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[GHA] experiment/rwkv-x-exp/multi-size-train/v5-L12-D2048-part1.ipynb result notebook & reports

#183
by picocreator - opened
base: refs/heads/main
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from: refs/pr/183
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  1. .gitattributes +1 -0
  2. experiment/rwkv-x-exp/multi-size-train/v5-L12-D2048-part1.ipynb +3 -2222
.gitattributes CHANGED
@@ -99,3 +99,4 @@ experiment/rwkv-x-exp/v5-r3-memory/L6-D2560-E1e-1-ctx4k/stage5.ipynb filter=lfs
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  experiment/rwkv-x-exp/v5-r3-memory/L6-D2048-E1e-1-ctx4k/stage5.ipynb filter=lfs diff=lfs merge=lfs -text
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  experiment/rwkv-x-exp/multi-size-train/v5-L6-D2048-part1.ipynb filter=lfs diff=lfs merge=lfs -text
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  experiment/rwkv-x-exp/multi-size-train/v5-L6-D2048-baseline.ipynb filter=lfs diff=lfs merge=lfs -text
 
 
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  experiment/rwkv-x-exp/v5-r3-memory/L6-D2048-E1e-1-ctx4k/stage5.ipynb filter=lfs diff=lfs merge=lfs -text
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  experiment/rwkv-x-exp/multi-size-train/v5-L6-D2048-part1.ipynb filter=lfs diff=lfs merge=lfs -text
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  experiment/rwkv-x-exp/multi-size-train/v5-L6-D2048-baseline.ipynb filter=lfs diff=lfs merge=lfs -text
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+ experiment/rwkv-x-exp/multi-size-train/v5-L12-D2048-part1.ipynb filter=lfs diff=lfs merge=lfs -text
experiment/rwkv-x-exp/multi-size-train/v5-L12-D2048-part1.ipynb CHANGED
@@ -1,2222 +1,3 @@
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- {
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- "cells": [
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- {
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- "attachments": {},
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- "cell_type": "markdown",
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- "id": "3a71b6b3",
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- "metadata": {
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- "papermill": {
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- "duration": 0.003347,
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- "end_time": "2023-09-29T09:57:11.488052",
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- "exception": false,
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- "start_time": "2023-09-29T09:57:11.484705",
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- "status": "completed"
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- },
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- "tags": []
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- },
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- "source": [
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- "# RWKV v5 multi-size training experiment\n",
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- "\n",
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- "**Note:** This project assumes you have the rwkv-infctx conda env setup"
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- ]
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- },
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- {
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- "attachments": {},
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- "cell_type": "markdown",
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- "id": "73dce349",
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- "metadata": {
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- "papermill": {
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- "duration": 0.002599,
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- "end_time": "2023-09-29T09:57:11.495409",
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- "exception": false,
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- "start_time": "2023-09-29T09:57:11.492810",
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- "status": "completed"
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- },
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- "tags": []
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- },
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- "source": [
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- "# Basic Setup"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 1,
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- "id": "2fa01ec7",
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- "metadata": {
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- "execution": {
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- "iopub.execute_input": "2023-09-29T09:57:11.502573Z",
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- "iopub.status.busy": "2023-09-29T09:57:11.502067Z",
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- "iopub.status.idle": "2023-09-29T09:57:12.255533Z",
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- "shell.execute_reply": "2023-09-29T09:57:12.254559Z"
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- },
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- "papermill": {
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- "duration": 0.759642,
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- "end_time": "2023-09-29T09:57:12.257872",
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- "exception": false,
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- "start_time": "2023-09-29T09:57:11.498230",
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- "status": "completed"
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- },
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- "tags": []
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- },
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- "outputs": [],
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- "source": [
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- "# First lets setup the various directories, and init the model\n",
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- "!mkdir -p ../../../../model/\n",
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- "!mkdir -p ../../../../datapath/\n",
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- "!mkdir -p ../../../../checkpoint/"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 2,
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- "id": "39dd6623",
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- "metadata": {
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- "execution": {
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- "iopub.execute_input": "2023-09-29T09:57:12.265541Z",
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- "iopub.status.busy": "2023-09-29T09:57:12.264984Z",
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- "iopub.status.idle": "2023-09-29T09:57:12.272639Z",
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- "shell.execute_reply": "2023-09-29T09:57:12.271887Z"
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- },
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- "papermill": {
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- "duration": 0.013629,
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- "end_time": "2023-09-29T09:57:12.274503",
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- "exception": false,
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- "start_time": "2023-09-29T09:57:12.260874",
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- "status": "completed"
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- },
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- "tags": []
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- },
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "DEEPSPEED_STRAT: deepspeed_stage_1\n",
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- "ENABLE_WANDB: True\n",
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- "GPU_DEVICES: auto\n",
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- "NOTEBOOK_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/notebook/experiment/rwkv-x-exp/multi-size-train\n",
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- "INFERENCE_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5\n",
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- "TRAINER_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5\n",
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- "PROJECT_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer\n"
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- ]
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- }
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- ],
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- "source": [
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- "DEEPSPEED_STRAT=\"deepspeed_stage_1\"\n",
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- "GPU_DEVICES=\"auto\"\n",
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- "ENABLE_WANDB=True\n",
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- "\n",
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- "EMBED_SCALE=0.01\n",
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- "EMBED_SCALE_LABEL=str(EMBED_SCALE).replace(\".\", \"_\")\n",
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- "\n",
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- "LAYER_COUNT=12\n",
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- "EMBED_SIZE=2048\n",
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- "\n",
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- "WANDB_PREFIX=f\"[Multi-size] v5-L{LAYER_COUNT}-D{EMBED_SIZE}-E{EMBED_SCALE}\"\n",
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- "FILENAME_PREFIX=f\"v5-L{LAYER_COUNT}-D{EMBED_SIZE}-E{EMBED_SCALE_LABEL}\"\n",
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- "\n",
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- "print(\"DEEPSPEED_STRAT:\", DEEPSPEED_STRAT)\n",
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- "print(\"ENABLE_WANDB:\", ENABLE_WANDB)\n",
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- "print(\"GPU_DEVICES:\", GPU_DEVICES)\n",
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- "\n",
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- "if ENABLE_WANDB:\n",
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- " WANDB_MODE=\"online\"\n",
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- "else:\n",
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- " WANDB_MODE=\"disabled\"\n",
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- "\n",
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- "# Computing the notebook, and various paths\n",
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- "import os\n",
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- "NOTEBOOK_DIR=os.path.dirname(os.path.abspath(\"__file__\"))\n",
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- "PROJECT_DIR=os.path.abspath(os.path.join(NOTEBOOK_DIR, \"../../../../\"))\n",
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- "TRAINER_DIR=os.path.abspath(os.path.join(PROJECT_DIR, \"./RWKV-v5/\"))\n",
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- "INFERENCE_DIR=os.path.abspath(os.path.join(PROJECT_DIR, \"./RWKV-v5/\"))\n",
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- "\n",
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- "print(\"NOTEBOOK_DIR:\", NOTEBOOK_DIR)\n",
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- "print(\"INFERENCE_DIR:\", INFERENCE_DIR)\n",
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- "print(\"TRAINER_DIR:\", TRAINER_DIR)\n",
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- "print(\"PROJECT_DIR:\", PROJECT_DIR)"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 3,
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- "id": "cf99b23f",
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- "metadata": {
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- "execution": {
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- "iopub.execute_input": "2023-09-29T09:57:12.282369Z",
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- "iopub.status.busy": "2023-09-29T09:57:12.281873Z",
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- "iopub.status.idle": "2023-09-29T09:57:56.980304Z",
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- "shell.execute_reply": "2023-09-29T09:57:56.979053Z"
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- },
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- "papermill": {
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- "duration": 44.705166,
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- "end_time": "2023-09-29T09:57:56.982856",
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- "exception": false,
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- "start_time": "2023-09-29T09:57:12.277690",
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- "status": "completed"
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- },
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- "tags": []
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- },
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "[2023-09-29 09:57:16,435] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
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- ]
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- },
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "[RWKV.model] Running RWKV model using 'torch-jit' with torch '2.0.1+cu118'\r\n",
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- "---- Initializing model ----\r\n",
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- "No of layers: 12\r\n",
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- "Embedding size: 2048\r\n",
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- "Output model path: ../model/v5-L12-D2048-E0_01-neox-v5base-init.pth\r\n",
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- "Vocab size: 50277\r\n",
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- "Emb scale: 0.01\r\n",
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- "Note: this process takes a significant time (and ram) for large models\r\n",
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- "---- ----- ----\r\n"
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- ]
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- },
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "50277 2048 -0.01 emb.weight\r\n"
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- ]
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- },
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- {
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- "output_type": "stream",
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- "2048 2048 1.0 blocks.0.att.gate.weight\r\n"
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- "2048 2048 1.0 blocks.0.att.receptance.weight\r\n"
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529
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536
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- {
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- "name": "stdout",
540
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543
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544
- ]
545
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548
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- "2048 2048 0 blocks.7.ffn.receptance.weight\r\n",
551
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552
- "2048 2048 1.0 blocks.8.att.gate.weight\r\n"
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567
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574
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579
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581
- "7168 2048 1.0 blocks.8.ffn.key.weight\r\n"
582
- ]
583
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- "name": "stdout",
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- "2048 2048 0 blocks.8.ffn.receptance.weight\r\n",
589
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618
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619
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622
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623
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625
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626
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627
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629
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630
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631
- "text": [
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633
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634
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648
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655
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659
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660
- "text": [
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662
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663
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664
- {
665
- "name": "stdout",
666
- "output_type": "stream",
667
- "text": [
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669
- "7168 2048 1.0 blocks.10.ffn.key.weight\r\n"
670
- ]
671
- },
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- {
673
- "name": "stdout",
674
- "output_type": "stream",
675
- "text": [
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677
- "2048 7168 0 blocks.10.ffn.value.weight\r\n"
678
- ]
679
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- {
681
- "name": "stdout",
682
- "output_type": "stream",
683
- "text": [
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- "2048 2048 1.0 blocks.11.att.gate.weight\r\n"
685
- ]
686
- },
687
- {
688
- "name": "stdout",
689
- "output_type": "stream",
690
- "text": [
691
- "2048 2048 1.0 blocks.11.att.receptance.weight\r\n"
692
- ]
693
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694
- {
695
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696
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697
- "text": [
698
- "2048 2048 1.0 blocks.11.att.key.weight\r\n"
699
- ]
700
- },
701
- {
702
- "name": "stdout",
703
- "output_type": "stream",
704
- "text": [
705
- "2048 2048 1.0 blocks.11.att.value.weight\r\n"
706
- ]
707
- },
708
- {
709
- "name": "stdout",
710
- "output_type": "stream",
711
- "text": [
712
- "2048 2048 0 blocks.11.att.output.weight\r\n",
713
- "7168 2048 1.0 blocks.11.ffn.key.weight\r\n"
714
- ]
715
- },
716
- {
717
- "name": "stdout",
718
- "output_type": "stream",
719
- "text": [
720
- "2048 2048 0 blocks.11.ffn.receptance.weight\r\n",
721
- "2048 7168 0 blocks.11.ffn.value.weight\r\n"
722
- ]
723
- },
724
- {
725
- "name": "stdout",
726
- "output_type": "stream",
727
- "text": [
728
- "50277 2048 0.5 head.weight\r\n"
729
- ]
730
- }
731
- ],
732
- "source": [
733
- "# Init the model\n",
734
- "!cd \"{TRAINER_DIR}\" && \\\n",
735
- " python3 ./init_model.py \\\n",
736
- " --n_layer {LAYER_COUNT} --n_embd {EMBED_SIZE} \\\n",
737
- " --emb-scale \"{EMBED_SCALE}\" \\\n",
738
- " --vocab_size neox --skip-if-exists \\\n",
739
- " \"../model/{FILENAME_PREFIX}-neox-v5base-init.pth\""
740
- ]
741
- },
742
- {
743
- "cell_type": "markdown",
744
- "id": "0c176d9f",
745
- "metadata": {
746
- "papermill": {
747
- "duration": 0.008403,
748
- "end_time": "2023-09-29T09:57:57.000220",
749
- "exception": false,
750
- "start_time": "2023-09-29T09:57:56.991817",
751
- "status": "completed"
752
- },
753
- "tags": []
754
- },
755
- "source": [
756
- "## Enwiki Stage 1 : Foundation 4k model training"
757
- ]
758
- },
759
- {
760
- "cell_type": "code",
761
- "execution_count": 4,
762
- "id": "bd55a062",
763
- "metadata": {
764
- "execution": {
765
- "iopub.execute_input": "2023-09-29T09:57:57.020044Z",
766
- "iopub.status.busy": "2023-09-29T09:57:57.019632Z",
767
- "iopub.status.idle": "2023-09-29T09:58:08.660786Z",
768
- "shell.execute_reply": "2023-09-29T09:58:08.660057Z"
769
- },
770
- "papermill": {
771
- "duration": 11.65489,
772
- "end_time": "2023-09-29T09:58:08.664002",
773
- "exception": false,
774
- "start_time": "2023-09-29T09:57:57.009112",
775
- "status": "completed"
776
- },
777
- "tags": []
778
- },
779
- "outputs": [
780
- {
781
- "name": "stdout",
782
- "output_type": "stream",
783
- "text": [
784
- "\r",
785
- "Saving the dataset (0/3 shards): 0%| | 0/54401 [00:00<?, ? examples/s]"
786
- ]
787
- },
788
- {
789
- "name": "stdout",
790
- "output_type": "stream",
791
- "text": [
792
- "\r",
793
- "Saving the dataset (0/3 shards): 4%| | 2000/54401 [00:00<00:03, 15197.33 examp"
794
- ]
795
- },
796
- {
797
- "name": "stdout",
798
- "output_type": "stream",
799
- "text": [
800
- "\r",
801
- "Saving the dataset (0/3 shards): 7%| | 4000/54401 [00:00<00:03, 15929.46 examp"
802
- ]
803
- },
804
- {
805
- "name": "stdout",
806
- "output_type": "stream",
807
- "text": [
808
- "\r",
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- "Saving the dataset (0/3 shards): 11%| | 6000/54401 [00:00<00:02, 16418.37 examp"
810
- ]
811
- },
812
- {
813
- "name": "stdout",
814
- "output_type": "stream",
815
- "text": [
816
- "\r",
817
- "Saving the dataset (0/3 shards): 15%|▏| 8000/54401 [00:00<00:02, 16923.89 examp"
818
- ]
819
- },
820
- {
821
- "name": "stdout",
822
- "output_type": "stream",
823
- "text": [
824
- "\r",
825
- "Saving the dataset (0/3 shards): 18%|▏| 10000/54401 [00:00<00:02, 17273.31 exam"
826
- ]
827
- },
828
- {
829
- "name": "stdout",
830
- "output_type": "stream",
831
- "text": [
832
- "\r",
833
- "Saving the dataset (0/3 shards): 22%|▏| 12000/54401 [00:00<00:02, 17662.61 exam"
834
- ]
835
- },
836
- {
837
- "name": "stdout",
838
- "output_type": "stream",
839
- "text": [
840
- "\r",
841
- "Saving the dataset (0/3 shards): 26%|▎| 14000/54401 [00:00<00:02, 17923.49 exam"
842
- ]
843
- },
844
- {
845
- "name": "stdout",
846
- "output_type": "stream",
847
- "text": [
848
- "\r",
849
- "Saving the dataset (0/3 shards): 29%|▎| 16000/54401 [00:00<00:02, 18184.27 exam"
850
- ]
851
- },
852
- {
853
- "name": "stdout",
854
- "output_type": "stream",
855
- "text": [
856
- "\r",
857
- "Saving the dataset (0/3 shards): 33%|▎| 18000/54401 [00:01<00:01, 18438.75 exam\r",
858
- "Saving the dataset (1/3 shards): 33%|▎| 18134/54401 [00:01<00:01, 18438.75 exam"
859
- ]
860
- },
861
- {
862
- "name": "stdout",
863
- "output_type": "stream",
864
- "text": [
865
- "\r",
866
- "Saving the dataset (1/3 shards): 37%|▎| 20134/54401 [00:01<00:01, 17356.03 exam"
867
- ]
868
- },
869
- {
870
- "name": "stdout",
871
- "output_type": "stream",
872
- "text": [
873
- "\r",
874
- "Saving the dataset (1/3 shards): 41%|▍| 22134/54401 [00:01<00:01, 17970.31 exam"
875
- ]
876
- },
877
- {
878
- "name": "stdout",
879
- "output_type": "stream",
880
- "text": [
881
- "\r",
882
- "Saving the dataset (1/3 shards): 44%|▍| 24134/54401 [00:01<00:01, 18401.36 exam"
883
- ]
884
- },
885
- {
886
- "name": "stdout",
887
- "output_type": "stream",
888
- "text": [
889
- "\r",
890
- "Saving the dataset (1/3 shards): 48%|▍| 26134/54401 [00:01<00:01, 18772.52 exam"
891
- ]
892
- },
893
- {
894
- "name": "stdout",
895
- "output_type": "stream",
896
- "text": [
897
- "\r",
898
- "Saving the dataset (1/3 shards): 52%|▌| 28134/54401 [00:01<00:01, 19015.25 exam"
899
- ]
900
- },
901
- {
902
- "name": "stdout",
903
- "output_type": "stream",
904
- "text": [
905
- "\r",
906
- "Saving the dataset (1/3 shards): 55%|▌| 30134/54401 [00:01<00:01, 19175.86 exam"
907
- ]
908
- },
909
- {
910
- "name": "stdout",
911
- "output_type": "stream",
912
- "text": [
913
- "\r",
914
- "Saving the dataset (1/3 shards): 59%|▌| 32134/54401 [00:01<00:01, 19340.44 exam"
915
- ]
916
- },
917
- {
918
- "name": "stdout",
919
- "output_type": "stream",
920
- "text": [
921
- "\r",
922
- "Saving the dataset (1/3 shards): 63%|▋| 34134/54401 [00:01<00:01, 19458.62 exam"
923
- ]
924
- },
925
- {
926
- "name": "stdout",
927
- "output_type": "stream",
928
- "text": [
929
- "\r",
930
- "Saving the dataset (1/3 shards): 67%|▋| 36268/54401 [00:01<00:00, 19480.21 exam\r",
931
- "Saving the dataset (2/3 shards): 67%|▋| 36268/54401 [00:01<00:00, 19480.21 exam"
932
- ]
933
- },
934
- {
935
- "name": "stdout",
936
- "output_type": "stream",
937
- "text": [
938
- "\r",
939
- "Saving the dataset (2/3 shards): 72%|▋| 39268/54401 [00:02<00:00, 19488.59 exam"
940
- ]
941
- },
942
- {
943
- "name": "stdout",
944
- "output_type": "stream",
945
- "text": [
946
- "\r",
947
- "Saving the dataset (2/3 shards): 80%|▊| 43268/54401 [00:02<00:00, 19830.22 exam"
948
- ]
949
- },
950
- {
951
- "name": "stdout",
952
- "output_type": "stream",
953
- "text": [
954
- "\r",
955
- "Saving the dataset (2/3 shards): 87%|▊| 47268/54401 [00:02<00:00, 20058.57 exam"
956
- ]
957
- },
958
- {
959
- "name": "stdout",
960
- "output_type": "stream",
961
- "text": [
962
- "\r",
963
- "Saving the dataset (2/3 shards): 94%|▉| 51268/54401 [00:02<00:00, 20178.13 exam"
964
- ]
965
- },
966
- {
967
- "name": "stdout",
968
- "output_type": "stream",
969
- "text": [
970
- "\r",
971
- "Saving the dataset (2/3 shards): 100%|█| 54401/54401 [00:02<00:00, 20197.74 exam\r",
972
- "Saving the dataset (3/3 shards): 100%|█| 54401/54401 [00:02<00:00, 20197.74 exam\r",
973
- "Saving the dataset (3/3 shards): 100%|█| 54401/54401 [00:02<00:00, 18877.90 exam\r\n",
974
- "\r",
975
- "Saving the dataset (0/1 shards): 0%| | 0/109 [00:00<?, ? examples/s]"
976
- ]
977
- },
978
- {
979
- "name": "stdout",
980
- "output_type": "stream",
981
- "text": [
982
- "\r",
983
- "Saving the dataset (1/1 shards): 100%|█| 109/109 [00:00<00:00, 7330.11 examples/\r",
984
- "Saving the dataset (1/1 shards): 100%|█| 109/109 [00:00<00:00, 7058.50 examples/\r\n"
985
- ]
986
- }
987
- ],
988
- "source": [
989
- "# Lets preload the requried dataset \n",
990
- "!cd \"{TRAINER_DIR}\" && \\\n",
991
- " python3 preload_datapath.py \"{NOTEBOOK_DIR}/enwiki-4k-part1.yaml\""
992
- ]
993
- },
994
- {
995
- "cell_type": "code",
996
- "execution_count": 5,
997
- "id": "5e1ede96",
998
- "metadata": {
999
- "execution": {
1000
- "iopub.execute_input": "2023-09-29T09:58:08.702501Z",
1001
- "iopub.status.busy": "2023-09-29T09:58:08.701875Z",
1002
- "iopub.status.idle": "2023-09-29T10:00:21.515956Z",
1003
- "shell.execute_reply": "2023-09-29T10:00:21.514599Z"
1004
- },
1005
- "papermill": {
1006
- "duration": 132.843495,
1007
- "end_time": "2023-09-29T10:00:21.518814",
1008
- "exception": false,
1009
- "start_time": "2023-09-29T09:58:08.675319",
1010
- "status": "completed"
1011
- },
1012
- "tags": []
1013
- },
1014
- "outputs": [
1015
- {
1016
- "name": "stdout",
1017
- "output_type": "stream",
1018
- "text": [
1019
- "[2023-09-29 09:58:12,868] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
1020
- ]
1021
- },
1022
- {
1023
- "name": "stdout",
1024
- "output_type": "stream",
1025
- "text": [
1026
- "[RWKV.model] Running RWKV model using 'torch-jit' with torch '2.0.1+cu118'\r\n"
1027
- ]
1028
- },
1029
- {
1030
- "name": "stdout",
1031
- "output_type": "stream",
1032
- "text": [
1033
- "/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/multi-size-train/enwiki-4k-part1.yaml', '--trainer.logger.init_args.name=[Multi-size] v5-L12-D2048-E0.01 - Enwiki-4k Part 1 (train-ctx=4k, deepspeed_stage_1)', '--trainer.strategy=deepspeed_stage_1', '--trainer.devices=auto', '--trainer.callbacks.init_args.dirpath=../checkpoint/v5-L12-D2048-E0_01-enwiki-4k-p1/', '--model.load_model=../model/v5-L12-D2048-E0_01-neox-v5base-init.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/multi-size-train/enwiki-4k-part1.yaml', '--trainer.logger.init_args.name=[Multi-size] v5-L12-D2048-E0.01 - Enwiki-4k Part 1 (train-ctx=4k, deepspeed_stage_1)', '--trainer.strategy=deepspeed_stage_1', '--trainer.devices=auto', '--trainer.callbacks.init_args.dirpath=../checkpoint/v5-L12-D2048-E0_01-enwiki-4k-p1/', '--model.load_model=../model/v5-L12-D2048-E0_01-neox-v5base-init.pth', '--model.ctx_len=4096', '--model.bptt_learning_range=1'].\r\n",
1034
- " rank_zero_warn(\r\n"
1035
- ]
1036
- },
1037
- {
1038
- "name": "stdout",
1039
- "output_type": "stream",
1040
- "text": [
1041
- "/usr/local/lib/python3.10/dist-packages/lightning/fabric/utilities/seed.py:39: UserWarning: No seed found, seed set to 207026176\r\n",
1042
- " rank_zero_warn(f\"No seed found, seed set to {seed}\")\r\n",
1043
- "Global seed set to 207026176\r\n"
1044
- ]
1045
- },
1046
- {
1047
- "name": "stdout",
1048
- "output_type": "stream",
1049
- "text": [
1050
- "\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"
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- "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.15.11\r\n",
1058
- "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in \u001b[35m\u001b[1m./wandb/run-20230929_095815-3rwyj6ei\u001b[0m\r\n",
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- "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-5X-Experiments\u001b[0m\r\n",
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- "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-5X-Experiments/runs/3rwyj6ei\u001b[0m\r\n"
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- "[rank: 0] Global seed set to 207026176\r\n",
1277
- "initializing deepspeed distributed: GLOBAL_RANK: 0, MEMBER: 1/1\r\n",
1278
- "[2023-09-29 09:58:33,172] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented\r\n"
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- },
1281
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1285
- "Enabling DeepSpeed BF16.\r\n"
1286
- ]
1287
- },
1288
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- "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\r\n",
1293
- "#\r\n",
1294
- "# RWKV lighting_trainer.py important notes \r\n",
1295
- "# https://github.com/RWKV/RWKV-infctx-trainer \r\n",
1296
- "#\r\n",
1297
- "# - 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",
1298
- "# - The terms used in wandb / the progress bar can be confusing, see the github README.md for beter clarifications\r\n",
1299
- "# - When resuming from checkpoint, the estimated time is inaccurate\r\n",
1300
- "#\r\n",
1301
- "\r\n",
1302
- "[RWKV.model] Configuring optimizer with\r\n",
1303
- " - lr_init: 6.000e-04 (0.0006)\r\n",
1304
- " - lr_final: 5.000e-04 (0.0005)\r\n",
1305
- "\r\n",
1306
- "Using /root/.cache/torch_extensions/py310_cu118 as PyTorch extensions root...\r\n"
1307
- ]
1308
- },
1309
- {
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1311
- "output_type": "stream",
1312
- "text": [
1313
- "Detected CUDA files, patching ldflags\r\n",
1314
- "Emitting ninja build file /root/.cache/torch_extensions/py310_cu118/fused_adam/build.ninja...\r\n",
1315
- "Building extension module fused_adam...\r\n",
1316
- "Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)\r\n"
1317
- ]
1318
- },
1319
- {
1320
- "name": "stdout",
1321
- "output_type": "stream",
1322
- "text": [
1323
- "ninja: no work to do.\r\n",
1324
- "Loading extension module fused_adam...\r\n",
1325
- "Time to load fused_adam op: 0.07915163040161133 seconds\r\n",
1326
- "Loading `train_dataloader` to estimate number of stepping batches.\r\n"
1327
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1328
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1329
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- "Rank: 0 partition count [1, 1] and sizes[(860549120, False), (768, False)] \r\n"
1334
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- "\r\n",
1341
- " | Name | Type | Params\r\n",
1342
- "--------------------------------------\r\n",
1343
- "0 | emb | Embedding | 102 M \r\n",
1344
- "1 | blocks | ModuleList | 654 M \r\n",
1345
- "2 | ln_out | LayerNorm | 4.1 K \r\n",
1346
- "3 | head | Linear | 102 M \r\n",
1347
- "--------------------------------------\r\n",
1348
- "860 M Trainable params\r\n",
1349
- "0 Non-trainable params\r\n",
1350
- "860 M Total params\r\n",
1351
- "3,442.200 Total estimated model params size (MB)\r\n"
1352
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- "Epoch 0: 0%| | 60/54401 [01:22<20:44:35, 1.37s/it, v_num=j6ei, train/loss=9.6\r",
1915
- "Epoch 0: 0%| | 60/54401 [01:22<20:44:35, 1.37s/it, v_num=j6ei, train/loss=9.5"
1916
- ]
1917
- },
1918
- {
1919
- "name": "stdout",
1920
- "output_type": "stream",
1921
- "text": [
1922
- "\r",
1923
- "Epoch 0: 0%| | 61/54401 [01:23<20:42:18, 1.37s/it, v_num=j6ei, train/loss=9.5\r",
1924
- "Epoch 0: 0%| | 61/54401 [01:23<20:42:19, 1.37s/it, v_num=j6ei, train/loss=9.3"
1925
- ]
1926
- },
1927
- {
1928
- "name": "stdout",
1929
- "output_type": "stream",
1930
- "text": [
1931
- "\r",
1932
- "Epoch 0: 0%| | 62/54401 [01:24<20:40:02, 1.37s/it, v_num=j6ei, train/loss=9.3\r",
1933
- "Epoch 0: 0%| | 62/54401 [01:24<20:40:03, 1.37s/it, v_num=j6ei, train/loss=9.6"
1934
- ]
1935
- },
1936
- {
1937
- "name": "stdout",
1938
- "output_type": "stream",
1939
- "text": [
1940
- "\r",
1941
- "Epoch 0: 0%| | 63/54401 [01:26<20:37:53, 1.37s/it, v_num=j6ei, train/loss=9.6\r",
1942
- "Epoch 0: 0%| | 63/54401 [01:26<20:37:54, 1.37s/it, v_num=j6ei, train/loss=9.4"
1943
- ]
1944
- },
1945
- {
1946
- "name": "stdout",
1947
- "output_type": "stream",
1948
- "text": [
1949
- "Traceback (most recent call last):\r\n",
1950
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/lightning_trainer.py\", line 278, in <module>\r\n",
1951
- " cli_main()\r\n",
1952
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/lightning_trainer.py\", line 253, in cli_main\r\n",
1953
- " LightningCLI(\r\n",
1954
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/cli.py\", line 353, in __init__\r\n",
1955
- " self._run_subcommand(self.subcommand)\r\n",
1956
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/cli.py\", line 642, in _run_subcommand\r\n",
1957
- " fn(**fn_kwargs)\r\n",
1958
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 529, in fit\r\n",
1959
- " call._call_and_handle_interrupt(\r\n",
1960
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/call.py\", line 41, in _call_and_handle_interrupt\r\n",
1961
- " return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)\r\n",
1962
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/strategies/launchers/subprocess_script.py\", line 91, in launch\r\n",
1963
- " return function(*args, **kwargs)\r\n",
1964
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 568, in _fit_impl\r\n",
1965
- " self._run(model, ckpt_path=ckpt_path)\r\n",
1966
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 973, in _run\r\n",
1967
- " results = self._run_stage()\r\n",
1968
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 1016, in _run_stage\r\n",
1969
- " self.fit_loop.run()\r\n",
1970
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/loops/fit_loop.py\", line 201, in run\r\n",
1971
- " self.advance()\r\n",
1972
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/loops/fit_loop.py\", line 354, in advance\r\n",
1973
- " self.epoch_loop.run(self._data_fetcher)\r\n",
1974
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/loops/training_epoch_loop.py\", line 133, in run\r\n",
1975
- " self.advance(data_fetcher)\r\n",
1976
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/loops/training_epoch_loop.py\", line 218, in advance\r\n",
1977
- " batch_output = self.automatic_optimization.run(trainer.optimizers[0], kwargs)\r\n",
1978
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/loops/optimization/automatic.py\", line 185, in run\r\n",
1979
- " self._optimizer_step(kwargs.get(\"batch_idx\", 0), closure)\r\n",
1980
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/loops/optimization/automatic.py\", line 260, in _optimizer_step\r\n",
1981
- " call._call_lightning_module_hook(\r\n",
1982
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/call.py\", line 144, in _call_lightning_module_hook\r\n",
1983
- " output = fn(*args, **kwargs)\r\n",
1984
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/core/module.py\", line 1256, in optimizer_step\r\n",
1985
- " optimizer.step(closure=optimizer_closure)\r\n",
1986
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/core/optimizer.py\", line 155, in step\r\n",
1987
- " step_output = self._strategy.optimizer_step(self._optimizer, closure, **kwargs)\r\n",
1988
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/strategies/ddp.py\", line 256, in optimizer_step\r\n",
1989
- " optimizer_output = super().optimizer_step(optimizer, closure, model, **kwargs)\r\n",
1990
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/strategies/strategy.py\", line 225, in optimizer_step\r\n",
1991
- " return self.precision_plugin.optimizer_step(optimizer, model=model, closure=closure, **kwargs)\r\n",
1992
- " File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/plugins/precision/deepspeed.py\", line 102, in optimizer_step\r\n",
1993
- " return deepspeed_engine.step(**kwargs)\r\n",
1994
- " File \"/usr/local/lib/python3.10/dist-packages/deepspeed/runtime/engine.py\", line 2087, in step\r\n",
1995
- " self._take_model_step(lr_kwargs)\r\n",
1996
- " File \"/usr/local/lib/python3.10/dist-packages/deepspeed/runtime/engine.py\", line 1994, in _take_model_step\r\n",
1997
- " self.optimizer.step()\r\n",
1998
- " File \"/usr/local/lib/python3.10/dist-packages/deepspeed/runtime/zero/stage_1_and_2.py\", line 1715, in step\r\n",
1999
- " int(self.partition_size[i])).to(self.single_partition_of_fp32_groups[i].dtype)\r\n",
2000
- "torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.21 GiB (GPU 0; 22.19 GiB total capacity; 14.81 GiB already allocated; 2.39 GiB free; 18.54 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF\r\n",
2001
- "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish... \u001b[31m(failed 1).\u001b[0m Press Control-C to abort syncing.\r\n"
2002
- ]
2003
- },
2004
- {
2005
- "name": "stdout",
2006
- "output_type": "stream",
2007
- "text": [
2008
- "\u001b[34m\u001b[1mwandb\u001b[0m: - 0.005 MB of 0.005 MB uploaded (0.000 MB deduped)\r"
2009
- ]
2010
- },
2011
- {
2012
- "name": "stdout",
2013
- "output_type": "stream",
2014
- "text": [
2015
- "\u001b[34m\u001b[1mwandb\u001b[0m: \\ 0.005 MB of 0.005 MB uploaded (0.000 MB deduped)\r"
2016
- ]
2017
- },
2018
- {
2019
- "name": "stdout",
2020
- "output_type": "stream",
2021
- "text": [
2022
- "\u001b[34m\u001b[1mwandb\u001b[0m: | 0.005 MB of 0.005 MB uploaded (0.000 MB deduped)\r"
2023
- ]
2024
- },
2025
- {
2026
- "name": "stdout",
2027
- "output_type": "stream",
2028
- "text": [
2029
- "\u001b[34m\u001b[1mwandb\u001b[0m: / 0.005 MB of 0.005 MB uploaded (0.000 MB deduped)\r"
2030
- ]
2031
- },
2032
- {
2033
- "name": "stdout",
2034
- "output_type": "stream",
2035
- "text": [
2036
- "\u001b[34m\u001b[1mwandb\u001b[0m: \r\n",
2037
- "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\r\n",
2038
- "\u001b[34m\u001b[1mwandb\u001b[0m: batchidx ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███\r\n",
2039
- "\u001b[34m\u001b[1mwandb\u001b[0m: global_rank ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁\r\n",
2040
- "\u001b[34m\u001b[1mwandb\u001b[0m: perf/tokens_per_sec.gpu.0 ▁▁▃▃▄▅▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇▇▇███████████████\r\n",
2041
- "\u001b[34m\u001b[1mwandb\u001b[0m: perf/tokens_total.gpu.0 ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███\r\n",
2042
- "\u001b[34m\u001b[1mwandb\u001b[0m: real_ctx_len ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁\r\n",
2043
- "\u001b[34m\u001b[1mwandb\u001b[0m: substep ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███\r\n",
2044
- "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss ████████████████████▂▁▃▂▂▂▃▂▂▂▂▂▃▂▂▂▃▂▃▃\r\n",
2045
- "\u001b[34m\u001b[1mwandb\u001b[0m: trainer/global_step ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████████████████████\r\n",
2046
- "\u001b[34m\u001b[1mwandb\u001b[0m: trainer/learning_rate ████████████████████▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁\r\n",
2047
- "\u001b[34m\u001b[1mwandb\u001b[0m: \r\n",
2048
- "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\r\n",
2049
- "\u001b[34m\u001b[1mwandb\u001b[0m: batchidx 63\r\n",
2050
- "\u001b[34m\u001b[1mwandb\u001b[0m: global_rank 0\r\n",
2051
- "\u001b[34m\u001b[1mwandb\u001b[0m: perf/tokens_per_sec.gpu.0 3052.94065\r\n",
2052
- "\u001b[34m\u001b[1mwandb\u001b[0m: perf/tokens_total.gpu.0 262080\r\n",
2053
- "\u001b[34m\u001b[1mwandb\u001b[0m: real_ctx_len 4095\r\n",
2054
- "\u001b[34m\u001b[1mwandb\u001b[0m: substep 63\r\n",
2055
- "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 9.625\r\n",
2056
- "\u001b[34m\u001b[1mwandb\u001b[0m: trainer/global_step 1\r\n",
2057
- "\u001b[34m\u001b[1mwandb\u001b[0m: trainer/learning_rate 0.0006\r\n",
2058
- "\u001b[34m\u001b[1mwandb\u001b[0m: \r\n",
2059
- "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run \u001b[33m[Multi-size] v5-L12-D2048-E0.01 - Enwiki-4k Part 1 (train-ctx=4k, deepspeed_stage_1)\u001b[0m at: \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-5X-Experiments/runs/3rwyj6ei\u001b[0m\r\n",
2060
- "\u001b[34m\u001b[1mwandb\u001b[0m: ️⚡ View job at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-5X-Experiments/jobs/QXJ0aWZhY3RDb2xsZWN0aW9uOjk0OTk4MDcy/version_details/v4\u001b[0m\r\n",
2061
- "\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",
2062
- "\u001b[34m\u001b[1mwandb\u001b[0m: Find logs at: \u001b[35m\u001b[1m./wandb/run-20230929_095815-3rwyj6ei/logs\u001b[0m\r\n"
2063
- ]
2064
- }
2065
- ],
2066
- "source": [
2067
- "# Start the foundation model training\n",
2068
- "!cd \"{TRAINER_DIR}\" && \\\n",
2069
- " export WANDB_MODE=\"{WANDB_MODE}\" && \\\n",
2070
- " python3 lightning_trainer.py fit \\\n",
2071
- " -c \"{NOTEBOOK_DIR}/enwiki-4k-part1.yaml\" \\\n",
2072
- " --trainer.logger.init_args.name=\"{WANDB_PREFIX} - Enwiki-4k Part 1 (train-ctx=4k, {DEEPSPEED_STRAT})\" \\\n",
2073
- " --trainer.strategy=\"{DEEPSPEED_STRAT}\" \\\n",
2074
- " --trainer.devices=\"{GPU_DEVICES}\" \\\n",
2075
- " --trainer.callbacks.init_args.dirpath=\"../checkpoint/{FILENAME_PREFIX}-enwiki-4k-p1/\" \\\n",
2076
- " --model.load_model=\"../model/{FILENAME_PREFIX}-neox-v5base-init.pth\" \\\n",
2077
- " --model.ctx_len=4096 \\\n",
2078
- " --model.bptt_learning_range=1"
2079
- ]
2080
- },
2081
- {
2082
- "cell_type": "code",
2083
- "execution_count": 6,
2084
- "id": "73f2dbdc",
2085
- "metadata": {
2086
- "execution": {
2087
- "iopub.execute_input": "2023-09-29T10:00:21.556396Z",
2088
- "iopub.status.busy": "2023-09-29T10:00:21.555187Z",
2089
- "iopub.status.idle": "2023-09-29T10:00:25.260439Z",
2090
- "shell.execute_reply": "2023-09-29T10:00:25.259001Z"
2091
- },
2092
- "papermill": {
2093
- "duration": 3.72759,
2094
- "end_time": "2023-09-29T10:00:25.263203",
2095
- "exception": false,
2096
- "start_time": "2023-09-29T10:00:21.535613",
2097
- "status": "completed"
2098
- },
2099
- "tags": []
2100
- },
2101
- "outputs": [
2102
- {
2103
- "name": "stdout",
2104
- "output_type": "stream",
2105
- "text": [
2106
- "[2023-09-29 10:00:23,854] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
2107
- ]
2108
- },
2109
- {
2110
- "name": "stdout",
2111
- "output_type": "stream",
2112
- "text": [
2113
- "Traceback (most recent call last):\r\n",
2114
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/export_checkpoint.py\", line 651, in <module>\r\n",
2115
- " convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, output_file, save_dtype=args.dtype)\r\n",
2116
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/export_checkpoint.py\", line 542, in convert_zero_checkpoint_to_fp32_state_dict\r\n",
2117
- " state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)\r\n",
2118
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/export_checkpoint.py\", line 516, in get_fp32_state_dict_from_zero_checkpoint\r\n",
2119
- " raise ValueError(f\"Unable to find 'latest' file at {latest_path}\")\r\n",
2120
- "ValueError: Unable to find 'latest' file at ../checkpoint/v5-L12-D2048-E0_01-enwiki-4k-p1/last.ckpt/latest\r\n"
2121
- ]
2122
- },
2123
- {
2124
- "name": "stdout",
2125
- "output_type": "stream",
2126
- "text": [
2127
- "ls: cannot access '../model/v5-L12-D2048-E0_01-enwiki-4k-p1.pth': No such file or directory\r\n"
2128
- ]
2129
- }
2130
- ],
2131
- "source": [
2132
- "# Lets export the model from the checkpoint\n",
2133
- "!cd \"{TRAINER_DIR}\" && \\\n",
2134
- " python3 export_checkpoint.py \"../checkpoint/{FILENAME_PREFIX}-enwiki-4k-p1/last.ckpt\" \"../model/{FILENAME_PREFIX}-enwiki-4k-p1.pth\" \"bf16\"\n",
2135
- "!cd \"{TRAINER_DIR}\" && ls -alh \"../model/{FILENAME_PREFIX}-enwiki-4k-p1.pth\""
2136
- ]
2137
- },
2138
- {
2139
- "cell_type": "code",
2140
- "execution_count": 7,
2141
- "id": "9b1932b1",
2142
- "metadata": {
2143
- "execution": {
2144
- "iopub.execute_input": "2023-09-29T10:00:25.302083Z",
2145
- "iopub.status.busy": "2023-09-29T10:00:25.300897Z",
2146
- "iopub.status.idle": "2023-09-29T10:00:31.273775Z",
2147
- "shell.execute_reply": "2023-09-29T10:00:31.272586Z"
2148
- },
2149
- "papermill": {
2150
- "duration": 5.996558,
2151
- "end_time": "2023-09-29T10:00:31.277049",
2152
- "exception": false,
2153
- "start_time": "2023-09-29T10:00:25.280491",
2154
- "status": "completed"
2155
- },
2156
- "tags": []
2157
- },
2158
- "outputs": [
2159
- {
2160
- "name": "stdout",
2161
- "output_type": "stream",
2162
- "text": [
2163
- "[2023-09-29 10:00:29,417] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
2164
- ]
2165
- },
2166
- {
2167
- "name": "stdout",
2168
- "output_type": "stream",
2169
- "text": [
2170
- "[RWKV.model] Running RWKV model using 'torch-jit' with torch '2.0.1+cu118'\r\n",
2171
- "Traceback (most recent call last):\r\n",
2172
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/dragon_test.py\", line 52, in <module>\r\n",
2173
- " model = SimpleRWKV(MODEL_PATH, device=DEVICE)\r\n",
2174
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/src/model.py\", line 1420, in __init__\r\n",
2175
- " self.model = RWKV(**model_config)\r\n",
2176
- " File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/src/model.py\", line 566, in __init__\r\n",
2177
- " raise ValueError(f\"load_model file '{load_model}' does not exist\")\r\n",
2178
- "ValueError: load_model file '../model/v5-L12-D2048-E0_01-enwiki-4k-p1.pth' does not exist\r\n"
2179
- ]
2180
- }
2181
- ],
2182
- "source": [
2183
- "# # Lets do a quick dragon prompt validation\n",
2184
- "!cd \"{INFERENCE_DIR}\" && \\\n",
2185
- " python3 dragon_test.py \"../model/{FILENAME_PREFIX}-enwiki-4k-p1.pth\" \"cuda fp32\""
2186
- ]
2187
- }
2188
- ],
2189
- "metadata": {
2190
- "kernelspec": {
2191
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2192
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