Make maximum_batch_area take into account python2.0 attention function.

More conservative xformers maximum_batch_area.

comfy/model_management.py

@@ -275,8 +275,17 @@ def xformers_enabled_vae():
     return XFORMERS_ENABLED_VAE
 
 def pytorch_attention_enabled():
+    global ENABLE_PYTORCH_ATTENTION
     return ENABLE_PYTORCH_ATTENTION
 
+def pytorch_attention_flash_attention():
+    global ENABLE_PYTORCH_ATTENTION
+    if ENABLE_PYTORCH_ATTENTION:
+        #TODO: more reliable way of checking for flash attention?
+        if torch.version.cuda: #pytorch flash attention only works on Nvidia
+            return True
+    return False
+
 def get_free_memory(dev=None, torch_free_too=False):
     global xpu_available
     global directml_enabled
@@ -312,9 +321,9 @@ def maximum_batch_area():
         return 0
 
     memory_free = get_free_memory() / (1024 * 1024)
-    if xformers_enabled():
+    if xformers_enabled() or pytorch_attention_flash_attention():
         #TODO: this needs to be tweaked
-        area = 50 * memory_free
+        area = 20 * memory_free
     else:
         #TODO: this formula is because AMD sucks and has memory management issues which might be fixed in the future
         area = ((memory_free - 1024) * 0.9) / (0.6)