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qualcomm
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ControlNet

Unconditional Image Generation
PyTorch
generative_ai
android
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v0.30.2

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See https://github.com/quic/ai-hub-models/releases/v0.30.2 for changelog.

Files changed (8) hide show
  1. ControlNet_Quantized.bin +0 -3
  2. README.md +39 -40
  3. TextEncoder_Quantized.bin +0 -3
  4. TextEncoder_Quantized.so +0 -3
  5. UNet_Quantized.bin +0 -3
  6. UNet_Quantized.so +0 -3
  7. VAEDecoder_Quantized.bin +0 -3
  8. VAEDecoder_Quantized.so +0 -3
ControlNet_Quantized.bin DELETED
@@ -1,3 +0,0 @@
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README.md CHANGED
@@ -1,9 +1,8 @@
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  ---
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  library_name: pytorch
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- license: apache-2.0
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  tags:
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  - generative_ai
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- - quantized
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  - android
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  pipeline_tag: unconditional-image-generation
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@@ -27,7 +26,7 @@ More details on model performance across various devices, can be found
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  ### Model Details
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- - **Model Type:** Image generation
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  - **Model Stats:**
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  - Input: Text prompt and input image as a reference
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  - Conditioning Input: Canny-Edge
@@ -37,20 +36,20 @@ More details on model performance across various devices, can be found
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  - ControlNet Number of parameters: 361M
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  - Model size: 1.4GB
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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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- | TextEncoder_Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 11.394 ms | 0 - 74 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/TextEncoder_Quantized.bin) |
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- | TextEncoder_Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 8.08 ms | 0 - 137 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/TextEncoder_Quantized.bin) |
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- | TextEncoder_Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 10.982 ms | 0 - 1 MB | UINT16 | NPU | Use Export Script |
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- | UNet_Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 262.52 ms | 11 - 17 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/UNet_Quantized.bin) |
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- | UNet_Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 192.789 ms | 3 - 1247 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/UNet_Quantized.bin) |
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- | UNet_Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 260.158 ms | 14 - 15 MB | UINT16 | NPU | Use Export Script |
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- | VAEDecoder_Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 390.243 ms | 0 - 36 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/VAEDecoder_Quantized.bin) |
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- | VAEDecoder_Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 294.404 ms | 0 - 88 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/VAEDecoder_Quantized.bin) |
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- | VAEDecoder_Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 379.548 ms | 0 - 1 MB | UINT16 | NPU | Use Export Script |
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- | ControlNet_Quantized | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 100.33 ms | 2 - 68 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/ControlNet_Quantized.bin) |
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- | ControlNet_Quantized | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 76.94 ms | 0 - 533 MB | UINT16 | NPU | [ControlNet.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/ControlNet_Quantized.bin) |
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- | ControlNet_Quantized | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 103.52 ms | 2 - 3 MB | UINT16 | NPU | Use Export Script |
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@@ -112,39 +111,39 @@ python -m qai_hub_models.models.controlnet.export
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  Profiling Results
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  ------------------------------------------------------------
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  TextEncoder_Quantized
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- Device : Samsung Galaxy S23 (13)
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- Runtime : QNN
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- Estimated inference time (ms) : 11.4
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- Estimated peak memory usage (MB): [0, 74]
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- Total # Ops : 570
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- Compute Unit(s) : NPU (570 ops)
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  ------------------------------------------------------------
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  UNet_Quantized
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- Device : Samsung Galaxy S23 (13)
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- Runtime : QNN
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- Estimated inference time (ms) : 262.5
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- Estimated peak memory usage (MB): [11, 17]
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- Total # Ops : 5434
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- Compute Unit(s) : NPU (5434 ops)
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  ------------------------------------------------------------
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  VAEDecoder_Quantized
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- Device : Samsung Galaxy S23 (13)
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- Runtime : QNN
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- Estimated inference time (ms) : 390.2
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- Estimated peak memory usage (MB): [0, 36]
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- Total # Ops : 409
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- Compute Unit(s) : NPU (409 ops)
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  ------------------------------------------------------------
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  ControlNet_Quantized
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- Device : Samsung Galaxy S23 (13)
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- Runtime : QNN
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- Estimated inference time (ms) : 100.3
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- Estimated peak memory usage (MB): [2, 68]
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- Total # Ops : 2406
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- Compute Unit(s) : NPU (2406 ops)
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  ```
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  ---
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  library_name: pytorch
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+ license: other
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  tags:
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  - generative_ai
 
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  - android
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  pipeline_tag: unconditional-image-generation
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26
 
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  ### Model Details
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+ - **Model Type:** Model_use_case.image_generation
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  - **Model Stats:**
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  - Input: Text prompt and input image as a reference
32
  - Conditioning Input: Canny-Edge
 
36
  - ControlNet Number of parameters: 361M
37
  - Model size: 1.4GB
38
 
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+ | Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model
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  |---|---|---|---|---|---|---|---|---|
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+ | TextEncoder_Quantized | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN | 10.874 ms | 0 - 3 MB | NPU | Use Export Script |
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+ | TextEncoder_Quantized | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN | 7.918 ms | 0 - 18 MB | NPU | Use Export Script |
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+ | TextEncoder_Quantized | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN | 10.875 ms | 0 - 3 MB | NPU | Use Export Script |
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+ | UNet_Quantized | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN | 258.151 ms | 13 - 15 MB | NPU | Use Export Script |
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+ | UNet_Quantized | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN | 197.629 ms | 13 - 31 MB | NPU | Use Export Script |
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+ | UNet_Quantized | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN | 256.936 ms | 13 - 16 MB | NPU | Use Export Script |
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+ | VAEDecoder_Quantized | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN | 397.625 ms | 0 - 2 MB | NPU | Use Export Script |
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+ | VAEDecoder_Quantized | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN | 300.627 ms | 0 - 21 MB | NPU | Use Export Script |
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+ | VAEDecoder_Quantized | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN | 395.006 ms | 0 - 3 MB | NPU | Use Export Script |
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+ | ControlNet_Quantized | w8a16 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN | 104.668 ms | 2 - 9 MB | NPU | Use Export Script |
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+ | ControlNet_Quantized | w8a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN | 77.289 ms | 2 - 23 MB | NPU | Use Export Script |
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+ | ControlNet_Quantized | w8a16 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN | 103.817 ms | 2 - 5 MB | NPU | Use Export Script |
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111
  Profiling Results
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  ------------------------------------------------------------
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  TextEncoder_Quantized
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+ Device : cs_8_gen_2 (ANDROID 13)
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+ Runtime : QNN
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+ Estimated inference time (ms) : 10.9
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+ Estimated peak memory usage (MB): [0, 3]
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+ Total # Ops : 569
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+ Compute Unit(s) : npu (569 ops) gpu (0 ops) cpu (0 ops)
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  ------------------------------------------------------------
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  UNet_Quantized
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+ Device : cs_8_gen_2 (ANDROID 13)
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+ Runtime : QNN
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+ Estimated inference time (ms) : 258.2
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+ Estimated peak memory usage (MB): [13, 15]
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+ Total # Ops : 5433
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+ Compute Unit(s) : npu (5433 ops) gpu (0 ops) cpu (0 ops)
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  ------------------------------------------------------------
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  VAEDecoder_Quantized
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+ Device : cs_8_gen_2 (ANDROID 13)
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+ Runtime : QNN
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+ Estimated inference time (ms) : 397.6
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+ Estimated peak memory usage (MB): [0, 2]
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+ Total # Ops : 408
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+ Compute Unit(s) : npu (408 ops) gpu (0 ops) cpu (0 ops)
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  ------------------------------------------------------------
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  ControlNet_Quantized
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+ Device : cs_8_gen_2 (ANDROID 13)
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+ Runtime : QNN
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+ Estimated inference time (ms) : 104.7
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+ Estimated peak memory usage (MB): [2, 9]
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+ Total # Ops : 2405
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+ Compute Unit(s) : npu (2405 ops) gpu (0 ops) cpu (0 ops)
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  ```
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