I asked a question on StackOverflow regarding as the return value of a custom loss funtion. But I didn't get a clear answer. In this guide on tensorflow website, I found an example of custom loss funciton: def custom_mean_squared_error(y...
Hello, I am trying to create a custom loss function in Keras, where the target values for my network and the output of my network are of different shapes. Here is the custom loss function I have defined: def custom_loss(y_true, y_pred): ...
return tf.where(is_small_error, small_error_loss, big_error_loss) # return the inner function tuned by the hyperparameter return my_huber_loss model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])]) model.compile(optimizer='sgd', loss=my_huber_loss_with_threshold(t...
Keras的文档中提供了可用loss和metrics的列表。 2. 自定义loss函数 当我们需要使用实现更复杂的loss函数或者metric时,就需要构造自定义函数并且传给model.compile。 例如,构建自定义metric(来自Keras文档): import keras.backend as Kdef mean_pred(y_true, y_pred):return K.mean(y_pred)model.compile(optimizer=...
方法： 1 lr_save_string 该函数主要是将程序中的常量或变量保存为lr中的参数 2 lr_eval_string 从...
loss_tf = tf.keras.losses.MeanSquaredError() def custom_loss(y_true, y_pred): error = y_true-y_pred sqr_error = K.square(error) mean_sqr_error = K.mean(sqr_error) sqrt_mean_sqr_error = K.sqrt(mean_sqr_error) return sqrt_mean_sqr_error def pseudo_custom_loss(y_true, y_pred...
Keras’ Low-Level API The Keras API actually has its own low-level API, located in keras.backend. It includes functions like square(), exp(), sqrt() and so on. In tf.keras, these functions generally just call the corresponding TensorFlow operations. If you want to write code that will...
The output layer uses sigmoid activation function for binary classification. This neural network is trained with our proposed custom loss function of two classes detailed Fig. 2. Figure 2 Dense connections in DenseNet (this figure was created with Draw.io). Full size image Selecting CNN ...
venv/lib/python3.6/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 166, in class_and_config_for_serialized_keras_object raise ValueError('Unknown ' + printable_module_name + ': ' + class_name) ValueError: Unknown loss function: MyCustomLoss Process finished with exit code...
I've created a custom loss function by subclassing from tf.keras.losses.Loss and a model using the functional API and specified its outputs to be that of two layers, I need one of them to passed to the loss function and another is the actual output that should print out to the user....