Added Derive Seed node (#1611)

* Added Random Seed node

* Added migration

* Rebrand to Derive Seed

* Made seeds their own datatype

* Added test for migration

backend/src/nodes/nodes/external_stable_diffusion/img2img.py

@@ -23,11 +23,12 @@
     BoolInput,
     EnumInput,
     ImageInput,
-    NumberInput,
+    SeedInput,
     SliderInput,
     TextAreaInput,
 )
 from ...properties.outputs import ImageOutput
+from ...utils.seed import Seed
 from ...utils.utils import get_h_w_c
 from . import category as ExternalStableDiffusionCategory
 
@@ -52,9 +53,7 @@ def __init__(self):
                 controls_step=0.1,
                 precision=2,
             ),
-            group("seed")(
-                NumberInput("Seed", minimum=0, default=42, maximum=4294967296)
-            ),
+            group("seed")(SeedInput()),
             SliderInput("Steps", minimum=1, default=20, maximum=150),
             EnumInput(
                 SamplerName,
@@ -115,7 +114,7 @@ def run(
         prompt: Optional[str],
         negative_prompt: Optional[str],
         denoising_strength: float,
-        seed: int,
+        seed: Seed,
         steps: int,
         sampler_name: SamplerName,
         cfg_scale: float,
@@ -132,7 +131,7 @@ def run(
             "prompt": prompt or "",
             "negative_prompt": negative_prompt or "",
             "denoising_strength": denoising_strength,
-            "seed": seed,
+            "seed": seed.to_u32(),
             "steps": steps,
             "sampler_name": sampler_name.value,
             "cfg_scale": cfg_scale,

backend/src/nodes/nodes/external_stable_diffusion/inpainting.py

@@ -27,11 +27,12 @@
     BoolInput,
     EnumInput,
     ImageInput,
-    NumberInput,
+    SeedInput,
     SliderInput,
     TextAreaInput,
 )
 from ...properties.outputs import ImageOutput
+from ...utils.seed import Seed
 from ...utils.utils import get_h_w_c
 from . import category as ExternalStableDiffusionCategory
 
@@ -64,9 +65,7 @@ def __init__(self):
                 controls_step=0.1,
                 precision=2,
             ),
-            group("seed")(
-                NumberInput("Seed", minimum=0, default=42, maximum=4294967296)
-            ),
+            group("seed")(SeedInput()),
             SliderInput("Steps", minimum=1, default=20, maximum=150),
             EnumInput(
                 SamplerName,
@@ -148,7 +147,7 @@ def run(
         prompt: Optional[str],
         negative_prompt: Optional[str],
         denoising_strength: float,
-        seed: int,
+        seed: Seed,
         steps: int,
         sampler_name: SamplerName,
         cfg_scale: float,
@@ -174,7 +173,7 @@ def run(
             "prompt": prompt or "",
             "negative_prompt": negative_prompt or "",
             "denoising_strength": denoising_strength,
-            "seed": seed,
+            "seed": seed.to_u32(),
             "steps": steps,
             "sampler_name": sampler_name.value,
             "cfg_scale": cfg_scale,

backend/src/nodes/nodes/external_stable_diffusion/outpainting.py

@@ -27,11 +27,12 @@
     BoolInput,
     EnumInput,
     ImageInput,
-    NumberInput,
+    SeedInput,
     SliderInput,
     TextAreaInput,
 )
 from ...properties.outputs import ImageOutput
+from ...utils.seed import Seed
 from ...utils.utils import get_h_w_c
 from . import category as ExternalStableDiffusionCategory
 
@@ -61,9 +62,7 @@ def __init__(self):
                 controls_step=0.1,
                 precision=2,
             ),
-            group("seed")(
-                NumberInput("Seed", minimum=0, default=42, maximum=4294967296)
-            ),
+            group("seed")(SeedInput()),
             SliderInput("Steps", minimum=1, default=20, maximum=150),
             EnumInput(
                 SamplerName,
@@ -176,7 +175,7 @@ def run(
         prompt: Optional[str],
         negative_prompt: Optional[str],
         denoising_strength: float,
-        seed: int,
+        seed: Seed,
         steps: int,
         sampler_name: SamplerName,
         cfg_scale: float,
@@ -221,7 +220,7 @@ def run(
             "prompt": prompt or "",
             "negative_prompt": negative_prompt or "",
             "denoising_strength": denoising_strength,
-            "seed": seed,
+            "seed": seed.to_u32(),
             "steps": steps,
             "sampler_name": sampler_name.value,
             "cfg_scale": cfg_scale,

backend/src/nodes/nodes/external_stable_diffusion/txt2img.py

@@ -19,11 +19,12 @@
 from ...properties.inputs import (
     BoolInput,
     EnumInput,
-    NumberInput,
+    SeedInput,
     SliderInput,
     TextAreaInput,
 )
 from ...properties.outputs import ImageOutput
+from ...utils.seed import Seed
 from ...utils.utils import get_h_w_c
 from . import category as ExternalStableDiffusionCategory
 
@@ -38,9 +39,7 @@ def __init__(self):
         self.inputs = [
             TextAreaInput("Prompt").make_optional(),
             TextAreaInput("Negative Prompt").make_optional(),
-            group("seed")(
-                NumberInput("Seed", minimum=0, default=42, maximum=4294967296)
-            ),
+            group("seed")(SeedInput()),
             SliderInput("Steps", minimum=1, default=20, maximum=150),
             EnumInput(
                 SamplerName,
@@ -94,7 +93,7 @@ def run(
         self,
         prompt: Optional[str],
         negative_prompt: Optional[str],
-        seed: int,
+        seed: Seed,
         steps: int,
         sampler_name: SamplerName,
         cfg_scale: float,
@@ -108,7 +107,7 @@ def run(
         request_data = {
             "prompt": prompt or "",
             "negative_prompt": negative_prompt or "",
-            "seed": seed,
+            "seed": seed.to_u32(),
             "steps": steps,
             "sampler_name": sampler_name.value,
             "cfg_scale": cfg_scale,

backend/src/nodes/nodes/image/create_noise.py

@@ -4,16 +4,22 @@
 
 import numpy as np
 
-from nodes.impl.image_utils import cartesian_product
-from nodes.impl.noise_functions.simplex import SimplexNoise
-from nodes.impl.noise_functions.value import ValueNoise
-from nodes.node_base import NodeBase, group
-from nodes.node_factory import NodeFactory
-from nodes.properties import expression
-from nodes.properties.inputs import BoolInput, EnumInput, NumberInput, SliderInput
-from nodes.properties.outputs import ImageOutput
-
 from ...groups import conditional_group
+from ...impl.image_utils import cartesian_product
+from ...impl.noise_functions.simplex import SimplexNoise
+from ...impl.noise_functions.value import ValueNoise
+from ...node_base import NodeBase, group
+from ...node_factory import NodeFactory
+from ...properties import expression
+from ...properties.inputs import (
+    BoolInput,
+    EnumInput,
+    NumberInput,
+    SeedInput,
+    SliderInput,
+)
+from ...properties.outputs import ImageOutput
+from ...utils.seed import Seed
 from . import category as ImageCategory
 
 
@@ -35,9 +41,7 @@ def __init__(self):
         self.inputs = [
             NumberInput("Width", minimum=1, unit="px", default=256),
             NumberInput("Height", minimum=1, unit="px", default=256),
-            group("seed")(
-                NumberInput("Seed", minimum=0, maximum=2**32 - 1, default=0),
-            ),
+            group("seed")(SeedInput()),
             EnumInput(
                 NoiseMethod,
                 default_value=NoiseMethod.SIMPLEX,
@@ -129,7 +133,7 @@ def run(
         self,
         width: int,
         height: int,
-        seed: int,
+        seed: Seed,
         noise_method: NoiseMethod,
         scale: float,
         brightness: float,
@@ -151,7 +155,7 @@ def run(
             "tile_spherical": tile_spherical,
             "scale": scale,
             "brightness": brightness,
-            "seed": seed,
+            "seed": seed.to_u32(),
         }
 
         generator_class = None

backend/src/nodes/nodes/image_filter/add_noise.py

@@ -14,8 +14,9 @@
 )
 from ...node_base import NodeBase, group
 from ...node_factory import NodeFactory
-from ...properties.inputs import EnumInput, ImageInput, NumberInput, SliderInput
+from ...properties.inputs import EnumInput, ImageInput, SeedInput, SliderInput
 from ...properties.outputs import ImageOutput
+from ...utils.seed import Seed
 from . import category as ImageFilterCategory
 
 
@@ -45,9 +46,7 @@ def __init__(self):
                 },
             ),
             SliderInput("Amount", minimum=0, maximum=100, default=50),
-            group("seed")(
-                NumberInput("Seed", minimum=None, maximum=None, default=0),
-            ),
+            group("seed")(SeedInput()),
         ]
         self.outputs = [
             ImageOutput(
@@ -73,17 +72,17 @@ def run(
         noise_type: NoiseType,
         noise_color: NoiseColor,
         amount: int,
-        seed: int,
+        seed: Seed,
     ) -> np.ndarray:
         if noise_type == NoiseType.GAUSSIAN:
-            return gaussian_noise(img, amount / 100, noise_color, seed)
+            return gaussian_noise(img, amount / 100, noise_color, seed.value)
         elif noise_type == NoiseType.UNIFORM:
-            return uniform_noise(img, amount / 100, noise_color, seed)
+            return uniform_noise(img, amount / 100, noise_color, seed.value)
         elif noise_type == NoiseType.SALT_AND_PEPPER:
-            return salt_and_pepper_noise(img, amount / 100, noise_color, seed)
+            return salt_and_pepper_noise(img, amount / 100, noise_color, seed.value)
         elif noise_type == NoiseType.POISSON:
-            return poisson_noise(img, amount / 100, noise_color, seed)
+            return poisson_noise(img, amount / 100, noise_color, seed.value)
         elif noise_type == NoiseType.SPECKLE:
-            return speckle_noise(img, amount / 100, noise_color, seed)
+            return speckle_noise(img, amount / 100, noise_color, seed.value)
         else:
             raise ValueError(f"Unknown noise type: {noise_type}")

backend/src/nodes/nodes/utility/derive_seed.py

@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+import hashlib
+import struct
+from typing import Union
+
+from ...node_base import NodeBase, group
+from ...node_factory import NodeFactory
+from ...properties.inputs import BaseInput, SeedInput
+from ...properties.outputs import SeedOutput
+from ...utils.seed import Seed
+from ...utils.utils import ALPHABET
+from . import category as UtilityCategory
+
+Source = Union[int, float, str, Seed]
+
+
+def SourceInput(label: str):
+    return BaseInput(
+        kind="generic",
+        label=label,
+        input_type="number | string | Directory | Seed",
+    ).make_optional()
+
+
+def _to_bytes(s: Source) -> bytes:
+    if isinstance(s, str):
+        return s.encode(errors="backslashreplace")
+    if isinstance(s, Seed):
+        s = s.value
+
+    i = int(s)
+    if isinstance(s, int) or s == i:
+        return i.to_bytes(i.bit_length() // 8 + 1, byteorder="big", signed=True)
+
+    return struct.pack("d", s)
+
+
+@NodeFactory.register("chainner:utility:derive_seed")
+class RandomNumberNode(NodeBase):
+    def __init__(self):
+        super().__init__()
+        self.description = "Creates a new seed from multiple sources of randomness."
+        self.inputs = [
+            group("seed")(SeedInput(has_handle=False)),
+            SourceInput(f"Source A"),
+            group("optional-list")(
+                *[SourceInput(f"Source {letter}") for letter in ALPHABET[1:10]],
+            ),
+        ]
+        self.outputs = [
+            SeedOutput(),
+        ]
+
+        self.category = UtilityCategory
+        self.name = "Derive Seed"
+        self.icon = "MdCalculate"
+        self.sub = "Random"
+
+    def run(self, seed: Seed, *sources: Source | None) -> Seed:
+        h = hashlib.sha256()
+
+        h.update(_to_bytes(seed))
+        for s in sources:
+            if s is not None:
+                h.update(_to_bytes(s))
+
+        return Seed.from_bytes(h.digest())

backend/src/nodes/nodes/utility/random_number.py

@@ -1,12 +1,10 @@
-from __future__ import annotations
-
 from random import Random
-from typing import Union
 
 from ...node_base import NodeBase, group
 from ...node_factory import NodeFactory
-from ...properties.inputs import BaseInput, NumberInput
+from ...properties.inputs import NumberInput, SeedInput
 from ...properties.outputs import NumberOutput
+from ...utils.seed import Seed
 from . import category as UtilityCategory
 
 
@@ -27,16 +25,7 @@ def __init__(self):
                 maximum=None,
                 default=100,
             ),
-            group("seed")(
-                NumberInput(
-                    "Seed",
-                    minimum=0,
-                    maximum=None,
-                ),
-            ),
-            BaseInput(
-                input_type="uint", label="Index from Iterator", kind="generic"
-            ).make_optional(),
+            group("seed")(SeedInput()),
         ]
         self.outputs = [
             NumberOutput(
@@ -47,11 +36,7 @@ def __init__(self):
         self.category = UtilityCategory
         self.name = "Random Number"
         self.icon = "MdCalculate"
-        self.sub = "Math"
+        self.sub = "Random"
 
-    def run(
-        self, minval: int, maxval: int, seedval: int, frameval: Union[int, None]
-    ) -> int:
-        if frameval == None:
-            frameval = 0
-        return Random((frameval + 1) * (seedval + 1)).randint(minval, maxval)
+    def run(self, min_val: int, max_val: int, seed: Seed) -> int:
+        return Random(seed.value).randint(min_val, max_val)