File size: 12,935 Bytes
75bc5dd
 
e143115
75bc5dd
 
ac274c4
75bc5dd
a2daae4
75bc5dd
 
 
a0087b5
75bc5dd
d666216
8011d05
75bc5dd
 
d666216
8c5b6a1
d666216
 
 
 
 
 
 
 
 
 
 
 
8c5b6a1
 
 
 
 
 
d666216
 
 
 
 
 
8c5b6a1
d666216
 
 
 
 
 
8c5b6a1
d666216
 
 
 
 
 
 
a53f169
d666216
 
a53f169
d666216
 
 
 
8c5b6a1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7d3a951
 
8c5b6a1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7d3a951
 
8c5b6a1
 
 
 
 
 
 
 
e1a2ea2
75bc5dd
a23cef4
 
e1a2ea2
75bc5dd
 
 
 
 
399bdf5
75bc5dd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
---
library_name: pytorch
license: bsd-3-clause
tags:
- backbone
- bu_auto
- android
pipeline_tag: image-classification

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/web-assets/model_demo.png)

# ResNeXt101: Optimized for Qualcomm Devices

ResNeXt101 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.

This is based on the implementation of ResNeXt101 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py).
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.63.0/src/qai_hub_models/models/resnext101) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).

Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.

## Getting Started
There are two ways to deploy this model on your device:

### Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

| Runtime | Precision | Chipset | SDK Versions | Download |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.50, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.63.0/resnext101-onnx-float.zip)
| ONNX | w8a8 | Universal | QAIRT 2.50, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.63.0/resnext101-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.63.0/resnext101-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.63.0/resnext101-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.63.0/resnext101-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.50 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext101/releases/v0.63.0/resnext101-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[ResNeXt101 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/resnext101)**.


### Option 2: Export with Custom Configurations

Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.63.0/src/qai_hub_models/models/resnext101) Python library to compile and export the model with your own:
- Custom weights (e.g., fine-tuned checkpoints)
- Custom input shapes
- Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for [ResNeXt101 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.63.0/src/qai_hub_models/models/resnext101) for usage instructions.

## Model Details

**Model Type:** Model_use_case.image_classification

**Model Stats:**
- Input resolution: 224x224
- Model checkpoint: Imagenet
- Model size (float): 338 MB
- Model size (w8a8): 87.3 MB
- Number of parameters: 88.7M

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| ResNeXt101 | ONNX | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 3.092 ms | 1 - 190 MB | NPU
| ResNeXt101 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.921 ms | 0 - 184 MB | NPU
| ResNeXt101 | ONNX | float | Snapdragon® X2 Elite | 3.083 ms | 2 - 2 MB | NPU
| ResNeXt101 | ONNX | float | Snapdragon® X Elite | 6.253 ms | 173 - 173 MB | NPU
| ResNeXt101 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 4.486 ms | 0 - 366 MB | NPU
| ResNeXt101 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 9.266 ms | 0 - 315 MB | NPU
| ResNeXt101 | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 10.864 ms | 0 - 5 MB | NPU
| ResNeXt101 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.18 ms | 1 - 3 MB | NPU
| ResNeXt101 | ONNX | float | Qualcomm® QCS8450 | 9.266 ms | 0 - 315 MB | NPU
| ResNeXt101 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 9.696 ms | 0 - 4 MB | NPU
| ResNeXt101 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 6.253 ms | 173 - 173 MB | NPU
| ResNeXt101 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 3.921 ms | 0 - 184 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 1.595 ms | 0 - 227 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 2.086 ms | 0 - 223 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® X2 Elite | 1.439 ms | 1 - 1 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® X Elite | 2.846 ms | 88 - 88 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 2.118 ms | 0 - 269 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® 8 Gen 1 Mobile | 3.386 ms | 0 - 271 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 9.815 ms | 0 - 3 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 3.067 ms | 0 - 4 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 2.869 ms | 0 - 3 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® QCS8450 | 3.386 ms | 0 - 271 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 3.259 ms | 0 - 4 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 2.846 ms | 88 - 88 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 37.653 ms | 0 - 361 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.918 ms | 0 - 253 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 2.086 ms | 0 - 223 MB | NPU
| ResNeXt101 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.918 ms | 0 - 253 MB | NPU
| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 3.122 ms | 1 - 184 MB | NPU
| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.98 ms | 0 - 183 MB | NPU
| ResNeXt101 | QNN_DLC | float | Snapdragon® X2 Elite | 3.483 ms | 1 - 1 MB | NPU
| ResNeXt101 | QNN_DLC | float | Snapdragon® X Elite | 6.746 ms | 1 - 1 MB | NPU
| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 4.61 ms | 0 - 364 MB | NPU
| ResNeXt101 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 9.811 ms | 0 - 311 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 10.823 ms | 1 - 4 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.411 ms | 1 - 3 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® SA8775P | 10.034 ms | 1 - 181 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® SA8650P | 10.034 ms | 1 - 181 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® SA8255P | 10.034 ms | 1 - 181 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® QCS8450 | 9.811 ms | 0 - 311 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 9.784 ms | 1 - 3 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 6.746 ms | 1 - 1 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 3.98 ms | 0 - 183 MB | NPU
| ResNeXt101 | QNN_DLC | float | Qualcomm® SA8295P | 10.806 ms | 1 - 137 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 1.516 ms | 0 - 225 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.792 ms | 0 - 220 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 1.678 ms | 0 - 0 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® X Elite | 3.05 ms | 0 - 0 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 2.089 ms | 0 - 265 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 3.357 ms | 0 - 268 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 10.046 ms | 0 - 2 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 3.024 ms | 0 - 3 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 2.837 ms | 0 - 271 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® SA8650P | 3.503 ms | 0 - 215 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® SA8255P | 3.503 ms | 0 - 215 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 3.357 ms | 0 - 268 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 3.219 ms | 2 - 4 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 3.05 ms | 0 - 0 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 33.95 ms | 0 - 361 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.946 ms | 0 - 254 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.792 ms | 0 - 220 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 4.04 ms | 0 - 225 MB | NPU
| ResNeXt101 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.946 ms | 0 - 254 MB | NPU
| ResNeXt101 | TFLITE | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 3.125 ms | 0 - 367 MB | NPU
| ResNeXt101 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.995 ms | 0 - 352 MB | NPU
| ResNeXt101 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 4.605 ms | 0 - 535 MB | NPU
| ResNeXt101 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 9.816 ms | 0 - 483 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 10.853 ms | 0 - 176 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.418 ms | 0 - 3 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® SA8775P | 10.144 ms | 0 - 357 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® SA8650P | 10.144 ms | 0 - 357 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® SA8255P | 10.144 ms | 0 - 357 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® QCS8450 | 9.816 ms | 0 - 483 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 9.859 ms | 0 - 175 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 3.995 ms | 0 - 352 MB | NPU
| ResNeXt101 | TFLITE | float | Qualcomm® SA7255P | 159.933 ms | 0 - 20 MB | GPU
| ResNeXt101 | TFLITE | float | Qualcomm® SA8295P | 10.787 ms | 0 - 309 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 1.462 ms | 0 - 219 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.718 ms | 0 - 211 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.973 ms | 0 - 256 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 8 Gen 1 Mobile | 3.211 ms | 0 - 253 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 9.289 ms | 0 - 89 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 2.858 ms | 0 - 90 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 2.628 ms | 0 - 2 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8650P | 3.3 ms | 0 - 214 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8255P | 3.3 ms | 0 - 214 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® QCS8450 | 3.211 ms | 0 - 253 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 3.012 ms | 0 - 89 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 26.014 ms | 0 - 354 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.863 ms | 0 - 246 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.718 ms | 0 - 211 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA7255P | 6.044 ms | 0 - 214 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Qualcomm® SA8295P | 3.892 ms | 0 - 219 MB | NPU
| ResNeXt101 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.863 ms | 0 - 246 MB | NPU

## License
* The license for the original implementation of ResNeXt101 can be found
  [here](https://github.com/pytorch/vision/blob/main/LICENSE).

## References
* [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/abs/1611.05431)
* [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py)

## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).