send weights to target device instead of CPU memory

1 files changed, 15 insertions, 9 deletions

diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py
index 719eeb93..8863107a 100644
--- a/modules/sd_disable_initialization.py
+++ b/modules/sd_disable_initialization.py
@@ -155,10 +155,16 @@ class LoadStateDictOnMeta(ReplaceHelper):
     ```

     """

 

-    def __init__(self, state_dict, device):

+    def __init__(self, state_dict, device, weight_dtype_conversion=None):

         super().__init__()

         self.state_dict = state_dict

         self.device = device

+        self.weight_dtype_conversion = weight_dtype_conversion or {}

+        self.default_dtype = self.weight_dtype_conversion.get('')

+

+    def get_weight_dtype(self, key):

+        key_first_term, _ = key.split('.', 1)

+        return self.weight_dtype_conversion.get(key_first_term, self.default_dtype)

 

     def __enter__(self):

         if shared.cmd_opts.disable_model_loading_ram_optimization:

@@ -167,24 +173,24 @@ class LoadStateDictOnMeta(ReplaceHelper):
         sd = self.state_dict

         device = self.device

 

-        def load_from_state_dict(original, self, state_dict, prefix, *args, **kwargs):

+        def load_from_state_dict(original, module, state_dict, prefix, *args, **kwargs):

             used_param_keys = []

 

-            for name, param in self._parameters.items():

+            for name, param in module._parameters.items():

                 if param is None:

                     continue

 

                 key = prefix + name

                 sd_param = sd.pop(key, None)

                 if sd_param is not None:

-                    state_dict[key] = sd_param

+                    state_dict[key] = sd_param.to(dtype=self.get_weight_dtype(key))

                     used_param_keys.append(key)

 

                 if param.is_meta:

                     dtype = sd_param.dtype if sd_param is not None else param.dtype

-                    self._parameters[name] = torch.nn.parameter.Parameter(torch.zeros_like(param, device=device, dtype=dtype), requires_grad=param.requires_grad)

+                    module._parameters[name] = torch.nn.parameter.Parameter(torch.zeros_like(param, device=device, dtype=dtype), requires_grad=param.requires_grad)

 

-            for name in self._buffers:

+            for name in module._buffers:

                 key = prefix + name

 

                 sd_param = sd.pop(key, None)

@@ -192,12 +198,12 @@ class LoadStateDictOnMeta(ReplaceHelper):
                     state_dict[key] = sd_param

                     used_param_keys.append(key)

 

-            original(self, state_dict, prefix, *args, **kwargs)

+            original(module, state_dict, prefix, *args, **kwargs)

 

             for key in used_param_keys:

                 state_dict.pop(key, None)

 

-        def load_state_dict(original, self, state_dict, strict=True):

+        def load_state_dict(original, module, state_dict, strict=True):

             """torch makes a lot of copies of the dictionary with weights, so just deleting entries from state_dict does not help

             because the same values are stored in multiple copies of the dict. The trick used here is to give torch a dict with

             all weights on meta device, i.e. deleted, and then it doesn't matter how many copies torch makes.

@@ -212,7 +218,7 @@ class LoadStateDictOnMeta(ReplaceHelper):
             if state_dict == sd:

                 state_dict = {k: v.to(device="meta", dtype=v.dtype) for k, v in state_dict.items()}

 

-            original(self, state_dict, strict=strict)

+            original(module, state_dict, strict=strict)

 

         module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs))

         module_load_from_state_dict = self.replace(torch.nn.Module, '_load_from_state_dict', lambda *args, **kwargs: load_from_state_dict(module_load_from_state_dict, *args, **kwargs))