File size: 4,070 Bytes
98aec57 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | #!/usr/bin/env bash
# Box B (audio) — dataset preprocess + flatten, so the trainer can render.
#
# WHY THIS IS NEEDED FOR PURE INFERENCE: ltx_a2a_generate*.py drives
# scripts/train.py with optimization.steps=1, because validation_runner IS the
# a2a inference path. train.py builds a train dataloader before validation
# fires, so preprocessed latents must exist even when we only want to render.
#
# SUBSET is the fast path. Preprocessing all 266 pairs runs the audio VAE and
# Gemma text encoder over every row and sits on the critical path behind the
# 66 GB weight pull. The dataloader only needs to be non-empty, so a handful of
# pairs unblocks rendering in under a minute; run the full pass afterwards, in
# the background, only if we are retraining.
#
# Usage:
# box_b_trainer_setup.sh 8 # subset of 8 train pairs — fast, render-only
# box_b_trainer_setup.sh full # all 266 pairs — required before any retrain
set -uo pipefail
export PATH="$HOME/.local/bin:$PATH" TMPDIR=/workspace/.tmp UV_CACHE_DIR=/workspace/.uv-cache
MODE="${1:-8}"
ASC=/workspace/Demos/LTX/acoustic-space-control
M=/workspace/models/ltx-2.5
DATA=/workspace/Demos/data/acoustic-space-v5
TOOLS=/workspace/akuspace-tools
for f in "$M/diffusion_models/ltx-2.5-22b-dev-transformer-bf16.safetensors" \
"$M/text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors" \
"$M/vae/ltx-2.5-video-vae-bf16.safetensors" \
"$M/vae/ltx-2.5-audio-vae-bf16.safetensors"; do
[ -s "$f" ] || { echo "WEIGHTS NOT READY: $f"; exit 2; }
done
[ -d "$ASC/training" ] || { echo "MAC PUSH NOT LANDED: $ASC/training missing"; exit 2; }
cd "$ASC"
SRC=training/ableton-assets-grid-v5.csv
if [ "$MODE" = "full" ]; then
MAN="$SRC"; echo "=== FULL preprocess (266 pairs) ==="
else
MAN=training/_subset_${MODE}.csv
head -1 "$SRC" > "$MAN"
awk -F, 'NR>1 && $2=="train"' "$SRC" | head -"$MODE" >> "$MAN"
echo "=== SUBSET preprocess ($(($(wc -l < "$MAN")-1)) train pairs) — render-only fast path ==="
fi
[ -d "$TOOLS" ] || uv venv "$TOOLS" --python 3.12 >/dev/null 2>&1
uv pip install --python "$TOOLS/bin/python" -q -r training/requirements.txt 2>&1 | tail -2
"$TOOLS/bin/python" training/prepare_dataset.py \
--manifest "$MAN" --output "$DATA" --mode copy 2>&1 | tail -3
echo "PREPARE_EXIT=$?"
cd /workspace/LTX-2.5-repo/packages/ltx-trainer
/workspace/LTX-2.5-repo/.venv/bin/python scripts/process_dataset.py \
"$DATA/dataset_train.json" \
--audio-durations 6.0 \
--model-path "$M/diffusion_models/ltx-2.5-22b-dev-transformer-bf16.safetensors" \
--text-encoder-path "$M/text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors" \
--video-vae-path "$M/vae/ltx-2.5-video-vae-bf16.safetensors" \
--audio-vae-path "$M/vae/ltx-2.5-audio-vae-bf16.safetensors" \
--output-dir "$DATA/.precomputed" \
--lora-trigger AKUSPACE 2>&1 | tail -5
echo "PROCESS_EXIT=$?"
# MANDATORY FLATTEN — process_dataset mirrors the dataset-JSON relative paths,
# but datasets.py::_discover_samples requires one identical rel_path across all
# three sources, so nested targets/references never match. Silent: the dirs are
# populated and the run still reports "No valid samples found".
PRE="$DATA/.precomputed"
[ -d "$PRE/audio_latents/audio/targets" ] && { mv "$PRE/audio_latents/audio/targets/"* "$PRE/audio_latents/"; rm -rf "$PRE/audio_latents/audio"; }
[ -d "$PRE/reference_audio_latents/audio/references" ] && { mv "$PRE/reference_audio_latents/audio/references/"* "$PRE/reference_audio_latents/"; rm -rf "$PRE/reference_audio_latents/audio"; }
[ -d "$PRE/conditions/audio/targets" ] && { mv "$PRE/conditions/audio/targets/"* "$PRE/conditions/"; rm -rf "$PRE/conditions/audio"; }
A=$(find "$PRE/audio_latents" -maxdepth 1 -name '*.pt' | wc -l)
R=$(find "$PRE/reference_audio_latents" -maxdepth 1 -name '*.pt' | wc -l)
C=$(find "$PRE/conditions" -maxdepth 1 -name '*.pt' | wc -l)
echo "flatten: audio=$A reference=$R conditions=$C (must be equal and non-zero)"
[ "$A" -gt 0 ] && [ "$A" -eq "$R" ] && echo "TRAINER_SETUP_DONE" || echo "TRAINER_SETUP_MISMATCH"
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