more review comments

n3fit/src/n3fit/backends/keras_backend/callbacks.py

@@ -15,7 +15,6 @@
 import logging
 from time import time
 
-# Callbacks need tensorflow installed even if the backend is pytorch
 from keras.callbacks import Callback, TensorBoard
 import numpy as np
 
@@ -196,7 +195,8 @@ def gen_tensorboard_callback(log_dir, profiling=False, histogram_freq=0):
     If the profiling flag is set to True, it will also attempt
     to save profiling data.
 
-    Note the usage of this callback can hurt performance.
+    Note the usage of this callback can hurt performance
+    At the moment can only be used with TensorFlow: https://github.com/keras-team/keras/issues/19121
 
     Parameters
     ----------

n3fit/src/n3fit/backends/keras_backend/internal_state.py

@@ -56,6 +56,10 @@ def set_threading(threads, cores):
                 "Could not set tensorflow parallelism settings from n3fit, maybe tensorflow is already initialized by a third program"
             )
 
+else:
+    # Keras should've failed by now, if it doesn't it could be a new backend that works ootb?
+    log.warning(f"Backend {K.backend()} not recognized. You are entering uncharted territory")
+
 
 def set_number_of_cores(max_cores=None, max_threads=None):
     """

n3fit/src/n3fit/checks.py

@@ -159,6 +159,14 @@ def check_dropout(parameters):
 def check_tensorboard(tensorboard):
     """Check that the tensorbard callback can be enabled correctly"""
     if tensorboard is not None:
+        # Check that Tensorflow is installed
+        try:
+            import tensorflow
+        except ModuleNotFoundError as e:
+            raise ModuleNotFoundError(
+                "The tensorboard callback requires `tensorflow` to be installed"
+            ) from e
+
         weight_freq = tensorboard.get("weight_freq", 0)
         if weight_freq < 0:
             raise CheckError(