echo-memory-train

Agent Building

Run Echo-Memory memory-baseline and context training recipes on Wan 2.1 1.3B. Use when training spatial/SSM/compression/context rows, editing train/*.sh launchers, or configuring DATASET_BASE_PATH for static or dynamic pools.

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How to use this skill

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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory/blob/HEAD/.cursor/skills/echo-memory-train/SKILL.md

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Echo-Memory training

Required env (repo root)

export WAN_BASE_MODEL=/path/to/Wan2.1-T2V-1.3B
export DATASET_BASE_PATH=data/Context-as-Memory-Dataset   # static in-domain pool
export PYTHONPATH=$PWD:${PYTHONPATH:-}
export OUTPUT_BASE_ROOT=$PWD/outputs

Static in-domain pool — default data/Context-as-Memory-Dataset; see doc/dataset_preprocessing.md
Dynamic training pool — e.g. data/dynamic-memory-dataset; see doc/dynamic_dataset_preprocessing.md

Entry scripts

Family	Directory	Example
Spatial / SSM / compression	`train/memory_baselines_basic/`	`run_spatial_memory_baseline.sh`, `run_ablation_block_wise_ssm_two_chunk.sh`
Context K=1/5/20	`train/context_learning/`	`run_pre_qkv_ctx1.sh`, `run_pre_qkv_ctx20.sh`

Run from repository root: bash train/memory_baselines_basic/run_spatial_memory_baseline.sh

Shared env: train/_shared/common_env_memory.sh — no private paths baked in.

Agent checklist

Confirm which memory row (paper family + row id) the user wants.
Set DATASET_BASE_PATH to the correct training pool name in docs (Echo terms only in public markdown).
Prefer editing existing run_*.sh patterns over new one-off Python entrypoints.
Outputs go to outputs/ unless OUTPUT_BASE_ROOT is set.
Do not commit data/, outputs/, checkpoints, or machine-local paths.

Docs

train/README.md — launcher index
train/memory_baselines_basic/README.md — ablation set