i just build a new deep learning network layer and i got this error

Question

Madhu Cherukula el 11 de Mayo de 2021

0
Enlazar

Enlace directo a esta pregunta

https://es.mathworks.com/matlabcentral/answers/827635-i-just-build-a-new-deep-learning-network-layer-and-i-got-this-error

Respondida: Katja Mogalle el 12 de Mayo de 2021

Create Deep Learning Network Architecture

Script for creating the layers for a deep learning network with the following properties:

Number of layers: 177

Number of connections: 192

Run the script to create the layers in the workspace variable lgraph.

To learn more, see Generate MATLAB Code From Deep Network Designer.

Auto-generated by MATLAB on 11-May-2021 23:22:35

Create Layer Graph

Create the layer graph variable to contain the network layers.

lgraph = layerGraph();

Add Layer Branches

Add the branches of the network to the layer graph. Each branch is a linear array of layers.

tempLayers = [

imageInputLayer([224 224 3],"Name","input_1")

convolution2dLayer([7 7],64,"Name","conv1","Padding",[3 3 3 3],"Stride",[2 2])

batchNormalizationLayer("Name","bn_conv1","Epsilon",0.001)

reluLayer("Name","activation_1_relu")

maxPooling2dLayer([3 3],"Name","max_pooling2d_1","Padding",[1 1 1 1],"Stride",[2 2])];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],64,"Name","res2a_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2a_branch2a","Epsilon",0.001)

reluLayer("Name","activation_2_relu")

convolution2dLayer([3 3],64,"Name","res2a_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn2a_branch2b","Epsilon",0.001)

reluLayer("Name","activation_3_relu")

convolution2dLayer([1 1],256,"Name","res2a_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2a_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res2a_branch1","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2a_branch1","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_1")

reluLayer("Name","activation_4_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],64,"Name","res2b_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2b_branch2a","Epsilon",0.001)

reluLayer("Name","activation_5_relu")

convolution2dLayer([3 3],64,"Name","res2b_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn2b_branch2b","Epsilon",0.001)

reluLayer("Name","activation_6_relu")

convolution2dLayer([1 1],256,"Name","res2b_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2b_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_2")

reluLayer("Name","activation_7_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],64,"Name","res2c_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2c_branch2a","Epsilon",0.001)

reluLayer("Name","activation_8_relu")

convolution2dLayer([3 3],64,"Name","res2c_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn2c_branch2b","Epsilon",0.001)

reluLayer("Name","activation_9_relu")

convolution2dLayer([1 1],256,"Name","res2c_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn2c_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_3")

reluLayer("Name","activation_10_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],128,"Name","res3a_branch2a","BiasLearnRateFactor",0,"Stride",[2 2])

batchNormalizationLayer("Name","bn3a_branch2a","Epsilon",0.001)

reluLayer("Name","activation_11_relu")

convolution2dLayer([3 3],128,"Name","res3a_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn3a_branch2b","Epsilon",0.001)

reluLayer("Name","activation_12_relu")

convolution2dLayer([1 1],512,"Name","res3a_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3a_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],512,"Name","res3a_branch1","BiasLearnRateFactor",0,"Stride",[2 2])

batchNormalizationLayer("Name","bn3a_branch1","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_4")

reluLayer("Name","activation_13_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],128,"Name","res3b_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3b_branch2a","Epsilon",0.001)

reluLayer("Name","activation_14_relu")

convolution2dLayer([3 3],128,"Name","res3b_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn3b_branch2b","Epsilon",0.001)

reluLayer("Name","activation_15_relu")

convolution2dLayer([1 1],512,"Name","res3b_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3b_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_5")

reluLayer("Name","activation_16_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],128,"Name","res3c_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3c_branch2a","Epsilon",0.001)

reluLayer("Name","activation_17_relu")

convolution2dLayer([3 3],128,"Name","res3c_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn3c_branch2b","Epsilon",0.001)

reluLayer("Name","activation_18_relu")

convolution2dLayer([1 1],512,"Name","res3c_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3c_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_6")

reluLayer("Name","activation_19_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],128,"Name","res3d_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3d_branch2a","Epsilon",0.001)

reluLayer("Name","activation_20_relu")

convolution2dLayer([3 3],128,"Name","res3d_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn3d_branch2b","Epsilon",0.001)

reluLayer("Name","activation_21_relu")

convolution2dLayer([1 1],512,"Name","res3d_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn3d_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_7")

reluLayer("Name","activation_22_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res4a_branch2a","BiasLearnRateFactor",0,"Stride",[2 2])

batchNormalizationLayer("Name","bn4a_branch2a","Epsilon",0.001)

reluLayer("Name","activation_23_relu")

convolution2dLayer([3 3],256,"Name","res4a_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn4a_branch2b","Epsilon",0.001)

reluLayer("Name","activation_24_relu")

convolution2dLayer([1 1],1024,"Name","res4a_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4a_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],1024,"Name","res4a_branch1","BiasLearnRateFactor",0,"Stride",[2 2])

batchNormalizationLayer("Name","bn4a_branch1","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_8")

reluLayer("Name","activation_25_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res4b_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4b_branch2a","Epsilon",0.001)

reluLayer("Name","activation_26_relu")

convolution2dLayer([3 3],256,"Name","res4b_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn4b_branch2b","Epsilon",0.001)

reluLayer("Name","activation_27_relu")

convolution2dLayer([1 1],1024,"Name","res4b_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4b_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_9")

reluLayer("Name","activation_28_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res4c_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4c_branch2a","Epsilon",0.001)

reluLayer("Name","activation_29_relu")

convolution2dLayer([3 3],256,"Name","res4c_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn4c_branch2b","Epsilon",0.001)

reluLayer("Name","activation_30_relu")

convolution2dLayer([1 1],1024,"Name","res4c_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4c_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_10")

reluLayer("Name","activation_31_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res4d_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4d_branch2a","Epsilon",0.001)

reluLayer("Name","activation_32_relu")

convolution2dLayer([3 3],256,"Name","res4d_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn4d_branch2b","Epsilon",0.001)

reluLayer("Name","activation_33_relu")

convolution2dLayer([1 1],1024,"Name","res4d_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4d_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_11")

reluLayer("Name","activation_34_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res4e_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4e_branch2a","Epsilon",0.001)

reluLayer("Name","activation_35_relu")

convolution2dLayer([3 3],256,"Name","res4e_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn4e_branch2b","Epsilon",0.001)

reluLayer("Name","activation_36_relu")

convolution2dLayer([1 1],1024,"Name","res4e_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4e_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_12")

reluLayer("Name","activation_37_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],256,"Name","res4f_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4f_branch2a","Epsilon",0.001)

reluLayer("Name","activation_38_relu")

convolution2dLayer([3 3],256,"Name","res4f_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn4f_branch2b","Epsilon",0.001)

reluLayer("Name","activation_39_relu")

convolution2dLayer([1 1],1024,"Name","res4f_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn4f_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_13")

reluLayer("Name","activation_40_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],2048,"Name","res5a_branch1","BiasLearnRateFactor",0,"Stride",[2 2])

batchNormalizationLayer("Name","bn5a_branch1","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],512,"Name","res5a_branch2a","BiasLearnRateFactor",0,"Stride",[2 2])

batchNormalizationLayer("Name","bn5a_branch2a","Epsilon",0.001)

reluLayer("Name","activation_41_relu")

convolution2dLayer([3 3],512,"Name","res5a_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn5a_branch2b","Epsilon",0.001)

reluLayer("Name","activation_42_relu")

convolution2dLayer([1 1],2048,"Name","res5a_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn5a_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_14")

reluLayer("Name","activation_43_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],512,"Name","res5b_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn5b_branch2a","Epsilon",0.001)

reluLayer("Name","activation_44_relu")

convolution2dLayer([3 3],512,"Name","res5b_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn5b_branch2b","Epsilon",0.001)

reluLayer("Name","activation_45_relu")

convolution2dLayer([1 1],2048,"Name","res5b_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn5b_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_15")

reluLayer("Name","activation_46_relu")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

convolution2dLayer([1 1],512,"Name","res5c_branch2a","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn5c_branch2a","Epsilon",0.001)

reluLayer("Name","activation_47_relu")

convolution2dLayer([3 3],512,"Name","res5c_branch2b","BiasLearnRateFactor",0,"Padding","same")

batchNormalizationLayer("Name","bn5c_branch2b","Epsilon",0.001)

reluLayer("Name","activation_48_relu")

convolution2dLayer([1 1],2048,"Name","res5c_branch2c","BiasLearnRateFactor",0)

batchNormalizationLayer("Name","bn5c_branch2c","Epsilon",0.001)];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

additionLayer(2,"Name","add_16")

leakyReluLayer(0.01,"Name","leakyrelu")

globalAveragePooling2dLayer("Name","gapool")

fullyConnectedLayer(10,"Name","fc")

softmaxLayer("Name","softmax")

classificationLayer("Name","classoutput")];

lgraph = addLayers(lgraph,tempLayers);

% clean up helper variable

clear tempLayers;

Connect Layer Branches

Connect all the branches of the network to create the network graph.

lgraph = connectLayers(lgraph,"max_pooling2d_1","res2a_branch2a");

lgraph = connectLayers(lgraph,"max_pooling2d_1","res2a_branch1");

lgraph = connectLayers(lgraph,"bn2a_branch2c","add_1/in1");

lgraph = connectLayers(lgraph,"bn2a_branch1","add_1/in2");

lgraph = connectLayers(lgraph,"activation_4_relu","res2b_branch2a");

lgraph = connectLayers(lgraph,"activation_4_relu","add_2/in2");

lgraph = connectLayers(lgraph,"bn2b_branch2c","add_2/in1");

lgraph = connectLayers(lgraph,"activation_7_relu","res2c_branch2a");

lgraph = connectLayers(lgraph,"activation_7_relu","add_3/in2");

lgraph = connectLayers(lgraph,"bn2c_branch2c","add_3/in1");

lgraph = connectLayers(lgraph,"activation_10_relu","res3a_branch2a");

lgraph = connectLayers(lgraph,"activation_10_relu","res3a_branch1");

lgraph = connectLayers(lgraph,"bn3a_branch1","add_4/in2");

lgraph = connectLayers(lgraph,"bn3a_branch2c","add_4/in1");

lgraph = connectLayers(lgraph,"activation_13_relu","res3b_branch2a");

lgraph = connectLayers(lgraph,"activation_13_relu","add_5/in2");

lgraph = connectLayers(lgraph,"bn3b_branch2c","add_5/in1");

lgraph = connectLayers(lgraph,"activation_16_relu","res3c_branch2a");

lgraph = connectLayers(lgraph,"activation_16_relu","add_6/in2");

lgraph = connectLayers(lgraph,"bn3c_branch2c","add_6/in1");

lgraph = connectLayers(lgraph,"activation_19_relu","res3d_branch2a");

lgraph = connectLayers(lgraph,"activation_19_relu","add_7/in2");

lgraph = connectLayers(lgraph,"bn3d_branch2c","add_7/in1");

lgraph = connectLayers(lgraph,"activation_22_relu","res4a_branch2a");

lgraph = connectLayers(lgraph,"activation_22_relu","res4a_branch1");

lgraph = connectLayers(lgraph,"bn4a_branch2c","add_8/in1");

lgraph = connectLayers(lgraph,"bn4a_branch1","add_8/in2");

lgraph = connectLayers(lgraph,"activation_25_relu","res4b_branch2a");

lgraph = connectLayers(lgraph,"activation_25_relu","add_9/in2");

lgraph = connectLayers(lgraph,"bn4b_branch2c","add_9/in1");

lgraph = connectLayers(lgraph,"activation_28_relu","res4c_branch2a");

lgraph = connectLayers(lgraph,"activation_28_relu","add_10/in2");

lgraph = connectLayers(lgraph,"bn4c_branch2c","add_10/in1");

lgraph = connectLayers(lgraph,"activation_31_relu","res4d_branch2a");

lgraph = connectLayers(lgraph,"activation_31_relu","add_11/in2");

lgraph = connectLayers(lgraph,"bn4d_branch2c","add_11/in1");

lgraph = connectLayers(lgraph,"activation_34_relu","res4e_branch2a");

lgraph = connectLayers(lgraph,"activation_34_relu","add_12/in2");

lgraph = connectLayers(lgraph,"bn4e_branch2c","add_12/in1");

lgraph = connectLayers(lgraph,"activation_37_relu","res4f_branch2a");

lgraph = connectLayers(lgraph,"activation_37_relu","add_13/in2");

lgraph = connectLayers(lgraph,"bn4f_branch2c","add_13/in1");

lgraph = connectLayers(lgraph,"activation_40_relu","res5a_branch1");

lgraph = connectLayers(lgraph,"activation_40_relu","res5a_branch2a");

lgraph = connectLayers(lgraph,"bn5a_branch1","add_14/in2");

lgraph = connectLayers(lgraph,"bn5a_branch2c","add_14/in1");

lgraph = connectLayers(lgraph,"activation_43_relu","res5b_branch2a");

lgraph = connectLayers(lgraph,"activation_43_relu","add_15/in2");

lgraph = connectLayers(lgraph,"bn5b_branch2c","add_15/in1");

lgraph = connectLayers(lgraph,"activation_46_relu","res5c_branch2a");

lgraph = connectLayers(lgraph,"activation_46_relu","add_16/in2");

lgraph = connectLayers(lgraph,"bn5c_branch2c","add_16/in1");

Plot Layers

plot(lgraph);

imds = imageDatastore('C:\Users\HP\Desktop\code\dataset',"IncludeSubfolders",true, 'LabelSource','folderNames')

options1 = trainingOptions('sgdm', ...

'LearnRateSchedule','piecewise', ...

'LearnRateDropFactor',0.2, ...

'LearnRateDropPeriod',5, ...

'MaxEpochs',20, ...

'MiniBatchSize',64, ...

'Plots','training-progress')

net = trainNetwork(imds,tempLayers,options)

%[net, traininfo] = trainNetwork(imds,tempLayers,options)

%covennet1 = trainNetwork(imds,lgraph,options)

imp = input('Enter Input')

I = imread(imp)

figure;

imshow(I)

class = classify(net,I)

msgbox(char(class))

inp = '00001.jpg'

I1 = imread(inp)

figure,

imshow(I1)

error is :

Unrecognized function or variable 'tempLayers'.

0 comentarios
Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

Iniciar sesión para comentar.

Iniciar sesión para responder a esta pregunta.

Answer 1

Katja Mogalle el 12 de Mayo de 2021

0
Enlazar

Enlace directo a esta respuesta

https://es.mathworks.com/matlabcentral/answers/827635-i-just-build-a-new-deep-learning-network-layer-and-i-got-this-error#answer_698330

Hello Madhu,

It looks like you used the Deep Network Designer app to build the network and now you are trying to train it.

The final network architecture that is being built in this script is encapsulated in the variable "lgraph". So the variable lgraph needs to be used when calling trainNetwork.

I see the line "covennet1 = trainNetwork(imds,lgraph,options)" in your script. Did you try to execute this? I think it should work.

Note that from MATLAB R2020a onwards you can also train the network directly from the Deep Network Designer app. See this documentation example for more information: https://uk.mathworks.com/help/releases/R2020a/deeplearning/gs/get-started-with-deep-network-designer.html

I hope this helps.

Katja

0 comentarios
Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

Iniciar sesión para comentar.

i just build a new deep learning network layer and i got this error

0 comentarios
Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

Respuestas (1)

0 comentarios
Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

Ver también

Categorías

Etiquetas

Community Treasure Hunt

i just build a new deep learning network layer and i got this error

0 comentarios Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

Respuestas (1)

0 comentarios Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

Ver también

Categorías

Etiquetas

Community Treasure Hunt

0 comentarios
Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos

0 comentarios
Mostrar -2 comentarios más antiguosOcultar -2 comentarios más antiguos