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Commit 957da953 authored by Joaquin Rives Gambin's avatar Joaquin Rives Gambin
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model 5

parent e2104a14
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...@@ -157,9 +157,6 @@ x = LSTM(units=200)(x) ...@@ -157,9 +157,6 @@ x = LSTM(units=200)(x)
x = BatchNormalization()(x) x = BatchNormalization()(x)
output_lvl_1 = LeakyReLU(alpha=0.3)(x) output_lvl_1 = LeakyReLU(alpha=0.3)(x)
# x = LeakyReLU(alpha=0.3)(x)
# output_lvl_1 = Dense(20, activation='sigmoid')(x)
model_lvl_1 = Model(inputs=input_lvl_1, outputs=output_lvl_1) model_lvl_1 = Model(inputs=input_lvl_1, outputs=output_lvl_1)
...@@ -183,16 +180,17 @@ main_output = Dense(9, activation='sigmoid')(x) ...@@ -183,16 +180,17 @@ main_output = Dense(9, activation='sigmoid')(x)
main_model = Model(inputs=main_input, outputs=main_output) main_model = Model(inputs=main_input, outputs=main_output)
main_model.summary() main_model.summary()
try: # try:
model = multi_gpu_model(main_model, gpus=4, cpu_relocation=False) # model = multi_gpu_model(main_model, gpus=4, cpu_relocation=False)
print("Training on 4 GPUs") # print("Training on 4 GPUs")
except: # except:
print("Training on 1 GPU (or CPU)") # print("Training on 1 GPU (or CPU)")
main_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['categorical_accuracy']) main_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['categorical_accuracy'])
main_model.summary() main_model.summary()
##########################################################
main_model.fit(arr_seg_train, arr_labels_train, epochs=20, batch_size=24, main_model.fit(arr_seg_train, arr_labels_train, epochs=20, batch_size=24,
verbose=1, validation_data=(arr_seg_test, arr_labels_test), shuffle=True) verbose=1, validation_data=(arr_seg_test, arr_labels_test), shuffle=True)
......
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