Dev

CHANGELOG.md

@@ -1,5 +1,46 @@
 # Change Log for SD.Next
 
+## Update for 2025-06-15
+
+- **Feature**  
+  - Support for Python 3.13  
+
+- **Changes**  
+  - Increase the medvram mode threshold from 8GB to 12GB  
+  - Set CPU backend to use FP32 by default  
+  - Relax Python version checks for Zluda  
+  - Make VAE options not require model reload  
+  - Add warning about incompatible attention processors  
+
+- **Torch**  
+  - Set default to `torch==2.7.1`  
+  - Force upgrade pip when installing Torch  
+
+- **ROCm**  
+  - Support ROCm 6.4 with `--use-nightly`  
+  - Don't override user set gfx version  
+  - Don't override gfx version with RX 9000  
+  - Fix flash-atten repo  
+
+- **SDNQ Quantization**  
+  - Add group size support for convolutional layers  
+  - Add quantized matmul support for for convolutional layers  
+  - Add 7-bit, 5-bit and 3-bit quantization support  
+  - Add separate quant mode option for Text Encoders  
+  - Fix forced FP32 with tensorwise FP8 matmul  
+  - Fix PyTorch <= 2.4 compatibility with FP8 matmul  
+  - Fix VAE with conv quant  
+  - Don't ignore the Quantize with GPU option with offload mode `none` and `model`  
+
+- **Fixes**  
+  - Meissonic with multiple generators  
+  - OmniGen with new transformers  
+  - Invalid attention processors  
+  - PixArt Sigma Small and Large loading  
+  - TAESD previews with PixArt and Lumina 2  
+  - VAE Tiling with non-default tile sizes  
+  - Lumina 2 with IPEX  
+
 ## Update for 2025-06-02
 
 ### Highlights for 2025-06-02
@@ -31,7 +72,6 @@ Take a look at [Docs](https://github.com/vladmandic/sdnext/wiki/Docs), [Hints](h
     - `INT4` -> `uint4`  
   - Add `float8_e4m3fn`, `float8_e5m2`, `float8_e4m3fnuz`, `float8_e5m2fnuz`, `int6`, `uint6`, `int2`, `uint2` and `uint1` support  
   - Add quantized matmul support for `float8_e4m3fn` and `float8_e5m2`  
-  - Add group size support for convolutional layers  
   - Set the default quant mode to `pre`  
   - Use per token input quant with int8 and fp8 quantized matmul  
   - Implement better layer hijacks  

installer.py

@@ -513,7 +513,7 @@ def get_platform():
 def check_python(supported_minors=[], experimental_minors=[], reason=None):
     if supported_minors is None or len(supported_minors) == 0:
         supported_minors = [9, 10, 11, 12]
-        experimental_minors = []
+        experimental_minors = [13]
     t_start = time.time()
     if args.quick:
         return
@@ -546,7 +546,7 @@ def check_diffusers():
     t_start = time.time()
     if args.skip_all or args.skip_git or args.experimental:
         return
-    sha = '6508da6f06a0da1054ae6a808d0025c04b70f0e8' # diffusers commit hash
+    sha = '8adc6003ba4dbf5b61bb4f1ce571e9e55e145a99' # diffusers commit hash
     pkg = pkg_resources.working_set.by_key.get('diffusers', None)
     minor = int(pkg.version.split('.')[1] if pkg is not None else 0)
     cur = opts.get('diffusers_version', '') if minor > 0 else ''
@@ -582,7 +582,7 @@ def install_cuda():
         cmd = os.environ.get('TORCH_COMMAND', '--upgrade --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu128 --extra-index-url https://download.pytorch.org/whl/nightly/cu126')
     else:
         # cmd = os.environ.get('TORCH_COMMAND', 'torch==2.6.0+cu126 torchvision==0.21.0+cu126 --index-url https://download.pytorch.org/whl/cu126')
-        cmd = os.environ.get('TORCH_COMMAND', 'torch==2.7.0+cu128 torchvision==0.22.0+cu128 --index-url https://download.pytorch.org/whl/cu128')
+        cmd = os.environ.get('TORCH_COMMAND', 'torch==2.7.1+cu128 torchvision==0.22.1+cu128 --index-url https://download.pytorch.org/whl/cu128')
     return cmd
 
 
@@ -633,7 +633,7 @@ def install_rocm_zluda():
     log.info(msg)
 
     if sys.platform == "win32": # TODO install: enable ROCm for windows when available
-        check_python(supported_minors=[10, 11], reason='ZLUDA backend requires Python 3.10 or 3.11')
+        #check_python(supported_minors=[9, 10, 11, 12, 13], reason='ZLUDA backend requires a Python version between 3.9 and 3.13')
 
         if args.device_id is not None:
             if os.environ.get('HIP_VISIBLE_DEVICES', None) is not None:
@@ -655,30 +655,32 @@ def install_rocm_zluda():
         if error is None:
             try:
                 zluda_installer.load()
-                torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.0 torchvision --index-url https://download.pytorch.org/whl/cu118')
+                torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.1+cu118 torchvision==0.22.1+cu118 --index-url https://download.pytorch.org/whl/cu118')
             except Exception as e:
                 error = e
                 log.warning(f'Failed to load ZLUDA: {e}')
         if error is not None:
             log.info('Using CPU-only torch')
             torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision')
     else:
-        check_python(supported_minors=[9, 10, 11, 12], reason='ROCm backend requires a Python version between 3.9 and 3.12')
+        #check_python(supported_minors=[9, 10, 11, 12, 13], reason='ROCm backend requires a Python version between 3.9 and 3.13')
 
         if os.environ.get("TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL", None) is None:
             os.environ.setdefault('TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL', '1')
 
         if args.use_nightly:
-            if rocm.version is None or float(rocm.version) >= 6.3: # assume the latest if version check fails
+            if rocm.version is None or float(rocm.version) >= 6.4: # assume the latest if version check fails
+                torch_command = os.environ.get('TORCH_COMMAND', '--upgrade --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm6.4')
+            elif rocm.version == "6.3":
                 torch_command = os.environ.get('TORCH_COMMAND', '--upgrade --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm6.3')
             else: # oldest rocm version on nightly is 6.2.4
                 torch_command = os.environ.get('TORCH_COMMAND', '--upgrade --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm6.2.4')
         else:
             if rocm.version is None or float(rocm.version) >= 6.3: # assume the latest if version check fails
-                torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.0+rocm6.3 torchvision==0.22.0+rocm6.3 --index-url https://download.pytorch.org/whl/rocm6.3')
+                torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.1+rocm6.3 torchvision==0.22.1+rocm6.3 --index-url https://download.pytorch.org/whl/rocm6.3')
             elif rocm.version == "6.2":
-                # use rocm 6.2.4 instead of 6.2 as torch==2.7.0+rocm6.2 doesn't exists
-                torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.0+rocm6.2.4 torchvision==0.22.0+rocm6.2.4 --index-url https://download.pytorch.org/whl/rocm6.2.4')
+                # use rocm 6.2.4 instead of 6.2 as torch==2.7.1+rocm6.2 doesn't exists
+                torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.1+rocm6.2.4 torchvision==0.22.1+rocm6.2.4 --index-url https://download.pytorch.org/whl/rocm6.2.4')
             elif rocm.version == "6.1":
                 torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.6.0+rocm6.1 torchvision==0.21.0+rocm6.1 --index-url https://download.pytorch.org/whl/rocm6.1')
             elif rocm.version == "6.0":
@@ -696,22 +698,21 @@ def install_rocm_zluda():
             log.debug(f'ROCm hipBLASLt: arch={device.name} available={device.blaslt_supported}')
             rocm.set_blaslt_enabled(device.blaslt_supported)
 
-    if device is None:
-        log.debug('ROCm: HSA_OVERRIDE_GFX_VERSION auto config skipped')
+    if device is None or os.environ.get("HSA_OVERRIDE_GFX_VERSION", None) is not None:
+        log.info(f'ROCm: HSA_OVERRIDE_GFX_VERSION auto config skipped: device={device.name if device is not None else None} version={os.environ.get("HSA_OVERRIDE_GFX_VERSION", None)}')
     else:
         gfx_ver = device.get_gfx_version()
         if gfx_ver is not None:
             os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', gfx_ver)
-        else:
-            log.warning(f'ROCm: device={device.name} could not auto-detect HSA version')
+            log.info(f'ROCm: HSA_OVERRIDE_GFX_VERSION config overridden: device={device.name} version={os.environ.get("HSA_OVERRIDE_GFX_VERSION", None)}')
 
     ts('amd', t_start)
     return torch_command
 
 
-def install_ipex(torch_command):
+def install_ipex():
     t_start = time.time()
-    check_python(supported_minors=[9, 10, 11, 12], reason='IPEX backend requires a Python version between 3.9 and 3.12')
+    #check_python(supported_minors=[9, 10, 11, 12, 13], reason='IPEX backend requires a Python version between 3.9 and 3.13')
     args.use_ipex = True # pylint: disable=attribute-defined-outside-init
     log.info('IPEX: Intel OneAPI toolkit detected')
 
@@ -736,20 +737,20 @@ def install_ipex(torch_command):
     if args.use_nightly:
         torch_command = os.environ.get('TORCH_COMMAND', '--upgrade --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/xpu')
     else:
-        torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.0+xpu torchvision==0.22.0+xpu --index-url https://download.pytorch.org/whl/xpu')
+        torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.1+xpu torchvision==0.22.1+xpu --index-url https://download.pytorch.org/whl/xpu')
 
     ts('ipex', t_start)
     return torch_command
 
 
-def install_openvino(torch_command):
+def install_openvino():
     t_start = time.time()
-    check_python(supported_minors=[9, 10, 11, 12], reason='OpenVINO backend requires a Python version between 3.9 and 3.12')
+    #check_python(supported_minors=[9, 10, 11, 12, 13], reason='OpenVINO backend requires a Python version between 3.9 and 3.13')
     log.info('OpenVINO: selected')
     if sys.platform == 'darwin':
-        torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.0 torchvision==0.22.0')
+        torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.1 torchvision==0.22.1')
     else:
-        torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.0+cpu torchvision==0.22.0+cpu --index-url https://download.pytorch.org/whl/cpu')
+        torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.7.1+cpu torchvision==0.22.1+cpu --index-url https://download.pytorch.org/whl/cpu')
 
     install(os.environ.get('OPENVINO_COMMAND', 'openvino==2025.1.0'), 'openvino')
     install(os.environ.get('NNCF_COMMAND', 'nncf==2.16.0'), 'nncf')
@@ -840,15 +841,15 @@ def check_torch():
         elif is_rocm_available and (args.use_rocm or args.use_zluda): # prioritize rocm
             torch_command = install_rocm_zluda()
         elif allow_ipex and args.use_ipex: # prioritize ipex
-            torch_command = install_ipex(torch_command)
+            torch_command = install_ipex()
         elif allow_openvino and args.use_openvino: # prioritize openvino
-            torch_command = install_openvino(torch_command)
+            torch_command = install_openvino()
         elif is_cuda_available:
             torch_command = install_cuda()
         elif is_rocm_available:
             torch_command = install_rocm_zluda()
         elif is_ipex_available:
-            torch_command = install_ipex(torch_command)
+            torch_command = install_ipex()
         else:
             machine = platform.machine()
             if sys.platform == 'darwin':
@@ -867,6 +868,7 @@ def check_torch():
     if 'torch' in torch_command and not args.version:
         if not installed('torch'):
             log.info(f'Torch: download and install in progress... cmd="{torch_command}"')
+            install('--upgrade pip', 'pip', reinstall=True) # pytorch rocm is too large for older pip
         install(torch_command, 'torch torchvision', quiet=True)
     else:
         try:
@@ -1155,8 +1157,8 @@ def update_setuptools():
 def install_optional():
     t_start = time.time()
     log.info('Installing optional requirements...')
-    install('basicsr')
-    install('gfpgan')
+    install('git+https://github.com/Disty0/BasicSR@2b6a12c28e0c81bfb13b7e984144f0b0f5461484', 'basicsr')
+    install('git+https://github.com/Disty0/GFPGAN@09b1190eabbc77e5f15c61fa7c38a2064b403e20', 'gfpgan')
     install('clean-fid')
     install('pillow-jxl-plugin==1.3.3', ignore=True)
     install('optimum-quanto==0.2.7', ignore=True)
@@ -1188,6 +1190,16 @@ def install_requirements():
         pr.enable()
     if args.skip_requirements and not args.requirements:
         return
+    if int(sys.version_info.minor) >= 13:
+        install('audioop-lts')
+        # gcc 15 patch
+        backup_cmake_policy = os.environ.get('CMAKE_POLICY_VERSION_MINIMUM', None)
+        backup_cxxflags = os.environ.get('CXXFLAGS', None)
+        os.environ.setdefault('CMAKE_POLICY_VERSION_MINIMUM', '3.5')
+        os.environ.setdefault('CXXFLAGS', '-include cstdint')
+        install('git+https://github.com/google/sentencepiece#subdirectory=python', 'sentencepiece')
+        os.environ.setdefault('CMAKE_POLICY_VERSION_MINIMUM', backup_cmake_policy)
+        os.environ.setdefault('CXXFLAGS', backup_cxxflags)
     if not installed('diffusers', quiet=True): # diffusers are not installed, so run initial installation
         global quick_allowed # pylint: disable=global-statement
         quick_allowed = False

modules/devices.py

@@ -331,7 +331,7 @@ def test_fp16():
     if fp16_ok is not None:
         return fp16_ok
     if opts.cuda_dtype != 'FP16': # don't override if the user sets it
-        if sys.platform == "darwin" or backend == 'openvino': # override
+        if sys.platform == "darwin" or backend in {'openvino', 'cpu'}: # override
             fp16_ok = False
             return fp16_ok
         elif backend == 'rocm':
@@ -362,7 +362,7 @@ def test_bf16():
     if bf16_ok is not None:
         return bf16_ok
     if opts.cuda_dtype != 'BF16': # don't override if the user sets it
-        if sys.platform == "darwin" or backend == 'openvino' or backend == 'directml': # override
+        if sys.platform == "darwin" or backend in {'openvino', 'directml', 'cpu'}: # override
             bf16_ok = False
             return bf16_ok
         elif backend == 'rocm' or backend == 'zluda':
@@ -426,8 +426,6 @@ def override_ipex_math():
 
 def set_sdpa_params():
     try:
-        if opts.cross_attention_optimization != "Scaled-Dot-Product":
-            return
         try:
             global sdpa_original # pylint: disable=global-statement
             if sdpa_original is not None:

modules/intel/ipex/__init__.py

@@ -39,7 +39,6 @@ def ipex_init(): # pylint: disable=too-many-statements
             torch.cuda.is_available = torch.xpu.is_available
             torch.cuda.is_initialized = torch.xpu.is_initialized
             torch.cuda.is_current_stream_capturing = lambda: False
-            torch.cuda.set_device = torch.xpu.set_device
             torch.cuda.stream = torch.xpu.stream
             torch.cuda.Event = torch.xpu.Event
             torch.cuda.Stream = torch.xpu.Stream

modules/intel/ipex/diffusers.py

@@ -81,14 +81,46 @@ def get_1d_sincos_pos_embed_from_grid(embed_dim, pos, output_type="np"):
     return emb
 
 
+def apply_rotary_emb(x, freqs_cis, use_real: bool = True, use_real_unbind_dim: int = -1):
+    if use_real:
+        cos, sin = freqs_cis  # [S, D]
+        cos = cos[None, None]
+        sin = sin[None, None]
+        cos, sin = cos.to(x.device), sin.to(x.device)
+
+        if use_real_unbind_dim == -1:
+            # Used for flux, cogvideox, hunyuan-dit
+            x_real, x_imag = x.reshape(*x.shape[:-1], -1, 2).unbind(-1)  # [B, S, H, D//2]
+            x_rotated = torch.stack([-x_imag, x_real], dim=-1).flatten(3)
+        elif use_real_unbind_dim == -2:
+            # Used for Stable Audio, OmniGen, CogView4 and Cosmos
+            x_real, x_imag = x.reshape(*x.shape[:-1], 2, -1).unbind(-2)  # [B, S, H, D//2]
+            x_rotated = torch.cat([-x_imag, x_real], dim=-1)
+        else:
+            raise ValueError(f"`use_real_unbind_dim={use_real_unbind_dim}` but should be -1 or -2.")
+
+        out = (x.float() * cos + x_rotated.float() * sin).to(x.dtype)
+        return out
+    else:
+        # used for lumina
+        # force cpu with Alchemist
+        x_rotated = torch.view_as_complex(x.to("cpu").float().reshape(*x.shape[:-1], -1, 2))
+        freqs_cis = freqs_cis.to("cpu").unsqueeze(2)
+        x_out = torch.view_as_real(x_rotated * freqs_cis).flatten(3)
+        return x_out.type_as(x).to(x.device)
+
+
 def ipex_diffusers(device_supports_fp64=False):
     diffusers.utils.torch_utils.fourier_filter = fourier_filter
     if not device_supports_fp64:
         # get around lazy imports
+        from diffusers.models import embeddings as diffusers_embeddings # pylint: disable=import-error, unused-import # noqa: F401
         from diffusers.models import transformers as diffusers_transformers # pylint: disable=import-error, unused-import # noqa: F401
         from diffusers.models import controlnets as diffusers_controlnets # pylint: disable=import-error, unused-import # noqa: F401
         diffusers.models.embeddings.get_1d_sincos_pos_embed_from_grid = get_1d_sincos_pos_embed_from_grid
         diffusers.models.embeddings.FluxPosEmbed = FluxPosEmbed
+        diffusers.models.embeddings.apply_rotary_emb = apply_rotary_emb
         diffusers.models.transformers.transformer_flux.FluxPosEmbed = FluxPosEmbed
+        diffusers.models.transformers.transformer_lumina2.apply_rotary_emb = apply_rotary_emb
         diffusers.models.controlnets.controlnet_flux.FluxPosEmbed = FluxPosEmbed
         diffusers.models.transformers.transformer_hidream_image.rope = hidream_rope

modules/intel/ipex/hijacks.py

@@ -379,6 +379,12 @@ def torch_cuda_device(device):
     else:
         return torch.xpu.device(device)
 
+@wraps(torch.cuda.set_device)
+def torch_cuda_set_device(device):
+    if check_cuda(device):
+        torch.xpu.set_device(return_xpu(device))
+    else:
+        torch.xpu.set_device(device)
 
 # torch.Generator has to be a class for isinstance checks
 original_torch_Generator = torch.Generator
@@ -412,6 +418,7 @@ def ipex_hijacks():
     torch.load = torch_load
     torch.cuda.synchronize = torch_cuda_synchronize
     torch.cuda.device = torch_cuda_device
+    torch.cuda.set_device = torch_cuda_set_device
 
     torch.Generator = torch_Generator
     torch._C.Generator = torch_Generator