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FFNet-40S

Image Segmentation
PyTorch
LiteRT
ONNX
real_time
android
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@@ -36,45 +36,44 @@ More details on model performance across various devices, can be found
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  | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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  |---|---|---|---|---|---|---|---|---|
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- | FFNet-40S | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 45.422 ms | 4 - 21 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 54.991 ms | 24 - 41 MB | FP16 | NPU | [FFNet-40S.so](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.so) |
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- | FFNet-40S | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 35.72 ms | 29 - 101 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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- | FFNet-40S | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 29.716 ms | 2 - 49 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 37.476 ms | 14 - 56 MB | FP16 | NPU | [FFNet-40S.so](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.so) |
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- | FFNet-40S | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 25.75 ms | 26 - 70 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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- | FFNet-40S | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 23.928 ms | 1 - 49 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 32.713 ms | 12 - 54 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 24.234 ms | 30 - 72 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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- | FFNet-40S | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 44.925 ms | 2 - 22 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 41.513 ms | 24 - 27 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | SA7255P ADP | SA7255P | TFLITE | 853.906 ms | 3 - 46 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | SA7255P ADP | SA7255P | QNN | 842.941 ms | 24 - 34 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 45.165 ms | 4 - 26 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | SA8255 (Proxy) | SA8255P Proxy | QNN | 41.508 ms | 24 - 26 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | SA8295P ADP | SA8295P | TFLITE | 66.395 ms | 2 - 45 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | SA8295P ADP | SA8295P | QNN | 64.583 ms | 24 - 38 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 45.194 ms | 2 - 23 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | SA8650 (Proxy) | SA8650P Proxy | QNN | 41.421 ms | 24 - 26 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | SA8775P ADP | SA8775P | TFLITE | 71.816 ms | 2 - 46 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | SA8775P ADP | SA8775P | QNN | 65.545 ms | 24 - 34 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 57.324 ms | 2 - 47 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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- | FFNet-40S | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 69.305 ms | 23 - 62 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 42.428 ms | 24 - 24 MB | FP16 | NPU | Use Export Script |
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- | FFNet-40S | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 38.682 ms | 24 - 24 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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  ## Installation
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- This model can be installed as a Python package via pip.
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  ```bash
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- pip install "qai-hub-models[ffnet_40s]"
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  ```
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-
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  ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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  Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
@@ -125,8 +124,8 @@ Profiling Results
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  FFNet-40S
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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- Estimated inference time (ms) : 45.4
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- Estimated peak memory usage (MB): [4, 21]
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  Total # Ops : 94
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  Compute Unit(s) : NPU (94 ops)
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  ```
@@ -153,7 +152,7 @@ from qai_hub_models.models.ffnet_40s import Model
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  torch_model = Model.from_pretrained()
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  # Device
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- device = hub.Device("Samsung Galaxy S23")
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  # Trace model
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  input_shape = torch_model.get_input_spec()
@@ -245,7 +244,8 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
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  ## License
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- * The license for the original implementation of FFNet-40S can be found [here](https://github.com/Qualcomm-AI-research/FFNet/blob/master/LICENSE).
 
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  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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  | Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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  |---|---|---|---|---|---|---|---|---|
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+ | FFNet-40S | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 45.018 ms | 2 - 26 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 55.016 ms | 24 - 41 MB | FP16 | NPU | [FFNet-40S.so](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.so) |
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+ | FFNet-40S | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 34.72 ms | 29 - 119 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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+ | FFNet-40S | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 29.645 ms | 1 - 50 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 37.001 ms | 9 - 49 MB | FP16 | NPU | [FFNet-40S.so](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.so) |
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+ | FFNet-40S | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 26.015 ms | 30 - 76 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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+ | FFNet-40S | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 29.038 ms | 9 - 58 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 33.165 ms | 24 - 67 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 23.801 ms | 28 - 70 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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+ | FFNet-40S | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 44.885 ms | 2 - 24 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 41.396 ms | 24 - 27 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | SA7255P ADP | SA7255P | TFLITE | 854.012 ms | 2 - 45 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | SA7255P ADP | SA7255P | QNN | 842.577 ms | 21 - 31 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 45.077 ms | 2 - 21 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | SA8255 (Proxy) | SA8255P Proxy | QNN | 41.467 ms | 24 - 26 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | SA8295P ADP | SA8295P | TFLITE | 66.248 ms | 2 - 45 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | SA8295P ADP | SA8295P | QNN | 64.495 ms | 24 - 38 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 45.311 ms | 2 - 24 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | SA8650 (Proxy) | SA8650P Proxy | QNN | 41.258 ms | 24 - 27 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | SA8775P ADP | SA8775P | TFLITE | 71.761 ms | 2 - 45 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | SA8775P ADP | SA8775P | QNN | 65.652 ms | 24 - 34 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 57.971 ms | 2 - 49 MB | FP16 | NPU | [FFNet-40S.tflite](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.tflite) |
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+ | FFNet-40S | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 69.253 ms | 23 - 60 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 42.478 ms | 24 - 24 MB | FP16 | NPU | Use Export Script |
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+ | FFNet-40S | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 38.729 ms | 24 - 24 MB | FP16 | NPU | [FFNet-40S.onnx](https://huggingface.co/qualcomm/FFNet-40S/blob/main/FFNet-40S.onnx) |
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  ## Installation
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+ Install the package via pip:
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  ```bash
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+ pip install "qai-hub-models[ffnet-40s]"
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  ```
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  ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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  Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
 
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  FFNet-40S
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  Device : Samsung Galaxy S23 (13)
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  Runtime : TFLITE
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+ Estimated inference time (ms) : 45.0
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+ Estimated peak memory usage (MB): [2, 26]
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  Total # Ops : 94
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  Compute Unit(s) : NPU (94 ops)
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  ```
 
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  torch_model = Model.from_pretrained()
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  # Device
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  # Trace model
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  input_shape = torch_model.get_input_spec()
 
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  ## License
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+ * The license for the original implementation of FFNet-40S can be found
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+ [here](https://github.com/Qualcomm-AI-research/FFNet/blob/master/LICENSE).
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  * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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