From 96b20cd43f104c943311a8548c0599bfff50f53b Mon Sep 17 00:00:00 2001 From: YWMditto <46778265+YWMditto@users.noreply.github.com> Date: Tue, 26 Sep 2023 16:58:46 +0800 Subject: [PATCH] doc(usage): add dynamic ntk into doc (#367) * add long text generation in doc/usage.md * add long text generation in doc/usage.md * add long text generation in doc/usage.md --------- Co-authored-by: YWMditto <862779238@qq.com> --- doc/en/usage.md | 33 +++++++++++++++++++++++++++++++++ doc/usage.md | 33 +++++++++++++++++++++++++++++++++ 2 files changed, 66 insertions(+) diff --git a/doc/en/usage.md b/doc/en/usage.md index 864ead6..cab08ca 100644 --- a/doc/en/usage.md +++ b/doc/en/usage.md @@ -385,3 +385,36 @@ Taking the configuration of the demo training on a single machine with 8 GPUs on 2023-07-07 12:29:13,147 INFO train.py:323 in record_current_batch_training_metrics -- tflops=189.65918563194305,step=4,loss=10.149517059326172,tgs (tokens/gpu/second)=4270.52,lr=1.2000000000000002e-06,loss_scale=65536.0,grad_norm=51.582841631508145,micro_num=4,num_consumed_tokens=655360,inf_nan_skip_batches=0,num_samples_in_batch=19,largest_length=2048,largest_batch=6,smallest_batch=3,adam_beta2=0.95,fwd_bwd_time=3.68 2023-07-07 12:29:16,994 INFO train.py:323 in record_current_batch_training_metrics -- tflops=189.3109313713174,step=5,loss=9.822169303894043,tgs (tokens/gpu/second)=4262.67,lr=1.4000000000000001e-06,loss_scale=65536.0,grad_norm=47.10386835560855,micro_num=4,num_consumed_tokens=786432,inf_nan_skip_batches=0,num_samples_in_batch=17,largest_length=2048,largest_batch=6,smallest_batch=3,adam_beta2=0.95,fwd_bwd_time=3.69 ``` + +### Long Text Generation + +During the inference phase, you can turn on the Dynamic NTK option of RoPE by setting `use_dynamic_ntk_rope=True` in the model configuration, so that the model can adapt to long text input and output and achieve an extrapolation effect of 16K: +```python #21 +model_type = "INTERNLM" # 模型类型，默认值为 "INTERNLM"，对应模型结构初始化接口函数 +NUM_ATTENTION_HEAD = 32 +VOCAB_SIZE = 103168 +HIDDEN_SIZE = 4096 +NUM_LAYER = 32 +MLP_RATIO = 8 / 3 +model = dict( + checkpoint=False, # 进行重计算的模型层数比例，可选值为 True/False/[0-1] + num_attention_heads=NUM_ATTENTION_HEAD, + embed_split_hidden=True, + vocab_size=VOCAB_SIZE, + embed_grad_scale=1, + parallel_output=True, + hidden_size=HIDDEN_SIZE, + num_layers=NUM_LAYER, + mlp_ratio=MLP_RATIO, + apply_post_layer_norm=False, + dtype="torch.bfloat16", + norm_type="rmsnorm", + layer_norm_epsilon=1e-5, + use_dynamic_ntk_rope=True +) +``` + +Regarding the principle of Dyanmic NTK, please refer to + +1. https://www.reddit.com/r/LocalLLaMA/comments/14mrgpr/dynamically_scaled_rope_further_increases +2. https://kexue.fm/archives/9675 diff --git a/doc/usage.md b/doc/usage.md index 82c20e0..347ca35 100644 --- a/doc/usage.md +++ b/doc/usage.md @@ -368,3 +368,36 @@ $ torchrun --nnodes=1 --nproc_per_node=8 train.py --config ./configs/7B_sft.py - 2023-07-07 12:29:13,147 INFO train.py:323 in record_current_batch_training_metrics -- tflops=189.65918563194305,step=4,loss=10.149517059326172,tgs (tokens/gpu/second)=4270.52,lr=1.2000000000000002e-06,loss_scale=65536.0,grad_norm=51.582841631508145,micro_num=4,num_consumed_tokens=655360,inf_nan_skip_batches=0,num_samples_in_batch=19,largest_length=2048,largest_batch=6,smallest_batch=3,adam_beta2=0.95,fwd_bwd_time=3.68 2023-07-07 12:29:16,994 INFO train.py:323 in record_current_batch_training_metrics -- tflops=189.3109313713174,step=5,loss=9.822169303894043,tgs (tokens/gpu/second)=4262.67,lr=1.4000000000000001e-06,loss_scale=65536.0,grad_norm=47.10386835560855,micro_num=4,num_consumed_tokens=786432,inf_nan_skip_batches=0,num_samples_in_batch=17,largest_length=2048,largest_batch=6,smallest_batch=3,adam_beta2=0.95,fwd_bwd_time=3.69 ``` + +### 长文本生成 + +在推理阶段，您可以在模型配置中通过设置 `use_dynamic_ntk_rope=True` 开启 RoPE 的 Dynamic NTK 选项，从而使得模型适应长文本输入输出，达到 16K 的外推效果: +```python #21 +model_type = "INTERNLM" # 模型类型，默认值为 "INTERNLM"，对应模型结构初始化接口函数 +NUM_ATTENTION_HEAD = 32 +VOCAB_SIZE = 103168 +HIDDEN_SIZE = 4096 +NUM_LAYER = 32 +MLP_RATIO = 8 / 3 +model = dict( + checkpoint=False, # 进行重计算的模型层数比例，可选值为 True/False/[0-1] + num_attention_heads=NUM_ATTENTION_HEAD, + embed_split_hidden=True, + vocab_size=VOCAB_SIZE, + embed_grad_scale=1, + parallel_output=True, + hidden_size=HIDDEN_SIZE, + num_layers=NUM_LAYER, + mlp_ratio=MLP_RATIO, + apply_post_layer_norm=False, + dtype="torch.bfloat16", + norm_type="rmsnorm", + layer_norm_epsilon=1e-5, + use_dynamic_ntk_rope=True +) +``` + +关于 Dyanmic NTK 的原理，详细请参考 + +1. https://www.reddit.com/r/LocalLLaMA/comments/14mrgpr/dynamically_scaled_rope_further_increases +2. https://kexue.fm/archives/9675