any way to do causal pad in Flux ?

[neoareslinux]

Motivation and description

does Cov support causal pad ? I want build causal dilated convolutional network model, but i cannot find any document to guid me to do this with Flux.

Possible Implementation

No response

[CarloLucibello]

Do you have some pytorch reference code?
I don't see it as an option in pytorch's Conv1d

Maybe just first process the input using NNlib.pad_constant?

[neoareslinux]

Do you have some pytorch reference code? I don't see it as an option in pytorch's Conv1d

Maybe just first process the input using NNlib.pad_constant?

keras code, I have not used pytorch, i learn DL in keras framework and now want to migrate to julia&Flux.

def get_model(input_length, num_features):
    model = keras.Sequential()

    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=1, padding='causal', activation='relu', 
                 input_shape=(input_length, num_features)))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=2, padding='causal', activation='relu'))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=4, padding='causal', activation='relu'))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=8, padding='causal', activation='relu'))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=1, padding='causal', activation='relu'))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=2, padding='causal', activation='relu'))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=4, padding='causal', activation='relu'))
    model.add(layers.Conv1D(filters=20, kernel_size=2, dilation_rate=8, padding='causal', activation='relu'))

    # Flatten the output
    model.add(layers.Flatten())

    # Add a dense layer for binary classification
    model.add(layers.Dense(1, activation='sigmoid'))

    # Compile the model
    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
    return model

[CarloLucibello]

I don't know what Keras does.
Looking at this
https://gist.github.com/paultsw/7a9d6e3ce7b70e9e2c61bc9287addefc
it seems like you just have to handle the padding appropriately.

[neoareslinux]

I don't know what Keras does. Looking at this https://gist.github.com/paultsw/7a9d6e3ce7b70e9e2c61bc9287addefc it seems like you just have to handle the padding appropriately.

thanks, maybe related to #258