006.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/logging/__init__.py\", line 1110, in emit\n",
      "    msg = self.format(record)\n",
      "          ^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/logging/__init__.py\", line 953, in format\n",
      "    return fmt.format(record)\n",
      "           ^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/logging/__init__.py\", line 687, in format\n",
      "    record.message = record.getMessage()\n",
      "                     ^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/logging/__init__.py\", line 377, in getMessage\n",
      "    msg = msg % self.args\n",
      "          ~~~~^~~~~~~~~~~\n",
      "TypeError: not all arguments converted during string formatting\n",
      "Call stack:\n",
      "  File \"<frozen runpy>\", line 198, in _run_module_as_main\n",
      "  File \"<frozen runpy>\", line 88, in _run_code\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel_launcher.py\", line 17, in <module>\n",
      "    app.launch_new_instance()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/traitlets/config/application.py\", line 992, in launch_instance\n",
      "    app.start()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/kernelapp.py\", line 736, in start\n",
      "    self.io_loop.start()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/tornado/platform/asyncio.py\", line 195, in start\n",
      "    self.asyncio_loop.run_forever()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/asyncio/base_events.py\", line 607, in run_forever\n",
      "    self._run_once()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/asyncio/base_events.py\", line 1922, in _run_once\n",
      "    handle._run()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/asyncio/events.py\", line 80, in _run\n",
      "    self._context.run(self._callback, *self._args)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/kernelbase.py\", line 516, in dispatch_queue\n",
      "    await self.process_one()\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/kernelbase.py\", line 505, in process_one\n",
      "    await dispatch(*args)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/kernelbase.py\", line 412, in dispatch_shell\n",
      "    await result\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/kernelbase.py\", line 740, in execute_request\n",
      "    reply_content = await reply_content\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/ipkernel.py\", line 422, in do_execute\n",
      "    res = shell.run_cell(\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/ipykernel/zmqshell.py\", line 546, in run_cell\n",
      "    return super().run_cell(*args, **kwargs)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3024, in run_cell\n",
      "    result = self._run_cell(\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3079, in _run_cell\n",
      "    result = runner(coro)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/IPython/core/async_helpers.py\", line 129, in _pseudo_sync_runner\n",
      "    coro.send(None)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3284, in run_cell_async\n",
      "    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3466, in run_ast_nodes\n",
      "    if await self.run_code(code, result, async_=asy):\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3526, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"/var/folders/_3/20vlbwwd3k36dszfcrzl4g340000gn/T/ipykernel_22101/3814238079.py\", line 6, in <module>\n",
      "    music = synthesiser(\"happy birthday song\", forward_params={\"do_sample\": True})\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/transformers/pipelines/text_to_audio.py\", line 138, in __call__\n",
      "    return super().__call__(text_inputs, **forward_params)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/transformers/pipelines/base.py\", line 1129, in __call__\n",
      "    return self.run_single(inputs, preprocess_params, forward_params, postprocess_params)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/transformers/pipelines/base.py\", line 1136, in run_single\n",
      "    model_outputs = self.forward(model_inputs, **forward_params)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/transformers/pipelines/base.py\", line 1035, in forward\n",
      "    model_outputs = self._forward(model_inputs, **forward_params)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/transformers/pipelines/text_to_audio.py\", line 114, in _forward\n",
      "    output = self.forward_method(**model_inputs, **kwargs)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 115, in decorate_context\n",
      "    return func(*args, **kwargs)\n",
      "  File \"/Users/yashaswi/anaconda3/lib/python3.11/site-packages/transformers/models/musicgen/modeling_musicgen.py\", line 2335, in generate\n",
      "    logger.warning(\n",
      "Message: 'Using the model-agnostic default `max_length` (=1500) to control the generation length.  recommend setting `max_new_tokens` to control the maximum length of the generation.'\n",
      "Arguments: (<class 'UserWarning'>,)\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for *: 'NoneType' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 8\u001b[0m\n\u001b[1;32m      4\u001b[0m synthesiser \u001b[38;5;241m=\u001b[39m pipeline(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtext-to-audio\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfacebook/musicgen-small\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      6\u001b[0m music \u001b[38;5;241m=\u001b[39m synthesiser(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhappy birthday song\u001b[39m\u001b[38;5;124m\"\u001b[39m, forward_params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdo_sample\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mTrue\u001b[39;00m})\n\u001b[0;32m----> 8\u001b[0m scipy\u001b[38;5;241m.\u001b[39mio\u001b[38;5;241m.\u001b[39mwavfile\u001b[38;5;241m.\u001b[39mwrite(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmusicgen_out.wav\u001b[39m\u001b[38;5;124m\"\u001b[39m, rate\u001b[38;5;241m=\u001b[39mmusic[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msampling_rate\u001b[39m\u001b[38;5;124m\"\u001b[39m], data\u001b[38;5;241m=\u001b[39mmusic[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maudio\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.11/site-packages/scipy/io/wavfile.py:794\u001b[0m, in \u001b[0;36mwrite\u001b[0;34m(filename, rate, data)\u001b[0m\n\u001b[1;32m    792\u001b[0m     channels \u001b[38;5;241m=\u001b[39m data\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m    793\u001b[0m bit_depth \u001b[38;5;241m=\u001b[39m data\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mitemsize \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m8\u001b[39m\n\u001b[0;32m--> 794\u001b[0m bytes_per_second \u001b[38;5;241m=\u001b[39m fs\u001b[38;5;241m*\u001b[39m(bit_depth \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m8\u001b[39m)\u001b[38;5;241m*\u001b[39mchannels\n\u001b[1;32m    795\u001b[0m block_align \u001b[38;5;241m=\u001b[39m channels \u001b[38;5;241m*\u001b[39m (bit_depth \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m8\u001b[39m)\n\u001b[1;32m    797\u001b[0m fmt_chunk_data \u001b[38;5;241m=\u001b[39m struct\u001b[38;5;241m.\u001b[39mpack(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m<HHIIHH\u001b[39m\u001b[38;5;124m'\u001b[39m, format_tag, channels, fs,\n\u001b[1;32m    798\u001b[0m                              bytes_per_second, block_align, bit_depth)\n",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for *: 'NoneType' and 'int'"
     ]
    }
   ],
   "source": [
    "from transformers import pipeline\n",
    "import scipy\n",
    "\n",
    "synthesiser = pipeline(\"text-to-audio\", \"facebook/musicgen-small\")\n",
    "\n",
    "music = synthesiser(\"happy birthday song\", forward_params={\"do_sample\": True})\n",
    "\n",
    "scipy.io.wavfile.write(\"musicgen_out.wav\", rate=music[\"sampling_rate\"], data=music[\"audio\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "419c1e3bf74f48eeb1089da2be44dcde",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "preprocessor_config.json:   0%|          | 0.00/275 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from transformers import AutoProcessor, MusicgenForConditionalGeneration\n",
    "\n",
    "processor = AutoProcessor.from_pretrained(\"facebook/musicgen-small\")\n",
    "model = MusicgenForConditionalGeneration.from_pretrained(\"facebook/musicgen-small\")\n",
    "\n",
    "inputs = processor(\n",
    "    text=[\"80s pop track with bassy drums and synth\", \"90s rock song with loud guitars and heavy drums\"],\n",
    "    padding=True,\n",
    "    return_tensors=\"pt\",\n",
    ")\n",
    "\n",
    "audio_values = model.generate(**inputs, max_new_tokens=256)\n",
    "import scipy\n",
    "\n",
    "sampling_rate = model.config.audio_encoder.sampling_rate\n",
    "scipy.io.wavfile.write(\"musicgen_out_2.wav\", rate=sampling_rate, data=audio_values[0, 0].numpy())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Packaging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import AutoProcessor, MusicgenForConditionalGeneration\n",
    "from transformers import pipeline\n",
    "import scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_a_new_song(description, name_of_the_output_file, max_new_tokens_hyperparameter=256):\n",
    "    processor = AutoProcessor.from_pretrained(\"facebook/musicgen-small\")\n",
    "    model = MusicgenForConditionalGeneration.from_pretrained(\"facebook/musicgen-small\")\n",
    "\n",
    "    inputs = processor(\n",
    "        text=[description],\n",
    "        padding=True,\n",
    "        return_tensors=\"pt\",\n",
    "    )\n",
    "\n",
    "    audio_values = model.generate(**inputs, max_new_tokens=max_new_tokens_hyperparameter)\n",
    "    import scipy\n",
    "\n",
    "    sampling_rate = model.config.audio_encoder.sampling_rate\n",
    "    scipy.io.wavfile.write(name_of_the_output_file, rate=sampling_rate, data=audio_values[0, 0].numpy())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yashaswi/anaconda3/lib/python3.11/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
      "  warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "version_minor": 0
      },
      "text/plain": [
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    }
   ],
   "source": [
    "DESCRIPTION = \"80s pop track with bassy drums and synth and 90s rock song with loud guitars and heavy drums\"\n",
    "OUTPUT_FILE_NAME = \"musicgen_out_3.wav\"\n",
    "\n",
    "# INVOKE the function (hyperparameter is optional)\n",
    "generate_a_new_song(DESCRIPTION, OUTPUT_FILE_NAME, 1024)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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