def PPHGNet_base(pretrained=False, use_ssld=True, **kwargs):
    """
    PPHGNet_base
    Args:
        pretrained: bool=False or str. If `True` load pretrained parameters, `False` otherwise.
                    If str, means the path of the pretrained model.
        use_ssld: bool=False. Whether using distillation pretrained model when pretrained=True.
    Returns:
        model: nn.Layer. Specific `PPHGNet_base` model depends on args.
    """
    stage_config = {
        # in_channels, mid_channels, out_channels, blocks, downsample
        "stage1": [160, 192, 320, 1, False, [2, 1]],
        "stage2": [320, 224, 640, 2, True, [1, 2]],
        "stage3": [640, 256, 960, 3, True, [2, 1]],
        "stage4": [960, 288, 1280, 2, True, [2, 1]],
    }

    model = PPHGNet(
        stem_channels=[96, 96, 160],
        stage_config=stage_config,
        layer_num=7,
        **kwargs)
    return model

    PPHGNet_base
    Args:
        pretrained: bool=False or str. If `True` load pretrained parameters, `False` otherwise.
                    If str, means the path of the pretrained model.
        use_ssld: bool=False. Whether using distillation pretrained model when pretrained=True.
    Returns:
        model: nn.Layer. Specific `PPHGNet_base` model depends on args.
    
pytorchocr/modeling/backbones/rec_hgnet.py