1- # Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
1+ # Copyright 2023-2026 , NVIDIA CORPORATION & AFFILIATES. All rights reserved.
22#
33# Redistribution and use in source and binary forms, with or without
44# modification, are permitted provided that the following conditions
2424# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
2525# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
2626
27- import numpy as np
2827import torch
28+ from torchvision import models
2929import triton_python_backend_utils as pb_utils
3030from torch .utils .dlpack import to_dlpack
3131
@@ -49,21 +49,7 @@ def initialize(self, args):
4949 device = "cuda" if args ["model_instance_kind" ] == "GPU" else "cpu"
5050 device_id = args ["model_instance_device_id" ]
5151 self .device = f"{ device } :{ device_id } "
52- # This example is configured to work with torch=1.13
53- # and torchvision=0.14. Thus, we need to provide a proper tag `0.14.1`
54- # to make sure loaded Resnet50 is compatible with
55- # installed `torchvision`.
56- # Refer to README for installation instructions.
57- self .model = (
58- torch .hub .load (
59- "pytorch/vision:v0.14.1" ,
60- "resnet50" ,
61- weights = "IMAGENET1K_V2" ,
62- skip_validation = True ,
63- )
64- .to (self .device )
65- .eval ()
66- )
52+ self .model = models .resnet50 (weights = models .ResNet50_Weights .IMAGENET1K_V2 ).to (self .device ).eval ()
6753
6854 def execute (self , requests ):
6955 """
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