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solved the weight streaming failure #4335

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solved the weight streaming failure #4335

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40 changes: 25 additions & 15 deletions py/torch_tensorrt/dynamo/runtime/_TRTEngine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -696,10 +696,17 @@ def device_memory_budget(self) -> Any:
def device_memory_budget(self, budget_bytes: int) -> None:
if budget_bytes < 0:
budget_bytes = self.streamable_device_memory_budget
# The weight streaming budget cannot be modified while an execution
# context is active, so release the current context first, then update
# the budget and recreate it (mirrors the C++ runtime's
# set_device_memory_budget).
self.context = None
self.cuda_engine.weight_streaming_budget_v2 = budget_bytes
if self.cuda_engine.weight_streaming_budget_v2 != budget_bytes:
logger.error(f"Failed to set weight streaming budget to {budget_bytes}")
self.context = self._create_execution_context()
if self._profile_execution:
self.enable_profiling()
self.runtime_states.context_changed = True

def reset_captured_graph(self) -> None:
Expand Down Expand Up @@ -882,11 +889,12 @@ def _prepare_streams(self, contiguous_inputs: List[torch.Tensor]) -> bool:
):
# Captured CUDA graph was recorded against the old stream.
self.runtime_states.context_changed = True
return caller_on_default
return bool(caller_on_default)

def _execute_standard(
self, contiguous_inputs: List[torch.Tensor]
) -> torch.Tensor | Tuple[torch.Tensor, ...]:

cudagraphs_enabled = torch_tensorrt.runtime.get_cudagraphs_mode()
if (
ENABLED_FEATURES.tensorrt_rtx
Expand All @@ -913,6 +921,9 @@ def _execute_standard(
# cudagraph recapture (set_runtime_states consumes and resets the
# flag).
caller_on_default = self._prepare_streams(contiguous_inputs)
engine_stream = self._engine_stream
caller_stream = self._caller_stream
assert engine_stream is not None and caller_stream is not None
shape_changed = self.validate_input_shapes(contiguous_inputs)
(
need_cudagraphs_record,
Expand Down Expand Up @@ -970,8 +981,8 @@ def _execute_standard(

with self._profile_section("TRTEngine:TensorRTRuntime"):
if caller_on_default:
self._engine_stream.wait_stream(self._caller_stream)
with torch.cuda.stream(self._engine_stream):
engine_stream.wait_stream(caller_stream)
with torch.cuda.stream(engine_stream):
if self.resource_allocation_strategy:
self._dynamic_workspace = torch.empty(
self.cuda_engine.device_memory_size_v2,
Expand All @@ -985,22 +996,18 @@ def _execute_standard(
self.cudagraph = torch.cuda.CUDAGraph()
if self._profile_execution:
self.cudagraph.enable_debug_mode()
with torch.cuda.graph(
self.cudagraph, stream=self._engine_stream
):
self.context.execute_async_v3(
self._engine_stream.cuda_stream
)
with torch.cuda.graph(self.cudagraph, stream=engine_stream):
self.context.execute_async_v3(engine_stream.cuda_stream)
if self._profile_execution:
self.cudagraph.debug_dump(
f"{DEBUG_LOGGING_DIR}/{self.name}_cudagraph.dot"
)
self.cudagraph.replay() # type: ignore[union-attr]
else:
self.context.execute_async_v3(self._engine_stream.cuda_stream)
self.context.execute_async_v3(engine_stream.cuda_stream)

if caller_on_default:
self._caller_stream.wait_stream(self._engine_stream)
caller_stream.wait_stream(engine_stream)

if self.use_pre_allocated_outputs and (
self.output_tensors_are_unowned
Expand Down Expand Up @@ -1040,14 +1047,17 @@ def _execute_output_allocator(
)

caller_on_default = self._prepare_streams(contiguous_inputs)
engine_stream = self._engine_stream
caller_stream = self._caller_stream
assert engine_stream is not None and caller_stream is not None

with self._profile_section("TRTEngine:TensorRTRuntime"):
if caller_on_default:
self._engine_stream.wait_stream(self._caller_stream)
with torch.cuda.stream(self._engine_stream):
self.context.execute_async_v3(self._engine_stream.cuda_stream)
engine_stream.wait_stream(caller_stream)
with torch.cuda.stream(engine_stream):
self.context.execute_async_v3(engine_stream.cuda_stream)
if caller_on_default:
self._caller_stream.wait_stream(self._engine_stream)
caller_stream.wait_stream(engine_stream)

outputs = []
assert self.output_allocator is not None
Expand Down
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