrt.InferenceSession(self.get_name("logicaland.pb"))
+            sess = onnxrt.InferenceSession(self.get_name("logicaland.onnx"))
             a = np.array([[True, True], [False, False]], dtype=np.bool)
             res = sess.run([], {'input:0': a})
 
@@ -340,7 +340,7 @@ class TestInferenceSession(unittest.TestCase):
     def testProfilerWithSessionOptions(self):
         so = onnxrt.SessionOptions()
         so.enable_profiling = True
-        sess = onnxrt.InferenceSession(self.get_name("mul_1.pb"), sess_options=so)
+        sess = onnxrt.InferenceSession(self.get_name("mul_1.onnx"), sess_options=so)
         x = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float32)
         sess.run([], {'X': x})
         profile_file = sess.end_profiling()
@@ -399,7 +399,7 @@ class TestInferenceSession(unittest.TestCase):
         np.testing.assert_allclose(output_expected, res[0], rtol=1e-05, atol=1e-08)
 
     def testLabelEncoder(self):
-        sess = onnxrt.InferenceSession(self.get_name("LabelEncoder.pb"))
+        sess = onnxrt.InferenceSession(self.get_name("LabelEncoder.onnx"))
         input_name = sess.get_inputs()[0].name
         self.assertEqual(input_name, "input")
         input_type = str(sess.get_inputs()[0].type)

onnxruntime/test/python/onnxruntime_test_python_backend.py

@@ -29,7 +29,7 @@ class TestBackend(unittest.TestCase):
         raise FileNotFoundError("Unable to find '{0}' or '{1}' or '{2}'".format(name, rel, res))
 
     def testRunModel(self):
-        name = self.get_name("mul_1.pb")
+        name = self.get_name("mul_1.onnx")
         rep = backend.prepare(name)
         x = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float32)
         res = rep.run(x)

onnxruntime/test/server/unit_tests/executor_test.cc

@@ -14,7 +14,7 @@ namespace server {
 namespace test {
 
 TEST(ExecutorTests, TestMul_1) {
-  const static auto model_file = "testdata/mul_1.pb";
+  const static auto model_file = "testdata/mul_1.onnx";
   const static auto input_json = R"({"inputs":{"X":{"dims":[3,2],"dataType":1,"floatData":[1,2,3,4,5,6]}},"outputFilter":["Y"]})";
   const static auto expected = R"({"outputs":{"Y":{"dims":["3","2"],"dataType":1,"floatData":[1,4,9,16,25,36]}}})";
 

onnxruntime/test/server/unit_tests/server_configuration_test.cc

@@ -13,7 +13,7 @@ namespace test {
 TEST(ConfigParsingTests, AllArgs) {
   char* test_argv[] = {
       const_cast<char*>("/path/to/binary"),
-      const_cast<char*>("--model_path"), const_cast<char*>("testdata/mul_1.pb"),
+      const_cast<char*>("--model_path"), const_cast<char*>("testdata/mul_1.onnx"),
       const_cast<char*>("--address"), const_cast<char*>("4.4.4.4"),
       const_cast<char*>("--http_port"), const_cast<char*>("80"),
       const_cast<char*>("--num_http_threads"), const_cast<char*>("1"),
@@ -22,7 +22,7 @@ TEST(ConfigParsingTests, AllArgs) {
   onnxruntime::server::ServerConfiguration config{};
   Result res = config.ParseInput(11, test_argv);
   EXPECT_EQ(res, Result::ContinueSuccess);
-  EXPECT_EQ(config.model_path, "testdata/mul_1.pb");
+  EXPECT_EQ(config.model_path, "testdata/mul_1.onnx");
   EXPECT_EQ(config.address, "4.4.4.4");
   EXPECT_EQ(config.http_port, 80);
   EXPECT_EQ(config.num_http_threads, 1);
@@ -32,13 +32,13 @@ TEST(ConfigParsingTests, AllArgs) {
 TEST(ConfigParsingTests, Defaults) {
   char* test_argv[] = {
       const_cast<char*>("/path/to/binary"),
-      const_cast<char*>("--model"), const_cast<char*>("testdata/mul_1.pb"),
+      const_cast<char*>("--model"), const_cast<char*>("testdata/mul_1.onnx"),
       const_cast<char*>("--num_http_threads"), const_cast<char*>("3")};
 
   onnxruntime::server::ServerConfiguration config{};
   Result res = config.ParseInput(5, test_argv);
   EXPECT_EQ(res, Result::ContinueSuccess);
-  EXPECT_EQ(config.model_path, "testdata/mul_1.pb");
+  EXPECT_EQ(config.model_path, "testdata/mul_1.onnx");
   EXPECT_EQ(config.address, "0.0.0.0");
   EXPECT_EQ(config.http_port, 8001);
   EXPECT_EQ(config.num_http_threads, 3);
@@ -82,7 +82,7 @@ TEST(ConfigParsingTests, WrongLoggingLevel) {
   char* test_argv[] = {
       const_cast<char*>("/path/to/binary"),
       const_cast<char*>("--log_level"), const_cast<char*>("not a logging level"),
-      const_cast<char*>("--model_path"), const_cast<char*>("testdata/mul_1.pb"),
+      const_cast<char*>("--model_path"), const_cast<char*>("testdata/mul_1.onnx"),
       const_cast<char*>("--address"), const_cast<char*>("4.4.4.4"),
       const_cast<char*>("--http_port"), const_cast<char*>("80"),
       const_cast<char*>("--num_http_threads"), const_cast<char*>("1")};

onnxruntime/test/shared_lib/test_inference.cc

@@ -114,10 +114,10 @@ void TestInference(Ort::Env& env, T model_uri,
                &value_y);
 }
 
-static constexpr PATH_TYPE MODEL_URI = TSTR("testdata/mul_1.pb");
-static constexpr PATH_TYPE CUSTOM_OP_MODEL_URI = TSTR("testdata/foo_1.pb");
+static constexpr PATH_TYPE MODEL_URI = TSTR("testdata/mul_1.onnx");
+static constexpr PATH_TYPE CUSTOM_OP_MODEL_URI = TSTR("testdata/foo_1.onnx");
 #ifdef ENABLE_LANGUAGE_INTEROP_OPS
-static constexpr PATH_TYPE PYOP_FLOAT_MODEL_URI = TSTR("testdata/pyop_1.pb");
+static constexpr PATH_TYPE PYOP_FLOAT_MODEL_URI = TSTR("testdata/pyop_1.onnx");
 #endif
 
 class CApiTestWithProvider : public CApiTest,

onnxruntime/test/shared_lib/test_model_loading.cc

@@ -170,7 +170,7 @@ TEST_F(CApiTest, model_with_external_data) {
 }
 
 TEST_F(CApiTest, model_from_array) {
-  const char* model_path = "testdata/matmul_1.pb";
+  const char* model_path = "testdata/matmul_1.onnx";
   std::vector<char> buffer;
   {
     std::ifstream file(model_path, std::ios::binary | std::ios::ate);

onnxruntime/test/tvm/tvm_basic_test.cc

@@ -303,7 +303,7 @@ static void RunSession(InferenceSession& session_object,
     ASSERT_EQ(found[i], values_y[i]);
 }
 
-static const std::string MODEL_URI = "testdata/fuse_mul_1.pb";
+static const std::string MODEL_URI = "testdata/fuse_mul_1.onnx";
 
 TEST(TVMTest, CodeGen_Demo_for_Fuse_Mul) {
   SessionOptions so;

setup.py

@@ -139,7 +139,7 @@ if '--use_openvino' in sys.argv:
   sys.argv.remove('--use_openvino')
 
 # Additional examples
-examples_names = ["mul_1.pb", "logreg_iris.onnx", "sigmoid.onnx"]
+examples_names = ["mul_1.onnx", "logreg_iris.onnx", "sigmoid.onnx"]
 examples = [path.join('datasets', x) for x in examples_names]
 
 # Extra files such as EULA and ThirdPartyNotices