llama2-7b_LISA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bb50eb7a-ecd1-4c86-acb4-1c789fac2be8",
   "metadata": {},
   "source": [
    "<span style=\"color:red\"> *Contrary to expectation, this does not work (yet)*</span>\n",
    "\n",
    "see https://github.com/OptimalScale/LMFlow/issues/726"
   ]
  },
  {
   "attachments": {
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    }
   },
   "cell_type": "markdown",
   "id": "b9074050-003a-4047-b91a-1c75e6ef9c68",
   "metadata": {},
   "source": [
    "# LISA\n",
    "\n",
    "yet another PEFT\n",
    "\n",
    "**Paper**: \n",
    "* LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning\n",
    "* https://arxiv.org/abs/2403.17919\n",
    "\n",
    "**Code**: https://github.com/OptimalScale/LMFlow\n",
    "\n",
    "**LISA Approach**:\n",
    "* Load all parameters, train a subset only, freeze the rest\n",
    "* randomly select `lisa_activated_layers` number of layers and set `requires_grad=True`\n",
    "* switch layers every `lisa_interval_steps` steps\n",
    "\n",
    "**Integration with HF Trainer**:\n",
    "* via Trainer Callback `DynamicLayerActivationCallback`\n",
    "* init with params `lisa_activated_layers` and `lisa_interval_steps`\n",
    "* `on_step_begin`: check current `step` vs `lisa_interval_steps`, call `switch_active_layers`\n",
    "\n",
    "**Code below**:\n",
    "* Load llama2-7b and prepare for ChatML\n",
    "* Load Open Assistant data(sub)set, 4k examples\n",
    "* `SFTTrainer` with constant LR of `2e-5` (`paged_adamw_8bit`), batch size 16, max seq. length 512. eval and save after each epoch\n",
    "* Setup Trainer Callback with `lisa_activated_layers = 1` and `lisa_interval_steps = 20`\n",
    "* Log with wandb\n",
    "* 3 epochs in ~1.5hrs on a 3090 (VRAM usage ~21GB)\n",
    "\n",
    "**Note**: seems to work, not thoroughly tested though\n",
    "\n",
    "![W&B Chart 30_03_2024, 13_09_00.jpg](attachment:aa74ec42-65d9-46a2-bcc1-47000360847f.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e255e301-683e-4e6b-87d9-9ec77e8c6139",
   "metadata": {},
   "source": [
    "## Prerequisites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1a18dec1-f6f6-4367-8e19-5ea44678c620",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install -U bitsandbytes wandb flash_attn accelerate datasets trl transformers tokenizers "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9411698-0783-4f15-b1ca-2ca4702661ae",
   "metadata": {},
   "source": [
    "## Load model, tokenizer, dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f0f24b7b-9922-4e58-b6c7-9e07879e3777",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "814f968a9989498fbdc7add4ad0b1dfd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565\n"
     ]
    }
   ],
   "source": [
    "from transformers import AutoTokenizer, AutoModelForCausalLM, TrainingArguments, set_seed, get_constant_schedule\n",
    "from trl import SFTTrainer, setup_chat_format, DataCollatorForCompletionOnlyLM\n",
    "from datasets import load_dataset\n",
    "import torch, uuid, wandb\n",
    "\n",
    "set_seed(42)\n",
    "run_id = f\"LISA-{str(uuid.uuid4())}\"\n",
    "\n",
    "modelpath = \"models/llama2-7b\"\n",
    "\n",
    "model = AutoModelForCausalLM.from_pretrained(\n",
    "    modelpath,    \n",
    "    torch_dtype = torch.bfloat16,\n",
    "    attn_implementation = \"flash_attention_2\",  \n",
    "    device_map = \"auto\",\n",
    "    use_cache = False,\n",
    ")\n",
    "tokenizer = AutoTokenizer.from_pretrained(modelpath, use_fast = False)\n",
    "\n",
    "model, tokenizer = setup_chat_format(model, tokenizer)\n",
    "if tokenizer.pad_token in [None, tokenizer.eos_token]: \n",
    "    tokenizer.pad_token = tokenizer.unk_token\n",
    "\n",
    "dataset = load_dataset(\"g-ronimo/oasst2_top4k_en\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2d7173d-0066-4f5d-805b-9533fbcd878a",
   "metadata": {},
   "source": [
    "## Setup `SFTTrainer`"
   ]
  },
  {
   "attachments": {
    "0ead8ab1-4766-4854-ac9a-044ade40e5a1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "00d6f778-2d36-4e4b-bc07-ddbd00a017c3",
   "metadata": {},
   "source": [
    "![Screenshot 2024-03-30 at 15.40.06.png](attachment:0ead8ab1-4766-4854-ac9a-044ade40e5a1.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9a7a0713-9b99-4d5d-ac9d-73e7f0a3e524",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/g/.local/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead: \n",
      "dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "lr = 5e-5\n",
    "\n",
    "training_arguments = TrainingArguments(\n",
    "    output_dir = f\"out_{run_id}\",\n",
    "    evaluation_strategy = \"steps\",\n",
    "    label_names = [\"labels\"],\n",
    "    per_device_train_batch_size = 16,\n",
    "    save_steps = 250,\n",
    "    eval_steps = 250,\n",
    "    logging_steps = 1, \n",
    "    learning_rate = lr,\n",
    "    num_train_epochs = 3,\n",
    "    lr_scheduler_type = \"constant\",\n",
    "    gradient_checkpointing = True,\n",
    "    group_by_length = False,\n",
    "    optim=\"paged_adamw_8bit\",\n",
    ")\n",
    "\n",
    "trainer = SFTTrainer(\n",
    "    model = model,\n",
    "    tokenizer = tokenizer,\n",
    "    train_dataset = dataset[\"train\"],\n",
    "    eval_dataset = dataset['test'],\n",
    "    data_collator = DataCollatorForCompletionOnlyLM(\n",
    "        instruction_template = \"<|im_start|>user\", \n",
    "        response_template = \"<|im_start|>assistant\", \n",
    "        tokenizer = tokenizer, \n",
    "        mlm = False),\n",
    "    max_seq_length = 512,\n",
    "    dataset_kwargs = dict(add_special_tokens = False),\n",
    "    args = training_arguments,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea6036af-e830-4c70-ae97-a05cf346c581",
   "metadata": {},
   "source": [
    "## Setup LISA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28a73e14-159f-43b8-853a-f228a7ffbd2f",
   "metadata": {},
   "source": [
    "[Authors](https://arxiv.org/pdf/2403.17919.pdf):\n",
    "> Generally, the rule of thumb is: More sampling layers\n",
    "and higher sampling period lead to better performance.\n",
    "\n",
    "32x `LlamaDecoderLayer` in llama2-7b:\n",
    "* `lisa_activated_layers = 8` -> 25% trainable parameters\n",
    "* `lisa_activated_layers = 4` -> 12.5% trainable parameters\n",
    "* `lisa_activated_layers = 2` -> 6.25% trainable parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d9f7b632-4f14-4d32-8b0c-aaebeb55e025",
   "metadata": {},
   "outputs": [],
   "source": [
    "lisa_activated_layers = 8\n",
    "lisa_interval_steps = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "efa3ef4f-7e93-47b2-a681-6fde3a6b90cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import TrainerCallback\n",
    "import numpy as np\n",
    "\n",
    "# source: https://github.com/OptimalScale/LMFlow/blob/main/src/lmflow/pipeline/finetuner.py\n",
    "class DynamicLayerActivationCallback(TrainerCallback):\n",
    "    def __init__(self, n_layers, interval_steps, model):\n",
    "        super().__init__()\n",
    "        self.n_layers = n_layers\n",
    "        self.interval_steps = interval_steps\n",
    "        self.model = model\n",
    "        # Determine the way to access layers based on the model type\n",
    "        if self.model.__class__.__name__ == 'LlamaForCausalLM':\n",
    "            self.layers_attribute = 'model.model.layers'  # Layer access path for LlamaForCausalLM\n",
    "        else:\n",
    "            self.layers_attribute = 'model.transformer.h'  # General access path\n",
    "        self.total_layers = len(eval('self.' + self.layers_attribute))  # Dynamically execute to get the number of layers\n",
    "\n",
    "        # Freeze all layers upon initialization\n",
    "        self.freeze_all_layers()\n",
    "        self.active_layers_indices = []\n",
    "\n",
    "    def freeze_all_layers(self):\n",
    "        layers = eval('self.' + self.layers_attribute)  # Dynamically execute to get layers\n",
    "        for layer in layers:\n",
    "            for param in layer.parameters():\n",
    "                param.requires_grad = False\n",
    "\n",
    "    def on_step_begin(self, args, state, control, **kwargs):\n",
    "        # Check if it's time to switch active layers, including at step 0\n",
    "        if state.global_step % self.interval_steps == 0 or state.global_step == 1:\n",
    "            self.switch_active_layers()\n",
    "\n",
    "    def switch_active_layers(self):\n",
    "        # First, disable gradients for all layers\n",
    "        self.freeze_all_layers()\n",
    "\n",
    "        # Randomly select n_layers to activate\n",
    "        layers = eval('self.' + self.layers_attribute)  # Re-fetch layer references\n",
    "        self.active_layers_indices = np.random.choice(range(self.total_layers), self.n_layers, replace=False)\n",
    "        print(f\"Activating layers at indices: {self.active_layers_indices} for the next steps.\")\n",
    "\n",
    "        # Enable gradients only for the selected layers\n",
    "        for idx in self.active_layers_indices:\n",
    "            for param in layers[idx].parameters():\n",
    "                param.requires_grad = True\n",
    "\n",
    "# Instantiate the callback\n",
    "dynamic_layer_activation_callback = DynamicLayerActivationCallback(\n",
    "    n_layers = lisa_activated_layers,                     # Number of layers to activate\n",
    "    interval_steps = lisa_interval_steps,               # Step interval to update active layers\n",
    "    model = model\n",
    ")\n",
    "\n",
    "trainer.add_callback(dynamic_layer_activation_callback)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3270d0a8-a600-43f4-8c20-dad8445c1aeb",
   "metadata": {},
   "source": [
    "## Train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1b7ac67d-dc30-48a6-a6ca-5e2a96a58993",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:wandb.jupyter:Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mg-ronimo\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.16.5"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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      "text/html": [
       "Run data is saved locally in <code>/home/g/3090_shorts/wandb/run-20240330_152905-wmzggs35</code>"
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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      "text/html": [
       "Syncing run <strong><a href='https://wandb.ai/g-ronimo/LISA-7B/runs/wmzggs35/workspace' target=\"_blank\">LISA-039723d3-f5b4-443d-8d31-6e2acb06d11f</a></strong> to <a href='https://wandb.ai/g-ronimo/LISA-7B' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
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       " View project at <a href='https://wandb.ai/g-ronimo/LISA-7B' target=\"_blank\">https://wandb.ai/g-ronimo/LISA-7B</a>"
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       " View run at <a href='https://wandb.ai/g-ronimo/LISA-7B/runs/wmzggs35/workspace' target=\"_blank\">https://wandb.ai/g-ronimo/LISA-7B/runs/wmzggs35/workspace</a>"
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       "<IPython.core.display.HTML object>"
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     "text": [
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:168: UserWarning: Could not find response key `<|im_start|>assistant` in the following instance: <|im_start|> user\n",
      "Answer as an expert in medical malpractice law in the UK, presenting your arguments to another lawyer. Identify if this constitutes a breach of duty and a settlement value broken down by how the different factors affect the amount. Justify it step by step.\n",
      "Our client’s mother approached our specialist erb’s palsy solicitors after realising that her son, Peter, may be eligible to claim compensation for the injuries he sustained during birth.\n",
      "During her pregnancy with Peter, his mother had attended all of the scans and they showed a baby of normal size. However, during her labour, it became apparent that Peter was quite a big baby and, due to this, they took his mother to theatre to monitor her progress.\n",
      "Peter’s head was delivered first, but due to his size, his shoulders became stuck (shoulder dystocia). Multiple attempts were made to deliver his body, including the use of a ventouse (vacuum cup) and forceps. The McRoberts position (a manoeuvre often used in this situation) was not adopted, nor was an episiotomy.\n",
      "It was unclear from the records how long there was between the delivery of Peter’s head and his body, but the degree of trauma our client suffered to his head and neck was disproportionate to the amount of traction required to deliver a baby, even under these very difficult circumstances.\n",
      "When Peter was born, he was floppy and not breathing on his own, so he needed help from machines. He also had a wound to his head as a result of the attempted delivery.\n",
      "Peter recovered fairly well in NICU and was breathing independently. However, a lump on the side of his neck was noted and, after further investigation, it was found that he had suffered a severe brachial plexus injury that affected the nerves found at C5, C6 and C7. \n",
      "During the first 10 years of his life, our client underwent five separate procedures to try and improve the long-standing impact of his birth injuries, all of which only helped a little. Peter was unable to raise his right arm above shoulder height and had restrictive movement in his right shoulder. He also had significant scarring on his back due to the amount of surgery he required. Peter also suffered significant psychiatric damage This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n",
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:183: UserWarning: Could not find instruction key `<|im_start|>user` in the following instance: <|im_start|> user\n",
      "Answer as an expert in medical malpractice law in the UK, presenting your arguments to another lawyer. Identify if this constitutes a breach of duty and a settlement value broken down by how the different factors affect the amount. Justify it step by step.\n",
      "Our client’s mother approached our specialist erb’s palsy solicitors after realising that her son, Peter, may be eligible to claim compensation for the injuries he sustained during birth.\n",
      "During her pregnancy with Peter, his mother had attended all of the scans and they showed a baby of normal size. However, during her labour, it became apparent that Peter was quite a big baby and, due to this, they took his mother to theatre to monitor her progress.\n",
      "Peter’s head was delivered first, but due to his size, his shoulders became stuck (shoulder dystocia). Multiple attempts were made to deliver his body, including the use of a ventouse (vacuum cup) and forceps. The McRoberts position (a manoeuvre often used in this situation) was not adopted, nor was an episiotomy.\n",
      "It was unclear from the records how long there was between the delivery of Peter’s head and his body, but the degree of trauma our client suffered to his head and neck was disproportionate to the amount of traction required to deliver a baby, even under these very difficult circumstances.\n",
      "When Peter was born, he was floppy and not breathing on his own, so he needed help from machines. He also had a wound to his head as a result of the attempted delivery.\n",
      "Peter recovered fairly well in NICU and was breathing independently. However, a lump on the side of his neck was noted and, after further investigation, it was found that he had suffered a severe brachial plexus injury that affected the nerves found at C5, C6 and C7. \n",
      "During the first 10 years of his life, our client underwent five separate procedures to try and improve the long-standing impact of his birth injuries, all of which only helped a little. Peter was unable to raise his right arm above shoulder height and had restrictive movement in his right shoulder. He also had significant scarring on his back due to the amount of surgery he required. Peter also suffered significant psychiatric damage This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Activating layers at indices: [29 15 24 17  8  9 30 25] for the next steps.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/g/.local/lib/python3.10/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n",
      "  warnings.warn(\n"
     ]
    },
    {
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       "\n",
       "    <div>\n",
       "      \n",
       "      <progress value='109' max='750' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      [109/750 13:05 < 1:18:27, 0.14 it/s, Epoch 0.43/3]\n",
       "    </div>\n",
       "    <table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       " <tr style=\"text-align: left;\">\n",
       "      <th>Step</th>\n",
       "      <th>Training Loss</th>\n",
       "      <th>Validation Loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table><p>"
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     "text": [
      "Activating layers at indices: [10  7  0 21  5 16 26 12] for the next steps.\n",
      "Activating layers at indices: [30  0 22 31 18 28 10 15] for the next steps.\n",
      "Activating layers at indices: [26 20  5  1 17 13 25  3] for the next steps.\n",
      "Activating layers at indices: [17 18  1  5  3 15 24 25] for the next steps.\n",
      "Activating layers at indices: [15  4 31  2  7 16  0 23] for the next steps.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:168: UserWarning: Could not find response key `<|im_start|>assistant` in the following instance: <|im_start|> user\n",
      "these are some examples of \"stable diffusion prompts\" (ai that generates images using text as input).\n",
      "\n",
      "example 1: portrait of a young ruggedly handsome but stern warrior in golden armor, male, light brown skin, muscular, masculine, upper body, red crimson hair, long flowing hair, fantasy, symmetrical face, golden eyes, intricate, elegant, highly detailed, digital painting, artstation, concept art, matte, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha.\n",
      "\n",
      "example 2: Girl playing on the computer PC, wearing a baggy hoodie and black tophat, masterpiece, best quality, CG, wallpaper, HDR, high quality, high-definition, extremely detailed, 1girl, bilibili, wide shot.\n",
      "\n",
      "example 3: Keanu Reeves portrait photo of a asia old warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes, 50mm portrait photography, hard rim lighting photography–beta –ar 2:3 –beta –upbeta –beta –upbeta –beta –upbeta.\n",
      "\n",
      "example 4: temple in ruines, forest, stairs, columns, cinematic, detailed, atmospheric, epic, concept art, Matte painting, background, mist, photo-realistic, concept art, volumetric light, cinematic epic + rule of thirds octane render, 8k, corona render, movie concept art, octane render, cinematic, trending on artstation, movie concept art, cinematic composition , ultra-detailed, realistic , hyper-realistic , volumetric lighting, 8k –ar 2:3 –test –uplight.\n",
      "\n",
      "styling tag's work as followed: \"girl looking at the sun, epic, wide shot, studio ghibli\", in this Stable diffusion prompt there are 3 styling tag's.\n",
      "\n",
      "negative tag's work as followed: \"ugly head, bad anathomy, hair floating, muddy water\", in this example there are 4 negative tag's.\n",
      "\n",
      "don't use \"[]\" and \"\\\" and anything written between \" This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n",
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:183: UserWarning: Could not find instruction key `<|im_start|>user` in the following instance: <|im_start|> user\n",
      "these are some examples of \"stable diffusion prompts\" (ai that generates images using text as input).\n",
      "\n",
      "example 1: portrait of a young ruggedly handsome but stern warrior in golden armor, male, light brown skin, muscular, masculine, upper body, red crimson hair, long flowing hair, fantasy, symmetrical face, golden eyes, intricate, elegant, highly detailed, digital painting, artstation, concept art, matte, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha.\n",
      "\n",
      "example 2: Girl playing on the computer PC, wearing a baggy hoodie and black tophat, masterpiece, best quality, CG, wallpaper, HDR, high quality, high-definition, extremely detailed, 1girl, bilibili, wide shot.\n",
      "\n",
      "example 3: Keanu Reeves portrait photo of a asia old warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes, 50mm portrait photography, hard rim lighting photography–beta –ar 2:3 –beta –upbeta –beta –upbeta –beta –upbeta.\n",
      "\n",
      "example 4: temple in ruines, forest, stairs, columns, cinematic, detailed, atmospheric, epic, concept art, Matte painting, background, mist, photo-realistic, concept art, volumetric light, cinematic epic + rule of thirds octane render, 8k, corona render, movie concept art, octane render, cinematic, trending on artstation, movie concept art, cinematic composition , ultra-detailed, realistic , hyper-realistic , volumetric lighting, 8k –ar 2:3 –test –uplight.\n",
      "\n",
      "styling tag's work as followed: \"girl looking at the sun, epic, wide shot, studio ghibli\", in this Stable diffusion prompt there are 3 styling tag's.\n",
      "\n",
      "negative tag's work as followed: \"ugly head, bad anathomy, hair floating, muddy water\", in this example there are 4 negative tag's.\n",
      "\n",
      "don't use \"[]\" and \"\\\" and anything written between \" This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Activating layers at indices: [30 15 10 17 26 25 23 21] for the next steps.\n",
      "Activating layers at indices: [ 9 12 15  6 14 24  2 13] for the next steps.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:168: UserWarning: Could not find response key `<|im_start|>assistant` in the following instance: <|im_start|> user\n",
      "Please have a look at the following hexdump and analyze it\n",
      "\n",
      "```0000000 203b 6f4d 7564 656c 4449 3d20 2720 7270\n",
      "0000010 626f 3065 342e 3133 3730 3332 2d30 6763\n",
      "0000020 2e75 2730 730a 756f 6372 5f65 6966 656c\n",
      "0000030 616e 656d 3d20 2220 7270 626f 3065 342e\n",
      "0000040 3133 3730 3332 2d30 6763 2e75 2230 740a\n",
      "0000050 7261 6567 2074 6164 6174 616c 6f79 7475\n",
      "0000060 3d20 2220 2d65 3a6d 2d65 3270 3037 333a\n",
      "0000070 3a32 3233 702d 3732 3a31 3233 333a 2d32\n",
      "0000080 3270 3237 363a 3a34 3436 692d 3436 363a\n",
      "0000090 2d34 3866 3a30 3231 2d38 386e 313a 3a36\n",
      "00000a0 3233 3 This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n",
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:183: UserWarning: Could not find instruction key `<|im_start|>user` in the following instance: <|im_start|> user\n",
      "Please have a look at the following hexdump and analyze it\n",
      "\n",
      "```0000000 203b 6f4d 7564 656c 4449 3d20 2720 7270\n",
      "0000010 626f 3065 342e 3133 3730 3332 2d30 6763\n",
      "0000020 2e75 2730 730a 756f 6372 5f65 6966 656c\n",
      "0000030 616e 656d 3d20 2220 7270 626f 3065 342e\n",
      "0000040 3133 3730 3332 2d30 6763 2e75 2230 740a\n",
      "0000050 7261 6567 2074 6164 6174 616c 6f79 7475\n",
      "0000060 3d20 2220 2d65 3a6d 2d65 3270 3037 333a\n",
      "0000070 3a32 3233 702d 3732 3a31 3233 333a 2d32\n",
      "0000080 3270 3237 363a 3a34 3436 692d 3436 363a\n",
      "0000090 2d34 3866 3a30 3231 2d38 386e 313a 3a36\n",
      "00000a0 3233 3 This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Activating layers at indices: [13 14 15 30  4 20  5 12] for the next steps.\n",
      "Activating layers at indices: [22 13 20  4  6  9 26 14] for the next steps.\n",
      "Activating layers at indices: [27 17  1 21 18 30 25  4] for the next steps.\n",
      "Activating layers at indices: [ 1 28  9 12 17 10  6 23] for the next steps.\n",
      "Activating layers at indices: [22 11  4  3 20 15 28 26] for the next steps.\n",
      "Activating layers at indices: [20  4 29 26 27 16 28 31] for the next steps.\n",
      "Activating layers at indices: [24 30 13 23  8 10 26 17] for the next steps.\n",
      "Activating layers at indices: [ 3 31 30 23 29 18 19 13] for the next steps.\n",
      "Activating layers at indices: [ 5 22 26 10 24 14  8 17] for the next steps.\n",
      "Activating layers at indices: [29 22  5  3  8 24  6 16] for the next steps.\n",
      "Activating layers at indices: [22 11 15 23 16  5 14 30] for the next steps.\n",
      "Activating layers at indices: [ 1  7 30  5  0 10  9 13] for the next steps.\n",
      "Activating layers at indices: [16 31 19  7 17  1 27 25] for the next steps.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:168: UserWarning: Could not find response key `<|im_start|>assistant` in the following instance: <|im_start|> user\n",
      "Can you write a TL;DR for the following paragraphs:\n",
      "\n",
      "Messi was born on 24 June 1987 in Rosario, Santa Fe,[8] the third of four children of Jorge Messi, a steel factory manager, and his wife Celia Cuccittini, who worked in a magnet manufacturing workshop. On his father's side, he is of Italian and Spanish descent, the great-grandson of immigrants from the north-central Adriatic Marche region of Italy, and on his mother's side, he has primarily Italian ancestry.[3] Growing up in a tight-knit, football-loving family, \"Leo\" developed a passion for the sport from an early age, playing constantly with his older brothers, Rodrigo and Matías, and his cousins, Maximiliano and Emanuel Biancucchi, both of whom became professional footballers.[9] At the age of four he joined local club Grandoli, where he was coached by his father, though his earliest influence as a player came from his maternal grandmother, Celia, who accompanied him to training and matches.[10] He was greatly affected by her death, shortly before his eleventh birthday; since then, as a devout Roman Catholic, he has celebrated his goals by looking up and pointing to the sky in tribute to his grandmother.[11][12]\n",
      "\n",
      "\"When you saw him you would think: this kid can't play ball. He's a dwarf, he's too fragile, too small. But immediately you'd realise that he was born different, that he was a phenomenon and that he was going to be something impressive.\"\n",
      "– Newell's Old Boys youth coach Adrián Coria shares his first impression of the 12-year-old Messi.[13]\n",
      "\n",
      "A lifelong supporter of Newell's Old Boys, Messi joined the Rosario club when he was six years old. During the six years he played for Newell's, he scored almost 500 goals as a member of \"The Machine of '87\", the near-unbeatable youth side named for the year of their birth, and regularly entertained crowds by performing ball tricks during half-time of the first team's home games This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n",
      "/home/g/.local/lib/python3.10/site-packages/trl/trainer/utils.py:183: UserWarning: Could not find instruction key `<|im_start|>user` in the following instance: <|im_start|> user\n",
      "Can you write a TL;DR for the following paragraphs:\n",
      "\n",
      "Messi was born on 24 June 1987 in Rosario, Santa Fe,[8] the third of four children of Jorge Messi, a steel factory manager, and his wife Celia Cuccittini, who worked in a magnet manufacturing workshop. On his father's side, he is of Italian and Spanish descent, the great-grandson of immigrants from the north-central Adriatic Marche region of Italy, and on his mother's side, he has primarily Italian ancestry.[3] Growing up in a tight-knit, football-loving family, \"Leo\" developed a passion for the sport from an early age, playing constantly with his older brothers, Rodrigo and Matías, and his cousins, Maximiliano and Emanuel Biancucchi, both of whom became professional footballers.[9] At the age of four he joined local club Grandoli, where he was coached by his father, though his earliest influence as a player came from his maternal grandmother, Celia, who accompanied him to training and matches.[10] He was greatly affected by her death, shortly before his eleventh birthday; since then, as a devout Roman Catholic, he has celebrated his goals by looking up and pointing to the sky in tribute to his grandmother.[11][12]\n",
      "\n",
      "\"When you saw him you would think: this kid can't play ball. He's a dwarf, he's too fragile, too small. But immediately you'd realise that he was born different, that he was a phenomenon and that he was going to be something impressive.\"\n",
      "– Newell's Old Boys youth coach Adrián Coria shares his first impression of the 12-year-old Messi.[13]\n",
      "\n",
      "A lifelong supporter of Newell's Old Boys, Messi joined the Rosario club when he was six years old. During the six years he played for Newell's, he scored almost 500 goals as a member of \"The Machine of '87\", the near-unbeatable youth side named for the year of their birth, and regularly entertained crowds by performing ball tricks during half-time of the first team's home games This instance will be ignored in loss calculation. Note, if this happens often, consider increasing the `max_seq_length`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Activating layers at indices: [24 25 31 22 29  8 10  9] for the next steps.\n",
      "Activating layers at indices: [17  9 30  1 20 26 28 23] for the next steps.\n"
     ]
    }
   ],
   "source": [
    "wandb.init(\n",
    "    project = \"LISA-7B\", \n",
    "    name = run_id,\n",
    ")#.log_code(include_fn=lambda path: path.endswith(\".py\") or path.endswith(\".ipynb\"))\n",
    "\n",
    "trainer.train()"
   ]
  }
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