Merge pull request #1329 from pytorch/python_tests

refactor(//tests) : Refactor the test suite

.circleci/config.yml

@@ -435,6 +435,7 @@ commands:
             mkdir -p /tmp/artifacts/test_results
             cd tests/py
             pytest --junitxml=/tmp/artifacts/test_results/api/api_test_results.xml api/
+            pytest --junitxml=/tmp/artifacts/test_results/models/models_test_results.xml models/
             pytest --junitxml=/tmp/artifacts/test_results/integrations/integrations_test_results.xml integrations/
             cd ~/project
 

.github/workflows/docgen.yml

@@ -31,7 +31,7 @@ jobs:
       - name: Set up Python 3.9.4
         uses: actions/setup-python@v2
         with:
-          python-version: 3.9.4 
+          python-version: 3.9.4
       - uses: actions/checkout@v2
         with:
           ref: ${{github.head_ref}}

.github/workflows/linter.yml

@@ -39,7 +39,7 @@ jobs:
           pip3 install -r $GITHUB_WORKSPACE/.github/scripts/requirements.txt
           pip3 install -r $GITHUB_WORKSPACE/requirements-dev.txt
       - name: Lint C++
-        run: | 
+        run: |
           cd $GITHUB_WORKSPACE
           python3 $GITHUB_WORKSPACE/.github/scripts/run_cpp_linter.py
         env:

noxfile.py

@@ -30,6 +30,9 @@
 if USE_HOST_DEPS:
     print("Using dependencies from host python")
 
+# Set epochs to train VGG model for accuracy tests
+EPOCHS = 25
+
 SUPPORTED_PYTHON_VERSIONS = ["3.7", "3.8", "3.9", "3.10"]
 
 nox.options.sessions = [
@@ -63,31 +66,6 @@ def install_torch_trt(session):
         session.run("python", "setup.py", "develop")
 
 
-def download_datasets(session):
-    print(
-        "Downloading dataset to path",
-        os.path.join(TOP_DIR, "examples/int8/training/vgg16"),
-    )
-    session.chdir(os.path.join(TOP_DIR, "examples/int8/training/vgg16"))
-    session.run_always(
-        "wget", "https://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz", external=True
-    )
-    session.run_always("tar", "-xvzf", "cifar-10-binary.tar.gz", external=True)
-    session.run_always(
-        "mkdir",
-        "-p",
-        os.path.join(TOP_DIR, "tests/accuracy/datasets/data"),
-        external=True,
-    )
-    session.run_always(
-        "cp",
-        "-rpf",
-        os.path.join(TOP_DIR, "examples/int8/training/vgg16/cifar-10-batches-bin"),
-        os.path.join(TOP_DIR, "tests/accuracy/datasets/data/cidar-10-batches-bin"),
-        external=True,
-    )
-
-
 def train_model(session):
     session.chdir(os.path.join(TOP_DIR, "examples/int8/training/vgg16"))
     session.install("-r", "requirements.txt")
@@ -107,14 +85,14 @@ def train_model(session):
             "--ckpt-dir",
             "vgg16_ckpts",
             "--epochs",
-            "25",
+            str(EPOCHS),
             env={"PYTHONPATH": PYT_PATH},
         )
 
         session.run_always(
             "python",
             "export_ckpt.py",
-            "vgg16_ckpts/ckpt_epoch25.pth",
+            "vgg16_ckpts/ckpt_epoch" + str(EPOCHS) + ".pth",
             env={"PYTHONPATH": PYT_PATH},
         )
     else:
@@ -130,10 +108,12 @@ def train_model(session):
             "--ckpt-dir",
             "vgg16_ckpts",
             "--epochs",
-            "25",
+            str(EPOCHS),
         )
 
-        session.run_always("python", "export_ckpt.py", "vgg16_ckpts/ckpt_epoch25.pth")
+        session.run_always(
+            "python", "export_ckpt.py", "vgg16_ckpts/ckpt_epoch" + str(EPOCHS) + ".pth"
+        )
 
 
 def finetune_model(session):
@@ -156,17 +136,17 @@ def finetune_model(session):
             "--ckpt-dir",
             "vgg16_ckpts",
             "--start-from",
-            "25",
+            str(EPOCHS),
             "--epochs",
-            "26",
+            str(EPOCHS + 1),
             env={"PYTHONPATH": PYT_PATH},
         )
 
         # Export model
         session.run_always(
             "python",
             "export_qat.py",
-            "vgg16_ckpts/ckpt_epoch26.pth",
+            "vgg16_ckpts/ckpt_epoch" + str(EPOCHS + 1) + ".pth",
             env={"PYTHONPATH": PYT_PATH},
         )
     else:
@@ -182,13 +162,17 @@ def finetune_model(session):
             "--ckpt-dir",
             "vgg16_ckpts",
             "--start-from",
-            "25",
+            str(EPOCHS),
             "--epochs",
-            "26",
+            str(EPOCHS + 1),
         )
 
         # Export model
-        session.run_always("python", "export_qat.py", "vgg16_ckpts/ckpt_epoch26.pth")
+        session.run_always(
+            "python",
+            "export_qat.py",
+            "vgg16_ckpts/ckpt_epoch" + str(EPOCHS + 1) + ".pth",
+        )
 
 
 def cleanup(session):
@@ -219,6 +203,19 @@ def run_base_tests(session):
             session.run_always("pytest", test)
 
 
+def run_model_tests(session):
+    print("Running model tests")
+    session.chdir(os.path.join(TOP_DIR, "tests/py"))
+    tests = [
+        "models",
+    ]
+    for test in tests:
+        if USE_HOST_DEPS:
+            session.run_always("pytest", test, env={"PYTHONPATH": PYT_PATH})
+        else:
+            session.run_always("pytest", test)
+
+
 def run_accuracy_tests(session):
     print("Running accuracy tests")
     session.chdir(os.path.join(TOP_DIR, "tests/py"))
@@ -282,7 +279,7 @@ def run_dla_tests(session):
     print("Running DLA tests")
     session.chdir(os.path.join(TOP_DIR, "tests/py"))
     tests = [
-        "test_api_dla.py",
+        "hw/test_api_dla.py",
     ]
     for test in tests:
         if USE_HOST_DEPS:
@@ -322,21 +319,19 @@ def run_l0_dla_tests(session):
     cleanup(session)
 
 
-def run_l1_accuracy_tests(session):
+def run_l1_model_tests(session):
     if not USE_HOST_DEPS:
         install_deps(session)
         install_torch_trt(session)
-    download_datasets(session)
-    train_model(session)
-    run_accuracy_tests(session)
+    download_models(session)
+    run_model_tests(session)
     cleanup(session)
 
 
 def run_l1_int8_accuracy_tests(session):
     if not USE_HOST_DEPS:
         install_deps(session)
         install_torch_trt(session)
-    download_datasets(session)
     train_model(session)
     finetune_model(session)
     run_int8_accuracy_tests(session)
@@ -347,9 +342,6 @@ def run_l2_trt_compatibility_tests(session):
     if not USE_HOST_DEPS:
         install_deps(session)
         install_torch_trt(session)
-    download_models(session)
-    download_datasets(session)
-    train_model(session)
     run_trt_compatibility_tests(session)
     cleanup(session)
 
@@ -376,9 +368,9 @@ def l0_dla_tests(session):
 
 
 @nox.session(python=SUPPORTED_PYTHON_VERSIONS, reuse_venv=True)
-def l1_accuracy_tests(session):
-    """Checking accuracy performance on various usecases"""
-    run_l1_accuracy_tests(session)
+def l1_model_tests(session):
+    """When a user needs to test the functionality of standard models compilation and results"""
+    run_l1_model_tests(session)
 
 
 @nox.session(python=SUPPORTED_PYTHON_VERSIONS, reuse_venv=True)
@@ -397,13 +389,3 @@ def l2_trt_compatibility_tests(session):
 def l2_multi_gpu_tests(session):
     """Makes sure that Torch-TensorRT can operate on multi-gpu systems"""
     run_l2_multi_gpu_tests(session)
-
-
-@nox.session(python=SUPPORTED_PYTHON_VERSIONS, reuse_venv=True)
-def download_test_models(session):
-    """Grab all the models needed for testing"""
-    try:
-        import torch
-    except ModuleNotFoundError:
-        install_deps(session)
-    download_models(session)

py/torch_tensorrt/ptq.py

@@ -56,6 +56,13 @@ def write_calibration_cache(self, cache):
         return b""
 
 
+# deepcopy (which involves pickling) is performed on the compile_spec internally during compilation.
+# We register this __reduce__ function for pickler to identity the calibrator object returned by DataLoaderCalibrator during deepcopy.
+# This should be the object's local name relative to the module https://docs.python.org/3/library/pickle.html#object.__reduce__
+def __reduce__(self):
+    return self.__class__.__name__
+
+
 class DataLoaderCalibrator(object):
     """
     Constructs a calibrator class in TensorRT and uses pytorch dataloader to load/preproces
@@ -114,24 +121,27 @@ def __new__(cls, *args, **kwargs):
             "get_batch": get_cache_mode_batch if use_cache else get_batch,
             "read_calibration_cache": read_calibration_cache,
             "write_calibration_cache": write_calibration_cache,
+            "__reduce__": __reduce__,  # used when you deepcopy the DataLoaderCalibrator object
         }
 
         # Using type metaclass to construct calibrator class based on algorithm type
         if algo_type == CalibrationAlgo.ENTROPY_CALIBRATION:
             return type(
-                "DataLoaderCalibrator", (_C.IInt8EntropyCalibrator,), attribute_mapping
+                "Int8EntropyCalibrator", (_C.IInt8EntropyCalibrator,), attribute_mapping
             )()
         elif algo_type == CalibrationAlgo.ENTROPY_CALIBRATION_2:
             return type(
-                "DataLoaderCalibrator", (_C.IInt8MinMaxCalibrator,), attribute_mapping
+                "Int8EntropyCalibrator2",
+                (_C.IInt8EntropyCalibrator2,),
+                attribute_mapping,
             )()
         elif algo_type == CalibrationAlgo.LEGACY_CALIBRATION:
             return type(
-                "DataLoaderCalibrator", (_C.IInt8LegacyCalibrator,), attribute_mapping
+                "Int8LegacyCalibrator", (_C.IInt8LegacyCalibrator,), attribute_mapping
             )()
         elif algo_type == CalibrationAlgo.MINMAX_CALIBRATION:
             return type(
-                "DataLoaderCalibrator", (_C.IInt8MinMaxCalibrator,), attribute_mapping
+                "Int8MinMaxCalibrator", (_C.IInt8MinMaxCalibrator,), attribute_mapping
             )()
         else:
             log(

py/torch_tensorrt/ts/_compile_spec.py

@@ -225,7 +225,7 @@ def _parse_input_signature(input_signature: Any):
 
 
 def _parse_compile_spec(compile_spec_: Dict[str, Any]) -> _ts_C.CompileSpec:
-    # TODO: Remove deep copy once collections does not need partial compilation
+    # TODO: Use deepcopy to support partial compilation of collections
     compile_spec = deepcopy(compile_spec_)
     info = _ts_C.CompileSpec()
 
@@ -301,7 +301,7 @@ def _parse_compile_spec(compile_spec_: Dict[str, Any]) -> _ts_C.CompileSpec:
             compile_spec["enabled_precisions"]
         )
 
-    if "calibrator" in compile_spec:
+    if "calibrator" in compile_spec and compile_spec["calibrator"]:
         info.ptq_calibrator = compile_spec["calibrator"]
 
     if "sparse_weights" in compile_spec:

tests/core/lowering/test_module_fallback_passes.cpp

@@ -124,5 +124,5 @@ TEST(Lowering, LowerAndPartitionSimpleModuleFallbackCorrectly) {
   }
 
   auto trt_results = trt_mod.forward(trt_inputs_ivalues).toTensor();
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results, trt_results, 2e-6));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(jit_results, trt_results, 0.99));
 }

tests/core/partitioning/test_fallback_graph_output.cpp

@@ -34,7 +34,7 @@ TEST(Partitioning, ComputeResNet50FallbackGraphCorrectly) {
   auto jit_results = mod.forward(jit_inputs_ivalues).toTensor();
   auto trt_mod = torch_tensorrt::core::CompileGraph(mod, cfg);
   auto trt_results = trt_mod.forward(trt_inputs_ivalues).toTensor();
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results, trt_results, 2e-6));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(jit_results, trt_results, 0.99));
 }
 
 TEST(Partitioning, ComputeMobileNetFallbackGraphCorrectly) {
@@ -64,6 +64,6 @@ TEST(Partitioning, ComputeMobileNetFallbackGraphCorrectly) {
   auto jit_results = mod.forward(jit_inputs_ivalues).toTensor();
   auto trt_mod = torch_tensorrt::core::CompileGraph(mod, cfg);
   auto trt_results = trt_mod.forward(trt_inputs_ivalues).toTensor();
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results, trt_results, 2e-6));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(jit_results, trt_results, 0.99));
 }
 #endif

tests/cpp/test_collections.cpp

@@ -42,7 +42,7 @@ TEST(CppAPITests, TestCollectionStandardTensorInput) {
   auto trt_mod = torch_tensorrt::torchscript::compile(mod, compile_settings);
   auto trt_out = trt_mod.forward(inputs_);
 
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(out.toTensor(), trt_out.toTensor(), 1e-5));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(out.toTensor(), trt_out.toTensor(), 0.99));
 }
 
 TEST(CppAPITests, TestCollectionTupleInput) {
@@ -85,7 +85,7 @@ TEST(CppAPITests, TestCollectionTupleInput) {
   auto trt_mod = torch_tensorrt::torchscript::compile(mod, compile_settings);
   auto trt_out = trt_mod.forward(complex_inputs);
 
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(out.toTensor(), trt_out.toTensor(), 1e-5));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(out.toTensor(), trt_out.toTensor(), 0.99));
 }
 
 TEST(CppAPITests, TestCollectionListInput) {
@@ -144,7 +144,7 @@ TEST(CppAPITests, TestCollectionListInput) {
   LOG_DEBUG("Finish compile");
   auto trt_out = trt_mod.forward(complex_inputs);
 
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(out.toTensor(), trt_out.toTensor(), 1e-5));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(out.toTensor(), trt_out.toTensor(), 0.99));
 }
 
 TEST(CppAPITests, TestCollectionTupleInputOutput) {
@@ -317,4 +317,4 @@ TEST(CppAPITests, TestCollectionComplexModel) {
       out.toTuple()->elements()[0].toTensor(), trt_out.toTuple()->elements()[0].toTensor(), 1e-5));
   ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(
       out.toTuple()->elements()[1].toTensor(), trt_out.toTuple()->elements()[1].toTensor(), 1e-5));
-}
+}

tests/cpp/test_compiled_modules.cpp

@@ -42,7 +42,7 @@ TEST_P(CppAPITests, CompiledModuleIsClose) {
 
   for (size_t i = 0; i < trt_results.size(); i++) {
     ASSERT_TRUE(
-        torch_tensorrt::tests::util::almostEqual(jit_results[i], trt_results[i].reshape_as(jit_results[i]), threshold));
+        torch_tensorrt::tests::util::cosineSimEqual(jit_results[i], trt_results[i].reshape_as(jit_results[i]), 0.99));
   }
 }
 
@@ -52,11 +52,7 @@ INSTANTIATE_TEST_SUITE_P(
     CompiledModuleForwardIsCloseSuite,
     CppAPITests,
     testing::Values(
-        PathAndInput({"tests/modules/resnet18_traced.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 2e-5}),
-        PathAndInput({"tests/modules/resnet50_traced.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 2e-5}),
-        PathAndInput({"tests/modules/mobilenet_v2_traced.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 2e-5}),
         PathAndInput({"tests/modules/resnet18_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 2e-5}),
-        PathAndInput({"tests/modules/resnet50_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 2e-5}),
         PathAndInput({"tests/modules/mobilenet_v2_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 2e-5}),
         PathAndInput({"tests/modules/efficientnet_b0_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}, 8e-3}),
         PathAndInput({"tests/modules/bert_base_uncased_traced.jit.pt", {{1, 14}, {1, 14}}, {at::kInt, at::kInt}, 8e-2}),

tests/cpp/test_module_fallback.cpp

@@ -30,7 +30,7 @@ TEST(CppAPITest, ResNetModuleFallbacksCorrectly) {
   auto jit_results = mod.forward(jit_inputs_ivalues).toTensor();
   auto trt_mod = torch_tensorrt::ts::compile(mod, cfg);
   auto trt_results = trt_mod.forward(trt_inputs_ivalues).toTensor();
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results, trt_results, 2e-6));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(jit_results, trt_results, 0.99));
 }
 
 TEST(CppAPITest, MobileNetModuleFallbacksCorrectlyWithOneEngine) {
@@ -69,6 +69,6 @@ TEST(CppAPITest, MobileNetModuleFallbacksCorrectlyWithOneEngine) {
   ASSERT_TRUE(trt_count == 1);
 
   auto trt_results = trt_mod.forward(trt_inputs_ivalues).toTensor();
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results, trt_results, 2e-6));
+  ASSERT_TRUE(torch_tensorrt::tests::util::cosineSimEqual(jit_results, trt_results, 0.99));
 }
 #endif