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perf: run one-frame Wan VAE convolutions as 2D convolutions (#2038)

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Dong Wang 2026-09-23 18:23:31 +02:00 committed by GitHub
parent 36746936c0
commit 70c1dbc01e
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1 changed files with 14 additions and 0 deletions
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src/model/vae/wan_vae.hpp
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@ -82,6 +82,20 @@ namespace WAN {
} }
x = ggml_ext_pad_ext(ctx->ggml_ctx, ctx->backend, x, lp0, rp0, lp1, rp1, lp2, rp2, 0, 0, ctx->circular_x_enabled, ctx->circular_y_enabled); x = ggml_ext_pad_ext(ctx->ggml_ctx, ctx->backend, x, lp0, rp0, lp1, rp1, lp2, rp2, 0, 0, ctx->circular_x_enabled, ctx->circular_y_enabled);
if (w->ne[2] == 1 && x->ne[2] == 1 && x->ne[3] == in_channels) {
// One frame through a one-frame-deep kernel is a 2D conv; backends without
// im2col_3d (Metal) otherwise fall back to a much slower direct conv_3d.
if (!ggml_is_contiguous(x)) {
x = ggml_cont(ctx->ggml_ctx, x);
}
ggml_tensor* x2 = ggml_reshape_4d(ctx->ggml_ctx, x, x->ne[0], x->ne[1], in_channels, 1);
ggml_tensor* w2 = ggml_reshape_4d(ctx->ggml_ctx, w, w->ne[0], w->ne[1], in_channels, out_channels);
x2 = ggml_ext_conv_2d(ctx->ggml_ctx, x2, w2, b,
std::get<2>(stride), std::get<1>(stride), 0, 0,
std::get<2>(dilation), std::get<1>(dilation),
ctx->conv2d_direct_enabled);
return ggml_reshape_4d(ctx->ggml_ctx, x2, x2->ne[0], x2->ne[1], 1, out_channels);
}
return ggml_ext_conv_3d(ctx->ggml_ctx, ctx->backend, x, w, b, in_channels, return ggml_ext_conv_3d(ctx->ggml_ctx, ctx->backend, x, w, b, in_channels,
std::get<2>(stride), std::get<1>(stride), std::get<0>(stride), std::get<2>(stride), std::get<1>(stride), std::get<0>(stride),
0, 0, 0, 0, 0, 0,