[Dev] Pull Main (#139)

* fix/fix_submodule_err (#61)

* fix/fix_submodule_err

---------

Co-authored-by: ChenQiaoling00 <qiaoling_chen@u.nus.edu>

* fix issue templates (#65)

* fix(tokenizer): refactor tokenizer and update usage in readme (#51)

* update tokenizer example

* fix(readme, requirements): fix typo at Chinese readme and select a lower version of transformers (#73)

* fix a typo in readme

* in order to find InternLMTokenizer, select a lower version of Transformers

---------

Co-authored-by: gouhchangjiang <gouhchangjiang@gmail.com>

* [Doc] Add wechat and discord link in readme (#78)

* Doc：add wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* Doc：update wechat and discord link

* [Docs]: add Japanese README (#43)

* Add Japanese README

* Update README-ja-JP.md

replace message

* Update README-ja-JP.md

* add repetition_penalty in GenerationConfig in web_demo.py (#48)

Co-authored-by: YWMditto <862779238@qq.com>

* use fp16 in instruction (#80)

* [Enchancement] add more options for issue template (#77)

* [Enchancement] add more options for issue template

* update qustion icon

* fix link

* Use tempfile for convert2hf.py (#23)

Fix https://github.com/InternLM/InternLM/issues/50

* delete torch_dtype of README's example code (#100)

* set the value of repetition_penalty to 1.0 to avoid random outputs (#99)

* Update web_demo.py (#97)

Remove meaningless log.

* [Fix]Fix wrong string cutoff in the script for sft text tokenizing (#106)

* docs(install.md): update dependency package transformers version to >= 4.28.0 (#124)

Co-authored-by: 黄婷 <huangting3@CN0014010744M.local>

* docs(LICENSE): add license (#125)

* add license of colossalai and flash-attn

* fix lint

* modify the name

* fix AutoModel map in convert2hf.py (#116)

* variables are not printly as expect (#114)

* feat(solver): fix code to adapt to torch2.0 and provide docker images (#128)

* feat(solver): fix code to adapt to torch2.0

* docs(install.md): publish internlm environment image

* docs(install.md): update dependency packages version

* docs(install.md): update default image

---------

Co-authored-by: 黄婷 <huangting3@CN0014010744M.local>

* add demo test (#132)

Co-authored-by: qa-caif-cicd <qa-caif-cicd@pjlab.org.cn>

* fix web_demo cache accelerate (#133)

* fix(hybrid_zero_optim.py): delete math import

* Update embedding.py

---------

Co-authored-by: ChenQiaoling00 <qiaoling_chen@u.nus.edu>
Co-authored-by: Kai Chen <chenkaidev@gmail.com>
Co-authored-by: Yang Gao <Gary1546308416AL@gmail.com>
Co-authored-by: Changjiang GOU <gouchangjiang@gmail.com>
Co-authored-by: gouhchangjiang <gouhchangjiang@gmail.com>
Co-authored-by: vansin <msnode@163.com>
Co-authored-by: Ikko Eltociear Ashimine <eltociear@gmail.com>
Co-authored-by: YWMditto <46778265+YWMditto@users.noreply.github.com>
Co-authored-by: YWMditto <862779238@qq.com>
Co-authored-by: WRH <12756472+wangruohui@users.noreply.github.com>
Co-authored-by: liukuikun <24622904+Harold-lkk@users.noreply.github.com>
Co-authored-by: x54-729 <45304952+x54-729@users.noreply.github.com>
Co-authored-by: Shuo Zhang <zhangshuolove@live.com>
Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com>
Co-authored-by: huangting4201 <1538303371@qq.com>
Co-authored-by: 黄婷 <huangting3@CN0014010744M.local>
Co-authored-by: ytxiong <45058324+yingtongxiong@users.noreply.github.com>
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
Co-authored-by: kkscilife <126147887+kkscilife@users.noreply.github.com>
Co-authored-by: qa-caif-cicd <qa-caif-cicd@pjlab.org.cn>
Co-authored-by: hw <45089338+MorningForest@users.noreply.github.com>

.github/workflows/demo_in_readme.yaml

@@ -0,0 +1,68 @@
+name: demo-in-readme
+on: 
+  pull_request:
+    branches:
+      - "main"
+      - "develop"
+    paths-ignore:
+      - "docs/**"
+      - "**.md"
+     
+jobs:
+  dataset-preparation:
+    runs-on: [lmtest]
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: raw-chinese-data
+      run: |
+        source activate internlm-env-test
+        sh ./ci_scripts/data/tokenizer_chinese.sh
+
+    - name: alpaca-data
+      run: |
+        source activate internlm-env-test
+        sh ./ci_scripts/data/tokenizer_alpaca.sh
+
+
+  train:
+    runs-on: [lmtest]
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: slurm-train
+      run: |
+        source activate internlm-env-test
+        sh ./ci_scripts/train/slurm_train.sh
+        rm -rf $GITHUB_WORKSPACE/llm_ckpts
+
+    - name: torchrun-train
+      run: |
+        source activate internlm-env-test
+        sh ./ci_scripts/train/torchrun.sh
+        rm -rf $GITHUB_WORKSPACE/llm_ckpts
+
+  convert-model-then-load:
+    runs-on: [lmtest]
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: convert-model-then-load
+      run: |
+        source activate internlm-env-test
+        export PYTHONPATH=$PWD:$PYTHONPATH
+        sh ./ci_scripts/model/convert_to_hf.sh 
+        cd ./hf_ckpt
+        srun -p llm2 python ../ci_scripts/model/loaded_as_transformer.py
+        cd ..
+        rm -rf $GITHUB_WORKSPACE/hf_ckpt
+  
+  load-chat-model-in-hf:
+    runs-on: [lmtest]
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: chat-model-in-hf
+      run: |
+        source activate internlm-env-test
+        srun -p llm2 python ./ci_scripts/model/demo_load_7B_chat_model.py

LICENSE

@@ -199,3 +199,51 @@
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
    limitations under the License.
+
+## Some of InternLM's code is derived from others projects, which is subject to the following copyright notice:
+
+Copyright 2021- HPC-AI Technology Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+---------------- LICENSE FOR Flash Attention ----------------
+
+BSD 3-Clause License
+
+Copyright (c) 2022, the respective contributors, as shown by the AUTHORS file.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+* Neither the name of the copyright holder nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

ci_scripts/common/basic_func.sh

@@ -0,0 +1,14 @@
+#!/bin/bash
+
+export exit_code=0
+
+function if_exist() {
+ls -l $file_path
+exit_code_now=$?
+exit_code=$(($exit_code + $exit_code_now))
+}
+
+function num_files() {
+file_num=$(ls -l $file_dir |wc -l)
+echo "there are $file_num files in $file_dir"
+}

ci_scripts/data/tokenizer_alpaca.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+rm -rf /mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/result/*
+
+python tools/alpaca_tokenizer.py /mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/alpaca_data.json /mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/result  tools/V7_sft.model --split_ratio 0.1
+
+file_one="/mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/result/train/en/dataset.bin"
+file_two="/mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/result/train/en/dataset.bin.meta"
+file_three="/mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/result/valid/en/dataset.bin"
+file_four="/mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/result/valid/en/dataset.bin.meta"
+file_list=($file_one $file_two $file_three $file_four)
+
+source ./ci_scripts/common/basic_func.sh
+for file_path in ${file_list[@]};
+do
+if_exist $file_path
+done
+
+if [ $exit_code -ne 0 ]
+then
+    exit 1
+fi

ci_scripts/data/tokenizer_chinese.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+
+rm -rf /mnt/petrelfs/qa-caif-cicd/data/lm_data/cn_data/result.*
+srun -p llm2 python tools/tokenizer.py --text_input_path /mnt/petrelfs/qa-caif-cicd/data/lm_data/cn_data/raw_data.txt --bin_output_path /mnt/petrelfs/qa-caif-cicd/data/lm_data/cn_data/result.bin
+
+file_one="/mnt/petrelfs/qa-caif-cicd/data/lm_data/cn_data/result.bin"
+file_two="/mnt/petrelfs/qa-caif-cicd/data/lm_data/cn_data/result.bin.meta"
+file_list=($file_one $file_two)
+
+source ./ci_scripts/common/basic_func.sh
+for file_path in ${file_list[@]};
+do
+if_exist $file_path
+done
+
+if [ $exit_code -ne 0 ]
+then
+    exit 1
+fi

ci_scripts/model/convert_to_hf.sh

@@ -0,0 +1,33 @@
+#!/bin/bash
+
+rm -rf ./hf_ckpt/*
+python ./tools/transformers/convert2hf.py --src_folder /mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/llm_ckpts/20 --tgt_folder hf_ckpt/ --tokenizer ./tools/V7_sft.model
+
+#assert exists model
+file_one="$GITHUB_WORKSPACE/hf_ckpt/tokenizer.model"
+file_two="$GITHUB_WORKSPACE/hf_ckpt/config.json"
+file_three="$GITHUB_WORKSPACE/hf_ckpt/modeling_internlm.py"
+file_list=($file_one $file_two $file_three)
+file_dir="$GITHUB_WORKSPACE/hf_ckpt/*"
+
+source ./ci_scripts/common/basic_func.sh
+
+for file_path in ${file_list[@]};
+do
+if_exist $file_path
+done
+
+
+num_files ${file_dir}
+
+if [ $file_num -ne 9 ]
+then
+    echo "The num of files is not right"
+    ls -l $file_dir
+    exit_code=$(($exit_code + 1)) 
+fi
+
+if [ $exit_code -ne 0 ]
+then
+    exit 1
+fi

ci_scripts/model/demo_load_7B_chat_model.py

@@ -0,0 +1,12 @@
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True).cuda()
+model = model.eval()
+response, history = model.chat(tokenizer, "你好", history=[])
+print(response)
+assert len(response) != 0
+response, history = model.chat(tokenizer, "请提供三个管理时间的建议。", history=history)
+print(response)
+assert len(response) != 0

ci_scripts/model/loaded_as_transformer.py

@@ -0,0 +1,7 @@
+from transformers import AutoModel
+
+model = AutoModel.from_pretrained("../hf_ckpt/", trust_remote_code=True).cuda()
+print(model)
+assert model.config.hidden_size == 2048
+assert model.config.num_attention_heads == 16
+assert model.config.num_hidden_layers == 16

ci_scripts/train/ci_7B_sft.py

@@ -0,0 +1,130 @@
+JOB_NAME = "7b_train"
+
+SEQ_LEN = 1024
+HIDDEN_SIZE = 2048
+NUM_ATTENTION_HEAD = 16
+MLP_RATIO = 8 / 3
+NUM_LAYER = 16
+VOCAB_SIZE = 103168
+
+# Ckpt folder format:
+# fs: 'local:/mnt/nfs/XXX'
+# oss: 'boto3:s3://model_weights/XXX'
+MODEL_ONLY_FOLDER = "local:llm_ckpts/xxxx"
+#SAVE_CKPT_FOLDER = "local:llm_ckpts"
+SAVE_CKPT_FOLDER = "local:llm_ckpts"
+#LOAD_CKPT_FOLDER = "local:llm_ckpts/49"
+ckpt = dict(
+    # Path to save training ckpt.
+    save_ckpt_folder=SAVE_CKPT_FOLDER,
+    # Path to continue training ckpt (load model weights and scheduler/context states).
+    # load_ckpt_folder=LOAD_CKPT_FOLDER,
+    # Path to initialize with given model weights.
+    # load_model_only_folder=MODEL_ONLY_FOLDER,
+    checkpoint_every=20,
+    # Wheter to load optimizer states when continuing training.
+    load_optimizer=True,
+)
+
+TRAIN_FOLDER = "/mnt/petrelfs/qa-caif-cicd/data/lm_data/alpaca_data/train/en"
+data = dict(
+    seq_len=SEQ_LEN,
+    # micro_num means the number of micro_batch contained in one gradient update
+    micro_num=4,
+    # packed_length = micro_bsz * SEQ_LEN
+    micro_bsz=2,
+    pack_sample_into_one=False,
+    total_steps=20,
+    skip_batches="",
+    rampup_batch_size="",
+    # Datasets with less than 50 rows will be discarded
+    min_length=50,
+    # train_folder=TRAIN_FOLDER,
+)
+
+grad_scaler = dict(
+    fp16=dict(
+        # the initial loss scale, defaults to 2**16
+        initial_scale=2**16,
+        # the minimum loss scale, defaults to None
+        min_scale=1,
+        # the number of steps to increase loss scale when no overflow occurs
+        growth_interval=1000,
+    ),
+    # the multiplication factor for increasing loss scale, defaults to 2
+    growth_factor=2,
+    # the multiplication factor for decreasing loss scale, defaults to 0.5
+    backoff_factor=0.5,
+    # the maximum loss scale, defaults to None
+    max_scale=2**24,
+    # the number of overflows before decreasing loss scale, defaults to 2
+    hysteresis=2,
+)
+
+hybrid_zero_optimizer = dict(
+    # Enable low_level_optimzer overlap_communication
+    zero_overlap_communication=True,
+    # bucket size for nccl communication params
+    reduce_bucket_size=512 * 1024 * 1024,
+    # grad clipping
+    clip_grad_norm=1.0,
+)
+
+loss = dict(
+    label_smoothing=0,
+)
+
+adam = dict(
+    lr=1e-4,
+    adam_beta1=0.9,
+    adam_beta2=0.95,
+    adam_beta2_c=0,
+    adam_eps=1e-8,
+    weight_decay=0.01,
+)
+
+lr_scheduler = dict(
+    total_steps=data["total_steps"],
+    init_steps=0,  # optimizer_warmup_step
+    warmup_ratio=0.01,
+    eta_min=1e-5,
+    last_epoch=-1,
+)
+
+beta2_scheduler = dict(
+    init_beta2=adam["adam_beta2"],
+    c=adam["adam_beta2_c"],
+    cur_iter=-1,
+)
+
+model = dict(
+    checkpoint=False,
+    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,
+)
+"""
+zero1 parallel:
+    1. if zero1 <= 0, The size of the zero process group is equal to the size of the dp process group,
+        so parameters will be divided within the range of dp.
+    2. if zero1 == 1, zero is not used, and all dp groups retain the full amount of model parameters.
+    3. zero1 > 1 and zero1 <= dp world size, the world size of zero is a subset of dp world size.
+        For smaller models, it is usually a better choice to split the parameters within nodes with a setting <= 8.
+pipeline parallel: pipeline parallel size, only 1 is accepted currently.
+tensor parallel: tensor parallel size, usually the number of GPUs per node, only 1 is accepted currently.
+"""
+parallel = dict(
+    zero1=8,
+)
+
+cudnn_deterministic = False
+cudnn_benchmark = False

ci_scripts/train/slurm_train.sh

@@ -0,0 +1,20 @@
+#!/bin/bash
+
+rm -rf $GITHUB_WORKSPACE/llm_ckpts/20
+
+srun -p llm2 --quotatype=spot -n 8 --ntasks-per-node=8 --gpus-per-task=1 python train.py --config ./ci_scripts/train/ci_7B_sft.py
+
+file_dir="$GITHUB_WORKSPACE/llm_ckpts/20/*.pt"
+source ./ci_scripts/common/basic_func.sh
+
+num_files ${file_dir}
+
+if [ $file_num -ne 21 ]
+then
+    echo "The num of files is not right"
+    ls -l $file_dir
+    rm -rf $GITHUB_WORKSPACE/llm_ckpts
+    exit 1
+fi
+
+

ci_scripts/train/torchrun.sh

@@ -0,0 +1,17 @@
+#!/bin/bash
+
+rm -rf $GITHUB_WORKSPACE/llm_ckpts/20
+srun -p llm2 -N 1 torchrun --nnodes=1 --nproc_per_node=8 --master_port=29501 train.py --config ./ci_scripts/train/ci_7B_sft.py --launcher "torch"
+
+file_dir="$GITHUB_WORKSPACE/llm_ckpts/20/*.pt"
+source ./ci_scripts/common/basic_func.sh
+
+num_files ${file_dir}
+
+if [ $file_num -ne 21 ]
+then
+    echo "The num of files is not right"
+    ls -l $file_dir
+    rm -rf $GITHUB_WORKSPACE/llm_ckpts
+    exit 1
+fi

doc/en/install.md

@@ -5,10 +5,10 @@ The required packages and corresponding version are shown as follows:
 - Python == 3.10
 - GCC == 10.2.0
 - MPFR == 4.1.0
-- CUDA == 11.7
+- CUDA >= 11.7
-- Pytorch == 1.13.1+cu117
+- Pytorch >= 1.13.1
-- Transformers >= 4.25.1
+- Transformers >= 4.28.0
-- Flash-Attention == v1.0.5
+- Flash-Attention >= v1.0.5
 - Apex == 23.05
 - GPU with Ampere or Hopper architecture (such as H100, A100)
 - Linux OS
@@ -57,3 +57,14 @@ cd ./third_party/apex
 pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./
 cd ../../
 ```
+
+### Environment Image
+Users can obtain an image with the InternLM runtime environment installed from https://hub.docker.com/r/sunpengsdu/internlm. The commands for pulling the image and starting the container are as follows:
+
+```bash
+# pull image
+docker pull sunpengsdu/internlm:torch1.13-cuda11.7-flashatten1.0.5-centos
+# start container
+docker run --gpus all -d -it --shm-size=2gb --name myinternlm sunpengsdu/internlm:torch1.13-cuda11.7-flashatten1.0.5-centos
+docker exec -it myinternlm bash
+```

doc/install.md

@@ -5,10 +5,10 @@
 - Python == 3.10
 - GCC == 10.2.0
 - MPFR == 4.1.0
-- CUDA == 11.7
+- CUDA >= 11.7
-- Pytorch == 1.13.1+cu117
+- Pytorch >= 1.13.1
-- Transformers >= 4.25.1
+- Transformers >= 4.28.0
-- Flash-Attention == v1.0.5
+- Flash-Attention >= v1.0.5
 - Apex == 23.05
 - Ampere或者Hopper架构的GPU (例如H100, A100)
 - Linux OS
@@ -57,3 +57,13 @@ cd ./third_party/apex
 pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./
 cd ../../
 ```
+
+### 环境镜像
+用户可以从 https://hub.docker.com/r/sunpengsdu/internlm 获取安装了 InternLM 运行环境的镜像，拉取镜像及启动容器的命令如下：
+```bash
+# 拉取镜像
+docker pull sunpengsdu/internlm:torch1.13-cuda11.7-flashatten1.0.5-centos
+# 启动容器
+docker run --gpus all -d -it --shm-size=2gb --name myinternlm sunpengsdu/internlm:torch1.13-cuda11.7-flashatten1.0.5-centos
+docker exec -it myinternlm bash
+```

internlm/model/embedding.py

@@ -175,7 +175,7 @@ class RotaryEmbedding(torch.nn.Module):
                 self._sin_cached = (torch.sin(freqs) * scale).to(x.dtype)
                 self._cos_k_cached = (torch.cos(freqs) / scale).to(x.dtype)
                 self._sin_k_cached = (torch.sin(freqs) / scale).to(x.dtype)
-    
+
     def forward(self, qkv: torch.Tensor, **kwargs):
         if kwargs.get("indexes", None) is not None:
             return self._forward(qkv, kwargs.pop("indexes"))
@@ -183,7 +183,7 @@ class RotaryEmbedding(torch.nn.Module):
             return self._eval_forward(qkv, seqlen_offset=kwargs.get("inference_params", None).sequence_len_offset)
         else:
             return self._eval_forward(qkv)
-    
+
     def _forward(self, qkv: torch.Tensor, indexes=0) -> Tuple[torch.Tensor, torch.Tensor]:
         self._update_cos_sin_cache(qkv, indexes)
         if self.scale is None:

internlm/solver/lr_scheduler.py

@@ -27,7 +27,7 @@ class WarmupScheduler(_LRScheduler):
 
     def state_dict(self):
         state_dict = {key: value for key, value in self.__dict__.items() if key not in "optimizer"}
-        if isinstance(state_dict["after_scheduler"], _LRScheduler):
+        if isinstance(state_dict["after_scheduler"], (_LRScheduler, _CosineAnnealingLR)):
             state_dict["after_scheduler_type"] = type(state_dict["after_scheduler"]).__name__
             state_dict["after_scheduler_dict"] = state_dict["after_scheduler"].state_dict()
             del state_dict["after_scheduler"]
@@ -40,7 +40,7 @@ class WarmupScheduler(_LRScheduler):
         for key in list(self.__dict__.keys()):
             if key in state_dict:
                 self.__dict__[key] = state_dict[key]
-        if isinstance(self.after_scheduler, _LRScheduler):
+        if isinstance(self.after_scheduler, (_LRScheduler, _CosineAnnealingLR)):
             assert type(self.after_scheduler).__name__ == state_dict["after_scheduler_type"]
             # state_dict['after_scheduler_dict'] = state_dict['after_scheduler'].state_dict()
             self.after_scheduler.load_state_dict(state_dict["after_scheduler_dict"])

tools/alpaca_tokenizer.py

@@ -160,5 +160,5 @@ if __name__ == "__main__":
     train_tokens, valid_tokens, train_samples, valid_samples = dump_bin_meta_bin(
         samples, args.output_path, args.split_ratio
     )
-    print(f"number of train dataset: {train_samples}, " "number of train dataset token: {train_tokens}")
+    print(f"number of train dataset: {train_samples}, number of train dataset token: {train_tokens}")
-    print(f"number of validation dataset: {valid_samples}, " "number of validation dataset token: {valid_tokens}")
+    print(f"number of validation dataset: {valid_samples}, number of validation dataset token: {valid_tokens}")

tools/transformers/convert2hf.py

@@ -167,7 +167,7 @@ if __name__ == "__main__":
     # TODO There should be a better way to add this.
     with open(os.path.join(target_folder, "config.json")) as fp:
         config_dict = json.load(fp)
-    config_dict["auto_map"]["AutoModel"] = "modeling_internlm.InternLMModel"
+    config_dict["auto_map"]["AutoModel"] = "modeling_internlm.InternLMForCausalLM"
     with open(os.path.join(target_folder, "config.json"), "w") as fp:
         json.dump(config_dict, fp, indent=2)
 

web_demo.py

@@ -199,7 +199,7 @@ def combine_history(prompt):
 
 
 def main():
-    torch.cuda.empty_cache()
+    #torch.cuda.empty_cache()
     print("load model begin.")
     model, tokenizer = load_model()
     print("load model end.")
@@ -237,6 +237,7 @@ def main():
             message_placeholder.markdown(cur_response)
         # Add robot response to chat history
         st.session_state.messages.append({"role": "robot", "content": cur_response, "avatar": robot_avator})
+        torch.cuda.empty_cache()
         
 
 if __name__ == "__main__":