{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "b33301f1",
   "metadata": {
    "papermill": {
     "duration": 0.002639,
     "end_time": "2023-09-29T06:40:35.355878",
     "exception": false,
     "start_time": "2023-09-29T06:40:35.353239",
     "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": "7f0c7442",
   "metadata": {
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     "end_time": "2023-09-29T06:40:35.361675",
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     "start_time": "2023-09-29T06:40:35.359778",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Basic Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5697b559",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:40:35.367571Z",
     "iopub.status.busy": "2023-09-29T06:40:35.367056Z",
     "iopub.status.idle": "2023-09-29T06:40:36.120936Z",
     "shell.execute_reply": "2023-09-29T06:40:36.120020Z"
    },
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     "exception": false,
     "start_time": "2023-09-29T06:40:35.363831",
     "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": "a6de4e7e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:40:36.129456Z",
     "iopub.status.busy": "2023-09-29T06:40:36.128952Z",
     "iopub.status.idle": "2023-09-29T06:40:36.137224Z",
     "shell.execute_reply": "2023-09-29T06:40:36.136398Z"
    },
    "papermill": {
     "duration": 0.013484,
     "end_time": "2023-09-29T06:40:36.138880",
     "exception": false,
     "start_time": "2023-09-29T06:40:36.125396",
     "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=12\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": "22f457d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:40:36.145747Z",
     "iopub.status.busy": "2023-09-29T06:40:36.145217Z",
     "iopub.status.idle": "2023-09-29T06:41:21.917242Z",
     "shell.execute_reply": "2023-09-29T06:41:21.916099Z"
    },
    "papermill": {
     "duration": 45.777858,
     "end_time": "2023-09-29T06:41:21.919315",
     "exception": false,
     "start_time": "2023-09-29T06:40:36.141457",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:40:40,584] [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: 12\r\n",
      "Embedding size: 2048\r\n",
      "Output model path: ../model/v5-L12-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"
     ]
    },
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      "2048  2048  0    blocks.11.ffn.receptance.weight\r\n",
      "2048  7168  0    blocks.11.ffn.value.weight\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "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": "fde86502",
   "metadata": {
    "papermill": {
     "duration": 0.006163,
     "end_time": "2023-09-29T06:41:21.931885",
     "exception": false,
     "start_time": "2023-09-29T06:41:21.925722",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Enwiki Stage 1 : Foundation 4k model training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a862f05f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:41:21.946957Z",
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     "shell.execute_reply": "2023-09-29T06:41:33.125478Z"
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     "duration": 11.190379,
     "end_time": "2023-09-29T06:41:33.128643",
     "exception": false,
     "start_time": "2023-09-29T06:41:21.938264",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):   0%|         | 0/54401 [00:00<?, ? examples/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):   4%| | 2000/54401 [00:00<00:03, 15028.12 examp"
     ]
    },
    {
     "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",
      "Saving the dataset (0/3 shards):  15%|▏| 8000/54401 [00:00<00:02, 16391.73 examp"
     ]
    },
    {
     "name": "stdout",
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      "\r",
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     ]
    },
    {
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     "text": [
      "\r",
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     ]
    },
    {
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     "text": [
      "\r",
      "Saving the dataset (0/3 shards):  29%|▎| 16000/54401 [00:00<00:02, 17630.70 exam"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (0/3 shards):  33%|▎| 18000/54401 [00:01<00:02, 17967.86 exam\r",
      "Saving the dataset (1/3 shards):  33%|▎| 18134/54401 [00:01<00:02, 17967.86 exam"
     ]
    },
    {
     "name": "stdout",
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      "\r",
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     ]
    },
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     ]
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      "\r",
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     ]
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     ]
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     ]
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     "text": [
      "\r",
      "Saving the dataset (1/3 shards):  67%|▋| 36268/54401 [00:02<00:00, 19448.25 exam\r",
      "Saving the dataset (2/3 shards):  67%|▋| 36268/54401 [00:02<00:00, 19448.25 exam"
     ]
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     ]
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      "\r",
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     ]
    },
    {
     "name": "stdout",
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      "\r",
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     ]
    },
    {
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      "\r",
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     ]
    },
    {
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     ]
    },
    {
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      "\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Saving the dataset (2/3 shards): 100%|█| 54401/54401 [00:02<00:00, 19987.22 exam\r",
      "Saving the dataset (3/3 shards): 100%|█| 54401/54401 [00:02<00:00, 19987.22 exam\r",
      "Saving the dataset (3/3 shards): 100%|█| 54401/54401 [00:02<00:00, 18650.55 exam\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\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, 7363.05 examples/\r",
      "Saving the dataset (1/1 shards): 100%|█| 109/109 [00:00<00:00, 7061.55 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": "4f60e7a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:41:33.164559Z",
     "iopub.status.busy": "2023-09-29T06:41:33.164036Z",
     "iopub.status.idle": "2023-09-29T06:46:52.824523Z",
     "shell.execute_reply": "2023-09-29T06:46:52.823454Z"
    },
    "papermill": {
     "duration": 319.688845,
     "end_time": "2023-09-29T06:46:52.826835",
     "exception": false,
     "start_time": "2023-09-29T06:41:33.137990",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:41:37,618] [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-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",
      "  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 794168672\r\n",
      "  rank_zero_warn(f\"No seed found, seed set to {seed}\")\r\n",
      "Global seed set to 794168672\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_064140-udijamu6\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-L12-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/udijamu6\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
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     ]
    },
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     "text": [
      "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-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/udijamu6\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/v3\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_064140-udijamu6/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": "9dcc8aa0",
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     "iopub.execute_input": "2023-09-29T06:46:53.049378Z",
     "iopub.status.busy": "2023-09-29T06:46:53.048820Z",
     "iopub.status.idle": "2023-09-29T06:46:56.789000Z",
     "shell.execute_reply": "2023-09-29T06:46:56.787968Z"
    },
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     "duration": 3.854596,
     "end_time": "2023-09-29T06:46:56.791829",
     "exception": false,
     "start_time": "2023-09-29T06:46:52.937233",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:46:55,390] [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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    raise ValueError(f\"Unable to find 'latest' file at {latest_path}\")\r\n",
      "ValueError: Unable to find 'latest' file at ../checkpoint/v5-L12-D2048-E0_01-enwiki-4k-p1/last.ckpt/latest\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ls: cannot access '../model/v5-L12-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": "fbac8551",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-29T06:46:57.029599Z",
     "iopub.status.busy": "2023-09-29T06:46:57.029240Z",
     "iopub.status.idle": "2023-09-29T06:47:03.411064Z",
     "shell.execute_reply": "2023-09-29T06:47:03.409916Z"
    },
    "papermill": {
     "duration": 6.495854,
     "end_time": "2023-09-29T06:47:03.413417",
     "exception": false,
     "start_time": "2023-09-29T06:46:56.917563",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2023-09-29 06:47:01,373] [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": [
      "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-L12-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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