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MNASNet05

Image Classification
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v0.58.0

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See https://github.com/qualcomm/ai-hub-models/releases/v0.58.0 for changelog.

Files changed (2) hide show
  1. README.md +80 -74
  2. release_assets.json +6 -6
README.md CHANGED
@@ -16,7 +16,7 @@ pipeline_tag: image-classification
16
  MNASNet05 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.
17
 
18
  This is based on the implementation of MNASNet05 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/mnasnet.py).
19
- 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/v0.57.3/src/qai_hub_models/models/mnasnet05) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
20
 
21
  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.
22
 
@@ -29,25 +29,25 @@ Below are pre-exported model assets ready for deployment.
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30
  | Runtime | Precision | Chipset | SDK Versions | Download |
31
  |---|---|---|---|---|
32
- | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-onnx-float.zip)
33
- | ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-onnx-w8a16.zip)
34
- | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-qnn_dlc-float.zip)
35
- | QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-qnn_dlc-w8a16.zip)
36
- | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-tflite-float.zip)
37
 
38
  For more device-specific assets and performance metrics, visit **[MNASNet05 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/mnasnet05)**.
39
 
40
 
41
  ### Option 2: Export with Custom Configurations
42
 
43
- Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.57.3/src/qai_hub_models/models/mnasnet05) Python library to compile and export the model with your own:
44
  - Custom weights (e.g., fine-tuned checkpoints)
45
  - Custom input shapes
46
  - Target device and runtime configurations
47
 
48
  This option is ideal if you need to customize the model beyond the default configuration provided here.
49
 
50
- See our repository for [MNASNet05 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.57.3/src/qai_hub_models/models/mnasnet05) for usage instructions.
51
 
52
  ## Model Details
53
 
@@ -63,78 +63,84 @@ See our repository for [MNASNet05 on GitHub](https://github.com/qualcomm/ai-hub-
63
  ## Performance Summary
64
  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
65
  |---|---|---|---|---|---|---
66
- | MNASNet05 | ONNX | float | Snapdragon® X2 Elite | 0.225 ms | 212 - 212 MB | NPU
67
- | MNASNet05 | ONNX | float | Snapdragon® X Elite | 0.484 ms | 181 - 181 MB | NPU
68
- | MNASNet05 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.33 ms | 0 - 35 MB | NPU
69
- | MNASNet05 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 0.877 ms | 1 - 44 MB | NPU
70
- | MNASNet05 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 0.484 ms | 0 - 69 MB | NPU
71
- | MNASNet05 | ONNX | float | Qualcomm® QCS8450 | 0.877 ms | 1 - 44 MB | NPU
72
- | MNASNet05 | ONNX | float | Snapdragon® 8 Elite Mobile | 0.268 ms | 0 - 28 MB | NPU
73
- | MNASNet05 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.222 ms | 1 - 24 MB | NPU
74
- | MNASNet05 | ONNX | float | Qualcomm® QCS9075 | 0.765 ms | 0 - 50 MB | NPU
75
- | MNASNet05 | ONNX | float | Qualcomm® QCS8750 | 0.268 ms | 0 - 28 MB | NPU
76
- | MNASNet05 | ONNX | float | Qualcomm® QCS7181 | 0.484 ms | 181 - 181 MB | NPU
77
- | MNASNet05 | ONNX | w8a16 | Snapdragon® X2 Elite | 0.214 ms | 213 - 213 MB | NPU
78
- | MNASNet05 | ONNX | w8a16 | Snapdragon® X Elite | 0.513 ms | 149 - 149 MB | NPU
79
- | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 0.347 ms | 0 - 32 MB | NPU
80
- | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 0.679 ms | 0 - 35 MB | NPU
81
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS6490 | 1.686 ms | 0 - 50 MB | NPU
82
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 0.516 ms | 0 - 15 MB | NPU
83
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS8450 | 0.679 ms | 0 - 35 MB | NPU
84
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS9075 | 0.694 ms | 0 - 48 MB | NPU
85
- | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.22 ms | 0 - 28 MB | NPU
86
- | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 0.266 ms | 0 - 30 MB | NPU
87
- | MNASNet05 | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 0.537 ms | 0 - 27 MB | NPU
88
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCM6690 | 2.289 ms | 0 - 141 MB | NPU
89
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS7790 | 0.537 ms | 0 - 27 MB | NPU
90
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS8750 | 0.266 ms | 0 - 30 MB | NPU
91
- | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS7181 | 0.513 ms | 149 - 149 MB | NPU
92
- | MNASNet05 | QNN_DLC | float | Snapdragon® X2 Elite | 0.406 ms | 1 - 1 MB | NPU
93
- | MNASNet05 | QNN_DLC | float | Snapdragon® X Elite | 0.919 ms | 1 - 1 MB | NPU
94
- | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.519 ms | 0 - 44 MB | NPU
95
- | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 1.569 ms | 0 - 52 MB | NPU
96
- | MNASNet05 | QNN_DLC | float | Qualcomm® QCS8275 | 2.32 ms | 1 - 27 MB | NPU
97
- | MNASNet05 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 0.79 ms | 1 - 2 MB | NPU
98
- | MNASNet05 | QNN_DLC | float | Qualcomm® QCS8450 | 1.569 ms | 0 - 52 MB | NPU
99
- | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 0.384 ms | 1 - 28 MB | NPU
100
- | MNASNet05 | QNN_DLC | float | Qualcomm® SA8295P | 1.435 ms | 0 - 27 MB | NPU
 
 
101
  | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.295 ms | 1 - 29 MB | NPU
102
- | MNASNet05 | QNN_DLC | float | Qualcomm® SA7255P | 2.32 ms | 1 - 27 MB | NPU
103
- | MNASNet05 | QNN_DLC | float | Qualcomm® QCS9075 | 0.975 ms | 3 - 5 MB | NPU
104
- | MNASNet05 | QNN_DLC | float | Qualcomm® QCS8750 | 0.384 ms | 1 - 28 MB | NPU
105
- | MNASNet05 | QNN_DLC | float | Qualcomm® QCS7181 | 0.919 ms | 1 - 1 MB | NPU
106
- | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 0.399 ms | 0 - 0 MB | NPU
 
107
  | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® X Elite | 0.891 ms | 0 - 0 MB | NPU
108
- | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 0.524 ms | 0 - 38 MB | NPU
109
  | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 1 Mobile | 0.953 ms | 0 - 45 MB | NPU
110
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS6490 | 2.25 ms | 2 - 4 MB | NPU
111
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS8275 | 1.721 ms | 0 - 28 MB | NPU
112
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS8550 (Proxy) | 0.762 ms | 0 - 19 MB | NPU
 
 
 
113
  | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS8450 | 0.953 ms | 0 - 45 MB | NPU
114
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS9075 | 0.917 ms | 2 - 4 MB | NPU
115
- | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.305 ms | 0 - 28 MB | NPU
116
- | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 0.352 ms | 0 - 28 MB | NPU
117
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA8295P | 1.219 ms | 0 - 25 MB | NPU
118
  | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 0.79 ms | 0 - 27 MB | NPU
119
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCM6690 | 3.052 ms | 0 - 140 MB | NPU
120
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA7255P | 1.721 ms | 0 - 28 MB | NPU
121
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS7790 | 0.79 ms | 0 - 27 MB | NPU
122
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS8750 | 0.352 ms | 0 - 28 MB | NPU
123
- | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS7181 | 0.891 ms | 0 - 0 MB | NPU
124
- | MNASNet05 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.517 ms | 0 - 45 MB | NPU
125
- | MNASNet05 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 1.575 ms | 0 - 47 MB | NPU
126
- | MNASNet05 | TFLITE | float | Qualcomm® QCS8275 | 2.335 ms | 0 - 28 MB | NPU
127
- | MNASNet05 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 0.799 ms | 0 - 2 MB | NPU
128
- | MNASNet05 | TFLITE | float | Qualcomm® SA8775P | 2.115 ms | 0 - 30 MB | GPU
129
- | MNASNet05 | TFLITE | float | Qualcomm® SA8650P | 2.115 ms | 0 - 30 MB | GPU
130
- | MNASNet05 | TFLITE | float | Qualcomm® SA8255P | 2.115 ms | 0 - 30 MB | GPU
131
- | MNASNet05 | TFLITE | float | Qualcomm® QCS8450 | 1.575 ms | 0 - 47 MB | NPU
132
- | MNASNet05 | TFLITE | float | Snapdragon® 8 Elite Mobile | 0.381 ms | 0 - 29 MB | NPU
133
- | MNASNet05 | TFLITE | float | Qualcomm® SA8295P | 1.449 ms | 0 - 28 MB | NPU
 
 
134
  | MNASNet05 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.295 ms | 0 - 30 MB | NPU
135
- | MNASNet05 | TFLITE | float | Qualcomm® SA7255P | 2.335 ms | 0 - 28 MB | NPU
136
- | MNASNet05 | TFLITE | float | Qualcomm® QCS9075 | 0.985 ms | 0 - 8 MB | NPU
137
- | MNASNet05 | TFLITE | float | Qualcomm® QCS8750 | 0.381 ms | 0 - 29 MB | NPU
 
138
 
139
  ## License
140
  * The license for the original implementation of MNASNet05 can be found
 
16
  MNASNet05 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.
17
 
18
  This is based on the implementation of MNASNet05 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/mnasnet.py).
19
+ 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/v0.58.0/src/qai_hub_models/models/mnasnet05) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
20
 
21
  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.
22
 
 
29
 
30
  | Runtime | Precision | Chipset | SDK Versions | Download |
31
  |---|---|---|---|---|
32
+ | ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-onnx-float.zip)
33
+ | ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-onnx-w8a16.zip)
34
+ | QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-qnn_dlc-float.zip)
35
+ | QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-qnn_dlc-w8a16.zip)
36
+ | TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-tflite-float.zip)
37
 
38
  For more device-specific assets and performance metrics, visit **[MNASNet05 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/mnasnet05)**.
39
 
40
 
41
  ### Option 2: Export with Custom Configurations
42
 
43
+ Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/mnasnet05) Python library to compile and export the model with your own:
44
  - Custom weights (e.g., fine-tuned checkpoints)
45
  - Custom input shapes
46
  - Target device and runtime configurations
47
 
48
  This option is ideal if you need to customize the model beyond the default configuration provided here.
49
 
50
+ See our repository for [MNASNet05 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.58.0/src/qai_hub_models/models/mnasnet05) for usage instructions.
51
 
52
  ## Model Details
53
 
 
63
  ## Performance Summary
64
  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
65
  |---|---|---|---|---|---|---
66
+ | MNASNet05 | ONNX | float | Snapdragon® X2 Elite | 0.245 ms | 2 - 2 MB | NPU
67
+ | MNASNet05 | ONNX | float | Snapdragon® X Elite | 0.483 ms | 5 - 5 MB | NPU
68
+ | MNASNet05 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.331 ms | 1 - 48 MB | NPU
69
+ | MNASNet05 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 0.871 ms | 1 - 51 MB | NPU
70
+ | MNASNet05 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.483 ms | 0 - 7 MB | NPU
71
+ | MNASNet05 | ONNX | float | Qualcomm® QCS8450 | 0.871 ms | 1 - 51 MB | NPU
72
+ | MNASNet05 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 0.812 ms | 1 - 3 MB | NPU
73
+ | MNASNet05 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.224 ms | 0 - 28 MB | NPU
74
+ | MNASNet05 | ONNX | float | Snapdragon® 8 Elite Mobile | 0.269 ms | 0 - 32 MB | NPU
75
+ | MNASNet05 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 0.269 ms | 0 - 32 MB | NPU
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+ | MNASNet05 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 0.483 ms | 5 - 5 MB | NPU
77
+ | MNASNet05 | ONNX | w8a16 | Snapdragon® X2 Elite | 0.215 ms | 1 - 1 MB | NPU
78
+ | MNASNet05 | ONNX | w8a16 | Snapdragon® X Elite | 0.52 ms | 0 - 0 MB | NPU
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+ | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 0.35 ms | 0 - 44 MB | NPU
80
+ | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 0.664 ms | 0 - 48 MB | NPU
81
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 2.151 ms | 0 - 3 MB | NPU
82
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.518 ms | 0 - 16 MB | NPU
83
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® QCS8450 | 0.664 ms | 0 - 48 MB | NPU
84
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 0.657 ms | 0 - 3 MB | NPU
85
+ | MNASNet05 | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 0.53 ms | 0 - 31 MB | NPU
86
+ | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.216 ms | 0 - 33 MB | NPU
87
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 2.232 ms | 0 - 145 MB | NPU
88
+ | MNASNet05 | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 0.259 ms | 0 - 30 MB | NPU
89
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 0.53 ms | 0 - 31 MB | NPU
90
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 0.259 ms | 0 - 30 MB | NPU
91
+ | MNASNet05 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 0.52 ms | 0 - 0 MB | NPU
92
+ | MNASNet05 | QNN_DLC | float | Snapdragon® X2 Elite | 0.411 ms | 1 - 1 MB | NPU
93
+ | MNASNet05 | QNN_DLC | float | Snapdragon® X Elite | 0.915 ms | 1 - 1 MB | NPU
94
+ | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.509 ms | 0 - 44 MB | NPU
95
+ | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 1.564 ms | 0 - 47 MB | NPU
96
+ | MNASNet05 | QNN_DLC | float | Qualcomm® QCS8275 | 2.347 ms | 1 - 28 MB | NPU
97
+ | MNASNet05 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.783 ms | 1 - 16 MB | NPU
98
+ | MNASNet05 | QNN_DLC | float | Qualcomm® SA8775P | 1.102 ms | 0 - 30 MB | NPU
99
+ | MNASNet05 | QNN_DLC | float | Qualcomm® SA8650P | 1.102 ms | 0 - 30 MB | NPU
100
+ | MNASNet05 | QNN_DLC | float | Qualcomm® SA8255P | 1.102 ms | 0 - 30 MB | NPU
101
+ | MNASNet05 | QNN_DLC | float | Qualcomm® QCS8450 | 1.564 ms | 0 - 47 MB | NPU
102
+ | MNASNet05 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 1.102 ms | 1 - 3 MB | NPU
103
  | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.295 ms | 1 - 29 MB | NPU
104
+ | MNASNet05 | QNN_DLC | float | Qualcomm® SA7255P | 2.347 ms | 1 - 28 MB | NPU
105
+ | MNASNet05 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 0.389 ms | 0 - 28 MB | NPU
106
+ | MNASNet05 | QNN_DLC | float | Qualcomm® SA8295P | 1.437 ms | 0 - 28 MB | NPU
107
+ | MNASNet05 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 0.389 ms | 0 - 28 MB | NPU
108
+ | MNASNet05 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 0.915 ms | 1 - 1 MB | NPU
109
+ | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 0.407 ms | 0 - 0 MB | NPU
110
  | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® X Elite | 0.891 ms | 0 - 0 MB | NPU
111
+ | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 0.528 ms | 0 - 39 MB | NPU
112
  | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 1 Mobile | 0.953 ms | 0 - 45 MB | NPU
113
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 2.72 ms | 0 - 2 MB | NPU
114
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS8275 | 1.656 ms | 0 - 27 MB | NPU
115
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.767 ms | 0 - 13 MB | NPU
116
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA8775P | 0.955 ms | 0 - 29 MB | NPU
117
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA8650P | 0.955 ms | 0 - 29 MB | NPU
118
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA8255P | 0.955 ms | 0 - 29 MB | NPU
119
  | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® QCS8450 | 0.953 ms | 0 - 45 MB | NPU
120
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 0.859 ms | 2 - 4 MB | NPU
 
 
 
121
  | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 0.79 ms | 0 - 27 MB | NPU
122
+ | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.298 ms | 0 - 29 MB | NPU
123
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 3.056 ms | 0 - 143 MB | NPU
124
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA7255P | 1.656 ms | 0 - 27 MB | NPU
125
+ | MNASNet05 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 0.351 ms | 0 - 28 MB | NPU
126
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® SA8295P | 1.232 ms | 0 - 25 MB | NPU
127
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 0.79 ms | 0 - 27 MB | NPU
128
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 0.351 ms | 0 - 28 MB | NPU
129
+ | MNASNet05 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 0.891 ms | 0 - 0 MB | NPU
130
+ | MNASNet05 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.524 ms | 0 - 46 MB | NPU
131
+ | MNASNet05 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 1.579 ms | 0 - 50 MB | NPU
132
+ | MNASNet05 | TFLITE | float | Qualcomm® QCS8275 | 2.359 ms | 0 - 28 MB | NPU
133
+ | MNASNet05 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 0.796 ms | 0 - 2 MB | NPU
134
+ | MNASNet05 | TFLITE | float | Qualcomm® SA8775P | 1.109 ms | 0 - 31 MB | NPU
135
+ | MNASNet05 | TFLITE | float | Qualcomm® SA8650P | 1.109 ms | 0 - 31 MB | NPU
136
+ | MNASNet05 | TFLITE | float | Qualcomm® SA8255P | 1.109 ms | 0 - 31 MB | NPU
137
+ | MNASNet05 | TFLITE | float | Qualcomm® QCS8450 | 1.579 ms | 0 - 50 MB | NPU
138
+ | MNASNet05 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 0.982 ms | 0 - 8 MB | NPU
139
  | MNASNet05 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.295 ms | 0 - 30 MB | NPU
140
+ | MNASNet05 | TFLITE | float | Qualcomm® SA7255P | 2.359 ms | 0 - 28 MB | NPU
141
+ | MNASNet05 | TFLITE | float | Snapdragon® 8 Elite Mobile | 0.382 ms | 0 - 28 MB | NPU
142
+ | MNASNet05 | TFLITE | float | Qualcomm® SA8295P | 1.441 ms | 0 - 28 MB | NPU
143
+ | MNASNet05 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 0.382 ms | 0 - 28 MB | NPU
144
 
145
  ## License
146
  * The license for the original implementation of MNASNet05 can be found
release_assets.json CHANGED
@@ -1,5 +1,5 @@
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  {
2
- "version": "0.57.3",
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  "precisions": {
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  "float": {
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  "universal_assets": {
@@ -8,20 +8,20 @@
8
  "qairt": "2.45.0.260326154327",
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  "litert": "1.4.4"
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  },
11
- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-tflite-float.zip"
12
  },
13
  "qnn_dlc": {
14
  "tool_versions": {
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  "qairt": "2.45.0.260326154327"
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  },
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- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-qnn_dlc-float.zip"
18
  },
19
  "onnx": {
20
  "tool_versions": {
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  "qairt": "2.45.0.260326154327",
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  "onnx_runtime": "1.25.0"
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  },
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- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-onnx-float.zip"
25
  }
26
  }
27
  },
@@ -31,14 +31,14 @@
31
  "tool_versions": {
32
  "qairt": "2.45.0.260326154327"
33
  },
34
- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-qnn_dlc-w8a16.zip"
35
  },
36
  "onnx": {
37
  "tool_versions": {
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  "qairt": "2.45.0.260326154327",
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  "onnx_runtime": "1.25.0"
40
  },
41
- "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.57.3/mnasnet05-onnx-w8a16.zip"
42
  }
43
  }
44
  }
 
1
  {
2
+ "version": "0.58.0",
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  "precisions": {
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  "float": {
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8
  "qairt": "2.45.0.260326154327",
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  "litert": "1.4.4"
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-tflite-float.zip"
12
  },
13
  "qnn_dlc": {
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  "tool_versions": {
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  "qairt": "2.45.0.260326154327"
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-qnn_dlc-float.zip"
18
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  "onnx": {
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+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-onnx-float.zip"
25
  }
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  }
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  },
 
31
  "tool_versions": {
32
  "qairt": "2.45.0.260326154327"
33
  },
34
+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-qnn_dlc-w8a16.zip"
35
  },
36
  "onnx": {
37
  "tool_versions": {
38
  "qairt": "2.45.0.260326154327",
39
  "onnx_runtime": "1.25.0"
40
  },
41
+ "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/mnasnet05/releases/v0.58.0/mnasnet05-onnx-w8a16.zip"
42
  }
43
  }
44
  }