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Prince Canuma
2026-03-18 17:40:05 +01:00
parent 78bcfba31b
commit 17397da70c
77 changed files with 4125 additions and 1655 deletions
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9
mlx_video/models/ltx_2/video_vae/ops.py
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@@ -1,6 +1,5 @@
"""Operations for Video VAE."""
from typing import List, Tuple
import mlx.core as mx
import mlx.nn as nn
@@ -32,7 +31,9 @@ def patchify(x: mx.array, patch_size_hw: int = 4, patch_size_t: int = 1) -> mx.a
new_c = c * patch_size_hw * patch_size_hw * patch_size_t
# Reshape: (B, C, F, H, W) -> (B, C, F/pt, pt, H/ph, ph, W/pw, pw)
x = mx.reshape(x, (b, c, new_f, patch_size_t, new_h, patch_size_hw, new_w, patch_size_hw))
x = mx.reshape(
x, (b, c, new_f, patch_size_t, new_h, patch_size_hw, new_w, patch_size_hw)
)
# Permute: (B, C, F', pt, H', ph, W', pw) -> (B, C, pt, pw, ph, F', H', W')
# PyTorch einops uses (c, p, r, q) = (c, temporal, width, height), so we need pw before ph
@@ -101,7 +102,7 @@ class PerChannelStatistics(nn.Module):
Normalized tensor
"""
# Expand mean and std for broadcasting: (C,) -> (1, C, 1, 1, 1)
dtype = x.dtype
dtype = x.dtype
# Cast to float32 for precision
mean = self.mean.astype(mx.float32).reshape(1, -1, 1, 1, 1)
std = self.std.astype(mx.float32).reshape(1, -1, 1, 1, 1)
@@ -117,7 +118,7 @@ class PerChannelStatistics(nn.Module):
Returns:
Denormalized tensor
"""
dtype = x.dtype
dtype = x.dtype
# Cast to float32 for precision
mean = self.mean.astype(mx.float32).reshape(1, -1, 1, 1, 1)
std = self.std.astype(mx.float32).reshape(1, -1, 1, 1, 1)