Error when checking target: expected dense_1 to have 3 dimensions, but got array with shape (118, 1)

Your second LSTM layer also returns sequences and Dense layers by default apply the kernel to every timestep also producing a sequence:

# (bs, 45, 2)
model.add( LSTM( 512, input_shape=(45, 2), return_sequences=True))
# (bs, 45, 512)
model.add( LSTM( 512, return_sequences=True))
# (bs, 45, 512)
model.add( (Dense(1)))
# (bs, 45, 1)

So your output is shape (bs, 45, 1). To solve the problem you need to set return_sequences=False in your second LSTM layer which will compress sequence:

# (bs, 45, 2)
model.add( LSTM( 512, input_shape=(45, 2), return_sequences=True))
# (bs, 45, 512)
model.add( LSTM( 512, return_sequences=False)) # SET HERE
# (bs, 512)
model.add( (Dense(1)))
# (bs, 1)

And you'll get the desired output. Note bs is the batch size.

I had a similar problem, found the answer here:

I added model.add(Flatten()) before the last Dense layer