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Add HUB-SDK Docs reference section (#7781)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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Glenn Jocher 2024-01-27 00:21:31 +01:00 • committed by GitHub
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commit ee88882874
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25 changed files with 142 additions and 47 deletions
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12
ultralytics/nn/autobackend.py
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@ -508,9 +508,6 @@ class AutoBackend(nn.Module):
Args:
imgsz (tuple): The shape of the dummy input tensor in the format (batch_size, channels, height, width)
Returns:
(None): This method runs the forward pass and don't return any value
"""
warmup_types = self.pt, self.jit, self.onnx, self.engine, self.saved_model, self.pb, self.triton, self.nn_module
if any(warmup_types) and (self.device.type != "cpu" or self.triton):
@ -521,13 +518,16 @@ class AutoBackend(nn.Module):
@staticmethod
def _model_type(p="path/to/model.pt"):
"""
This function takes a path to a model file and returns the model type.
This function takes a path to a model file and returns the model type. Possibles types are pt, jit, onnx, xml,
engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, ncnn or paddle.
Args:
p: path to the model file. Defaults to path/to/model.pt
Examples:
>>> model = AutoBackend(weights="path/to/model.onnx")
>>> model_type = model._model_type() # returns "onnx"
"""
# Return model type from model path, i.e. path='path/to/model.onnx' -> type=onnx
# types = [pt, jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, paddle]
from ultralytics.engine.exporter import export_formats
sf = list(export_formats().Suffix) # export suffixes