o #j5"@sddlZddlmmZddlmZddlmZddlmZm Z m Z m Z m Z m Z ddlmZddlmZgZddiZd d ZGd d d ejZGd ddejZGdddejZdddZdS)N)nn) ParamAttr)AdaptiveAvgPool2D AvgPool2DConv2DDropoutLinear MaxPool2D)Uniform)get_weights_path_from_url googlenet)zWhttps://paddle-imagenet-models-name.bj.bcebos.com/dygraph/GoogLeNet_pretrained.pdparamsZ 80c06f038e905c53ab32c40eca6e26aecCs*d|d|d}tt| |d}|S)Ng@g?)Z initializer)rr )Zchannels filter_sizeZstdvZ param_attrr_/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/paddle/vision/models/googlenet.pyxavier(srcs(eZdZ dfdd ZddZZS) ConvLayerc s.tt|||||dd|dd|_dS)Nrr F)Z in_channelsZ out_channels kernel_sizestridepaddinggroupsZ bias_attr)super__init__r_conv)selfZ num_channelsZ num_filtersrrr __class__rrr/s   zConvLayer.__init__cCs||}|S)N)r)rinputsyrrrforward>s zConvLayer.forward)rr__name__ __module__ __qualname__rr __classcell__rrrrr.srcs$eZdZfddZddZZS) Inceptionc srtt||d|_t||d|_t||d|_t||d|_t||d|_tdddd|_ t||d|_ dS)Nr)rrr) rrr_conv1_conv3r_conv3_conv5r_conv5r _pool_convprj) rZinput_channelsZoutput_channelsZfilter1Zfilter3RZfilter3Zfilter5RZfilter5ZprojrrrrDs zInception.__init__c Csj||}||}||}||}||}||}||}tj||||gdd} t | } | S)NrZaxis) r)r*r+r,r-r.r/paddleconcatFrelu) rrZconv1Zconv3rZconv3Zconv5rZconv5poolZconvprjcatrrrr Zs        zInception.forwardr!rrrrr&Cs r&cs*eZdZdZdfdd ZddZZS) GoogLeNetaoGoogLeNet (Inception v1) model architecture from `"Going Deeper with Convolutions" `_. Args: num_classes (int, optional): Output dim of last fc layer. If num_classes <= 0, last fc layer will not be defined. Default: 1000. with_pool (bool, optional): Use pool before the last fc layer or not. Default: True. Returns: :ref:`api_paddle_nn_Layer`. An instance of GoogLeNet (Inception v1) model. Examples: .. code-block:: python >>> import paddle >>> from paddle.vision.models import GoogLeNet >>> # Build model >>> model = GoogLeNet() >>> x = paddle.rand([1, 3, 224, 224]) >>> out, out1, out2 = model(x) >>> print(out.shape, out1.shape, out2.shape) [1, 1000] [1, 1000] [1, 1000] Tc st||_||_tdddd|_tddd|_tddd|_tddd|_ t ddddd d d d |_ t d d d d dd dd|_ t d d dddd dd|_ t dddddddd|_t ddd d d ddd|_t dddddd dd|_t ddd ddd d d |_t ddd ddd d d |_t ddddddd d |_|rtd|_tddd|_tddd|_|dkr tddd|_td |td dd!|_tdd d|_td"d td#dd!|_td$dd|_ td |td dd!|_!tdd d|_"td"d td#dd!|_#td$dd|_$td |td dd!|_%dSdS)%Nr'@r )rrr` i0ipi ii@i@ir(rg?Zdownscale_in_infer)pmodei)Z weight_attriigffffff?)&rr num_classes with_poolrrr r._conv_1_conv_2r&_ince3a_ince3b_ince4a_ince4b_ince4c_ince4d_ince4e_ince5a_ince5br_pool_5r_pool_o1_pool_o2r_droprr_fc_out_conv_o1_fc_o1_drop_o1_out1_conv_o2_fc_o2_drop_o2_out2)rrJrKrrrrsD    zGoogLeNet.__init__c Cs||}||}||}||}||}||}||}||}||}||}||}| |}| |}||}| |}| |}|||}}}|j rj||}||}||}|jdkr||}tj|ddgd}||}||}tj|ddd}||}t|}||}||}||}tj|ddd}||}||}| |}|||gS)Nrr r'r0r)Z start_axisZ stop_axis)!rr.rLrMrNrOrPrQrRrSrTrUrVrKrWrXrYrJrZr1Zsqueezer[r\flattenr]r3r4r^r_r`rarbrc) rrxZince4aZince4dZince5boutZout1Zout2rrrr sJ                                zGoogLeNet.forward)r8T)r"r#r$__doc__rr r%rrrrr7ks1r7FcKs^tdi|}d}|r-|tvsJ|dtt|dt|d}t|}|||S)aGoogLeNet (Inception v1) model architecture from `"Going Deeper with Convolutions" `_. Args: pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained on ImageNet. Default: False. **kwargs (optional): Additional keyword arguments. For details, please refer to :ref:`GoogLeNet `. Returns: :ref:`api_paddle_nn_Layer`. An instance of GoogLeNet (Inception v1) model. Examples: .. code-block:: python >>> import paddle >>> from paddle.vision.models import googlenet >>> # Build model >>> model = googlenet() >>> # Build model and load imagenet pretrained weight >>> # model = googlenet(pretrained=True) >>> x = paddle.rand([1, 3, 224, 224]) >>> out, out1, out2 = model(x) >>> print(out.shape, out1.shape, out2.shape) [1, 1000] [1, 1000] [1, 1000] r zJ model do not have a pretrained model now, you should set pretrained=FalserrNr)r7 model_urlsr r1loadZset_dict)Z pretrainedkwargsmodelarchZ weight_pathparamrrrr s   )F)r1Zpaddle.nn.functionalrZ functionalr3Zpaddle.base.param_attrrZ paddle.nnrrrrrr Zpaddle.nn.initializerr Zpaddle.utils.downloadr __all__rirZLayerrr&r7r rrrrs     (~