model opt pass fix and avg pool fix

Author: calad0i

hls4ml/model/optimizer/optimizer.py

@@ -308,10 +308,11 @@ def optimize_model(model, passes):
     optimization_done = False
     while not optimization_done:
         for opt_name, opt in optimizers.items():
-            if isinstance(opt, ModelOptimizerPass) and opt_name not in applied_passes:
-                res = opt.transform(model)
-                if res:
-                    applied_passes.add(opt_name)
+            if isinstance(opt, ModelOptimizerPass):
+                if opt_name not in applied_passes:
+                    res = opt.transform(model)
+                    if res:
+                        applied_passes.add(opt_name)
                 continue
             for node in model.graph.values():
                 if opt.match(node):

hls4ml/model/optimizer/passes/bit_exact.py

@@ -759,7 +759,8 @@ def _(node: Pooling1D | Pooling2D | GlobalPooling1D | GlobalPooling2D):
     if pool_op != 'Average':
         return
     px_shape = _get_px_shape(node)
-    i_add = int(log2(prod(px_shape)))
+    # Used before division, also more int bits
+    i_add = ceil(log2(prod(px_shape)))
     node.attributes['accum_t'].precision.width += i_add
     node.attributes['accum_t'].precision.integer += i_add
 
@@ -804,7 +805,7 @@ def transform(self, model: 'ModelGraph'):
             if node.attributes.get('_request_kif'):
                 del node.attributes['_request_kif']
 
-        return False
+        return True
 
 
 class FixInputPrecision(OptimizerPass):
@@ -861,5 +862,3 @@ def transform(self, model, node: Layer):
         node.get_output_variable().type = new_type
         node.model.config.layer_name_precision[node.name] = str(new_type)
         return False
-        node.model.config.layer_name_precision[node.name] = str(new_type)
-        return False