Skip to content

Accelerate network interpretation by 15x; fixed redundant code in TRT Interpreter #3396

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Feb 15, 2025
Merged

Accelerate network interpretation by 15x; fixed redundant code in TRT Interpreter #3396

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 3 additions & 10 deletions py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,9 @@
from torch_tensorrt.dynamo.conversion._ConverterRegistry import (
DYNAMO_CONVERTERS as CONVERTERS,
)
from torch_tensorrt.dynamo.conversion._ConverterRegistry import CallingConvention
from torch_tensorrt.dynamo.conversion._ConverterRegistry import (
CallingConvention,
)
from torch_tensorrt.dynamo.conversion._TRTBuilderMonitor import TRTBulderMonitor
from torch_tensorrt.dynamo.conversion.converter_utils import (
get_node_io,
Expand Down Expand Up @@ -740,10 +742,6 @@ def run(
def run_node(self, n: torch.fx.Node) -> torch.fx.Node:
self._cur_node_name = get_node_name(n)
self._cur_node = n
# add "_itensor_to_tensor_meta"
kwargs = dict(n.kwargs)
kwargs["_itensor_to_tensor_meta"] = self._itensor_to_tensor_meta
n.kwargs = kwargs

if _LOGGER.isEnabledFor(logging.DEBUG):
_LOGGER.debug(
Expand All @@ -759,11 +757,6 @@ def run_node(self, n: torch.fx.Node) -> torch.fx.Node:
f"Converted node {self._cur_node_name} [{n.target}] ({get_node_io(n, self.const_mapping)})"
)

# remove "_itensor_to_tensor_meta"
kwargs = dict(n.kwargs)
del kwargs["_itensor_to_tensor_meta"]
n.kwargs = kwargs

if isinstance(trt_node, trt.ITensor):
self._itensor_to_tensor_meta[trt_node] = n.meta.get("tensor_meta")

Expand Down
Loading