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segmentation_models_pytorch/decoders/dpt/model.py

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@@ -54,10 +54,10 @@ class DPT(SegmentationModel):
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**callable** and **None**. Default is **None**.
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aux_params: Dictionary with parameters of the auxiliary output (classification head). Auxiliary output is build
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on top of encoder if **aux_params** is not **None** (default). Supported params:
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* classes (int): A number of classes;
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* pooling (str): One of "max", "avg". Default is "avg";
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* dropout (float): Dropout factor in [0, 1);
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* activation (str): An activation function to apply "sigmoid"/"softmax" (could be **None** to return logits).
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- **classes** (*int*): A number of classes;
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- **pooling** (*str*): One of "max", "avg". Default is "avg";
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- **dropout** (*float*): Dropout factor in [0, 1);
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- **activation** (*str*): An activation function to apply "sigmoid"/"softmax" (could be **None** to return logits).
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kwargs: Arguments passed to the encoder class ``__init__()`` function. Applies only to ``timm`` models. Keys with
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``None`` values are pruned before passing. Specify ``dynamic_img_size=True`` to allow the model to handle images of different sizes.
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