{
"cells": [
{
"cell_type": "markdown",
"id": "8f9ba648",
"metadata": {
"tags": [
"papermill-error-cell-tag"
]
},
"source": [
"An Exception was encountered at 'In [9]'."
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "0fa80441",
"metadata": {
"papermill": {
"duration": 0.005046,
"end_time": "2023-09-06T16:21:38.086651",
"exception": false,
"start_time": "2023-09-06T16:21:38.081605",
"status": "completed"
},
"tags": []
},
"source": [
"# RWKV v5\n",
"\n",
"Simple memory training for a small model\n",
"\n",
"**Note:** This project assumes you have the rwkv-infctx conda env setup"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "bbfc0a03",
"metadata": {
"papermill": {
"duration": 0.002135,
"end_time": "2023-09-06T16:21:38.092947",
"exception": false,
"start_time": "2023-09-06T16:21:38.090812",
"status": "completed"
},
"tags": []
},
"source": [
"# Basic Setup"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "1fe0f82c",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:21:38.098818Z",
"iopub.status.busy": "2023-09-06T16:21:38.098531Z",
"iopub.status.idle": "2023-09-06T16:21:38.979393Z",
"shell.execute_reply": "2023-09-06T16:21:38.978561Z"
},
"papermill": {
"duration": 0.886067,
"end_time": "2023-09-06T16:21:38.981283",
"exception": false,
"start_time": "2023-09-06T16:21:38.095216",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CITATION.cff RWKV-v4wavenet\t RWKV-v5headsize32 checkpoint\tnotebook\r\n",
"LICENSE RWKV-v5\t\t RWKV-v5r2\t datapath\toutput\r\n",
"README.md RWKV-v5altwavenet RWKV-v5rstack\t docker\r\n",
"RWKV-v4neo RWKV-v5headsize2x RWKV-v5wavenet model\r\n"
]
}
],
"source": [
"# First lets setup the various directories, and init the model\n",
"!ls ../../../../../\n",
"!mkdir -p ../../../../../model/\n",
"!mkdir -p ../../../../../datapath/\n",
"!mkdir -p ../../../../../checkpoint/"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "333141ec",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:21:38.991928Z",
"iopub.status.busy": "2023-09-06T16:21:38.991392Z",
"iopub.status.idle": "2023-09-06T16:21:41.124533Z",
"shell.execute_reply": "2023-09-06T16:21:41.123643Z"
},
"papermill": {
"duration": 2.140539,
"end_time": "2023-09-06T16:21:41.126606",
"exception": false,
"start_time": "2023-09-06T16:21:38.986067",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n",
"\u001b[0m"
]
}
],
"source": [
"# Additional dependencies for eval stuff\n",
"!pip install -q aiocsv aiofiles"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "5bae6c49",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:21:41.136483Z",
"iopub.status.busy": "2023-09-06T16:21:41.136334Z",
"iopub.status.idle": "2023-09-06T16:21:41.142021Z",
"shell.execute_reply": "2023-09-06T16:21:41.141451Z"
},
"papermill": {
"duration": 0.011523,
"end_time": "2023-09-06T16:21:41.143031",
"exception": false,
"start_time": "2023-09-06T16:21:41.131508",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"DEEPSPEED_STRAT: deepspeed_stage_1\n",
"ENABLE_WANDB: True\n",
"GPU_DEVICES: auto\n",
"DIR_NAME: L12-D2048-E1e-1-ctx4k\n",
"NOTEBOOK_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/notebook/experiment/rwkv-x-exp/v5-r3-memory/L12-D2048-E1e-1-ctx4k\n",
"INFERENCE_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5\n",
"TRAINER_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5\n",
"PROJECT_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer\n"
]
}
],
"source": [
"DEEPSPEED_STRAT=\"deepspeed_stage_1\"\n",
"GPU_DEVICES=\"auto\"\n",
"ENABLE_WANDB=True\n",
"\n",
"# Layer count and embed dim to start with\n",
"LAYER_COUNT=12\n",
"EMBED_DIM=2048\n",
"\n",
"EMBED_SCALE=0.1\n",
"EMBED_SCALE_LABEL=str(EMBED_SCALE).replace(\".\", \"_\")\n",
"\n",
"WANDB_PREFIX=f\"v5r3-L{LAYER_COUNT}-D{EMBED_DIM}-E{EMBED_SCALE}\"\n",
"FILENAME_PREFIX=f\"v5r3-L{LAYER_COUNT}-D{EMBED_DIM}-E{EMBED_SCALE_LABEL}\"\n",
"\n",
"print(\"DEEPSPEED_STRAT:\", DEEPSPEED_STRAT)\n",
"print(\"ENABLE_WANDB:\", ENABLE_WANDB)\n",
"print(\"GPU_DEVICES:\", GPU_DEVICES)\n",
"\n",
"if ENABLE_WANDB:\n",
" WANDB_MODE=\"online\"\n",
"else:\n",
" WANDB_MODE=\"disabled\"\n",
"\n",
"# Computing the notebook, and various paths\n",
"import os\n",
"NOTEBOOK_DIR=os.path.dirname(os.path.abspath(\"__file__\"))\n",
"CONFIG_DIR=os.path.abspath(os.path.join(NOTEBOOK_DIR, \"../\"))\n",
"PROJECT_DIR=os.path.abspath(os.path.join(CONFIG_DIR, \"../../../../\"))\n",
"TRAINER_DIR=os.path.abspath(os.path.join(PROJECT_DIR, \"./RWKV-v5/\"))\n",
"INFERENCE_DIR=os.path.abspath(os.path.join(PROJECT_DIR, \"./RWKV-v5/\"))\n",
"\n",
"# Get the notebook dir name\n",
"DIR_NAME=os.path.basename(NOTEBOOK_DIR)\n",
"\n",
"# Log names and dir\n",
"print(\"DIR_NAME:\", DIR_NAME)\n",
"print(\"NOTEBOOK_DIR:\", NOTEBOOK_DIR)\n",
"print(\"INFERENCE_DIR:\", INFERENCE_DIR)\n",
"print(\"TRAINER_DIR:\", TRAINER_DIR)\n",
"print(\"PROJECT_DIR:\", PROJECT_DIR)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c0de3166",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:21:41.151365Z",
"iopub.status.busy": "2023-09-06T16:21:41.151176Z",
"iopub.status.idle": "2023-09-06T16:27:17.337465Z",
"shell.execute_reply": "2023-09-06T16:27:17.336590Z"
},
"papermill": {
"duration": 336.192521,
"end_time": "2023-09-06T16:27:17.339221",
"exception": false,
"start_time": "2023-09-06T16:21:41.146700",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2023-09-06 16:21:41-- https://huggingface.co/rwkv-x-dev/rwkv-x-playground/resolve/main/experiment/rwkv-x-exp/v5-r3-memory/L12-D2048-E1e-1-ctx4k/v5r3-L12-D2048-E0_1-enwiki-4k.pth\r\n",
"Resolving huggingface.co (huggingface.co)... 13.33.33.102, 13.33.33.110, 13.33.33.20, ...\r\n",
"Connecting to huggingface.co (huggingface.co)|13.33.33.102|:443... connected.\r\n",
"HTTP request sent, awaiting response... "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"302 Found\r\n",
"Location: https://cdn-lfs.huggingface.co/repos/2e/f7/2ef78555202aa92abdbdf476ce3d0fd5a8b15f7245edf0b80d4d30572355f30d/fcd2c54e435c74dc2a43bd3bbde6594de9c6937156caf9f72a77137ed3d49539?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27v5r3-L12-D2048-E0_1-enwiki-4k.pth%3B+filename%3D%22v5r3-L12-D2048-E0_1-enwiki-4k.pth%22%3B&Expires=1694276501&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY5NDI3NjUwMX19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy5odWdnaW5nZmFjZS5jby9yZXBvcy8yZS9mNy8yZWY3ODU1NTIwMmFhOTJhYmRiZGY0NzZjZTNkMGZkNWE4YjE1ZjcyNDVlZGYwYjgwZDRkMzA1NzIzNTVmMzBkL2ZjZDJjNTRlNDM1Yzc0ZGMyYTQzYmQzYmJkZTY1OTRkZTljNjkzNzE1NmNhZjlmNzJhNzcxMzdlZDNkNDk1Mzk%7EcmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qIn1dfQ__&Signature=CI61yjWgEWnbmEXPc-wPNVHfdsEO2SQfSDn7vOjQ7Hh%7EdsoGq591AfvsbeKBNfhOGa5jqdGrS-L83TUjfWEygfteOhNTryi-noWjp6Su6U0Cy0NV742DJDSjTPuCEpiIg1kkKP%7EI5qaveJTJrUQQLahYV20Djlh%7EkLRgNGLplnHLyIJUC5hRX8eyxEdJQnt8nC95k7cKLKz-yWIXtsdoHj%7EZcVToiGG3IFw%7EdNAjm1ns8WTbdW2v8si4lEZd9WCGf0Brx77zxWrFP1Ot9U5fk4AbQzBnmLE-xOLe0w4%7EhSY%7EburifbyLbNO-f-GEY6UFaFni8ILeziJIkPOJPb8mJA__&Key-Pair-Id=KVTP0A1DKRTAX [following]\r\n",
"--2023-09-06 16:21:41-- https://cdn-lfs.huggingface.co/repos/2e/f7/2ef78555202aa92abdbdf476ce3d0fd5a8b15f7245edf0b80d4d30572355f30d/fcd2c54e435c74dc2a43bd3bbde6594de9c6937156caf9f72a77137ed3d49539?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27v5r3-L12-D2048-E0_1-enwiki-4k.pth%3B+filename%3D%22v5r3-L12-D2048-E0_1-enwiki-4k.pth%22%3B&Expires=1694276501&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY5NDI3NjUwMX19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy5odWdnaW5nZmFjZS5jby9yZXBvcy8yZS9mNy8yZWY3ODU1NTIwMmFhOTJhYmRiZGY0NzZjZTNkMGZkNWE4YjE1ZjcyNDVlZGYwYjgwZDRkMzA1NzIzNTVmMzBkL2ZjZDJjNTRlNDM1Yzc0ZGMyYTQzYmQzYmJkZTY1OTRkZTljNjkzNzE1NmNhZjlmNzJhNzcxMzdlZDNkNDk1Mzk%7EcmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qIn1dfQ__&Signature=CI61yjWgEWnbmEXPc-wPNVHfdsEO2SQfSDn7vOjQ7Hh%7EdsoGq591AfvsbeKBNfhOGa5jqdGrS-L83TUjfWEygfteOhNTryi-noWjp6Su6U0Cy0NV742DJDSjTPuCEpiIg1kkKP%7EI5qaveJTJrUQQLahYV20Djlh%7EkLRgNGLplnHLyIJUC5hRX8eyxEdJQnt8nC95k7cKLKz-yWIXtsdoHj%7EZcVToiGG3IFw%7EdNAjm1ns8WTbdW2v8si4lEZd9WCGf0Brx77zxWrFP1Ot9U5fk4AbQzBnmLE-xOLe0w4%7EhSY%7EburifbyLbNO-f-GEY6UFaFni8ILeziJIkPOJPb8mJA__&Key-Pair-Id=KVTP0A1DKRTAX\r\n",
"Resolving cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)... "
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"18.155.68.128, 18.155.68.94, 18.155.68.73, ...\r\n",
"Connecting to cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)|18.155.68.128|:443... connected.\r\n",
"HTTP request sent, awaiting response... "
]
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{
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"200 OK\r\n",
"Length: 1721187013 (1.6G) [binary/octet-stream]\r\n",
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"h 98%[==================> ] 1.58G 9.87MB/s eta 5s "
]
},
{
"name": "stdout",
"output_type": "stream",
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"\r",
" 98%[==================> ] 1.58G 9.45MB/s eta 5s "
]
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{
"name": "stdout",
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"text": [
"\r",
" v 98%[==================> ] 1.58G 9.12MB/s eta 5s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5 98%[==================> ] 1.58G 9.15MB/s eta 5s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r 98%[==================> ] 1.59G 8.76MB/s eta 5s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3 99%[==================> ] 1.59G 8.35MB/s eta 3s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3- 99%[==================> ] 1.59G 8.02MB/s eta 3s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L 99%[==================> ] 1.59G 8.47MB/s eta 3s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L1 99%[==================> ] 1.59G 8.08MB/s eta 3s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L12 99%[==================> ] 1.59G 7.88MB/s eta 3s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L12- 99%[==================> ] 1.60G 7.72MB/s eta 1s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L12-D 99%[==================> ] 1.60G 7.50MB/s eta 1s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L12-D2 99%[==================> ] 1.60G 7.28MB/s eta 1s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L12-D20 99%[==================> ] 1.60G 7.09MB/s eta 1s "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" v5r3-L12-D204 99%[==================> ] 1.60G 6.86MB/s eta 1s \r",
"v5r3-L12-D2048-E0_1 100%[===================>] 1.60G 6.89MB/s in 5m 34s \r\n",
"\r\n",
"2023-09-06 16:27:17 (4.91 MB/s) - ‘v5r3-L12-D2048-E0_1-enwiki-4k.pth’ saved [1721187013/1721187013]\r\n",
"\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"total 1.6G\r\n",
"drwxr-xr-x 2 root root 3 Sep 6 16:21 .\r\n",
"drwxr-xr-x 20 root root 24 Sep 6 16:21 ..\r\n",
"-rw-r--r-- 1 root root 1.7G Sep 6 15:04 v5r3-L12-D2048-E0_1-enwiki-4k.pth\r\n"
]
}
],
"source": [
"# Download the model directly (stop gap till HF sync issues is resolved)\n",
"!cd \"{TRAINER_DIR}\" && cd \"../model/\" && \\\n",
" wget -nc \"https://huggingface.co/rwkv-x-dev/rwkv-x-playground/resolve/main/experiment/rwkv-x-exp/v5-r3-memory/{DIR_NAME}/{FILENAME_PREFIX}-enwiki-4k.pth\"\n",
"\n",
"!cd \"{TRAINER_DIR}\" && cd \"../model/\" && \\\n",
" ls -alh ."
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "5176ef5b",
"metadata": {
"papermill": {
"duration": 0.051299,
"end_time": "2023-09-06T16:27:17.447337",
"exception": false,
"start_time": "2023-09-06T16:27:17.396038",
"status": "completed"
},
"tags": []
},
"source": [
"# Enwiki Stage 2 : Basic Instruct Tuning"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d5c54c51",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:27:17.550805Z",
"iopub.status.busy": "2023-09-06T16:27:17.550559Z",
"iopub.status.idle": "2023-09-06T16:27:32.626011Z",
"shell.execute_reply": "2023-09-06T16:27:32.625244Z"
},
"papermill": {
"duration": 15.129219,
"end_time": "2023-09-06T16:27:32.627774",
"exception": false,
"start_time": "2023-09-06T16:27:17.498555",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Downloading readme: 0%| | 0.00/7.79k [00:00, ?B/s]\r",
"Downloading readme: 100%|██████████████████| 7.79k/7.79k [00:00<00:00, 8.88MB/s]\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Downloading data files: 0%| | 0/1 [00:00, ?it/s]\r\n",
"\r",
"Downloading data: 0%| | 0.00/7.80M [00:00, ?B/s]\u001b[A"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\r",
"Downloading data: 54%|██████████▊ | 4.19M/7.80M [00:03<00:03, 1.13MB/s]\u001b[A\r",
"Downloading data: 100%|████████████████████| 7.80M/7.80M [00:03<00:00, 2.10MB/s]\r\n",
"\r",
"Downloading data files: 100%|█████████████████████| 1/1 [00:03<00:00, 3.72s/it]\r",
"Downloading data files: 100%|█████████████████████| 1/1 [00:03<00:00, 3.72s/it]\r\n",
"\r",
"Extracting data files: 0%| | 0/1 [00:00, ?it/s]\r",
"Extracting data files: 100%|████████████████████| 1/1 [00:00<00:00, 2184.53it/s]\r\n",
"Setting num_proc from 16 back to 1 for the train split to disable multiprocessing as it only contains one shard.\r\n",
"\r",
"Generating train split: 0%| | 0/15015 [00:00, ? examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Generating train split: 100%|██| 15015/15015 [00:00<00:00, 426812.57 examples/s]\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 0%| | 0/15015 [00:00, ? examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 1%| | 83/15015 [00:00<00:35, 424.93 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
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]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
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]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 23%|██▎ | 3449/15015 [00:00<00:01, 8195.54 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 38%|███▍ | 5704/15015 [00:00<00:00, 12379.36 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 50%|████▌ | 7564/15015 [00:00<00:00, 14224.80 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 61%|█████▍ | 9132/15015 [00:00<00:00, 14582.16 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 71%|█████▋ | 10669/15015 [00:00<00:00, 14763.29 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 81%|██████▌ | 12231/15015 [00:01<00:00, 14947.14 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 92%|███████▎| 13770/15015 [00:01<00:00, 13182.64 examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Map (num_proc=16): 100%|█████████| 15015/15015 [00:01<00:00, 9963.96 examples/s]\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Filter (num_proc=16): 0%| | 0/15015 [00:00, ? examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
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]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Filter (num_proc=16): 100%|█████| 15015/15015 [00:00<00:00, 31449.72 examples/s]\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Saving the dataset (0/1 shards): 0%| | 0/14932 [00:00, ? examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Saving the dataset (1/1 shards): 100%|█| 14932/14932 [00:00<00:00, 218347.77 exa\r",
"Saving the dataset (1/1 shards): 100%|█| 14932/14932 [00:00<00:00, 216439.43 exa\r\n",
"\r",
"Saving the dataset (0/1 shards): 0%| | 0/76 [00:00, ? examples/s]\r",
"Saving the dataset (1/1 shards): 100%|█| 76/76 [00:00<00:00, 18721.27 examples/s\r",
"Saving the dataset (1/1 shards): 100%|█| 76/76 [00:00<00:00, 18206.94 examples/s\r\n"
]
}
],
"source": [
"# Lets preload the requried dataset\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" python3 preload_datapath.py \"{CONFIG_DIR}/config-enwiki-instruct.yaml\""
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e110c0bc",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:27:32.739374Z",
"iopub.status.busy": "2023-09-06T16:27:32.738987Z",
"iopub.status.idle": "2023-09-06T16:49:59.819612Z",
"shell.execute_reply": "2023-09-06T16:49:59.818839Z"
},
"papermill": {
"duration": 1347.136045,
"end_time": "2023-09-06T16:49:59.821639",
"exception": false,
"start_time": "2023-09-06T16:27:32.685594",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2023-09-06 16:27:35,671] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[RWKV.model] Running RWKV model using 'torch-jit' with torch '2.0.1+cu118'\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/cli.py:484: UserWarning: LightningCLI's args parameter is intended to run from within Python like if it were from the command line. To prevent mistakes it is not recommended to provide both args and command line arguments, got: sys.argv[1:]=['fit', '-c', '/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/notebook/experiment/rwkv-x-exp/v5-r3-memory/config-enwiki-instruct.yaml', '--trainer.logger.init_args.name=v5r3-L12-D2048-E0.1 - Enwiki-Instruct (train-ctx=4k, deepspeed_stage_1)', '--trainer.strategy=deepspeed_stage_1', '--trainer.devices=auto', '--trainer.callbacks.init_args.dirpath=../checkpoint/v5r3-L12-D2048-E0_1-enwiki-instruct/', '--model.load_model=../model/v5r3-L12-D2048-E0_1-enwiki-4k.pth', '--model.ctx_len=4096', '--model.bptt_learning_range=1'], args=['fit', '-c', '/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/notebook/experiment/rwkv-x-exp/v5-r3-memory/config-enwiki-instruct.yaml', '--trainer.logger.init_args.name=v5r3-L12-D2048-E0.1 - Enwiki-Instruct (train-ctx=4k, deepspeed_stage_1)', '--trainer.strategy=deepspeed_stage_1', '--trainer.devices=auto', '--trainer.callbacks.init_args.dirpath=../checkpoint/v5r3-L12-D2048-E0_1-enwiki-instruct/', '--model.load_model=../model/v5r3-L12-D2048-E0_1-enwiki-4k.pth', '--model.ctx_len=4096', '--model.bptt_learning_range=1'].\r\n",
" rank_zero_warn(\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.10/dist-packages/lightning/fabric/utilities/seed.py:39: UserWarning: No seed found, seed set to 2510647850\r\n",
" rank_zero_warn(f\"No seed found, seed set to {seed}\")\r\n",
"Global seed set to 2510647850\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mpicocreator\u001b[0m (\u001b[33mrwkv-x-dev\u001b[0m). Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.15.9\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in \u001b[35m\u001b[1m./wandb/run-20230906_162738-83nu4box\u001b[0m\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Run \u001b[1m`wandb offline`\u001b[0m to turn off syncing.\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33mv5r3-L12-D2048-E0.1 - Enwiki-Instruct (train-ctx=4k, deepspeed_stage_1)\u001b[0m\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-X-Experiments\u001b[0m\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-X-Experiments/runs/83nu4box\u001b[0m\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.10/dist-packages/lightning/fabric/connector.py:554: UserWarning: bf16 is supported for historical reasons but its usage is discouraged. Please set your precision to bf16-mixed instead!\r\n",
" rank_zero_warn(\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"GPU available: True (cuda), used: True\r\n",
"TPU available: False, using: 0 TPU cores\r\n",
"IPU available: False, using: 0 IPUs\r\n",
"HPU available: False, using: 0 HPUs\r\n",
"\r\n",
"\r\n",
"[RWKV.Trainer] Applying 'target_batch_size' with the following:\r\n",
" - target_batch_size: 32\r\n",
" - num_nodes: 1\r\n",
" - num_devices: 1\r\n",
" - accumulate_grad_batches: 32\r\n",
" - effective_batch_size: 32\r\n",
"\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Saving the dataset (0/1 shards): 0%| | 0/14932 [00:00, ? examples/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Saving the dataset (1/1 shards): 100%|█| 14932/14932 [00:00<00:00, 226572.32 exa\r",
"Saving the dataset (1/1 shards): 100%|█| 14932/14932 [00:00<00:00, 224175.03 exa\r\n",
"\r",
"Saving the dataset (0/1 shards): 0%| | 0/76 [00:00, ? examples/s]\r",
"Saving the dataset (1/1 shards): 100%|█| 76/76 [00:00<00:00, 19090.14 examples/s\r",
"Saving the dataset (1/1 shards): 100%|█| 76/76 [00:00<00:00, 18222.55 examples/s\r\n",
"[rank: 0] Global seed set to 2510647850\r\n",
"initializing deepspeed distributed: GLOBAL_RANK: 0, MEMBER: 1/1\r\n",
"[2023-09-06 16:27:48,828] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enabling DeepSpeed BF16.\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\r\n",
"#\r\n",
"# RWKV lighting_trainer.py important notes \r\n",
"# https://github.com/RWKV/RWKV-infctx-trainer \r\n",
"#\r\n",
"# - Ensure your host is not running cuda 12.0 (use either 11.8, or >=12.1), as this is known to have freeze issues\r\n",
"# - The terms used in wandb / the progress bar can be confusing, see the github README.md for beter clarifications\r\n",
"# - When resuming from checkpoint, the estimated time is inaccurate\r\n",
"#\r\n",
"\r\n",
"[RWKV.model] Configuring optimizer with\r\n",
" - lr_init: 4.000e-04 (0.0004)\r\n",
" - lr_final: 3.000e-04 (0.0003)\r\n",
"\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Using /root/.cache/torch_extensions/py310_cu118 as PyTorch extensions root...\r\n",
"Detected CUDA files, patching ldflags\r\n",
"Emitting ninja build file /root/.cache/torch_extensions/py310_cu118/fused_adam/build.ninja...\r\n",
"Building extension module fused_adam...\r\n",
"Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"ninja: no work to do.\r\n",
"Loading extension module fused_adam...\r\n",
"Time to load fused_adam op: 0.07197451591491699 seconds\r\n",
"Loading `train_dataloader` to estimate number of stepping batches.\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Rank: 0 partition count [1, 1] and sizes[(860549120, False), (768, False)] \r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
" | Name | Type | Params\r\n",
"--------------------------------------\r\n",
"0 | emb | Embedding | 102 M \r\n",
"1 | blocks | ModuleList | 654 M \r\n",
"2 | ln_out | LayerNorm | 4.1 K \r\n",
"3 | head | Linear | 102 M \r\n",
"--------------------------------------\r\n",
"860 M Trainable params\r\n",
"0 Non-trainable params\r\n",
"860 M Total params\r\n",
"3,442.200 Total estimated model params size (MB)\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Training: 0it [00:00, ?it/s]\r",
"Training: 0%| | 0/14932 [00:00, ?it/s]\r",
"Epoch 0: 0%| | 0/14932 [00:00, ?it/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Epoch 0: 0%| | 1/14932 [00:04<19:59:46, 4.82s/it]\r",
"Epoch 0: 0%| | 1/14932 [00:04<20:00:01, 4.82s/it, v_num=4box, train/loss=4.44"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Epoch 0: 0%| | 2/14932 [00:05<12:19:51, 2.97s/it, v_num=4box, train/loss=4.44\r",
"Epoch 0: 0%| | 2/14932 [00:05<12:19:55, 2.97s/it, v_num=4box, train/loss=8.19"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"Epoch 0: 0%| | 3/14932 [00:06<9:03:40, 2.19s/it, v_num=4box, train/loss=8.190\r",
"Epoch 0: 0%| | 3/14932 [00:06<9:03:43, 2.19s/it, v_num=4box, train/loss=5.310"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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"Epoch 0: 100%|█| 14932/14932 [21:18<00:00, 11.68it/s, v_num=4box, train/loss=3.6\r\n",
"\r",
" \u001b[A\r",
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]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"`Trainer.fit` stopped: `max_epochs=1` reached.\r\n",
"\r",
"Epoch 0: 100%|█| 14932/14932 [21:46<00:00, 11.43it/s, v_num=4box, train/loss=3.6\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish... \u001b[32m(success).\u001b[0m\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: \r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: batchidx ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███▁\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: epoch ▁▁▁▁▁▁▁▁▁▁\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: global_rank ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: real_ctx_len ▅▂▇▅█▂▁▃▂▃▃▂▄▁▁▂▃▄▃▃▃▆▂▁▄▅▁▂▁▂▆▁▅▁▃▁▆▅▂▄\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: substep ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███▁\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: train/loss ▇▄▆▄▇▃▇▅▃▆▅▆▆▅▅▃▄▃▃▃▇▅▃▅▅▁▅▆▄▃█▁▆▄▄▅▆▃▄▅\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: trainer/global_step ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: trainer/learning_rate ████▇▇▇▇▇▆▆▆▆▆▆▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▂▂▂▂▂▂▁▁▁\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: validation/loss ▁\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: \r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: batchidx 75\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: epoch 0\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: global_rank 0\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: real_ctx_len 1227\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: substep 75\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 2.65625\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: trainer/global_step 466\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: trainer/learning_rate 0.0003\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: validation/loss 2.93318\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: \r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run \u001b[33mv5r3-L12-D2048-E0.1 - Enwiki-Instruct (train-ctx=4k, deepspeed_stage_1)\u001b[0m at: \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-X-Experiments/runs/83nu4box\u001b[0m\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: ️⚡ View job at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-X-Experiments/jobs/QXJ0aWZhY3RDb2xsZWN0aW9uOjkzMjg5ODA3/version_details/v21\u001b[0m\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)\r\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Find logs at: \u001b[35m\u001b[1m./wandb/run-20230906_162738-83nu4box/logs\u001b[0m\r\n"
]
}
],
"source": [
"# Start the instruct finetuning\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" export WANDB_MODE=\"{WANDB_MODE}\" && \\\n",
" python3 lightning_trainer.py fit \\\n",
" -c \"{CONFIG_DIR}/config-enwiki-instruct.yaml\" \\\n",
" --trainer.logger.init_args.name=\"{WANDB_PREFIX} - Enwiki-Instruct (train-ctx=4k, {DEEPSPEED_STRAT})\" \\\n",
" --trainer.strategy=\"{DEEPSPEED_STRAT}\" \\\n",
" --trainer.devices=\"{GPU_DEVICES}\" \\\n",
" --trainer.callbacks.init_args.dirpath=\"../checkpoint/{FILENAME_PREFIX}-enwiki-instruct/\" \\\n",
" --model.load_model=\"../model/{FILENAME_PREFIX}-enwiki-4k.pth\" \\\n",
" --model.ctx_len=4096 \\\n",
" --model.bptt_learning_range=1"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d290ae75",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:50:01.195431Z",
"iopub.status.busy": "2023-09-06T16:50:01.195130Z",
"iopub.status.idle": "2023-09-06T16:50:09.989273Z",
"shell.execute_reply": "2023-09-06T16:50:09.988569Z"
},
"papermill": {
"duration": 9.475232,
"end_time": "2023-09-06T16:50:09.991009",
"exception": false,
"start_time": "2023-09-06T16:50:00.515777",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2023-09-06 16:50:02,874] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Processing zero checkpoint '../checkpoint/v5r3-L12-D2048-E0_1-enwiki-instruct/last.ckpt/checkpoint'\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Detected checkpoint of type zero stage 1, world_size: 1\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Parsing checkpoint created by deepspeed==0.10.0\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Reconstructed fp32 state dict with 270 params 860549888 elements\r\n",
"Saving bf16 state dict to ../model/v5r3-L12-D2048-E0_1-enwiki-instruct.pth\r\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-rw-r--r-- 1 root root 1.7G Sep 6 16:50 ../model/v5r3-L12-D2048-E0_1-enwiki-instruct.pth\r\n"
]
}
],
"source": [
"# Lets export the model from the checkpoint\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" python3 export_checkpoint.py \"../checkpoint/{FILENAME_PREFIX}-enwiki-instruct/last.ckpt\" \"../model/{FILENAME_PREFIX}-enwiki-instruct.pth\" \"bf16\"\n",
"!cd \"{TRAINER_DIR}\" && ls -alh \"../model/{FILENAME_PREFIX}-enwiki-instruct.pth\""
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ee659e30",
"metadata": {
"execution": {
"iopub.execute_input": "2023-09-06T16:50:11.337129Z",
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"[2023-09-06 16:50:14,300] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
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"--- DRAGON PROMPT ---\r\n",
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"source": [
"# # Lets do a quick dragon prompt validation\n",
"!cd \"{INFERENCE_DIR}\" && \\\n",
" python3 dragon_test.py \"../model/{FILENAME_PREFIX}-enwiki-instruct.pth\" \"cuda fp32\""
]
},
{
"cell_type": "markdown",
"id": "e8720f96",
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"Execution using papermill encountered an exception here and stopped:"
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{
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"execution_count": 9,
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"execution": {
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"status": "failed"
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"outputs": [
{
"ename": "IndentationError",
"evalue": "unexpected indent (598249315.py, line 3)",
"output_type": "error",
"traceback": [
"\u001b[0;36m Cell \u001b[0;32mIn[9], line 3\u001b[0;36m\u001b[0m\n\u001b[0;31m python3 ../memory_script/eval_v5_memory_guided.py \"{PROJECT_DIR}/model/{FILENAME_PREFIX}-enwiki-instruct.pth\"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m unexpected indent\n"
]
}
],
"source": [
"# Lets do a quick memory test\n",
"!python3\n",
" python3 ../memory_script/eval_v5_memory_guided.py \"{PROJECT_DIR}/model/{FILENAME_PREFIX}-enwiki-instruct.pth\""
]
},
{
"cell_type": "markdown",
"id": "30ba2692",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
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"tags": []
},
"source": [
"## Tune 1 : Simple Memory instruct finetuning\n",
"\n",
"- Tune 1: Low ctx size (512), Training with only the input masked. This does very limited memory training, and is used primarily to train the instruction set."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f4b49799",
"metadata": {
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"outputs": [],
"source": [
"%%script bash\n",
"\n",
"########################################\n",
"# Generate the required jsonl dataset\n",
"########################################\n",
"\n",
"# Reset the dataset dir\n",
"mkdir -p ../dataset\n",
"rm -rf ../dataset/*.jsonl\n",
"\n",
"# Generate the various datasets\n",
"echo \"## Generating word reptition dataset ##\"\n",
"\n",
"# We do a strong bias for smaller word count, to teach the concept from scratch\n",
"# so that the model can learn the function. \n",
"#\n",
"# Note that all document samples, are randomized between the target word count, \n",
"# to half of the target word count.\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-2-count.jsonl 2 5000 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-5-count.jsonl 5 5000 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-10-count.jsonl 10 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-15-count.jsonl 15 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-20-count.jsonl 20 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-25-count.jsonl 25 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-40-count.jsonl 40 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-50-count.jsonl 50 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-60-count.jsonl 80 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-80-count.jsonl 80 2500 &\n",
"\n",
"# With a slight mix of the larger word count\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-100-count.jsonl 100 2500 &\n",
"python3 ../memory_script/gen_limited_segmented_jsonl.py ../dataset/word-200-count.jsonl 200 2500 &\n",
"\n",
"wait\n",
"echo \"## Done ##\"\n",
"\n",
"ls -alh ../dataset/"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f45649ff",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
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"status": "pending"
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"tags": []
},
"outputs": [],
"source": [
"# Start the finetune model training\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" export WANDB_MODE=\"{WANDB_MODE}\" && \\\n",
" python3 lightning_trainer.py fit \\\n",
" -c \"{CONFIG_DIR}/config-mem-instruct.yaml\" \\\n",
" --trainer.logger.init_args.name=\"{WANDB_PREFIX} - Mem-Instruct (train-ctx=512, {DEEPSPEED_STRAT})\" \\\n",
" --trainer.strategy=\"{DEEPSPEED_STRAT}\" \\\n",
" --trainer.devices=\"{GPU_DEVICES}\" \\\n",
" --trainer.callbacks.init_args.dirpath=\"../checkpoint/{FILENAME_PREFIX}-mem-instruct/\" \\\n",
" --model.load_model=\"../model/{FILENAME_PREFIX}-enwiki-instruct.pth\" \\\n",
" --model.ctx_len=512 \\\n",
" --model.bptt_learning_range=1"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "eee1dae8",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"# Lets export the model from the checkpoint\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" python3 export_checkpoint.py \\\n",
" \"../checkpoint/{FILENAME_PREFIX}-mem-instruct/last.ckpt\" \\\n",
" \"../model/{FILENAME_PREFIX}-mem-instruct.pth\" \"bf16\"\n",
"!cd \"{TRAINER_DIR}\" && ls -alh \"../model/{FILENAME_PREFIX}-mem-instruct.pth\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "77c46f2c",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"# Lets do a quick memory test\n",
"!python3 ../memory_script/eval_v5_memory_guided.py \"{PROJECT_DIR}/model/{FILENAME_PREFIX}-mem-instruct.pth\""
]
},
{
"cell_type": "markdown",
"id": "afe593cc",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"source": [
"## Tune 2 : Low ctx size (512), memory training\n",
"\n",
"- Tune 2: Low ctx size (512), Training with instruction & input masked. This forces the actual memory training on the output tokens."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e27a0ba5",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
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"status": "pending"
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"tags": []
},
"outputs": [],
"source": [
"%%script bash\n",
"\n",
"########################################\n",
"# Generate the required jsonl dataset\n",
"########################################\n",
"\n",
"# Reset the dataset dir\n",
"mkdir -p ../dataset\n",
"rm -rf ../dataset/*.jsonl\n",
"\n",
"# Generate the various datasets\n",
"echo \"## Generating word reptition dataset ##\"\n",
"\n",
"#\n",
"# We switch over to fully masked instruct+input, to properly learn the memorization task\n",
"#\n",
"python3 ../memory_script/gen_limited_prompt_completion_jsonl.py ../dataset/word-2-count.jsonl 2 5000 &\n",
"for i in {5..95..5} \n",
"do\n",
" python3 ../memory_script/gen_limited_prompt_completion_jsonl.py ../dataset/gen-word-$i-count.jsonl $i 5000 & \n",
"done\n",
"python3 ../memory_script/gen_limited_prompt_completion_jsonl.py ../dataset/word-100-count.jsonl 100 5000 &\n",
"python3 ../memory_script/gen_limited_prompt_completion_jsonl.py ../dataset/word-200-count.jsonl 200 5000 &\n",
"\n",
"#\n",
"# We mixin the shuffled word list, so that we ensure all words / tokens are learned\n",
"# however this might intrduce an exclusion bias (if seen this word, never repeat it), \n",
"# so we limit the mixture of this data samples\n",
"#\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-10-count.jsonl 10 20 &\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-15-count.jsonl 15 20 &\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-25-count.jsonl 25 30 &\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-50-count.jsonl 50 50 &\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-75-count.jsonl 75 50 &\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-100-count.jsonl 100 50 &\n",
"python3 ../memory_script/shuffle_limited_prompt_completion_jsonl.py ../dataset/shuffle-word-200-count.jsonl 200 50 &\n",
"\n",
"wait\n",
"echo \"## Done ##\"\n",
"\n",
"ls -alh ../dataset/"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "71899f60",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"# Start the finetune model training\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" export WANDB_MODE=\"{WANDB_MODE}\" && \\\n",
" python3 lightning_trainer.py fit \\\n",
" -c \"{CONFIG_DIR}/config-mem-template.yaml\" \\\n",
" --trainer.logger.init_args.name=\"{WANDB_PREFIX} - Mem-Tune ctx-512 (train-ctx=512, {DEEPSPEED_STRAT})\" \\\n",
" --trainer.strategy=\"{DEEPSPEED_STRAT}\" \\\n",
" --trainer.devices=\"{GPU_DEVICES}\" \\\n",
" --trainer.callbacks.init_args.dirpath=\"../checkpoint/{FILENAME_PREFIX}-mem-ctx-512/\" \\\n",
" --model.lr_init=5e-4 \\\n",
" --model.lr_final=4e-4 \\\n",
" --data.max_token_size=512 \\\n",
" --model.ctx_len=512 \\\n",
" --model.bptt_learning_range=1 \\\n",
" --model.load_model=\"../model/{FILENAME_PREFIX}-mem-instruct.pth\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "29773d32",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
},
"tags": []
},
"outputs": [],
"source": [
"# Lets export the model from the checkpoint\n",
"!cd \"{TRAINER_DIR}\" && \\\n",
" python3 export_checkpoint.py \\\n",
" \"../checkpoint/{FILENAME_PREFIX}-mem-ctx-512/last.ckpt\" \\\n",
" \"../model/{FILENAME_PREFIX}-mem-ctx-512.pth\" \"bf16\"\n",
"!cd \"{TRAINER_DIR}\" && ls -alh \"../model/{FILENAME_PREFIX}-mem-ctx-512.pth\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "680bcd20",
"metadata": {
"papermill": {
"duration": null,
"end_time": null,
"exception": null,
"start_time": null,
"status": "pending"
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"tags": []
},
"outputs": [],
"source": [
"# Lets do a quick memory test\n",
"!python3 ../memory_script/eval_v5_memory_guided.py \"{PROJECT_DIR}/model/{FILENAME_PREFIX}-mem-ctx-512.pth\""
]
}
],
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