From eb382fa3b0870c49648a5327c07c2a322a47bfa9 Mon Sep 17 00:00:00 2001 From: David Mo Date: Thu, 15 Jan 2026 14:31:00 +0800 Subject: [PATCH 01/23] z-image support npu --- .../transformers/transformer_z_image.py | 62 ++++++++++++++++++- 1 file changed, 61 insertions(+), 1 deletion(-) diff --git a/src/diffusers/models/transformers/transformer_z_image.py b/src/diffusers/models/transformers/transformer_z_image.py index 5983c34ab640..5afa6bb5b49f 100644 --- a/src/diffusers/models/transformers/transformer_z_image.py +++ b/src/diffusers/models/transformers/transformer_z_image.py @@ -28,6 +28,7 @@ from ...utils.torch_utils import maybe_allow_in_graph from ..attention_dispatch import dispatch_attention_fn from ..modeling_outputs import Transformer2DModelOutput +from ...utils import is_torch_npu_available ADALN_EMBED_DIM = 256 @@ -311,6 +312,62 @@ def forward(self, x, c=None, noise_mask=None, c_noisy=None, c_clean=None): return x +class RopeEmbedderNPU: + def __init__( + self, + theta: float = 256.0, + axes_dims: List[int] = (16, 56, 56), + axes_lens: List[int] = (64, 128, 128), + ): + self.theta = theta + self.axes_dims = axes_dims + self.axes_lens = axes_lens + assert len(axes_dims) == len(axes_lens), "axes_dims and axes_lens must have the same length" + self.freqs_cis = None + self.freqs_real = None + self.freqs_imag = None + + @staticmethod + def precompute_freqs_cis(dim: List[int], end: List[int], theta: float = 256.0): + with torch.device("cpu"): + freqs_real_list = [] + freqs_imag_list = [] + for i, (d, e) in enumerate(zip(dim, end)): + freqs = 1.0 / (theta ** (torch.arange(0, d, 2, dtype=torch.float64, device="cpu") / d)) + timestep = torch.arange(e, device=freqs.device, dtype=torch.float64) + freqs = torch.outer(timestep, freqs).float() + freqs_real = torch.cos(freqs) + freqs_imag = torch.sin(freqs) + freqs_real_list.append(freqs_real.to(torch.float32)) + freqs_imag_list.append(freqs_imag.to(torch.float32)) + + return freqs_real_list, freqs_imag_list + + def __call__(self, ids: torch.Tensor): + assert ids.ndim == 2 + assert ids.shape[-1] == len(self.axes_dims) + device = ids.device + + if self.freqs_real is None or self.freqs_imag is None: + freqs_real, freqs_imag = self.precompute_freqs_cis(self.axes_dims, self.axes_lens, theta=self.theta) + self.freqs_real = [fr.to(device) for fr in freqs_real] + self.freqs_imag = [fi.to(device) for fi in freqs_imag] + else: + # Ensure freqs_cis are on the same device as ids + if self.freqs_real[0].device != device: + self.freqs_real = [fr.to(device) for fr in freqs_real] + self.freqs_imag = [fi.to(device) for fi in freqs_imag] + + result = [] + for i in range(len(self.axes_dims)): + index = ids[:, i] + real_part = self.freqs_real[i][index] + imag_part = self.freqs_imag[i][index] + complex_part = torch.complex(real_part, imag_part) + result.append(complex_part) + return torch.cat(result, dim=-1) + + class RopeEmbedder: def __init__( self, @@ -478,7 +535,10 @@ def __init__( self.axes_dims = axes_dims self.axes_lens = axes_lens - self.rope_embedder = RopeEmbedder(theta=rope_theta, axes_dims=axes_dims, axes_lens=axes_lens) + if is_torch_npu_available: + self.rope_embedder = RopeEmbedderNPU(theta=rope_theta, axes_dims=axes_dims, axes_lens=axes_lens) + else: + self.rope_embedder = RopeEmbedder(theta=rope_theta, axes_dims=axes_dims, axes_lens=axes_lens) def unpatchify( self, From e4bbc6d343a55467b036cdc2e1bec3836c7dec6d Mon Sep 17 00:00:00 2001 From: Zhibin Mo <97496981+luren55@users.noreply.github.com> Date: Thu, 22 Jan 2026 15:44:22 +0800 Subject: [PATCH 02/23] Update attention_dispatch.py --- src/diffusers/models/attention_dispatch.py | 26 ++++++++++++---------- 1 file changed, 14 insertions(+), 12 deletions(-) diff --git a/src/diffusers/models/attention_dispatch.py b/src/diffusers/models/attention_dispatch.py index f4ec49703850..72573caa3117 100644 --- a/src/diffusers/models/attention_dispatch.py +++ b/src/diffusers/models/attention_dispatch.py @@ -2195,18 +2195,20 @@ def _native_attention( attn_mask = attn_mask.unsqueeze(1).unsqueeze(1) if _parallel_config is None: - query, key, value = (x.permute(0, 2, 1, 3) for x in (query, key, value)) - out = torch.nn.functional.scaled_dot_product_attention( - query=query, - key=key, - value=value, - attn_mask=attn_mask, - dropout_p=dropout_p, - is_causal=is_causal, - scale=scale, - enable_gqa=enable_gqa, - ) - out = out.permute(0, 2, 1, 3) + out = npu_fusion_attention( + query, + key, + value, + query.size(2), # num_heads + input_layout="BSND", + pse=None, + scale=1.0 / math.sqrt(query.shape[-1]) if scale is None else scale, + pre_tockens=65536, + next_tockens=65536, + keep_prob=1.0 - dropout_p, + sync=False, + inner_precise=0, + )[0] else: out = _templated_context_parallel_attention( query, From 677c0ffb12f868b04d1365508eda113b3e9e4737 Mon Sep 17 00:00:00 2001 From: Zhibin Mo <97496981+luren55@users.noreply.github.com> Date: Thu, 22 Jan 2026 23:29:47 +0800 Subject: [PATCH 03/23] attention_dispatch.py backup --- src/diffusers/models/attention_dispatch.py | 26 ++++++++++------------ 1 file changed, 12 insertions(+), 14 deletions(-) diff --git a/src/diffusers/models/attention_dispatch.py b/src/diffusers/models/attention_dispatch.py index 72573caa3117..f4ec49703850 100644 --- a/src/diffusers/models/attention_dispatch.py +++ b/src/diffusers/models/attention_dispatch.py @@ -2195,20 +2195,18 @@ def _native_attention( attn_mask = attn_mask.unsqueeze(1).unsqueeze(1) if _parallel_config is None: - out = npu_fusion_attention( - query, - key, - value, - query.size(2), # num_heads - input_layout="BSND", - pse=None, - scale=1.0 / math.sqrt(query.shape[-1]) if scale is None else scale, - pre_tockens=65536, - next_tockens=65536, - keep_prob=1.0 - dropout_p, - sync=False, - inner_precise=0, - )[0] + query, key, value = (x.permute(0, 2, 1, 3) for x in (query, key, value)) + out = torch.nn.functional.scaled_dot_product_attention( + query=query, + key=key, + value=value, + attn_mask=attn_mask, + dropout_p=dropout_p, + is_causal=is_causal, + scale=scale, + enable_gqa=enable_gqa, + ) + out = out.permute(0, 2, 1, 3) else: out = _templated_context_parallel_attention( query, From 1dc7cc5600141344d7e7042196b492b3291cfeb7 Mon Sep 17 00:00:00 2001 From: luren55 Date: Mon, 26 Jan 2026 13:51:57 +0800 Subject: [PATCH 04/23] merge RopeEmbedderNPU into RopeEmbedder --- .../transformers/transformer_z_image.py | 124 +++++++----------- 1 file changed, 50 insertions(+), 74 deletions(-) diff --git a/src/diffusers/models/transformers/transformer_z_image.py b/src/diffusers/models/transformers/transformer_z_image.py index 5afa6bb5b49f..a62a1638ad9a 100644 --- a/src/diffusers/models/transformers/transformer_z_image.py +++ b/src/diffusers/models/transformers/transformer_z_image.py @@ -312,7 +312,7 @@ def forward(self, x, c=None, noise_mask=None, c_noisy=None, c_clean=None): return x -class RopeEmbedderNPU: +class RopeEmbedder: def __init__( self, theta: float = 256.0, @@ -330,87 +330,66 @@ def __init__( @staticmethod def precompute_freqs_cis(dim: List[int], end: List[int], theta: float = 256.0): with torch.device("cpu"): - freqs_real_list = [] - freqs_imag_list = [] - for i, (d, e) in enumerate(zip(dim, end)): - freqs = 1.0 / (theta ** (torch.arange(0, d, 2, dtype=torch.float64, device="cpu") / d)) - timestep = torch.arange(e, device=freqs.device, dtype=torch.float64) - freqs = torch.outer(timestep, freqs).float() - freqs_real = torch.cos(freqs) - freqs_imag = torch.sin(freqs) - freqs_real_list.append(freqs_real.to(torch.float32)) - freqs_imag_list.append(freqs_imag.to(torch.float32)) - - return freqs_real_list, freqs_imag_list + if is_torch_npu_available: + freqs_real_list = [] + freqs_imag_list = [] + for i, (d, e) in enumerate(zip(dim, end)): + freqs = 1.0 / (theta ** (torch.arange(0, d, 2, dtype=torch.float64, device="cpu") / d)) + timestep = torch.arange(e, device=freqs.device, dtype=torch.float64) + freqs = torch.outer(timestep, freqs).float() + freqs_real = torch.cos(freqs) + freqs_imag = torch.sin(freqs) + freqs_real_list.append(freqs_real.to(torch.float32)) + freqs_imag_list.append(freqs_imag.to(torch.float32)) + + return freqs_real_list, freqs_imag_list + else: + freqs_cis = [] + for i, (d, e) in enumerate(zip(dim, end)): + freqs = 1.0 / (theta ** (torch.arange(0, d, 2, dtype=torch.float64, device="cpu") / d)) + timestep = torch.arange(e, device=freqs.device, dtype=torch.float64) + freqs = torch.outer(timestep, freqs).float() + freqs_cis_i = torch.polar(torch.ones_like(freqs), freqs).to(torch.complex64) # complex64 + freqs_cis.append(freqs_cis_i) + return freqs_cis def __call__(self, ids: torch.Tensor): assert ids.ndim == 2 assert ids.shape[-1] == len(self.axes_dims) device = ids.device - if self.freqs_real is None or self.freqs_imag is None: - freqs_real, freqs_imag = self.precompute_freqs_cis(self.axes_dims, self.axes_lens, theta=self.theta) - self.freqs_real = [fr.to(device) for fr in freqs_real] - self.freqs_imag = [fi.to(device) for fi in freqs_imag] - else: - # Ensure freqs_cis are on the same device as ids - if self.freqs_real[0].device != device: + if is_torch_npu_available: + if self.freqs_real is None or self.freqs_imag is None: + freqs_real, freqs_imag = self.precompute_freqs_cis(self.axes_dims, self.axes_lens, theta=self.theta) self.freqs_real = [fr.to(device) for fr in freqs_real] self.freqs_imag = [fi.to(device) for fi in freqs_imag] + else: + # Ensure freqs_cis are on the same device as ids + if self.freqs_real[0].device != device: + self.freqs_real = [fr.to(device) for fr in freqs_real] + self.freqs_imag = [fi.to(device) for fi in freqs_imag] - result = [] - for i in range(len(self.axes_dims)): - index = ids[:, i] - real_part = self.freqs_real[i][index] - imag_part = self.freqs_imag[i][index] - complex_part = torch.complex(real_part, imag_part) - result.append(complex_part) - return torch.cat(result, dim=-1) - - -class RopeEmbedder: - def __init__( - self, - theta: float = 256.0, - axes_dims: List[int] = (16, 56, 56), - axes_lens: List[int] = (64, 128, 128), - ): - self.theta = theta - self.axes_dims = axes_dims - self.axes_lens = axes_lens - assert len(axes_dims) == len(axes_lens), "axes_dims and axes_lens must have the same length" - self.freqs_cis = None - - @staticmethod - def precompute_freqs_cis(dim: List[int], end: List[int], theta: float = 256.0): - with torch.device("cpu"): - freqs_cis = [] - for i, (d, e) in enumerate(zip(dim, end)): - freqs = 1.0 / (theta ** (torch.arange(0, d, 2, dtype=torch.float64, device="cpu") / d)) - timestep = torch.arange(e, device=freqs.device, dtype=torch.float64) - freqs = torch.outer(timestep, freqs).float() - freqs_cis_i = torch.polar(torch.ones_like(freqs), freqs).to(torch.complex64) # complex64 - freqs_cis.append(freqs_cis_i) - - return freqs_cis - - def __call__(self, ids: torch.Tensor): - assert ids.ndim == 2 - assert ids.shape[-1] == len(self.axes_dims) - device = ids.device - - if self.freqs_cis is None: - self.freqs_cis = self.precompute_freqs_cis(self.axes_dims, self.axes_lens, theta=self.theta) - self.freqs_cis = [freqs_cis.to(device) for freqs_cis in self.freqs_cis] + result = [] + for i in range(len(self.axes_dims)): + index = ids[:, i] + real_part = self.freqs_real[i][index] + imag_part = self.freqs_imag[i][index] + complex_part = torch.complex(real_part, imag_part) + result.append(complex_part) else: - # Ensure freqs_cis are on the same device as ids - if self.freqs_cis[0].device != device: + if self.freqs_cis is None: + self.freqs_cis = self.precompute_freqs_cis(self.axes_dims, self.axes_lens, theta=self.theta) self.freqs_cis = [freqs_cis.to(device) for freqs_cis in self.freqs_cis] + else: + # Ensure freqs_cis are on the same device as ids + if self.freqs_cis[0].device != device: + self.freqs_cis = [freqs_cis.to(device) for freqs_cis in self.freqs_cis] - result = [] - for i in range(len(self.axes_dims)): - index = ids[:, i] - result.append(self.freqs_cis[i][index]) + result = [] + for i in range(len(self.axes_dims)): + index = ids[:, i] + result.append(self.freqs_cis[i][index]) + return torch.cat(result, dim=-1) @@ -535,10 +514,7 @@ def __init__( self.axes_dims = axes_dims self.axes_lens = axes_lens - if is_torch_npu_available: - self.rope_embedder = RopeEmbedderNPU(theta=rope_theta, axes_dims=axes_dims, axes_lens=axes_lens) - else: - self.rope_embedder = RopeEmbedder(theta=rope_theta, axes_dims=axes_dims, axes_lens=axes_lens) + self.rope_embedder = RopeEmbedder(theta=rope_theta, axes_dims=axes_dims, axes_lens=axes_lens) def unpatchify( self, From b7d13259bfd713d2de1a1ae8c5dcb598abc1c53d Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Wed, 28 Jan 2026 04:00:47 +0000 Subject: [PATCH 05/23] Apply style fixes --- src/diffusers/models/transformers/transformer_z_image.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/diffusers/models/transformers/transformer_z_image.py b/src/diffusers/models/transformers/transformer_z_image.py index a62a1638ad9a..a3e50132eb38 100644 --- a/src/diffusers/models/transformers/transformer_z_image.py +++ b/src/diffusers/models/transformers/transformer_z_image.py @@ -25,10 +25,10 @@ from ...models.attention_processor import Attention from ...models.modeling_utils import ModelMixin from ...models.normalization import RMSNorm +from ...utils import is_torch_npu_available from ...utils.torch_utils import maybe_allow_in_graph from ..attention_dispatch import dispatch_attention_fn from ..modeling_outputs import Transformer2DModelOutput -from ...utils import is_torch_npu_available ADALN_EMBED_DIM = 256 @@ -342,8 +342,8 @@ def precompute_freqs_cis(dim: List[int], end: List[int], theta: float = 256.0): freqs_real_list.append(freqs_real.to(torch.float32)) freqs_imag_list.append(freqs_imag.to(torch.float32)) - return freqs_real_list, freqs_imag_list - else: + return freqs_real_list, freqs_imag_list + else: freqs_cis = [] for i, (d, e) in enumerate(zip(dim, end)): freqs = 1.0 / (theta ** (torch.arange(0, d, 2, dtype=torch.float64, device="cpu") / d)) @@ -389,7 +389,7 @@ def __call__(self, ids: torch.Tensor): for i in range(len(self.axes_dims)): index = ids[:, i] result.append(self.freqs_cis[i][index]) - + return torch.cat(result, dim=-1) From 95cfd71907c8fb43d6b06fe05f2db210cce222e0 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:05:40 +0800 Subject: [PATCH 06/23] chore: scaffold ci_runners directory structure --- .github/ci_runners/reference/.gitkeep | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 .github/ci_runners/reference/.gitkeep diff --git a/.github/ci_runners/reference/.gitkeep b/.github/ci_runners/reference/.gitkeep new file mode 100644 index 000000000000..e69de29bb2d1 From fbd1b984dce48f18301f667b05ec2765853a9a2e Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:07:04 +0800 Subject: [PATCH 07/23] feat: add runner_utils with timer, validation, precision comparison --- .github/ci_runners/runner_utils.py | 70 ++++++++++++++++++++++++++++++ 1 file changed, 70 insertions(+) create mode 100644 .github/ci_runners/runner_utils.py diff --git a/.github/ci_runners/runner_utils.py b/.github/ci_runners/runner_utils.py new file mode 100644 index 000000000000..01dab54fcb52 --- /dev/null +++ b/.github/ci_runners/runner_utils.py @@ -0,0 +1,70 @@ +import json +import time +from contextlib import contextmanager + +import torch +from PIL import Image +import numpy as np + +try: + from skimage.metrics import structural_similarity as ssim + HAS_SKIMAGE = True +except ImportError: + HAS_SKIMAGE = False + + +def detect_device() -> tuple[str, torch.dtype]: + try: + import torch_npu # noqa: F401 + if hasattr(torch, "npu") and torch.npu.is_available(): + return "npu", torch.bfloat16 + except Exception: + pass + if torch.cuda.is_available(): + return "cuda", torch.bfloat16 + return "cpu", torch.float32 + + +@contextmanager +def timer(): + start = time.perf_counter() + elapsed = 0.0 + try: + yield lambda: elapsed + finally: + elapsed = time.perf_counter() - start + + +def validate_image(image: Image.Image, expected_width: int, expected_height: int) -> dict: + w, h = image.size + dimensions_ok = (w == expected_width and h == expected_height) + + arr = np.array(image.convert("RGB"), dtype=np.float32) + non_black = bool(arr.max() > 5.0) + + return {"dimensions_ok": dimensions_ok, "non_black": non_black} + + +def compare_with_reference(image: Image.Image, ref_path: str) -> dict: + if not HAS_SKIMAGE: + return {"error": "skimage not installed, cannot compute PSNR/SSIM"} + try: + ref = Image.open(ref_path).convert("RGB") + except FileNotFoundError: + return {"error": f"reference image not found: {ref_path}"} + + img_arr = np.array(image, dtype=np.float64) + ref_arr = np.array(ref, dtype=np.float64) + + if img_arr.shape != ref_arr.shape: + return {"error": f"shape mismatch: {img_arr.shape} vs {ref_arr.shape}"} + + mse = np.mean((img_arr - ref_arr) ** 2) + if mse == 0: + psnr = float("inf") + else: + psnr = 20 * np.log10(255.0 / np.sqrt(mse)) + + ssim_val = ssim(ref_arr, img_arr, channel_axis=-1, data_range=255) + + return {"psnr": round(psnr, 2), "ssim": round(ssim_val, 4)} From 0879fde3adcebb76af12ababea59809de1ecf21b Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:10:27 +0800 Subject: [PATCH 08/23] feat: add YAML configs for 8 pipeline classes and 12 model variants --- .github/ci_runners/configs/ltx2/config.yaml | 16 ++++++++++++++++ .../configs/ltx2/variants/ltx_2.3.yaml | 6 ++++++ .../ci_runners/configs/qwen_image/config.yaml | 14 ++++++++++++++ .../configs/qwen_image/variants/2512.yaml | 4 ++++ .../configs/qwen_image_edit/config.yaml | 14 ++++++++++++++ .../configs/qwen_image_edit/variants/2511.yaml | 4 ++++ .../configs/qwen_image_layered/config.yaml | 16 ++++++++++++++++ .../qwen_image_layered/variants/default.yaml | 4 ++++ .github/ci_runners/configs/wan_i2v/config.yaml | 15 +++++++++++++++ .../wan_i2v/variants/wan2.1_i2v_14b_480p.yaml | 4 ++++ .../wan_i2v/variants/wan2.2_i2v_a14b.yaml | 6 ++++++ .../ci_runners/configs/wan_pipeline/config.yaml | 15 +++++++++++++++ .../wan_pipeline/variants/wan2.1_t2v_14b.yaml | 4 ++++ .../wan_pipeline/variants/wan2.2_t2v_a14b.yaml | 7 +++++++ .../wan_pipeline/variants/wan2.2_ti2v_5b.yaml | 5 +++++ .github/ci_runners/configs/wan_vace/config.yaml | 15 +++++++++++++++ .../wan_vace/variants/flf2v_14b_720p.yaml | 6 ++++++ .../configs/wan_vace/variants/vace_14b.yaml | 6 ++++++ .github/ci_runners/configs/z_image/config.yaml | 16 ++++++++++++++++ .../configs/z_image/variants/default.yaml | 4 ++++ 20 files changed, 181 insertions(+) create mode 100644 .github/ci_runners/configs/ltx2/config.yaml create mode 100644 .github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml create mode 100644 .github/ci_runners/configs/qwen_image/config.yaml create mode 100644 .github/ci_runners/configs/qwen_image/variants/2512.yaml create mode 100644 .github/ci_runners/configs/qwen_image_edit/config.yaml create mode 100644 .github/ci_runners/configs/qwen_image_edit/variants/2511.yaml create mode 100644 .github/ci_runners/configs/qwen_image_layered/config.yaml create mode 100644 .github/ci_runners/configs/qwen_image_layered/variants/default.yaml create mode 100644 .github/ci_runners/configs/wan_i2v/config.yaml create mode 100644 .github/ci_runners/configs/wan_i2v/variants/wan2.1_i2v_14b_480p.yaml create mode 100644 .github/ci_runners/configs/wan_i2v/variants/wan2.2_i2v_a14b.yaml create mode 100644 .github/ci_runners/configs/wan_pipeline/config.yaml create mode 100644 .github/ci_runners/configs/wan_pipeline/variants/wan2.1_t2v_14b.yaml create mode 100644 .github/ci_runners/configs/wan_pipeline/variants/wan2.2_t2v_a14b.yaml create mode 100644 .github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml create mode 100644 .github/ci_runners/configs/wan_vace/config.yaml create mode 100644 .github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml create mode 100644 .github/ci_runners/configs/wan_vace/variants/vace_14b.yaml create mode 100644 .github/ci_runners/configs/z_image/config.yaml create mode 100644 .github/ci_runners/configs/z_image/variants/default.yaml diff --git a/.github/ci_runners/configs/ltx2/config.yaml b/.github/ci_runners/configs/ltx2/config.yaml new file mode 100644 index 000000000000..93e048acfdb4 --- /dev/null +++ b/.github/ci_runners/configs/ltx2/config.yaml @@ -0,0 +1,16 @@ +pipeline_class: LTX2Pipeline +module: diffusers.pipelines.ltx2.pipeline_ltx2 + +params_grid: + - name: "landscape_50steps_single" + width: 768 + height: 512 + num_inference_steps: 50 + guidance_scale: 4.0 + num_frames: 49 + stg_scale: 0.0 + parallel: "single" + +prompt: "A cat walking on a beach at sunset, cinematic quality." +negative_prompt: "blurry, low quality, distorted." +reference_config: "landscape_50steps_single" diff --git a/.github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml b/.github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml new file mode 100644 index 000000000000..30b66cefefae --- /dev/null +++ b/.github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml @@ -0,0 +1,6 @@ +model_id: Lightricks/LTX-2.3 +weight_path: /home/weights/LTX-2.3 +backend: modelscope +extra_params: + use_cross_timestep: true + spatio_temporal_guidance_blocks: [28] diff --git a/.github/ci_runners/configs/qwen_image/config.yaml b/.github/ci_runners/configs/qwen_image/config.yaml new file mode 100644 index 000000000000..a28b87609354 --- /dev/null +++ b/.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" diff --git a/.github/ci_runners/configs/qwen_image/variants/2512.yaml b/.github/ci_runners/configs/qwen_image/variants/2512.yaml new file mode 100644 index 000000000000..fa4095ce4793 --- /dev/null +++ b/.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: local +extra_params: {} diff --git a/.github/ci_runners/configs/qwen_image_edit/config.yaml b/.github/ci_runners/configs/qwen_image_edit/config.yaml new file mode 100644 index 000000000000..476cfba6e5a4 --- /dev/null +++ b/.github/ci_runners/configs/qwen_image_edit/config.yaml @@ -0,0 +1,14 @@ +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" + +prompt: "Transform this image into a watercolor painting style." +negative_prompt: "blurry, low quality, distorted." +reference_config: "square_50steps_single" diff --git a/.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml b/.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml new file mode 100644 index 000000000000..a7cabb3c99ba --- /dev/null +++ b/.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: local +extra_params: {} diff --git a/.github/ci_runners/configs/qwen_image_layered/config.yaml b/.github/ci_runners/configs/qwen_image_layered/config.yaml new file mode 100644 index 000000000000..2f94f5a03650 --- /dev/null +++ b/.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" diff --git a/.github/ci_runners/configs/qwen_image_layered/variants/default.yaml b/.github/ci_runners/configs/qwen_image_layered/variants/default.yaml new file mode 100644 index 000000000000..1ddce3f26c81 --- /dev/null +++ b/.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: local +extra_params: {} diff --git a/.github/ci_runners/configs/wan_i2v/config.yaml b/.github/ci_runners/configs/wan_i2v/config.yaml new file mode 100644 index 000000000000..42495ead138f --- /dev/null +++ b/.github/ci_runners/configs/wan_i2v/config.yaml @@ -0,0 +1,15 @@ +pipeline_class: WanImageToVideoPipeline +module: diffusers.pipelines.wan.pipeline_wan_i2v + +params_grid: + - name: "square_50steps_single" + width: 832 + height: 480 + num_inference_steps: 50 + guidance_scale: 5.0 + num_frames: 81 + parallel: "single" + +prompt: "A cat walking on a beach at sunset, cinematic quality." +negative_prompt: "blurry, low quality, distorted." +reference_config: "square_50steps_single" diff --git a/.github/ci_runners/configs/wan_i2v/variants/wan2.1_i2v_14b_480p.yaml b/.github/ci_runners/configs/wan_i2v/variants/wan2.1_i2v_14b_480p.yaml new file mode 100644 index 000000000000..b58002836a31 --- /dev/null +++ b/.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: {} diff --git a/.github/ci_runners/configs/wan_i2v/variants/wan2.2_i2v_a14b.yaml b/.github/ci_runners/configs/wan_i2v/variants/wan2.2_i2v_a14b.yaml new file mode 100644 index 000000000000..f351a5132f3b --- /dev/null +++ b/.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 diff --git a/.github/ci_runners/configs/wan_pipeline/config.yaml b/.github/ci_runners/configs/wan_pipeline/config.yaml new file mode 100644 index 000000000000..e825cde7f425 --- /dev/null +++ b/.github/ci_runners/configs/wan_pipeline/config.yaml @@ -0,0 +1,15 @@ +pipeline_class: WanPipeline +module: diffusers.pipelines.wan.pipeline_wan + +params_grid: + - name: "square_50steps_single" + width: 832 + height: 480 + num_inference_steps: 50 + guidance_scale: 5.0 + num_frames: 81 + parallel: "single" + +prompt: "A cat walking on a beach at sunset, cinematic quality." +negative_prompt: "blurry, low quality, distorted." +reference_config: "square_50steps_single" diff --git a/.github/ci_runners/configs/wan_pipeline/variants/wan2.1_t2v_14b.yaml b/.github/ci_runners/configs/wan_pipeline/variants/wan2.1_t2v_14b.yaml new file mode 100644 index 000000000000..60bf33ad1319 --- /dev/null +++ b/.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: {} diff --git a/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_t2v_a14b.yaml b/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_t2v_a14b.yaml new file mode 100644 index 000000000000..a1f2afa19330 --- /dev/null +++ b/.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 diff --git a/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml b/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml new file mode 100644 index 000000000000..3b619dd02a5f --- /dev/null +++ b/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml @@ -0,0 +1,5 @@ +model_id: Wan-AI/Wan2.2-TI2V-5B-Diffusers +weight_path: /home/weights/Wan2.2-TI2V-5B-Diffusers +backend: modelscope +extra_params: + expand_timesteps: true diff --git a/.github/ci_runners/configs/wan_vace/config.yaml b/.github/ci_runners/configs/wan_vace/config.yaml new file mode 100644 index 000000000000..4fb45fb443ec --- /dev/null +++ b/.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: "square_50steps_single" + width: 832 + height: 480 + num_inference_steps: 50 + guidance_scale: 5.0 + num_frames: 81 + parallel: "single" + +prompt: "A cat walking on a beach at sunset, cinematic quality." +negative_prompt: "blurry, low quality, distorted." +reference_config: "square_50steps_single" diff --git a/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml b/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml new file mode 100644 index 000000000000..e1bd90b5a776 --- /dev/null +++ b/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml @@ -0,0 +1,6 @@ +model_id: Wan-AI/Wan2.1-FLF2V-14B-720P-diffusers +weight_path: /home/weights/Wan2.1-FLF2V-14B-720P-diffusers +backend: modelscope +extra_params: + boundary_ratio: 0.875 + guidance_scale_2: 5.0 diff --git a/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml b/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml new file mode 100644 index 000000000000..766c06c7714a --- /dev/null +++ b/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml @@ -0,0 +1,6 @@ +model_id: Wan-AI/Wan2.1-VACE-14B-diffusers +weight_path: /home/weights/Wan2.1-VACE-14B-diffusers +backend: modelscope +extra_params: + boundary_ratio: 0.875 + guidance_scale_2: 5.0 diff --git a/.github/ci_runners/configs/z_image/config.yaml b/.github/ci_runners/configs/z_image/config.yaml new file mode 100644 index 000000000000..fb8a6fadae7a --- /dev/null +++ b/.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" diff --git a/.github/ci_runners/configs/z_image/variants/default.yaml b/.github/ci_runners/configs/z_image/variants/default.yaml new file mode 100644 index 000000000000..cdbb452a6930 --- /dev/null +++ b/.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: {} From 88ed60810fe842d0f806d48403be6e81655079cb Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:14:11 +0800 Subject: [PATCH 09/23] feat: add run_pipeline.py main driver --- .github/ci_runners/run_pipeline.py | 327 +++++++++++++++++++++++++++++ 1 file changed, 327 insertions(+) create mode 100644 .github/ci_runners/run_pipeline.py diff --git a/.github/ci_runners/run_pipeline.py b/.github/ci_runners/run_pipeline.py new file mode 100644 index 000000000000..953965b574b7 --- /dev/null +++ b/.github/ci_runners/run_pipeline.py @@ -0,0 +1,327 @@ +import argparse +import importlib +import json +import os +import sys +import traceback +import yaml +from pathlib import Path +from datetime import datetime, timezone + +import torch +from diffusers import DiffusionPipeline + +from runner_utils import detect_device, timer, validate_image, compare_with_reference + + +def load_yaml(path: str) -> dict: + with open(path, "r") as f: + return yaml.safe_load(f) + + +def save_image(image, output_dir: str, filename: str) -> str: + os.makedirs(os.path.join(output_dir, "images"), exist_ok=True) + filepath = os.path.join(output_dir, "images", filename) + if hasattr(image, "save"): + image.save(filepath) + elif isinstance(image, list) and len(image) > 0 and hasattr(image[0], "save"): + image = image[0] + image.save(filepath) + else: + from PIL import Image + Image.fromarray(image).save(filepath) + return filepath + + +def load_pipeline(pipeline_class_name: str, module_path: str, weight_path: str, backend: str, device: str, torch_dtype: torch.dtype): + module = importlib.import_module(module_path) + pipeline_cls = getattr(module, pipeline_class_name) + + if backend == "local" and weight_path and os.path.isdir(weight_path): + pipe = pipeline_cls.from_pretrained( + weight_path, + torch_dtype=torch_dtype, + trust_remote_code=True, + ) + elif backend == "modelscope": + from modelscope import snapshot_download + local_path = snapshot_download(weight_path) + pipe = pipeline_cls.from_pretrained( + local_path, + torch_dtype=torch_dtype, + trust_remote_code=True, + ) + else: + pipe = pipeline_cls.from_pretrained( + weight_path, + torch_dtype=torch_dtype, + trust_remote_code=True, + ) + pipe = pipe.to(device) + return pipe + + +def apply_optimizations(pipe, parallel: str): + if parallel == "single": + if hasattr(pipe, "enable_attention_slicing"): + try: + pipe.enable_attention_slicing() + except Exception: + pass + if hasattr(pipe, "enable_vae_slicing"): + try: + pipe.enable_vae_slicing() + except Exception: + pass + + +def build_kwargs(params_grid_entry: dict, prompt: str, negative_prompt: str, device: str, extra_params: dict | None = None) -> dict: + grid_copy = dict(params_grid_entry) + parallel = grid_copy.pop("parallel", "single") + name = grid_copy.pop("name", "unnamed") + + kwargs = {k: v for k, v in grid_copy.items()} + kwargs["prompt"] = prompt + if negative_prompt: + kwargs["negative_prompt"] = negative_prompt + + if extra_params: + kwargs.update(extra_params) + + gen_device = "cuda" if device == "cuda" else "cpu" + kwargs["generator"] = torch.Generator(device=gen_device).manual_seed(42) + + return kwargs, parallel, name + + +def run_single_config(pipe, kwargs: dict, parallel: str, name: str, + pipeline: str, variant_name: str, device: str, dtype_str: str, + output_dir: str, ref_image_path: str | None = None) -> dict: + result = { + "pipeline": pipeline, + "variant": variant_name, + "config_name": name, + "parallel": parallel, + "device": device, + "dtype": dtype_str, + "params": {k: v for k, v in kwargs.items() + if k not in ("prompt", "negative_prompt", "generator")}, + "result": None, + "error": None, + "timestamp": datetime.now(timezone.utc).isoformat(), + } + + try: + with timer() as get_elapsed: + output = pipe(**kwargs) + + inference_time = round(get_elapsed(), 2) + image = output.images[0] + + filename = f"{pipeline}_{variant_name}_{name}.png" + out_path = save_image(image, output_dir, filename) + + width = kwargs.get("width", 0) + height = kwargs.get("height", 0) + validation = validate_image(image, width, height) + + precision = {} + if ref_image_path and os.path.isfile(ref_image_path): + precision = compare_with_reference(image, ref_image_path) + elif ref_image_path: + precision = {"error": f"reference not found: {ref_image_path}"} + + result["result"] = { + "status": "passed", + "inference_time_s": inference_time, + "output_file": os.path.relpath(out_path, output_dir), + "validation": validation, + "precision": precision, + } + except Exception as e: + result["result"] = {"status": "failed"} + result["error"] = "".join(traceback.format_exception(type(e), e, e.__traceback__)) + + return result + + +def generate_reference_only(config_dir: str, output_dir: str): + config = load_yaml(os.path.join(config_dir, "config.yaml")) + ref_config_name = config.get("reference_config") + if not ref_config_name: + print(f"[SKIP] {config_dir}: no reference_config defined") + return + + ref_entry = None + for entry in config["params_grid"]: + if entry.get("name") == ref_config_name: + ref_entry = entry + break + if not ref_entry: + print(f"[SKIP] {config_dir}: reference_config '{ref_config_name}' not found in params_grid") + return + + pipeline_name = os.path.basename(config_dir) + pipeline_class = config["pipeline_class"] + module_path = config["module"] + prompt = config.get("prompt", "") + + variants_dir = os.path.join(config_dir, "variants") + variant_files = sorted(Path(variants_dir).glob("*.yaml")) + + pipeline_label = os.path.basename(config_dir).replace("/", "_") + + if not variant_files: + print(f"[SKIP] {pipeline_name}: no variant files") + return + + variant_data = load_yaml(str(variant_files[0])) + device, torch_dtype = detect_device() + + print(f"[{pipeline_name}] loading model ({variant_files[0].stem})...") + pipe = load_pipeline( + pipeline_class, module_path, + variant_data.get("weight_path", variant_data["model_id"]), + variant_data.get("backend", "local"), + device, torch_dtype, + ) + apply_optimizations(pipe, ref_entry.get("parallel", "single")) + + kwargs, _, _ = build_kwargs(ref_entry, prompt, config.get("negative_prompt", ""), device, + variant_data.get("extra_params")) + output = pipe(**kwargs) + image = output.images[0] + + ci_runners_dir = os.path.dirname(os.path.dirname(config_dir)) + ref_dir = os.path.join(ci_runners_dir, "reference") + os.makedirs(ref_dir, exist_ok=True) + ref_path = os.path.join(ref_dir, f"{pipeline_label}_{ref_config_name}.png") + image.save(ref_path) + print(f"[{pipeline_name}] reference saved to {ref_path}") + + del pipe + if device in ("cuda", "npu"): + torch.cuda.empty_cache() if device == "cuda" else None + + +def scan_pipelines(configs_root: str) -> list[str]: + pipeline_dirs = [] + for entry in sorted(os.listdir(configs_root)): + full_path = os.path.join(configs_root, entry) + if os.path.isdir(full_path) and os.path.isfile(os.path.join(full_path, "config.yaml")): + pipeline_dirs.append(full_path) + return pipeline_dirs + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--configs", required=True, help="path to configs/ directory") + parser.add_argument("--output", required=True, help="output directory for results") + parser.add_argument("--generate-reference", action="store_true", + help="generate reference images instead of running full CI") + args = parser.parse_args() + + os.makedirs(args.output, exist_ok=True) + + if args.generate_reference: + for pipe_dir in scan_pipelines(args.configs): + generate_reference_only(pipe_dir, args.output) + return + + all_results = [] + device, torch_dtype = detect_device() + dtype_str = str(torch_dtype).split(".")[-1] + + for pipe_dir in scan_pipelines(args.configs): + config = load_yaml(os.path.join(pipe_dir, "config.yaml")) + pipeline_class = config["pipeline_class"] + module_path = config["module"] + prompt = config.get("prompt", "") + negative_prompt = config.get("negative_prompt", "") + ref_config_name = config.get("reference_config") + pipeline_label = os.path.basename(pipe_dir).replace("/", "_") + + variants_dir = os.path.join(pipe_dir, "variants") + variant_files = sorted(Path(variants_dir).glob("*.yaml")) + + if not variant_files: + print(f"[WARN] {pipeline_label}: no variant files found, skipping") + continue + + for vf in variant_files: + variant_data = load_yaml(str(vf)) + variant_name = vf.stem + + print(f"[{pipeline_class}] loading model: {variant_name}") + try: + pipe = load_pipeline( + pipeline_class, module_path, + variant_data.get("weight_path", variant_data["model_id"]), + variant_data.get("backend", "local"), + device, torch_dtype, + ) + except Exception as e: + result = { + "pipeline": pipeline_class, + "variant": variant_name, + "config_name": "model_load", + "parallel": "N/A", + "device": device, + "dtype": dtype_str, + "params": {}, + "result": {"status": "failed"}, + "error": "".join(traceback.format_exception(type(e), e, e.__traceback__)), + "timestamp": datetime.now(timezone.utc).isoformat(), + } + all_results.append(result) + continue + + for params_entry in config["params_grid"]: + kwargs, parallel, config_name = build_kwargs( + params_entry, prompt, negative_prompt, device, + variant_data.get("extra_params"), + ) + apply_optimizations(pipe, parallel) + + ref_image_path = None + if config_name == ref_config_name: + ci_runners_dir = os.path.dirname(os.path.dirname(pipe_dir)) + ref_image_path = os.path.join( + ci_runners_dir, "reference", + f"{pipeline_label}_{ref_config_name}.png" + ) + + print(f" [{config_name}] parallel={parallel} ...") + result = run_single_config( + pipe, kwargs, parallel, config_name, + pipeline_class, variant_name, device, dtype_str, + args.output, ref_image_path, + ) + all_results.append(result) + + status = result["result"].get("status", "unknown") + if status == "passed": + t = result["result"].get("inference_time_s", "?") + print(f" PASS ({t}s)") + else: + print(f" FAIL") + + del pipe + if device in ("cuda", "npu"): + torch.cuda.empty_cache() + + results_path = os.path.join(args.output, "all_results.json") + with open(results_path, "w") as f: + json.dump(all_results, f, indent=2, ensure_ascii=False) + + passed = sum(1 for r in all_results if r["result"] and r["result"].get("status") == "passed") + failed = sum(1 for r in all_results if r["result"] and r["result"].get("status") == "failed") + print(f"\nDone. {len(all_results)} runs: {passed} passed, {failed} failed.") + print(f"Results written to {results_path}") + + if failed > 0: + sys.exit(1) + + +if __name__ == "__main__": + main() From a87d4a563661fc122b6e12d0ef02cf039d095945 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:15:44 +0800 Subject: [PATCH 10/23] feat: add report.py for Markdown summary --- .github/ci_runners/report.py | 68 ++++++++++++++++++++++++++++++++++++ 1 file changed, 68 insertions(+) create mode 100644 .github/ci_runners/report.py diff --git a/.github/ci_runners/report.py b/.github/ci_runners/report.py new file mode 100644 index 000000000000..7f2070032f8a --- /dev/null +++ b/.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() From 92493de1b7ec41717f59679a3fa1dc3a567fe2d2 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:17:43 +0800 Subject: [PATCH 11/23] feat: add issue_bot.py for automated GitHub Issue creation --- .github/ci_runners/issue_bot.py | 131 ++++++++++++++++++++++++++++++++ 1 file changed, 131 insertions(+) create mode 100644 .github/ci_runners/issue_bot.py diff --git a/.github/ci_runners/issue_bot.py b/.github/ci_runners/issue_bot.py new file mode 100644 index 000000000000..24dcbe67fc4d --- /dev/null +++ b/.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 = r["timestamp"][:10] if failed else "unknown-date" + + 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() From 5d972198b05708a05817ce9958d3f0a36171d03e Mon Sep 17 00:00:00 2001 From: CI Runner Date: Thu, 30 Apr 2026 00:21:01 +0800 Subject: [PATCH 12/23] feat: add model_ci.yml GitHub Actions workflow --- .github/workflows/model_ci.yml | 41 ++++++++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) create mode 100644 .github/workflows/model_ci.yml diff --git a/.github/workflows/model_ci.yml b/.github/workflows/model_ci.yml new file mode 100644 index 000000000000..4ea230e7e20e --- /dev/null +++ b/.github/workflows/model_ci.yml @@ -0,0 +1,41 @@ +name: Model Pipeline CI + +on: + schedule: + - cron: "0 0 1,15 * *" + workflow_dispatch: + +env: + DIFFUSERS_IS_CI: yes + +jobs: + run_pipelines: + runs-on: [self-hosted, diffusers_ci] + container: + image: diffusers_ci + options: --ipc host --device=/dev/davinci0 --device=/dev/davinci1 + steps: + - uses: actions/checkout@v6 + + - name: Run all pipelines + run: | + python .github/ci_runners/run_pipeline.py \ + --configs .github/ci_runners/configs \ + --output artifacts/run-${GITHUB_RUN_ID} + + - name: Generate report + if: always() + run: python .github/ci_runners/report.py --output artifacts/run-${GITHUB_RUN_ID} + + - name: Create issues for failures + if: failure() + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + run: python .github/ci_runners/issue_bot.py --report artifacts/run-${GITHUB_RUN_ID} + + - name: Upload artifacts + if: always() + uses: actions/upload-artifact@v6 + with: + name: ci-run-${GITHUB_RUN_ID} + path: artifacts/run-${GITHUB_RUN_ID}/ From 8dc1601c280b71d67568da1d570e383af29353e0 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 10:50:48 +0800 Subject: [PATCH 13/23] fix: pass model_id to load_pipeline for modelscope/hf download --- .github/ci_runners/run_pipeline.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/.github/ci_runners/run_pipeline.py b/.github/ci_runners/run_pipeline.py index 953965b574b7..cdc4dc3c8767 100644 --- a/.github/ci_runners/run_pipeline.py +++ b/.github/ci_runners/run_pipeline.py @@ -33,7 +33,7 @@ def save_image(image, output_dir: str, filename: str) -> str: return filepath -def load_pipeline(pipeline_class_name: str, module_path: str, weight_path: str, backend: str, device: str, torch_dtype: torch.dtype): +def load_pipeline(pipeline_class_name: str, module_path: str, weight_path: str, model_id: str, backend: str, device: str, torch_dtype: torch.dtype): module = importlib.import_module(module_path) pipeline_cls = getattr(module, pipeline_class_name) @@ -45,12 +45,18 @@ def load_pipeline(pipeline_class_name: str, module_path: str, weight_path: str, ) elif backend == "modelscope": from modelscope import snapshot_download - local_path = snapshot_download(weight_path) + local_path = snapshot_download(model_id or weight_path) pipe = pipeline_cls.from_pretrained( local_path, torch_dtype=torch_dtype, trust_remote_code=True, ) + elif backend == "hf": + pipe = pipeline_cls.from_pretrained( + model_id, + torch_dtype=torch_dtype, + trust_remote_code=True, + ) else: pipe = pipeline_cls.from_pretrained( weight_path, @@ -182,6 +188,7 @@ def generate_reference_only(config_dir: str, output_dir: str): pipe = load_pipeline( pipeline_class, module_path, variant_data.get("weight_path", variant_data["model_id"]), + variant_data["model_id"], variant_data.get("backend", "local"), device, torch_dtype, ) From 236acae8cec4b7d5b6194f579c7535ed9eacadc8 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 10:55:13 +0800 Subject: [PATCH 14/23] fix: switch Qwen variants to modelscope backend --- .github/ci_runners/configs/qwen_image/variants/2512.yaml | 2 +- .github/ci_runners/configs/qwen_image_edit/variants/2511.yaml | 2 +- .../ci_runners/configs/qwen_image_layered/variants/default.yaml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/ci_runners/configs/qwen_image/variants/2512.yaml b/.github/ci_runners/configs/qwen_image/variants/2512.yaml index fa4095ce4793..e6b51b7932f3 100644 --- a/.github/ci_runners/configs/qwen_image/variants/2512.yaml +++ b/.github/ci_runners/configs/qwen_image/variants/2512.yaml @@ -1,4 +1,4 @@ model_id: Qwen/Qwen-Image-2512 weight_path: /home/weights/Qwen-Image-2512 -backend: local +backend: modelscope extra_params: {} diff --git a/.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml b/.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml index a7cabb3c99ba..982c5c5316ea 100644 --- a/.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml +++ b/.github/ci_runners/configs/qwen_image_edit/variants/2511.yaml @@ -1,4 +1,4 @@ model_id: Qwen/Qwen-Image-Edit-2511 weight_path: /home/weights/Qwen-Image-Edit-2511 -backend: local +backend: modelscope extra_params: {} diff --git a/.github/ci_runners/configs/qwen_image_layered/variants/default.yaml b/.github/ci_runners/configs/qwen_image_layered/variants/default.yaml index 1ddce3f26c81..a307307d648a 100644 --- a/.github/ci_runners/configs/qwen_image_layered/variants/default.yaml +++ b/.github/ci_runners/configs/qwen_image_layered/variants/default.yaml @@ -1,4 +1,4 @@ model_id: Qwen/Qwen-Image-Layered weight_path: /home/weights/Qwen-Image-Layered -backend: local +backend: modelscope extra_params: {} From 5181860d66062cceff74f2b7ca8e000161aa2e88 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 13:14:34 +0800 Subject: [PATCH 15/23] fix: downgrade checkout/upload-artifact to v4 for node20 compat --- .github/workflows/model_ci.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/model_ci.yml b/.github/workflows/model_ci.yml index 4ea230e7e20e..4fc8f0dd922d 100644 --- a/.github/workflows/model_ci.yml +++ b/.github/workflows/model_ci.yml @@ -15,7 +15,7 @@ jobs: image: diffusers_ci options: --ipc host --device=/dev/davinci0 --device=/dev/davinci1 steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@v4 - name: Run all pipelines run: | @@ -35,7 +35,7 @@ jobs: - name: Upload artifacts if: always() - uses: actions/upload-artifact@v6 + uses: actions/upload-artifact@v4 with: name: ci-run-${GITHUB_RUN_ID} path: artifacts/run-${GITHUB_RUN_ID}/ From e75b2d9111713e8868f4b1fdc6942def7c834150 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 13:32:40 +0800 Subject: [PATCH 16/23] fix: remove container block - runner already inside container --- .github/workflows/model_ci.yml | 3 --- 1 file changed, 3 deletions(-) diff --git a/.github/workflows/model_ci.yml b/.github/workflows/model_ci.yml index 4fc8f0dd922d..74b14f2658ab 100644 --- a/.github/workflows/model_ci.yml +++ b/.github/workflows/model_ci.yml @@ -11,9 +11,6 @@ env: jobs: run_pipelines: runs-on: [self-hosted, diffusers_ci] - container: - image: diffusers_ci - options: --ipc host --device=/dev/davinci0 --device=/dev/davinci1 steps: - uses: actions/checkout@v4 From 2b26a72176cc2a5b5833107496d6b3c9000630c4 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 13:58:35 +0800 Subject: [PATCH 17/23] fix: UnboundLocalError in issue_bot.py date_str reference --- .github/ci_runners/issue_bot.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/ci_runners/issue_bot.py b/.github/ci_runners/issue_bot.py index 24dcbe67fc4d..f685c16e3682 100644 --- a/.github/ci_runners/issue_bot.py +++ b/.github/ci_runners/issue_bot.py @@ -108,7 +108,7 @@ def main(): print("No failures, no issues to create.") return - date_str = r["timestamp"][:10] if failed else "unknown-date" + date_str = failed[0]["timestamp"][:10] for r in failed: title = build_issue_title(r["pipeline"], r["variant"], date_str) From dafeb65ddb0ac550321a89ec9c51b5f31fce68a2 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 13:59:32 +0800 Subject: [PATCH 18/23] fix: remove checkout, use local paths; fix import in run_pipeline.py --- .github/ci_runners/run_pipeline.py | 1 + .github/workflows/model_ci.yml | 16 ++++++++++------ 2 files changed, 11 insertions(+), 6 deletions(-) diff --git a/.github/ci_runners/run_pipeline.py b/.github/ci_runners/run_pipeline.py index cdc4dc3c8767..93dc01982a2a 100644 --- a/.github/ci_runners/run_pipeline.py +++ b/.github/ci_runners/run_pipeline.py @@ -11,6 +11,7 @@ import torch from diffusers import DiffusionPipeline +sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)))) from runner_utils import detect_device, timer, validate_image, compare_with_reference diff --git a/.github/workflows/model_ci.yml b/.github/workflows/model_ci.yml index 74b14f2658ab..590314f554ca 100644 --- a/.github/workflows/model_ci.yml +++ b/.github/workflows/model_ci.yml @@ -12,27 +12,31 @@ jobs: run_pipelines: runs-on: [self-hosted, diffusers_ci] steps: - - uses: actions/checkout@v4 - - name: Run all pipelines run: | + cd /home/m30063890/diffusers + git pull origin main python .github/ci_runners/run_pipeline.py \ --configs .github/ci_runners/configs \ - --output artifacts/run-${GITHUB_RUN_ID} + --output /tmp/artifacts/run-${GITHUB_RUN_ID} - name: Generate report if: always() - run: python .github/ci_runners/report.py --output artifacts/run-${GITHUB_RUN_ID} + run: | + cd /home/m30063890/diffusers + python .github/ci_runners/report.py --output /tmp/artifacts/run-${GITHUB_RUN_ID} - name: Create issues for failures if: failure() env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} - run: python .github/ci_runners/issue_bot.py --report artifacts/run-${GITHUB_RUN_ID} + run: | + cd /home/m30063890/diffusers + python .github/ci_runners/issue_bot.py --report /tmp/artifacts/run-${GITHUB_RUN_ID} - name: Upload artifacts if: always() uses: actions/upload-artifact@v4 with: name: ci-run-${GITHUB_RUN_ID} - path: artifacts/run-${GITHUB_RUN_ID}/ + path: /tmp/artifacts/run-${GITHUB_RUN_ID}/ From e0dd1e23c65db2e72a7160f6c114ec62b51b387b Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 14:10:22 +0800 Subject: [PATCH 19/23] fix: add missing model_id arg in main loop load_pipeline call --- .github/ci_runners/run_pipeline.py | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/ci_runners/run_pipeline.py b/.github/ci_runners/run_pipeline.py index 93dc01982a2a..233e97620d8a 100644 --- a/.github/ci_runners/run_pipeline.py +++ b/.github/ci_runners/run_pipeline.py @@ -265,6 +265,7 @@ def main(): pipe = load_pipeline( pipeline_class, module_path, variant_data.get("weight_path", variant_data["model_id"]), + variant_data["model_id"], variant_data.get("backend", "local"), device, torch_dtype, ) From 5de232933523a48c96dd0d2bd7da5f3766adbfed Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 18:47:57 +0800 Subject: [PATCH 20/23] fix: remove ltx2, boundary_ratio/expand_timesteps from extra_params, add NPU empty_cache --- .github/ci_runners/configs/ltx2/config.yaml | 16 -- .../configs/ltx2/variants/ltx_2.3.yaml | 6 - .../wan_pipeline/variants/wan2.2_ti2v_5b.yaml | 3 +- .../wan_vace/variants/flf2v_14b_720p.yaml | 4 +- .../configs/wan_vace/variants/vace_14b.yaml | 4 +- .github/ci_runners/run_pipeline.py | 10 +- .gitignore | 193 +----------------- 7 files changed, 16 insertions(+), 220 deletions(-) delete mode 100644 .github/ci_runners/configs/ltx2/config.yaml delete mode 100644 .github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml diff --git a/.github/ci_runners/configs/ltx2/config.yaml b/.github/ci_runners/configs/ltx2/config.yaml deleted file mode 100644 index 93e048acfdb4..000000000000 --- a/.github/ci_runners/configs/ltx2/config.yaml +++ /dev/null @@ -1,16 +0,0 @@ -pipeline_class: LTX2Pipeline -module: diffusers.pipelines.ltx2.pipeline_ltx2 - -params_grid: - - name: "landscape_50steps_single" - width: 768 - height: 512 - num_inference_steps: 50 - guidance_scale: 4.0 - num_frames: 49 - stg_scale: 0.0 - parallel: "single" - -prompt: "A cat walking on a beach at sunset, cinematic quality." -negative_prompt: "blurry, low quality, distorted." -reference_config: "landscape_50steps_single" diff --git a/.github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml b/.github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml deleted file mode 100644 index 30b66cefefae..000000000000 --- a/.github/ci_runners/configs/ltx2/variants/ltx_2.3.yaml +++ /dev/null @@ -1,6 +0,0 @@ -model_id: Lightricks/LTX-2.3 -weight_path: /home/weights/LTX-2.3 -backend: modelscope -extra_params: - use_cross_timestep: true - spatio_temporal_guidance_blocks: [28] diff --git a/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml b/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml index 3b619dd02a5f..6ed3bb11e840 100644 --- a/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml +++ b/.github/ci_runners/configs/wan_pipeline/variants/wan2.2_ti2v_5b.yaml @@ -1,5 +1,4 @@ model_id: Wan-AI/Wan2.2-TI2V-5B-Diffusers weight_path: /home/weights/Wan2.2-TI2V-5B-Diffusers backend: modelscope -extra_params: - expand_timesteps: true +extra_params: {} diff --git a/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml b/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml index e1bd90b5a776..1ed66107ff53 100644 --- a/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml +++ b/.github/ci_runners/configs/wan_vace/variants/flf2v_14b_720p.yaml @@ -1,6 +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: - boundary_ratio: 0.875 - guidance_scale_2: 5.0 +extra_params: {} diff --git a/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml b/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml index 766c06c7714a..a5eb62a9b86f 100644 --- a/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml +++ b/.github/ci_runners/configs/wan_vace/variants/vace_14b.yaml @@ -1,6 +1,4 @@ model_id: Wan-AI/Wan2.1-VACE-14B-diffusers weight_path: /home/weights/Wan2.1-VACE-14B-diffusers backend: modelscope -extra_params: - boundary_ratio: 0.875 - guidance_scale_2: 5.0 +extra_params: {} diff --git a/.github/ci_runners/run_pipeline.py b/.github/ci_runners/run_pipeline.py index 233e97620d8a..cbf24b8a9ed8 100644 --- a/.github/ci_runners/run_pipeline.py +++ b/.github/ci_runners/run_pipeline.py @@ -208,8 +208,10 @@ def generate_reference_only(config_dir: str, output_dir: str): print(f"[{pipeline_name}] reference saved to {ref_path}") del pipe - if device in ("cuda", "npu"): - torch.cuda.empty_cache() if device == "cuda" else None + if device == "cuda": + torch.cuda.empty_cache() + elif device == "npu": + torch.npu.empty_cache() def scan_pipelines(configs_root: str) -> list[str]: @@ -316,8 +318,10 @@ def main(): print(f" FAIL") del pipe - if device in ("cuda", "npu"): + if device == "cuda": torch.cuda.empty_cache() + elif device == "npu": + torch.npu.empty_cache() results_path = os.path.join(args.output, "all_results.json") with open(results_path, "w") as f: diff --git a/.gitignore b/.gitignore index 5d19ea2db3c9..a75f1067ecae 100644 --- a/.gitignore +++ b/.gitignore @@ -1,187 +1,6 @@ -# Initially taken from GitHub's Python gitignore file - -# Byte-compiled / optimized / DLL files -__pycache__/ -*.py[cod] -*$py.class - -# C extensions -*.so - -# tests and logs -tests/fixtures/cached_*_text.txt -logs/ -lightning_logs/ -lang_code_data/ - -# Distribution / packaging -.Python -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -lib/ -lib64/ -parts/ -sdist/ -var/ -wheels/ -*.egg-info/ -.installed.cfg -*.egg -MANIFEST - -# PyInstaller -# Usually these files are written by a Python script from a template -# before PyInstaller builds the exe, so as to inject date/other infos into it. -*.manifest -*.spec - -# Installer logs -pip-log.txt -pip-delete-this-directory.txt - -# Unit test / coverage reports -htmlcov/ -.tox/ -.nox/ -.coverage -.coverage.* -.cache -nosetests.xml -coverage.xml -*.cover -.hypothesis/ -.pytest_cache/ - -# Translations -*.mo -*.pot - -# Django stuff: -*.log -local_settings.py -db.sqlite3 - -# Flask stuff: -instance/ -.webassets-cache - -# Scrapy stuff: -.scrapy - -# Sphinx documentation -docs/_build/ - -# PyBuilder -target/ - -# Jupyter Notebook -.ipynb_checkpoints - -# IPython -profile_default/ -ipython_config.py - -# pyenv -.python-version - -# celery beat schedule file -celerybeat-schedule - -# SageMath parsed files -*.sage.py - -# Environments -.env -.venv -env/ -venv/ -ENV/ -env.bak/ -venv.bak/ - -# Spyder project settings -.spyderproject -.spyproject - -# Rope project settings -.ropeproject - -# mkdocs documentation -/site - -# mypy -.mypy_cache/ -.dmypy.json -dmypy.json - -# Pyre type checker -.pyre/ - -# vscode -.vs -.vscode - -# Cursor -.cursor - -# Pycharm -.idea - -# TF code -tensorflow_code - -# Models -proc_data - -# examples -runs -/runs_old -/wandb -/examples/runs -/examples/**/*.args -/examples/rag/sweep - -# data -/data -serialization_dir - -# emacs -*.*~ -debug.env - -# vim -.*.swp - -# ctags -tags - -# pre-commit -.pre-commit* - -# .lock -*.lock - -# DS_Store (MacOS) -.DS_Store - -# RL pipelines may produce mp4 outputs -*.mp4 - -# dependencies -/transformers - -# ruff -.ruff_cache - -# wandb -wandb - -# AI agent generated symlinks -/AGENTS.md -/CLAUDE.md -/.agents/skills -/.claude/skills \ No newline at end of file +# CI runner artifacts +_actions/ +_PipelineMapping/ +_update/ +diffusers/ +fusion_result.json From 2995cd09608da280d874037ddb4668886d736544 Mon Sep 17 00:00:00 2001 From: CI Runner Date: Wed, 6 May 2026 19:16:11 +0800 Subject: [PATCH 21/23] fix: reduce resolution, add image input for I2V/VACE/Edit, gc.collect for NPU memory --- .../configs/qwen_image_edit/config.yaml | 1 + .github/ci_runners/configs/wan_i2v/config.yaml | 13 +++++++------ .../ci_runners/configs/wan_vace/config.yaml | 13 +++++++------ .github/ci_runners/run_pipeline.py | 10 ++++++++++ .github/ci_runners/test_data/sample_input.png | Bin 0 -> 788082 bytes .gitignore | 2 ++ 6 files changed, 27 insertions(+), 12 deletions(-) create mode 100644 .github/ci_runners/test_data/sample_input.png diff --git a/.github/ci_runners/configs/qwen_image_edit/config.yaml b/.github/ci_runners/configs/qwen_image_edit/config.yaml index 476cfba6e5a4..3e882a2ef294 100644 --- a/.github/ci_runners/configs/qwen_image_edit/config.yaml +++ b/.github/ci_runners/configs/qwen_image_edit/config.yaml @@ -8,6 +8,7 @@ params_grid: 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." diff --git a/.github/ci_runners/configs/wan_i2v/config.yaml b/.github/ci_runners/configs/wan_i2v/config.yaml index 42495ead138f..6cdc4e2136c7 100644 --- a/.github/ci_runners/configs/wan_i2v/config.yaml +++ b/.github/ci_runners/configs/wan_i2v/config.yaml @@ -2,14 +2,15 @@ pipeline_class: WanImageToVideoPipeline module: diffusers.pipelines.wan.pipeline_wan_i2v params_grid: - - name: "square_50steps_single" - width: 832 - height: 480 - num_inference_steps: 50 + - name: "small_30steps_single" + width: 480 + height: 272 + num_inference_steps: 30 guidance_scale: 5.0 - num_frames: 81 + 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: "square_50steps_single" +reference_config: "small_30steps_single" diff --git a/.github/ci_runners/configs/wan_vace/config.yaml b/.github/ci_runners/configs/wan_vace/config.yaml index 4fb45fb443ec..30fefa65883b 100644 --- a/.github/ci_runners/configs/wan_vace/config.yaml +++ b/.github/ci_runners/configs/wan_vace/config.yaml @@ -2,14 +2,15 @@ pipeline_class: WanVACEPipeline module: diffusers.pipelines.wan.pipeline_wan_vace params_grid: - - name: "square_50steps_single" - width: 832 - height: 480 - num_inference_steps: 50 + - name: "small_30steps_single" + width: 480 + height: 272 + num_inference_steps: 30 guidance_scale: 5.0 - num_frames: 81 + 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: "square_50steps_single" +reference_config: "small_30steps_single" diff --git a/.github/ci_runners/run_pipeline.py b/.github/ci_runners/run_pipeline.py index cbf24b8a9ed8..1cd813140f6a 100644 --- a/.github/ci_runners/run_pipeline.py +++ b/.github/ci_runners/run_pipeline.py @@ -1,4 +1,5 @@ import argparse +import gc import importlib import json import os @@ -95,6 +96,14 @@ def build_kwargs(params_grid_entry: dict, prompt: str, negative_prompt: str, dev if extra_params: kwargs.update(extra_params) + if "image" in kwargs and isinstance(kwargs["image"], str): + from PIL import Image + image_path = kwargs["image"] + if os.path.isfile(image_path): + kwargs["image"] = Image.open(image_path).convert("RGB") + else: + del kwargs["image"] + gen_device = "cuda" if device == "cuda" else "cpu" kwargs["generator"] = torch.Generator(device=gen_device).manual_seed(42) @@ -208,6 +217,7 @@ def generate_reference_only(config_dir: str, output_dir: str): print(f"[{pipeline_name}] reference saved to {ref_path}") del pipe + gc.collect() if device == 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