|j(%fddlmZddlmZmZddlmZmZddlZddl m cm Z ddlm Z ddl mZddlmZmZmZmZmZmZddlmZdd lmZerdd lmZdd lmZGd d eZgZddiZd"dZ Gdde j!Z"Gdde j!Z#Gdde j!Z$ d#d$d!Z%dS)%) annotations) TYPE_CHECKING TypedDict) NotRequiredUnpackN)nn) ParamAttr)AdaptiveAvgPool2D AvgPool2DConv2DDropoutLinear MaxPool2D)Uniform)get_weights_path_from_url)Tensor)Size2c$eZdZUded<ded<dS)_GoogLeNetOptionszNotRequired[int] num_classeszNotRequired[bool] with_poolN)__name__ __module__ __qualname____annotations__n/lsinfo/ai/hellotax_ai/data_center/backend/venv/lib/python3.11/site-packages/paddle/vision/models/googlenet.pyrr+s*%%%%$$$$$$rr googlenet)zWhttps://paddle-imagenet-models-name.bj.bcebos.com/dygraph/GoogLeNet_pretrained.pdparams 80c06f038e905c53ab32c40eca6e26aechannelsint filter_sizereturnr c`d|dz|zz dz}tt| |}|S)Ng@g?) initializer)r r)r!r#stdv param_attrs rxavierr*:s< ;>H, -# 5Dwud';';<<`_. 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) paddle.Size([1, 1000]) paddle.Size([1, 1000]) paddle.Size([1, 1000]) r"rboolrTr$Nonec t||_||_t dddd|_t dd|_t ddd|_t ddd|_ tddddd d d d |_ td d d d dd dd|_ td d dddd dd|_ tdddddddd|_tddd d d ddd|_tdddddd dd|_tddd ddd d d |_tddd ddd d d |_tddddddd d |_|r@t)d|_t-dd|_t-dd|_|dkr)t3dd|_t7d |t9d d!|_t dd d|_t7d"d t9d#d!|_t3d$d|_ t7d |t9d d!|_!t dd d|_"t7d"d t9d#d!|_#t3d$d|_$t7d |t9d d!|_%dSdS)%NrP@r&)r5r0r-` i0ipi ii@i@irQrg?downscale_in_infer)pmodei) weight_attriigffffff?)&r8r9rrr,r:rrW_conv_1_conv_2rF_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)r;rrr<s rr9zGoogLeNet.__init__s &"q"a++ 1Q777  R++  S!,,  c2r3BCC  c3S"b"EE  c3CRDD  c3S"b"EE  c3S"b"EE  c3S"b"EE  c3S"c3GG  c3S"c3GG  c3S"c3GG  ?,Q//DL%!A>>>DM%!A>>>DM ?? 3-ABBBDJ!kvdADL &c322DM taIIIDK#c0DEEEDMkvdAOOODJ&c322DM taIIIDK#c0DEEEDMkvdAOOODJJJ# ?rr=rtuple[Tensor, Tensor, Tensor]c||}||}||}||}||}||}||}||}||}||}||}| |}| |}||}| |}| |}|||}}}|j r?||}||}||}|jdkr,||}t'j|ddg}||}||}t'j|dd}||}t3j|}||}||}||}t'j|dd}||}||}| |}|||fS)Nrr&rPrZr-) start_axis stop_axis)!r:rWrrrrrrrrrrrrrrrrrr\squeezerrflattenrr^r_rrrrrr) r;r=xince4aince4dince5boutout1out2s rr@zGoogLeNet.forwardsU JJv   JJqMM LLOO LLOO JJqMM LLOO LLOO JJqMMa LL  LLOOa LL  JJqMM LLOOa &&4T > ',,s##C==&&D==&&D  a  **S//C.Aq6222C,,s##C==&&D>$1CCCD;;t$$D6$<$1CCCD;;t$$D==&&D::d##DD$r)rkT)rr"rrjr$rl)r=rr$r)rrr__doc__rr9r@rCrDs@rriris6OOO/P/P/P/P/P/P/Pb........rriF pretrainedrjkwargsUnpack[_GoogLeNetOptions]c tdi|}d}|rq|tvs J|dtt|dt|d}tj|}|||S)aCGoogLeNet (Inception v1) model architecture from `"Going Deeper with Convolutions" `_. Args: pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained on ImageNet. Default: False. **kwargs (optional): Additional keyword arguments. For details, please refer to :ref:`GoogLeNet `. Returns: :ref:`api_paddle_nn_Layer`. An instance of GoogLeNet (Inception v1) model. Examples: .. code-block:: python >>> import paddle >>> from paddle.vision.models import googlenet >>> # Build model >>> model = googlenet() >>> # Build model and load imagenet pretrained weight >>> # model = googlenet(pretrained=True) >>> x = paddle.rand([1, 3, 224, 224]) >>> out, out1, out2 = model(x) >>> print(out.shape, out1.shape, out2.shape) paddle.Size([1, 1000]) paddle.Size([1, 1000]) paddle.Size([1, 1000]) rzJ model do not have a pretrained model now, you should set pretrained=Falserr-r)ri model_urlsrr\loadset_dict)rrmodelarch weight_pathparams rrrs@     E D z!!! _ _ _"!!0 t Q D!1!!4   K(( u Lr)r!r"r#r"r$r )F)rrjrrr$ri)& __future__rtypingrrtyping_extensionsrrr\paddle.nn.functionalr functionalr^paddle.base.param_attrr paddle.nnr r r r rrpaddle.nn.initializerrpaddle.utils.downloadrrpaddle._typingrr__all__rr*Layerr,rFrirrrrrsQ#""""" 21111111 ,,,,,,*)))));;;;;;%$$$$$$%%%%%I%%%   4%%%%%%%%P~~~~~~~~D,,,,,,,r