Hello, beginner requiring help here

I’ve just picked up tensorflow and I’m trying to make a simple Siamese neural network.

How would I import csv’s as the left and right input? Any help would be greatly appreciated

def siamese_model(input_shape):

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Model Architecture

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# define the tensor for the two input texts

left_input = Input(input_shape1)

right_input = Input(input_shape2)

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# convolutional neural network

model = Sequential()

model.add(Conv2D(64, (10,10),activation=’relu’,input_shape=input_shape,

kernel_initializer=initialize_weights, kernal_regularizer=12(2e-4)))

model.add(MaxPooling2D())

model.add(Conv2D(128, (7,7),activation=’relu’,

kernel_initializer=initialize_weights,

bias_initializer=initialize_bias, kernel_regularizer=12(2e-4)))

model.add(MaxPooling2D())

model.add(Conv2D(128, (4,4),activation=’relu’,

kernel_initializer=initialize_weights,

bias_initializer=initialize_bias, kernel_regularizer=12(2e-4)))

model.add(MaxPooling2D())

model.add(Conv2D(256, (4,4),activation=’relu’,

kernel_initializer=initialize_weights,

bias_initializer=initialize_bias, kernel_regularizer=12(2e-4)))

model.add(Flatten())

model.add(Dense(4096,activation=’sigmoid’,

kernel_regularizer=12(1e-3),

kernel_initializer=initialize_weights,bias_initializer=bias_initializer))

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# Generate the encodings (feature vectors) for the two images

encoded_l = model(left_input)

encoded_r = model(right_input)

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# Add a custom layer to compute the absolute difference between the encodings

l1_layer = Lambda(lambda tensors:K.abs(tensors[0] – tensors[1]))

l1_distance = l1_layer([encoded_l, encoded_r])

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# Add a denselayer with a sigmoid unit to generate the similarity score

prediction = Dense(1,activation=’sigmoid’,bias_initializer=initialize_bias)(l1_distance)

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#connect the inputs with the outputs

siamese_net = Model(inputs=[left_input, right_input],outputs=prediction)

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# return model

return siamese_netamese_net