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from torchvision import models
import torch
from torch.utils.bundled_inputs import augment_model_with_bundled_inputs
from torch.utils.mobile_optimizer import optimize_for_mobile
class MobileNetV2Module:
def getModule(self):
model = models.mobilenet_v2(weights=models.MobileNet_V2_Weights.IMAGENET1K_V1)
model.eval()
example = torch.zeros(1, 3, 224, 224)
traced_script_module = torch.jit.trace(model, example)
optimized_module = optimize_for_mobile(traced_script_module)
augment_model_with_bundled_inputs(
optimized_module,
[
(example,),
],
)
optimized_module(example)
return optimized_module
class MobileNetV2VulkanModule:
def getModule(self):
model = models.mobilenet_v2(weights=models.MobileNet_V2_Weights.IMAGENET1K_V1)
model.eval()
example = torch.zeros(1, 3, 224, 224)
traced_script_module = torch.jit.trace(model, example)
optimized_module = optimize_for_mobile(traced_script_module, backend="vulkan")
augment_model_with_bundled_inputs(
optimized_module,
[
(example,),
],
)
optimized_module(example)
return optimized_module
class Resnet18Module:
def getModule(self):
model = models.resnet18(weights=models.ResNet18_Weights.IMAGENET1K_V1)
model.eval()
example = torch.zeros(1, 3, 224, 224)
traced_script_module = torch.jit.trace(model, example)
optimized_module = optimize_for_mobile(traced_script_module)
augment_model_with_bundled_inputs(
optimized_module,
[
(example,),
],
)
optimized_module(example)
return optimized_module
|
