Enable hpz when running with torch.no_grad (#4232)

* enable hpz when running with torch.no_grad

* change the way to detect no_grad

* fix format

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Co-authored-by: Ammar Ahmad Awan <ammar.awan@microsoft.com>

deepspeed/runtime/zero/parameter_offload.py

@@ -490,19 +490,20 @@ def _run_after_backward_function(sub_module):
         # post backward hook
         self.backward_hooks.append(module.register_forward_pre_hook(_post_backward_module_hook))
 
-    @torch.no_grad()
     def pre_sub_module_forward_function(self, sub_module):
         see_memory_usage(f"Before sub module function {sub_module.__class__.__name__}", force=False)
-
+        prev_grad_state = torch.is_grad_enabled(
+        )  # we don't want to enable grad for sub modules fetching, yet the subfunction need to know if grad is enabled
+        torch.set_grad_enabled(False)
         global FWD_MODULE_STACK
         FWD_MODULE_STACK.append(sub_module)
 
         param_coordinator = self.get_param_coordinator(training=sub_module.training)
         param_coordinator.trace_prologue(sub_module)
         if param_coordinator.is_record_trace():
             param_coordinator.record_module(sub_module)
-        param_coordinator.fetch_sub_module(sub_module, forward=True)
-
+        param_coordinator.fetch_sub_module(sub_module, forward=prev_grad_state)
+        torch.set_grad_enabled(prev_grad_state)
         see_memory_usage(f"Before sub module function {sub_module.__class__.__name__} after fetch", force=False)
 
     @torch.no_grad()