Merge branch 'main' into improve-lora-warning-msg

Author: sayakpaul

src/diffusers/loaders/single_file_utils.py

@@ -606,10 +606,14 @@ def infer_diffusers_model_type(checkpoint):
         if any(
             g in checkpoint for g in ["guidance_in.in_layer.bias", "model.diffusion_model.guidance_in.in_layer.bias"]
         ):
-            if checkpoint["img_in.weight"].shape[1] == 384:
-                model_type = "flux-fill"
+            if "model.diffusion_model.img_in.weight" in checkpoint:
+                key = "model.diffusion_model.img_in.weight"
+            else:
+                key = "img_in.weight"
 
-            elif checkpoint["img_in.weight"].shape[1] == 128:
+            if checkpoint[key].shape[1] == 384:
+                model_type = "flux-fill"
+            elif checkpoint[key].shape[1] == 128:
                 model_type = "flux-depth"
             else:
                 model_type = "flux-dev"

tests/single_file/test_model_flux_transformer_single_file.py

@@ -0,0 +1,72 @@
+# coding=utf-8
+# Copyright 2024 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import gc
+import unittest
+
+import torch
+
+from diffusers import (
+    FluxTransformer2DModel,
+)
+from diffusers.utils.testing_utils import (
+    backend_empty_cache,
+    enable_full_determinism,
+    require_torch_accelerator,
+    torch_device,
+)
+
+
+enable_full_determinism()
+
+
+@require_torch_accelerator
+class FluxTransformer2DModelSingleFileTests(unittest.TestCase):
+    model_class = FluxTransformer2DModel
+    ckpt_path = "https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/flux1-dev.safetensors"
+    alternate_keys_ckpt_paths = ["https://huggingface.co/Comfy-Org/flux1-dev/blob/main/flux1-dev-fp8.safetensors"]
+
+    repo_id = "black-forest-labs/FLUX.1-dev"
+
+    def setUp(self):
+        super().setUp()
+        gc.collect()
+        backend_empty_cache(torch_device)
+
+    def tearDown(self):
+        super().tearDown()
+        gc.collect()
+        backend_empty_cache(torch_device)
+
+    def test_single_file_components(self):
+        model = self.model_class.from_pretrained(self.repo_id, subfolder="transformer")
+        model_single_file = self.model_class.from_single_file(self.ckpt_path)
+
+        PARAMS_TO_IGNORE = ["torch_dtype", "_name_or_path", "_use_default_values", "_diffusers_version"]
+        for param_name, param_value in model_single_file.config.items():
+            if param_name in PARAMS_TO_IGNORE:
+                continue
+            assert (
+                model.config[param_name] == param_value
+            ), f"{param_name} differs between single file loading and pretrained loading"
+
+    def test_checkpoint_loading(self):
+        for ckpt_path in self.alternate_keys_ckpt_paths:
+            torch.cuda.empty_cache()
+            model = self.model_class.from_single_file(ckpt_path)
+
+            del model
+            gc.collect()
+            torch.cuda.empty_cache()