Improve Python tooling #2126
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Improve Python tooling #2126
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There are some changes that do not conform to C++ style guidelines:
diff --git a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp b/tmp/changes.txt
index 8258a13..8381754 100644
--- a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp
+++ b/tmp/changes.txt
@@ -103,7 +103,12 @@ DEFINE_ARITHMATIC_TWO_INPUT_EVALUATOR(
"aten::pow.float_int(float a, int b) -> (float)",
}));
-DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(and, "aten::__and__", a&& b, bool, std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
+DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
+ and,
+ "aten::__and__",
+ a&& b,
+ bool,
+ std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(or, "aten::__or__", a || b, bool, {"aten::__or__(int a, int b) -> (bool)"});
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
xor,
ERROR: Some files do not conform to style guidelinesThere was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:30:59.066389 +0000
+++ tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:31:18.329140 +0000
@@ -72,15 +72,11 @@
inputs = [
torch.randint(-40, 40, (16, 7, 5), dtype=torch.int).cuda(),
torch.randint(1, 40, (16, 7, 5), dtype=torch.int).cuda(),
]
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=1,
torch_executed_ops={"torch.ops.aten.add.Tensor"},
--- tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:30:59.066389 +0000
+++ tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:31:18.355272 +0000
@@ -91,15 +91,11 @@
(5,),
),
]
fx_graph = torch.fx.symbolic_trace(PartiallySupportedMultiOp())
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=2,
torch_executed_ops={"torch.ops.aten.add.Tensor"},There was a problem hiding this comment.
There are some changes that do not conform to C++ style guidelines:
diff --git a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp b/tmp/changes.txt
index 8258a13..8381754 100644
--- a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp
+++ b/tmp/changes.txt
@@ -103,7 +103,12 @@ DEFINE_ARITHMATIC_TWO_INPUT_EVALUATOR(
"aten::pow.float_int(float a, int b) -> (float)",
}));
-DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(and, "aten::__and__", a&& b, bool, std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
+DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
+ and,
+ "aten::__and__",
+ a&& b,
+ bool,
+ std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(or, "aten::__or__", a || b, bool, {"aten::__or__(int a, int b) -> (bool)"});
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
xor,
ERROR: Some files do not conform to style guidelinesThere was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:38:43.705986 +0000
+++ tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:39:13.917759 +0000
@@ -72,15 +72,11 @@
inputs = [
torch.randint(-40, 40, (16, 7, 5), dtype=torch.int).cuda(),
torch.randint(1, 40, (16, 7, 5), dtype=torch.int).cuda(),
]
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=1,
torch_executed_ops={"torch.ops.aten.add.Tensor"},
--- tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:38:43.705986 +0000
+++ tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:39:13.978766 +0000
@@ -91,15 +91,11 @@
(5,),
),
]
fx_graph = torch.fx.symbolic_trace(PartiallySupportedMultiOp())
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=2,
torch_executed_ops={"torch.ops.aten.add.Tensor"},There was a problem hiding this comment.
There are some changes that do not conform to C++ style guidelines:
diff --git a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp b/tmp/changes.txt
index 8258a13..8381754 100644
--- a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp
+++ b/tmp/changes.txt
@@ -103,7 +103,12 @@ DEFINE_ARITHMATIC_TWO_INPUT_EVALUATOR(
"aten::pow.float_int(float a, int b) -> (float)",
}));
-DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(and, "aten::__and__", a&& b, bool, std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
+DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
+ and,
+ "aten::__and__",
+ a&& b,
+ bool,
+ std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(or, "aten::__or__", a || b, bool, {"aten::__or__(int a, int b) -> (bool)"});
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
xor,
ERROR: Some files do not conform to style guidelinesThere was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- py/torch_tensorrt/dynamo/runtime/__init__.py 2023-07-20 20:40:52.942688 +0000
+++ py/torch_tensorrt/dynamo/runtime/__init__.py 2023-07-20 20:41:09.494994 +0000
@@ -1,2 +1,2 @@
-from ._PythonTorchTensorRTModule import PythonTorchTensorRTModule # noqa: F401
+from ._PythonTorchTensorRTModule import PythonTorchTensorRTModule # noqa: F401
from ._TorchTensorRTModule import TorchTensorRTModule # noqa: F401
--- tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:40:52.958688 +0000
+++ tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:41:12.851884 +0000
@@ -72,15 +72,11 @@
inputs = [
torch.randint(-40, 40, (16, 7, 5), dtype=torch.int).cuda(),
torch.randint(1, 40, (16, 7, 5), dtype=torch.int).cuda(),
]
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=1,
torch_executed_ops={"torch.ops.aten.add.Tensor"},
--- tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:40:52.958688 +0000
+++ tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:41:12.944283 +0000
@@ -91,15 +91,11 @@
(5,),
),
]
fx_graph = torch.fx.symbolic_trace(PartiallySupportedMultiOp())
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=2,
torch_executed_ops={"torch.ops.aten.add.Tensor"},There was a problem hiding this comment.
There are some changes that do not conform to C++ style guidelines:
diff --git a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp b/tmp/changes.txt
index 8258a13..8381754 100644
--- a/home/runner/work/TensorRT/TensorRT/core/conversion/evaluators/aten.cpp
+++ b/tmp/changes.txt
@@ -103,7 +103,12 @@ DEFINE_ARITHMATIC_TWO_INPUT_EVALUATOR(
"aten::pow.float_int(float a, int b) -> (float)",
}));
-DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(and, "aten::__and__", a&& b, bool, std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
+DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
+ and,
+ "aten::__and__",
+ a&& b,
+ bool,
+ std::set<std::string>({"aten::__and__(int a, int b) -> (bool)", "aten::__and__.bool(bool a, bool b) -> (bool)"}));
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(or, "aten::__or__", a || b, bool, {"aten::__or__(int a, int b) -> (bool)"});
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
xor,
ERROR: Some files do not conform to style guidelinesThere was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- py/torch_tensorrt/dynamo/runtime/__init__.py 2023-07-20 20:44:40.035477 +0000
+++ py/torch_tensorrt/dynamo/runtime/__init__.py 2023-07-20 20:45:01.353601 +0000
@@ -1,2 +1,2 @@
-from ._PythonTorchTensorRTModule import PythonTorchTensorRTModule # noqa: F401
+from ._PythonTorchTensorRTModule import PythonTorchTensorRTModule # noqa: F401
from ._TorchTensorRTModule import TorchTensorRTModule # noqa: F401
--- tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:44:40.059478 +0000
+++ tests/py/dynamo/backend/test_backend_compiler.py 2023-07-20 20:45:05.744794 +0000
@@ -72,15 +72,11 @@
inputs = [
torch.randint(-40, 40, (16, 7, 5), dtype=torch.int).cuda(),
torch.randint(1, 40, (16, 7, 5), dtype=torch.int).cuda(),
]
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=1,
torch_executed_ops={"torch.ops.aten.add.Tensor"},
--- tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:44:40.059478 +0000
+++ tests/py/dynamo/backend/test_partitioning.py 2023-07-20 20:45:05.866701 +0000
@@ -91,15 +91,11 @@
(5,),
),
]
fx_graph = torch.fx.symbolic_trace(PartiallySupportedMultiOp())
- (
- unexpected_ops_seen,
- _,
- partitioned_graphs,
- ) = lower_graph_testing(
+ (unexpected_ops_seen, _, partitioned_graphs,) = lower_graph_testing(
fx_graph,
inputs,
unexpected_ops=unexpected_ops,
min_block_size=2,
torch_executed_ops={"torch.ops.aten.add.Tensor"},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/ts/_compiler.py 2023-07-27 19:39:59.343464+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/_compiler.py 2023-07-27 19:42:21.824739+00:00
@@ -302,12 +302,16 @@
output_binding_names (List[str]): List of names of TensorRT bindings in order that should be returned from the encompassing PyTorch module
device (Union(torch_tensorrt.Device, torch.device, dict)): Target device to run engine on. Must be compatible with engine provided. Default: Current active device
Returns:
torch.jit.ScriptModule: New TorchScript module with engine embedded
"""
- input_binding_name_list = input_binding_names if input_binding_names is not None else []
- output_binding_name_list = output_binding_names if output_binding_names is not None else []
+ input_binding_name_list = (
+ input_binding_names if input_binding_names is not None else []
+ )
+ output_binding_name_list = (
+ output_binding_names if output_binding_names is not None else []
+ )
cpp_mod = _C.embed_engine_in_new_module(
serialized_engine,
_parse_device(device),
input_binding_name_list,
output_binding_name_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/ts/_compiler.py 2023-07-31 19:15:49.366140+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/_compiler.py 2023-07-31 19:18:09.264729+00:00
@@ -302,12 +302,16 @@
output_binding_names (List[str]): List of names of TensorRT bindings in order that should be returned from the encompassing PyTorch module
device (Union(torch_tensorrt.Device, torch.device, dict)): Target device to run engine on. Must be compatible with engine provided. Default: Current active device
Returns:
torch.jit.ScriptModule: New TorchScript module with engine embedded
"""
- input_binding_name_list = input_binding_names if input_binding_names is not None else []
- output_binding_name_list = output_binding_names if output_binding_names is not None else []
+ input_binding_name_list = (
+ input_binding_names if input_binding_names is not None else []
+ )
+ output_binding_name_list = (
+ output_binding_names if output_binding_names is not None else []
+ )
cpp_mod = _C.embed_engine_in_new_module(
serialized_engine,
_parse_device(device),
input_binding_name_list,
output_binding_name_list,
narendasan
commented
Jul 31, 2023
| @@ -53,7 +49,9 @@ def gelu( | |||
|
|
|||
| layer = network.add_plugin_v2([input_val], plugin) | |||
|
|
|||
| def gelu_dyn_range_fn(dyn_range): | |||
| def gelu_dyn_range_fn( | |||
There was a problem hiding this comment.
This would likely fail in the FakeTensor context we use in the torch.compile path. I believe the correct type signature for dyn_range should be Tuple[float, float], as mentioned here. Then, the fix would be to change the return to be:
import math
...
return (
dyn_range[0] * 0.5 * (1.0 + math.erf(dyn_range[0] / math.sqrt(2.0)))
), (dyn_range[1] * 0.5 * (1.0 + math.erf(dyn_range[1] / math.sqrt(2.0))))The above avoids the unnecessary cast to torch.Tensor. Additionally, the correct return type would then also be Tuple[float, float].
Note: I changed the second return argument from using dyn_range[0] to dyn_range[1]. Not sure if this is a bug in the original implementation.
There was a problem hiding this comment.
Is it supposed to be an op on a scalar or on a tensor?
There was a problem hiding this comment.
I think this nested function gelu_dyn_range_function is supposed to be a function on a Tuple of two scalars.
gs-olive
reviewed
Aug 2, 2023
Comment on lines
55
to
57
| return ( | ||
| dyn_range[0] * 0.5 * (1.0 + torch.erf(dyn_range[0] / math.sqrt(2.0))) | ||
| ), (dyn_range[1] * 0.5 * (1.0 + torch.erf(dyn_range[0] / math.sqrt(2.0)))) |
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/torch_compile_advanced_usage.py 2023-08-07 18:32:08.732415+00:00
+++ /home/runner/work/TensorRT/TensorRT/examples/dynamo/torch_compile_advanced_usage.py 2023-08-07 18:34:44.880582+00:00
@@ -12,10 +12,11 @@
import torch
import torch_tensorrt
# %%
+
# We begin by defining a model
class Model(torch.nn.Module):
def __init__(self) -> None:
super().__init__()
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/tools/opset_coverage.py 2023-08-07 18:32:08.744415+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/tools/opset_coverage.py 2023-08-07 18:34:45.808594+00:00
@@ -108,11 +108,10 @@
def opset_coverage(
opset: List[Tuple[str, str]],
converter_registry: Optional[ConverterRegistry] = None,
decomposition_registry: Optional[Dict[OpOverload, Callable[..., Any]]] = None,
) -> OpsetCoverage:
-
opset_schemas = dict(opset)
opset_targets = set(opset_schemas.keys())
support_status = {}
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/_compiler.py 2023-08-07 18:32:08.756415+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/_compiler.py 2023-08-07 18:34:49.220113+00:00
@@ -302,12 +302,16 @@
output_binding_names (List[str]): List of names of TensorRT bindings in order that should be returned from the encompassing PyTorch module
device (Union(torch_tensorrt.Device, torch.device, dict)): Target device to run engine on. Must be compatible with engine provided. Default: Current active device
Returns:
torch.jit.ScriptModule: New TorchScript module with engine embedded
"""
- input_binding_name_list = input_binding_names if input_binding_names is not None else []
- output_binding_name_list = output_binding_names if output_binding_names is not None else []
+ input_binding_name_list = (
+ input_binding_names if input_binding_names is not None else []
+ )
+ output_binding_name_list = (
+ output_binding_names if output_binding_names is not None else []
+ )
cpp_mod = _C.embed_engine_in_new_module(
serialized_engine,
_parse_device(device),
input_binding_name_list,
output_binding_name_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/examples/dynamo/torch_compile_advanced_usage.py 2023-08-07 19:05:24.508037+00:00
+++ /home/runner/work/TensorRT/TensorRT/examples/dynamo/torch_compile_advanced_usage.py 2023-08-07 19:07:53.410940+00:00
@@ -12,10 +12,11 @@
import torch
import torch_tensorrt
# %%
+
# We begin by defining a model
class Model(torch.nn.Module):
def __init__(self) -> None:
super().__init__()We are adding: - mypy: Type checking - ruff: Linting and common bug detection - isort: import order cleanup These tools will run as part of the precommit system and are required for all code in //py and //examples. They are suggested for the rest Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/ts): Make torch_tensorrt.ts.TorchScriptInput mypy compliant Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/ts): Making compile mypy compliant Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): Make Device conform to mypy Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): Making Input mypy compilaint Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/ts): Make compile_spec conform to mypy Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): more _Input.py mypy stuff Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): conforming logging to mypy Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): _compile.py conforms to mypy Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/dynamo/backend): Backend is mypy conforming Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): subsitutions mypy compliant Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/dynamo/lowering): mypy compilance Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/dynamo): Tracer mypy compliance Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): ptq mypy compliance Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt): __init__.py mypy conforming Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore(//py/torch_tensorrt/dynamo/conversion): mypy conforming Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore: mypy compliance with 3.11 syntax Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore: Buildifier on build files Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore: linting for the remaining files Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore: All code is now flake8 compliant Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore: adding isort to pre-commit Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com> chore: ready to start review Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com>
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Description
Installing a number of standard tools to make the codebase more maintainable longterm
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Please delete options that are not relevant and/or add your own.
Checklist: