Implemented basic Mutable torch tensorrt module pipeline #2981
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--- /home/runner/work/TensorRT/TensorRT/examples/dynamo/mutable_torchtrt_module_example.py 2024-07-03 00:33:30.637263+00:00
+++ /home/runner/work/TensorRT/TensorRT/examples/dynamo/mutable_torchtrt_module_example.py 2024-07-03 00:35:20.326993+00:00
@@ -36,20 +36,18 @@
# %%
# Compile the module for the first time and save it.
# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
kwargs = {
- 'use_python': False,
- 'enabled_precisions': {torch.float16, torch.float32},
- 'mutable': True
+ "use_python": False,
+ "enabled_precisions": {torch.float16, torch.float32},
+ "mutable": True,
}
model = models.resnet18(pretrained=False).eval().to("cuda")
model2 = models.resnet18(pretrained=True).eval().to("cuda")
-mutable_module = torch_trt.compile(inputs=inputs,
- module=model,
- **kwargs)
+mutable_module = torch_trt.compile(inputs=inputs, module=model, **kwargs)
# Save the graph module as an exported program
# This is only supported when use_python_runtime = False
mutable_module.load_state_dict(model2.state_dict())
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-03 00:33:30.645263+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-03 00:35:20.875148+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2024-07-03 00:33:30.653263+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2024-07-03 00:35:21.749591+00:00
@@ -7,10 +7,11 @@
import torch_tensorrt as torch_trt
import torch
from torch_tensorrt.dynamo.utils import prepare_inputs
from torch_tensorrt.dynamo._tracer import trace as dynamo_trace
from torch_tensorrt.dynamo._compiler import compile as dynamo_compile
+
class RefitFlag:
def __init__(self):
self.flag = False
@@ -20,12 +21,15 @@
def set_off(self):
self.flag = False
print("RefitFlag is set to OFF.")
+
class MutableTorchTensorRTModule(object):
- def __init__(self, pytorch_model, sample_inputs, enabled_precisions_set, **kwargs) -> None:
+ def __init__(
+ self, pytorch_model, sample_inputs, enabled_precisions_set, **kwargs
+ ) -> None:
self.refit_flag = RefitFlag()
self.original_inputs = sample_inputs
if not isinstance(sample_inputs, collections.abc.Sequence):
sample_inputs = [sample_inputs]
self.sample_inputs = tuple(sample_inputs)
@@ -40,84 +44,89 @@
self.refit_flag.set_on()
self.pytorch_model.load_state_dict(sd)
def refit_gm(self):
if self.exp_program is None:
- self.exp_program = torch.export.export(self.pytorch_model, self.sample_inputs)
+ self.exp_program = torch.export.export(
+ self.pytorch_model, self.sample_inputs
+ )
# TODO: Check refit condition and fallback to recompile
- self.exp_program._state_dict = MutableTorchTensorRTModule._transform_state_dict(self.pytorch_model.state_dict())
+ self.exp_program._state_dict = MutableTorchTensorRTModule._transform_state_dict(
+ self.pytorch_model.state_dict()
+ )
self.gm = refit_module_weights(self.gm, self.exp_program, self.sample_inputs)
-
def compile(self):
-
+
# Export the module
- self.exp_program = dynamo_trace(self.original_model, self.torchtrt_inputs, **self.kwargs)
+ self.exp_program = dynamo_trace(
+ self.original_model, self.torchtrt_inputs, **self.kwargs
+ )
self.gm = dynamo_compile(
self.exp_program,
inputs=self.torchtrt_inputs,
enabled_precisions=self.enabled_precisions_set,
make_refitable=True,
**self.kwargs,
)
-
+
def _transform_state_dict(sd):
return {k: torch.nn.Parameter(v, requires_grad=False) for k, v in sd.items()}
-
+
def __getattr__(self, name):
-
+
if name in self.__dict__:
# this object has it
return getattr(self, name)
return getattr(self.pytorch_model, name)
-
+
# raise AttributeError(f"'{type(self.pytorch_model)}' object has no attribute '{name}'")
def __call__(self, *args, **kwargs):
# We can update this once the kwarg pull request got merged
return self.forward(*args, **kwargs)
-
+
def forward(self, *args, **kwargs):
# TODO: Check the inputs is the same as the sample input
if self.refit_flag.flag:
print("Model weight change detected. Refitting the module...")
self.refit_flag.set_off()
self.refit_gm()
return self.gm(*args, **kwargs)
-
-
def _make_refit_change_trigger(obj: Any, refit_flag: RefitFlag) -> Any:
class ChangeTriggerWrapper(obj.__class__):
def __init__(self, obj: Any):
- object.__setattr__(self, 'instance', obj)
+ object.__setattr__(self, "instance", obj)
def __getattr__(self, name: str):
# This will cause infinte loop if there is a cycle
obj = getattr(self.instance, name)
- if not hasattr(obj, '__dict__'):
- return obj
+ if not hasattr(obj, "__dict__"):
+ return obj
else:
return _make_refit_change_trigger(obj, refit_flag)
-
- def __setattr__(self, name:str, value: Any):
+
+ def __setattr__(self, name: str, value: Any):
self._on_change()
setattr(self.instance, name, value)
def __delattr__(self, name: str):
self._on_change()
- delattr(self.instance, name, )
+ delattr(
+ self.instance,
+ name,
+ )
def _on_change(self):
refit_flag.set_on()
print("Change!")
def __call__(self, *args: Any, **kwargs: Any) -> Any:
print("Warning: uncatched change in function!")
self.instance(*args, **kwargs)
return ChangeTriggerWrapper(obj)
-
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py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py
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py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 18:47:36.308343+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 18:49:28.137706+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 19:03:35.588909+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 19:05:25.168514+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 20:13:17.684296+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 20:15:07.402520+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 21:05:16.080984+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-05 21:07:04.224364+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
narendasan
reviewed
Jul 8, 2024
py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 19:50:34.267992+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 19:52:23.991166+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 19:59:37.315433+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:02:01.355058+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:32:36.364774+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:34:26.453620+00:00
@@ -9,11 +9,13 @@
import torch.fx
from torch_tensorrt._enums import dtype
from torch_tensorrt._features import ENABLED_FEATURES
from torch_tensorrt._Input import Input
from torch_tensorrt.dynamo import _defaults
-from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import MutableTorchTensorRTModule
+from torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule import (
+ MutableTorchTensorRTModule,
+)
from torch_tensorrt.fx import InputTensorSpec
from torch_tensorrt.fx.lower import compile as fx_compile
from torch_tensorrt.fx.utils import LowerPrecision
from typing_extensions import TypeGuard
@@ -238,15 +240,17 @@
**kwargs,
)
return compiled_fx_module
elif target_ir == _IRType.dynamo:
if kwargs["mutable"]:
- mutable_trt_graph_module = MutableTorchTensorRTModule(module, input_list, enabled_precisions_set, **kwargs)
+ mutable_trt_graph_module = MutableTorchTensorRTModule(
+ module, input_list, enabled_precisions_set, **kwargs
+ )
mutable_trt_graph_module.compile()
return mutable_trt_graph_module
else:
- # Prepare torch and torchtrt inputs
+ # Prepare torch and torchtrt inputs
from torch_tensorrt.dynamo.utils import prepare_inputs
if not isinstance(input_list, collections.abc.Sequence):
input_list = [input_list]
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:35:49.249381+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:37:40.201769+00:00
@@ -473,6 +473,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(inputs), strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:39:58.446119+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-07-08 20:41:48.798417+00:00
@@ -473,6 +473,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(inputs), strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/examples/dynamo/mutable_torchtrt_module_stable_diffusion_example.py 2024-07-11 21:29:42.735735+00:00
+++ /home/runner/work/TensorRT/TensorRT/examples/dynamo/mutable_torchtrt_module_stable_diffusion_example.py 2024-07-11 21:31:37.121983+00:00
@@ -52,23 +52,21 @@
pipe = DiffusionPipeline.from_pretrained(
model_id, revision="fp16", torch_dtype=torch.float16, safety_checker=None
)
pipe.to(device)
-backend = "torch_tensorrt"
+backend = "torch_tensorrt"
pipe.unet = torch_trt.MutableTorchTensorRTModule(pipe.unet, **kwargs)
image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]
-image.save('./without_LoRA.jpg')
+image.save("./without_LoRA.jpg")
pipe.load_lora_weights("/opt/torch_tensorrt/moxin.safetensors", adapter_name="lora1")
pipe.set_adapters(["lora1"], adapter_weights=[1])
-pipe.fuse_lora(['lora1'], 1)
+pipe.fuse_lora(["lora1"], 1)
pipe.unload_lora_weights()
# Check the output
image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]
-image.save('./with_LoRA.jpg')
-
-
+image.save("./with_LoRA.jpg")
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/examples/dynamo/mutable_torchtrt_module_stable_diffusion_example.py 2024-07-11 21:32:22.202416+00:00
+++ /home/runner/work/TensorRT/TensorRT/examples/dynamo/mutable_torchtrt_module_stable_diffusion_example.py 2024-07-11 21:34:14.063863+00:00
@@ -52,23 +52,21 @@
pipe = DiffusionPipeline.from_pretrained(
model_id, revision="fp16", torch_dtype=torch.float16, safety_checker=None
)
pipe.to(device)
-backend = "torch_tensorrt"
+backend = "torch_tensorrt"
pipe.unet = torch_trt.MutableTorchTensorRTModule(pipe.unet, **kwargs)
image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]
-image.save('./without_LoRA.jpg')
+image.save("./without_LoRA.jpg")
pipe.load_lora_weights("/opt/torch_tensorrt/moxin.safetensors", adapter_name="lora1")
pipe.set_adapters(["lora1"], adapter_weights=[1])
-pipe.fuse_lora(['lora1'], 1)
+pipe.fuse_lora(["lora1"], 1)
pipe.unload_lora_weights()
# Check the output
image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]
-image.save('./with_LoRA.jpg')
-
-
+image.save("./with_LoRA.jpg")
narendasan
reviewed
Jul 31, 2024
| hardware_compatible: bool = _defaults.HARDWARE_COMPATIBLE, | ||
| timing_cache_path: str = _defaults.TIMING_CACHE_PATH, | ||
| **kwargs: Any, | ||
| ) -> None: |
narendasan
reviewed
Aug 6, 2024
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 21:55:55.416655+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 22:00:22.024407+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 21:58:09.155212+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 22:05:03.968754+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 22:22:50.002715+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 22:24:35.279571+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
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There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 22:39:11.275361+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-13 22:41:42.248930+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
cehongwang
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There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-14 23:52:00.233996+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-14 23:53:45.828886+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
cehongwang
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There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-15 00:10:53.392627+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-15 00:16:07.394087+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2024-08-15 00:10:53.396627+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2024-08-15 00:16:08.728715+00:00
@@ -372,11 +372,11 @@
return result
def to(self, device: str):
logger.warning("Original PyTorch model is moved. CPU offload may failed.")
self.orignial_model.to(device)
-
+
def __deepcopy__(self, memo: Any) -> Any:
cls = self.__class__
result = cls.__new__(cls)
memo[id(self)] = result
for k, v in self.__dict__.items():
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-15 18:26:39.178114+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-15 18:28:37.121097+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2024-08-15 18:26:39.186114+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2024-08-15 18:28:38.508444+00:00
@@ -372,11 +372,11 @@
return result
def to(self, device: str):
logger.warning("Original PyTorch model is moved. CPU offload may failed.")
self.orignial_model.to(device)
-
+
def __deepcopy__(self, memo: Any) -> Any:
cls = self.__class__
result = cls.__new__(cls)
memo[id(self)] = result
for k, v in self.__dict__.items():
Signed-off-by: Naren Dasan <[email protected]>
cehongwang
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There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-15 19:35:17.585819+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/_compile.py 2024-08-15 19:37:02.052771+00:00
@@ -532,6 +532,6 @@
with enable_torchbind_tracing():
exp_program = torch.export.export(
module, tuple(arg_inputs), kwargs=kwarg_inputs, strict=False
)
- torch.export.save(exp_program, file_path)
\ No newline at end of file
+ torch.export.save(exp_program, file_path)
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Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Fixes # (issue)
Type of change
Please delete options that are not relevant and/or add your own.
Checklist:
Refit state transition graph