o Qe-$@sddlmZddlmZddlZddlmZddlmmZddlm Z m Z m Z ddlm Z m Z mZddlmZddlmZddlmZgZd d iZd d ZGd ddejZGdddejZGdddejZddd ZdS))division)print_functionN)Conv2DLinearDropout) MaxPool2D AvgPool2DAdaptiveAvgPool2D)Uniform) ParamAttr)get_weights_path_from_url googlenet)zWhttps://paddle-imagenet-models-name.bj.bcebos.com/dygraph/GoogLeNet_pretrained.pdparamsZ 80c06f038e905c53ab32c40eca6e26aecCs*d|d|d}tt| |d}|S)Ng@g?)Z initializer)r r )Zchannels filter_sizeZstdvZ param_attrrND:\Projects\ConvertPro\env\Lib\site-packages\paddle/vision/models/googlenet.pyxavier%srcs*eZdZ  dfdd ZddZZS) ConvLayerc s2tt|t|||||dd|dd|_dS)NrrF)Z in_channelsZ out_channels kernel_sizestridepaddinggroupsZ bias_attr)superr__init__r_conv)selfZ num_channelsZ num_filtersrrr __class__rrr-s  zConvLayer.__init__cCs||}|S)N)r)rinputsyrrrforward=s zConvLayer.forward)rr__name__ __module__ __qualname__rr! __classcell__rrrrr+s rcs$eZdZfddZddZZS) Inceptionc svtt|t||d|_t||d|_t||d|_t||d|_t||d|_t dddd|_ t||d|_ dS)Nr)rrr) rr'rr_conv1_conv3r_conv3_conv5r_conv5r_pool_convprj) rZinput_channelsZoutput_channelsZfilter1Zfilter3RZfilter3Zfilter5RZfilter5ZprojrrrrDszInception.__init__c Csj||}||}||}||}||}||}||}tj||||gdd} t | } | S)NrZaxis) r*r+r,r-r.r/r0paddleconcatFrelu) rrZconv1Zconv3rZconv3Zconv5rZconv5poolZconvprjcatrrrr!Qs        zInception.forwardr"rrrrr'Bs  r'cs*eZdZdZdfdd ZddZZS) GoogLeNetajGoogLeNet (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 stt|||_||_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$dd|_%td |td dd!|_&dSdS)%Nr(@r)rrr` i0ipi ii@i@ir)rg?Zdownscale_in_infer)pmodei)Z weight_attriigffffff?)'rr8r num_classes with_poolrrrr/_conv_1_conv_2r'_ince3a_ince3b_ince4a_ince4b_ince4c_ince4d_ince4e_ince5a_ince5br _pool_5r_pool_o1_pool_o2r_droprr_fc_out_conv_o1_fc_o1_drop_o1_out1_conv_o2_fc_o2_drop_o2_out2)rrKrLrrrr~sF  zGoogLeNet.__init__c Cs||}||}||}||}||}||}||}||}||}||}||}| |}| |}||}| |}| |}|||}}}|j rj||}||}||}|jdkr||}tj|ddgd}||}||}tj|ddd}||}t|}||}||}||}tj|ddd}||}||}| |}|||gS)Nrrr(r1r)Z start_axisZ stop_axis)!rr/rMrNrOrPrQrRrSrTrUrVrWrLrXrYrZrKr[r2Zsqueezer\r]flattenr^r4r5r_r`rarbrcrd) rrxZince4aZince4dZince5boutZout1Zout2rrrr!sJ                                zGoogLeNet.forward)r9T)r#r$r%__doc__rr!r&rrrrr8bs1r8FcKs^tdi|}d}|r-|tvsJd|tt|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 zL{} model do not have a pretrained model now, you should set pretrained=FalserrNr)r8 model_urlsformatr r2loadZset_dict)Z pretrainedkwargsmodelarchZ weight_pathparamrrrr s     )F) __future__rrr2Z paddle.nnnnZpaddle.nn.functionalZ functionalr4rrrrrr Zpaddle.nn.initializerr Zpaddle.fluid.param_attrr Zpaddle.utils.downloadr __all__rjrZLayerrr'r8r rrrrs&       ~