feat:Latent Save/Load (#662)

* wip

* latent dir

* fix

* fix

* now working

* mark todo

* remove server.py changes to separate PRt

---------
Co-authored-by: Lt.Dr.Data <lt.dr.data@gmail.com>

nodes.py

@@ -29,6 +29,8 @@ import importlib
 
 import folder_paths
 
+import safetensors.torch as sft
+
 def before_node_execution():
     comfy.model_management.throw_exception_if_processing_interrupted()
 
@@ -246,6 +248,91 @@ class VAEEncodeForInpaint:
 
         return ({"samples":t, "noise_mask": (mask_erosion[:,:,:x,:y].round())}, )
 
+
+class SaveLatent:
+    def __init__(self):
+        self.output_dir = os.path.join(folder_paths.get_input_directory(), "latents")
+        self.type = "output"
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "samples": ("LATENT", ),
+                              "filename_prefix": ("STRING", {"default": "ComfyUI"})},
+                "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+                }
+    RETURN_TYPES = ()
+    FUNCTION = "save"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "_for_testing"
+
+    def save(self, samples, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
+        def map_filename(filename):
+            prefix_len = len(os.path.basename(filename_prefix))
+            prefix = filename[:prefix_len + 1]
+            try:
+                digits = int(filename[prefix_len + 1:].split('_')[0])
+            except:
+                digits = 0
+            return (digits, prefix)
+
+        subfolder = os.path.dirname(os.path.normpath(filename_prefix))
+        filename = os.path.basename(os.path.normpath(filename_prefix))
+
+        full_output_folder = os.path.join(self.output_dir, subfolder)
+
+        if os.path.commonpath((self.output_dir, os.path.abspath(full_output_folder))) != self.output_dir:
+            print("Saving latent outside the 'input/latents' folder is not allowed.")
+            return {}
+
+        try:
+            counter = max(filter(lambda a: a[1][:-1] == filename and a[1][-1] == "_", map(map_filename, os.listdir(full_output_folder))))[0] + 1
+        except ValueError:
+            counter = 1
+        except FileNotFoundError:
+            os.makedirs(full_output_folder, exist_ok=True)
+            counter = 1
+
+        # support save metadata for latent sharing
+        prompt_info = ""
+        if prompt is not None:
+            prompt_info = json.dumps(prompt)
+
+        metadata = {"workflow": prompt_info}
+        if extra_pnginfo is not None:
+            for x in extra_pnginfo:
+                metadata[x] = json.dumps(extra_pnginfo[x])
+
+        file = f"{filename}_{counter:05}_.latent"
+        file = os.path.join(full_output_folder, file)
+
+        sft.save_file(samples, file, metadata=metadata)
+
+        return {}
+
+
+class LoadLatent:
+    input_dir = os.path.join(folder_paths.get_input_directory(), "latents")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        files = [f for f in os.listdir(s.input_dir) if os.path.isfile(os.path.join(s.input_dir, f)) and f.endswith(".latent")]
+        return {"required": {"latent": [sorted(files), ]}, }
+
+    CATEGORY = "_for_testing"
+
+    RETURN_TYPES = ("LATENT", )
+    FUNCTION = "load"
+
+    def load(self, latent):
+        file = folder_paths.get_annotated_filepath(latent, self.input_dir)
+
+        latent = sft.load_file(file, device="cpu")
+
+        return (latent, )
+
+
 class CheckpointLoader:
     @classmethod
     def INPUT_TYPES(s):
@@ -1235,6 +1322,9 @@ NODE_CLASS_MAPPINGS = {
 
     "CheckpointLoader": CheckpointLoader,
     "DiffusersLoader": DiffusersLoader,
+
+    "LoadLatent": LoadLatent,
+    "SaveLatent": SaveLatent
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {