Custom metric access X input data

I'd like to write a custom metric for a spelling correction model that counts correctly substituted letters that were previously incorrect. And it should be counted incorrectly substituted letters that were previously correct.

That's why I need access to the x_input data. Unfortunately, only y_true and y_pred are accessible by default. Is there a workaround to get to the matching x_input?

Is:

def custom_metric(y_true, y_pred):

Wanted:

def custom_metric(x_input, y_true, y_pred):

Solution

def custom_loss(x_input):
    def loss_fn(y_true, y_pred):
        # Use your x_input here directly
        return #Your loss value
    return loss_fn

model = # Define your model
model.compile(loss=custom_loss(x_input))   
# Values of y_true and y_pred will be passed implicitly by Keras

Remember that x_input will be having same values across all batches of input while model is getting trained.

EDIT:

Since you need x_input data only of every batch for estimating during the loss function and you are having your own custom loss function, why don't you pass the x_input as labels. Something like this:

model.fit(x=x_input, y=x_input)
model.compile(loss=custom_loss())

def custom_loss(y_true, y_pred):
  # y_true corresponds to x_input data

If you need x_input and you need to pass some other data, you can do like this:

model.fit(x=x_input, y=[x_input, other_data])
model.compile(loss=custom_loss())

You just need to decouple the data in y_true now.