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Tests and docstrings improvements (#4475)

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Glenn Jocher 2023-08-21 17:02:14 +02:00 • committed by GitHub
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22 changed files with 107 additions and 186 deletions
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9
ultralytics/nn/modules/transformer.py
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@ -97,8 +97,7 @@ class AIFI(TransformerEncoderLayer):
out_w = grid_w.flatten()[..., None] @ omega[None]
out_h = grid_h.flatten()[..., None] @ omega[None]
return torch.concat([torch.sin(out_w), torch.cos(out_w),
torch.sin(out_h), torch.cos(out_h)], axis=1)[None, :, :]
return torch.cat([torch.sin(out_w), torch.cos(out_w), torch.sin(out_h), torch.cos(out_h)], 1)[None]
class TransformerLayer(nn.Module):
@ -170,9 +169,11 @@ class MLP(nn.Module):
return x
# From https://github.com/facebookresearch/detectron2/blob/main/detectron2/layers/batch_norm.py # noqa
# Itself from https://github.com/facebookresearch/ConvNeXt/blob/d1fa8f6fef0a165b27399986cc2bdacc92777e40/models/convnext.py#L119 # noqa
class LayerNorm2d(nn.Module):
"""
LayerNorm2d module from https://github.com/facebookresearch/detectron2/blob/main/detectron2/layers/batch_norm.py
https://github.com/facebookresearch/ConvNeXt/blob/d1fa8f6fef0a165b27399986cc2bdacc92777e40/models/convnext.py#L119
"""
def __init__(self, num_channels, eps=1e-6):
super().__init__()

6
ultralytics/nn/tasks.py
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@ -229,7 +229,7 @@ class DetectionModel(BaseModel):
ch = self.yaml['ch'] = self.yaml.get('ch', ch) # input channels
if nc and nc != self.yaml['nc']:
LOGGER.info(f"Overriding model.yaml nc={self.yaml['nc']} with nc={nc}")
self.yaml['nc'] = nc # override yaml value
self.yaml['nc'] = nc # override YAML value
self.model, self.save = parse_model(deepcopy(self.yaml), ch=ch, verbose=verbose) # model, savelist
self.names = {i: f'{i}' for i in range(self.yaml['nc'])} # default names dict
self.inplace = self.yaml.get('inplace', True)
@ -329,7 +329,7 @@ class ClassificationModel(BaseModel):
ch=3,
nc=None,
cutoff=10,
verbose=True): # yaml, model, channels, number of classes, cutoff index, verbose flag
verbose=True): # YAML, model, channels, number of classes, cutoff index, verbose flag
super().__init__()
self._from_detection_model(model, nc, cutoff) if model is not None else self._from_yaml(cfg, ch, nc, verbose)
@ -357,7 +357,7 @@ class ClassificationModel(BaseModel):
ch = self.yaml['ch'] = self.yaml.get('ch', ch) # input channels
if nc and nc != self.yaml['nc']:
LOGGER.info(f"Overriding model.yaml nc={self.yaml['nc']} with nc={nc}")
self.yaml['nc'] = nc # override yaml value
self.yaml['nc'] = nc # override YAML value
elif not nc and not self.yaml.get('nc', None):
raise ValueError('nc not specified. Must specify nc in model.yaml or function arguments.')
self.model, self.save = parse_model(deepcopy(self.yaml), ch=ch, verbose=verbose) # model, savelist