{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4ae47336",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "B, T, D = 4, 7, 32\n",
    "x = torch.randn(B, T, D)\n",
    "attn_mask = torch.triu(torch.ones(T, T, dtype=torch.bool), diagonal=1)  # [T,T]\n",
    "pad_mask  = torch.zeros(B, T, dtype=torch.bool)  # no pads\n",
    "mha = torch.nn.MultiheadAttention(D, num_heads=4, batch_first=True)\n",
    "y, _ = mha(x, x, x, attn_mask=attn_mask, key_padding_mask=pad_mask)  # should work\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e38e3fb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[[0, 0, 0, 0, 1, 0, 0, 0, 0, 0],\n",
       "         [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 0, 1]],\n",
       "\n",
       "        [[0, 0, 1, 0, 0, 0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],\n",
       "         [0, 0, 0, 0, 0, 1, 0, 0, 0, 0]]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.nn.functional.one_hot(torch.tensor([\n",
    "    [4, 1, 9],\n",
    "    [2,4,5]\n",
    "]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7119ad53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cpu')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.get_default_device()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8c95691a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "xpu\n"
     ]
    }
   ],
   "source": [
    "from Project_Model.Libs.TorchShims import get_default_device\n",
    "\n",
    "print(get_default_device())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "deep_learning",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}