From a4df8a754b363934defa995fa850e72648d19347 Mon Sep 17 00:00:00 2001 From: Alexander Eichhorn Date: Tue, 29 Sep 2026 04:20:11 +0200 Subject: [PATCH] chore(deps): move the cpu and cuda extras to torch 2.13.0 (cu130) Pin cpu/cuda to 2.13.0+cpu/+cu130 (macOS and linux-aarch64 stay on 2.7.1), hold the no-extra lock to 2.13.0 and take xformers from the cu130 index. Draw seeded noise in float32 by default (new `noise_dtype` setting), since torch changed its half-precision CPU random numbers. Log a startup error for NVIDIA drivers older than the build's CUDA and GPUs below its lowest architecture, and document the new GPU floor. --- docker/Dockerfile | 6 +- .../src/content/docs/configuration/docker.mdx | 2 +- .../docs/configuration/fp8-storage.mdx | 2 +- docs/src/content/docs/start-here/manual.mdx | 8 +- .../docs/start-here/system-requirements.mdx | 5 +- docs/src/content/docs/troubleshooting/faq.mdx | 4 + docs/src/generated/settings.json | 14 + .../invocations/cogview4/cogview4_denoise.py | 2 +- invokeai/app/invocations/latent_noise.py | 88 +- invokeai/app/invocations/sd3/sd3_denoise.py | 2 +- .../z_image/z_image_seed_variance_enhancer.py | 8 +- invokeai/app/run_app.py | 2 + .../app/services/config/config_default.py | 3 + invokeai/app/util/startup_utils.py | 52 ++ invokeai/backend/flux/sampling_utils.py | 4 +- invokeai/backend/flux2/sampling_utils.py | 4 +- invokeai/backend/util/devices.py | 11 + invokeai/frontend/web/openapi.json | 9 +- .../frontend/web/src/services/api/schema.ts | 8 + pins.json | 4 +- pyproject.toml | 93 +- scripts/check_aarch64_lock.py | 4 +- .../app/util/test_cuda_build_compatibility.py | 95 ++ tests/backend/util/test_noise_dtype.py | 142 +++ uv.lock | 836 ++++++++---------- 25 files changed, 816 insertions(+), 592 deletions(-) create mode 100644 tests/app/util/test_cuda_build_compatibility.py create mode 100644 tests/backend/util/test_noise_dtype.py diff --git a/docker/Dockerfile b/docker/Dockerfile index a9a983e3587..402ce118511 100644 --- a/docker/Dockerfile +++ b/docker/Dockerfile @@ -66,10 +66,8 @@ WORKDIR ${INVOKEAI_SRC} # Install project's dependencies as a separate layer so they aren't rebuilt every commit. # bind-mount instead of copy to defer adding sources to the image until next layer. # -# NOTE: on arm64 (aarch64), torch/torchvision resolve to PyPI CPU wheels regardless of -# GPU_DRIVER — the WHL indexes carry aarch64 torch wheels (+cpu/+cu128) but no aarch64 -# torchvision wheels, so the pinned pairs only apply on x86_64. Use GPU_DRIVER=cpu on arm64. -# CUDA-on-arm64 (e.g. Grace/GH200) would need a torchvision-specific workaround; see pyproject.toml. +# NOTE: on arm64 (aarch64), torch/torchvision resolve to the PyPI CPU wheels (2.7.1) regardless of +# GPU_DRIVER -- the pinned WHL-index pairs only apply on x86_64 (see pyproject.toml). Use GPU_DRIVER=cpu on arm64. # x86_64/CUDA is the default RUN --mount=type=cache,target=/root/.cache/uv \ --mount=type=bind,source=pyproject.toml,target=pyproject.toml \ diff --git a/docs/src/content/docs/configuration/docker.mdx b/docs/src/content/docs/configuration/docker.mdx index 17f6e108eb6..9ab015bf304 100644 --- a/docs/src/content/docs/configuration/docker.mdx +++ b/docs/src/content/docs/configuration/docker.mdx @@ -25,7 +25,7 @@ import SystemRequirementsLink from '@components/SystemRequirmentsLink.astro' ## TL;DR -Ensure your Docker setup is able to use your GPU. Then: +Ensure your Docker setup is able to use your GPU. The CUDA image needs an Nvidia driver from the R580 series or newer on the host and a GPU with compute capability 7.5 or newer (GTX 16xx, RTX 20xx and later). Then: ```bash docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai diff --git a/docs/src/content/docs/configuration/fp8-storage.mdx b/docs/src/content/docs/configuration/fp8-storage.mdx index 880d99dbf13..013fd4a0822 100644 --- a/docs/src/content/docs/configuration/fp8-storage.mdx +++ b/docs/src/content/docs/configuration/fp8-storage.mdx @@ -17,7 +17,7 @@ FP8 Storage is meant for **full precision** checkpoints (FP16 / BF16 / FP32). It ## Requirements - **Nvidia GPU on Windows or Linux.** FP8 Storage uses CUDA tensor types and is silently disabled on CPU and MPS. -- **CUDA 12.x and recent PyTorch.** The `float8_e4m3fn` dtype was added in PyTorch 2.1 — InvokeAI's bundled versions satisfy this. +- **A CUDA build of recent PyTorch.** The `float8_e4m3fn` dtype was added in PyTorch 2.1 — InvokeAI's bundled versions satisfy this. There is no hardware requirement for FP8 *compute* — InvokeAI casts back to FP16/BF16 for math. This means FP8 Storage works on GPUs that do not natively support FP8 matmul (e.g. RTX 30-series), at a small per-step throughput cost. diff --git a/docs/src/content/docs/start-here/manual.mdx b/docs/src/content/docs/start-here/manual.mdx index 7b8f6266bea..ff93fe3413b 100644 --- a/docs/src/content/docs/start-here/manual.mdx +++ b/docs/src/content/docs/start-here/manual.mdx @@ -87,7 +87,7 @@ The following commands vary depending on the version of Invoke being installed a 6. Determine the package specifier to use when installing. This is a performance optimization. - - If you have an Nvidia 20xx series GPU or older, use `invokeai[xformers]`. + - If you have an Nvidia 16xx or 20xx series GPU, use `invokeai[xformers]`. - If you have an Nvidia 30xx series GPU or newer, or do not have an Nvidia GPU, use `invokeai`. 7. Determine the torch backend to use for installation, if any. This is necessary to get the right version of torch installed. This is achieved by using [UV's built in torch support.](https://docs.astral.sh/uv/guides/integration/pytorch/#automatic-backend-selection) @@ -102,7 +102,7 @@ The following commands vary depending on the version of Invoke being installed a Use: ```sh - --torch-backend=cu128 + --torch-backend=cu130 ``` @@ -122,7 +122,7 @@ The following commands vary depending on the version of Invoke being installed a Use: ```sh - --torch-backend=cu128 + --torch-backend=cu130 ``` @@ -130,7 +130,7 @@ The following commands vary depending on the version of Invoke being installed a ```sh --torch-backend=cpu ``` - On ARM64 (`aarch64`, e.g. Raspberry Pi 5), do **not** use a torch backend — PyTorch's `cpu` index has no ARM64 torchvision wheels. The default PyPI wheels are CPU-only on ARM64 and work out of the box. + On ARM64 (`aarch64`, e.g. Raspberry Pi 5), do **not** use a torch backend. The default PyPI wheels are CPU-only on ARM64 and work out of the box. Use: diff --git a/docs/src/content/docs/start-here/system-requirements.mdx b/docs/src/content/docs/start-here/system-requirements.mdx index ede60e15bbb..1196ce26cee 100644 --- a/docs/src/content/docs/start-here/system-requirements.mdx +++ b/docs/src/content/docs/start-here/system-requirements.mdx @@ -16,6 +16,7 @@ Hardware requirements vary significantly depending on model and image output siz The requirements below are rough guidelines for best performance. GPUs with less VRAM typically still work, if a bit slower. Follow the [Low VRAM Guide] to optimize performance. - All Apple Silicon (M1, M2, etc) Macs work, but 16GB+ memory is recommended. +- Nvidia GPUs need compute capability 7.5 or newer (GTX 16xx, RTX 20xx and everything after) and a driver from the R580 series or newer. Maxwell, Pascal and Volta cards (GTX 9xx/10xx, Titan V, Tesla P40/P100/V100) are not supported by Invoke's CUDA build: stay on the previous Invoke release, or do a [manual install](../manual) with `--torch-backend=cu126`, whose PyTorch build still includes these GPUs (not tested by the Invoke team). With a driver that is too old, Invoke starts on the CPU and logs an error saying so; on an unsupported GPU it logs an error at startup and generation fails. - AMD GPUs are supported on Linux only. The VRAM requirements are the same as Nvidia GPUs. - Intel Arc GPUs (Alchemist, Battlemage and newer) are supported on Windows and Linux `x86_64`. The VRAM requirements are the same as Nvidia GPUs. - Linux ARM64 (`aarch64`) devices — e.g. Raspberry Pi 5, other SBCs, ARM servers — are supported in CPU-only mode. Local generation is slow without a GPU, but API-backed models (e.g. GPT Image, Gemini) work well. @@ -24,7 +25,7 @@ The requirements below are rough guidelines for best performance. GPUs with less | Model Family | Best resolution | GPU (series) | VRAM (min) | RAM (min) | Notes | |---|---:|---|---:|---:|---| -| SD1.5 | 512x512 | Nvidia 10xx+ | 4GB | 8GB | | +| SD1.5 | 512x512 | Nvidia 16xx+ | 4GB | 8GB | | | SDXL | 1024x1024 | Nvidia 20xx+ | 8GB | 16GB | | | FLUX.1 | 1024x1024 | Nvidia 20xx+ | 10GB | 32GB | Download totals: NF4 ~12GB, int8 ~18GB, bf16 ~33GB. The int8 transformer is 11.5GB resident on any supported GPU, so it streams on a 10GB card | | FLUX.2 Klein 4B | 1024x1024 | Nvidia 30xx+ | 12GB | 16GB | FP8 works with 8GB+; Diffusers + encoder | @@ -112,6 +113,8 @@ Go to the [CUDA Toolkit Downloads] and carefully follow the instructions for you Confirm that `nvidia-smi` displays driver and CUDA versions after installation. +Invoke's CUDA build (PyTorch 2.13 with CUDA 13.0) needs an Nvidia driver from the R580 series or newer. See [Hardware](#hardware) for the supported GPUs. + #### Linux - via Nvidia Container Runtime An alternative to installing CUDA locally is to use the [Nvidia Container Runtime] to run the application in a container. diff --git a/docs/src/content/docs/troubleshooting/faq.mdx b/docs/src/content/docs/troubleshooting/faq.mdx index 3c33845f995..bdd339130bb 100644 --- a/docs/src/content/docs/troubleshooting/faq.mdx +++ b/docs/src/content/docs/troubleshooting/faq.mdx @@ -59,6 +59,10 @@ Firefox does not allow Invoke to directly access the clipboard by default. As a Most example images with prompts that you'll find on the internet have been generated using different software, so you can't expect to get identical results. In order to reproduce an image, you need to replicate the exact settings and processing steps, including (but not limited to) the model, the positive and negative prompts, the seed, the sampler, the exact image size, any upscaling steps, etc. +## Same seed, different image after an update + +Invoke now draws its seeded noise in `float32`, because PyTorch 2.13 changed its half-precision random numbers. For SD1.5, SDXL, SD3, FLUX.1, FLUX.2, CogView4 and Z-Image's seed variance enhancer, a seed therefore gives a different image than it did before this update. On Windows and Linux the older images cannot be reproduced exactly. On macOS, set `noise_dtype: float16` in the [configuration file][configuration docs] to keep the images your seeds gave before. + ## Invalid configuration file Everything seems to install ok, you get a `ValidationError` when starting up the app. diff --git a/docs/src/generated/settings.json b/docs/src/generated/settings.json index f23aaf9fc22..cd4dddc8f5d 100644 --- a/docs/src/generated/settings.json +++ b/docs/src/generated/settings.json @@ -652,6 +652,20 @@ "type": "", "validation": {} }, + { + "category": "GENERATION", + "default": "float32", + "description": "The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there.", + "env_var": "INVOKEAI_NOISE_DTYPE", + "literal_values": [ + "float32", + "float16" + ], + "name": "noise_dtype", + "required": false, + "type": "typing.Literal['float32', 'float16']", + "validation": {} + }, { "category": "GENERATION", "default": false, diff --git a/invokeai/app/invocations/cogview4/cogview4_denoise.py b/invokeai/app/invocations/cogview4/cogview4_denoise.py index cb06d2b3ff6..283c190dbde 100644 --- a/invokeai/app/invocations/cogview4/cogview4_denoise.py +++ b/invokeai/app/invocations/cogview4/cogview4_denoise.py @@ -140,7 +140,7 @@ def _get_noise( ) -> torch.Tensor: # We always generate noise on the same device and dtype then cast to ensure consistency across devices/dtypes. rand_device = "cpu" - rand_dtype = torch.float16 + rand_dtype = TorchDevice.choose_noise_dtype(torch.float16) return torch.randn( batch_size, diff --git a/invokeai/app/invocations/latent_noise.py b/invokeai/app/invocations/latent_noise.py index 815effe972c..55195459d5d 100644 --- a/invokeai/app/invocations/latent_noise.py +++ b/invokeai/app/invocations/latent_noise.py @@ -58,79 +58,17 @@ def generate_noise_tensor( dtype: torch.dtype, use_cpu: bool = True, ) -> torch.Tensor: - validate_noise_dimensions(noise_type, width, height) + shape = get_expected_noise_shape(noise_type, width, height) rand_device = "cpu" if use_cpu else device.type - rand_dtype = TorchDevice.choose_torch_dtype(device=device) - - if noise_type == "SD": - return torch.randn( - 1, - 4, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - dtype=rand_dtype, - device=rand_device, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - if noise_type == "FLUX": - return torch.randn( - 1, - 16, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - device=rand_device, - dtype=rand_dtype, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - if noise_type == "FLUX.2": - return torch.randn( - 1, - 32, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - device=rand_device, - dtype=rand_dtype, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - if noise_type == "SD3": - return torch.randn( - 1, - 16, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - device=rand_device, - dtype=rand_dtype, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - if noise_type == "CogView4": - return torch.randn( - 1, - 16, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - device=rand_device, - dtype=rand_dtype, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - if noise_type == "Z-Image": - return torch.randn( - 1, - 16, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - device=rand_device, - dtype=torch.float32, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - if noise_type == "Anima": - return torch.randn( - 1, - 16, - 1, - height // LATENT_SCALE_FACTOR, - width // LATENT_SCALE_FACTOR, - device=rand_device, - dtype=torch.float32, - generator=torch.Generator(device=rand_device).manual_seed(seed), - ).to("cpu") - raise ValueError(f"Unsupported noise type: {noise_type}") + if noise_type in ("Z-Image", "Anima"): + output_dtype = rand_dtype = torch.float32 + else: + # The tensor keeps the device precision it always had; only the dtype it is drawn in follows `noise_dtype`. + output_dtype = dtype + rand_dtype = TorchDevice.choose_noise_dtype(dtype) + return torch.randn( + *shape, + device=rand_device, + dtype=rand_dtype, + generator=torch.Generator(device=rand_device).manual_seed(seed), + ).to(device="cpu", dtype=output_dtype) diff --git a/invokeai/app/invocations/sd3/sd3_denoise.py b/invokeai/app/invocations/sd3/sd3_denoise.py index d512fb284f5..eb575611c6e 100644 --- a/invokeai/app/invocations/sd3/sd3_denoise.py +++ b/invokeai/app/invocations/sd3/sd3_denoise.py @@ -159,7 +159,7 @@ def _get_noise( ) -> torch.Tensor: # We always generate noise on the same device and dtype then cast to ensure consistency across devices/dtypes. rand_device = "cpu" - rand_dtype = torch.float16 + rand_dtype = TorchDevice.choose_noise_dtype(torch.float16) return torch.randn( num_samples, diff --git a/invokeai/app/invocations/z_image/z_image_seed_variance_enhancer.py b/invokeai/app/invocations/z_image/z_image_seed_variance_enhancer.py index 72819a966a2..800bb69c2a3 100644 --- a/invokeai/app/invocations/z_image/z_image_seed_variance_enhancer.py +++ b/invokeai/app/invocations/z_image/z_image_seed_variance_enhancer.py @@ -13,6 +13,7 @@ ConditioningFieldData, ZImageConditioningInfo, ) +from invokeai.backend.util.devices import TorchDevice @invocation( @@ -82,8 +83,11 @@ def invoke(self, context: InvocationContext) -> ZImageConditioningOutput: generator = torch.Generator(device=prompt_embeds.device) generator.manual_seed(self.seed) noise = torch.rand( - prompt_embeds.shape, generator=generator, device=prompt_embeds.device, dtype=prompt_embeds.dtype - ) + prompt_embeds.shape, + generator=generator, + device=prompt_embeds.device, + dtype=TorchDevice.choose_noise_dtype(prompt_embeds.dtype), + ).to(prompt_embeds.dtype) noise = noise * 2 - 1 # Scale to [-1, 1) noise = noise * actual_strength diff --git a/invokeai/app/run_app.py b/invokeai/app/run_app.py index 759c246b14c..ca75d1a1f95 100644 --- a/invokeai/app/run_app.py +++ b/invokeai/app/run_app.py @@ -82,6 +82,7 @@ def run_app() -> None: # Import from startup_utils here to avoid importing torch before configure_torch_cuda_allocator() is called. from invokeai.app.util.startup_utils import ( apply_monkeypatches, + check_cuda_build_compatibility, check_cudnn, enable_dev_reload, find_open_port, @@ -100,6 +101,7 @@ def run_app() -> None: apply_monkeypatches() register_mime_types() check_cudnn(logger) + check_cuda_build_compatibility(logger) # Fail here rather than inside a generation: the value is read per generation, so a typo would # otherwise surface as a failed queue item minutes after the server came up. resolve_krea2_sdpa_backends() diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py index f4640c36537..032db938ed3 100644 --- a/invokeai/app/services/config/config_default.py +++ b/invokeai/app/services/config/config_default.py @@ -28,6 +28,7 @@ LEGACY_INIT_FILE = Path("invokeai.init") PRECISION = Literal["auto", "float16", "bfloat16", "float32"] ATTENTION_TYPE = Literal["auto", "normal", "xformers", "sliced", "torch-sdp"] +NOISE_DTYPE = Literal["float32", "float16"] ATTENTION_SLICE_SIZE = Literal["auto", "balanced", "max", 1, 2, 3, 4, 5, 6, 7, 8] LOG_FORMAT = Literal["plain", "color", "syslog", "legacy"] LOG_LEVEL = Literal["debug", "info", "warning", "error", "critical"] @@ -120,6 +121,7 @@ class InvokeAIAppConfig(BaseSettings): device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.
Valid values: `auto`, `cpu`, `cuda`, `mps`, `xpu`, `cuda:N`, `xpu:N` (where N is a device number) precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.
Valid values: `auto`, `float16`, `bfloat16`, `float32` sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements. + noise_dtype: The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there.
Valid values: `float32`, `float16` wan_memory_optimization: Enable experimental Wan memory optimizations at the cost of slower generation. pid_memory_optimization: Enable experimental PiD decode memory optimizations. Roughly halves the peak activation memory of a PiD decode; in exchange the decoded image changes slightly, because neither the chunked pixel pathway nor the float32 sampler intermediates are bit-exact with the default path. attention_type: Attention type.
Valid values: `auto`, `normal`, `xformers`, `sliced`, `torch-sdp` @@ -244,6 +246,7 @@ class InvokeAIAppConfig(BaseSettings): # GENERATION sequential_guidance: bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.") + noise_dtype: NOISE_DTYPE = Field(default="float32", description="The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there.") wan_memory_optimization: bool = Field(default=False, description="Enable experimental Wan memory optimizations at the cost of slower generation.") pid_memory_optimization: bool = Field(default=False, description="Enable experimental PiD decode memory optimizations. Roughly halves the peak activation memory of a PiD decode; in exchange the decoded image changes slightly, because neither the chunked pixel pathway nor the float32 sampler intermediates are bit-exact with the default path.") attention_type: ATTENTION_TYPE = Field(default="auto", description="Attention type.") diff --git a/invokeai/app/util/startup_utils.py b/invokeai/app/util/startup_utils.py index 8a5c49399c0..36c1d08bc2f 100644 --- a/invokeai/app/util/startup_utils.py +++ b/invokeai/app/util/startup_utils.py @@ -1,6 +1,9 @@ +import ctypes import logging import mimetypes +import re import socket +import sys from pathlib import Path import torch @@ -34,6 +37,55 @@ def check_cudnn(logger: logging.Logger) -> None: ) +def nvidia_driver_cuda_version() -> int | None: + """The CUDA version the installed NVIDIA driver supports (12040 for 12.4), or None when there is no driver.""" + try: + driver = ctypes.CDLL("nvcuda.dll" if sys.platform == "win32" else "libcuda.so.1") + except OSError: + return None + version = ctypes.c_int() + try: + if driver.cuDriverGetVersion(ctypes.byref(version)) != 0: + return None + except AttributeError: # a stub library without the driver API + return None + return version.value + + +def check_cuda_build_compatibility(logger: logging.Logger) -> None: + """Name the two ways a CUDA build of torch fails on an NVIDIA machine that torch itself only warns about. + + A driver too old for the build's CUDA version leaves torch without CUDA, so Invoke silently runs on the CPU and + generation looks hung. A GPU older than the build's lowest architecture passes `is_available()` and then fails + at the first kernel launch. + """ + if torch.version.cuda is None or torch.version.hip is not None: + return + if not torch.cuda.is_available(): + driver = nvidia_driver_cuda_version() + major, minor = (int(part) for part in torch.version.cuda.split(".")[:2]) + if driver is not None and driver < major * 1000 + minor * 10: + logger.error( + f"PyTorch here is built for CUDA {torch.version.cuda}, but the NVIDIA driver only supports CUDA " + f"{driver // 1000}.{driver % 1000 // 10}, so Invoke is running on the CPU. Update the NVIDIA driver " + "(R580 or newer for CUDA 13)." + ) + return + # Custom builds may list suffixed targets (sm_90a, sm_100f); a diagnostic must not stop the server over them. + architectures = [int(m.group(1)) for arch in torch.cuda.get_arch_list() if (m := re.match(r"sm_(\d+)", arch))] + if not architectures: + return + lowest = min(architectures) + for index in range(torch.cuda.device_count()): + major, minor = torch.cuda.get_device_capability(index) + if major * 10 + minor < lowest: + logger.error( + f"{torch.cuda.get_device_name(index)} has compute capability {major}.{minor}, but this PyTorch build " + f"supports {lowest // 10}.{lowest % 10} and newer, so generation on it will fail. See the system " + "requirements for the options on older GPUs." + ) + + # The shape the diffusion transformers actually attend over: one image, many heads, head_dim 128. # Availability can depend on the shape, so probing with a toy one would answer a different question. _PROBE_HEADS = 24 diff --git a/invokeai/backend/flux/sampling_utils.py b/invokeai/backend/flux/sampling_utils.py index be81d6458d8..bad1e7084a7 100644 --- a/invokeai/backend/flux/sampling_utils.py +++ b/invokeai/backend/flux/sampling_utils.py @@ -6,6 +6,8 @@ import torch from einops import rearrange, repeat +from invokeai.backend.util.devices import TorchDevice + def get_noise( num_samples: int, @@ -17,7 +19,7 @@ def get_noise( ): # We always generate noise on the same device and dtype then cast to ensure consistency across devices/dtypes. rand_device = "cpu" - rand_dtype = torch.float16 + rand_dtype = TorchDevice.choose_noise_dtype(torch.float16) return torch.randn( num_samples, 16, diff --git a/invokeai/backend/flux2/sampling_utils.py b/invokeai/backend/flux2/sampling_utils.py index 98d69cd04d0..88649603fb7 100644 --- a/invokeai/backend/flux2/sampling_utils.py +++ b/invokeai/backend/flux2/sampling_utils.py @@ -9,6 +9,8 @@ import torch from einops import rearrange +from invokeai.backend.util.devices import TorchDevice + def get_noise_flux2( num_samples: int, @@ -36,7 +38,7 @@ def get_noise_flux2( """ # We always generate noise on the same device and dtype then cast to ensure consistency. rand_device = "cpu" - rand_dtype = torch.float16 + rand_dtype = TorchDevice.choose_noise_dtype(torch.float16) # FLUX.2 uses 32 latent channels # Latent dimensions: height/8, width/8 (from VAE downsampling) diff --git a/invokeai/backend/util/devices.py b/invokeai/backend/util/devices.py index ff2e9da8c9b..ea52050d696 100644 --- a/invokeai/backend/util/devices.py +++ b/invokeai/backend/util/devices.py @@ -162,6 +162,17 @@ def choose_torch_dtype(cls, device: Optional[torch.device] = None) -> torch.dtyp # CPU / safe fallback return cls._to_dtype("float32") + @classmethod + def choose_noise_dtype(cls, legacy_dtype: torch.dtype) -> torch.dtype: + """The dtype to draw seeded noise in on the CPU, for the draws that used to happen in `legacy_dtype`. + + float32 unless `noise_dtype` asks for the old draw. torch's float32 `randn`/`rand` give the same numbers on + every version, but its float16/bfloat16 ones changed after 2.7 (for tensors of 16 or more elements), so a + seed drawn in half precision gives a different image on macOS, which stays on torch 2.7, than on + Windows/Linux. + """ + return legacy_dtype if get_config().noise_dtype == "float16" else torch.float32 + @classmethod def get_device_name(cls, device: torch.device) -> str: """Return the human-readable name for a torch device (e.g. 'AMD Radeon PRO W7900', 'CPU'). diff --git a/invokeai/frontend/web/openapi.json b/invokeai/frontend/web/openapi.json index 7b5d82e2c4a..d231764582e 100644 --- a/invokeai/frontend/web/openapi.json +++ b/invokeai/frontend/web/openapi.json @@ -57736,6 +57736,13 @@ "description": "Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.", "default": false }, + "noise_dtype": { + "type": "string", + "enum": ["float32", "float16"], + "title": "Noise Dtype", + "description": "The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there.", + "default": "float32" + }, "wan_memory_optimization": { "type": "boolean", "title": "Wan Memory Optimization", @@ -58061,7 +58068,7 @@ "additionalProperties": false, "type": "object", "title": "InvokeAIAppConfig", - "description": "Invoke's global app configuration.\n\nTypically, you won't need to interact with this class directly. Instead, use the `get_config` function from `invokeai.app.services.config` to get a singleton config object.\n\nAttributes:\n host: IP address to bind to. Use `0.0.0.0` to serve to your local network.\n port: Port to bind to.\n allow_origins: Allowed CORS origins.\n allow_credentials: Allow CORS credentials.\n allow_methods: Methods allowed for CORS.\n allow_headers: Headers allowed for CORS.\n ssl_certfile: SSL certificate file for HTTPS. See https://www.uvicorn.dev/settings/#https.\n ssl_keyfile: SSL key file for HTTPS. See https://www.uvicorn.dev/settings/#https.\n log_tokenization: Enable logging of parsed prompt tokens.\n patchmatch: Enable patchmatch inpaint code.\n models_dir: Path to the models directory.\n convert_cache_dir: Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).\n download_cache_dir: Path to the directory that contains dynamically downloaded models.\n legacy_conf_dir: Path to directory of legacy checkpoint config files.\n db_dir: Path to InvokeAI databases directory.\n db_synchronous: SQLite durability setting. `full`, the default and what InvokeAI has always used, flushes every commit to disk. `normal` acknowledges commits without waiting for that flush - measured at roughly 12x shorter commits on an SSD - and cannot corrupt the database under WAL, which is why it is refused, with a warning, when WAL is unavailable for the database file. What `normal` gives up is the most recent transactions on a power loss or OS crash: a just-written image record or queue status, not the image file itself.
Valid values: `full`, `normal`\n outputs_dir: Path to directory for outputs.\n image_subfolder_strategy: Strategy for organizing images into subfolders. 'flat' stores all images in a single folder. 'date' organizes by YYYY/MM/DD. 'type' organizes by image category. 'hash' uses first 2 characters of UUID for filesystem performance.
Valid values: `flat`, `date`, `type`, `hash`\n custom_nodes_dir: Path to directory for custom nodes.\n style_presets_dir: Path to directory for style presets.\n workflow_thumbnails_dir: Path to directory for workflow thumbnails.\n log_handlers: Log handler. Valid options are \"console\", \"file=\", \"syslog=path|address:host:port\", \"http=\".\n log_format: Log format. Use \"plain\" for text-only, \"color\" for colorized output, \"legacy\" for 2.3-style logging and \"syslog\" for syslog-style.
Valid values: `plain`, `color`, `syslog`, `legacy`\n log_level: Emit logging messages at this level or higher.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n log_sql: Log SQL queries. `log_level` must be `debug` for this to do anything. Extremely verbose.\n log_level_network: Log level for network-related messages. 'info' and 'debug' are very verbose.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n use_memory_db: Use in-memory database. Useful for development.\n dev_reload: Automatically reload when Python sources are changed. Does not reload node definitions.\n profile_graphs: Enable graph profiling using `cProfile`.\n profile_prefix: An optional prefix for profile output files.\n profiles_dir: Path to profiles output directory.\n max_cache_ram_gb: The maximum amount of CPU RAM to use for model caching in GB. If unset, the limit will be configured based on the available RAM. In most cases, it is recommended to leave this unset.\n max_cache_vram_gb: The amount of VRAM to use for model caching in GB. If unset, the limit will be configured based on the available VRAM and the device_working_mem_gb. In most cases, it is recommended to leave this unset.\n log_memory_usage: If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.\n model_cache_keep_alive_min: How long to keep models in cache after last use, in minutes. A value of 0 (the default) means models are kept in cache indefinitely. If no model generations occur within the timeout period, the model cache is cleared using the same logic as the 'Clear Model Cache' button.\n device_working_mem_gb: The amount of working memory to keep available on the compute device (in GB). Has no effect if running on CPU. If you are experiencing OOM errors, try increasing this value.\n enable_partial_loading: Enable partial loading of models. This enables models to run with reduced VRAM requirements (at the cost of slower speed) by streaming the model from RAM to VRAM as its used. In some edge cases, partial loading can cause models to run more slowly if they were previously being fully loaded into VRAM.\n keep_ram_copy_of_weights: Whether to keep a full RAM copy of a model's weights when the model is loaded in VRAM. Keeping a RAM copy increases average RAM usage, but speeds up model switching and LoRA patching (assuming there is sufficient RAM). Set this to False if RAM pressure is consistently high.\n fp8_compute: Keep ComfyUI 'scaled fp8' checkpoints quantized instead of dequantizing them at load, and run their matmuls on the fp8 tensor cores (requires an Ada/SM 8.9 or newer NVIDIA GPU; falls back automatically otherwise). Roughly halves the transformer's VRAM and speeds up denoising, but quantizes activations as well, so images will differ from previous versions at the same seed. Reproducibility also requires the model to be FULLY resident in VRAM: a layer whose weights are still in RAM falls back to the dequantized path, and since which layers are resident shifts from run to run, the same seed then yields visibly different images. For repeatable output, ensure the model loads at 100% (e.g. enable_partial_loading=false with enough free VRAM).\n fp8_compute_full_precision_hints: Honor the per-layer 'full_precision_matrix_mult' flags that some scaled-fp8 checkpoints ship. Those layers then dequantize on every forward instead of using the fp8 tensor cores, which can cost a large part of the fp8_compute speedup - on checkpoints that mark many layers, most of it. Set to false to run every quantized layer on the fp8 tensor cores, ignoring the producer's instruction; faster, but the marked layers were flagged as numerically sensitive, so quality may suffer. Only has an effect when fp8_compute is enabled.\n ram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_ram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n vram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_vram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n lazy_offload: DEPRECATED: This setting is no longer used. Lazy-offloading is enabled by default. This config setting will be removed once the new model cache behavior is stable.\n pytorch_cuda_alloc_conf: Configure the Torch CUDA memory allocator. This will impact peak reserved VRAM usage and performance. Setting to \"backend:cudaMallocAsync\" works well on many systems. The optimal configuration is highly dependent on the system configuration (device type, VRAM, CUDA driver version, etc.), so must be tuned experimentally.\n device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.
Valid values: `auto`, `cpu`, `cuda`, `mps`, `xpu`, `cuda:N`, `xpu:N` (where N is a device number)\n precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.
Valid values: `auto`, `float16`, `bfloat16`, `float32`\n sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.\n wan_memory_optimization: Enable experimental Wan memory optimizations at the cost of slower generation.\n pid_memory_optimization: Enable experimental PiD decode memory optimizations. Roughly halves the peak activation memory of a PiD decode; in exchange the decoded image changes slightly, because neither the chunked pixel pathway nor the float32 sampler intermediates are bit-exact with the default path.\n attention_type: Attention type.
Valid values: `auto`, `normal`, `xformers`, `sliced`, `torch-sdp`\n attention_slice_size: Slice size, valid when attention_type==\"sliced\".
Valid values: `auto`, `balanced`, `max`, `1`, `2`, `3`, `4`, `5`, `6`, `7`, `8`\n force_tiled_decode: Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty). A tiled decode is not pixel-identical to a single-pass one: a VAE decoder normalises and attends over the whole image, so the difference is spread across it rather than confined to the tile seams. As of this release the setting also applies to FLUX.1, which previously ignored it.\n pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.\n max_queue_size: Maximum number of items in the session queue.\n session_queue_mode: Session queue mode. Use 'FIFO' for traditional first-in-first-out, or 'round_robin' to serve each user's jobs in turn. In single-user mode, FIFO is always used regardless of this setting.
Valid values: `FIFO`, `round_robin`\n clear_queue_on_startup: Empties session queue on startup. If true, disables `max_queue_history`.\n max_queue_history: Keep the last N completed, failed, and canceled queue items. Older items are deleted on startup. Set to 0 to prune all terminal items. Ignored if `clear_queue_on_startup` is true.\n allow_nodes: List of nodes to allow. Omit to allow all.\n deny_nodes: List of nodes to deny. Omit to deny none.\n node_cache_size: How many cached nodes to keep in memory.\n hashing_algorithm: Model hashing algorthim for model installs. 'blake3_multi' is best for SSDs. 'blake3_single' is best for spinning disk HDDs. 'random' disables hashing, instead assigning a UUID to models. Useful when using a memory db to reduce model installation time, or if you don't care about storing stable hashes for models. Alternatively, any other hashlib algorithm is accepted, though these are not nearly as performant as blake3.
Valid values: `blake3_multi`, `blake3_single`, `random`, `md5`, `sha1`, `sha224`, `sha256`, `sha384`, `sha512`, `blake2b`, `blake2s`, `sha3_224`, `sha3_256`, `sha3_384`, `sha3_512`, `shake_128`, `shake_256`\n remote_api_tokens: List of regular expression and token pairs used when downloading models from URLs. The download URL is tested against the regex, and if it matches, the token is provided in as a Bearer token.\n scan_models_on_startup: Scan the models directory on startup, registering orphaned models. This is typically only used in conjunction with `use_memory_db` for testing purposes.\n allow_private_download_urls: Allow the download queue to fetch from loopback, link-local and private-network addresses. Disabled by default so that a download URL cannot be used to reach services that are only reachable from the server. Enable this only if you install models from a mirror on your own network.\n download_proxy: Optional HTTP proxy for model downloads. The proxy must enforce the public-address policy because proxy-side DNS cannot be checked by InvokeAI.\n unsafe_disable_picklescan: UNSAFE. Disable the picklescan security check during model installation. Recommended only for development and testing purposes. This will allow arbitrary code execution during model installation, so should never be used in production.\n allow_unknown_models: Allow installation of models that we are unable to identify. If enabled, models will be marked as `unknown` in the database, and will not have any metadata associated with them. If disabled, unknown models will be rejected during installation.\n multiuser: Enable multiuser support. When disabled, the application runs in single-user mode using a default system account with administrator privileges. When enabled, requires user authentication and authorization.\n strict_password_checking: Enforce strict password requirements. When True, passwords must contain uppercase, lowercase, and numbers. When False (default), any password is accepted but its strength (weak/moderate/strong) is reported to the user.\n image_index_enabled: Maintain a semantic embedding index of gallery images and videos, used by the image map and semantic search features.\n image_index_model: Name of the installed CLIP Vision or SigLIP model used to embed gallery images and video thumbnails. Changing the model discards embeddings computed by the previous model.\n image_index_device: Set to `cpu` to compute image embeddings on the CPU with a service-local copy of the model - avoids VRAM use and lets indexing run during generations. Any other value is ignored: embeddings otherwise run on the model cache's device, pausing while generations are in progress.\n image_index_batch_size: Number of gallery items embedded per batch by the image index worker.\n external_alibabacloud_api_key: API key for Alibaba Cloud DashScope image generation.\n external_alibabacloud_base_url: Base URL override for Alibaba Cloud DashScope image generation.\n external_gemini_api_key: API key for Gemini image generation.\n external_openai_api_key: API key for OpenAI image generation.\n external_gemini_base_url: Base URL override for Gemini image generation.\n external_openai_base_url: Base URL override for OpenAI image generation.\n external_seedream_api_key: API key for Seedream image generation.\n external_seedream_base_url: Base URL override for Seedream image generation.\n base_url: Public base path when running behind a reverse proxy under a sub-path, e.g. `/invoke`. Set only when the proxy PRESERVES the sub-path (the backend receives `/invoke/api/...`). Leave unset when the proxy strips the sub-path or when serving at the domain root.\n forwarded_allow_ips: Comma-separated list of IPs (or `*`) allowed to set X-Forwarded-* headers. Set to the reverse proxy's IP. Only used when `base_url` is set.\n http_compression_level: Compression level for gzipped HTTP API responses. 0 disables response compression entirely, 1 is fastest, 9 (the default) is smallest. Compression runs on the event loop and blocks the whole server while it works, and level 9 costs about 5.5x the time of level 1 for 0.4 percentage points of extra compression, so lowering this makes the app noticeably more responsive on large libraries. Set to 0 when a reverse proxy already compresses responses." + "description": "Invoke's global app configuration.\n\nTypically, you won't need to interact with this class directly. Instead, use the `get_config` function from `invokeai.app.services.config` to get a singleton config object.\n\nAttributes:\n host: IP address to bind to. Use `0.0.0.0` to serve to your local network.\n port: Port to bind to.\n allow_origins: Allowed CORS origins.\n allow_credentials: Allow CORS credentials.\n allow_methods: Methods allowed for CORS.\n allow_headers: Headers allowed for CORS.\n ssl_certfile: SSL certificate file for HTTPS. See https://www.uvicorn.dev/settings/#https.\n ssl_keyfile: SSL key file for HTTPS. See https://www.uvicorn.dev/settings/#https.\n log_tokenization: Enable logging of parsed prompt tokens.\n patchmatch: Enable patchmatch inpaint code.\n models_dir: Path to the models directory.\n convert_cache_dir: Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).\n download_cache_dir: Path to the directory that contains dynamically downloaded models.\n legacy_conf_dir: Path to directory of legacy checkpoint config files.\n db_dir: Path to InvokeAI databases directory.\n db_synchronous: SQLite durability setting. `full`, the default and what InvokeAI has always used, flushes every commit to disk. `normal` acknowledges commits without waiting for that flush - measured at roughly 12x shorter commits on an SSD - and cannot corrupt the database under WAL, which is why it is refused, with a warning, when WAL is unavailable for the database file. What `normal` gives up is the most recent transactions on a power loss or OS crash: a just-written image record or queue status, not the image file itself.
Valid values: `full`, `normal`\n outputs_dir: Path to directory for outputs.\n image_subfolder_strategy: Strategy for organizing images into subfolders. 'flat' stores all images in a single folder. 'date' organizes by YYYY/MM/DD. 'type' organizes by image category. 'hash' uses first 2 characters of UUID for filesystem performance.
Valid values: `flat`, `date`, `type`, `hash`\n custom_nodes_dir: Path to directory for custom nodes.\n style_presets_dir: Path to directory for style presets.\n workflow_thumbnails_dir: Path to directory for workflow thumbnails.\n log_handlers: Log handler. Valid options are \"console\", \"file=\", \"syslog=path|address:host:port\", \"http=\".\n log_format: Log format. Use \"plain\" for text-only, \"color\" for colorized output, \"legacy\" for 2.3-style logging and \"syslog\" for syslog-style.
Valid values: `plain`, `color`, `syslog`, `legacy`\n log_level: Emit logging messages at this level or higher.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n log_sql: Log SQL queries. `log_level` must be `debug` for this to do anything. Extremely verbose.\n log_level_network: Log level for network-related messages. 'info' and 'debug' are very verbose.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n use_memory_db: Use in-memory database. Useful for development.\n dev_reload: Automatically reload when Python sources are changed. Does not reload node definitions.\n profile_graphs: Enable graph profiling using `cProfile`.\n profile_prefix: An optional prefix for profile output files.\n profiles_dir: Path to profiles output directory.\n max_cache_ram_gb: The maximum amount of CPU RAM to use for model caching in GB. If unset, the limit will be configured based on the available RAM. In most cases, it is recommended to leave this unset.\n max_cache_vram_gb: The amount of VRAM to use for model caching in GB. If unset, the limit will be configured based on the available VRAM and the device_working_mem_gb. In most cases, it is recommended to leave this unset.\n log_memory_usage: If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.\n model_cache_keep_alive_min: How long to keep models in cache after last use, in minutes. A value of 0 (the default) means models are kept in cache indefinitely. If no model generations occur within the timeout period, the model cache is cleared using the same logic as the 'Clear Model Cache' button.\n device_working_mem_gb: The amount of working memory to keep available on the compute device (in GB). Has no effect if running on CPU. If you are experiencing OOM errors, try increasing this value.\n enable_partial_loading: Enable partial loading of models. This enables models to run with reduced VRAM requirements (at the cost of slower speed) by streaming the model from RAM to VRAM as its used. In some edge cases, partial loading can cause models to run more slowly if they were previously being fully loaded into VRAM.\n keep_ram_copy_of_weights: Whether to keep a full RAM copy of a model's weights when the model is loaded in VRAM. Keeping a RAM copy increases average RAM usage, but speeds up model switching and LoRA patching (assuming there is sufficient RAM). Set this to False if RAM pressure is consistently high.\n fp8_compute: Keep ComfyUI 'scaled fp8' checkpoints quantized instead of dequantizing them at load, and run their matmuls on the fp8 tensor cores (requires an Ada/SM 8.9 or newer NVIDIA GPU; falls back automatically otherwise). Roughly halves the transformer's VRAM and speeds up denoising, but quantizes activations as well, so images will differ from previous versions at the same seed. Reproducibility also requires the model to be FULLY resident in VRAM: a layer whose weights are still in RAM falls back to the dequantized path, and since which layers are resident shifts from run to run, the same seed then yields visibly different images. For repeatable output, ensure the model loads at 100% (e.g. enable_partial_loading=false with enough free VRAM).\n fp8_compute_full_precision_hints: Honor the per-layer 'full_precision_matrix_mult' flags that some scaled-fp8 checkpoints ship. Those layers then dequantize on every forward instead of using the fp8 tensor cores, which can cost a large part of the fp8_compute speedup - on checkpoints that mark many layers, most of it. Set to false to run every quantized layer on the fp8 tensor cores, ignoring the producer's instruction; faster, but the marked layers were flagged as numerically sensitive, so quality may suffer. Only has an effect when fp8_compute is enabled.\n ram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_ram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n vram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_vram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n lazy_offload: DEPRECATED: This setting is no longer used. Lazy-offloading is enabled by default. This config setting will be removed once the new model cache behavior is stable.\n pytorch_cuda_alloc_conf: Configure the Torch CUDA memory allocator. This will impact peak reserved VRAM usage and performance. Setting to \"backend:cudaMallocAsync\" works well on many systems. The optimal configuration is highly dependent on the system configuration (device type, VRAM, CUDA driver version, etc.), so must be tuned experimentally.\n device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.
Valid values: `auto`, `cpu`, `cuda`, `mps`, `xpu`, `cuda:N`, `xpu:N` (where N is a device number)\n precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.
Valid values: `auto`, `float16`, `bfloat16`, `float32`\n sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.\n noise_dtype: The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there.
Valid values: `float32`, `float16`\n wan_memory_optimization: Enable experimental Wan memory optimizations at the cost of slower generation.\n pid_memory_optimization: Enable experimental PiD decode memory optimizations. Roughly halves the peak activation memory of a PiD decode; in exchange the decoded image changes slightly, because neither the chunked pixel pathway nor the float32 sampler intermediates are bit-exact with the default path.\n attention_type: Attention type.
Valid values: `auto`, `normal`, `xformers`, `sliced`, `torch-sdp`\n attention_slice_size: Slice size, valid when attention_type==\"sliced\".
Valid values: `auto`, `balanced`, `max`, `1`, `2`, `3`, `4`, `5`, `6`, `7`, `8`\n force_tiled_decode: Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty). A tiled decode is not pixel-identical to a single-pass one: a VAE decoder normalises and attends over the whole image, so the difference is spread across it rather than confined to the tile seams. As of this release the setting also applies to FLUX.1, which previously ignored it.\n pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.\n max_queue_size: Maximum number of items in the session queue.\n session_queue_mode: Session queue mode. Use 'FIFO' for traditional first-in-first-out, or 'round_robin' to serve each user's jobs in turn. In single-user mode, FIFO is always used regardless of this setting.
Valid values: `FIFO`, `round_robin`\n clear_queue_on_startup: Empties session queue on startup. If true, disables `max_queue_history`.\n max_queue_history: Keep the last N completed, failed, and canceled queue items. Older items are deleted on startup. Set to 0 to prune all terminal items. Ignored if `clear_queue_on_startup` is true.\n allow_nodes: List of nodes to allow. Omit to allow all.\n deny_nodes: List of nodes to deny. Omit to deny none.\n node_cache_size: How many cached nodes to keep in memory.\n hashing_algorithm: Model hashing algorthim for model installs. 'blake3_multi' is best for SSDs. 'blake3_single' is best for spinning disk HDDs. 'random' disables hashing, instead assigning a UUID to models. Useful when using a memory db to reduce model installation time, or if you don't care about storing stable hashes for models. Alternatively, any other hashlib algorithm is accepted, though these are not nearly as performant as blake3.
Valid values: `blake3_multi`, `blake3_single`, `random`, `md5`, `sha1`, `sha224`, `sha256`, `sha384`, `sha512`, `blake2b`, `blake2s`, `sha3_224`, `sha3_256`, `sha3_384`, `sha3_512`, `shake_128`, `shake_256`\n remote_api_tokens: List of regular expression and token pairs used when downloading models from URLs. The download URL is tested against the regex, and if it matches, the token is provided in as a Bearer token.\n scan_models_on_startup: Scan the models directory on startup, registering orphaned models. This is typically only used in conjunction with `use_memory_db` for testing purposes.\n allow_private_download_urls: Allow the download queue to fetch from loopback, link-local and private-network addresses. Disabled by default so that a download URL cannot be used to reach services that are only reachable from the server. Enable this only if you install models from a mirror on your own network.\n download_proxy: Optional HTTP proxy for model downloads. The proxy must enforce the public-address policy because proxy-side DNS cannot be checked by InvokeAI.\n unsafe_disable_picklescan: UNSAFE. Disable the picklescan security check during model installation. Recommended only for development and testing purposes. This will allow arbitrary code execution during model installation, so should never be used in production.\n allow_unknown_models: Allow installation of models that we are unable to identify. If enabled, models will be marked as `unknown` in the database, and will not have any metadata associated with them. If disabled, unknown models will be rejected during installation.\n multiuser: Enable multiuser support. When disabled, the application runs in single-user mode using a default system account with administrator privileges. When enabled, requires user authentication and authorization.\n strict_password_checking: Enforce strict password requirements. When True, passwords must contain uppercase, lowercase, and numbers. When False (default), any password is accepted but its strength (weak/moderate/strong) is reported to the user.\n image_index_enabled: Maintain a semantic embedding index of gallery images and videos, used by the image map and semantic search features.\n image_index_model: Name of the installed CLIP Vision or SigLIP model used to embed gallery images and video thumbnails. Changing the model discards embeddings computed by the previous model.\n image_index_device: Set to `cpu` to compute image embeddings on the CPU with a service-local copy of the model - avoids VRAM use and lets indexing run during generations. Any other value is ignored: embeddings otherwise run on the model cache's device, pausing while generations are in progress.\n image_index_batch_size: Number of gallery items embedded per batch by the image index worker.\n external_alibabacloud_api_key: API key for Alibaba Cloud DashScope image generation.\n external_alibabacloud_base_url: Base URL override for Alibaba Cloud DashScope image generation.\n external_gemini_api_key: API key for Gemini image generation.\n external_openai_api_key: API key for OpenAI image generation.\n external_gemini_base_url: Base URL override for Gemini image generation.\n external_openai_base_url: Base URL override for OpenAI image generation.\n external_seedream_api_key: API key for Seedream image generation.\n external_seedream_base_url: Base URL override for Seedream image generation.\n base_url: Public base path when running behind a reverse proxy under a sub-path, e.g. `/invoke`. Set only when the proxy PRESERVES the sub-path (the backend receives `/invoke/api/...`). Leave unset when the proxy strips the sub-path or when serving at the domain root.\n forwarded_allow_ips: Comma-separated list of IPs (or `*`) allowed to set X-Forwarded-* headers. Set to the reverse proxy's IP. Only used when `base_url` is set.\n http_compression_level: Compression level for gzipped HTTP API responses. 0 disables response compression entirely, 1 is fastest, 9 (the default) is smallest. Compression runs on the event loop and blocks the whole server while it works, and level 9 costs about 5.5x the time of level 1 for 0.4 percentage points of extra compression, so lowering this makes the app noticeably more responsive on large libraries. Set to 0 when a reverse proxy already compresses responses." }, "InvokeAIAppConfigWithSetFields": { "properties": { diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts index 508a31ce75b..cd41cd678aa 100644 --- a/invokeai/frontend/web/src/services/api/schema.ts +++ b/invokeai/frontend/web/src/services/api/schema.ts @@ -22126,6 +22126,7 @@ export type components = { * device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.
Valid values: `auto`, `cpu`, `cuda`, `mps`, `xpu`, `cuda:N`, `xpu:N` (where N is a device number) * precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.
Valid values: `auto`, `float16`, `bfloat16`, `float32` * sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements. + * noise_dtype: The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there.
Valid values: `float32`, `float16` * wan_memory_optimization: Enable experimental Wan memory optimizations at the cost of slower generation. * pid_memory_optimization: Enable experimental PiD decode memory optimizations. Roughly halves the peak activation memory of a PiD decode; in exchange the decoded image changes slightly, because neither the chunked pixel pathway nor the float32 sampler intermediates are bit-exact with the default path. * attention_type: Attention type.
Valid values: `auto`, `normal`, `xformers`, `sliced`, `torch-sdp` @@ -22527,6 +22528,13 @@ export type components = { * @default false */ sequential_guidance?: boolean; + /** + * Noise Dtype + * @description The dtype seeded noise is drawn in for SD1.5/SDXL, SD3, FLUX.1, FLUX.2, CogView4 and the Z-Image seed variance enhancer. `float32` draws the same noise on every platform. `float16` is the half-precision draw of earlier versions: on macOS it keeps the images your seeds gave before this update; on Windows and Linux both values give (nearly) the same images, and images made before the update cannot be reproduced there. + * @default float32 + * @enum {string} + */ + noise_dtype?: "float32" | "float16"; /** * Wan Memory Optimization * @description Enable experimental Wan memory optimizations at the cost of slower generation. diff --git a/pins.json b/pins.json index 4450e732b35..254c7da6d6c 100644 --- a/pins.json +++ b/pins.json @@ -3,13 +3,13 @@ "torchIndexUrl": { "win32": { "cpu": "https://download.pytorch.org/whl/cpu", - "cuda": "https://download.pytorch.org/whl/cu128", + "cuda": "https://download.pytorch.org/whl/cu130", "xpu": "https://download.pytorch.org/whl/xpu" }, "linux": { "cpu": "https://download.pytorch.org/whl/cpu", "rocm": "https://download.pytorch.org/whl/rocm7.2", - "cuda": "https://download.pytorch.org/whl/cu128", + "cuda": "https://download.pytorch.org/whl/cu130", "xpu": "https://download.pytorch.org/whl/xpu" }, "darwin": {} diff --git a/pyproject.toml b/pyproject.toml index f47cf69ca36..feac0ddabaf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,8 +52,9 @@ dependencies = [ "sentencepiece==0.2.0", # 0.2.1 coredumps windows when loading t5 tokenizer "spandrel", # Loosely pinned, will respect requirement of `diffusers[torch]`. Split by platform: linux/win allow - # >=2.10 so the rocm extra can use torch 2.13.0+rocm7.2, while macOS stays on 2.7.x — newer macOS torch - # wheels exercise MPS on CI runners (no usable Metal GPU) and fail with MPS OOM. + # the 2.13 line every backend extra pins (the lock itself is held there by `constraint-dependencies` in + # [tool.uv]), while macOS stays on 2.7.x — newer macOS torch wheels exercise MPS on CI runners (no + # usable Metal GPU) and fail with MPS OOM. # Deliberately NOT capped below 2.12 here. torch 2.12.x+rocm7.1 was reported to break generation (#9410), # but this range is what every backend-agnostic install resolves against — manual installs use # `--torch-backend=` with no extra (see docs/start-here/manual), so a blanket cap would also @@ -124,29 +125,33 @@ dependencies = [ # torch 2.4+cu carries its own triton dependency ] -# The +cpu/+cu128/+rocm7.2 pins live on PyTorch's WHL indexes. torchvision has no -# linux_aarch64 wheels there (torch does for +cpu/+cu128), so on linux_aarch64 these -# pins are unsatisfiable and are gated behind a marker that excludes only that -# platform; every other platform (Windows, macOS, Linux x86_64) is unaffected. On -# linux_aarch64 the base `torch` / `torchvision` declarations resolve from PyPI -# instead (CPU-only wheels — an aarch64 install requesting `cuda` gets CPU torch). -# Since torch+cu128 aarch64 wheels DO exist on the index, real CUDA-on-aarch64 -# (e.g. Grace/GH200) is feasible later with a torchvision-specific workaround. +# The +cpu/+cu130/+rocm7.2 pins live on PyTorch's WHL indexes and are gated to the +# platforms the project resolves and tests them on: Windows and Linux x86_64 (rocm: Linux +# only). macOS is capped below torch 2.8 (see the base requirement), and linux_aarch64 stays +# on the CPU-only PyPI 2.7.1 it was set up with (an aarch64 install requesting `cuda` gets +# CPU torch), so both fall back to the base `torch` / `torchvision` from PyPI. The index has +# carried aarch64 torchvision since 0.28, so moving aarch64 onto the pinned pairs -- and real +# CUDA-on-aarch64 (e.g. Grace/GH200) -- is open, just untested. +# +# cu130 builds cover compute capability 7.5 and newer (Turing through Blackwell) and need +# an NVIDIA driver from the R580 series or newer. CUDA 13 cannot build for Maxwell, Pascal +# or Volta; the cu126 builds that still can have no Blackwell kernels, and cu128 stops at +# torch 2.11. "cpu" = [ - "torch==2.7.1+cpu; sys_platform != 'linux' or platform_machine != 'aarch64'", - "torchvision==0.22.1+cpu; sys_platform != 'linux' or platform_machine != 'aarch64'", - # linux_aarch64 fallback: same versions, resolved from PyPI. Without these - # explicit entries the extra's conflict-universe would contain no torch at all - # on aarch64 (uv partitions the base declarations into the no-extra universe). - "torch==2.7.1; sys_platform == 'linux' and platform_machine == 'aarch64'", - "torchvision==0.22.1; sys_platform == 'linux' and platform_machine == 'aarch64'", + "torch==2.13.0+cpu; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", + "torchvision==0.28.0+cpu; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", + # macOS / linux_aarch64 fallback, resolved from PyPI. Without these explicit entries + # the extra's conflict-universe would contain no torch at all there (uv partitions + # the base declarations into the no-extra universe). + "torch==2.7.1; sys_platform == 'darwin' or (sys_platform == 'linux' and platform_machine == 'aarch64')", + "torchvision==0.22.1; sys_platform == 'darwin' or (sys_platform == 'linux' and platform_machine == 'aarch64')", ] "cuda" = [ - "torch==2.7.1+cu128; sys_platform != 'linux' or platform_machine != 'aarch64'", - "torchvision==0.22.1+cu128; sys_platform != 'linux' or platform_machine != 'aarch64'", - # linux_aarch64 fallback, see note under "cpu" - "torch==2.7.1; sys_platform == 'linux' and platform_machine == 'aarch64'", - "torchvision==0.22.1; sys_platform == 'linux' and platform_machine == 'aarch64'", + "torch==2.13.0+cu130; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", + "torchvision==0.28.0+cu130; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", + # macOS / linux_aarch64 fallback, see note under "cpu" + "torch==2.7.1; sys_platform == 'darwin' or (sys_platform == 'linux' and platform_machine == 'aarch64')", + "torchvision==0.22.1; sys_platform == 'darwin' or (sys_platform == 'linux' and platform_machine == 'aarch64')", ] "rocm" = [ # ROCm wheels are x86_64-linux-only; gate by platform so macOS/win/linux-aarch64 resolution is unaffected. @@ -164,10 +169,9 @@ dependencies = [ # windows-amd64 on PyTorch's WHL index. Gate the +xpu pins to those platforms; the # Intel oneAPI runtime libs (intel-sycl-rt, etc.) come in automatically as deps of # torch+xpu. -# Pinned ahead of the cpu/cuda extras (2.7.1), as the rocm extra already is. Intel's XPU -# backend matured considerably after 2.7.1: torch.xpu.mem_get_info() works on driver/kernel -# combinations where it previously raised, and the bundled oneAPI runtime ships with the wheel -# (intel-sycl-rt), so upgrading torch upgrades the user-space runtime too. +# Intel's XPU backend matured considerably after 2.7.1: torch.xpu.mem_get_info() works on +# driver/kernel combinations where it previously raised, and the bundled oneAPI runtime ships +# with the wheel (intel-sycl-rt), so upgrading torch upgrades the user-space runtime too. "xpu" = [ "torch==2.13.0+xpu; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", "torchvision==0.28.0+xpu; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", @@ -175,9 +179,7 @@ dependencies = [ # Renamed from pytorch-triton-xpu to triton-xpu upstream. "triton-xpu==3.7.2; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'", # macOS / linux_aarch64 have no +xpu wheels: fall back to base torch so the extra's - # conflict-universe always contains a torch. See note under "cpu". These stay on 2.7.1 to - # match the other extras and the project's `torch<2.8.0` constraint on darwin -- only the - # +xpu wheels above move. + # conflict-universe always contains a torch. See note under "cpu". "torch==2.7.1; sys_platform == 'darwin' or (sys_platform == 'linux' and platform_machine == 'aarch64')", "torchvision==0.22.1; sys_platform == 'darwin' or (sys_platform == 'linux' and platform_machine == 'aarch64')", ] @@ -213,6 +215,16 @@ index-strategy = "unsafe-best-match" # and macOS. (ROCm and the PyTorch WHL-index pins are x86_64-only; on aarch64 # Linux torch/torchvision fall back to PyPI via the markers below.) environments = ["sys_platform == 'win32' or sys_platform == 'darwin' or (sys_platform == 'linux' and (platform_machine == 'x86_64' or platform_machine == 'aarch64'))"] +# Hold every resolution on Windows and Linux x86_64 to the torch the backend extras pin -- including the +# no-extra one, which is what CI installs and tests. Without this the lock is free to keep an older torch +# there, or move it to the newest PyPI release, independently of the extras. `tool.uv` never reaches the +# published metadata, so installing the released package with `--torch-backend` keeps the open range of the base +# requirement; only `uv pip install` inside a checkout is held to it. +# `==2.13.0` also matches the local builds (+cpu, +cu130, +rocm7.2, +xpu). +constraint-dependencies = [ + "torch==2.13.0; sys_platform == 'win32' or (sys_platform == 'linux' and platform_machine == 'x86_64')", + "torchvision==0.28.0; sys_platform == 'win32' or (sys_platform == 'linux' and platform_machine == 'x86_64')", +] # compel, could you please not pull in all of Jupyter. (compel declares `notebook>=6.5.7` but does not # reference IPython/Jupyter anywhere in its code.) Dropping it takes ~65 packages out of the environment. @@ -227,20 +239,18 @@ environments = ["sys_platform == 'win32' or sys_platform == 'darwin' or (sys_pla exclude-dependencies = ["notebook"] [tool.uv.sources] -# Exclude linux_aarch64 from the PyTorch WHL indexes so that uv resolves torch / -# torchvision from PyPI on that platform. The indexes DO carry aarch64 torch wheels -# (+cpu/+cu128), but no aarch64 torchvision wheels, so the pinned pairs cannot -# resolve there. All other platforms (Windows, macOS, Linux x86_64) are unaffected. +# Keep linux_aarch64 (and, for cpu/cuda, macOS) off the PyTorch WHL indexes so that uv +# resolves their 2.7.1 fallback pins from PyPI; see the note above the extras. torch = [ - { index = "torch-cpu", extra = "cpu", marker = "sys_platform != 'linux' or platform_machine != 'aarch64'" }, - { index = "torch-cuda", extra = "cuda", marker = "sys_platform != 'linux' or platform_machine != 'aarch64'" }, + { index = "torch-cpu", extra = "cpu", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, + { index = "torch-cuda", extra = "cuda", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, { index = "torch-rocm", extra = "rocm", marker = "sys_platform != 'linux' or platform_machine != 'aarch64'" }, { index = "torch-xpu", extra = "xpu", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, { index = "pypi", marker = "sys_platform == 'linux' and platform_machine == 'aarch64'" }, ] torchvision = [ - { index = "torch-cpu", extra = "cpu", marker = "sys_platform != 'linux' or platform_machine != 'aarch64'" }, - { index = "torch-cuda", extra = "cuda", marker = "sys_platform != 'linux' or platform_machine != 'aarch64'" }, + { index = "torch-cpu", extra = "cpu", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, + { index = "torch-cuda", extra = "cuda", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, { index = "torch-rocm", extra = "rocm", marker = "sys_platform != 'linux' or platform_machine != 'aarch64'" }, { index = "torch-xpu", extra = "xpu", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, { index = "pypi", marker = "sys_platform == 'linux' and platform_machine == 'aarch64'" }, @@ -248,6 +258,13 @@ torchvision = [ triton-rocm = [ { index = "torch-rocm", marker = "sys_platform == 'linux' and platform_machine != 'aarch64'" }, ] +# PyPI's xformers wheels are built against CUDA 12.8 and cannot load their extension next to a CUDA 13 torch (every +# memory-efficient attention call then fails); PyTorch's cu130 index carries the CUDA 13 build of the same release. +# Not scoped to the `cuda` extra: uv only allows that for packages the extra itself lists, and the CUDA 13 torch that +# PyPI serves on Linux needs the same build. The cpu/rocm/xpu builds cannot use xformers' CUDA kernels either way. +xformers = [ + { index = "torch-cuda", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, +] triton-xpu = [ { index = "torch-xpu", marker = "(sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'win32'" }, ] @@ -263,7 +280,7 @@ explicit = true [[tool.uv.index]] name = "torch-cuda" -url = "https://download.pytorch.org/whl/cu128" +url = "https://download.pytorch.org/whl/cu130" explicit = true [[tool.uv.index]] diff --git a/scripts/check_aarch64_lock.py b/scripts/check_aarch64_lock.py index 8ed86ae400b..6de8716bb70 100644 --- a/scripts/check_aarch64_lock.py +++ b/scripts/check_aarch64_lock.py @@ -1,7 +1,7 @@ """Assert that `uv.lock` gives linux/aarch64 an installable torch and torchvision. Nothing else in CI covers aarch64. Three separate mechanisms in `pyproject.toml` conspire to make torch -resolve from PyPI there instead of from the PyTorch WHL indexes (which ship no aarch64 torchvision wheel): +resolve from PyPI there instead of from the PyTorch WHL indexes (whose pinned pairs had no aarch64 torchvision wheel): `tool.uv.environments`, the `[tool.uv.sources]` platform markers, and the aarch64 fallback pins in each torch extra. Break the sources markers and `uv lock` fails loudly, but break either of the other two and the lockfile simply stops mentioning torch on aarch64 while `uv lock --locked` stays green -- which is how @@ -65,7 +65,7 @@ def has_aarch64_wheel(package: dict[str, Any], python_version: str) -> bool: minor = int(python_version.split(".")[1]) accepted = {f"cp3{minor}", "py3", f"py3{minor}"} for wheel in package.get("wheels", []): - # The PyTorch WHL indexes percent-encode the `+` of local versions in wheel URLs (`torch-2.7.1%2Bcpu-...`). + # The PyTorch WHL indexes percent-encode the `+` of local versions in wheel URLs (`torch-2.13.0%2Bcpu-...`). filename = unquote(wheel.get("url", wheel.get("path", "")).rsplit("/", 1)[-1]) if not filename.endswith(".whl"): continue diff --git a/tests/app/util/test_cuda_build_compatibility.py b/tests/app/util/test_cuda_build_compatibility.py new file mode 100644 index 00000000000..b3ce5f11b37 --- /dev/null +++ b/tests/app/util/test_cuda_build_compatibility.py @@ -0,0 +1,95 @@ +"""The startup check names the two ways a CUDA build fails on an NVIDIA machine, and stays quiet otherwise. + +Hardware is faked: CI has no GPU, and the cases that matter (an R570 driver, a Pascal card) are not on the dev machine +either. The fakes stand in for torch's device queries and the driver probe only; the decision is the code under test. +""" + +import logging + +import pytest +import torch + +from invokeai.app.util import startup_utils +from invokeai.app.util.startup_utils import check_cuda_build_compatibility + +LOGGER = "test_cuda_build_compatibility" + + +@pytest.fixture +def cuda_build(monkeypatch: pytest.MonkeyPatch): + def configure(*, cuda: str | None = "13.0", hip: str | None = None, available: bool, driver: int | None = None): + monkeypatch.setattr(torch.version, "cuda", cuda) + monkeypatch.setattr(torch.version, "hip", hip) + monkeypatch.setattr(torch.cuda, "is_available", lambda: available) + monkeypatch.setattr(startup_utils, "nvidia_driver_cuda_version", lambda: driver) + + return configure + + +@pytest.fixture +def gpus(monkeypatch: pytest.MonkeyPatch): + def configure(*devices: tuple[str, tuple[int, int]], arch_list: list[str]): + monkeypatch.setattr(torch.cuda, "get_arch_list", lambda: arch_list) + monkeypatch.setattr(torch.cuda, "device_count", lambda: len(devices)) + monkeypatch.setattr(torch.cuda, "get_device_name", lambda index: devices[index][0]) + monkeypatch.setattr(torch.cuda, "get_device_capability", lambda index: devices[index][1]) + + return configure + + +def errors(caplog: pytest.LogCaptureFixture) -> list[str]: + return [r.getMessage() for r in caplog.records if r.name == LOGGER and r.levelno == logging.ERROR] + + +def run(caplog: pytest.LogCaptureFixture) -> list[str]: + with caplog.at_level(logging.INFO, logger=LOGGER): + check_cuda_build_compatibility(logging.getLogger(LOGGER)) + return errors(caplog) + + +def test_a_driver_too_old_for_the_build_is_named_with_both_versions(cuda_build, caplog) -> None: + cuda_build(available=False, driver=12080) + + [message] = run(caplog) + + assert "CUDA 13.0" in message and "CUDA 12.8" in message and "R580" in message + + +@pytest.mark.parametrize("driver", [None, 13000, 13030]) +def test_no_error_without_a_driver_or_with_a_new_enough_one(cuda_build, caplog, driver: int | None) -> None: + # No driver: a CPU-only machine that got the CUDA build (PyPI's Linux torch is one). New enough: no NVIDIA GPU. + cuda_build(available=False, driver=driver) + + assert run(caplog) == [] + + +def test_a_gpu_below_the_lowest_built_architecture_is_named(cuda_build, gpus, caplog) -> None: + cuda_build(available=True) + gpus(("NVIDIA GeForce GTX 1080", (6, 1)), ("NVIDIA GeForce RTX 4090", (8, 9)), arch_list=["sm_75", "sm_120"]) + + [message] = run(caplog) + + assert "GTX 1080" in message and "6.1" in message and "7.5" in message + + +def test_supported_gpus_pass_and_ptx_entries_do_not_lower_the_floor(cuda_build, gpus, caplog) -> None: + cuda_build(available=True) + gpus(("NVIDIA GeForce GTX 1660", (7, 5)), arch_list=["sm_75", "sm_120", "compute_50"]) + + assert run(caplog) == [] + + +def test_suffixed_architectures_from_custom_builds_are_understood(cuda_build, gpus, caplog) -> None: + cuda_build(available=True) + gpus(("NVIDIA TITAN V", (7, 0)), arch_list=["sm_75", "sm_90a", "sm_100f"]) + + [message] = run(caplog) + + assert "TITAN V" in message and "7.5" in message + + +@pytest.mark.parametrize(("cuda", "hip"), [(None, None), (None, "7.15.26333")]) +def test_cpu_and_rocm_builds_are_not_checked(cuda_build, caplog, cuda, hip) -> None: + cuda_build(cuda=cuda, hip=hip, available=False, driver=12080) + + assert run(caplog) == [] diff --git a/tests/backend/util/test_noise_dtype.py b/tests/backend/util/test_noise_dtype.py new file mode 100644 index 00000000000..6deb5f3f964 --- /dev/null +++ b/tests/backend/util/test_noise_dtype.py @@ -0,0 +1,142 @@ +"""Seeded noise is drawn in float32 unless `noise_dtype: float16` asks for the old half-precision draw. + +float32 is what keeps a seed on the same image across torch versions: torch's float16/bfloat16 CPU `randn`/`rand` +changed after 2.7, its float32 ones did not. The setting tests compute their expectations from torch directly, with +float32/float64 targets where the two draws never coincide, so a draw site that stops honouring the setting fails on +any torch version. The golden values catch the other failure: a future torch changing the float32 draw itself. +""" + +from unittest.mock import MagicMock + +import pytest +import torch + +from invokeai.app.invocations.cogview4.cogview4_denoise import CogView4DenoiseInvocation +from invokeai.app.invocations.fields import ZImageConditioningField +from invokeai.app.invocations.flux.flux_denoise import FluxDenoiseInvocation +from invokeai.app.invocations.flux2.flux2_denoise import Flux2DenoiseInvocation +from invokeai.app.invocations.latent_noise import generate_noise_tensor +from invokeai.app.invocations.sd3.sd3_denoise import SD3DenoiseInvocation +from invokeai.app.invocations.z_image.z_image_seed_variance_enhancer import ZImageSeedVarianceEnhancerInvocation +from invokeai.app.services.config.config_default import InvokeAIAppConfig +from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ( + ConditioningFieldData, + ZImageConditioningInfo, +) +from invokeai.backend.util import devices as devices_module + +SEED = 1234 +CPU = torch.device("cpu") + + +@pytest.fixture +def noise_dtype(monkeypatch: pytest.MonkeyPatch): + def set_noise_dtype(value: str | None) -> None: + """None leaves the setting at its default.""" + monkeypatch.delenv("INVOKEAI_NOISE_DTYPE", raising=False) + config = InvokeAIAppConfig() if value is None else InvokeAIAppConfig(noise_dtype=value) + monkeypatch.setattr(devices_module, "get_config", lambda: config) + + return set_noise_dtype + + +def seeded(shape: tuple[int, ...], dtype: torch.dtype) -> torch.Tensor: + return torch.randn(*shape, dtype=dtype, generator=torch.Generator(device="cpu").manual_seed(SEED)) + + +def prepared(invocation_class, *channels: int) -> torch.Tensor: + """The noise a denoise node prepares when no noise is connected, cast to float32.""" + invocation = invocation_class.model_construct(width=64, height=64, seed=SEED, noise=None) + return invocation._prepare_noise_tensor(MagicMock(), *channels, torch.float32, CPU) + + +# Each denoise node used to draw its own noise in float16 on the CPU. +DENOISE_NODES = { + "flux": (lambda: prepared(FluxDenoiseInvocation), (1, 16, 8, 8)), + "flux2": (lambda: prepared(Flux2DenoiseInvocation), (1, 32, 8, 8)), + "sd3": (lambda: prepared(SD3DenoiseInvocation, 16), (1, 16, 8, 8)), + "cogview4": (lambda: prepared(CogView4DenoiseInvocation, 16), (1, 16, 8, 8)), +} + + +def test_float32_draw_matches_the_values_every_supported_torch_gives(noise_dtype) -> None: + # Measured on torch 2.7.1 (macOS pin) and 2.13.0 (Windows/Linux pins); a torch that changes these changes seeds. + # The tolerance allows for the vectorized x86 and scalar/ARM `normal_fill` paths; an algorithm change moves O(1). + noise_dtype(None) + + first = prepared(FluxDenoiseInvocation).flatten()[:8] + + expected = [-0.1117186, -0.4965901, 0.1630737, -0.8816878, 0.0539002, 0.6683737, -0.0596576, -0.4674979] + assert torch.allclose(first, torch.tensor(expected), atol=1e-4) + + +@pytest.mark.parametrize("name", DENOISE_NODES) +def test_denoise_nodes_draw_in_float32_by_default(noise_dtype, name: str) -> None: + noise_dtype(None) + generate, shape = DENOISE_NODES[name] + + assert torch.equal(generate(), seeded(shape, torch.float32)) + + +@pytest.mark.parametrize("name", DENOISE_NODES) +def test_float16_setting_restores_the_half_precision_draw(noise_dtype, name: str) -> None: + noise_dtype("float16") + generate, shape = DENOISE_NODES[name] + + noise = generate() + + assert torch.equal(noise, seeded(shape, torch.float16).float()) + assert not torch.equal(noise, seeded(shape, torch.float32)) + + +@pytest.mark.parametrize("noise_type", ["SD", "FLUX", "FLUX.2", "SD3", "CogView4"]) +def test_noise_node_draws_in_float32_and_keeps_the_device_precision(noise_dtype, noise_type: str) -> None: + # float64 stands in for the device precision so the two draws differ on every torch version. + noise_dtype(None) + + noise = generate_noise_tensor(noise_type, 64, 64, SEED, CPU, torch.float64) + + assert noise.dtype == torch.float64 + assert torch.equal(noise, seeded(tuple(noise.shape), torch.float32).double()) + + +def test_noise_node_float16_setting_draws_in_the_device_precision(noise_dtype) -> None: + noise_dtype("float16") + + noise = generate_noise_tensor("FLUX", 64, 64, SEED, CPU, torch.float64) + + assert torch.equal(noise, seeded((1, 16, 8, 8), torch.float64)) + + +@pytest.mark.parametrize("setting", ["float32", "float16"]) +@pytest.mark.parametrize(("noise_type", "shape"), [("Z-Image", (1, 16, 8, 8)), ("Anima", (1, 16, 1, 8, 8))]) +def test_float32_noise_types_ignore_the_setting(noise_dtype, setting: str, noise_type: str, shape) -> None: + noise_dtype(setting) + + noise = generate_noise_tensor(noise_type, 64, 64, SEED, CPU, torch.float16) + + assert torch.equal(noise, seeded(shape, torch.float32)) + + +@pytest.mark.parametrize(("setting", "draw_dtype"), [(None, torch.float32), ("float16", torch.float64)]) +def test_z_image_seed_variance_draws_in_the_configured_dtype(noise_dtype, setting, draw_dtype) -> None: + """The enhancer's uniform draw follows the setting too; float64 embeddings stand in for the old bf16 ones.""" + noise_dtype(setting) + embeds = torch.randn(4, 64, dtype=torch.float64, generator=torch.Generator().manual_seed(7)) + context = MagicMock() + context.conditioning.load.return_value = ConditioningFieldData( + conditionings=[ZImageConditioningInfo(prompt_embeds=embeds.clone())] + ) + context.conditioning.save.return_value = "c-varied" + invocation = ZImageSeedVarianceEnhancerInvocation( + conditioning=ZImageConditioningField(conditioning_name="c"), seed=SEED, strength=0.5, randomize_percent=50.0 + ) + + invocation.invoke(context) + + out = context.conditioning.save.call_args.args[0].conditionings[0].prompt_embeds + changed = out != embeds + uniform = torch.rand(embeds.shape, dtype=draw_dtype, generator=torch.Generator().manual_seed(SEED)).double() + expected = (uniform * 2 - 1) * (0.5 * torch.std(embeds).item()) + assert changed.any() + assert torch.allclose((out - embeds)[changed], expected[changed], atol=1e-12) diff --git a/uv.lock b/uv.lock index a8d3fc2bc4d..cf84101fe56 100644 --- a/uv.lock +++ b/uv.lock @@ -2,9 +2,22 @@ version = 1 revision = 3 requires-python = "==3.12.*" resolution-markers = [ - "platform_machine == 'aarch64' and sys_platform == 'linux'", - "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'win32'", - "sys_platform == 'darwin'", + "platform_machine == 'aarch64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu'", + "platform_machine == 'aarch64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "platform_machine == 'aarch64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "platform_machine == 'aarch64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')", + "platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu')", + "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu')", + "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu')", + "sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu'", + "sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "sys_platform == 'darwin' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", + "sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu'", ] supported-markers = [ "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", @@ -17,6 +30,10 @@ conflicts = [[ ]] [manifest] +constraints = [ + { name = "torch", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'win32'", specifier = "==2.13.0" }, + { name = "torchvision", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'win32'", specifier = "==0.28.0" }, +] overrides = [{ name = "opencv-python", marker = "sys_platform == 'never'" }] excludes = ["notebook"] @@ -40,10 +57,11 @@ dependencies = [ { name = "psutil" }, { name = "pyyaml" }, { name = "safetensors" }, - { name = "torch", version = "2.7.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu')" }, - { name = "torch", version = "2.7.1+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra != 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and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "torch", version = "2.13.0+rocm7.2", source = { registry = "https://download.pytorch.org/whl/rocm7.2" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu')" }, { name = "torch", version = "2.13.0+xpu", source = { registry = "https://download.pytorch.org/whl/xpu" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu')" }, ] wheels = [ @@ -233,7 +252,7 @@ name = "build" version = "1.5.0" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "colorama", marker = "(os_name == 'nt' and platform_machine == 'x86_64' and sys_platform == 'linux') or (os_name == 'nt' and sys_platform == 'win32') or (os_name != 'nt' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (os_name != 'nt' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (os_name != 'nt' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (os_name != 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'extra-8-invokeai-cpu') or (os_name == 'nt' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (os_name == 'nt' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-rocm') or (os_name == 'nt' and sys_platform == 'win32') or (os_name != 'nt' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (os_name != 'nt' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (os_name != 'nt' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (os_name != 'nt' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (os_name != 'nt' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (os_name != 'nt' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 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sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, { name = "packaging" }, { name = "pyproject-hooks" }, ] @@ -359,10 +378,11 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "diffusers" }, { name = "pyparsing" }, - { name = "torch", version = "2.7.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and 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'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] +cupti = [ + { name = "nvidia-cuda-cupti", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 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'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] +curand = [ + { name = "nvidia-curand", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 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== 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] +cusolver = [ + { name = "nvidia-cublas", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 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or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "nvidia-cusolver", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 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or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "nvidia-cusparse", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "nvidia-nvjitlink", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 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'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] +cusparse = [ + { name = "nvidia-cusparse", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "nvidia-nvjitlink", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 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or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] +nvjitlink = [ + { name = "nvidia-nvjitlink", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] +nvrtc = [ + { name = "nvidia-cuda-nvrtc", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 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(platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (platform_machine == 'AMD64' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, +] + [[package]] name = "cycler" version = "0.12.1" @@ -484,10 +575,11 @@ wheels = [ [package.optional-dependencies] torch = [ { name = "accelerate" }, - { name = "torch", version = "2.7.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') 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(sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, - { name = "torch", version = "2.7.1+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 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and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 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extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, - { name = "torchvision", version = "0.22.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, - { name = "torchvision", version = "0.22.1+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "torch", version = "2.7.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 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== 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "torchvision", version = "0.22.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "torchvision", version = "0.28.0+cu130", source = { registry = "https://download.pytorch.org/whl/cu130" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, ] dev = [ { name = "gprof2dot" }, @@ -1097,8 +1191,8 @@ test = [ { name = "ruff-lsp" }, ] xformers = [ - { name = "xformers", version = "0.0.31.post1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra != 'extra-8-invokeai-rocm' and extra != 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-rocm' and extra != 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!= 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu')" }, + { name = "xformers", version = "0.0.31.post1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine == 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 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extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or sys_platform == 'win32' or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, ] xpu = [ { name = "torch", version = "2.7.1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine != 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and sys_platform != 'win32' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-xpu')" }, @@ -1177,6 +1271,8 @@ requires-dist = [ { name = "spandrel" }, { name = "torch", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')", specifier = ">=2.7.0,<3.0" }, { name = "torch", marker = "sys_platform == 'darwin'", specifier = ">=2.7.0,<2.8.0" }, + { name = "torch", marker = "sys_platform == 'darwin' and extra == 'cpu'", specifier = "==2.7.1" }, + { name = "torch", marker = "sys_platform == 'darwin' and extra == 'cuda'", specifier = "==2.7.1" }, { name = "torch", marker = "sys_platform == 'darwin' and extra == 'xpu'", specifier = "==2.7.1" }, { name = "torch", marker = "platform_machine == 'aarch64' and sys_platform == 'linux'", specifier = ">=2.7.0,<3.0", index = "https://pypi.org/simple" }, { name = "torch", marker = "platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cpu'", 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extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu')" }, + { name = "torch", version = "2.13.0+rocm7.2", source = { registry = "https://download.pytorch.org/whl/rocm7.2" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-rocm' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-xpu') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cuda' and extra == 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