Ewald
a4154ccf05
- Fix batch bypass tuple handling, memory budget device-awareness, grain RNG device, roto payload limits, preview temp-file cleanup, and route double-registration. - Add native VIDEO output (fps/audio) to effect nodes that previously only returned IMAGE/MASK when fed a VIDEO input. - Split the oversized src/preview/ops/geometry.ts and add a starting golden-fixture test harness (spherize, transform) comparing backend and frontend math. - Remove ImageOpsAppendV2 (Autogrow) and ImageOpsLensArtifacts; inline Append's helper back into its single caller. - Collapse the Color Correct curve widget behind a toggle so the node no longer grows too tall. - Fix Crop/generic-node video preview playback running at the RAF rate instead of the source video's real fps. - Fix Crop losing its saved output size after a workflow reload: syncCropWidgets recomputed height from width and a preset aspect ratio on every resync (including onConfigure on load), discarding the restored value. It now only refreshes aspect-ratio bookkeeping on a resync.
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
"""Grain RNG must generate on the tensor's own device for CUDA/MPS instead of
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always paying a CPU round-trip, while staying on CPU for backends torch.Generator
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doesn't support directly (DirectML, XPU, NPU)."""
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from __future__ import annotations
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import torch
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from nodes.grain import _grain_generator_device, _grain_noise_like
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class _DeviceStub:
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def __init__(self, type_name):
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self.type = type_name
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class _TensorStub:
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def __init__(self, type_name):
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self.device = _DeviceStub(type_name)
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def test_generator_device_matches_supported_backends():
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assert _grain_generator_device(_TensorStub("cuda")).type == "cuda"
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assert _grain_generator_device(_TensorStub("mps")).type == "mps"
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assert _grain_generator_device(_TensorStub("cpu")).type == "cpu"
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def test_generator_device_falls_back_to_cpu_for_unsupported_backends():
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# torch.Generator has no native support for DirectML/XPU/NPU backends.
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assert _grain_generator_device(_TensorStub("privateuseone")).type == "cpu"
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assert _grain_generator_device(_TensorStub("xpu")).type == "cpu"
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def test_grain_noise_like_still_produces_correct_shape_and_device_on_cpu():
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source = torch.zeros(2, 8, 8, 3)
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noise = _grain_noise_like(source, seed=1, monochrome=False, animated=True)
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assert noise.shape == source.shape
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assert noise.device == source.device
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