feat: Refactor FX APIs under dynamo namespace for parity with TS APIs

.circleci/config.yml

@@ -508,6 +508,7 @@ commands:
       - store_artifacts:
           path: /tmp/testlogs
 
+# =================== FX tests start ======================== #
   test-fx_core:
     description: "Test the fx core"
     steps:
@@ -707,6 +708,61 @@ commands:
       - store_artifacts:
           path: /tmp/testlogs
 
+# =================== FX tests end ======================== #
+
+# =================== Dynamo tests start ======================== #
+  test-dynamo-fx_ts:
+    description: "Test the Dynamo fx_ts_compat path"
+    steps:
+      - run:
+          name: Run Dynamo fx_ts_compat core tests
+          command: |
+            cd py/torch_tensorrt/dynamo/fx_ts_compat/test
+            pushd core/
+            pytest --junitxml=/tmp/artifacts/test_results/dynamo/fx_ts_compat/test_results.xml
+            popd
+
+      - store_test_results:
+          path: /tmp/artifacts
+      - store_artifacts:
+          path: /tmp/testlogs
+
+  test-dynamo-torch_compile-core:
+    description: "Test the Dynamo torch_compile path"
+    steps:
+      - run:
+          name: Run Dynamo torch_compile core tests
+          command: |
+            cd py/torch_tensorrt/dynamo/torch_compile
+            pushd test/
+            pytest --junitxml=/tmp/artifacts/test_results/dynamo/torch_compile/test_results.xml
+            popd
+
+      - store_test_results:
+          path: /tmp/artifacts
+      - store_artifacts:
+          path: /tmp/testlogs
+
+  test-dynamo-torch_compile:
+    description: "Test the Dynamo torch_compile path"
+    steps:
+      - run:
+          name: Run Dynamo torch_compile E2E tests
+          command: |
+            cd py/torch_tensorrt/dynamo/
+            pushd test/
+            pip3 install timm
+            pip3 install transformers
+            pytest --junitxml=/tmp/artifacts/test_results/dynamo/torch_compile/test_results.xml --ir torch_compile
+            popd
+
+      - store_test_results:
+          path: /tmp/artifacts
+      - store_artifacts:
+          path: /tmp/testlogs
+
+# =================== Dynamo tests end ======================== #
+
 # Define a job to be invoked later in a workflow.
 # See: https://circleci.com/docs/2.0/configuration-reference/#jobs
 jobs:
@@ -883,6 +939,39 @@ jobs:
       - dump-test-env
       - test-fx-no-aten
 
+  test-py-dynamo-x86_64-linux:
+    parameters:
+      torch-build:
+        type: string
+      torch-build-index:
+        type: string
+      trt-version-long:
+        type: string
+    machine:
+      image: ubuntu-2004-cuda-11.4:202110-01
+    resource_class: gpu.nvidia.large
+    steps:
+      - checkout
+      - attach_workspace:
+          at: /tmp/dist/
+      - install-torch-from-index:
+          torch-build:  << parameters.torch-build >>
+          torch-build-index: << parameters.torch-build-index >>
+      - create-py-env:
+          trt-version-long: << parameters.trt-version-long >>
+      - install-cudnn
+      # - run:
+      #     name: "Set LD_LIBRARY_PATH path to include the installed CUDNN"
+      #     command: export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu/:$LD_LIBRARY_PATH
+      - run:
+          name: "Install torch-tensorrt"
+          command: pip3 install --pre /tmp/dist/x86_64-linux/*cp39-cp39*.whl
+      # We install torch after torch-trt because pip automatically enforces the version constraint otherwise
+      - dump-test-env
+      - test-dynamo-torch_compile
+      - test-dynamo-torch_compile-core
+      - test-dynamo-fx_ts
+
   package-x86_64-linux:
     parameters:
       enabled:
@@ -1261,6 +1350,13 @@ workflows:
           requires:
             - build-x86_64-linux
 
+      - test-py-dynamo-x86_64-linux:
+          torch-build: << pipeline.parameters.torch-build >>
+          torch-build-index: << pipeline.parameters.torch-build-index >>
+          trt-version-long: << pipeline.parameters.trt-version-long >>
+          requires:
+            - build-x86_64-linux
+
       - build-x86_64-linux:
           name: build-x86_64-linux-legacy
           torch-build: << pipeline.parameters.torch-build-legacy >>
@@ -1328,6 +1424,13 @@ workflows:
           requires:
             - package-x86_64-linux
 
+      - test-py-dynamo-x86_64-linux:
+          torch-build: << pipeline.parameters.torch-build >>
+          torch-build-index: << pipeline.parameters.torch-build-index >>
+          trt-version-long: << pipeline.parameters.trt-version-long >>
+          requires:
+            - package-x86_64-linux
+
   on-push:
     jobs:
       - build-x86_64-linux:
@@ -1357,6 +1460,13 @@ workflows:
           requires:
             - build-x86_64-linux
 
+      - test-py-dynamo-x86_64-linux:
+          torch-build: << pipeline.parameters.torch-build >>
+          torch-build-index: << pipeline.parameters.torch-build-index >>
+          trt-version-long: << pipeline.parameters.trt-version-long >>
+          requires:
+            - build-x86_64-linux
+
       - build-x86_64-linux-cmake:
           torch-build: << pipeline.parameters.torch-build >>
           torch-build-index: << pipeline.parameters.torch-build-index >>

py/setup.py

@@ -356,6 +356,10 @@ def run(self):
         "torch_tensorrt.fx.tools",
         "torch_tensorrt.fx.tracer.acc_tracer",
         "torch_tensorrt.fx.tracer.dispatch_tracer",
+        "torch_tensorrt.dynamo",
+        "torch_tensorrt.dynamo.fx_ts_compat",
+        "torch_tensorrt.dynamo.fx_ts_compat.passes",
+        "torch_tensorrt.dynamo.fx_ts_compat.tools",
     ]
     package_dir = {
         "torch_tensorrt.fx": "torch_tensorrt/fx",
@@ -364,11 +368,47 @@ def run(self):
         "torch_tensorrt.fx.tools": "torch_tensorrt/fx/tools",
         "torch_tensorrt.fx.tracer.acc_tracer": "torch_tensorrt/fx/tracer/acc_tracer",
         "torch_tensorrt.fx.tracer.dispatch_tracer": "torch_tensorrt/fx/tracer/dispatch_tracer",
+        "torch_tensorrt.dynamo": "torch_tensorrt/dynamo",
+        "torch_tensorrt.dynamo.fx_ts_compat": "torch_tensorrt/dynamo/fx_ts_compat",
+        "torch_tensorrt.dynamo.fx_ts_compat.passes": "torch_tensorrt/dynamo/fx_ts_compat/passes",
+        "torch_tensorrt.dynamo.fx_ts_compat.tools": "torch_tensorrt/dynamo/fx_ts_compat/tools",
     }
 
 with open("README.md", "r", encoding="utf-8") as fh:
     long_description = fh.read()
 
+if FX_ONLY:
+    package_data_list = [
+        "_Input.py",
+    ]
+else:
+    package_data_list = [
+        "lib/*",
+        "include/torch_tensorrt/*.h",
+        "include/torch_tensorrt/core/*.h",
+        "include/torch_tensorrt/core/conversion/*.h",
+        "include/torch_tensorrt/core/conversion/conversionctx/*.h",
+        "include/torch_tensorrt/core/conversion/converters/*.h",
+        "include/torch_tensorrt/core/conversion/evaluators/*.h",
+        "include/torch_tensorrt/core/conversion/tensorcontainer/*.h",
+        "include/torch_tensorrt/core/conversion/var/*.h",
+        "include/torch_tensorrt/core/ir/*.h",
+        "include/torch_tensorrt/core/lowering/*.h",
+        "include/torch_tensorrt/core/lowering/passes/*.h",
+        "include/torch_tensorrt/core/partitioning/*.h",
+        "include/torch_tensorrt/core/partitioning/segmentedblock/*.h",
+        "include/torch_tensorrt/core/partitioning/partitioninginfo/*.h",
+        "include/torch_tensorrt/core/partitioning/partitioningctx/*.h",
+        "include/torch_tensorrt/core/plugins/*.h",
+        "include/torch_tensorrt/core/plugins/impl/*.h",
+        "include/torch_tensorrt/core/runtime/*.h",
+        "include/torch_tensorrt/core/util/*.h",
+        "include/torch_tensorrt/core/util/logging/*.h",
+        "bin/*",
+        "BUILD",
+        "WORKSPACE",
+    ]
+
 setup(
     name="torch_tensorrt",
     version=__version__,
@@ -412,32 +452,7 @@ def run(self):
     python_requires=">=3.7",
     include_package_data=True,
     package_data={
-        "torch_tensorrt": [
-            "lib/*",
-            "include/torch_tensorrt/*.h",
-            "include/torch_tensorrt/core/*.h",
-            "include/torch_tensorrt/core/conversion/*.h",
-            "include/torch_tensorrt/core/conversion/conversionctx/*.h",
-            "include/torch_tensorrt/core/conversion/converters/*.h",
-            "include/torch_tensorrt/core/conversion/evaluators/*.h",
-            "include/torch_tensorrt/core/conversion/tensorcontainer/*.h",
-            "include/torch_tensorrt/core/conversion/var/*.h",
-            "include/torch_tensorrt/core/ir/*.h",
-            "include/torch_tensorrt/core/lowering/*.h",
-            "include/torch_tensorrt/core/lowering/passes/*.h",
-            "include/torch_tensorrt/core/partitioning/*.h",
-            "include/torch_tensorrt/core/partitioning/segmentedblock/*.h",
-            "include/torch_tensorrt/core/partitioning/partitioninginfo/*.h",
-            "include/torch_tensorrt/core/partitioning/partitioningctx/*.h",
-            "include/torch_tensorrt/core/plugins/*.h",
-            "include/torch_tensorrt/core/plugins/impl/*.h",
-            "include/torch_tensorrt/core/runtime/*.h",
-            "include/torch_tensorrt/core/util/*.h",
-            "include/torch_tensorrt/core/util/logging/*.h",
-            "bin/*",
-            "BUILD",
-            "WORKSPACE",
-        ],
+        "torch_tensorrt": package_data_list,
     },
     exclude_package_data={
         "": ["*.cpp"],

py/torch_tensorrt/_Device.py

@@ -1,11 +1,18 @@
 import torch
 
-from torch_tensorrt import _enums
+# from torch_tensorrt import _enums
+import tensorrt as trt
 from torch_tensorrt import logging
-from torch_tensorrt import _C
-
 import warnings
 
+try:
+    from torch_tensorrt import _C
+except:
+    warnings.warn(
+        "Unable to import _C extension of Torch-TensorRT. Some methods might be unavailable. You can ignore this error if you're \
+                  not using any functions dependent on internal C++ APIs"
+    )
+
 
 class Device(object):
     """
@@ -51,7 +58,7 @@ def __init__(self, *args, **kwargs):
                 )
             else:
                 (self.device_type, id) = Device._parse_device_str(args[0])
-                if self.device_type == _enums.DeviceType.GPU:
+                if self.device_type == trt.DeviceType.GPU:
                     self.gpu_id = id
                 else:
                     self.dla_core = id
@@ -64,7 +71,7 @@ def __init__(self, *args, **kwargs):
         elif len(args) == 0:
             if "gpu_id" in kwargs or "dla_core" in kwargs:
                 if "dla_core" in kwargs:
-                    self.device_type = _enums.DeviceType.DLA
+                    self.device_type = trt.DeviceType.DLA
                     self.dla_core = kwargs["dla_core"]
                     if "gpu_id" in kwargs:
                         self.gpu_id = kwargs["gpu_id"]
@@ -76,7 +83,7 @@ def __init__(self, *args, **kwargs):
                         )
                 else:
                     self.gpu_id = kwargs["gpu_id"]
-                    self.device_type = _enums.DeviceType.GPU
+                    self.device_type = trt.DeviceType.GPU
             else:
                 raise ValueError(
                     "Either gpu_id or dla_core or both must be defined if no string with device specs is provided as an arg"
@@ -97,15 +104,23 @@ def __init__(self, *args, **kwargs):
     def __str__(self) -> str:
         return (
             "Device(type={}, gpu_id={}".format(self.device_type, self.gpu_id) + ")"
-            if self.device_type == _enums.DeviceType.GPU
+            if self.device_type == trt.DeviceType.GPU
             else ", dla_core={}, allow_gpu_fallback={}".format(
                 self.dla_core, self.allow_gpu_fallback
             )
         )
 
     def _to_internal(self) -> _C.Device:
         internal_dev = _C.Device()
-        internal_dev.device_type = self.device_type
+        if self.device_type == trt.DeviceType.GPU:
+            internal_dev.device_type = _C.DeviceType.GPU
+        elif self.device_type == trt.DeviceType.DLA:
+            internal_dev.device_type = _C.DeviceType.DLA
+        else:
+            raise ValueError(
+                "Invalid DeviceType detected while parsing the Device class"
+            )
+
         internal_dev.gpu_id = self.gpu_id
         internal_dev.dla_core = self.dla_core
         internal_dev.allow_gpu_fallback = self.allow_gpu_fallback
@@ -136,6 +151,6 @@ def _parse_device_str(s):
         s = s.lower()
         spec = s.split(":")
         if spec[0] == "gpu" or spec[0] == "cuda":
-            return (_enums.DeviceType.GPU, int(spec[1]))
+            return (trt.DeviceType.GPU, int(spec[1]))
         elif spec[0] == "dla":
-            return (_enums.DeviceType.DLA, int(spec[1]))
+            return (trt.DeviceType.DLA, int(spec[1]))