WARNING:tensorflow:sample_weight modes were coerced from … to ['…']

Question

Training an image classifier using .fit_generator() or .fit() and passing a dictionary to class_weight= as an argument.

I never go

Answer 1

I believe this is a bug with tensorflow that will happen when you call model.compile() with default parameter sample_weight_mode=None and then call model.fit() with specified sample_weight or class_weight.

From the tensorflow repos:

• fit() eventually calls _process_training_inputs()
• _process_training_inputs() sets sample_weight_modes = [None] based on model.sample_weight_mode = None and then creates a DataAdapter with sample_weight_modes = [None]
• the DataAdapter calls broadcast_sample_weight_modes() with sample_weight_modes = [None] during initialization
• broadcast_sample_weight_modes() seems to expect sample_weight_modes = None but receives [None]
• it asserts that [None] is a different structure from sample_weight / class_weight, overwrites it back to None by fitting to the structure of sample_weight / class_weight and outputs a warning

Warning aside this has no effect on fit() as sample_weight_modes in the DataAdapter is set back to None.

Note that tensorflow documentation states that sample_weight must be a numpy-array. If you call fit() with sample_weight.tolist() instead, you will not get a warning but sample_weight is silently overwritten to None when _process_numpy_inputs() is called in preprocessing and receives an input of length greater than one.