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@@ -0,0 +1,1159 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "P3V5qVVV11Md"
+   },
+   "source": [
+    "# Pymarian Quick Start\n",
+    "\n",
+    "Last updated: 2024-10-18\n",
+    "\n",
+    ">This notebook accompanies Pymarian demo paper @ EMNLP24 Demo.\n",
+    ">* OpenReview link: https://openreview.net/forum?id=3BKsyqIieh\n",
+    ">* ArXiv : https://arxiv.org/abs/2408.11853\n",
+    ">* Benchmarking Scripts: https://github.com/thammegowda/017-pymarian\n",
+    "\n",
+    "\n",
+    "In this notebook, we demonstrate how to work with Pymarian APIs.\n",
+    "* Evaluator\n",
+    "* Translator\n",
+    "* Trainer\n",
+    "\n",
+    "---\n",
+    "## Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "9KoqMLQ8qhhq",
+    "outputId": "82db372f-60ad-4b91-e441-8f405aa6cae5"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting pymarian==1.12.31\n",
+      "  Downloading pymarian-1.12.31-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (8.7 kB)\n",
+      "Collecting portalocker (from pymarian==1.12.31)\n",
+      "  Downloading portalocker-2.10.1-py3-none-any.whl.metadata (8.5 kB)\n",
+      "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from pymarian==1.12.31) (6.0.2)\n",
+      "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from pymarian==1.12.31) (4.66.5)\n",
+      "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from pymarian==1.12.31) (2.32.3)\n",
+      "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from pymarian==1.12.31) (0.23.5)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->pymarian==1.12.31) (3.15.4)\n",
+      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->pymarian==1.12.31) (2024.6.1)\n",
+      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->pymarian==1.12.31) (24.1)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->pymarian==1.12.31) (4.12.2)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->pymarian==1.12.31) (3.3.2)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->pymarian==1.12.31) (3.7)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->pymarian==1.12.31) (2.0.7)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->pymarian==1.12.31) (2024.7.4)\n",
+      "Downloading pymarian-1.12.31-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (602.7 MB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m602.7/602.7 MB\u001b[0m \u001b[31m2.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hDownloading portalocker-2.10.1-py3-none-any.whl (18 kB)\n",
+      "Installing collected packages: portalocker, pymarian\n",
+      "Successfully installed portalocker-2.10.1 pymarian-1.12.31\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Install pymarian\n",
+    "!pip install pymarian==1.12.31"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "u-GeQtsoxct5",
+    "outputId": "896068cd-d55c-43e1-c88b-82b161ce5caf"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "pymarian-eval 1.12.31\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pymarian-eval --version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "ff26zQAFPh6p",
+    "outputId": "1cfef76e-954e-42ff-e2f5-f1f2a7be0c1c"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Python 3.10.12 (main, Jul 29 2024, 16:56:48) [GCC 11.4.0]; pymarian 1.12.31\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "import urllib\n",
+    "import tarfile\n",
+    "from pathlib import Path\n",
+    "from huggingface_hub import hf_hub_download as hf_get\n",
+    "import pymarian\n",
+    "print(f'Python {sys.version}; pymarian {pymarian.__version__}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8E4ft-ek1SUf"
+   },
+   "source": [
+    "---\n",
+    "## Evaluator\n",
+    "\n",
+    "\n",
+    "NOTE: run `huggingface-cli login` for accessing gated models such as  cometkiwi22 or newer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 243,
+     "referenced_widgets": [
+      "637ca7ba08e949fea3785eff934f020a",
+      "523886666955408ead223a9a4000f875",
+      "4e465ef0da6e42ffb3e5c16662df9091",
+      "dc33862700374d37ae3a2e6a1a475a0f",
+      "2b229f0467e549828ec45cc2827bca11",
+      "027ebfb5f34f4fda96b401a8b155476a",
+      "cc82d496719b404caf0bf81a7b5a97fe",
+      "9ede3132d44d4f4b861b4e420cea24be",
+      "ebf25c1c64ae4081aedb89fb152a1ded",
+      "2d60f2ba4d58406f987b36494ef03f82",
+      "4f0f617b5e9a463080f69e758f0f2d28",
+      "fc179b3b59a94d6f8030280ba52b3c5a",
+      "984f2ee5ee4241c599d7d505122830ce",
+      "ae68418d1a034d0787dd2d2ebd9e7981",
+      "4ec14312802e4a16b13b76001853d659",
+      "ec6263930052437492882363b59bd385",
+      "4760b72992d542028064a7f05e80b517",
+      "6e76351324f84e4fb45cc9440faca4e5",
+      "6313d37086a848148893de8a18f42de5",
+      "56426bccb6cc4902ba2ef498af311972",
+      "65242377d0ee40e28fb47ddafadd9140",
+      "43b6326733b54938a32ec5b6d9fd641b"
+     ]
+    },
+    "id": "T8ay4DGo1Pv9",
+    "outputId": "79907f72-15cc-44c5-b712-fef483a831ee"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
+      "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+      "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+      "You will be able to reuse this secret in all of your notebooks.\n",
+      "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "637ca7ba08e949fea3785eff934f020a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "marian.model.bin:   0%|          | 0.00/2.28G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fc179b3b59a94d6f8030280ba52b3c5a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "vocab.spm:   0%|          | 0.00/5.07M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0165\n",
+      "0.0000\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pymarian import Evaluator\n",
+    "\n",
+    "model = hf_get(\"marian-nmt/chrfoid-wmt23\",\n",
+    "    filename=\"checkpoints/marian.model.bin\")\n",
+    "vocab = hf_get(\"marian-nmt/chrfoid-wmt23\",\n",
+    "    filename=\"vocab.spm\")\n",
+    "evaluator = Evaluator.new(\n",
+    "    model_file=Path(model), vocab_file=Path(vocab),\n",
+    "    like='comet-qe', quiet=True, fp16=False,\n",
+    "    cpu_threads=4)\n",
+    "\n",
+    "srcs =  ['Hello', 'Howdy']\n",
+    "mts = ['Howdy', 'Hello']\n",
+    "lines = [f'{s}\\t{t}' for s,t in zip(srcs, mts)]\n",
+    "scores = evaluator.evaluate(lines)\n",
+    "for score in scores:\n",
+    "    print(f'{score:.4f}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zbHfud9L1b-8"
+   },
+   "source": [
+    "## Translator\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "PAYL0FWI1bMy",
+    "outputId": "0a8fae9f-ef47-433c-c929-e80aff300006"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading http://data.statmt.org/romang/marian-regression-tests/models/wngt19.tar.gz and extracting to /root/tmp/marian-models\n",
+      "Downloaded and extracted model files\n",
+      "Hallo , Guten Morgen .\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pymarian import Translator\n",
+    "\n",
+    "model_url = \"http://data.statmt.org/romang/marian-regression-tests/models/wngt19.tar.gz\"\n",
+    "model_dir = Path.home() / 'tmp' /  'marian-models'\n",
+    "model_file = str(model_dir / 'wngt19' / 'model.base.npz')\n",
+    "vocab_file = str(model_dir / 'wngt19' / 'en-de.spm')\n",
+    "\n",
+    "if not Path(model_file).exists():\n",
+    "    print(f\"Downloading {model_url} and extracting to {model_dir}\")\n",
+    "    request = urllib.request.urlopen(model_url)\n",
+    "    with tarfile.open(fileobj=request, mode=\"r|gz\") as tar:\n",
+    "        tar.extractall(path=model_dir)\n",
+    "    print(\"Downloaded and extracted model files\")\n",
+    "\n",
+    "translator = Translator(models=model_file, vocabs=[vocab_file, vocab_file], quiet=True)\n",
+    "hyp = translator.translate(\"Hello. Good morning.\")\n",
+    "print(hyp)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "KnasOIf91iJi"
+   },
+   "source": [
+    "## Trainer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "LzdSxrJS1mPR",
+    "outputId": "6d73c260-942a-41f8-bf36-909174167d7b"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "==> /root/tmp/marian-tests-data/deu-eng/sample.5k.deu <==\n",
+      "Steigt Gold auf 10.000 Dollar?\n",
+      "SAN FRANCISCO – Es war noch nie leicht, ein rationales Gespräch über den Wert von Gold zu führen.\n",
+      "In letzter Zeit allerdings ist dies schwieriger denn je, ist doch der Goldpreis im letzten Jahrzehnt um über 300 Prozent angestiegen.\n",
+      "Erst letzten Dezember verfassten meine Kollegen Martin Feldstein und Nouriel Roubini Kommentare, in denen sie mutig die vorherrschende optimistische Marktstimmung hinterfragten und sehr überlegt auf die Risiken des Goldes  hinwiesen.\n",
+      "\n",
+      "==> /root/tmp/marian-tests-data/deu-eng/sample.5k.eng <==\n",
+      "$10,000 Gold?\n",
+      "SAN FRANCISCO – It has never been easy to have a rational conversation about the value of gold.\n",
+      "Lately, with gold prices up more than 300% over the last decade, it is harder than ever.\n",
+      "Just last December, fellow economists Martin Feldstein and Nouriel Roubini each penned op-eds bravely questioning bullish market sentiment, sensibly pointing out gold’s risks.\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_url = \"https://textmt.blob.core.windows.net/www/data/marian-tests-data.tgz\"\n",
+    "data_dir = Path.home() / 'tmp' / 'marian-tests-data'\n",
+    "data_dir.mkdir(parents=True, exist_ok=True)\n",
+    "vocab_file = data_dir / 'deu-eng/vocab.8k.spm'\n",
+    "train_src = data_dir / 'deu-eng/sample.5k.deu'\n",
+    "train_tgt = train_src.with_suffix('.eng')\n",
+    "\n",
+    "if not train_tgt.exists():\n",
+    "    print(f\"Downloading data package... to {data_dir}\")\n",
+    "    with urllib.request.urlopen(data_url) as response:\n",
+    "        with tarfile.open(fileobj=response, mode=\"r|gz\") as tar:\n",
+    "            tar.extractall(path=data_dir.parent)\n",
+    "    print(\"Downloaded the data package\")\n",
+    "\n",
+    "!head -n4 {train_src} {train_tgt}\n",
+    "\n",
+    "vocab_file = str(vocab_file)\n",
+    "train_src = str(train_src)\n",
+    "train_tgt = str(train_tgt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "fT7JnH5d1uoQ"
+   },
+   "outputs": [],
+   "source": [
+    "from pymarian import Trainer\n",
+    "args = {\n",
+    "    'type': 'transformer',\n",
+    "    'dim_emb': 512,\n",
+    "    'enc_depth': 6,\n",
+    "    'dec_depth': 6,\n",
+    "    'tied_embeddings_all': True,\n",
+    "    'transformer_heads': 8,\n",
+    "    'transformer_dim_ffn': 2048,\n",
+    "    'transformer_ffn_activation': 'relu',\n",
+    "    'transformer_dropout': 0.1,\n",
+    "    'cost_type': 'ce-mean-words',\n",
+    "    'max_length': 80,\n",
+    "    'mini_batch_fit': False,\n",
+    "    'maxi_batch': 256,\n",
+    "    'optimizer_params': [0.9, 0.98, 1e-09],\n",
+    "    'sync_sgd': True,\n",
+    "    'learn_rate': 0.0003,\n",
+    "    'lr_decay_inv_sqrt': [16000],\n",
+    "    'lr_warmup': 16000,\n",
+    "    'label_smoothing': 0.1,\n",
+    "    'clip_norm': 0,\n",
+    "    'exponential_smoothing': 0.0001,\n",
+    "    'early_stopping': 8,\n",
+    "    'keep_best': True,\n",
+    "    'beam_size': 2,\n",
+    "    'normalize': 1,\n",
+    "    'valid_metrics': ['ce-mean-words', 'bleu', 'perplexity'],\n",
+    "    'valid_mini_batch': 16,\n",
+    "    'mini_batch': '1Mt',\n",
+    "    'after': '100e',  # stop after 500 updates\n",
+    "    'valid_freq': '100Mt',  # validate every 250 updates\n",
+    "    'disp_freq': '50kt',\n",
+    "    'disp_first': 10,\n",
+    "    'save_freq': '100Mt',\n",
+    "    'vocabs': [vocab_file, vocab_file],\n",
+    "    'train_sets': [train_src, train_tgt],\n",
+    "    'quiet': False,\n",
+    "}\n",
+    "\n",
+    "args['model'] = f'{data_dir.parent}/model.npz'\n",
+    "\n",
+    "trainer = Trainer(**args)\n",
+    "trainer.train()\n",
+    "\n",
+    "# careful with notebook retaining objects in memory\n",
+    "# you cant create second object if first one is still consuming GPU RAM\n",
+    "del trainer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DnCvzd6ojTMB",
+    "outputId": "4ac287a1-8743-4eac-86af-06e684a7ad15"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "marian-models\t   model.iter200.npz.decoder.yml  model.npz\t\t   model.npz.progress.yml\n",
+      "marian-tests-data  model.iter400.npz\t\t  model.npz.decoder.yml    model.npz.yml\n",
+      "model.iter200.npz  model.iter400.npz.decoder.yml  model.npz.optimizer.npz\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls {data_dir.parent}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tSu_g0RvkIyZ"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "gpuType": "T4",
+   "provenance": []
+  },
+  "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": "3.10.14"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "027ebfb5f34f4fda96b401a8b155476a": {
+     "model_module": "@jupyter-widgets/base",
+     "model_module_version": "1.2.0",
+     "model_name": "LayoutModel",
+     "state": {
+      "_model_module": "@jupyter-widgets/base",
+      "_model_module_version": "1.2.0",
+      "_model_name": "LayoutModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/base",
+      "_view_module_version": "1.2.0",
+      "_view_name": "LayoutView",
+      "align_content": null,
+      "align_items": null,
+      "align_self": null,
+      "border": null,
+      "bottom": null,
+      "display": null,
+      "flex": null,
+      "flex_flow": null,
+      "grid_area": null,
+      "grid_auto_columns": null,
+      "grid_auto_flow": null,
+      "grid_auto_rows": null,
+      "grid_column": null,
+      "grid_gap": null,
+      "grid_row": null,
+      "grid_template_areas": null,
+      "grid_template_columns": null,
+      "grid_template_rows": null,
+      "height": null,
+      "justify_content": null,
+      "justify_items": null,
+      "left": null,
+      "margin": null,
+      "max_height": null,
+      "max_width": null,
+      "min_height": null,
+      "min_width": null,
+      "object_fit": null,
+      "object_position": null,
+      "order": null,
+      "overflow": null,
+      "overflow_x": null,
+      "overflow_y": null,
+      "padding": null,
+      "right": null,
+      "top": null,
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