add todo

src/learn.jl

@@ -12,14 +12,38 @@ export learn!
 
 function learn!(m::model, model_respond, correct_answer)
     if m.learning_stage == "learning"
+        #WORKING compute error
+        if m.time_stamp < m.model_params[:perfect_timing]
+            too_early = m.model_params[:perfect_timing] - m.time_stamp
+            model_error = (model_respond .- correct_answer) * too_early
+
+
+
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+
         model_error = Flux.logitcrossentropy(model_respond, correct_answer)
         output_elements_error = model_respond - correct_answer
 
         learn!(m.knowledgeFn[:I], model_error, output_elements_error)
 
-        #WORKING compute error
-        # if m.time_stamp < m.m
-        model_error = model_respond .- correct_answer
+
+
+        
+        
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+
         
 
 
@@ -34,18 +58,18 @@ function learn!(m::model, model_respond, correct_answer)
 end
 
 
-function learn!(m::model, raw_model_respond, correct_answer=nothing)
-    if m.learning_stage != "doing_inference"
-        model_error = Flux.logitcrossentropy(raw_model_respond, correct_answer)
-        output_elements_error = raw_model_respond - correct_answer
+# function learn!(m::model, raw_model_respond, correct_answer=nothing)
+#     if m.learning_stage != "doing_inference"
+#         model_error = Flux.logitcrossentropy(raw_model_respond, correct_answer)
+#         output_elements_error = raw_model_respond - correct_answer
 
-        learn!(m.knowledgeFn[:I], model_error, output_elements_error)
-    else
-        model_error = nothing
-    end
+#         learn!(m.knowledgeFn[:I], model_error, output_elements_error)
+#     else
+#         model_error = nothing
+#     end
 
-    return model_error
-end
+#     return model_error
+# end