ValueError: The first argument to Layer.call must always be passed.

[SuryaVikram]

Hello, thank you for sharing this.

I am getting this error when am trying to run this in Colab
"ValueError: The first argument to Layer.call must always be passed."

This is my model code:
from attention import AttentionLayer

from keras import backend as K
K.clear_session()
latent_dim = 100
embedding_dim=100

Encoder

encoder_inputs = Input(shape=(max_len_text,))
enc_emb = Embedding(x_voc_size, latent_dim,trainable=True)(encoder_inputs)

#LSTM 1
encoder_lstm1 = LSTM(latent_dim,return_sequences=True,return_state=True)
encoder_output1, state_h1, state_c1 = encoder_lstm1(enc_emb)

#LSTM 2
encoder_lstm2 = LSTM(latent_dim,return_sequences=True,return_state=True)
encoder_output2, state_h2, state_c2 = encoder_lstm2(encoder_output1)

#LSTM 3
encoder_lstm3=LSTM(latent_dim, return_state=True, return_sequences=True)
encoder_outputs, state_h, state_c= encoder_lstm3(encoder_output2)

Set up the decoder.

decoder_inputs = Input(shape=(None,))
dec_emb_layer = Embedding(y_voc_size, latent_dim,trainable=True)
dec_emb = dec_emb_layer(decoder_inputs)

#LSTM using encoder_states as initial state
decoder_lstm = LSTM(latent_dim, return_sequences=True, return_state=True)
decoder_outputs,decoder_fwd_state, decoder_back_state = decoder_lstm(dec_emb,initial_state=[state_h, state_c])

#Attention Layer
attn_layer = AttentionLayer(name='attention_layer')
attn_out, attn_states = attn_layer()([encoder_outputs, decoder_outputs])

Concat attention output and decoder LSTM output

decoder_concat_input = Concatenate(axis=-1, name='concat_layer')([decoder_outputs, attn_out])

#Dense layer
decoder_dense = TimeDistributed(Dense(y_voc_size, activation='softmax'))
decoder_outputs = decoder_dense(decoder_outputs)

Define the model

model = Model([encoder_inputs, decoder_inputs], decoder_outputs)
model.summary()

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Please advice if I am missing something, thank you

[Diamondcast]

attn_layer() - Should you have () here?