model_mono: fix bottleneck

This commit is contained in:
Starbeamrainbowlabs 2022-11-11 19:11:40 +00:00
parent 73acda6d9a
commit 0662d0854b
Signed by: sbrl
GPG key ID: 1BE5172E637709C2

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@ -38,10 +38,10 @@ def model_rainfallwater_mono(metadata, shape_water_out, model_arch_enc="convnext
arch_name = model_arch_enc
)(layer_input)
print("DEBUG:model ENCODER output_shape", layer_next.output_shape)
print("DEBUG:model ENCODER output_shape", layer_next.shape)
# BOTTLENECK
layer_next = tf.keras.layers.Dense(name="cns.stage.bottleneck.dense2", units=feature_dim)(layer_input)
layer_next = tf.keras.layers.Dense(name="cns.stage.bottleneck.dense2", units=feature_dim)(layer_next)
layer_next = tf.keras.layers.Activation(name="cns.stage.bottleneck.gelu2", activation="gelu")(layer_next)
layer_next = tf.keras.layers.LayerNormalization(name="cns.stage.bottleneck.norm2", epsilon=1e-6)(layer_next)
layer_next = tf.keras.layers.Dropout(name="cns.stage.bottleneck.dropout", rate=0.1)(layer_next)
@ -50,7 +50,7 @@ def model_rainfallwater_mono(metadata, shape_water_out, model_arch_enc="convnext
layer_next = LayerStack2Image(target_width=4, target_height=4)(layer_next)
# layer_next = tf.keras.layers.Reshape((4, 4, math.floor(feature_dim_in/(4*4))), name="cns.stable_begin.reshape")(layer_next)
print("DEBUG:model BOTTLENECK:stack2image output_shape", layer_next.output_shape)
print("DEBUG:model BOTTLENECK:stack2image output_shape", layer_next.shape)
layer_next = tf.keras.layers.Dense(name="cns.stage.begin.dense2", units=feature_dim)(layer_next)
layer_next = tf.keras.layers.Activation(name="cns.stage_begin.relu2", activation="gelu")(layer_next)