Model: "hotWater" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== atom_vectors (InputLayer) [(None, 50, 3)] 0 __________________________________________________________________________________________________ beta (InputLayer) [(None, 50, 30)] 0 __________________________________________________________________________________________________ 1d_conv1 (Conv1D) (None, 50, 30) 120 atom_vectors[0][0] __________________________________________________________________________________________________ 1d_conv2 (Conv1D) (None, 50, 30) 930 beta[0][0] __________________________________________________________________________________________________ merge12a (Concatenate) (None, 50, 60) 0 1d_conv1[0][0] 1d_conv2[0][0] __________________________________________________________________________________________________ 1d_conv_reduce (Conv1D) (None, 50, 30) 7230 merge12a[0][0] __________________________________________________________________________________________________ BatchNormalization_residual_0_0 (None, 50, 30) 120 1d_conv_reduce[0][0] __________________________________________________________________________________________________ relu_residual_0_0_1 (Activation (None, 50, 30) 0 BatchNormalization_residual_0_0_1 __________________________________________________________________________________________________ conv1d_residual_0_0_1 (Conv1D) (None, 50, 30) 3630 relu_residual_0_0_1[0][0] __________________________________________________________________________________________________ BatchNormalization_residual_0_0 (None, 50, 30) 120 conv1d_residual_0_0_1[0][0] __________________________________________________________________________________________________ relu_residual_0_0_2 (Activation (None, 50, 30) 0 BatchNormalization_residual_0_0_2 __________________________________________________________________________________________________ conv1d_residual_0_0_2 (Conv1D) (None, 50, 30) 3630 relu_residual_0_0_2[0][0] __________________________________________________________________________________________________ add (Add) (None, 50, 30) 0 conv1d_residual_0_0_2[0][0] 1d_conv_reduce[0][0] __________________________________________________________________________________________________ BatchNormalization_residual_1_0 (None, 50, 30) 120 add[0][0] __________________________________________________________________________________________________ relu_residual_1_0_1 (Activation (None, 50, 30) 0 BatchNormalization_residual_1_0_1 __________________________________________________________________________________________________ conv1d_residual_1_0_1 (Conv1D) (None, 50, 30) 3630 relu_residual_1_0_1[0][0] __________________________________________________________________________________________________ BatchNormalization_residual_1_0 (None, 50, 30) 120 conv1d_residual_1_0_1[0][0] __________________________________________________________________________________________________ relu_residual_1_0_2 (Activation (None, 50, 30) 0 BatchNormalization_residual_1_0_2 __________________________________________________________________________________________________ merge12b (Concatenate) (None, 50, 60) 0 1d_conv1[0][0] 1d_conv2[0][0] __________________________________________________________________________________________________ conv1d_residual_1_0_2 (Conv1D) (None, 50, 30) 3630 relu_residual_1_0_2[0][0] __________________________________________________________________________________________________ 1d_skip_reduce (Conv1D) (None, 50, 30) 7230 merge12b[0][0] __________________________________________________________________________________________________ convforskip0 (Conv1D) (None, 50, 30) 930 add[0][0] __________________________________________________________________________________________________ add_1 (Add) (None, 50, 30) 0 conv1d_residual_1_0_2[0][0] add[0][0] __________________________________________________________________________________________________ skip0 (Add) (None, 50, 30) 0 1d_skip_reduce[0][0] convforskip0[0][0] __________________________________________________________________________________________________ convforskip1 (Conv1D) (None, 50, 30) 930 add_1[0][0] __________________________________________________________________________________________________ skip1 (Add) (None, 50, 30) 0 skip0[0][0] convforskip1[0][0] __________________________________________________________________________________________________ BatchNormalization_residual_fin (None, 50, 30) 120 skip1[0][0] __________________________________________________________________________________________________ relu_residual_final_1 (Activati (None, 50, 30) 0 BatchNormalization_residual_final __________________________________________________________________________________________________ conv1d_residual_final_1 (Conv1D (None, 50, 30) 930 relu_residual_final_1[0][0] __________________________________________________________________________________________________ BatchNormalization_residual_fin (None, 50, 30) 120 conv1d_residual_final_1[0][0] __________________________________________________________________________________________________ relu_residual_final_2 (Activati (None, 50, 30) 0 BatchNormalization_residual_final __________________________________________________________________________________________________ conv1d_residual_final_2 (Conv1D (None, 50, 30) 930 relu_residual_final_2[0][0] __________________________________________________________________________________________________ add_2 (Add) (None, 50, 30) 0 conv1d_residual_final_2[0][0] skip1[0][0] __________________________________________________________________________________________________ conv_final (Conv1D) (None, 50, 1) 31 add_2[0][0] __________________________________________________________________________________________________ output (GlobalMaxPooling1D) (None, 1) 0 conv_final[0][0] ================================================================================================== Total params: 34,501 Trainable params: 34,141 Non-trainable params: 360