Xcode Version: Version 15.2 (15C500b)
com.github.apple.coremltools.source: torch==1.12.1
com.github.apple.coremltools.version: 7.2
Compute: Mixed (Float16, Int32)
Storage: Float16
The input to the mlpackage is MultiArray (Float16 1 × 1 × 544 × 960)
The flexibility is: 1 × 1 × 544 × 960 | 1 × 1 × 384 × 640 | 1 × 1 × 736 × 1280 | 1 × 1 × 1088 × 1920
I tested this on iPhone XR, iPhone 11, iPhone 12, iPhone 13, and iPhone 14. On all devices except the iPhone 11, the model runs correctly on the NPU. However, on the iPhone 11, the model runs on the CPU instead.
Here is the CoreMLTools conversion code I used:
mlmodel = ct.convert(trace,
inputs=[ct.TensorType(shape=input_shape, name="input", dtype=np.float16)],
outputs=[ct.TensorType(name="output", dtype=np.float16, shape=output_shape)],
convert_to='mlprogram',
minimum_deployment_target=ct.target.iOS16
)
laumt
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video url: https://devstreaming-cdn.apple.com/videos/streaming/examples/bipbop_4x3/gear1/prog_index.m3u8
iOS13 is success.