o + iúã@sVddlmZddlmZddlZddlmZerddlmZgZGdd„dejƒZ dS)é)Ú annotations)Ú TYPE_CHECKINGN)Únn)ÚTensorcs8eZdZUdZded<d d‡fdd„ Zdd d „Z‡ZS)ÚLeNetaœLeNet model from `"Gradient-based learning applied to document recognition" `_. Args: num_classes (int, optional): Output dim of last fc layer. If num_classes <= 0, last fc layer will not be defined. Default: 10. Returns: :ref:`api_paddle_nn_Layer`. An instance of LeNet model. Examples: .. code-block:: python >>> import paddle >>> from paddle.vision.models import LeNet >>> model = LeNet() >>> x = paddle.rand([1, 1, 28, 28]) >>> out = model(x) >>> print(out.shape) [1, 10] ÚintÚ num_classesé ÚreturnÚNonec s–tƒ ¡||_t tjddddddt ¡t dd¡tjddddddt ¡t dd¡¡|_|dkrIt t  d d ¡t  d d ¡t  d |¡¡|_ dSdS) Nééé)ZstrideÚpaddingééériéxéT) ÚsuperÚ__init__rrZ SequentialZConv2DZReLUZ MaxPool2DÚfeaturesZLinearÚfc)Úselfr©Ú __class__©úf/home/app/PaddleOCR-VL-test/.venv_paddleocr/lib/python3.10/site-packages/paddle/vision/models/lenet.pyr:s"   ú     ýÿzLeNet.__init__ÚinputsrcCs.| |¡}|jdkrt |d¡}| |¡}|S)Nrr )rrÚpaddleÚflattenr)rrÚxrrrÚforwardMs    z LeNet.forward)r )rrr r )rrr r)Ú__name__Ú __module__Ú __qualname__Ú__doc__Ú__annotations__rr"Ú __classcell__rrrrrs r) Ú __future__rÚtypingrrrrÚ__all__ZLayerrrrrrÚs