fix: un-existing tmp config file in linux, avoid unnecessary disk IO (#2591)

src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py

@@ -14,9 +14,8 @@
 # limitations under the License.
 """ Conversion script for the Stable Diffusion checkpoints."""
 
-import os
 import re
-import tempfile
+from io import BytesIO
 from typing import Optional
 
 import requests
@@ -1046,31 +1045,23 @@ def load_pipeline_from_original_stable_diffusion_ckpt(
     if "state_dict" in checkpoint:
         checkpoint = checkpoint["state_dict"]
 
-    with tempfile.TemporaryDirectory() as tmpdir:
-        if original_config_file is None:
-            key_name = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
-
-            original_config_file = os.path.join(tmpdir, "inference.yaml")
-            if key_name in checkpoint and checkpoint[key_name].shape[-1] == 1024:
-                if not os.path.isfile("v2-inference-v.yaml"):
-                    # model_type = "v2"
-                    r = requests.get(
-                        " https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml"
-                    )
-                    open(original_config_file, "wb").write(r.content)
-
-                if global_step == 110000:
-                    # v2.1 needs to upcast attention
-                    upcast_attention = True
-            else:
-                if not os.path.isfile("v1-inference.yaml"):
-                    # model_type = "v1"
-                    r = requests.get(
-                        " https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml"
-                    )
-                    open(original_config_file, "wb").write(r.content)
-
-        original_config = OmegaConf.load(original_config_file)
+    if original_config_file is None:
+        key_name = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
+
+        # model_type = "v1"
+        config_url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml"
+
+        if key_name in checkpoint and checkpoint[key_name].shape[-1] == 1024:
+            # model_type = "v2"
+            config_url = "https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml"
+
+            if global_step == 110000:
+                # v2.1 needs to upcast attention
+                upcast_attention = True
+
+        original_config_file = BytesIO(requests.get(config_url).content)
+
+    original_config = OmegaConf.load(original_config_file)
 
     if num_in_channels is not None:
         original_config["model"]["params"]["unet_config"]["params"]["in_channels"] = num_in_channels