{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "950d36bf-2792-434e-920d-31954ec49878",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "text_projection.npy: 6.3 MB\n"
     ]
    }
   ],
   "source": [
    "  import os\n",
    "  npy_path = \"/workspace/sdxl_tflite/text_projection.npy\"\n",
    "  size_mb = os.path.getsize(npy_path) / 1024 / 1024\n",
    "  print(f\"text_projection.npy: {size_mb:.1f} MB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0db2e3ce-274a-4af3-bdd3-87886afd603a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done: (1280, 1280), float32\n"
     ]
    }
   ],
   "source": [
    "  import numpy as np\n",
    "  tp = np.load(\"/workspace/sdxl_tflite_fp16/text_projection.npy\")\n",
    "  tp.astype(np.float32).tofile(\"/workspace/sdxl_tflite_fp16/text_projection.bin\")\n",
    "  print(f\"Done: {tp.shape}, {tp.dtype}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eb0f13c8-4ac0-4e8e-b717-5e4723b49e93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/workspace/sdxl_tflite/clip.tflite: 470 MB\n",
      "/workspace/sdxl_tflite/open_clip.tflite: 2644 MB\n",
      "/workspace/sdxl_tflite/diffusion.tflite: 9800 MB\n",
      "/workspace/sdxl_tflite/decoder.tflite: 189 MB\n",
      "\n",
      "/workspace/sdxl_tflite_fp16/clip.tflite: 235 MB\n",
      "/workspace/sdxl_tflite_fp16/open_clip.tflite: 1323 MB\n",
      "/workspace/sdxl_tflite_fp16/diffusion.tflite: 4906 MB\n",
      "/workspace/sdxl_tflite_fp16/decoder.tflite: 95 MB\n",
      "\n"
     ]
    }
   ],
   "source": [
    "  import os\n",
    "  for d in [\"/workspace/sdxl_tflite\", \"/workspace/sdxl_tflite_fp16\"]:\n",
    "      if os.path.exists(d):\n",
    "          for f in [\"clip.tflite\", \"open_clip.tflite\", \"diffusion.tflite\", \"decoder.tflite\"]:\n",
    "              path = f\"{d}/{f}\"\n",
    "              if os.path.exists(path):\n",
    "                  size = os.path.getsize(path) / 1024 / 1024\n",
    "                  print(f\"{d}/{f}: {size:.0f} MB\")\n",
    "          print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4409a65f-e9b8-417a-98a3-6683c8e3d6f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FP16 clip: 235 MB\n"
     ]
    }
   ],
   "source": [
    "  # 원격 서버에서 실행\n",
    "  import os\n",
    "  size = os.path.getsize(\"/workspace/sdxl_tflite_fp16/clip.tflite\")\n",
    "  print(f\"FP16 clip: {size / 1024 / 1024:.0f} MB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d1b11b7e-3acd-4f78-a091-36f628198fc3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/workspace/sdxl_tflite_quantized/clip.tflite: 120 MB\n",
      "/workspace/sdxl_tflite_quantized/open_clip.tflite: 668 MB\n",
      "/workspace/sdxl_tflite_quantized/diffusion.tflite: 2476 MB\n",
      "/workspace/sdxl_tflite_quantized/decoder.tflite: 48 MB\n"
     ]
    }
   ],
   "source": [
    "  import os\n",
    "  # INT8 모델 경로 확인\n",
    "  for d in [\"/workspace/sdxl_tflite_quantized\", \"/tmp/sdxl_tflite_quantized\"]:\n",
    "      if os.path.exists(d):\n",
    "          for f in os.listdir(d):\n",
    "              if f.endswith('.tflite'):\n",
    "                  size = os.path.getsize(f\"{d}/{f}\") / 1024 / 1024\n",
    "                  print(f\"{d}/{f}: {size:.0f} MB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b16e345-80ad-495f-8151-8a1664b5446f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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