implement cumprod

more work on timestamps (WIP)
cleanup
2026-10-26 03:39:28 -04:00 · 2025-02-25 00:25:19 -05:00 · 2025-02-24 19:36:31 -05:00 · 2025-02-24 17:48:24 -05:00 · 2025-02-24 17:45:08 -05:00 · 2025-02-24 17:22:25 -05:00
22 changed files with 1173 additions and 86 deletions
@@ -609,6 +609,7 @@ dependencies = [
 "candle-core",
 "candle-nn",
 "candle-transformers",
+ "cudarc",
 "filesys",
 "hf-hub",
 "image",
@@ -1424,14 +1425,14 @@ dependencies = [

 [[package]]
 name = "candle-core"
-version = "0.8.2"
+version = "0.8.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "855dfedff437d2681d68e1f34ae559d88b0dd84aa5a6b63f2c8e75ebdd875bbf"
+checksum = "bef79e00300acaaa6b0b33168e2ed5050f06125d1add87e7103c40a119083581"
 dependencies = [
 "byteorder",
 "candle-kernels",
 "cudarc",
- "gemm",
+ "gemm 0.17.1",
 "half",
 "memmap2",
 "num-traits",
@@ -1449,9 +1450,9 @@ dependencies = [

 [[package]]
 name = "candle-kernels"
-version = "0.8.2"
+version = "0.8.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "53343628fa470b7075c28c589b98735b4220b464e37ddbb8e117040e199f4787"
+checksum = "e3134cc19a080a326f95bdcbe057ecaa9658598e5146e37ba1a8cd550c342a9b"
 dependencies = [
 "bindgen_cuda",
 ]
@@ -2228,9 +2229,9 @@ dependencies = [

 [[package]]
 name = "cudarc"
-version = "0.12.1"
+version = "0.13.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "38cd60a9a42ec83a2ed7effb0b1f073270264ea99da7acfc44f7e8d74dee0384"
+checksum = "4e29ce3bfa797c1183053ceb496316203ef561c183941c3c181500d9ade6daf4"
 dependencies = [
 "half",
 "libloading 0.8.6",
@@ -2891,6 +2892,15 @@ dependencies = [
 "reborrow",
 ]

+[[package]]
+name = "dyn-stack"
+version = "0.13.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "490bd48eb68fffcfed519b4edbfd82c69cbe741d175b84f0e0cbe8c57cbe0bdd"
+dependencies = [
+ "bytemuck",
+]
+
 [[package]]
 name = "easyenv"
 version = "0.1.0"
@@ -3743,17 +3753,37 @@ version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "6ab24cc62135b40090e31a76a9b2766a501979f3070fa27f689c27ec04377d32"
 dependencies = [
- "dyn-stack",
- "gemm-c32",
- "gemm-c64",
- "gemm-common",
- "gemm-f16",
- "gemm-f32",
- "gemm-f64",
+ "dyn-stack 0.10.0",
+ "gemm-c32 0.17.1",
+ "gemm-c64 0.17.1",
+ "gemm-common 0.17.1",
+ "gemm-f16 0.17.1",
+ "gemm-f32 0.17.1",
+ "gemm-f64 0.17.1",
 "num-complex",
 "num-traits",
 "paste",
- "raw-cpuid",
+ "raw-cpuid 10.7.0",
+ "seq-macro",
+]
+
+[[package]]
+name = "gemm"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ab96b703d31950f1aeddded248bc95543c9efc7ac9c4a21fda8703a83ee35451"
+dependencies = [
+ "dyn-stack 0.13.0",
+ "gemm-c32 0.18.2",
+ "gemm-c64 0.18.2",
+ "gemm-common 0.18.2",
+ "gemm-f16 0.18.2",
+ "gemm-f32 0.18.2",
+ "gemm-f64 0.18.2",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "raw-cpuid 11.4.0",
 "seq-macro",
 ]

@@ -3763,12 +3793,27 @@ version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b9c030d0b983d1e34a546b86e08f600c11696fde16199f971cd46c12e67512c0"
 dependencies = [
- "dyn-stack",
- "gemm-common",
+ "dyn-stack 0.10.0",
+ "gemm-common 0.17.1",
 "num-complex",
 "num-traits",
 "paste",
- "raw-cpuid",
+ "raw-cpuid 10.7.0",
+ "seq-macro",
+]
+
+[[package]]
+name = "gemm-c32"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f6db9fd9f40421d00eea9dd0770045a5603b8d684654816637732463f4073847"
+dependencies = [
+ "dyn-stack 0.13.0",
+ "gemm-common 0.18.2",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "raw-cpuid 11.4.0",
 "seq-macro",
 ]

@@ -3778,12 +3823,27 @@ version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "fbb5f2e79fefb9693d18e1066a557b4546cd334b226beadc68b11a8f9431852a"
 dependencies = [
- "dyn-stack",
- "gemm-common",
+ "dyn-stack 0.10.0",
+ "gemm-common 0.17.1",
 "num-complex",
 "num-traits",
 "paste",
- "raw-cpuid",
+ "raw-cpuid 10.7.0",
+ "seq-macro",
+]
+
+[[package]]
+name = "gemm-c64"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "dfcad8a3d35a43758330b635d02edad980c1e143dc2f21e6fd25f9e4eada8edf"
+dependencies = [
+ "dyn-stack 0.13.0",
+ "gemm-common 0.18.2",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "raw-cpuid 11.4.0",
 "seq-macro",
 ]

@@ -3794,17 +3854,38 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "a2e7ea062c987abcd8db95db917b4ffb4ecdfd0668471d8dc54734fdff2354e8"
 dependencies = [
 "bytemuck",
- "dyn-stack",
+ "dyn-stack 0.10.0",
 "half",
 "num-complex",
 "num-traits",
 "once_cell",
 "paste",
- "pulp",
- "raw-cpuid",
+ "pulp 0.18.22",
+ "raw-cpuid 10.7.0",
 "rayon",
 "seq-macro",
- "sysctl",
+ "sysctl 0.5.5",
+]
+
+[[package]]
+name = "gemm-common"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a352d4a69cbe938b9e2a9cb7a3a63b7e72f9349174a2752a558a8a563510d0f3"
+dependencies = [
+ "bytemuck",
+ "dyn-stack 0.13.0",
+ "half",
+ "libm",
+ "num-complex",
+ "num-traits",
+ "once_cell",
+ "paste",
+ "pulp 0.21.4",
+ "raw-cpuid 11.4.0",
+ "rayon",
+ "seq-macro",
+ "sysctl 0.6.0",
 ]

 [[package]]
@@ -3813,14 +3894,32 @@ version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "7ca4c06b9b11952071d317604acb332e924e817bd891bec8dfb494168c7cedd4"
 dependencies = [
- "dyn-stack",
- "gemm-common",
- "gemm-f32",
+ "dyn-stack 0.10.0",
+ "gemm-common 0.17.1",
+ "gemm-f32 0.17.1",
 "half",
 "num-complex",
 "num-traits",
 "paste",
- "raw-cpuid",
+ "raw-cpuid 10.7.0",
+ "rayon",
+ "seq-macro",
+]
+
+[[package]]
+name = "gemm-f16"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "cff95ae3259432f3c3410eaa919033cd03791d81cebd18018393dc147952e109"
+dependencies = [
+ "dyn-stack 0.13.0",
+ "gemm-common 0.18.2",
+ "gemm-f32 0.18.2",
+ "half",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "raw-cpuid 11.4.0",
 "rayon",
 "seq-macro",
 ]
@@ -3831,12 +3930,27 @@ version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "e9a69f51aaefbd9cf12d18faf273d3e982d9d711f60775645ed5c8047b4ae113"
 dependencies = [
- "dyn-stack",
- "gemm-common",
+ "dyn-stack 0.10.0",
+ "gemm-common 0.17.1",
 "num-complex",
 "num-traits",
 "paste",
- "raw-cpuid",
+ "raw-cpuid 10.7.0",
+ "seq-macro",
+]
+
+[[package]]
+name = "gemm-f32"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "bc8d3d4385393304f407392f754cd2dc4b315d05063f62cf09f47b58de276864"
+dependencies = [
+ "dyn-stack 0.13.0",
+ "gemm-common 0.18.2",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "raw-cpuid 11.4.0",
 "seq-macro",
 ]

@@ -3846,12 +3960,27 @@ version = "0.17.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "aa397a48544fadf0b81ec8741e5c0fba0043008113f71f2034def1935645d2b0"
 dependencies = [
- "dyn-stack",
- "gemm-common",
+ "dyn-stack 0.10.0",
+ "gemm-common 0.17.1",
 "num-complex",
 "num-traits",
 "paste",
- "raw-cpuid",
+ "raw-cpuid 10.7.0",
+ "seq-macro",
+]
+
+[[package]]
+name = "gemm-f64"
+version = "0.18.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "35b2a4f76ce4b8b16eadc11ccf2e083252d8237c1b589558a49b0183545015bd"
+dependencies = [
+ "dyn-stack 0.13.0",
+ "gemm-common 0.18.2",
+ "num-complex",
+ "num-traits",
+ "paste",
+ "raw-cpuid 11.4.0",
 "seq-macro",
 ]

@@ -5237,9 +5366,9 @@ dependencies = [

 [[package]]
 name = "libm"
-version = "0.2.8"
+version = "0.2.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4ec2a862134d2a7d32d7983ddcdd1c4923530833c9f2ea1a44fc5fa473989058"
+checksum = "8355be11b20d696c8f18f6cc018c4e372165b1fa8126cef092399c9951984ffa"

 [[package]]
 name = "libredox"
@@ -6238,7 +6367,7 @@ version = "0.7.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "681030a937600a36906c185595136d26abfebb4aa9c65701cefcaf8578bb982b"
 dependencies = [
- "proc-macro-crate 3.1.0",
+ "proc-macro-crate 1.3.1",
 "proc-macro2",
 "quote",
 "syn 2.0.87",
@@ -7323,6 +7452,20 @@ dependencies = [
 "reborrow",
 ]

+[[package]]
+name = "pulp"
+version = "0.21.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "95fb7a99b37aaef4c7dd2fd15a819eb8010bfc7a2c2155230d51f497316cad6d"
+dependencies = [
+ "bytemuck",
+ "cfg-if 1.0.0",
+ "libm",
+ "num-complex",
+ "reborrow",
+ "version_check",
+]
+
 [[package]]
 name = "qoi"
 version = "0.4.1"
@@ -7636,6 +7779,15 @@ dependencies = [
 "bitflags 1.3.2",
 ]

+[[package]]
+name = "raw-cpuid"
+version = "11.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "529468c1335c1c03919960dfefdb1b3648858c20d7ec2d0663e728e4a717efbc"
+dependencies = [
+ "bitflags 2.5.0",
+]
+
 [[package]]
 name = "raw-window-handle"
 version = "0.6.2"
@@ -9774,6 +9926,20 @@ dependencies = [
 "walkdir",
 ]

+[[package]]
+name = "sysctl"
+version = "0.6.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "01198a2debb237c62b6826ec7081082d951f46dbb64b0e8c7649a452230d1dfc"
+dependencies = [
+ "bitflags 2.5.0",
+ "byteorder",
+ "enum-as-inner",
+ "libc",
+ "thiserror 1.0.63",
+ "walkdir",
+]
+
 [[package]]
 name = "system-configuration"
 version = "0.5.1"
@@ -10846,27 +11012,34 @@ checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"

 [[package]]
 name = "ug"
-version = "0.0.2"
+version = "0.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c4eef2ebfc18c67a6dbcacd9d8a4d85e0568cc58c82515552382312c2730ea13"
+checksum = "03719c61a91b51541f076dfdba45caacf750b230cefaa4b32d6f5411c3f7f437"
 dependencies = [
+ "gemm 0.18.2",
 "half",
+ "libloading 0.8.6",
+ "memmap2",
 "num",
+ "num-traits",
+ "num_cpus",
+ "rayon",
+ "safetensors",
 "serde",
- "serde_json",
 "thiserror 1.0.63",
+ "tracing",
+ "yoke",
 ]

 [[package]]
 name = "ug-cuda"
-version = "0.0.2"
+version = "0.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1c4dcab280ad0ef3957e153a82dcad608c954d02cf253b695322f502d1f8902e"
+checksum = "50758486d7941f8b0a636ba7e29455c07071f41590beac1fd307ec893e8db69a"
 dependencies = [
 "cudarc",
 "half",
 "serde",
- "serde_json",
 "thiserror 1.0.63",
 "ug",
 ]
@@ -11192,9 +11365,9 @@ dependencies = [

 [[package]]
 name = "version_check"
-version = "0.9.4"
+version = "0.9.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "49874b5167b65d7193b8aba1567f5c7d93d001cafc34600cee003eda787e483f"
+checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"

 [[package]]
 name = "videos"
@@ -23,6 +23,9 @@ tauri-build = { version = "2.0.4", features = [] }
 filesys = { path = "../../lib/files/filesys" }
 memory_caching = { path = "../../lib/caching/memory_caching" }

+# Bypass cudarc issues on Windows https://github.com/coreylowman/cudarc/issues/332
+cudarc = "0.13.7"
+
 # External
 anyhow = "1.0"
 bytes = "1.10"
@@ -44,4 +47,10 @@ tokenizers = "0.15.2"

 [features]
 default = ["cuda"]
-cuda = ["candle-core/cuda", "candle-nn/cuda", "candle-transformers/cuda"]
+cuda = [
+  "candle-core/cuda",
+  # TODO(bt,2025-02-22): cuDNN might speed up Stable Diffusion
+  # "candle-core/cudnn",
+  "candle-nn/cuda",
+  "candle-transformers/cuda",
+]
@@ -0,0 +1,150 @@
+use candle_core::shape::Dim;
+use candle_core::Tensor;
+
+/// Tensor Cumulative Product
+/// 
+/// Candle doesn't implement cumprod, only cumsum.
+/// This implementation is adapted from cumsum in candle-ext:
+///  https://github.com/mokeyish/candle-ext/blob/main/tests/cumsum.rs
+///
+/// See Also: https://pytorch.org/docs/stable/generated/torch.cumprod.html
+/// See Also: https://numpy.org/doc/stable/reference/generated/numpy.cumprod.html
+/// See Also: https://github.com/huggingface/candle/issues/1646
+///
+pub fn cumprod<D: Dim>(input: &Tensor, dim: D) -> candle_core::Result<Tensor> {
+  let dim = dim.to_index(input.shape(), "cumprod")?;
+  let dim_size = input.dim(dim)?;
+  let rank = input.rank();
+  if rank == 0 {
+    return Ok(input.clone());
+  }
+
+  let mut tensors = Vec::with_capacity(dim_size);
+
+  let mut a = input.clone();
+  for i in 0..dim_size {
+    if i > 0 {
+      a = a.narrow(dim, 1, dim_size - i)?;
+      let b = input.narrow(dim, 0, dim_size - i)?;
+      a = (a * b)?;
+    }
+    tensors.push(a.narrow(dim, 0, 1)?);
+  }
+
+  let cumsum = Tensor::cat(&tensors, dim)?;
+  Ok(cumsum)
+}
+
+#[cfg(test)]
+mod tests {
+  use crate::ml::cumprod::cumprod;
+  use candle_core::{Device, Tensor};
+
+  mod base_cases {
+    use super::*;
+
+    #[test]
+    fn zeroes_vector() -> anyhow::Result<()> {
+      let a = Tensor::new(&[0i64, 0, 0, 0], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[0, 0, 0, 0]);
+      Ok(())
+    }
+
+    #[test]
+    fn zeroes_tensor() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [0i64, 0, 0],
+        [0i64, 0, 0],
+        [0i64, 0, 0],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 0)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [0, 0, 0],
+        [0, 0, 0],
+        [0, 0, 0],
+      ]);
+      Ok(())
+    }
+
+    #[test]
+    fn ones_vector() -> anyhow::Result<()> {
+      let a = Tensor::new(&[1i64, 1, 1, 1], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[1, 1, 1, 1]);
+      Ok(())
+    }
+
+    #[test]
+    fn ones_tensor() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [1i64, 1, 1],
+        [1i64, 1, 1],
+        [1i64, 1, 1],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 0)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [1, 1, 1],
+        [1, 1, 1],
+        [1, 1, 1],
+      ]);
+      Ok(())
+    }
+  }
+
+  mod test_cases {
+    use super::*;
+
+    #[test]
+    fn vector() -> anyhow::Result<()> {
+      let a = Tensor::new(&[1i64, 2, 3, 4, 5], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[1, 2, 6, 24, 120]);
+
+      let a = Tensor::new(&[0, 1i64, 2, 3, 4, 5], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[0, 0, 0, 0, 0, 0]);
+      Ok(())
+    }
+
+    #[test]
+    fn tensor_dim_0() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [1i64, 2, 3],
+        [4i64, 5, 6],
+        [7i64, 8, 9],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 0)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [1, 2, 3],
+        [4, 10, 18],
+        [28, 80, 162],
+      ]);
+      Ok(())
+    }
+
+    #[test]
+    fn tensor_dim_1() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [1i64, 2, 3],
+        [4i64, 5, 6],
+        [7i64, 8, 9],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 1)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [1, 2, 6],
+        [4, 20, 120],
+        [7, 56, 504],
+      ]);
+      Ok(())
+    }
+  }
+}
@@ -0,0 +1,474 @@
+use anyhow::anyhow;
+use candle_core::{DType, Device, Shape, Tensor, WithDType};
+use candle_transformers::models::stable_diffusion::schedulers::Scheduler;
+use candle_transformers::models::stable_diffusion::utils::linspace;
+use log::error;
+
+/*
+Notes on LCM implementation:
+
+  - Robust technical comparison of samplers: https://stable-diffusion-art.com/samplers/
+  - Apple Swift LCM Implementation ticket: https://github.com/apple/ml-stable-diffusion/issues/319
+  - Reference Swift Implementation: https://github.com/GuernikaCore/Schedulers/blob/main/Sources/Schedulers/LCMScheduler.swift
+
+Candle is missing several "batteries" we'll have to implement, and some we might want to upstream:
+
+  - t[::-1] (syntax to reverse the tensor)
+
+  - torch/numpy.cumprod :
+      - https://numpy.org/doc/stable/reference/generated/numpy.cumprod.html
+      - https://pytorch.org/docs/stable/generated/torch.cumprod.html
+
+Remaining work:
+
+  - [ ] implement add_noise
+  - [ ] implement cumprod
+  - [ ] initialize step_index / begin_index
+  - [ ] find out how `set_timestamps` is called in diffusers and see if we want to change it to CTOR param in candle
+  - [ ] try to plug this into candle and run
+  - [ ] fix timesteps() method to cache values
+  - [ ] compare with diffusers
+  - [ ] compare with candle schedulers
+  - [ ] compare with swift schedulers
+  - [ ] test + unit test
+*/
+
+struct LcmScheduler {
+  alphas: Tensor,
+  alphas_cumprod: Tensor,
+  final_alpha_cumprod: Tensor,
+
+  betas: Tensor,
+
+  timesteps: Tensor,
+
+  // Standard deviation of the initial noise distribution
+  // NB: Only in diffusers, and seems to only hold the value "1.0". Swift implementation omits it.
+  init_noise_sigma: f64,
+
+  // TODO: This is set by the set_timesteps() method after construction in python.
+  //  We might want to handle this upfront in the constructor ourselves
+  num_inference_steps: Option<usize>,
+
+  _step_index: Option<usize>,
+  _begin_index: Option<usize>,
+}
+
+impl LcmScheduler {
+  pub fn new(
+    num_train_timestamps: i64,
+    beta_start: f64,
+    beta_end: f64,
+    beta_schedule: &str,
+    trained_betas: Option<Tensor>,
+    set_alpha_to_one: bool,
+    rescale_betas_zero_snr: bool,
+    device: &Device,
+  ) -> anyhow::Result<Self> {
+    let betas;
+
+    if let Some(trained) = trained_betas {
+      betas = trained;
+    } else {
+      betas = match beta_schedule {
+        "scaled_linear" => {
+          // this schedule is very specific to the latent diffusion model.
+          let t = linspace(
+            beta_start.powf(0.5),
+            beta_end.powf(0.5),
+            num_train_timestamps as usize
+          )?;
+          t.to_device(device)?
+        }
+        _ => {
+          return Err(anyhow!("schedule {beta_schedule} is not implemented"))
+        }
+      };
+    }
+
+    if rescale_betas_zero_snr {
+      return Err(anyhow!("rescale_betas_zero_snr is not used upstream"));
+    }
+
+    let alphas = (1.0 - &betas)?;
+
+    // TODO: Implement cumprod: https://github.com/huggingface/candle/issues/1646
+    //  https://numpy.org/doc/stable/reference/generated/numpy.cumprod.html
+    error!("THIS IS USING CUMSUM, NOT CUMPROD. WE NEED TO IMPLEMENT CUMPROD.");
+    // self.alphas_cumprod = torch.cumprod(self.alphas, dim=0)
+    let alphas_cumprod = alphas.cumsum(0)?;
+
+    // TODO: Check implementation
+    // At every step in ddim, we are looking into the previous alphas_cumprod
+    // For the final step, there is no previous alphas_cumprod because we are already at 0
+    // `set_alpha_to_one` decides whether we set this parameter simply to one or
+    // whether we use the final alpha of the "non-previous" one.
+    let final_alpha_cumprod = if set_alpha_to_one {
+      initialize_scalar_tensor(1.0, device)? // NB: `set_alpha_to_one` is false in python
+    } else {
+      alphas_cumprod.get(0)?
+    };
+
+    // standard deviation of the initial noise distribution
+    let init_noise_sigma = 1.0;
+
+    let timesteps = initialize_timesteps(num_train_timestamps, device)?;
+
+    Ok(Self {
+      alphas,
+      alphas_cumprod,
+      final_alpha_cumprod,
+      betas,
+      init_noise_sigma,
+      timesteps,
+      num_inference_steps: None,
+      _step_index: None,
+      _begin_index: None,
+    })
+  }
+
+  pub fn set_begin_index(&mut self, begin_index: usize) {
+    self._begin_index = Some(begin_index);
+  }
+
+  pub fn init_step_index(&mut self, timestep: usize) -> candle_core::Result<()> {
+    match self._begin_index {
+      None => {
+        todo!("implement begin index none branch")
+      }
+      Some(begin_index) => {
+        self._step_index = Some(begin_index);
+      }
+    }
+    Ok(())
+  }
+
+  pub fn set_timesteps(&mut self, num_inference_steps: usize, device: &Device) -> candle_core::Result<()> {
+    // NB: The diffusers version of this method passes `None` for `original_inference_steps` and `timesteps`.
+    // It passes strength = 1.0, and config.original_inference_steps = 50.
+    const STRENGTH : f64 = 1.0;
+    const CONFIG_ORIGINAL_INFERENCE_STEPS : usize = 50;
+    const CONFIG_NUM_TRAIN_TIMESTEPS : usize = 1000;
+
+    let original_steps = CONFIG_ORIGINAL_INFERENCE_STEPS;
+
+    // LCM Timesteps Setting
+    // The skipping step parameter k from the paper.
+    let k = (CONFIG_NUM_TRAIN_TIMESTEPS as f64 / original_steps as f64).floor();
+
+    let end = (original_steps as f64 * STRENGTH) as i64 + 1;
+    let lcm_origin_timesteps = ((Tensor::arange::<i64>(1, end, device)? * k)? - 1.0)?;
+
+    if num_inference_steps > CONFIG_NUM_TRAIN_TIMESTEPS {
+      return Err(candle_core::Error::Msg("num_inference_steps cannot be larger than train timesteps".to_string()));
+    }
+
+    let skipping_step = (lcm_origin_timesteps.dims().len() as f64 / num_inference_steps as f64).floor() as usize;
+
+    self.num_inference_steps = Some(num_inference_steps);
+    
+    // TODO: This is not efficient
+    let lcm_origin_timesteps = lcm_origin_timesteps.to_vec1::<i64>()?
+      .into_iter()
+      .map(i64::from)
+      .rev()
+      .collect::<Vec<i64>>();
+    
+    // TODO: This might not be exact. We should unit test this
+    let inference_indices = linspace(0.0, lcm_origin_timesteps.len() as f64, num_inference_steps)?;
+    
+    let inference_indices = inference_indices.floor()?
+      .to_dtype(DType::I64)?;
+    
+    let timestamps = {
+      // TODO: This code is awful
+      let inference_indices_t: Vec<usize> = inference_indices.to_vec1::<i64>()?
+        .into_iter()
+        .map(|n| n as usize)
+        .collect();
+
+      let mut timesteps: Vec<i64> = Vec::with_capacity(inference_indices.dims().len());
+      
+      for i in inference_indices_t {
+        if let Some(val) = lcm_origin_timesteps.get(i) {
+          timesteps.push(*val);
+        }
+      }
+      
+      let shape = Shape::from_dims(&[timesteps.len()]);
+      
+      Tensor::from_vec(timesteps, shape, device)?
+        .to_dtype(DType::I64)?
+        .to_device(device)?
+    };
+
+    self.timesteps = timestamps;
+
+    Ok(())
+  }
+
+}
+
+impl Scheduler for LcmScheduler {
+  fn timesteps(&self) -> &[usize] {
+    // TODO: We can't use the implementation from DDIM. This method requires
+    //  (1) an infallible response and (2) a reference we can't dynamically allocate. We must
+    //  cache this somewhere.
+    &[]
+  }
+
+  fn add_noise(&self, original_samples: &Tensor, noise: Tensor, timestep: usize) -> candle_core::Result<Tensor> {
+    // TODO: Make sure alphas_cumprod and timestep have same device and dtype as original_samples
+    //  Move the self.alphas_cumprod to device to avoid redundant CPU to GPU data movement
+    //  for the subsequent add_noise calls
+    let mut alphas_cumprod = self.alphas_cumprod.to_device(original_samples.device())?;
+    alphas_cumprod = alphas_cumprod.to_dtype(original_samples.dtype())?;
+    //let timesteps = timesteps.to_device(original_samples.device())?;
+
+    let sqrt_alpha_prod = alphas_cumprod.get(timestep)?.powf(0.5)?;
+    let mut sqrt_alpha_prod = sqrt_alpha_prod.flatten_all()?; // TODO: Verify that flatten_all works here
+
+
+    while sqrt_alpha_prod.dims().len() < original_samples.dims().len() {
+      // TODO: Verify that this works for `unsqueeze(-1)`
+      sqrt_alpha_prod = sqrt_alpha_prod.unsqueeze(sqrt_alpha_prod.dims().len())?;
+    }
+
+    let sqrt_one_minus_alpha_prod = (1.0 - alphas_cumprod.get(timestep)?)?.powf(0.5)?;
+    let mut sqrt_one_minus_alpha_prod = sqrt_one_minus_alpha_prod.flatten_all()?; // TODO: Verify flatten all works here.
+
+    while sqrt_one_minus_alpha_prod.dims().len() < original_samples.dims().len() {
+      // TODO: Verify that this works for `unsqueeze(-1)`
+      sqrt_one_minus_alpha_prod = sqrt_one_minus_alpha_prod.unsqueeze(sqrt_one_minus_alpha_prod.dims().len())?;
+    }
+
+    let noisy_samples = ((sqrt_alpha_prod * original_samples)? + (sqrt_one_minus_alpha_prod * noise)?)?;
+
+    Ok(noisy_samples)
+  }
+
+  fn init_noise_sigma(&self) -> f64 {
+    self.init_noise_sigma
+  }
+
+  /// Ensures interchangeability with schedulers that need to scale the denoising model input
+  /// depending on the current timestep. (For LCM, this is a pass through no-op!)
+  fn scale_model_input(&self, sample: Tensor, _timestep: usize) -> candle_core::Result<Tensor> {
+    Ok(sample) // NB: The diffusers scheduling_lcm.py implementation is a pass through no-op !
+  }
+
+  /// Predict the sample from the previous timestep by reversing the SDE. This function
+  /// propagates the diffusion process from the learned model outputs (most often the
+  /// predicted noise).
+  fn step(&mut self, model_output: &Tensor, timestep: usize, sample: &Tensor) -> candle_core::Result<Tensor> {
+
+    if self.num_inference_steps.is_none() {
+      return Err(candle_core::Error::Msg(
+        "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"
+          .to_string()));
+    }
+
+    if self._step_index.is_none() {
+      self.init_step_index(timestep)?;
+    }
+
+    let step_index = self._step_index.clone().expect("unsafe unwrap; should exist per above");
+
+    // 1. Get previous step value
+    let prev_step_index = step_index + 1;
+    let prev_timestep;
+
+    if prev_step_index < self.timesteps.elem_count() {
+      prev_timestep = self.timesteps.get(timestep)?.to_scalar::<i64>()? as usize;
+    } else {
+      prev_timestep = timestep;
+    }
+
+    // 2. Compute alphas, betas
+    let alpha_prod_t = self.alphas_cumprod.get(timestep)?;
+    let alpha_prod_t_prev = if prev_timestep >= 0 {
+      self.alphas_cumprod.get(prev_timestep)?
+    } else {
+      self.final_alpha_cumprod.clone()
+    };
+
+    let beta_prod_t = (1. - &alpha_prod_t)?;
+    let beta_prod_t_prev = (1. - &alpha_prod_t_prev)?;
+
+    // 3. Get scaling for boundary conditions
+    // NB: timestep_scaling seems to be always set to 10.0 in diffusers examples, but it is passed
+    // via a config object. Hardcoding this for now until we need to change it.
+    const TIMESTEP_SCALING : f64 = 10.0;
+    let (c_skip, c_out) = get_scalings_for_boundary_condition_discrete(timestep, TIMESTEP_SCALING);
+
+    // 4. Compute the predicted original sample x_0 based on the model parameterization
+    // NB: Prediction type is "epsilon" in the diffusers examples, but that is configurable.
+    // This is the only one we'll implement for now.
+    let predicted_original_sample = ((sample - (beta_prod_t.sqrt()? * model_output)?)? / &alpha_prod_t.sqrt()?)?;
+
+    // 5. (skip clip/threshold - not used in diffusers example)
+
+    // 6. Denoise model output using boundary conditions
+    let denoised = ((c_out * predicted_original_sample)? + (c_skip * sample)?)?;
+
+    // TODO: Step 7. We have to return the previous example somehow.
+    //  Diffusers tolerates it not being sent back, but the quality degrades as if one step is absent.
+    Ok(denoised)
+  }
+}
+
+fn initialize_scalar_tensor<D: WithDType>(value: D, device: &Device) -> anyhow::Result<Tensor> {
+  let scalar = Tensor::from_vec(vec![value], Shape::from(vec![]), device)?;
+  Ok(scalar)
+}
+
+// TODO(bt,2025-02-23): Use native implementations
+fn initialize_timesteps(num_train_timesteps: i64, device: &Device) -> anyhow::Result<Tensor> {
+  // Testing LCM scheduler assumptions:
+  // [::-1] is shorthand for reversing a numpy vector, eg. [0, 1,2,3,4] -> [4, 3, 2, 1, 0]
+  // self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy().astype(np.int64))
+  //let tensor = Tensor::arange::<i64>(0, 5, &Device::Cpu)?; // This works, but we can't reverse/flip it!
+
+  // https://github.com/tracel-ai/burn/pull/1468 flip impl? Will this work in place?
+  // https://github.com/huggingface/candle/issues/1875
+
+  let data = (0..num_train_timesteps)
+    .map(i64::from)
+    .rev()
+    .collect();
+
+  let shape = Shape::from_dims(&[num_train_timesteps as usize]);
+
+  let tensor = Tensor::from_vec(data, shape, device)?;
+
+  Ok(tensor)
+}
+
+fn get_scalings_for_boundary_condition_discrete(timestep: usize, timestep_scaling: f64) -> (f64, f64) {
+  let sigma_data = 0.5f64; // Default 0.5
+  let scaled_timestep = timestep as f64 * timestep_scaling;
+
+  let c_skip = sigma_data.powf(2.0) / (scaled_timestep.powf(2.0) + sigma_data.powf(2.0));
+  let c_out = scaled_timestep / (scaled_timestep.powf(2.0) + sigma_data.powf(2.0)).powf(0.5);
+
+  (c_skip, c_out)
+}
+
+// The Candle sources, and moreover, the Candle tests, are a great source of information for how the library works.
+//assert_eq!(t.i(..-1)?, 1.0);
+#[cfg(test)]
+mod tests {
+  use crate::ml::lcm_scheduler::{initialize_scalar_tensor, initialize_timesteps};
+  use crate::ml::lcm_scheduler::tests::test_helper_fn::*;
+  use candle_core::Device;
+
+  mod helper_function_unit_tests {
+    use crate::ml::lcm_scheduler::get_scalings_for_boundary_condition_discrete;
+    use super::*;
+
+    #[test]
+    fn test_initialize_scalar_tensor() -> anyhow::Result<()> {
+      let t = initialize_scalar_tensor(1.0, &Device::Cpu)?;
+      let empty: [usize; 0] = [];
+      assert_eq!(t.dims(), &empty);
+      assert_eq!(t.to_vec0::<f64>()?, 1.0);
+      Ok(())
+    }
+
+    #[test]
+    fn test_initialize_timesteps() -> anyhow::Result<()> {
+      let tensor = initialize_timesteps(5, &Device::Cpu)?;
+      assert_eq!(tensor.to_vec1::<i64>()?, &[4, 3, 2, 1,0]);
+      Ok(())
+    }
+
+    #[test]
+    fn test_get_scalings_for_boundary_condition_discrete() -> anyhow::Result<()> {
+      // Base cases
+      let v = get_scalings_for_boundary_condition_discrete(0, 0.0);
+      assert_eq!(v, (1.0, 0.0));
+      let v = get_scalings_for_boundary_condition_discrete(1, 0.0);
+      assert_eq!(v, (1.0, 0.0));
+      let v = get_scalings_for_boundary_condition_discrete(0, 1.0);
+      assert_eq!(v, (1.0, 0.0));
+
+      // Production code has "timestep_scaling" = 10.0
+      let v = get_scalings_for_boundary_condition_discrete(0, 10.0);
+      assert_eq!(v, (1.0, 0.0));
+
+      // Production code has "timestep_scaling" = 10.0
+      let v = get_scalings_for_boundary_condition_discrete(1, 10.0);
+      assert!((v.0 - 0.0024937655860349127).abs() < 0.01);
+      assert!((v.1 - 0.9987523388778445).abs() < 0.01);
+
+      // TODO: More test cases -
+      //let v = get_scalings_for_boundary_condition_discrete(10, 10.0);
+      //let v = get_scalings_for_boundary_condition_discrete(100, 10.0);
+
+      Ok(())
+    }
+  }
+
+  mod confirm_various_pytorch_behaviors {
+    use candle_core::IndexOp;
+    use super::*;
+
+    // NB: Non-unit tests, just to test understanding while porting code
+
+    #[test]
+    fn unsqueeze_zero() -> anyhow::Result<()> {
+      let t = tensor_1234()?;
+      let x = t.unsqueeze(0)?;
+      assert_eq!(x.to_vec2::<i64>()?, &[&[1, 2, 3, 4]]);
+      Ok(())
+    }
+
+    #[test]
+    fn unsqueeze_simulating_negative_one() -> anyhow::Result<()> {
+      let t = tensor_1234()?;
+      // NB: It looks like this matches the behavior of unsqueeze(-1)
+      // Per: https://pytorch.org/docs/stable/generated/torch.unsqueeze.html
+      let x = t.unsqueeze(t.dims().len())?;
+      assert_eq!(x.to_vec2::<i64>()?, &[&[1],&[2],&[3],&[4]]);
+      Ok(())
+    }
+
+    #[test]
+    fn one_minus_vector() -> anyhow::Result<()> {
+      let t = tensor_01234()?;
+      let x = (1. - t)?;
+      assert_eq!(x.rank(), 1); // NB: 1-dimensional output
+      assert_eq!(x.to_vec1::<i64>()?, &[1, 0, -1, -2, -3]);
+      Ok(())
+    }
+    
+    // #[test]
+    // fn reverse_vector() -> anyhow::Result<()> {
+    //   let t = tensor_1234()?;
+    //   let x = t.i(5..0)?;
+    //   assert_eq!(x.rank(), 1); // NB: 1-dimensional output
+    //   assert_eq!(x.to_vec1::<i64>()?, &[1, 0, -1, -2, -3]);
+    //   Ok(())
+    // }
+  }
+
+  pub mod test_helper_fn {
+    use candle_core::{Device, Shape, Tensor};
+
+    pub fn tensor_1234() -> anyhow::Result<Tensor> {
+      // Return an example tensor
+      let data: Vec<i64> = vec![1, 2, 3, 4];
+      let t = Tensor::from_vec(data, Shape::from(vec![4]), &Device::Cpu)?;
+      assert_eq!(t.to_vec1::<i64>()?, &[1, 2, 3, 4]);
+      Ok(t)
+    }
+
+    pub fn tensor_01234() -> anyhow::Result<Tensor> {
+      // Return an example tensor
+      let data: Vec<i64> = vec![0, 1, 2, 3, 4];
+      let t = Tensor::from_vec(data, Shape::from(vec![5]), &Device::Cpu)?;
+      assert_eq!(t.to_vec1::<i64>()?, &[0, 1, 2, 3, 4]);
+      Ok(t)
+    }
+  }
+}
@@ -1,4 +1,6 @@
+pub mod cumprod;
 pub mod image;
+pub mod lcm_scheduler;
 pub mod model_cache;
 pub mod model_file;
 pub mod models;
@@ -4525,6 +4525,8 @@
    },
    "node_modules/npm/node_modules/@isaacs/cliui/node_modules/string-width": {
      "version": "5.1.2",
+      "resolved": "https://registry.npmjs.org/string-width/-/string-width-5.1.2.tgz",
+      "integrity": "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA==",
      "dev": true,
      "inBundle": true,
      "license": "MIT",
@@ -5265,6 +5267,8 @@
    },
    "node_modules/npm/node_modules/cross-spawn/node_modules/which": {
      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz",
+      "integrity": "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA==",
      "dev": true,
      "inBundle": true,
      "license": "ISC",
@@ -5313,6 +5317,8 @@
    },
    "node_modules/npm/node_modules/debug/node_modules/ms": {
      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/ms/-/ms-2.1.2.tgz",
+      "integrity": "sha512-sGkPx+VjMtmA6MX27oA4FBFELFCZZ4S4XqeGOXCv68tT+jb3vk/RyaKWP0PTKyWtmLSM0b+adUTEvbs1PEaH2w==",
      "dev": true,
      "inBundle": true,
      "license": "MIT"
@@ -7139,6 +7145,8 @@
    },
    "node_modules/npm/node_modules/wrap-ansi-cjs/node_modules/ansi-styles": {
      "version": "4.3.0",
+      "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-4.3.0.tgz",
+      "integrity": "sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg==",
      "dev": true,
      "inBundle": true,
      "license": "MIT",
@@ -7176,6 +7184,8 @@
    },
    "node_modules/npm/node_modules/wrap-ansi/node_modules/string-width": {
      "version": "5.1.2",
+      "resolved": "https://registry.npmjs.org/string-width/-/string-width-5.1.2.tgz",
+      "integrity": "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA==",
      "dev": true,
      "inBundle": true,
      "license": "MIT",
@@ -27,8 +27,9 @@ import { NavigateFunction } from "react-router-dom";
 import { LoadingVideosProvider } from "./EngineUtitlities/LoadingVideosProvider";

 import { VideoExtractionHandler } from "./EngineUtitlities/VideoExtractionHandler/VideoExtractionHandler";
-import { RealTimeDrawEngine, ShapeType } from "./RenderingPrimitives/RealTimeDrawEngine";
-
+import { RealTimeDrawEngine } from "./RenderingPrimitives/RealTimeDrawEngine";
+import { NodeColor } from "~/signals/uiEvents/toolbarNode";
+import { ShapeType } from "./Nodes";
 // for testing loading files from system
 // import { FileUtilities } from "./FileUtilities/FileUtilities";

@@ -180,8 +181,8 @@ export class Engine {
    this.setupEventSystem();
    this.setAppMode(AppModes.SELECT);

-    
- 
+
+
  }


@@ -364,7 +365,7 @@ export class Engine {
    // Listen to Toolbar Main
    uiEvents.toolbarMain.UNDO.onClick(() => this.undoStackManager.undo());
    uiEvents.toolbarMain.REDO.onClick(() => this.undoStackManager.redo());
-    
+
    uiEvents.toolbarMain.SAVE.onClick(async (/*event*/) => {
      await this.realTimeDrawEngine.saveOutput();

@@ -398,7 +399,7 @@ export class Engine {
      this.addImage(image);
    });

-  
+

    uiEvents.onAddTextToEngine((textdata) => {
      this.addText(textdata);
@@ -430,7 +431,7 @@ export class Engine {
        }
      }
    });
-    
+
    uiEvents.promptEvents.onPromptStrengthChanged((strength) => {
      this.realTimeDrawEngine.currentStrength = strength;
    });
@@ -439,21 +440,32 @@ export class Engine {
      this.realTimeDrawEngine.currentPrompt = prompt;
    });

-    uiEvents.onAddShapeToEngine((shapeData)=> {
-
+    uiEvents.onAddShapeToEngine((shapeData) => {
      switch (shapeData.shape) {
        case "circle":
-          this.addShape(ShapeType.Circle, 100);
+          this.addShape(ShapeType.CIRCLE, 100);
          break;
-        case "square": 
-          this.addShape(ShapeType.Square, 100);
+        case "square":
+          this.addShape(ShapeType.SQUARE, 100);
          break;
        case "triangle":
-          this.addShape(ShapeType.Triangle, 100);
+          this.addShape(ShapeType.TRIANGLE, 100);
          break;
      }
    });

+    uiEvents.toolbarNode.color.onConfirmChanged((nodeColor) => {
+      console.log("Color change event triggered with:", nodeColor);
+      if (!nodeColor) {
+        console.warn("nodeColor is undefined or null");
+        return;
+      }
+      if (!nodeColor.kNodeId) {
+        console.warn("nodeColor.kNodeId is undefined or null");
+        return;
+      }
+      this.changeNodeColor(nodeColor);
+    })
  }

  disableAllButtons() {
@@ -489,7 +501,7 @@ export class Engine {
  }

  // Sandbox is quickly a way to test your idea.
-  public async sandbox() {}
+  public async sandbox() { }

  public onMessage(event: MessageEvent) {
    console.log("Message From Shared Worker");
@@ -536,6 +548,40 @@ export class Engine {
    this.addKeyboardShortcuts();
  }

+  private changeNodeColor(nodeColor: NodeColor) {
+    console.log('Changing node color:', nodeColor);
+    // Find the node that is selected with the id
+    const idSelector = '#' + nodeColor.kNodeId;
+    const selectedNode = this.mediaLayer.findOne(idSelector);
+    console.log('Selected node:', selectedNode);
+    console.log('ID selector:', idSelector);
+    console.log('Media layer:', this.mediaLayer);
+    // TODO: Change the color of the node
+    // Turns out shapes are image nodes... how do we change the image's fill??
+    if (selectedNode) {
+      // Get the shape node from the real time drawing engine's image nodes
+      const shapeNode = this.realTimeDrawEngine.findImageNodeById(nodeColor.kNodeId);
+      if (shapeNode && shapeNode instanceof ShapeNode) {
+        // Create new shape node with updated color
+        const newShapeNode = new ShapeNode({
+          canvasPosition: this.realTimeDrawEngine.captureCanvas.position(),
+          canvasSize: this.realTimeDrawEngine.captureCanvas.size(), 
+          shapeType: shapeNode.shapeType,
+          size: shapeNode.size,
+          color: nodeColor.color,
+          mediaLayerRef: this.mediaLayer,
+          selectionManagerRef: this.selectionManager
+        });
+        newShapeNode.kNode.position(shapeNode.kNode.position());
+        newShapeNode.kNode.zIndex(shapeNode.kNode.zIndex());
+        
+        // Remove old node and add new one
+        shapeNode.kNode.destroy();
+        this.commandManager.createNode(newShapeNode);
+      }
+    }
+  }
+
  public addText(textNodeData: TextNodeData) {
    const textNode = new TextNode({
      textNodeData: textNodeData,
@@ -558,8 +604,10 @@ export class Engine {
      selectionManagerRef: this.selectionManager
    });
    shapeNode.kNode.zIndex(1); // Replace desiredZIndex with a number
-   
+
    this.commandManager.createNode(shapeNode);
+    console.debug("Added shapenode:", shapeNode);
+    console.debug("Added node's ID:", shapeNode.kNode._id);
    //this.realTimeDrawEngine.addNodes(shapeNode);
  }

@@ -617,7 +665,7 @@ export class Engine {
          if (
            longestVideoNode === undefined ||
            node.videoComponent.duration >
-              longestVideoNode.videoComponent.duration
+            longestVideoNode.videoComponent.duration
          ) {
            longestVideoNode = node;
          }
@@ -58,6 +58,10 @@ export class CommandManager {
      renderEngineRef: this.renderEngineRef,
    });
    this.undoStackManagerRef.executeCommand(command);
+
+    // Set the kNode's manual id to same as kNode's internal _id
+    // This helps identify the kNode in the Konva layer with find
+    node.kNode.id(node.kNode._id.toString());
  }
  deleteNodes() {
    const nodes = this.selectionManagerRef.getSelectedNodes();
@@ -1,7 +1,6 @@
 import Konva from "konva";
 import { SelectionManager } from "../NodesManagers";
 import { Position, Size, NodeData, TransformationData } from "../types";
-import { BaseNode } from "./BaseNode";
 import { NodeType } from "./constants";
 import { NodeUtilities } from "./NodeUtilities";
 import { NetworkedNode } from "./NetworkedNode";
@@ -24,6 +23,13 @@ interface ShapeNodeConstructor {
 }

 export class ShapeNode extends NetworkedNode {
+  
+  retry(): void {
+    throw new Error("Method not implemented.");
+  }
+
+  public shapeType: ShapeType;
+  public size: number;

  constructor({
    canvasPosition,
@@ -159,6 +165,9 @@ export class ShapeNode extends NetworkedNode {
      kNode: shape,
    });

+    this.shapeType = shapeType;
+    this.size = size;
+
    // Add shape to group
    const centerPosition = NodeUtilities.positionNodeOnCanvasCenter({
      canvasOffset: canvasPosition,
@@ -3,4 +3,4 @@ export { BaseNode } from "./BaseNode";
 export { ImageNode } from "./ImageNode";
 export { VideoNode } from "./VideoNode";
 export { TextNode } from "./TextNode";
-export { ShapeNode } from "./ShapeNode";
+export { ShapeNode , ShapeType} from "./ShapeNode";
@@ -9,6 +9,7 @@ import {
  calculateContextualsPosition,
  getImageNodeButtonStates,
  getMultiSelectButtonStates,
+  getShapeNodeButtonStates,
  getTextNodeButtonStates,
  getVideoNodeButtonStates,
 } from "./ToolbarNodeUtilities";
@@ -271,22 +272,31 @@ export class SelectionManager {
      return; // no node
    }
    if (this.selectedNodes.size === 1) {
-      if (node instanceof ImageNode || node instanceof ShapeNode) {
+      if (node instanceof ImageNode) {
        showOrUpdate({
+          knodeIds: [node.kNode.id()],
          locked: node.isLocked(),
          buttonStates: getImageNodeButtonStates({ locked: node.isLocked() }),
+        });
+      }
+      else if (node instanceof ShapeNode) {
+        console.debug("Selected node is of type ShapeNode", node.kNode.id())
+        showOrUpdate({
+          knodeIds: [node.kNode.id()],
+          locked: node.isLocked(),
+          buttonStates: getShapeNodeButtonStates({ locked: node.isLocked() }),
          color: node.getNodeData({ x: 0, y: 0 })?.textNodeData?.color ?? "#000000",
        });
      }
-      if (node instanceof TextNode) {
+      else if (node instanceof TextNode) {
        showOrUpdate({
-          // TODO: Add ID to identify/mutate the color?
+          knodeIds: [node.kNode.id()],
          locked: node.isLocked(),
          buttonStates: getTextNodeButtonStates({ locked: node.isLocked() }),
-        
+          color: node.getNodeData({ x: 0, y: 0 })?.textNodeData?.color ?? "#000000",
        });
      }
-      if (node instanceof VideoNode) {
+      else if (node instanceof VideoNode) {
        showOrUpdate({
          locked: node.isLocked(),
          buttonStates: getVideoNodeButtonStates({ locked: node.isLocked() }),
@@ -317,7 +327,7 @@ export class SelectionManager {
      this.hideContextComponents();
      return; // no nodes
    }
-  
+
    // console.log("SelectionManager > updateContextComponents for node:", node);
    const coord = calculateContextualsPosition(
      this.nodeTransformerRef.getKonvaNode(),
@@ -152,6 +152,50 @@ export function getVideoNodeButtonStates(
    {} as ContextualToolbarProps["buttonStates"],
  );
 }
+
+export function getShapeNodeButtonStates(
+  props: { locked?: boolean | "unknown" } = {},
+) {
+  const ButtonNames = ToolbarNodeButtonNames;
+  return Object.values(ButtonNames).reduce(
+    (buttonStates, buttonName) => {
+      // transform button depends on locked state
+      if (props.locked !== undefined && buttonName === ButtonNames.TRANSFORM) {
+        buttonStates.TRANSFORM = {
+          disabled: props.locked === "unknown" || props.locked === true,
+          hidden: false,
+          active: true,
+        };
+        return buttonStates;
+      }
+
+      // hidden buttons
+      if (
+        buttonName === ButtonNames.AI_STYLIZE ||
+        buttonName === ButtonNames.SEGMENTATION ||
+        buttonName === ButtonNames.DOWNLOAD ||
+        buttonName === ButtonNames.CHROMA
+      ) {
+        buttonStates[buttonName] = {
+          disabled: true,
+          hidden: true,
+          active: false,
+        };
+        return buttonStates;
+      }
+
+      // all other buttons
+      buttonStates[buttonName] = {
+        disabled: false,
+        hidden: false,
+        active: false,
+      };
+      return buttonStates;
+    },
+    {} as ContextualToolbarProps["buttonStates"],
+  );
+}
+
 export function getMultiSelectButtonStates(
  props: { locked?: boolean | "unknown" } = {},
 ) {
@@ -6,18 +6,14 @@ import { Group } from "konva/lib/Group";
 import { invoke } from "@tauri-apps/api/core";

 import { FileUtilities } from "../FileUtilities/FileUtilities";
-import { ImageNode, VideoNode, TextNode, ShapeNode } from "../Nodes";
+import { ImageNode, VideoNode, TextNode, ShapeNode, ShapeType } from "../Nodes";
 import { MediaNode } from "../types";

 import { RenderTask } from "./RenderTask";
 import { OffScreenSceneCanvas } from "./OffScreenSceneCanvas";

 // https://www.aiseesoft.com/resource/phone-aspect-ratio-screen-resolution.html#:~:text=16%3A9%20Aspect%20Ratio
-export enum ShapeType {
-  Square = "square",
-  Triangle = "triangle", 
-  Circle = "circle"
-}
+
 export class RealTimeDrawEngine {
  private videoNodes: VideoNode[];
  private imageNodes: (ImageNode | TextNode | ShapeNode)[];
@@ -80,7 +76,6 @@ export class RealTimeDrawEngine {
    this.offScreenCanvas.width = this.width;
    this.offScreenCanvas.height = this.height;

-
    // this is the whole canvas
    this.mediaLayerRef = mediaLayerRef;

@@ -123,8 +118,79 @@ export class RealTimeDrawEngine {
    // send back
    this.captureCanvas.setZIndex(0);
    this.previewCanvas.setZIndex(1);
+    // Add mouse events for preview canvas copying
+    //this.previewCopyListener();
+
  }

+  public previewCopyListener() {
+    this.previewCanvas.on('mousedown touchstart', () => {
+      if (!this.outputBitmap) {
+        console.log("No preview image to copy"); 
+        return;
+      }
+      
+      // TODO create it as a node.
+      
+      // const imageNode = new ImageNode({
+      //   mediaLayerRef: this.mediaLayer,
+      //   canvasPosition: this.renderEngine.captureCanvas.position(),
+      //   canvasSize: this.renderEngine.captureCanvas.size(),
+      //   imageFile: imageFile,
+      //   selectionManagerRef: this.selectionManager,
+      // });
+
+      // Create draggable preview copy
+      const previewCopy = new Konva.Image({
+        x: this.previewCanvas.x(),
+        y: this.previewCanvas.y(),
+        width: this.width,
+        height: this.height,
+        image: this.outputBitmap,
+        draggable: true,
+        listening: true
+      });
+
+      this.mediaLayerRef.add(previewCopy);
+      previewCopy.moveToTop();
+      this.mediaLayerRef.draw();
+
+      // Start dragging immediately
+      previewCopy.startDrag();
+
+      // Handle drag events
+      previewCopy.on('dragmove', () => {
+        this.mediaLayerRef.draw();
+      });
+
+      previewCopy.on('dragend', () => {
+        const previewBox = previewCopy.getClientRect();
+        const captureBox = this.captureCanvas.getClientRect();
+        
+        if (Konva.Util.haveIntersection(previewBox, captureBox)) {
+          // Snap to capture canvas position
+          previewCopy.position({
+            x: this.captureCanvas.x(),
+            y: this.captureCanvas.y()
+          });
+          this.mediaLayerRef.batchDraw();
+        } else {
+          // Remove if dropped outside capture area
+          previewCopy.destroy();
+          this.mediaLayerRef.batchDraw();
+        }
+      });
+    });
+  }
+
+  public findImageNodeById(id: string): (ImageNode | TextNode | ShapeNode | undefined) {
+    return this.imageNodes.find(node => {
+      if (node.kNode) {
+        return node.kNode.id() === id;
+      }
+      return false;
+    });
+  }
  async updateCaptureCanvas(
    width: number | undefined,
    height: number | undefined,
@@ -467,7 +533,7 @@ export class RealTimeDrawEngine {
    })) as ImageBitmap;

    // Test code
-    if (true) {
+    if (false) {
      this.outputBitmap = bitmap;
      this.previewCanvas.image(bitmap);
      this.isProcessing = false;
@@ -26,6 +26,10 @@ export type VideoNodeData = {
  extractionUrl?: string;
 };

+export type ShapeNodeData = {
+  shape: "triangle" | "square" | "circle";
+}
+
 export type NodeData = {
  type: NodeType;
  transform: TransformationData;
@@ -50,6 +50,20 @@ export const ContextualToolbarNode = () => {
    };
  }, []);

+  const handleColorChange = (color: string) => {
+    // Don't do anything if no node is known to be bound
+    if (uiAccess.toolbarNode.signal.value.knodeIds.length < 1) {
+      return;
+    }
+
+    // Update the UI component
+    uiAccess.toolbarNode.setColor(color);
+
+    // Signal the engine with the node ID (just grab the first -and expected only- node)
+    const nodeID = uiAccess.toolbarNode.signal.value.knodeIds[0];
+    dispatchUiEvents.toolbarNode.setSelectedColor({ kNodeId: nodeID, color });
+  }
+
  const boundedTopPosition = Math.min(position.y, winSize.height - 164);
  return (
    <Transition
@@ -72,7 +86,7 @@ export const ContextualToolbarNode = () => {
          dispatchUiEvents.toolbarNode.lock(e);
        }}
        color={uiAccess.toolbarNode.signal.value.color}
-        onColorChange={(color) => { uiAccess.toolbarNode.setColor(color) }}
+        onColorChange={handleColorChange}
      />
    </Transition>
  );
@@ -78,7 +78,7 @@ const Landing = () => {
              </div>
            </div>
          </div>
-          <div className="col-span-12 mt-12 aspect-video w-full transform overflow-hidden rounded-xl border border-white/[15%] bg-transparent md:mt-16 xl:col-span-9 xl:col-start-4 xl:mt-0">
+          <div className="col-span-12 mt-12 aspect-video w-full transform overflow-hidden rounded-xl border border-white/[16%] bg-transparent md:mt-16 xl:col-span-9 xl:col-start-4 xl:mt-0">
            <img
              src="/images/landing_hero.png"
              alt="AI Video Creation"
@@ -118,6 +118,52 @@ const Landing = () => {
            </div>
          ))}
        </div>
+
+        {/* Installation Steps Section */}
+        <div className="mt-36">
+          <h1 className="mb-12 text-5xl font-bold">
+            How to install Mira AI Editor
+          </h1>
+          <div className="grid gap-6 md:grid-cols-3">
+            <div className="rounded-xl bg-[#1C1C20] p-8">
+              <div className="mb-4 w-fit rounded-full bg-white/15 px-3 py-1 text-sm font-medium text-white">
+                STEP 1
+              </div>
+              <h3 className="mb-4 text-2xl font-semibold">Download the app</h3>
+              <p className="mb-6 text-gray-400">
+                Download and install our application to start creating amazing
+                AI-powered content.
+              </p>
+              <Button className="rounded-lg bg-[#2D81FF] px-4 py-2 text-sm font-medium hover:bg-[#438AF6]">
+                Download App
+              </Button>
+            </div>
+
+            <div className="rounded-xl bg-[#1C1C20] p-8">
+              <div className="mb-4 w-fit rounded-full bg-white/15 px-3 py-1 text-sm font-medium text-white">
+                STEP 2
+              </div>
+              <h3 className="mb-4 text-2xl font-semibold">Create an account</h3>
+              <p className="mb-6 text-gray-400">
+                Sign up for an account to access all features and start your
+                journey.
+              </p>
+              <Button className="text-sm font-medium" variant="secondary">
+                Sign up
+              </Button>
+            </div>
+
+            <div className="rounded-xl bg-[#1C1C20] p-8">
+              <div className="mb-4 w-fit rounded-full bg-white/15 px-3 py-1 text-sm font-medium text-white">
+                STEP 3
+              </div>
+              <h3 className="mb-4 text-2xl font-semibold">Start creating</h3>
+              <p className="mb-6 text-gray-400">
+                Begin creating with our realtime AI editor!
+              </p>
+            </div>
+          </div>
+        </div>
      </div>

      <Footer />
@@ -97,7 +97,7 @@ export const ToolbarNode = ({
          );
        } else {
          return (
-            <ColorPicker color={color} onChange={onColorChange} faIcon={faPalette} borderStyle="" />
+            <ColorPicker color={color} onChange={onColorChange} faIcon={faPalette} borderStyle="" key={idx} />
          )
        }
      })}
@@ -10,7 +10,7 @@ type ButtonStates = {
  };
 };
 export interface ContextualToolbarProps extends ContextualUi {
-  knodeIds: number[];
+  knodeIds: string[];
  disabled: boolean;
  downloadUrl?: string;
  locked: boolean | "unknown";
@@ -1,5 +1,5 @@
 import { signal, effect } from "@preact/signals-react";
-import { TextNodeData } from "~/KonvaApp/types";
+import { ShapeNodeData, TextNodeData } from "~/KonvaApp/types";

 // ADDING IMAGES
 const stagedImage = signal<File | null>(null);
@@ -50,8 +50,6 @@ const onAddTextToEngine = (callback: (data: TextNodeData) => void) => {
 };

 // Add shapes
-// TODO: Remove this line and replace with actual shape data that engine needs
-type ShapeNodeData = any;
 const stagedShape = signal<ShapeNodeData | null>(null);
 const addShapeToEngine = (data: ShapeNodeData) => {
  stagedShape.value = data;
@@ -44,6 +44,11 @@ const buttonEventsRecords = Object.values(ButtonNames).reduce(

 const buttonEventsHandlers = Object.values(ButtonNames).reduce(
  (acc, buttonName) => {
+    // We define custom events/handlers for color changes
+    if (buttonName === ButtonNames.COLOR) {
+      return acc;
+    }
+
    acc[buttonName] = {
      onClick: (callback: MouseEventHandler<HTMLButtonElement>) => {
        const { eventSignal, effectCleanup, lastEventTimestamp } =
@@ -111,9 +116,27 @@ const retryEventHandler = (callback: MouseEventHandler<HTMLButtonElement>) => {
 const retryDispatcher = (e: React.MouseEvent<HTMLButtonElement>) => {
  retryEvent.value = e;
 };
+
+export type NodeColor = {
+  kNodeId: string;
+  color: string;
+}
+const selectedColorEvent = signal<NodeColor | null>();
+const setSelectedColor = (nodeColor: NodeColor) => {
+  selectedColorEvent.value = nodeColor;
+}
+const onSelectedColorChanged = (callback: (color: NodeColor) => void) => {
+  effect(() => {
+    if (selectedColorEvent.value) {
+      callback(selectedColorEvent.value);
+    }
+  });
+};
+
 export const dispatchers = {
  lock: lockDispatcher,
  retry: retryDispatcher,
+  setSelectedColor,
  ...buttonDispatchers,
 };
 export const eventsHandlers = {
@@ -123,5 +146,8 @@ export const eventsHandlers = {
  retry: {
    onClick: retryEventHandler,
  },
+  color: {
+    onConfirmChanged: onSelectedColorChanged,
+  },
  ...buttonEventsHandlers,
 };
Author	SHA1	Message	Date
Brandon Thomas	b6a9d52e19	implement cumprod	2025-02-25 00:25:19 -05:00
Brandon Thomas	97fe9f90c9	more work on timestamps (WIP)	2025-02-24 19:36:31 -05:00
Brandon Thomas	5cec883b15	cleanup	2025-02-24 17:48:24 -05:00
Brandon Thomas	70fa084e30	step() mostly done	2025-02-24 17:45:08 -05:00
Brandon Thomas	8111c84d12	implementing step()	2025-02-24 17:22:25 -05:00
Brandon Thomas	a55e3f84dc	notes	2025-02-24 02:07:48 -05:00
Brandon Thomas	221861eb9f	clarify	2025-02-23 23:08:14 -05:00
Brandon Thomas	e9e6c66ba1	add_noise WIP	2025-02-23 22:38:31 -05:00
Brandon Thomas	d2da91a8bd	implement constructor, tests	2025-02-23 20:53:19 -05:00
Brandon Thomas	ee5efc378e	implement timestep initialization	2025-02-23 14:56:49 -05:00
Brandon Thomas	dbd06ee7b3	LCM implementation (wip)	2025-02-23 14:37:24 -05:00
Michael Chung	6077232cd3	Hide Preview Drag Layer as it is not done.	2025-02-21 17:21:43 -05:00
Michael Chung	f013373180	Copy Shift Still needs some UX work but it does work. Need to store it as a image node.	2025-02-21 00:39:59 -05:00
Michael Chung	f0c1fcf516	Got the color changes to work.	2025-02-20 22:34:17 -05:00
Brandon Thomas	9f392de9c5	bump packages to enable windows builds	2025-02-20 18:10:07 -05:00
BFlat	f5fb340de9	landing hero update (#419 )	2025-02-21 01:49:28 +07:00
Tanish Manku	0392bda03c	Forward color picker events to engine (#418 )	2025-02-20 11:38:29 -05:00