a ==ic@s4ddlmZddlmZddlZGdddeZdS))schema) ModelLayerNc s*eZdZdZd fdd ZddZZS) Conva Convolutional layer Input: - input_record: at least has the shape info of C (num_channels) - output_dim: number of convolutional filters - kernel_h, kernel_w: kernel size for h and w - stride_h, stride_w: stride for h and w - pad_b, pad_l, pad_r, pad_t: padding sizes, if stride == 1, 'None' value will do auto padding - order: either 'NHWC' or 'NCHW' NNHWCconvc stt|j|||fi|t|tjs0Jd|j}|dkrLt|tsTJd|dkrft|tsnJd||_ ||_ |dkrt|tsJd|dkrt|tsJd||_ ||_ |dkr| durt|ddn| } |durt|ddn|}n$| dur dn| } |durdn|}|dkrh| durDt|ddn| } | durbt|ddn| } n$| durvdn| } | durdn| } | dkrt| tsJd |dkrt|tsJd | dkrt| tsJd | dkrt| tsJd | |_ ||_| |_| |_| d vs.Jd| |_| dkrT|d}||||g}n| dkrr|d}||||g}|dksJd| r| ndif} |r|n dddif}|jd|| |d|_|jd|g||d|_ttj|ff|d|_dS)NzIncorrect input typerz#kernel_h should be positive integerz#kernel_w should be positive integerz#stride_h should be positive integerz#stride_w should be positive integerzpad_t should be int >= 0zpad_b should be int >= 0zpad_r should be int >= 0zpad_l should be int >= 0)rNCHWz$order should either 'NHWC' or 'NCHW'rr z>Number of input channels in conv parameters should be positiveZ XavierFillZ ConstantFillvaluegZ conv_kernel) param_nameshapeZ initializerZ optimizerZ conv_biasoutput)superr__init__ isinstancerZScalarZ field_typer intkernel_hkernel_wstride_hstride_wpad_tpad_bpad_rpad_lorderZ create_paramkernelbiasnpfloat32Zget_next_blob_reference output_schema)selfmodel input_recordZ output_dimrrrrrrrrrZ kernel_initZ bias_initZ kernel_optimZ bias_optimnamekwargsZ input_dimsZinput_cZ kernel_shape __class__j/home/droni/.local/share/virtualenvs/DPS-5Je3_V2c/lib/python3.9/site-packages/caffe2/python/layers/conv.pyrs           z Conv.__init__c CsN|j|j|j|jg|j|j|j|j|j |j |j |j |j |jd dS)N) rrrrrrrrr)rr#Z field_blobsrrr rrrrrrrrr)r!netr(r(r)add_opszsz Conv.add_ops) NNNNrNNNNr)__name__ __module__ __qualname____doc__rr+ __classcell__r(r(r&r)rs ^r)Z caffe2.pythonrZcaffe2.python.layers.layersrnumpyrrr(r(r(r)s