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Enable UFMT on a bunch of low traffic Python files outside of main files (#106052)

Browse Source 
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/106052
Approved by: https://github.com/albanD, https://github.com/Skylion007
This commit is contained in:
Edward Z. Yang
2023-07-26 14:30:45 -04:00
committed by PyTorch MergeBot
parent 5a114f72bf
commit f70844bec7
56 changed files with 2317 additions and 1659 deletions
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16
android/pytorch_android/generate_test_torchscripts.py
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@ -1,18 +1,21 @@
from typing import Dict, List, Optional, Tuple
import torch
from torch import Tensor
from typing import Dict, List, Tuple, Optional
OUTPUT_DIR = "src/androidTest/assets/"
def scriptAndSave(module, fileName):
print('-' * 80)
print("-" * 80)
script_module = torch.jit.script(module)
print(script_module.graph)
outputFileName = OUTPUT_DIR + fileName
# note that the lite interpreter model can also be used in full JIT
script_module._save_for_lite_interpreter(outputFileName)
print("Saved to " + outputFileName)
print('=' * 80)
print("=" * 80)
class Test(torch.jit.ScriptModule):
@torch.jit.script_method
@ -73,7 +76,9 @@ class Test(torch.jit.ScriptModule):
return res
@torch.jit.script_method
def tupleIntSumReturnTuple(self, input: Tuple[int, int, int]) -> Tuple[Tuple[int, int, int], int]:
def tupleIntSumReturnTuple(
self, input: Tuple[int, int, int]
) -> Tuple[Tuple[int, int, int], int]:
sum = 0
for x in input:
sum += x
@ -114,7 +119,7 @@ class Test(torch.jit.ScriptModule):
@torch.jit.script_method
def conv2d(self, x: Tensor, w: Tensor, toChannelsLast: bool) -> Tensor:
r = torch.nn.functional.conv2d(x, w)
if (toChannelsLast):
if toChannelsLast:
r = r.contiguous(memory_format=torch.channels_last)
else:
r = r.contiguous()
@ -132,4 +137,5 @@ class Test(torch.jit.ScriptModule):
def contiguousChannelsLast3d(self, x: Tensor) -> Tensor:
return x.contiguous(memory_format=torch.channels_last_3d)
scriptAndSave(Test(), "test.pt")

16
android/test_app/make_assets.py
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@ -5,12 +5,20 @@ print(torch.version.__version__)
resnet18 = torchvision.models.resnet18(pretrained=True)
resnet18.eval()
resnet18_traced = torch.jit.trace(resnet18, torch.rand(1, 3, 224, 224)).save("app/src/main/assets/resnet18.pt")
resnet18_traced = torch.jit.trace(resnet18, torch.rand(1, 3, 224, 224)).save(
"app/src/main/assets/resnet18.pt"
)
resnet50 = torchvision.models.resnet50(pretrained=True)
resnet50.eval()
torch.jit.trace(resnet50, torch.rand(1, 3, 224, 224)).save("app/src/main/assets/resnet50.pt")
torch.jit.trace(resnet50, torch.rand(1, 3, 224, 224)).save(
"app/src/main/assets/resnet50.pt"
)
mobilenet2q = torchvision.models.quantization.mobilenet_v2(pretrained=True, quantize=True)
mobilenet2q = torchvision.models.quantization.mobilenet_v2(
pretrained=True, quantize=True
)
mobilenet2q.eval()
torch.jit.trace(mobilenet2q, torch.rand(1, 3, 224, 224)).save("app/src/main/assets/mobilenet2q.pt")
torch.jit.trace(mobilenet2q, torch.rand(1, 3, 224, 224)).save(
"app/src/main/assets/mobilenet2q.pt"
)

2
android/test_app/make_assets_custom.py
View File

@ -21,5 +21,5 @@ traced_script_module.save("MobileNetV2.pt")
# Dump root ops used by the model (for custom build optimization).
ops = torch.jit.export_opnames(traced_script_module)
with open('MobileNetV2.yaml', 'w') as output:
with open("MobileNetV2.yaml", "w") as output:
yaml.dump(ops, output)