z-image support npu

.github/ci_runners/configs/qwen_image/config.yaml

@@ -0,0 +1,14 @@
+pipeline_class: QwenImagePipeline
+module: diffusers.pipelines.qwenimage.pipeline_qwenimage
+
+params_grid:
+  - name: "landscape_50steps_single"
+    width: 1344
+    height: 768
+    num_inference_steps: 50
+    true_cfg_scale: 4.0
+    parallel: "single"
+
+prompt: "A 20-year-old East Asian girl with delicate, charming features and large, bright brown eyes, cheerful expression, wavy long hair tied in twin ponytails, fair skin, light makeup, wearing a modern cute dress in bright soft colors, standing indoors at an anime convention, casual iPhone snapshot style."
+negative_prompt: "低分辨率，低画质，肢体畸形，手指畸形，画面过饱和，蜡像感，人脸无细节，过度光滑，画面具有AI感。构图混乱。文字模糊，扭曲。"
+reference_config: "landscape_50steps_single"

.github/ci_runners/configs/qwen_image/variants/2512.yaml

@@ -0,0 +1,4 @@
+model_id: Qwen/Qwen-Image-2512
+weight_path: /home/weights/Qwen-Image-2512
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/qwen_image_edit/config.yaml

@@ -0,0 +1,15 @@
+pipeline_class: QwenImageEditPipeline
+module: diffusers.pipelines.qwenimage.pipeline_qwenimage_edit
+
+params_grid:
+  - name: "square_50steps_single"
+    width: 1024
+    height: 1024
+    num_inference_steps: 50
+    true_cfg_scale: 4.0
+    parallel: "single"
+    image: ".github/ci_runners/test_data/sample_input.png"
+
+prompt: "Transform this image into a watercolor painting style."
+negative_prompt: "blurry, low quality, distorted."
+reference_config: "square_50steps_single"

.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml

@@ -0,0 +1,4 @@
+model_id: Qwen/Qwen-Image-Edit-2511
+weight_path: /home/weights/Qwen-Image-Edit-2511
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/qwen_image_layered/config.yaml

@@ -0,0 +1,16 @@
+pipeline_class: QwenImageLayeredPipeline
+module: diffusers.pipelines.qwenimage.pipeline_qwenimage_layered
+
+params_grid:
+  - name: "default_50steps_single"
+    width: 1024
+    height: 1024
+    num_inference_steps: 50
+    true_cfg_scale: 4.0
+    layers: 4
+    resolution: 640
+    parallel: "single"
+
+prompt: "A cute cat sitting on a wooden table."
+negative_prompt: "blurry, low quality, distorted."
+reference_config: "default_50steps_single"

.github/ci_runners/configs/qwen_image_layered/variants/default.yaml

@@ -0,0 +1,4 @@
+model_id: Qwen/Qwen-Image-Layered
+weight_path: /home/weights/Qwen-Image-Layered
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/wan_i2v/config.yaml

@@ -0,0 +1,16 @@
+pipeline_class: WanImageToVideoPipeline
+module: diffusers.pipelines.wan.pipeline_wan_i2v
+
+params_grid:
+  - name: "small_30steps_single"
+    width: 480
+    height: 272
+    num_inference_steps: 30
+    guidance_scale: 5.0
+    num_frames: 33
+    parallel: "single"
+    image: ".github/ci_runners/test_data/sample_input.png"
+
+prompt: "A cat walking on a beach at sunset, cinematic quality."
+negative_prompt: "blurry, low quality, distorted."
+reference_config: "small_30steps_single"

.github/ci_runners/configs/wan_i2v/variants/wan2.1_i2v_14b_480p.yaml

@@ -0,0 +1,4 @@
+model_id: Wan-AI/Wan2.1-I2V-14B-480P-Diffusers
+weight_path: /home/weights/Wan2.1-I2V-14B-480P-Diffusers
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/wan_i2v/variants/wan2.2_i2v_a14b.yaml

@@ -0,0 +1,6 @@
+model_id: Wan-AI/Wan2.2-I2V-A14B-Diffusers
+weight_path: /home/weights/Wan2.2-I2V-A14B-Diffusers
+backend: modelscope
+extra_params:
+  boundary_ratio: 0.875
+  guidance_scale_2: 5.0

.github/ci_runners/configs/wan_pipeline/config.yaml

@@ -0,0 +1,15 @@
+pipeline_class: WanPipeline
+module: diffusers.pipelines.wan.pipeline_wan
+
+params_grid:
+  - name: "small_30steps_single"
+    width: 640
+    height: 352
+    num_inference_steps: 30
+    guidance_scale: 5.0
+    num_frames: 49
+    parallel: "single"
+
+prompt: "A cat walking on a beach at sunset, cinematic quality."
+negative_prompt: "blurry, low quality, distorted."
+reference_config: "small_30steps_single"

.github/ci_runners/configs/wan_pipeline/variants/wan2.1_t2v_14b.yaml

@@ -0,0 +1,4 @@
+model_id: Wan-AI/Wan2.1-T2V-14B-Diffusers
+weight_path: /home/weights/Wan2.1-T2V-14B-Diffusers
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/wan_pipeline/variants/wan2.2_t2v_a14b.yaml

@@ -0,0 +1,7 @@
+model_id: Wan-AI/Wan2.2-T2V-A14B-Diffusers
+weight_path: /home/weights/Wan2.2-T2V-A14B-Diffusers
+backend: modelscope
+extra_params:
+  boundary_ratio: 0.875
+  guidance_scale_2: 5.0
+  expand_timesteps: false

.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml

@@ -0,0 +1,4 @@
+model_id: Wan-AI/Wan2.2-TI2V-5B-Diffusers
+weight_path: /home/weights/Wan2.2-TI2V-5B-Diffusers
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/wan_vace/config.yaml

@@ -0,0 +1,15 @@
+pipeline_class: WanVACEPipeline
+module: diffusers.pipelines.wan.pipeline_wan_vace
+
+params_grid:
+  - name: "small_30steps_single"
+    width: 480
+    height: 272
+    num_inference_steps: 30
+    guidance_scale: 5.0
+    num_frames: 33
+    parallel: "single"
+
+prompt: "A cat walking on a beach at sunset, cinematic quality."
+negative_prompt: "blurry, low quality, distorted."
+reference_config: "small_30steps_single"

.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml

@@ -0,0 +1,4 @@
+model_id: Wan-AI/Wan2.1-FLF2V-14B-720P-diffusers
+weight_path: /home/weights/Wan2.1-FLF2V-14B-720P-diffusers
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml

@@ -0,0 +1,4 @@
+model_id: Wan-AI/Wan2.1-VACE-14B-diffusers
+weight_path: /home/weights/Wan2.1-VACE-14B-diffusers
+backend: modelscope
+extra_params: {}

.github/ci_runners/configs/z_image/config.yaml

@@ -0,0 +1,16 @@
+pipeline_class: ZImagePipeline
+module: diffusers.pipelines.z_image.pipeline_z_image
+
+params_grid:
+  - name: "landscape_50steps_single"
+    width: 1024
+    height: 1024
+    num_inference_steps: 50
+    guidance_scale: 5.0
+    cfg_normalization: false
+    cfg_truncation: 1.0
+    parallel: "single"
+
+prompt: "A serene mountain lake at sunrise, hyperrealistic, 8k quality."
+negative_prompt: ""
+reference_config: "landscape_50steps_single"

.github/ci_runners/configs/z_image/variants/default.yaml

@@ -0,0 +1,4 @@
+model_id: Tongyi-MAI/Z-Image
+weight_path: /home/weights/Z-Image
+backend: modelscope
+extra_params: {}

.github/ci_runners/issue_bot.py

@@ -0,0 +1,131 @@
+import argparse
+import json
+import os
+import re
+import urllib.request
+import urllib.error
+
+
+def find_existing_issues(repo: str, token: str, title_prefix: str) -> list[dict]:
+    url = f"https://api.github.com/repos/{repo}/issues?state=open&labels=ci-failure"
+    req = urllib.request.Request(url)
+    req.add_header("Authorization", f"Bearer {token}")
+    req.add_header("Accept", "application/vnd.github+json")
+    req.add_header("User-Agent", "diffusers-ci-bot")
+
+    try:
+        with urllib.request.urlopen(req) as resp:
+            issues = json.loads(resp.read())
+        return [i for i in issues if title_prefix in i.get("title", "")]
+    except Exception:
+        return []
+
+
+def create_issue(repo: str, token: str, title: str, body: str, label: str = "ci-failure") -> str:
+    url = f"https://api.github.com/repos/{repo}/issues"
+    data = json.dumps({"title": title, "body": body, "labels": [label]}).encode("utf-8")
+
+    req = urllib.request.Request(url, data=data, method="POST")
+    req.add_header("Authorization", f"Bearer {token}")
+    req.add_header("Accept", "application/vnd.github+json")
+    req.add_header("User-Agent", "diffusers-ci-bot")
+    req.add_header("Content-Type", "application/json")
+
+    with urllib.request.urlopen(req) as resp:
+        result = json.loads(resp.read())
+    return result.get("html_url", "")
+
+
+def classify_error(error_text: str) -> str:
+    if "out of memory" in error_text.lower() or "OOM" in error_text:
+        return ("**错误类型**: OOM (显存不足)\n\n"
+                "**建议**: 减小 `num_frames`、`width`/`height`，或启用 `enable_attention_slicing`")
+    if "connection" in error_text.lower() or "timeout" in error_text.lower():
+        return ("**错误类型**: 网络/连接异常\n\n"
+                "**建议**: 检查 HuggingFace/ModelScope 网络连通性，或切换到本地权重")
+    if "key" in error_text.lower() or "AttributeError" in error_text:
+        return ("**错误类型**: API 不兼容\n\n"
+                "**建议**: 检查 diffusers 版本与模型是否匹配，检查参数名是否正确（true_cfg_scale vs guidance_scale）")
+    if "import" in error_text.lower() or "ModuleNotFoundError" in error_text.lower():
+        return ("**错误类型**: 依赖缺失\n\n"
+                "**建议**: 检查 requirements，安装缺失的依赖包")
+    return ("**错误类型**: 未知\n\n"
+            "**建议**: 请查看上方错误日志进行人工排查")
+
+
+def build_issue_title(pipeline: str, variant: str, date_str: str) -> str:
+    return f"[CI] {pipeline} / {variant} 运行失败 ({date_str})"
+
+
+def build_issue_body(r: dict, run_url: str) -> str:
+    error_text = r.get("error", "无错误信息")
+    lines = [
+        "## 失败信息",
+        f"- **Pipeline**: {r['pipeline']}",
+        f"- **Variant**: {r['variant']}",
+        f"- **配置**: {r['config_name']}",
+        f"- **设备**: {r['device']} / {r['dtype']}",
+        f"- **并行策略**: {r['parallel']}",
+        "",
+        "## 修复建议",
+        classify_error(error_text),
+        "",
+        "## 错误日志",
+        "```",
+        error_text[:5000],
+        "```",
+        "",
+        f"## 完整日志",
+        f"[Actions Run]({run_url})" if run_url else run_url,
+    ]
+    return "\n".join(lines)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--report", required=True, help="output directory containing all_results.json")
+    args = parser.parse_args()
+
+    repo = os.environ.get("GITHUB_REPOSITORY", "luren55/diffusers")
+    token = os.environ.get("GITHUB_TOKEN", "")
+    run_url = ""
+    server_url = os.environ.get("GITHUB_SERVER_URL", "https://github.com")
+    run_id = os.environ.get("GITHUB_RUN_ID", "")
+    if server_url and repo and run_id:
+        run_url = f"{server_url}/{repo}/actions/runs/{run_id}"
+
+    results_path = os.path.join(args.report, "all_results.json")
+    if not os.path.isfile(results_path):
+        print(f"ERROR: {results_path} not found")
+        return
+
+    with open(results_path, "r") as f:
+        results = json.load(f)
+
+    failed = [r for r in results if r["result"] and r["result"].get("status") == "failed"]
+
+    if not failed:
+        print("No failures, no issues to create.")
+        return
+
+    date_str = failed[0]["timestamp"][:10]
+
+    for r in failed:
+        title = build_issue_title(r["pipeline"], r["variant"], date_str)
+        title_prefix = f"[CI] {r['pipeline']} / {r['variant']}"
+
+        existing = find_existing_issues(repo, token, title_prefix)
+        if existing:
+            print(f"[SKIP] Issue already exists for {r['pipeline']} / {r['variant']}: {existing[0].get('html_url')}")
+            continue
+
+        body = build_issue_body(r, run_url)
+        try:
+            url = create_issue(repo, token, title, body)
+            print(f"[OK] Created issue: {url}")
+        except Exception as e:
+            print(f"[FAIL] Could not create issue: {e}")
+
+
+if __name__ == "__main__":
+    main()

.github/ci_runners/report.py

@@ -0,0 +1,68 @@
+import argparse
+import json
+import os
+from datetime import datetime, timezone
+
+
+def generate_report(results_path: str) -> str:
+    with open(results_path, "r") as f:
+        results = json.load(f)
+
+    passed = [r for r in results if r["result"] and r["result"].get("status") == "passed"]
+    failed = [r for r in results if r["result"] and r["result"].get("status") == "failed"]
+
+    lines = []
+    lines.append("# Diffusers Model CI Report")
+    lines.append(f"**Generated**: {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S UTC')}")
+    lines.append(f"**Total**: {len(results)} | **Passed**: {len(passed)} | **Failed**: {len(failed)}")
+    lines.append("")
+
+    if passed:
+        lines.append("## Passed")
+        lines.append("| Pipeline | Variant | Config | Parallel | Time (s) | PSNR | SSIM |")
+        lines.append("|---|---|---|---|---|---|---|")
+        for r in passed:
+            prec = r["result"].get("precision", {})
+            psnr = prec.get("psnr", "-") if isinstance(prec, dict) else "-"
+            ssim = prec.get("ssim", "-") if isinstance(prec, dict) else "-"
+            lines.append(
+                f"| {r['pipeline']} | {r['variant']} | {r['config_name']} | "
+                f"{r['parallel']} | {r['result'].get('inference_time_s', '-')} | "
+                f"{psnr} | {ssim} |"
+            )
+        lines.append("")
+
+    if failed:
+        lines.append("## Failed")
+        for r in failed:
+            lines.append(f"### {r['pipeline']} / {r['variant']} / {r['config_name']}")
+            lines.append(f"- **Parallel**: {r['parallel']}")
+            lines.append(f"- **Device**: {r['device']} / {r['dtype']}")
+            lines.append("```")
+            lines.append(r.get("error", "")[:2000])
+            lines.append("```")
+            lines.append("")
+    else:
+        lines.append("## All tests passed!")
+
+    return "\n".join(lines)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--output", required=True, help="output directory containing all_results.json")
+    args = parser.parse_args()
+
+    results_path = os.path.join(args.output, "all_results.json")
+    report = generate_report(results_path)
+
+    report_path = os.path.join(args.output, "report.md")
+    with open(report_path, "w") as f:
+        f.write(report)
+
+    print(report)
+    print(f"\nReport written to {report_path}")
+
+
+if __name__ == "__main__":
+    main()