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535.104.05 Driver Version: 535.104.05 CUDA Version: 12.2 |\n", "|-----------------------------------------+----------------------+----------------------+\n", "| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n", "| | | MIG M. |\n", "|=========================================+======================+======================|\n", "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 59C P8 10W / 70W | 0MiB / 15360MiB | 0% Default |\n", "| | | N/A |\n", "+-----------------------------------------+----------------------+----------------------+\n", " \n", "+---------------------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=======================================================================================|\n", "| No running processes found |\n", "+---------------------------------------------------------------------------------------+\n" ] } ], "source": [ "!nvidia-smi" ] }, { "cell_type": "code", "source": [ "from IPython.display import display, HTML\n", "js = ('')\n", "display(HTML(js))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 17 }, "id": "n_jKmRjyPbEl", "outputId": "8bf86f0a-6556-4e20-b1fc-3caca5f56418" }, "execution_count": 46, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "" ] }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "!pip install transformers datasets soundfile speechbrain accelerate" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ri43Fm6aQCdk", "outputId": "4105fd1e-6ca0-4fa0-a769-db5c13b9f407" }, "execution_count": 3, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.46.2)\n", "Collecting datasets\n", " Downloading datasets-3.1.0-py3-none-any.whl.metadata (20 kB)\n", "Requirement already satisfied: soundfile in /usr/local/lib/python3.10/dist-packages (0.12.1)\n", "Collecting speechbrain\n", " Downloading 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speechbrain, datasets\n", " Attempting uninstall: fsspec\n", " Found existing installation: fsspec 2024.10.0\n", " Uninstalling fsspec-2024.10.0:\n", " Successfully uninstalled fsspec-2024.10.0\n", "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed datasets-3.1.0 dill-0.3.8 fsspec-2024.9.0 hyperpyyaml-1.2.2 multiprocess-0.70.16 ruamel.yaml-0.18.6 ruamel.yaml.clib-0.2.12 speechbrain-1.0.2 xxhash-3.5.0\n" ] } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login\n", "\n", "notebook_login()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 17, "referenced_widgets": [ "dc710b2d90564aea92472ad151453444", "83ac947298704da296eff1ea8a7fd6ad", "2602312d215545718963d78b9700e153", "d2a6e27b564944c6973cc8544db15736", "38c99757bddd4e0aa6ac6b845239cd7c", "c3eb7fec1cd0470381642e2b7520f3c8", "86af62717c2f4d51b4a59d73f71be1fe", "623925336fed4ce784c8915a8592f642", "0c287eb0e7674b56b1c3799e68ade613", "68e7824df35c439f8524ae6b10098c53", "246c884fe3944a51b94706fc10d7408f", "767479110c6f4d568b416926e2d64dcd", "a5baffb76f7c46f99f7fa1edcc9e4229", "e8f2627f0cd249e0af8f49ff1150796c", "cd640da14fb346d0ba65ad213d395d62", "194341988ba34eb98e46cc063eb3c3ff", "40153a03586948a39ee8687467be1ff8", "de5cc35977f54cfeb96daeaecd6e1cce", "cc8161c0852e43dc912dc8d1c42d7c83", "2e7b98b521b34121a128a6bdc84f2a61" ] }, "id": "3ZcqhrGrQJ1u", "outputId": "d476ce48-a6b3-42e1-f22e-301e68092d5f" }, "execution_count": 4, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='
= ten_hours_in_seconds:\n", " return i\n", " return -1\n", "\n", "# Example usage (assuming 'dataset' is defined as in your previous code):\n", "index = find_10_hour_index(dataset)\n", "\n", "if index != -1:\n", " print(f\"Cumulative audio duration exceeds 10 hours at index {index}.\")\n", " sliced_dataset = dataset.take(index + 1)\n", "else:\n", " print(\"Cumulative audio duration does not reach 10 hours within the dataset.\")\n", " sliced_dataset = dataset.take(index + 1)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "9WN_N9VzSuLu", "outputId": "27ec9841-70cc-410a-f91b-30277b439300" }, "execution_count": 12, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Cumulative audio duration exceeds 10 hours at index 4030.\n" ] } ] }, { "cell_type": "code", "source": [ "from IPython.display import Audio\n", "\n", "example = sliced_dataset[0]\n", "print(\"Normalized Text:\", example[\"normalized_text\"])\n", "print(\"Default Text:\", example[\"raw_text\"])\n", "\n", "Audio(data=example[\"audio\"][\"array\"], rate=example[\"audio\"][\"sampling_rate\"])\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 131 }, "id": "RkxLMP49QKN6", "outputId": "a1ecd69d-635a-44f6-95d6-049db41e862a" }, "execution_count": 13, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Normalized Text: natürlich gibt es übergriffe des herrscherhauses und des sicherheitsapparates und der saudis die sich dahinter verstecken und die gerne bahrain in ihren staat integrieren würden.\n", "Default Text: Natürlich gibt es Übergriffe des Herrscherhauses und des Sicherheitsapparates und der Saudis, die sich dahinter verstecken und die gerne Bahrain in ihren Staat integrieren würden.\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "" ], "text/html": [ "\n", " \n", " " ] }, "metadata": {}, "execution_count": 13 } ] }, { "cell_type": "code", "source": [ "def extract_all_chars(batch):\n", " all_text = \" \".join(batch['normalized_text'])\n", " vocab = list(set(all_text))\n", " return {\"vocab\": [vocab], \"all_text\": [all_text]}" ], "metadata": { "id": "R2WU20GcQKIc" }, "execution_count": 14, "outputs": [] }, { "cell_type": "code", "source": [ "vocabs = sliced_dataset.map(extract_all_chars,\n", " batched=True,\n", " batch_size=-1,\n", " keep_in_memory=True,\n", " remove_columns=sliced_dataset.column_names)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 49, "referenced_widgets": [ "caca230b4c984de0bf8f6cf066c11891", "447ecb5fd5ff49b2b642b4483e9803fa", "770c8e2398bd47b7a45ca039fa5ba0ca", "98bd65cc7f7949a78c536b6d44536063", "bbfba5049fd14e2b9ee109b6cada048e", "a111135b46f34913b43ab62877f3faec", "8c42ae72e146422fa67f8e50ffc3a561", "92e4f18461934e23ad81c38d6d2f3103", "7fe1b50d320447b788de97834e8ec033", "1749b0abdd404482a02eb66f5c3c8454", "9b8e92cdddca4c52aa16ab7fcc5262bb" ] }, "id": "iJ9bx9MeQKQk", "outputId": "ab639357-37ac-4749-ce68-d198d41a067e" }, "execution_count": 15, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Map: 0%| | 0/4031 [00:00" ], "image/png": 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TkyOn06n/+q//UsOGDTV79mw5nU4tWrTI23UCAACU4dGOzLhx49S1a1fX+8hccO+99yo9Pd1rxQEAAFyKRzsyW7Zs0datWxUQEODW3qJFCx05csQrhQEAAFyORzsypaWlKikpKdP+ww8/qGHDhldcFAAAQEV4FGR69eqlefPmue47HA6dPn1a06dP19133+2t2gAAAC7Jo5eWXnzxRSUlJenGG2/U2bNn9dBDD2nfvn1q0qSJli9f7u0aAQAAyuVRkGnatKm+/vprrVixQt98841Onz6t4cOHKzk52e3wLwAAQFXyKMhIUp06dfTwww97sxYAAIBK8TjIZGVlaf78+fruu+8kSW3bttXo0aPVpk0brxUHAABwKR4d9n333XfVvn17ZWZmqlOnTurUqZN27typDh066N133/V2jQAAAOXyaEfm6aefVmpqqmbOnOnWPn36dD399NMaNGiQV4oDAAC4FI92ZI4dO6YhQ4aUaX/44Yd17NixKy4KAACgIjwKMj169NCWLVvKtH/xxRe6/fbbr7goAACAivDopaV77rlHkyZNUmZmprp37y5J2rZtm1atWqUZM2boww8/dOsLAABQFRzGGFPZB/n5VWwjx+FwlPtRBtWpsLBQoaGhKigoUEhIiFfHbjF5rVfHqy4HZ/X1dQkAAFxSRX9/e7QjU1pa6nFhAAAA3lKpMzIZGRlas2aNW9ubb76puLg4RUREaOTIkXI6nR4VMmvWLDkcDo0fP97VdvbsWaWkpCg8PFzBwcEaNGiQ8vLyPBofAADUPpUKMjNnztQ///lP1/09e/Zo+PDhSkxM1OTJk/XRRx8pLS2t0kXs2LFDr7zyijp27OjWPmHCBH300UdatWqVNm3apKNHj2rgwIGVHh8AANROlQoyu3fvVs+ePV33V6xYofj4eC1ZskQTJ07Uyy+/rHfeeadSBZw+fVrJyclasmSJGjdu7GovKCjQ0qVL9dJLL+muu+5Sly5dtGzZMm3dulXbtm2r1PcAAAC1U6WCzM8//6zIyEjX/U2bNqlPnz6u+926ddPhw4crVUBKSor69u2rxMREt/bMzEydO3fOrb1NmzZq1qyZMjIyLjqe0+lUYWGh2w0AANROlQoykZGRys7OliQVFxdr586drj+/lqRTp06pbt26FR5vxYoV2rlzZ7kvR+Xm5iogIECNGjUqU0Nubu5Fx0xLS1NoaKjrFhsbW+F6AACAXSoVZO6++25NnjxZW7ZsUWpqqho0aOD2BnjffPONWrZsWaGxDh8+rHHjxumtt95SvXr1Klf1JaSmpqqgoMB1q+wOEQAAsEel/vz6T3/6kwYOHKg777xTwcHBeuONNxQQEOC6/tprr6lXr14VGiszM1PHjx/XzTff7GorKSnR5s2b9Ze//EWffPKJiouLlZ+f77Yrk5eXp6ioqIuOGxgYqMDAwMpMCwAAWKpSQaZJkybavHmzCgoKFBwcLH9/f7frq1atUnBwcIXG6tmzp/bs2ePW9sgjj6hNmzaaNGmSYmNjVbduXaWnp7s+hDIrK0s5OTlKSEioTNkAAKCW8ugN8UJDQ8ttDwsLq/AYDRs2VPv27d3agoKCFB4e7mofPny4Jk6cqLCwMIWEhGjMmDFKSEhwO5cDAACuXh4Fmeoyd+5c+fn5adCgQXI6nUpKStJf//pXX5cFAABqCI8+a8kmfNZSWXzWEgCgpqvo7+9K/dUSAABATUKQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAa9XxdQGofi0mr62ScQ/O6lsl4wIAcDHsyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACs5dMgk5aWpm7duqlhw4aKiIjQgAEDlJWV5dbn7NmzSklJUXh4uIKDgzVo0CDl5eX5qGIAAFCT+DTIbNq0SSkpKdq2bZvWr1+vc+fOqVevXioqKnL1mTBhgj766COtWrVKmzZt0tGjRzVw4EAfVg0AAGqKOr785uvWrXO7//rrrysiIkKZmZm64447VFBQoKVLl+rtt9/WXXfdJUlatmyZ2rZtq23btql79+5lxnQ6nXI6na77hYWFVTsJAADgMzXqjExBQYEkKSwsTJKUmZmpc+fOKTEx0dWnTZs2atasmTIyMsodIy0tTaGhoa5bbGxs1RcOAAB8osYEmdLSUo0fP1633nqr2rdvL0nKzc1VQECAGjVq5NY3MjJSubm55Y6TmpqqgoIC1+3w4cNVXToAAPARn7609GspKSn69ttv9cUXX1zROIGBgQoMDPRSVQAAoCarETsyo0eP1po1a7RhwwY1bdrU1R4VFaXi4mLl5+e79c/Ly1NUVFQ1VwkAAGoanwYZY4xGjx6t999/X59//rni4uLcrnfp0kV169ZVenq6qy0rK0s5OTlKSEio7nIBAEAN49OXllJSUvT222/rgw8+UMOGDV3nXkJDQ1W/fn2FhoZq+PDhmjhxosLCwhQSEqIxY8YoISGh3L9YAgAAVxefBpmFCxdKknr06OHWvmzZMg0bNkySNHfuXPn5+WnQoEFyOp1KSkrSX//612quFAAA1EQ+DTLGmMv2qVevnhYsWKAFCxZUQ0UAAMAmNeKwLwAAgCcIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAa9WYT7+G/VpMXltlYx+c1bfKxgYA2IsdGQAAYC2CDAAAsBZBBgAAWIszMrBCVZ2/4ewNANiNHRkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwVh1fFwD4UovJa6ts7IOz+lbZ2ACAf2NHBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFp1fF0AUFu1mLy2SsY9OKtvlYwLADZiRwYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC3eRwZAlauq99SReF8d4GrHjgwAALAWQQYAAFiLIAMAAKxlxRmZBQsW6IUXXlBubq46deqk+fPn65ZbbvF1WYBPVOV5E+BiOOdkv9r6+W81fkdm5cqVmjhxoqZPn66dO3eqU6dOSkpK0vHjx31dGgAA8LEaH2ReeukljRgxQo888ohuvPFGLVq0SA0aNNBrr73m69IAAICP1eiXloqLi5WZmanU1FRXm5+fnxITE5WRkVHuY5xOp5xOp+t+QUGBJKmwsNDr9ZU6z3h9TACVUxU/2yirKv97xxpWj6paw6pavwvjGmMu2a9GB5kff/xRJSUlioyMdGuPjIzUv/71r3Ifk5aWphkzZpRpj42NrZIaAfhW6DxfV4ArxRrararX79SpUwoNDb3o9RodZDyRmpqqiRMnuu6Xlpbq5MmTCg8Pl8PhuOLxCwsLFRsbq8OHDyskJOSKx7PJ1Tr3q3Xe0tU796t13hJzvxrnXlPnbYzRqVOnFBMTc8l+NTrINGnSRP7+/srLy3Nrz8vLU1RUVLmPCQwMVGBgoFtbo0aNvF5bSEhIjVrw6nS1zv1qnbd09c79ap23xNyvxrnXxHlfaifmghp92DcgIEBdunRRenq6q620tFTp6elKSEjwYWUAAKAmqNE7MpI0ceJEDR06VF27dtUtt9yiefPmqaioSI888oivSwMAAD5W44PMAw88oBMnTmjatGnKzc3VTTfdpHXr1pU5AFxdAgMDNX369DIvX10Nrta5X63zlq7euV+t85aY+9U4d9vn7TCX+7smAACAGqpGn5EBAAC4FIIMAACwFkEGAABYiyADAACsRZCphAULFqhFixaqV6+e4uPj9eWXX/q6JK9LS0tTt27d1LBhQ0VERGjAgAHKyspy69OjRw85HA632+OPP+6jir3nmWeeKTOvNm3auK6fPXtWKSkpCg8PV3BwsAYNGlTmzRpt1KJFizLzdjgcSklJkVS71nvz5s3q16+fYmJi5HA4tHr1arfrxhhNmzZN0dHRql+/vhITE7Vv3z63PidPnlRycrJCQkLUqFEjDR8+XKdPn67GWVTepeZ97tw5TZo0SR06dFBQUJBiYmI0ZMgQHT161G2M8p4ns2bNquaZVN7l1nzYsGFl5tW7d2+3PjauuXT5uZf3c+9wOPTCCy+4+tiw7gSZClq5cqUmTpyo6dOna+fOnerUqZOSkpJ0/PhxX5fmVZs2bVJKSoq2bdum9evX69y5c+rVq5eKiorc+o0YMULHjh1z3ebMmeOjir2rXbt2bvP64osvXNcmTJigjz76SKtWrdKmTZt09OhRDRw40IfVeseOHTvc5rx+/XpJ0n333efqU1vWu6ioSJ06ddKCBQvKvT5nzhy9/PLLWrRokbZv366goCAlJSXp7Nmzrj7Jycn65z//qfXr12vNmjXavHmzRo4cWV1T8Mil5n3mzBnt3LlTU6dO1c6dO/Xee+8pKytL99xzT5m+M2fOdHsejBkzpjrKvyKXW3NJ6t27t9u8li9f7nbdxjWXLj/3X8/52LFjeu211+RwODRo0CC3fjV+3Q0q5JZbbjEpKSmu+yUlJSYmJsakpaX5sKqqd/z4cSPJbNq0ydV25513mnHjxvmuqCoyffp006lTp3Kv5efnm7p165pVq1a52r777jsjyWRkZFRThdVj3LhxpmXLlqa0tNQYU3vXW5J5//33XfdLS0tNVFSUeeGFF1xt+fn5JjAw0CxfvtwYY8zevXuNJLNjxw5Xn48//tg4HA5z5MiRaqv9SvznvMvz5ZdfGknm0KFDrrbmzZubuXPnVm1xVay8uQ8dOtT079//oo+pDWtuTMXWvX///uauu+5ya7Nh3dmRqYDi4mJlZmYqMTHR1ebn56fExERlZGT4sLKqV1BQIEkKCwtza3/rrbfUpEkTtW/fXqmpqTpzpmo+Hr667du3TzExMbruuuuUnJysnJwcSVJmZqbOnTvn9hxo06aNmjVrVqueA8XFxfr73/+u3//+924fslpb1/vXsrOzlZub67bGoaGhio+Pd61xRkaGGjVqpK5du7r6JCYmys/PT9u3b6/2mqtKQUGBHA5Hmc+pmzVrlsLDw9W5c2e98MILOn/+vG8K9LKNGzcqIiJCrVu31qhRo/TTTz+5rl0ta56Xl6e1a9dq+PDhZa7V9HWv8e/sWxP8+OOPKikpKfNuwpGRkfrXv/7lo6qqXmlpqcaPH69bb71V7du3d7U/9NBDat68uWJiYvTNN99o0qRJysrK0nvvvefDaq9cfHy8Xn/9dbVu3VrHjh3TjBkzdPvtt+vbb79Vbm6uAgICyvyHPTIyUrm5ub4puAqsXr1a+fn5GjZsmKuttq73f7qwjuX9nF+4lpubq4iICLfrderUUVhYWK15Hpw9e1aTJk3S4MGD3T5AcOzYsbr55psVFhamrVu3KjU1VceOHdNLL73kw2qvXO/evTVw4EDFxcXpwIED+uMf/6g+ffooIyND/v7+V8WaS9Ibb7yhhg0blnm53IZ1J8jgolJSUvTtt9+6nROR5PbacIcOHRQdHa2ePXvqwIEDatmyZXWX6TV9+vRxfd2xY0fFx8erefPmeuedd1S/fn0fVlZ9li5dqj59+igmJsbVVlvXG2WdO3dO999/v4wxWrhwodu1iRMnur7u2LGjAgIC9NhjjyktLc3at7aXpAcffND1dYcOHdSxY0e1bNlSGzduVM+ePX1YWfV67bXXlJycrHr16rm127DuvLRUAU2aNJG/v3+Zv1DJy8tTVFSUj6qqWqNHj9aaNWu0YcMGNW3a9JJ94+PjJUn79++vjtKqTaNGjXTDDTdo//79ioqKUnFxsfLz89361KbnwKFDh/TZZ5/p0UcfvWS/2rreF9bxUj/nUVFRZQ74nz9/XidPnrT+eXAhxBw6dEjr1693240pT3x8vM6fP6+DBw9WT4HV5LrrrlOTJk1cz+/avOYXbNmyRVlZWZf92Zdq5roTZCogICBAXbp0UXp6uquttLRU6enpSkhI8GFl3meM0ejRo/X+++/r888/V1xc3GUfs3v3bklSdHR0FVdXvU6fPq0DBw4oOjpaXbp0Ud26dd2eA1lZWcrJyak1z4Fly5YpIiJCffv2vWS/2rrecXFxioqKclvjwsJCbd++3bXGCQkJys/PV2ZmpqvP559/rtLSUlfAs9GFELNv3z599tlnCg8Pv+xjdu/eLT8/vzIvu9juhx9+0E8//eR6ftfWNf+1pUuXqkuXLurUqdNl+9bIdff1aWNbrFixwgQGBprXX3/d7N2714wcOdI0atTI5Obm+ro0rxo1apQJDQ01GzduNMeOHXPdzpw5Y4wxZv/+/WbmzJnmq6++MtnZ2eaDDz4w1113nbnjjjt8XPmVe/LJJ83GjRtNdna2+cc//mESExNNkyZNzPHjx40xxjz++OOmWbNm5vPPPzdfffWVSUhIMAkJCT6u2jtKSkpMs2bNzKRJk9zaa9t6nzp1yuzatcvs2rXLSDIvvfSS2bVrl+uvc2bNmmUaNWpkPvjgA/PNN9+Y/v37m7i4OPPLL7+4xujdu7fp3Lmz2b59u/niiy9Mq1atzODBg301pQq51LyLi4vNPffcY5o2bWp2797t9nPvdDqNMcZs3brVzJ071+zevdscOHDA/P3vfzfXXHONGTJkiI9ndnmXmvupU6fMH/7wB5ORkWGys7PNZ599Zm6++WbTqlUrc/bsWdcYNq65MZd/vhtjTEFBgWnQoIFZuHBhmcfbsu4EmUqYP3++adasmQkICDC33HKL2bZtm69L8jpJ5d6WLVtmjDEmJyfH3HHHHSYsLMwEBgaa66+/3jz11FOmoKDAt4V7wQMPPGCio6NNQECAufbaa80DDzxg9u/f77r+yy+/mCeeeMI0btzYNGjQwNx7773m2LFjPqzYez755BMjyWRlZbm117b13rBhQ7nP76FDhxpj/v0n2FOnTjWRkZEmMDDQ9OzZs8y/yU8//WQGDx5sgoODTUhIiHnkkUfMqVOnfDCbirvUvLOzsy/6c79hwwZjjDGZmZkmPj7ehIaGmnr16pm2bdua559/3u2XfU11qbmfOXPG9OrVy1xzzTWmbt26pnnz5mbEiBFl/gfVxjU35vLPd2OMeeWVV0z9+vVNfn5+mcfbsu4OY4yp0i0fAACAKsIZGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAFetHj16aPz48b4uA8AVIMgAuCLDhg2Tw+Eoc+vdu7evSwNwFajj6wIA2K93795atmyZW1tgYKCPqgFwNWFHBsAVCwwMVFRUlNutcePG2rhxowICArRlyxZX3zlz5igiIkJ5eXmSpHXr1um2225To0aNFB4ert/97nc6cOCAq//BgwflcDj0zjvv6Pbbb1f9+vXVrVs3ff/999qxY4e6du2q4OBg9enTRydOnHA9btiwYRowYIBmzJiha665RiEhIXr88cdVXFx80Xk4nU794Q9/0LXXXqugoCDFx8dr48aNruuHDh1Sv3791LhxYwUFBaldu3b63//9Xy/+SwKoLIIMgCpz4QzKf//3f6ugoEC7du3S1KlT9eqrryoyMlKSVFRUpIkTJ+qrr75Senq6/Pz8dO+996q0tNRtrOnTp2vKlCnauXOn6tSpo4ceekhPP/20/vznP2vLli3av3+/pk2b5vaY9PR0fffdd9q4caOWL1+u9957TzNmzLhovaNHj1ZGRoZWrFihb775Rvfdd5969+6tffv2SZJSUlLkdDq1efNm7dmzR7Nnz1ZwcLCX/9UAVIqvP34bgN2GDh1q/P39TVBQkNvtueeeM8YY43Q6zU033WTuv/9+c+ONN5oRI0ZccrwTJ04YSWbPnj3GGGOys7ONJPPqq6+6+ixfvtxIMunp6a62tLQ007p1a7e6wsLCTFFRkatt4cKFJjg42JSUlBhjjLnzzjvNuHHjjDHGHDp0yPj7+5sjR4641dOzZ0+TmppqjDGmQ4cO5plnnqnsPxGAKsQZGQBX7Le//a0WLlzo1hYWFiZJCggI0FtvvaWOHTuqefPmmjt3rlu/ffv2adq0adq+fbt+/PFH105MTk6O2rdv7+rXsWNH19cXdnM6dOjg1nb8+HG3sTt16qQGDRq47ickJOj06dM6fPiwmjdv7tZ3z549Kikp0Q033ODW7nQ6FR4eLkkaO3asRo0apU8//VSJiYkaNGiQW10Aqh9BBsAVCwoK0vXXX3/R61u3bpUknTx5UidPnlRQUJDrWr9+/dS8eXMtWbJEMTExKi0tVfv27cucZalbt67ra4fDUW7bf74cVRmnT5+Wv7+/MjMz5e/v73btwstHjz76qJKSkrR27Vp9+umnSktL04svvqgxY8Z4/H0BXBnOyACoUgcOHNCECRO0ZMkSxcfHa+jQoa7A8dNPPykrK0tTpkxRz5491bZtW/38889e+95ff/21fvnlF9f9bdu2KTg4WLGxsWX6du7cWSUlJTp+/Liuv/56t1tUVJSrX2xsrB5//HG99957evLJJ7VkyRKv1Qug8tiRAXDFnE6ncnNz3drq1Kmjxo0b6+GHH1ZSUpIeeeQR9e7dWx06dNCLL76op556So0bN1Z4eLgWL16s6Oho5eTkaPLkyV6rq7i4WMOHD9eUKVN08OBBTZ8+XaNHj5afX9n/h7vhhhuUnJysIUOG6MUXX1Tnzp114sQJpaenq2PHjurbt6/Gjx+vPn366IYbbtDPP/+sDRs2qG3btl6rF0DlEWQAXLF169YpOjrara1169Z66KGHdOjQIa1Zs0aSFB0drcWLF2vw4MHq1auXOnXqpBUrVmjs2LFq3769WrdurZdfflk9evTwSl09e/ZUq1atdMcdd8jpdGrw4MF65plnLtp/2bJlevbZZ/Xkk0/qyJEjatKkibp3767f/e53kqSSkhKlpKTohx9+UEhIiHr37l3mzA+A6uUwxhhfFwEA3jZs2DDl5+dr9erVvi4FQBXijAwAALAWQQYAAFiLl5YAAIC12JEBAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKz1/wB895mveN4gRQAAAABJRU5ErkJggg==\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "def select_speaker(speaker_id):\n", " return 100 <= speaker_counts[speaker_id] <= 400\n", "\n", "\n", "dataset = dataset.filter(select_speaker, input_columns=[\"speaker_id\"])" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 49, "referenced_widgets": [ "7de8572020c24e839c0f021bea116ca6", "ac63d357aba342a894ce3b4d74f20c09", "53e693040482499c845fa0f668496093", "6bf8e453b061431b892820ce9f4eac3e", "0960afd2674547eab7620e26c0b0f38e", "0513e95c77984d6587bc178723601288", "3ac02e78c2b143619d46118177aab1e3", "47172325d1c8494ab5f7eda524479ba6", "7ded7cb9e66a4bf39b8baf30f017f250", "8b5349254934414babe292d292120734", "6ab972d2820d4f6c9b254b889cf7d7e0" ] }, "id": "DyYSndGohxbT", "outputId": "0d32fb64-fbd6-487f-9ef4-e4caf8f77872" }, "execution_count": 23, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Filter: 0%| | 0/108473 [00:00" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "sliced_dataset = sliced_dataset.map(prepare_dataset, remove_columns=dataset.column_names)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 87, "referenced_widgets": [ "cb5db8faf1bb4f18ac2a39b55950850b", "4a59afb71c80415d92333d3fe3a5edcb", "e126e2442ece4280b7cbfb7afdea9c19", "040e0a75e7c64a65a4067acde76e1838", "71b6e12fe82f4605a6dd54d494432dff", "f44104c386654426b0f2a61da7972be0", "d7d61c9c8495478c8631616edec8a4f3", "bba9686fd14b4d50a889090776e9d85c", "fda1fcca30ea4cad9b9ed9684e4b1c75", "9d12bf02e3524483af29bf7c2a2ce6b2", "804d43a3bba1416e98848c4b221cea2b" ] }, "id": "282bF-s-kpFy", "outputId": "c4907fe2-4e8b-4cda-89ba-71ed33b69681" }, "execution_count": 33, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Map: 0%| | 0/4031 [00:00 600). Running this sequence through the model will result in indexing errors\n" ] } ] }, { "cell_type": "code", "source": [ "sliced_dataset" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8T7PbybPpeEw", "outputId": "b9fca3f5-ab2f-4720-d994-64467fa6e42d" }, "execution_count": 34, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Dataset({\n", " features: ['input_ids', 'labels', 'speaker_embeddings'],\n", " num_rows: 4031\n", "})" ] }, "metadata": {}, "execution_count": 34 } ] }, { "cell_type": "code", "source": [ "def is_not_too_long(input_ids):\n", " input_length = len(input_ids)\n", " return input_length < 200\n", "\n", "\n", "sliced_dataset = sliced_dataset.filter(is_not_too_long, input_columns=[\"input_ids\"])\n", "len(sliced_dataset)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 67, "referenced_widgets": [ "3692573bf5ec422a889974e3c7af37ce", "0dbf3111b57a40f890270c596e066294", "9a44517c4f564285bc2508200644d466", "85d21406f8bd4810add30a8ac00d43f5", "665a671750ff4f1cbbddfae6f6cf0dca", "2b8d0d7e85bc44bd8f6a9f7fca325df9", "39685c297807418d931257c6d905dfaa", "c7a57088a7734656982e80f7bf06d818", "d394d24026944d45bd27fd92c9e04c50", "43377a48b2f94b228e8d2b37b85799d6", "646ca5dd221c407ea3451b0484b7c070" ] }, "id": "ggnSP4TZkpIj", "outputId": "aac0d800-a4d3-418d-8b83-236742b7e264" }, "execution_count": 35, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Filter: 0%| | 0/4031 [00:00 Dict[str, torch.Tensor]:\n", " input_ids = [{\"input_ids\": feature[\"input_ids\"]} for feature in features]\n", " label_features = [{\"input_values\": feature[\"labels\"]} for feature in features]\n", " speaker_features = [feature[\"speaker_embeddings\"] for feature in features]\n", "\n", " # collate the inputs and targets into a batch\n", " batch = processor.pad(\n", " input_ids=input_ids, labels=label_features, return_tensors=\"pt\"\n", " )\n", "\n", " # replace padding with -100 to ignore loss correctly\n", " batch[\"labels\"] = batch[\"labels\"].masked_fill(\n", " batch.decoder_attention_mask.unsqueeze(-1).ne(1), -100\n", " )\n", "\n", " # not used during fine-tuning\n", " del batch[\"decoder_attention_mask\"]\n", "\n", " # round down target lengths to multiple of reduction factor\n", " if model.config.reduction_factor > 1:\n", " target_lengths = torch.tensor(\n", " [len(feature[\"input_values\"]) for feature in label_features]\n", " )\n", " target_lengths = target_lengths.new(\n", " [\n", " length - length % model.config.reduction_factor\n", " for length in target_lengths\n", " ]\n", " )\n", " max_length = max(target_lengths)\n", " batch[\"labels\"] = batch[\"labels\"][:, :max_length]\n", "\n", " # also add in the speaker embeddings\n", " batch[\"speaker_embeddings\"] = torch.tensor(speaker_features)\n", "\n", " return batch" ], "metadata": { "id": "IOR95x2nmqii" }, "execution_count": 37, "outputs": [] }, { "cell_type": "code", "source": [ "data_collator = TTSDataCollatorWithPadding(processor=processor)" ], "metadata": { "id": "ttKBtlibmqr6" }, "execution_count": 38, "outputs": [] }, { "cell_type": "code", "source": [ "model = SpeechT5ForTextToSpeech.from_pretrained(checkpoint)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "ee3d8d4b68c9455a90430accd489106c", "9e065594d3144636b9eb0979e9531840", "dbc221e3cc2f4b0a86f9d030d34da6c7", "7aa97150fbca4ebbab549a98f98a5c04", "451ca47fd2cb4f9492ceffda49b42989", "a9ec34a2402945df9f37acca46a4263d", "51eccaaf486c43f1aeef8690a8f8833b", "78e4319694c64a86a08361c62ef2be78", "a3c3705c6283454a8104379be733bc52", "bf8e69df26704f44bb84ea8cfab564c6", "608c79e7983c4cdaa1d25372b735db0f", "3446dd051d6145f5979e71b44bbc230f", "ebc1bc7f65c447adac19faf61c6f4097", "f36bfec1e64c4565a177a8c3980017ce", "27e33656e1fd4200b46195ccd950c669", "121cbc11db2e45208d70df62b0d1cdf0", "b103440376074c35a7d64fabb97ed506", "809d529b7f0042f683e60283753d5d9e", "dd82b7170e82424f973eb03c0dbfe481", "7806e95cd3a54a509965dfeb3d71d23b", "bdd586cf24a14ff4b1f4fa33907ad07c", "e85db6cd8c464beca5448d9f83b685e6" ] }, "id": "uAIDgUjZmqu1", "outputId": "1af2a45f-dde8-4504-d3c2-516bd0c0ff68" }, "execution_count": 39, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "config.json: 0%| | 0.00/2.06k [00:00:1: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `Seq2SeqTrainer.__init__`. Use `processing_class` instead.\n", " trainer = Seq2SeqTrainer(\n", "max_steps is given, it will override any value given in num_train_epochs\n" ] } ] }, { "cell_type": "code", "source": [ "trainer.train()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 310 }, "id": "i9LP4i3Krv77", "outputId": "bca1b691-e6c2-44a4-a0d4-b5ccdcb43738" }, "execution_count": 50, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "
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" ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py:2817: UserWarning: Moving the following attributes in the config to the generation config: {'max_length': 1876}. You are seeing this warning because you've set generation parameters in the model config, as opposed to in the generation config.\n", " warnings.warn(\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "TrainOutput(global_step=4000, training_loss=0.5268438875675201, metrics={'train_runtime': 7569.18, 'train_samples_per_second': 16.911, 'train_steps_per_second': 0.528, 'total_flos': 1.7291685751808688e+16, 'train_loss': 0.5268438875675201, 'epoch': 46.44412191582003})" ] }, "metadata": {}, "execution_count": 50 } ] }, { "cell_type": "code", "source": [ "trainer.push_to_hub()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 106 }, "id": "CDoKUQCZrwAf", "outputId": "a887161a-725b-426b-b953-91c159477bb0" }, "execution_count": 51, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "CommitInfo(commit_url='https://huggingface.co/ahk-d/speecht5_finetuned_voxpopuli_de/commit/f8d4ca958006e881a2228df5089e9a184063bc63', commit_message='End of training', commit_description='', oid='f8d4ca958006e881a2228df5089e9a184063bc63', pr_url=None, repo_url=RepoUrl('https://huggingface.co/ahk-d/speecht5_finetuned_voxpopuli_de', endpoint='https://huggingface.co', repo_type='model', repo_id='ahk-d/speecht5_finetuned_voxpopuli_de'), pr_revision=None, pr_num=None)" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 51 } ] }, { "cell_type": "code", "source": [ "def generate_speech_with_random_speaker(text):\n", " dataset = sliced_dataset['test']\n", " processor = SpeechT5Processor.from_pretrained(\"microsoft/speecht5_tts\")\n", " model = SpeechT5ForTextToSpeech.from_pretrained(\"ahk-d/speecht5_finetuned_voxpopuli_de\")\n", " vocoder = SpeechT5HifiGan.from_pretrained(\"microsoft/speecht5_hifigan\")\n", " random_index = random.randint(0, len(dataset) - 1)\n", " example = dataset[random_index]\n", " speaker_embeddings = torch.tensor(example[\"speaker_embeddings\"]).unsqueeze(0)\n", "\n", " inputs = processor(text=text, return_tensors=\"pt\")\n", " speech = model.generate_speech(inputs[\"input_ids\"], speaker_embeddings, vocoder=vocoder)\n", "\n", " return IAudio(speech.numpy(), rate=16000)" ], "metadata": { "id": "JKkb2e32zJCt" }, "execution_count": 88, "outputs": [] }, { "cell_type": "code", "source": [ "generate_speech_with_random_speaker('das ist nicht meine katze')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 75 }, "id": "UiATG1WVzXBN", "outputId": "3c7ba93b-3386-47ac-8a53-b3213dc92ac6" }, "execution_count": 89, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ], "text/html": [ "\n", " \n", " " ] }, "metadata": {}, "execution_count": 89 } ] }, { "cell_type": "code", "source": [ "generate_speech_with_random_speaker('ich bin ein roboter')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 75 }, "id": "UOh2x4c0zh4a", "outputId": "2b0e526e-12aa-4ece-d894-4d6875289827" }, "execution_count": 90, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ], "text/html": [ "\n", " \n", " " ] }, "metadata": {}, "execution_count": 90 } ] } ] }