add ci for deepcache and int8 (#556)

Co-authored-by: clackhan <han_binbin@163.com>

.github/workflows/examples.yml

@@ -164,7 +164,7 @@ jobs:
       - run: docker exec ${{ env.CONTAINER_NAME }} python3 -m oneflow --doctor
       - run: docker exec ${{ env.CONTAINER_NAME }} python3 -m pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
       - name: Install onediff-quant if needed
-        if: matrix.image == 'onediff-pro:cu121'
+        if: startsWith(matrix.image, 'onediff-pro')
         run: |
           docker exec ${{ env.CONTAINER_NAME }} python3 -m pip install --pre onediff-quant -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/onediff-quant/
       - name: Pip Install Requirements for ComfyUI & Test
@@ -200,6 +200,14 @@ jobs:
         if: matrix.test-suite == 'comfy'
         run: |
           docker exec ${{ env.CONTAINER_NAME }} cat /app/ComfyUI/onediff_comfyui.log
+      - name: Setup OneDiff diffusers extension
+        if: matrix.test-suite == 'diffusers_examples' && startsWith(matrix.image, 'onediff-pro')
+        run: |
+          docker exec -w /src/onediff/onediff_diffusers_extensions ${{ env.CONTAINER_NAME }} python3 -m pip install e .
+      - if: matrix.test-suite == 'diffusers_examples' && startsWith(matrix.image, 'onediff-pro')
+        run: docker exec ${{ env.CONTAINER_NAME }} python3 examples/text_to_image_sdxl_enterprise.py --model /share_nfs/hf_models/stable-diffusion-xl-base-1.0-int8 --width 512 --height 512 --saved_image output_enterprise_sdxl.png
+      - if: matrix.test-suite == 'diffusers_examples' && startsWith(matrix.image, 'onediff-pro')
+        run: docker exec ${{ env.CONTAINER_NAME }} python3 examples/text_to_image_deep_cache_sdxl_enterprise.py --model /share_nfs/stable-diffusion-xl-base-1.0-int8-deep-cache --width 512 --height 512 --saved_image output_enterprise_deepcache_sdxl.png
       - if: matrix.test-suite == 'diffusers_examples'
         run: docker exec ${{ env.CONTAINER_NAME }} python3 examples/text_to_image.py --model_id=/share_nfs/hf_models/stable-diffusion-v1-5
       - if: matrix.test-suite == 'diffusers_examples'

examples/text_to_image_deep_cache_sdxl_enterprise.py

@@ -27,12 +27,12 @@ def parse_args():
     parser.add_argument("--steps", type=int, default=30)
     parser.add_argument("--bits", type=int, default=8)
     parser.add_argument(
-        "--complie",
+        "--compile",
         default=True,
         type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
     )
     parser.add_argument(
-        "--complie_text_encoder",
+        "--compile_text_encoder",
         default=False,
         type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
         help=(
@@ -61,10 +61,6 @@ def parse_args():
     os.path.join(args.model, "calibrate_info.txt")
 ), f"calibrate_info.txt is required in args.model ({args.model})"
 
-assert (
-    args.complie
-), "Onediff enterprise model can not be executed in pytorch environment. Please set args.complie to 1!"
-
 from diffusers_extensions.deep_cache import StableDiffusionXLPipeline
 import onediff_quant
 from onediff_quant.utils import replace_sub_module_with_quantizable_module
@@ -113,13 +109,13 @@ def parse_args():
         args.bits,
     )
 
-if args.complie_text_encoder:
+if args.compile_text_encoder:
     if pipe.text_encoder is not None:
         pipe.text_encoder = oneflow_compile(pipe.text_encoder, use_graph=args.graph)
     if pipe.text_encoder_2 is not None:
         pipe.text_encoder_2 = oneflow_compile(pipe.text_encoder_2, use_graph=args.graph)
 
-if args.complie:
+if args.compile:
     if pipe.text_encoder is not None:
         pipe.text_encoder = oneflow_compile(pipe.text_encoder, use_graph=args.graph)
     if pipe.text_encoder_2 is not None:

examples/text_to_image_sdxl_enterprise.py

@@ -27,12 +27,12 @@ def parse_args():
     parser.add_argument("--steps", type=int, default=30)
     parser.add_argument("--bits", type=int, default=8)
     parser.add_argument(
-        "--complie",
+        "--compile",
         default=True,
         type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
     )
     parser.add_argument(
-        "--complie_text_encoder",
+        "--compile_text_encoder",
         default=False,
         type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
         help=(
@@ -47,9 +47,6 @@ def parse_args():
     )
     parser.add_argument("--seed", type=int, default=1)
     parser.add_argument("--warmup", type=int, default=1)
-    parser.add_argument("--cache_interval", type=int, default=3)
-    parser.add_argument("--cache_layer_id", type=int, default=0)
-    parser.add_argument("--cache_block_id", type=int, default=0)
 
     args = parser.parse_args()
     return args
@@ -61,10 +58,6 @@ def parse_args():
     os.path.join(args.model, "calibrate_info.txt")
 ), f"calibrate_info.txt is required in args.model ({args.model})"
 
-assert (
-    args.complie
-), "Onediff enterprise model can not be executed in pytorch environment. Please set args.complie to 1!"
-
 from diffusers import StableDiffusionXLPipeline
 import onediff_quant
 from onediff_quant.utils import replace_sub_module_with_quantizable_module
@@ -111,17 +104,13 @@ def parse_args():
         args.bits,
     )
 
-if args.complie_text_encoder:
+if args.compile_text_encoder:
     if pipe.text_encoder is not None:
         pipe.text_encoder = oneflow_compile(pipe.text_encoder, use_graph=args.graph)
     if pipe.text_encoder_2 is not None:
         pipe.text_encoder_2 = oneflow_compile(pipe.text_encoder_2, use_graph=args.graph)
 
-if args.complie:
-    if pipe.text_encoder is not None:
-        pipe.text_encoder = oneflow_compile(pipe.text_encoder, use_graph=args.graph)
-    if pipe.text_encoder_2 is not None:
-        pipe.text_encoder_2 = oneflow_compile(pipe.text_encoder_2, use_graph=args.graph)
+if args.compile:
     pipe.unet = oneflow_compile(pipe.unet, use_graph=args.graph)
     pipe.vae.decoder = oneflow_compile(pipe.vae.decoder, use_graph=args.graph)
 

examples/unet_torch_interplay.py

@@ -4,6 +4,8 @@
 load graph compiled example: python3 examples/unet_torch_interplay.py --load
 """
 import os
+import importlib.metadata
+from packaging import version
 import random
 import click
 import oneflow as flow
@@ -112,7 +114,11 @@ def benchmark(token, repeat, sync_interval, save, load, file, model_id, variant)
 
     num_channels = 4
     cross_attention_dim = unet.config["cross_attention_dim"]
-    from diffusers.utils import floats_tensor
+    diffusers_version = version.parse(importlib.metadata.version("diffusers"))
+    if diffusers_version < version.parse("0.21.0"):
+        from diffusers.utils import floats_tensor
+    else:
+        from diffusers.utils.testing_utils import floats_tensor
 
     if (
         model_id == "stabilityai/stable-diffusion-xl-base-1.0"

onediff_diffusers_extensions/setup.py

@@ -16,7 +16,6 @@
         "accelerate",
         "torch",
         "onefx",
-        "onediff",
     ],
     classifiers=[
         "Development Status :: 5 - Production/Stable",