Upload gemma-tokenizer-test.ipynb

gemma-tokenizer-test.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f9427918",
+   "metadata": {},
+   "source": [
+    "## Load original and transformers tokenizers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "48a7fddf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from huggingface_hub import hf_hub_download\n",
+    "\n",
+    "original_path = hf_hub_download(repo_id=\"google/codegemma-1.1-2b\", filename=\"tokenizer.model\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "aae9d9de",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from gemma.tokenizer import Tokenizer\n",
+    "\n",
+    "original = Tokenizer(original_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "06b063cf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import GemmaTokenizer, AutoTokenizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a584d69f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Fails for \"main\"\n",
+    "revision = \"refs/pr/4\"\n",
+    "\n",
+    "t_fast = AutoTokenizer.from_pretrained(\"google/codegemma-1.1-7b-it\", revision=revision)\n",
+    "t_slow = GemmaTokenizer.from_pretrained(\"google/codegemma-1.1-7b-it\", revision=revision)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "72a1c087",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for s in [\n",
+    "    '<start_of_turn>', '<end_of_turn>', '<mask>',\n",
+    "    '<|fim_prefix|>', '<|fim_suffix|>', '<|fim_middle|>', '<|file_separator|>'\n",
+    "]:\n",
+    "    encoded = original.encode(s, bos=False, eos=False)\n",
+    "    assert t_fast.encode(s, add_special_tokens=False) == encoded, f\"Failed: {s}\"\n",
+    "    assert t_slow.encode(s, add_special_tokens=False) == encoded, f\"Failed: {s}\"\n",
+    "    assert t_fast.decode(encoded) == s, f\"Failed: {s}\"\n",
+    "    assert t_slow.decode(encoded) == s, f\"Failed: {s}\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8ab89d7b",
+   "metadata": {},
+   "source": [
+    "## Verify on XNLI (validation split)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0160405a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "from tqdm import tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a743115c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xnli = load_dataset(\"xnli\", \"all_languages\", split=\"validation\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "9a52691b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def verify(lang, text):\n",
+    "    encoded_original = original.encode(text, bos=True, eos=False)\n",
+    "    encoded_fast = t_fast.encode(text)\n",
+    "    encoded_slow = t_slow.encode(text)\n",
+    "    assert encoded_fast == encoded_original, f\"Fast encode error: {lang} - {text}\"\n",
+    "    assert encoded_slow == encoded_original, f\"Slow encode error: {lang} - {text}\"\n",
+    "    decoded = original.decode(encoded_original)\n",
+    "    decoded_fast = t_fast.decode(encoded_fast, skip_special_tokens=True)\n",
+    "    decoded_slow = t_slow.decode(encoded_slow, skip_special_tokens=True)\n",
+    "    assert decoded_fast == decoded, f\"Fast decode error: {lang} - {text}\"\n",
+    "    assert decoded_slow == decoded, f\"Slow decode error: {lang} - {text}\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f3123ffd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2490/2490 [00:30<00:00, 80.45it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "for p in tqdm(xnli[\"premise\"]):\n",
+    "    for lang, text in p.items():\n",
+    "        verify(lang, text)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}