| module Layer_1 #(parameter NN = 30,numWeight=784,dataWidth=16,layerNum=1,sigmoidSize=10,weightIntWidth=4,actType="sigmoid") |
| ( |
| input clk, |
| input rst, |
| input x_valid, |
| input [dataWidth-1:0] x_in, |
| output [NN-1:0] o_valid, |
| output [NN*dataWidth-1:0] x_out |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(0),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_0.mif"),.biasFile("b_1_0.mif"))n_0( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[0*dataWidth+:dataWidth]), |
| .outvalid(o_valid[0]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(1),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_1.mif"),.biasFile("b_1_1.mif"))n_1( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[1*dataWidth+:dataWidth]), |
| .outvalid(o_valid[1]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(2),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_2.mif"),.biasFile("b_1_2.mif"))n_2( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[2*dataWidth+:dataWidth]), |
| .outvalid(o_valid[2]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(3),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_3.mif"),.biasFile("b_1_3.mif"))n_3( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[3*dataWidth+:dataWidth]), |
| .outvalid(o_valid[3]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(4),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_4.mif"),.biasFile("b_1_4.mif"))n_4( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[4*dataWidth+:dataWidth]), |
| .outvalid(o_valid[4]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(5),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_5.mif"),.biasFile("b_1_5.mif"))n_5( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[5*dataWidth+:dataWidth]), |
| .outvalid(o_valid[5]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(6),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_6.mif"),.biasFile("b_1_6.mif"))n_6( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[6*dataWidth+:dataWidth]), |
| .outvalid(o_valid[6]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(7),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_7.mif"),.biasFile("b_1_7.mif"))n_7( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[7*dataWidth+:dataWidth]), |
| .outvalid(o_valid[7]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(8),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_8.mif"),.biasFile("b_1_8.mif"))n_8( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[8*dataWidth+:dataWidth]), |
| .outvalid(o_valid[8]) |
| ); |
| neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(9),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_9.mif"),.biasFile("b_1_9.mif"))n_9( |
| .clk(clk), |
| .rst(rst), |
| .myinput(x_in), |
| .myinputValid(x_valid), |
| .out(x_out[9*dataWidth+:dataWidth]), |
| .outvalid(o_valid[9]) |
| ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(10),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_10.mif"),.biasFile("b_1_10.mif"))n_10( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[10*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[10]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(11),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_11.mif"),.biasFile("b_1_11.mif"))n_11( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[11*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[11]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(12),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_12.mif"),.biasFile("b_1_12.mif"))n_12( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[12*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[12]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(13),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_13.mif"),.biasFile("b_1_13.mif"))n_13( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[13*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[13]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(14),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_14.mif"),.biasFile("b_1_14.mif"))n_14( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[14*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[14]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(15),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_15.mif"),.biasFile("b_1_15.mif"))n_15( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[15*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[15]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(16),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_16.mif"),.biasFile("b_1_16.mif"))n_16( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[16*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[16]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(17),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_17.mif"),.biasFile("b_1_17.mif"))n_17( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[17*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[17]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(18),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_18.mif"),.biasFile("b_1_18.mif"))n_18( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[18*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[18]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(19),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_19.mif"),.biasFile("b_1_19.mif"))n_19( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[19*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[19]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(20),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_20.mif"),.biasFile("b_1_20.mif"))n_20( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[20*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[20]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(21),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_21.mif"),.biasFile("b_1_21.mif"))n_21( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[21*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[21]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(22),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_22.mif"),.biasFile("b_1_22.mif"))n_22( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[22*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[22]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(23),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_23.mif"),.biasFile("b_1_23.mif"))n_23( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[23*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[23]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(24),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_24.mif"),.biasFile("b_1_24.mif"))n_24( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[24*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[24]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(25),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_25.mif"),.biasFile("b_1_25.mif"))n_25( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[25*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[25]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(26),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_26.mif"),.biasFile("b_1_26.mif"))n_26( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[26*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[26]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(27),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_27.mif"),.biasFile("b_1_27.mif"))n_27( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[27*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[27]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(28),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_28.mif"),.biasFile("b_1_28.mif"))n_28( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[28*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[28]) |
| // ); |
| // neuron #(.numWeight(numWeight),.layerNo(layerNum),.neuronNo(29),.dataWidth(dataWidth),.sigmoidSize(sigmoidSize),.weightIntWidth(weightIntWidth),.actType(actType),.weightFile("w_1_29.mif"),.biasFile("b_1_29.mif"))n_29( |
| // .clk(clk), |
| // .rst(rst), |
| // .myinput(x_in), |
| // .myinputValid(x_valid), |
| // .out(x_out[29*dataWidth+:dataWidth]), |
| // .outvalid(o_valid[29]) |
| // ); |
| endmodule |
