Imagenet_train/timm/models/operations.py
def build_upsample_neg_stride(name=None, stride=None, **kwargs):
    """ Use negative stride to represent scales, i.e., stride=-2 means scale=2
        Return upsample op if the stride is negative, return None otherwise
        Reset and return the stride to 1 if it is negative
    """
    if name is None:
        return None, stride

    if isinstance(stride, numbers.Number):
        if stride > 0:
            return None, stride
        stride = (stride, stride)
    assert isinstance(stride, (tuple, list))

    neg_strides = all(x < 0 for x in stride)
    if not neg_strides:
        return None, stride

    scales = [-x for x in stride]
    if name == "default":
        ret = Upsample(scale_factor=scales, **kwargs)
    else:
        ret = None
    return ret, 1
 Use negative stride to represent scales, i.e., stride=-2 means scale=2
        Return upsample op if the stride is negative, return None otherwise
        Reset and return the stride to 1 if it is negative
    
Use negative stride to represent scales, i.e., stride=-2 means scale=2
Return upsample op if the stride is negative, return None otherwise
Reset and return the stride to 1 if it is negative
Use negative stride to represent scales i . e . stride = - 2 means scale = 2 Return upsample op if the stride is negative return None otherwise Reset and return the stride to 1 if it is negative
def build_upsample_neg_stride(name=None, stride=None, **kwargs):
    if name is None:
        return None, stride
    if isinstance(stride, numbers.Number):
        if stride > 0:
            return None, stride
        stride = (stride, stride)
    assert isinstance(stride, (tuple, list))
    neg_strides = all(x < 0 for x in stride)
    if not neg_strides:
        return None, stride
    scales = [-x for x in stride]
    if name == "default":
        ret = Upsample(scale_factor=scales, **kwargs)
    else:
        ret = None
    return ret, 1
def build_upsample_neg_stride ( name = None , stride = None , ** kwargs ) : if name is None : return None , stride if isinstance ( stride , numbers . Number ) : if stride > 0 : return None , stride stride = ( stride , stride ) assert isinstance ( stride , ( tuple , list ) ) neg_strides = all ( x < 0 for x in stride ) if not neg_strides : return None , stride scales = [ - x for x in stride ] if name == "default" : ret = Upsample ( scale_factor = scales , ** kwargs ) else : ret = None return ret , 1
Use negative stride to represent scales, i.e., stride=-2 means scale=2
Return upsample op if the stride is negative, return None otherwise
Reset and return the stride to 1 if it is negative
Use negative stride to represent scales i . e . stride = - 2 means scale = 2 Return upsample op if the stride is negative return None otherwise Reset and return the stride to 1 if it is negative
""" Use negative stride to represent scales, i.e., stride=-2 means scale=2
        Return upsample op if the stride is negative, return None otherwise
        Reset and return the stride to 1 if it is negative
    """
name
stride