{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "215f6d68",
   "metadata": {
    "papermill": {
     "duration": 0.00298,
     "end_time": "2023-09-29T06:34:37.429814",
     "exception": false,
     "start_time": "2023-09-29T06:34:37.426834",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# RWKV v5 multi-size training experiment\n",
    "\n",
    "**Note:** This project assumes you have the rwkv-infctx conda env setup"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "bf0cf97c",
   "metadata": {
    "papermill": {
     "duration": 0.002312,
     "end_time": "2023-09-29T06:34:37.435725",
     "exception": false,
     "start_time": "2023-09-29T06:34:37.433413",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Basic Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "98d95606",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:34:37.440037Z",
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     "shell.execute_reply": "2023-09-29T06:34:38.106666Z"
    },
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     "duration": 0.672001,
     "end_time": "2023-09-29T06:34:38.109558",
     "exception": false,
     "start_time": "2023-09-29T06:34:37.437557",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# First lets setup the various directories, and init the model\n",
    "!mkdir -p ../../../../model/\n",
    "!mkdir -p ../../../../datapath/\n",
    "!mkdir -p ../../../../checkpoint/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d799a503",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:34:38.116182Z",
     "iopub.status.busy": "2023-09-29T06:34:38.115939Z",
     "iopub.status.idle": "2023-09-29T06:34:38.124075Z",
     "shell.execute_reply": "2023-09-29T06:34:38.123428Z"
    },
    "papermill": {
     "duration": 0.012774,
     "end_time": "2023-09-29T06:34:38.125078",
     "exception": false,
     "start_time": "2023-09-29T06:34:38.112304",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEEPSPEED_STRAT: deepspeed_stage_1\n",
      "ENABLE_WANDB: True\n",
      "GPU_DEVICES: auto\n",
      "NOTEBOOK_DIR: /actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/notebook/experiment/rwkv-x-exp/multi-size-train\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",
    "EMBED_SCALE=0.01\n",
    "EMBED_SCALE_LABEL=str(EMBED_SCALE).replace(\".\", \"_\")\n",
    "\n",
    "LAYER_COUNT=6\n",
    "EMBED_SIZE=2048\n",
    "\n",
    "WANDB_PREFIX=f\"[Multi-size] v5-L{LAYER_COUNT}-D{EMBED_SIZE}-E{EMBED_SCALE}\"\n",
    "FILENAME_PREFIX=f\"v5-L{LAYER_COUNT}-D{EMBED_SIZE}-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",
    "PROJECT_DIR=os.path.abspath(os.path.join(NOTEBOOK_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",
    "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": 3,
   "id": "e4204bbd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:34:38.128341Z",
     "iopub.status.busy": "2023-09-29T06:34:38.128199Z",
     "iopub.status.idle": "2023-09-29T06:34:57.534218Z",
     "shell.execute_reply": "2023-09-29T06:34:57.533501Z"
    },
    "papermill": {
     "duration": 19.409767,
     "end_time": "2023-09-29T06:34:57.536209",
     "exception": false,
     "start_time": "2023-09-29T06:34:38.126442",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:34:40,927] [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",
      "---- Initializing model ----\r\n",
      "No of layers: 6\r\n",
      "Embedding size: 2048\r\n",
      "Output model path: ../model/v5-L6-D2048-E0_01-neox-v5base-init.pth\r\n",
      "Vocab size: 50277\r\n",
      "Emb scale: 0.01\r\n",
      "Note: this process takes a significant time (and ram) for large models\r\n",
      "---- ----- ----\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50277 2048  -0.01 emb.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048  2048  1.0  blocks.0.att.gate.weight\r\n"
     ]
    },
    {
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     "text": [
      "2048  2048  1.0  blocks.0.att.receptance.weight\r\n"
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      "2048  2048  1.0  blocks.0.att.key.weight\r\n"
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      "2048  2048  1.0  blocks.0.att.value.weight\r\n"
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      "2048  2048  0    blocks.0.att.output.weight\r\n",
      "7168  2048  1.0  blocks.0.ffn.key.weight\r\n"
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      "2048  2048  0    blocks.0.ffn.receptance.weight\r\n",
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      "2048  2048  1.0  blocks.1.att.gate.weight\r\n"
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      "2048  2048  1.0  blocks.1.att.receptance.weight\r\n"
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      "2048  2048  1.0  blocks.1.att.key.weight\r\n"
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      "2048  2048  1.0  blocks.1.att.value.weight\r\n"
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      "2048  2048  0    blocks.1.att.output.weight\r\n",
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      "2048  2048  1.0  blocks.4.att.key.weight\r\n"
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      "2048  2048  1.0  blocks.4.att.value.weight\r\n"
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      "2048  2048  0    blocks.4.att.output.weight\r\n",
      "7168  2048  1.0  blocks.4.ffn.key.weight\r\n"
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     "text": [
      "2048  2048  0    blocks.4.ffn.receptance.weight\r\n",
      "2048  7168  0    blocks.4.ffn.value.weight\r\n",
      "2048  2048  1.0  blocks.5.att.gate.weight\r\n"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048  2048  1.0  blocks.5.att.receptance.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048  2048  1.0  blocks.5.att.key.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048  2048  1.0  blocks.5.att.value.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048  2048  0    blocks.5.att.output.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7168  2048  1.0  blocks.5.ffn.key.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048  2048  0    blocks.5.ffn.receptance.weight\r\n",
      "2048  7168  0    blocks.5.ffn.value.weight\r\n",
      "50277 2048  0.5  head.weight\r\n"
     ]
    }
   ],
   "source": [
    "# Init the model\n",
    "!cd \"{TRAINER_DIR}\" && \\\n",
    "    python3 ./init_model.py \\\n",
    "        --n_layer {LAYER_COUNT} --n_embd {EMBED_SIZE} \\\n",
    "        --emb-scale \"{EMBED_SCALE}\" \\\n",
    "        --vocab_size neox --skip-if-exists \\\n",
    "        \"../model/{FILENAME_PREFIX}-neox-v5base-init.pth\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25aa156c",
   "metadata": {
    "papermill": {
     "duration": 0.004287,
     "end_time": "2023-09-29T06:34:57.545982",
     "exception": false,
     "start_time": "2023-09-29T06:34:57.541695",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Enwiki Stage 1 : Foundation 4k model training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dfb884c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:34:57.552286Z",
     "iopub.status.busy": "2023-09-29T06:34:57.552023Z",
     "iopub.status.idle": "2023-09-29T06:35:06.302944Z",
     "shell.execute_reply": "2023-09-29T06:35:06.302095Z"
    },
    "papermill": {
     "duration": 8.756445,
     "end_time": "2023-09-29T06:35:06.305010",
     "exception": false,
     "start_time": "2023-09-29T06:34:57.548565",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):   0%|         | 0/54405 [00:00<?, ? examples/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):   7%| | 4000/54405 [00:00<00:01, 37249.67 examp"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):  15%|▏| 8000/54405 [00:00<00:01, 38219.54 examp"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):  26%|▎| 14000/54405 [00:00<00:01, 39689.52 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):  33%|▎| 18135/54405 [00:00<00:00, 40242.23 exam\r",
      "Saving the dataset (1/3 shards):  33%|▎| 18135/54405 [00:00<00:00, 40242.23 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (1/3 shards):  44%|▍| 24135/54405 [00:00<00:00, 41554.48 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (1/3 shards):  55%|▌| 30135/54405 [00:00<00:00, 42818.03 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (1/3 shards):  66%|▋| 36135/54405 [00:00<00:00, 41776.96 exam\r",
      "Saving the dataset (2/3 shards):  67%|▋| 36270/54405 [00:00<00:00, 41776.96 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (2/3 shards):  80%|▊| 43270/54405 [00:01<00:00, 39166.69 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (2/3 shards):  91%|▉| 49270/54405 [00:01<00:00, 42149.53 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (3/3 shards): 100%|█| 54405/54405 [00:01<00:00, 42149.53 exam\r",
      "Saving the dataset (3/3 shards): 100%|█| 54405/54405 [00:01<00:00, 41937.72 exam\r\n",
      "\r",
      "Saving the dataset (0/1 shards):   0%|           | 0/109 [00:00<?, ? examples/s]\r",
      "Saving the dataset (1/1 shards): 100%|█| 109/109 [00:00<00:00, 22056.11 examples\r",
      "Saving the dataset (1/1 shards): 100%|█| 109/109 [00:00<00:00, 21440.66 examples\r\n"
     ]
    }
   ],
   "source": [
    "# Lets preload the requried dataset \n",
    "!cd \"{TRAINER_DIR}\" && \\\n",
    "    python3 preload_datapath.py \"{NOTEBOOK_DIR}/enwiki-4k-part1.yaml\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4e9efefc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:35:06.316650Z",
     "iopub.status.busy": "2023-09-29T06:35:06.316380Z",
     "iopub.status.idle": "2023-09-29T06:40:32.568932Z",
     "shell.execute_reply": "2023-09-29T06:40:32.568052Z"
    },
    "papermill": {
     "duration": 326.259608,
     "end_time": "2023-09-29T06:40:32.570962",
     "exception": false,
     "start_time": "2023-09-29T06:35:06.311354",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:35:09,045] [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/multi-size-train/enwiki-4k-part1.yaml', '--trainer.logger.init_args.name=[Multi-size] v5-L6-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-L6-D2048-E0_01-enwiki-4k-p1/', '--model.load_model=../model/v5-L6-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-L6-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-L6-D2048-E0_01-enwiki-4k-p1/', '--model.load_model=../model/v5-L6-D2048-E0_01-neox-v5base-init.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 1303123097\r\n",
      "  rank_zero_warn(f\"No seed found, seed set to {seed}\")\r\n",
      "Global seed set to 1303123097\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 0.15.11\r\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in \u001b[35m\u001b[1m./wandb/run-20230929_063511-nua9z0t5\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[33m[Multi-size] v5-L6-D2048-E0.01 - Enwiki-4k Part 1 (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-5X-Experiments\u001b[0m\r\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/rwkv-x-dev/RWKV-5X-Experiments/runs/nua9z0t5\u001b[0m\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"
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      "Traceback (most recent call last):\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/lightning_trainer.py\", line 278, in <module>\r\n",
      "    cli_main()\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/lightning_trainer.py\", line 253, in cli_main\r\n",
      "    LightningCLI(\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/cli.py\", line 353, in __init__\r\n",
      "    self._run_subcommand(self.subcommand)\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/cli.py\", line 642, in _run_subcommand\r\n",
      "    fn(**fn_kwargs)\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 529, in fit\r\n",
      "    call._call_and_handle_interrupt(\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/call.py\", line 41, in _call_and_handle_interrupt\r\n",
      "    return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/strategies/launchers/subprocess_script.py\", line 91, in launch\r\n",
      "    return function(*args, **kwargs)\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 568, in _fit_impl\r\n",
      "    self._run(model, ckpt_path=ckpt_path)\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/trainer.py\", line 925, in _run\r\n",
      "    self._data_connector.prepare_data()\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/connectors/data_connector.py\", line 94, in prepare_data\r\n",
      "    call._call_lightning_datamodule_hook(trainer, \"prepare_data\")\r\n",
      "  File \"/usr/local/lib/python3.10/dist-packages/lightning/pytorch/trainer/call.py\", line 164, in _call_lightning_datamodule_hook\r\n",
      "    return fn(*args, **kwargs)\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/src/data.py\", line 549, in prepare_data\r\n",
      "    prepare_data_static(**self._init_locals)\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/src/data.py\", line 464, in prepare_data_static\r\n",
      "    src_dataset[\"train\"] = src_dataset[\"train\"].select(range(offset_val, offset_val + length_val))\r\n",
      "TypeError: 'float' object cannot be interpreted as an integer\r\n",
      "\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run \u001b[33m[Multi-size] v5-L6-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/nua9z0t5\u001b[0m\r\n",
      "\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/v2\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-20230929_063511-nua9z0t5/logs\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "# Start the foundation model training\n",
    "!cd \"{TRAINER_DIR}\" && \\\n",
    "    export WANDB_MODE=\"{WANDB_MODE}\" && \\\n",
    "    python3 lightning_trainer.py fit \\\n",
    "        -c \"{NOTEBOOK_DIR}/enwiki-4k-part1.yaml\" \\\n",
    "        --trainer.logger.init_args.name=\"{WANDB_PREFIX} - Enwiki-4k Part 1 (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-4k-p1/\" \\\n",
    "        --model.load_model=\"../model/{FILENAME_PREFIX}-neox-v5base-init.pth\" \\\n",
    "        --model.ctx_len=4096 \\\n",
    "        --model.bptt_learning_range=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e03ffed6",
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     "iopub.execute_input": "2023-09-29T06:40:32.715392Z",
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     "iopub.status.idle": "2023-09-29T06:40:35.440958Z",
     "shell.execute_reply": "2023-09-29T06:40:35.440200Z"
    },
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     "duration": 2.797683,
     "end_time": "2023-09-29T06:40:35.442702",
     "exception": false,
     "start_time": "2023-09-29T06:40:32.645019",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:40:34,511] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect)\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/export_checkpoint.py\", line 651, in <module>\r\n",
      "    convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, output_file, save_dtype=args.dtype)\r\n",
      "  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",
      "    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)\r\n",
      "  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",
      "    raise ValueError(f\"Unable to find 'latest' file at {latest_path}\")\r\n",
      "ValueError: Unable to find 'latest' file at ../checkpoint/v5-L6-D2048-E0_01-enwiki-4k-p1/last.ckpt/latest\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ls: cannot access '../model/v5-L6-D2048-E0_01-enwiki-4k-p1.pth': No such file or directory\r\n"
     ]
    }
   ],
   "source": [
    "# Lets export the model from the checkpoint\n",
    "!cd \"{TRAINER_DIR}\" && \\\n",
    "    python3 export_checkpoint.py \"../checkpoint/{FILENAME_PREFIX}-enwiki-4k-p1/last.ckpt\" \"../model/{FILENAME_PREFIX}-enwiki-4k-p1.pth\" \"bf16\"\n",
    "!cd \"{TRAINER_DIR}\" && ls -alh \"../model/{FILENAME_PREFIX}-enwiki-4k-p1.pth\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b2d5fe57",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:40:35.588027Z",
     "iopub.status.busy": "2023-09-29T06:40:35.587772Z",
     "iopub.status.idle": "2023-09-29T06:40:39.405717Z",
     "shell.execute_reply": "2023-09-29T06:40:39.404915Z"
    },
    "papermill": {
     "duration": 3.890278,
     "end_time": "2023-09-29T06:40:39.407623",
     "exception": false,
     "start_time": "2023-09-29T06:40:35.517345",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:40:38,394] [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",
      "Traceback (most recent call last):\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/dragon_test.py\", line 52, in <module>\r\n",
      "    model = SimpleRWKV(MODEL_PATH, device=DEVICE)\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/src/model.py\", line 1420, in __init__\r\n",
      "    self.model = RWKV(**model_config)\r\n",
      "  File \"/actions-runner/_work/RWKV-infctx-trainer/RWKV-infctx-trainer/RWKV-v5/src/model.py\", line 566, in __init__\r\n",
      "    raise ValueError(f\"load_model file '{load_model}' does not exist\")\r\n",
      "ValueError: load_model file '../model/v5-L6-D2048-E0_01-enwiki-4k-p1.pth' does not exist\r\n"
     ]
    }
   ],
   "source": [
    "# # Lets do a quick dragon prompt validation\n",
    "!cd \"{INFERENCE_DIR}\" && \\\n",
    "    python3 dragon_test.py \"../model/{FILENAME_PREFIX}-enwiki-4k-p1.pth\" \"cuda fp32\""
   ]
  }
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