mirror of
https://github.com/NVIDIA/Model-Optimizer.git
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h-guo18
82d96a635f
## What does this PR do?
Refactors EAGLE3 training to use a single base YAML config with
OmegaConf dotlist overrides.
**Type of change:** Refactor
## Changes
- Single base config
`modelopt_recipes/speculative_decoding/_base_eagle3.yaml` for all EAGLE3
training; removed per-model child YAMLs.
- `launch_train.sh` accepts `--config <yaml>` plus dotlist overrides
(e.g. `model.model_name_or_path=xxx`).
- Removed `__base__` YAML inheritance logic from `main.py`.
- `dp_shard_size` default changed from `0` sentinel to `None` for
clarity.
- Removed `eagle_config.json` and `fsdp_config.json`; architecture
config is now nested under `eagle.eagle_architecture_config` in YAML.
- `train_eagle3_and_export.sh` now uses base YAML + dotlist instead of
generating a temporary YAML.
- Updated README and tests accordingly.
## Usage
```bash
# Online training
./launch_train.sh \
--config ../../modelopt_recipes/speculative_decoding/_base_eagle3.yaml \
model.model_name_or_path=meta-llama/Llama-3.2-1B \
data.data_path=input_conversations/train.jsonl \
training.output_dir=ckpts/llama-3.2-1b-online
# Offline training
./launch_train.sh \
--config ../../modelopt_recipes/speculative_decoding/_base_eagle3.yaml \
model.model_name_or_path=meta-llama/Llama-3.2-1B \
data.offline_data_path=$HIDDEN_STATES_DIR \
training.output_dir=ckpts/llama-3.2-1b-offline
```
---------
Signed-off-by: h-guo18 <67671475+h-guo18@users.noreply.github.com>
59 lines
2.0 KiB
Bash
Executable File
59 lines
2.0 KiB
Bash
Executable File
#!/bin/bash
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# SPDX-FileCopyrightText: Copyright (c) 2023-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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set -eo pipefail
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BASE_MODEL=meta-llama/Llama-3.2-1B-Instruct
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DATA=input_conversations/train.jsonl
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while [[ $# -gt 0 ]]; do
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case $1 in
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--base_model) BASE_MODEL="$2"; shift; shift ;;
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--data) DATA="$2"; shift; shift ;;
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--offline_data) OFFLINE_DATA_PATH="$2"; shift; shift ;;
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*) echo "Unknown argument: $1"; exit 1 ;;
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esac
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done
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MODEL_BASENAME=$(basename "$BASE_MODEL")
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OUTPUT_DIR=ckpts/${MODEL_BASENAME}-$(date +%Y%m%d_%H%M)
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mkdir -p "$OUTPUT_DIR"
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BASE_CFG="$(dirname "$(readlink -f "$0")")/../../modelopt_recipes/general/speculative_decoding/eagle3.yaml"
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# Build dotlist overrides
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OVERRIDES=(
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model.model_name_or_path="$BASE_MODEL"
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training.output_dir="$OUTPUT_DIR"
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)
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if [[ -n "$OFFLINE_DATA_PATH" ]]; then
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OVERRIDES+=( data.offline_data_path="$OFFLINE_DATA_PATH" )
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else
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OVERRIDES+=( data.data_path="$DATA" )
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fi
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echo "==== [1/3] Training draft model ===="
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./launch_train.sh --config "$BASE_CFG" "${OVERRIDES[@]}"
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echo "==== [2/3] Evaluating ModelOpt checkpoint on MT-Bench ===="
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python scripts/ar_validate.py --model_path $OUTPUT_DIR
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echo "==== [3/3] Exporting checkpoint to deployment format ===="
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EXPORT_PATH=export/${MODEL_BASENAME}-$(date +%Y%m%d_%H%M)
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mkdir -p "$(dirname "$EXPORT_PATH")"
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python scripts/export_hf_checkpoint.py --model_path $OUTPUT_DIR --export_path $EXPORT_PATH
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