Revert "fix found_inf bug for custom optimizer (#50158)"

This reverts commit 64573f9f.

python/paddle/amp/grad_scaler.py

@@ -228,16 +228,9 @@ class AmpScaler:
 
         optimize_ops, params_grads = (None, None)
 
-        if hasattr(optimizer, "_set_auxiliary_var"):
         optimizer._set_auxiliary_var('found_inf', self._found_inf)
         optimize_ops, params_grads = optimizer.minimize(*args, **kwargs)
         self._cache_founf_inf = optimizer._get_auxiliary_var('found_inf')
-        else:
-            if self._found_inf:
-                self._cache_founf_inf = True
-            else:
-                optimize_ops, params_grads = optimizer.minimize(*args, **kwargs)
-                self._cache_founf_inf = False
 
         if self._use_dynamic_loss_scaling:
             # uopdate the scale
@@ -778,16 +771,9 @@ class GradScaler(AmpScaler):
         if optimizer_state["state"] is OptimizerState.INIT:
             self._unscale(optimizer)
 
-        if hasattr(optimizer, "_set_auxiliary_var"):
         optimizer._set_auxiliary_var('found_inf', self._found_inf)
         optimizer.step()
         self._cache_founf_inf = optimizer._get_auxiliary_var('found_inf')
-        else:
-            if self._found_inf:
-                self._cache_founf_inf = True
-            else:
-                optimizer.step()
-                self._cache_founf_inf = False
 
         optimizer_state["state"] = OptimizerState.STEPPED
 

python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/hybrid_parallel_gradscaler.py

@@ -41,16 +41,9 @@ class HybridParallelGradScaler:
 
         optimize_ops, params_grads = (None, None)
 
-        if hasattr(optimizer, "_set_auxiliary_var"):
         optimizer._set_auxiliary_var('found_inf', self._found_inf)
         optimize_ops, params_grads = optimizer.minimize(*args, **kwargs)
         self._cache_founf_inf = optimizer._get_auxiliary_var('found_inf')
-        else:
-            if self._found_inf:
-                self._cache_founf_inf = True
-            else:
-                optimize_ops, params_grads = optimizer.minimize(*args, **kwargs)
-                self._cache_founf_inf = False
 
         if self._use_dynamic_loss_scaling:
             self._update()