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Merged
leejet merged 2 commits into from
Mar 1, 2026
Merged

refactor: reuse DiT's patchify/unpatchify functions #1304

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15ac9da
refactor: reuse DiT's patchify/unpatchify functions
leejet Mar 1, 2026
1ae49b0
remove MMDiT::unpatchify
leejet Mar 1, 2026
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102 changes: 7 additions & 95 deletions src/anima.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -6,81 +6,13 @@
#include <utility>
#include <vector>

#include "common.hpp"
#include "common_block.hpp"
#include "flux.hpp"
#include "ggml_extend.hpp"
#include "rope.hpp"

namespace Anima {
constexpr int ANIMA_GRAPH_SIZE = 65536;

__STATIC_INLINE__ struct ggml_tensor* patchify_2d(struct ggml_context* ctx,
struct ggml_tensor* x,
int64_t patch_size) {
// x: [W*r, H*q, T, C]
// return: [W, H, T, C*q*r]
if (patch_size == 1) {
return x;
}
GGML_ASSERT(x->ne[2] == 1);

int64_t W = x->ne[0];
int64_t H = x->ne[1];
int64_t T = x->ne[2];
int64_t C = x->ne[3];
int64_t p = patch_size;
int64_t h = H / p;
int64_t w = W / p;

GGML_ASSERT(T == 1);
GGML_ASSERT(h * p == H && w * p == W);

// Reuse Flux patchify layout on a [W, H, C, N] view.
x = ggml_reshape_4d(ctx, x, W, H, C, T); // [W, H, C, N]

// Flux patchify: [N, C, H, W] -> [N, h*w, C*p*p]
x = ggml_reshape_4d(ctx, x, p, w, p, h * C * T); // [p, w, p, h*C*N]
x = ggml_ext_cont(ctx, ggml_permute(ctx, x, 0, 2, 1, 3)); // [p, p, w, h*C*N]
x = ggml_reshape_4d(ctx, x, p * p, w * h, C, T); // [p*p, h*w, C, N]
x = ggml_ext_cont(ctx, ggml_permute(ctx, x, 0, 2, 1, 3)); // [p*p, C, h*w, N]
x = ggml_reshape_3d(ctx, x, p * p * C, w * h, T); // [C*p*p, h*w, N]

// Return [w, h, T, C*p*p]
x = ggml_reshape_4d(ctx, x, p * p * C, w, h, T); // [C*p*p, w, h, N]
x = ggml_ext_cont(ctx, ggml_permute(ctx, x, 3, 0, 1, 2)); // [w, h, N, C*p*p]
return x;
}

__STATIC_INLINE__ struct ggml_tensor* unpatchify_2d(struct ggml_context* ctx,
struct ggml_tensor* x,
int64_t patch_size) {
// x: [W, H, T, C*q*r]
// return: [W*r, H*q, T, C]
if (patch_size == 1) {
return x;
}
GGML_ASSERT(x->ne[2] == 1);

int64_t w = x->ne[0];
int64_t h = x->ne[1];
int64_t T = x->ne[2];
int64_t p = patch_size;
int64_t nm = p * p;
int64_t Cp = x->ne[3];
int64_t C = Cp / nm;
int64_t W = w * p;
int64_t H = h * p;

GGML_ASSERT(T == 1);
GGML_ASSERT(C * nm == Cp);

// [w, h, 1, C*p*p] -> [W, H, 1, C]
x = ggml_reshape_4d(ctx, x, w, h * C, p, p); // [w, h*C, p2, p1]
x = ggml_ext_cont(ctx, ggml_ext_torch_permute(ctx, x, 2, 0, 3, 1)); // [p2, w, p1, h*C]
x = ggml_reshape_4d(ctx, x, W, H, T, C); // [W, H, 1, C]
return x;
}

__STATIC_INLINE__ struct ggml_tensor* apply_gate(struct ggml_context* ctx,
struct ggml_tensor* x,
struct ggml_tensor* gate) {
Expand Down Expand Up @@ -491,7 +423,7 @@ namespace Anima {
int64_t text_embed_dim = 1024;
int64_t num_heads = 16;
int64_t head_dim = 128;
int64_t patch_size = 2;
int patch_size = 2;
int64_t num_layers = 28;
std::vector<int> axes_dim = {44, 42, 42};
int theta = 10000;
Expand Down Expand Up @@ -533,24 +465,10 @@ namespace Anima {
int64_t W = x->ne[0];
int64_t H = x->ne[1];

x = ggml_reshape_4d(ctx->ggml_ctx, x, x->ne[0], x->ne[1], 1, x->ne[2] * x->ne[3]); // [N*C, T, H, W] style

int64_t pad_h = (patch_size - H % patch_size) % patch_size;
int64_t pad_w = (patch_size - W % patch_size) % patch_size;
if (pad_h > 0 || pad_w > 0) {
x = ggml_ext_pad(ctx->ggml_ctx, x, static_cast<int>(pad_w), static_cast<int>(pad_h), 0, 0, ctx->circular_x_enabled, ctx->circular_y_enabled);
}

auto padding_mask = ggml_ext_zeros(ctx->ggml_ctx, x->ne[0], x->ne[1], x->ne[2], 1);
x = ggml_concat(ctx->ggml_ctx, x, padding_mask, 3); // concat mask channel

x = patchify_2d(ctx->ggml_ctx, x, patch_size); // [C*4, T, H/2, W/2]
auto padding_mask = ggml_ext_zeros(ctx->ggml_ctx, x->ne[0], x->ne[1], 1, x->ne[3]);
x = ggml_concat(ctx->ggml_ctx, x, padding_mask, 2); // [N, C + 1, H, W]

int64_t w_len = x->ne[0];
int64_t h_len = x->ne[1];
int64_t t_len = x->ne[2];
x = ggml_reshape_3d(ctx->ggml_ctx, x, x->ne[0] * x->ne[1] * x->ne[2], x->ne[3], 1);
x = ggml_ext_cont(ctx->ggml_ctx, ggml_ext_torch_permute(ctx->ggml_ctx, x, 1, 0, 2, 3)); // [N, n_token, C]
x = DiT::pad_and_patchify(ctx, x, patch_size, patch_size); // [N, h*w, (C+1)*ph*pw]

x = x_embedder->forward(ctx, x);

Expand Down Expand Up @@ -586,15 +504,9 @@ namespace Anima {
x = block->forward(ctx, x, encoder_hidden_states, embedded_timestep, temb, image_pe);
}

x = final_layer->forward(ctx, x, embedded_timestep, temb); // [N, n_token, C*4]

x = ggml_ext_cont(ctx->ggml_ctx, ggml_ext_torch_permute(ctx->ggml_ctx, x, 1, 0, 2, 3)); // [n_token, C*4, N]
x = ggml_reshape_4d(ctx->ggml_ctx, x, w_len, h_len, t_len, x->ne[1]); // [C*4, T, H/2, W/2]
x = unpatchify_2d(ctx->ggml_ctx, x, patch_size); // [C, T, H, W]
x = final_layer->forward(ctx, x, embedded_timestep, temb); // [N, h*w, ph*pw*C]

x = ggml_ext_slice(ctx->ggml_ctx, x, 1, 0, H); // [C, T, H, W + pad]
x = ggml_ext_slice(ctx->ggml_ctx, x, 0, 0, W); // [C, T, H, W]
x = ggml_reshape_4d(ctx->ggml_ctx, x, x->ne[0], x->ne[1], x->ne[3], x->ne[2]); // [N, C, H, W]
x = DiT::unpatchify_and_crop(ctx->ggml_ctx, x, H, W, patch_size, patch_size, false); // [N, C, H, W]

return x;
}
Expand Down
6 changes: 3 additions & 3 deletions src/common.hpp → src/common_block.hpp
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
#ifndef __COMMON_HPP__
#define __COMMON_HPP__
#ifndef __COMMON_BLOCK_HPP__
#define __COMMON_BLOCK_HPP__

#include "ggml_extend.hpp"

Expand Down Expand Up @@ -590,4 +590,4 @@ class VideoResBlock : public ResBlock {
}
};

#endif // __COMMON_HPP__
#endif // __COMMON_BLOCK_HPP__
108 changes: 108 additions & 0 deletions src/common_dit.hpp
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Original file line number Diff line number Diff line change
@@ -0,0 +1,108 @@
#ifndef __COMMON_DIT_HPP__
#define __COMMON_DIT_HPP__

#include "ggml_extend.hpp"

namespace DiT {
ggml_tensor* patchify(ggml_context* ctx,
ggml_tensor* x,
int pw,
int ph,
bool patch_last = true) {
// x: [N, C, H, W]
// return: [N, h*w, C*ph*pw] if patch_last else [N, h*w, ph*pw*C]
int64_t N = x->ne[3];
int64_t C = x->ne[2];
int64_t H = x->ne[1];
int64_t W = x->ne[0];
int64_t h = H / ph;
int64_t w = W / pw;

GGML_ASSERT(h * ph == H && w * pw == W);

x = ggml_reshape_4d(ctx, x, pw, w, ph, h * C * N); // [N*C*h, ph, w, pw]
x = ggml_cont(ctx, ggml_permute(ctx, x, 0, 2, 1, 3)); // [N*C*h, w, ph, pw]
x = ggml_reshape_4d(ctx, x, pw * ph, w * h, C, N); // [N, C, h*w, ph*pw]
if (patch_last) {
x = ggml_cont(ctx, ggml_permute(ctx, x, 0, 2, 1, 3)); // [N, h*w, C, ph*pw]
x = ggml_reshape_3d(ctx, x, pw * ph * C, w * h, N); // [N, h*w, C*ph*pw]
} else {
x = ggml_cont(ctx, ggml_ext_torch_permute(ctx, x, 2, 0, 1, 3)); // [N, h*w, C, ph*pw]
x = ggml_reshape_3d(ctx, x, C * pw * ph, w * h, N); // [N, h*w, ph*pw*C]
}
return x;
}

ggml_tensor* unpatchify(ggml_context* ctx,
ggml_tensor* x,
int64_t h,
int64_t w,
int ph,
int pw,
bool patch_last = true) {
// x: [N, h*w, C*ph*pw] if patch_last else [N, h*w, ph*pw*C]
// return: [N, C, H, W]
int64_t N = x->ne[2];
int64_t C = x->ne[0] / ph / pw;
int64_t H = h * ph;
int64_t W = w * pw;

GGML_ASSERT(C * ph * pw == x->ne[0]);

if (patch_last) {
x = ggml_reshape_4d(ctx, x, pw * ph, C, w * h, N); // [N, h*w, C, ph*pw]
x = ggml_cont(ctx, ggml_permute(ctx, x, 0, 2, 1, 3)); // [N, C, h*w, ph*pw]
} else {
x = ggml_reshape_4d(ctx, x, C, pw * ph, w * h, N); // [N, h*w, ph*pw, C]
x = ggml_cont(ctx, ggml_permute(ctx, x, 2, 0, 1, 3)); // [N, C, h*w, ph*pw]
}

x = ggml_reshape_4d(ctx, x, pw, ph, w, h * C * N); // [N*C*h, w, ph, pw]
x = ggml_cont(ctx, ggml_permute(ctx, x, 0, 2, 1, 3)); // [N*C*h, ph, w, pw]
x = ggml_reshape_4d(ctx, x, W, H, C, N); // [N, C, h*ph, w*pw]

return x;
}

ggml_tensor* pad_to_patch_size(GGMLRunnerContext* ctx,
ggml_tensor* x,
int ph,
int pw) {
int64_t W = x->ne[0];
int64_t H = x->ne[1];

int pad_h = (ph - H % ph) % ph;
int pad_w = (pw - W % pw) % pw;
x = ggml_ext_pad(ctx->ggml_ctx, x, pad_w, pad_h, 0, 0, ctx->circular_x_enabled, ctx->circular_y_enabled);
return x;
}

ggml_tensor* pad_and_patchify(GGMLRunnerContext* ctx,
ggml_tensor* x,
int ph,
int pw,
bool patch_last = true) {
x = pad_to_patch_size(ctx, x, ph, pw);
x = patchify(ctx->ggml_ctx, x, ph, pw, patch_last);
return x;
}

ggml_tensor* unpatchify_and_crop(ggml_context* ctx,
ggml_tensor* x,
int64_t H,
int64_t W,
int ph,
int pw,
bool patch_last = true) {
int pad_h = (ph - H % ph) % ph;
int pad_w = (pw - W % pw) % pw;
int64_t h = ((H + pad_h) / ph);
int64_t w = ((W + pad_w) / pw);
x = unpatchify(ctx, x, h, w, ph, pw, patch_last); // [N, C, H + pad_h, W + pad_w]
x = ggml_ext_slice(ctx, x, 1, 0, H); // [N, C, H, W + pad_w]
x = ggml_ext_slice(ctx, x, 0, 0, W); // [N, C, H, W]
return x;
}
} // namespace DiT

#endif // __COMMON_DIT_HPP__
3 changes: 1 addition & 2 deletions src/control.hpp
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Original file line number Diff line number Diff line change
@@ -1,8 +1,7 @@
#ifndef __CONTROL_HPP__
#define __CONTROL_HPP__

#include "common.hpp"
#include "ggml_extend.hpp"
#include "common_block.hpp"
#include "model.h"

#define CONTROL_NET_GRAPH_SIZE 1536
Expand Down
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