SepNorm.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c5Btyg-cL35G",
        "outputId": "0e26e614-8d0a-4c40-c554-d2d4157068ce"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.0.1+cu118)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.12.4)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch) (4.5.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.2)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch) (2.0.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch) (3.27.6)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch) (17.0.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (2.1.3)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch) (1.3.0)\n"
          ]
        }
      ],
      "source": [
        "!pip3 install torch"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "import torch.nn as nn"
      ],
      "metadata": {
        "id": "Ah69f3DDMDGv"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class SepNorm(nn.Module):\n",
        "    def __init__(self, hidden_size, cls_norm=nn.BatchNorm1d, tok_norm=nn.LayerNorm):\n",
        "        super().__init__()\n",
        "        self.cls_norm_layer = cls_norm(hidden_size)\n",
        "        self.tok_norm_layer = tok_norm(hidden_size)\n",
        "    def forward(self, x):\n",
        "        n, l, d = x.shape\n",
        "        cls_states, hidden_states = torch.split(x, [1, l-1], dim=1)\n",
        "        cls_states = self.cls_norm_layer(cls_states.view(n,d))[:, None, :]\n",
        "        hidden_states = self.tok_norm_layer(hidden_states)\n",
        "        hidden_states = torch.cat((cls_states, hidden_states), dim=1)\n",
        "        return hidden_states"
      ],
      "metadata": {
        "id": "Js1QA4fNL8Mr"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "mV_b1wtVMGCr"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}