chore/fix: Update TRTInterpreter impl in Dynamo compile [1 / x]

py/torch_tensorrt/dynamo/backend/__init__.py

@@ -14,7 +14,7 @@
 from torch_tensorrt.dynamo.backend._defaults import (
     PRECISION,
     DEBUG,
-    MAX_WORKSPACE_SIZE,
+    WORKSPACE_SIZE,
     MIN_BLOCK_SIZE,
     PASS_THROUGH_BUILD_FAILURES,
 )
@@ -35,7 +35,7 @@ def compile(
     debug=DEBUG,
     capability=EngineCapability.default,
     num_avg_timing_iters=1,
-    workspace_size=MAX_WORKSPACE_SIZE,
+    workspace_size=WORKSPACE_SIZE,
     dla_sram_size=1048576,
     dla_local_dram_size=1073741824,
     dla_global_dram_size=536870912,
@@ -105,7 +105,7 @@ def compile(
 def create_backend(
     precision: LowerPrecision = PRECISION,
     debug: bool = DEBUG,
-    workspace_size: int = MAX_WORKSPACE_SIZE,
+    workspace_size: int = WORKSPACE_SIZE,
     min_block_size: int = MIN_BLOCK_SIZE,
     torch_executed_ops: Sequence[str] = set(),
     pass_through_build_failures: bool = PASS_THROUGH_BUILD_FAILURES,
@@ -114,10 +114,12 @@ def create_backend(
     """Create torch.compile backend given specified arguments
 
     Args:
-        precision:
-        debug: Whether to print out verbose debugging information
-        workspace_size: Maximum workspace TRT is allowed to use for the module
         precision: Model Layer precision
+        debug: Whether to print out verbose debugging information
+        workspace_size: Workspace TRT is allowed to use for the module (0 is default)
+        min_block_size: Minimum number of operators per TRT-Engine Block
+        torch_executed_ops: Sequence of operations to run in Torch, regardless of converter coverage
+        pass_through_build_failures: Whether to fail on TRT engine build errors (True) or not (False)
     Returns:
         Backend for torch.compile
     """

py/torch_tensorrt/dynamo/backend/_defaults.py

@@ -3,6 +3,6 @@
 
 PRECISION = LowerPrecision.FP32
 DEBUG = False
-MAX_WORKSPACE_SIZE = 20 << 30
+WORKSPACE_SIZE = 0
 MIN_BLOCK_SIZE = 5
 PASS_THROUGH_BUILD_FAILURES = False

py/torch_tensorrt/dynamo/backend/_settings.py

@@ -5,7 +5,7 @@
 from torch_tensorrt.dynamo.backend._defaults import (
     PRECISION,
     DEBUG,
-    MAX_WORKSPACE_SIZE,
+    WORKSPACE_SIZE,
     MIN_BLOCK_SIZE,
     PASS_THROUGH_BUILD_FAILURES,
 )
@@ -15,7 +15,7 @@
 class CompilationSettings:
     precision: LowerPrecision = PRECISION
     debug: bool = DEBUG
-    workspace_size: int = MAX_WORKSPACE_SIZE
+    workspace_size: int = WORKSPACE_SIZE
     min_block_size: int = MIN_BLOCK_SIZE
     torch_executed_ops: Sequence[str] = field(default_factory=set)
     pass_through_build_failures: bool = PASS_THROUGH_BUILD_FAILURES

py/torch_tensorrt/dynamo/backend/conversion.py

@@ -3,7 +3,7 @@
 from torch_tensorrt.fx.trt_module import TRTModule
 from torch_tensorrt import TRTModuleNext
 from torch_tensorrt.dynamo.backend._settings import CompilationSettings
-from torch_tensorrt.fx.fx2trt import (
+from torch_tensorrt.dynamo.fx_ts_compat.fx2trt import (
     InputTensorSpec,
     TRTInterpreter,
 )
@@ -24,15 +24,15 @@ def convert_module(
     Returns:
         TRTModule or TRTModuleNext
     """
-    interp = TRTInterpreter(
+    interpreter = TRTInterpreter(
         module,
         InputTensorSpec.from_tensors(inputs),
         explicit_batch_dimension=True,
         logger_level=(trt.Logger.VERBOSE if settings.debug else trt.Logger.WARNING),
     )
 
-    r = interp.run(
-        max_workspace_size=settings.workspace_size,
+    interpreter_result = interpreter.run(
+        workspace_size=settings.workspace_size,
         lower_precision=settings.precision,
         profiling_verbosity=(
             trt.ProfilingVerbosity.VERBOSE
@@ -41,4 +41,8 @@ def convert_module(
         ),
     )
 
-    return TRTModule(*r)
+    return TRTModule(
+        engine=interpreter_result.engine,
+        input_names=interpreter_result.input_names,
+        output_names=interpreter_result.output_names,
+    )