英文:
TypeError: Input 'y' of 'Mul' Op has type float32 that does not match type int64 of argument 'x'. in computer vision
问题
I'm working in training my model.
so, I do:
# create the base pre-trained modelbase_model = DenseNet121(weights='/Users/awabe/Desktop/Project/PapilaDB/ClinicalData/DenseNet-BC-121-32-no-top.h5', include_top=False)x = base_model.output# add a global spatial average pooling layerx = GlobalAveragePooling2D()(x)# and a logistic layerpredictions = Dense(len(labels), activation="sigmoid")(x)model = Model(inputs=base_model.input, outputs=predictions)model.compile(optimizer='adam', loss=get_weighted_loss(pos_weights, neg_weights))
then I go to plot section and I use:
history = model.fit_generator(train_generator,validation_data=test_generator,steps_per_epoch=100,validation_steps=25,epochs = 3)plt.plot(history.history['loss'])plt.ylabel("loss")plt.xlabel("epoch")plt.title("Training Loss Curve")plt.show()
then it gives me this error message:
TypeError: in user code:File "/opt/anaconda3/envs/tensorflow/lib/python3.10/site-packages/keras/engine/training.py", line 1160, in train_function *return step_function(self, iterator)File "/var/folders/p4/gy9qtf594h3d5q85bzzgflz00000gn/T/ipykernel_1809/4264699890.py", line 27, in weighted_loss *loss += -(K.mean((pos_weights[i] * y_true[:,i] * K.log(y_pred[:,i] + epsilon) + neg_weights[i]*(1-y_true[:,i]) * K.log(1-y_pred[:,i]+epsilon))))TypeError: Input 'y' of 'Mul' Op has type float32 that does not match type int64 of argument 'x'.
英文:
I'm working in training my model.
so, I do:
# create the base pre-trained modelbase_model = DenseNet121(weights='/Users/awabe/Desktop/Project/PapilaDB/ClinicalData/DenseNet-BC-121-32-no-top.h5', include_top=False)x = base_model.output# add a global spatial average pooling layerx = GlobalAveragePooling2D()(x)# and a logistic layerpredictions = Dense(len(labels), activation="sigmoid")(x)model = Model(inputs=base_model.input, outputs=predictions)model.compile(optimizer='adam', loss=get_weighted_loss(pos_weights, neg_weights))
then I go to plot section and I use:
history = model.fit_generator(train_generator,validation_data=test_generator,steps_per_epoch=100,validation_steps=25,epochs = 3)plt.plot(history.history['loss'])plt.ylabel("loss")plt.xlabel("epoch")plt.title("Training Loss Curve")plt.show()
then it gives me this error message:
TypeError: in user code:
File "/opt/anaconda3/envs/tensorflow/lib/python3.10/site-packages/keras/engine/training.py", line 1160, in train_function *return step_function(self, iterator)File "/var/folders/p4/gy9qtf594h3d5q85bzzgflz00000gn/T/ipykernel_1809/4264699890.py", line 27, in weighted_loss *loss += -(K.mean((pos_weights[i] * y_true[:,i] * K.log(y_pred[:,i] + epsilon) + neg_weights[i]*(1-y_true[:,i]) * K.log(1-y_pred[:,i]+epsilon))))TypeError: Input 'y' of 'Mul' Op has type float32 that does not match type int64 of argument 'x'.
答案1
得分: 0
as delirium mentioned, I used : tf.cast(variable, tf.float32)
英文:
as delirium mentioned, I used : tf.cast(variable, tf.float32)
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