CODEWITHSUNDEEP
neural-networkkeras
Jonathan
Jonathan

Reputation: 1936

unable to add layer in keras

I am trying to following this suggestion. 

outputs = Conv2DTranspose(3, (1, 1), activation='sigmoid') (c9)
model = Model(inputs=[inputs], outputs=[outputs])
model = multi_gpu_model(model, gpus=8)
model.compile(optimizer='adam', loss = bce, metrics = [mean_iou])
model.add(Lambda(lambda x: K.batch_flatten(x)))

But at that last line of code, I receive the following error:

'Model' object has no attribute 'add'

I understand that since I didn't instantiate model as sequential() as in linked post, the function add() might not be available to me. However, I'm not sure how to work around this.

Upvotes: 0

Views: 92

Answers (2)

Jonathan
Jonathan

Reputation: 1936

Going off @Today's answer in the OP's comments,

outputs = Lambda(lambda x: K.batch_flatten(x))(outputs)

Upvotes: 0

swiftg
swiftg

Reputation: 346

Corrected to reflect the working solution:

outputs = Conv2DTranspose(3, (1, 1), activation='sigmoid') (c9)
outputs = Lambda(lambda x: K.batch_flatten(x))(outputs)
model = Model(inputs=[inputs], outputs=[outputs])
model = multi_gpu_model(model, gpus=8)
model.compile(optimizer='adam', loss = bce, metrics = [mean_iou])

Upvotes: 1

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