Add additional categorical cross entropy logic

src/TensorFlowNET.Keras/BackendImpl.cs

@@ -260,7 +260,19 @@ namespace Tensorflow.Keras
             if (from_logits)
                 return tf.nn.softmax_cross_entropy_with_logits_v2(labels: target, logits: output, axis: axis);
 
-            throw new NotImplementedException("");
+            if (output.op != null && output.op.type == "Softmax")
+            {
+                if (output.op.inputs.Length != 1) throw new ApplicationException();
+                var o = output = output.op.inputs[0];
+                return tf.nn.softmax_cross_entropy_with_logits_v2(labels: target, logits: o, axis: axis);
+            }
+
+            // scale preds so that the class probas of each sample sum to 1
+            output = output / math_ops.reduce_sum(output, new Axis(axis), true);
+            // Compute cross entropy from probabilities.
+            var epsilon_ = constant_op.constant(epsilon(), output.dtype.as_base_dtype());
+            output = clip_ops.clip_by_value(output, epsilon_, 1.0 - epsilon_);
+            return -math_ops.reduce_sum(target * math_ops.log(output), new Axis(axis));
         }
 
         /// <summary>