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Runtime error
File size: 225,833 Bytes
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{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"id": "9db7bd27",
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "72b076a5",
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append('..')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "391c8ebe",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"import torch\n",
"from torchsummary import summary\n",
"import torchaudio\n",
"from IPython.display import Audio\n",
"from scipy.io import wavfile \n",
"import librosa"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "0f0b166a",
"metadata": {},
"outputs": [],
"source": [
"from dataset import *\n",
"from cnn import CNNetwork"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "b690f559",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Using device cpu\n"
]
}
],
"source": [
"if torch.cuda.is_available():\n",
" device = \"cuda\"\n",
"else:\n",
" device = \"cpu\"\n",
"print(f\"Using device {device}\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "5b4cac66",
"metadata": {},
"outputs": [],
"source": [
"mel_spectrogram = torchaudio.transforms.MelSpectrogram(\n",
" sample_rate=16000,\n",
" n_fft=1024,\n",
" hop_length=512,\n",
" n_mels=64\n",
" )\n",
"dataset = VoiceDataset('../data/train', mel_spectrogram, 16000, device)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "55928782",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5717"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dataset)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "296fc1d0",
"metadata": {},
"outputs": [
{
"ename": "AssertionError",
"evalue": "Torch not compiled with CUDA enabled",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mdataset\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n",
"File \u001b[0;32m~/ml-sandbox/VoID/notebooks/../dataset.py:43\u001b[0m, in \u001b[0;36mVoiceDataset.__getitem__\u001b[0;34m(self, index)\u001b[0m\n\u001b[1;32m 40\u001b[0m wav, sr \u001b[38;5;241m=\u001b[39m torchaudio\u001b[38;5;241m.\u001b[39mload(filepath, normalize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 42\u001b[0m \u001b[38;5;66;03m# modify wav file, if necessary\u001b[39;00m\n\u001b[0;32m---> 43\u001b[0m wav \u001b[38;5;241m=\u001b[39m \u001b[43mwav\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 44\u001b[0m wav \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_resample(wav, sr)\n\u001b[1;32m 45\u001b[0m wav \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mix_down(wav)\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/torch/cuda/__init__.py:239\u001b[0m, in \u001b[0;36m_lazy_init\u001b[0;34m()\u001b[0m\n\u001b[1;32m 235\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 236\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot re-initialize CUDA in forked subprocess. To use CUDA with \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 237\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmultiprocessing, you must use the \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mspawn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m start method\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 238\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(torch\u001b[38;5;241m.\u001b[39m_C, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_cuda_getDeviceCount\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m--> 239\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTorch not compiled with CUDA enabled\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 240\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _cudart \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 241\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(\n\u001b[1;32m 242\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlibcudart functions unavailable. It looks like you have a broken build?\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
"\u001b[0;31mAssertionError\u001b[0m: Torch not compiled with CUDA enabled"
]
}
],
"source": [
"dataset[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b921ef42",
"metadata": {},
"outputs": [],
"source": [
"dataset[0][0].shape"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "83671781",
"metadata": {},
"outputs": [],
"source": [
"cnn = CNNetwork()\n",
"# summary(cnn, (1, 64, 44))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "5a12b59f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor(0)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"torch.tensor(0)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "4845de38",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'aman': 0, 'imran': 1, 'labib': 2}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset.label_mapping"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "51c03aaf",
"metadata": {},
"outputs": [
{
"ename": "AssertionError",
"evalue": "Torch not compiled with CUDA enabled",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mdataset\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n",
"File \u001b[0;32m~/ml-sandbox/VoID/notebooks/../dataset.py:43\u001b[0m, in \u001b[0;36mVoiceDataset.__getitem__\u001b[0;34m(self, index)\u001b[0m\n\u001b[1;32m 40\u001b[0m wav, sr \u001b[38;5;241m=\u001b[39m torchaudio\u001b[38;5;241m.\u001b[39mload(filepath, normalize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 42\u001b[0m \u001b[38;5;66;03m# modify wav file, if necessary\u001b[39;00m\n\u001b[0;32m---> 43\u001b[0m wav \u001b[38;5;241m=\u001b[39m \u001b[43mwav\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 44\u001b[0m wav \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_resample(wav, sr)\n\u001b[1;32m 45\u001b[0m wav \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mix_down(wav)\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/torch/cuda/__init__.py:239\u001b[0m, in \u001b[0;36m_lazy_init\u001b[0;34m()\u001b[0m\n\u001b[1;32m 235\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 236\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot re-initialize CUDA in forked subprocess. To use CUDA with \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 237\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmultiprocessing, you must use the \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mspawn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m start method\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 238\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(torch\u001b[38;5;241m.\u001b[39m_C, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_cuda_getDeviceCount\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m--> 239\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTorch not compiled with CUDA enabled\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 240\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _cudart \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 241\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(\n\u001b[1;32m 242\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlibcudart functions unavailable. It looks like you have a broken build?\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
"\u001b[0;31mAssertionError\u001b[0m: Torch not compiled with CUDA enabled"
]
}
],
"source": [
"dataset[0]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "ba6b88ee",
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime\n",
"now = datetime.now()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a6046ccf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'20230516_095454'"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"now.strftime(\"%Y%m%d_%H%M%S\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "d7789a04",
"metadata": {},
"outputs": [
{
"ename": "RuntimeError",
"evalue": "Error(s) in loading state_dict for CNNetwork:\n\tsize mismatch for linear.weight: copying a param with shape torch.Size([3, 7040]) from checkpoint, the shape in current model is torch.Size([3, 35712]).",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mcnn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_state_dict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m../models/void_20230512_225714.pth\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/torch/nn/modules/module.py:2041\u001b[0m, in \u001b[0;36mModule.load_state_dict\u001b[0;34m(self, state_dict, strict)\u001b[0m\n\u001b[1;32m 2036\u001b[0m error_msgs\u001b[38;5;241m.\u001b[39minsert(\n\u001b[1;32m 2037\u001b[0m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMissing key(s) in state_dict: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 2038\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(k) \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m missing_keys)))\n\u001b[1;32m 2040\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(error_msgs) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 2041\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mError(s) in loading state_dict for \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 2042\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(error_msgs)))\n\u001b[1;32m 2043\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _IncompatibleKeys(missing_keys, unexpected_keys)\n",
"\u001b[0;31mRuntimeError\u001b[0m: Error(s) in loading state_dict for CNNetwork:\n\tsize mismatch for linear.weight: copying a param with shape torch.Size([3, 7040]) from checkpoint, the shape in current model is torch.Size([3, 35712])."
]
}
],
"source": [
"cnn.load_state_dict(torch.load(\"../models/void_20230512_225714.pth\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a6030b42",
"metadata": {},
"outputs": [],
"source": [
"x, y = dataset[10]"
]
},
{
"cell_type": "code",
"execution_count": 152,
"id": "78352b6b",
"metadata": {},
"outputs": [],
"source": [
"labels = dataset._labels"
]
},
{
"cell_type": "code",
"execution_count": 153,
"id": "b8cc2162",
"metadata": {},
"outputs": [],
"source": [
"input = x.unsqueeze_(0) "
]
},
{
"cell_type": "code",
"execution_count": 182,
"id": "845ecea4",
"metadata": {},
"outputs": [],
"source": [
"def predict(model, input, target, class_mapping):\n",
" model.eval()\n",
" with torch.no_grad():\n",
" predictions = model(input)\n",
" predicted_index = predictions[0].argmax(0)\n",
" predicted = class_mapping[predicted_index]\n",
" expected = class_mapping[target]\n",
" return predictions"
]
},
{
"cell_type": "code",
"execution_count": 155,
"id": "eb8d1e55",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([[1.0000e+00, 1.3728e-20, 2.8026e-44]])\n"
]
},
{
"data": {
"text/plain": [
"('aman', 'aman')"
]
},
"execution_count": 155,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"predict(cnn, input, y, labels)"
]
},
{
"cell_type": "code",
"execution_count": 156,
"id": "5d58683e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([[[[0.0259, 0.1384, 0.0784, ..., 0.0000, 0.0000, 0.0000],\n",
" [0.0334, 0.1320, 0.0701, ..., 0.0000, 0.0000, 0.0000],\n",
" [0.0481, 0.0324, 0.0545, ..., 0.0000, 0.0000, 0.0000],\n",
" ...,\n",
" [0.2665, 0.3647, 0.3147, ..., 0.0000, 0.0000, 0.0000],\n",
" [0.2710, 0.3796, 0.2160, ..., 0.0000, 0.0000, 0.0000],\n",
" [0.1950, 0.2607, 0.1905, ..., 0.0000, 0.0000, 0.0000]]]])"
]
},
"execution_count": 156,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"input"
]
},
{
"cell_type": "code",
"execution_count": 157,
"id": "b0af5b69",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 1, 64, 157])"
]
},
"execution_count": 157,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"input.shape"
]
},
{
"cell_type": "code",
"execution_count": 158,
"id": "28c0768a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 1, 64, 157])"
]
},
"execution_count": 158,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x.shape"
]
},
{
"cell_type": "code",
"execution_count": 159,
"id": "c5817d01",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'data/aman/aman_1'"
]
},
"execution_count": 159,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.path.join('data', 'aman', 'aman_1')"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "03bb835e",
"metadata": {},
"outputs": [],
"source": [
"test_dataset = VoiceDataset('../data/test', mel_spectrogram, device)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "151f8cb9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[('aman_1.wav', 'aman'),\n",
" ('aman_3.wav', 'aman'),\n",
" ('aman_2.wav', 'aman'),\n",
" ('aman_6.wav', 'aman'),\n",
" ('aman_7.wav', 'aman'),\n",
" ('aman_5.wav', 'aman'),\n",
" ('aman_4.wav', 'aman'),\n",
" ('imran_4.wav', 'imran'),\n",
" ('imran_5.wav', 'imran'),\n",
" ('imran_6.wav', 'imran'),\n",
" ('imran_2.wav', 'imran'),\n",
" ('imran_3.wav', 'imran'),\n",
" ('imran_1.wav', 'imran'),\n",
" ('labib_1.wav', 'labib'),\n",
" ('labib_3.wav', 'labib'),\n",
" ('labib_2.wav', 'labib'),\n",
" ('labib_6.wav', 'labib'),\n",
" ('labib_5.wav', 'labib'),\n",
" ('labib_4.wav', 'labib')]"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_dataset.audio_files_labels"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "4c09f2c2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 64, 469])"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_input, test_output = test_dataset[0]\n",
"test_input.shape"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "c7b767ca",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"48000"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": 179,
"id": "1f4254aa",
"metadata": {},
"outputs": [],
"source": [
"test_input = test_input.unsqueeze_(0) "
]
},
{
"cell_type": "code",
"execution_count": 180,
"id": "f1559f5c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 1, 64, 157])"
]
},
"execution_count": 180,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_input.shape"
]
},
{
"cell_type": "code",
"execution_count": 185,
"id": "5e683c2e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([[1., 0., 0.]])\n"
]
}
],
"source": [
"output = predict(cnn, test_input, test_output, test_dataset._labels)"
]
},
{
"cell_type": "code",
"execution_count": 188,
"id": "581911ad",
"metadata": {},
"outputs": [],
"source": [
"pred = torch.argmax(output, 1)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "135eecde",
"metadata": {},
"outputs": [
{
"ename": "FileNotFoundError",
"evalue": "[Errno 2] No such file or directory: 'https://www2.cs.uic.edu/~i101/SoundFiles/BabyElephantWalk60.wav'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[19], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhttps://www2.cs.uic.edu/~i101/SoundFiles/BabyElephantWalk60.wav\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/torch/serialization.py:791\u001b[0m, in \u001b[0;36mload\u001b[0;34m(f, map_location, pickle_module, weights_only, **pickle_load_args)\u001b[0m\n\u001b[1;32m 788\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mencoding\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m pickle_load_args\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[1;32m 789\u001b[0m pickle_load_args[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mencoding\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m--> 791\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43m_open_file_like\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrb\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m opened_file:\n\u001b[1;32m 792\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _is_zipfile(opened_file):\n\u001b[1;32m 793\u001b[0m \u001b[38;5;66;03m# The zipfile reader is going to advance the current file position.\u001b[39;00m\n\u001b[1;32m 794\u001b[0m \u001b[38;5;66;03m# If we want to actually tail call to torch.jit.load, we need to\u001b[39;00m\n\u001b[1;32m 795\u001b[0m \u001b[38;5;66;03m# reset back to the original position.\u001b[39;00m\n\u001b[1;32m 796\u001b[0m orig_position \u001b[38;5;241m=\u001b[39m opened_file\u001b[38;5;241m.\u001b[39mtell()\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/torch/serialization.py:271\u001b[0m, in \u001b[0;36m_open_file_like\u001b[0;34m(name_or_buffer, mode)\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_open_file_like\u001b[39m(name_or_buffer, mode):\n\u001b[1;32m 270\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _is_path(name_or_buffer):\n\u001b[0;32m--> 271\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_open_file\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 272\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 273\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01min\u001b[39;00m mode:\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/torch/serialization.py:252\u001b[0m, in \u001b[0;36m_open_file.__init__\u001b[0;34m(self, name, mode)\u001b[0m\n\u001b[1;32m 251\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, name, mode):\n\u001b[0;32m--> 252\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'https://www2.cs.uic.edu/~i101/SoundFiles/BabyElephantWalk60.wav'"
]
}
],
"source": [
"torch.load(\"https://www2.cs.uic.edu/~i101/SoundFiles/BabyElephantWalk60.wav\")"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "79807f0c",
"metadata": {},
"outputs": [],
"source": [
"import tempfile"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "05e5d79e",
"metadata": {},
"outputs": [],
"source": [
"temp = tempfile.TemporaryFile()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "225ae469",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting wget\n",
" Downloading wget-3.2.zip (10 kB)\n",
" Preparing metadata (setup.py) ... \u001b[?25ldone\n",
"\u001b[?25hBuilding wheels for collected packages: wget\n",
" Building wheel for wget (setup.py) ... \u001b[?25ldone\n",
"\u001b[?25h Created wheel for wget: filename=wget-3.2-py3-none-any.whl size=9656 sha256=67b26307ba20670a602d8355a077eb17f9f0a53530002bc0f5bc406c82dda766\n",
" Stored in directory: /Users/amanmibra/Library/Caches/pip/wheels/04/5f/3e/46cc37c5d698415694d83f607f833f83f0149e49b3af9d0f38\n",
"Successfully built wget\n",
"Installing collected packages: wget\n",
"Successfully installed wget-3.2\n"
]
}
],
"source": [
"!pip install wget"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "87bf5d95",
"metadata": {},
"outputs": [],
"source": [
"import wget"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "7404e7ac",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"100% [..........................................................................] 2646044 / 2646044"
]
}
],
"source": [
"filename = wget.download(\"https://www2.cs.uic.edu/~i101/SoundFiles/BabyElephantWalk60.wav\")"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "5b6affd4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'BabyElephantWalk60.wav'"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filename"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "bdc86a10",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(tensor([[ 0.0000, 0.0000, 0.0000, ..., 0.0125, -0.0136, -0.0661]]), 22050)"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"torchaudio.load(filename)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "6678dcdd",
"metadata": {},
"outputs": [],
"source": [
"os.remove(filename)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "c838c4b8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.path.exists(filename)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "0574d22f",
"metadata": {},
"outputs": [],
"source": [
"import requests"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "170914df",
"metadata": {},
"outputs": [],
"source": [
"size = (1, 128, 469)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "cae16681",
"metadata": {},
"outputs": [],
"source": [
"fake_wav = torch.rand(size)"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "99c8edf8",
"metadata": {},
"outputs": [
{
"ename": "SSLError",
"evalue": "HTTPSConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /predict (Caused by SSLError(SSLError(1, '[SSL: WRONG_VERSION_NUMBER] wrong version number (_ssl.c:1129)')))",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mSSLError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/connectionpool.py:703\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m 702\u001b[0m \u001b[38;5;66;03m# Make the request on the httplib connection object.\u001b[39;00m\n\u001b[0;32m--> 703\u001b[0m httplib_response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 704\u001b[0m \u001b[43m \u001b[49m\u001b[43mconn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 705\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 706\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 707\u001b[0m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 708\u001b[0m \u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 709\u001b[0m \u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 710\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 711\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 713\u001b[0m \u001b[38;5;66;03m# If we're going to release the connection in ``finally:``, then\u001b[39;00m\n\u001b[1;32m 714\u001b[0m \u001b[38;5;66;03m# the response doesn't need to know about the connection. Otherwise\u001b[39;00m\n\u001b[1;32m 715\u001b[0m \u001b[38;5;66;03m# it will also try to release it and we'll have a double-release\u001b[39;00m\n\u001b[1;32m 716\u001b[0m \u001b[38;5;66;03m# mess.\u001b[39;00m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/connectionpool.py:386\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m 385\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 386\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_conn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 387\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (SocketTimeout, BaseSSLError) \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 388\u001b[0m \u001b[38;5;66;03m# Py2 raises this as a BaseSSLError, Py3 raises it as socket timeout.\u001b[39;00m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/connectionpool.py:1042\u001b[0m, in \u001b[0;36mHTTPSConnectionPool._validate_conn\u001b[0;34m(self, conn)\u001b[0m\n\u001b[1;32m 1041\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(conn, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msock\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m): \u001b[38;5;66;03m# AppEngine might not have `.sock`\u001b[39;00m\n\u001b[0;32m-> 1042\u001b[0m \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1044\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m conn\u001b[38;5;241m.\u001b[39mis_verified:\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/connection.py:419\u001b[0m, in \u001b[0;36mHTTPSConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 417\u001b[0m context\u001b[38;5;241m.\u001b[39mload_default_certs()\n\u001b[0;32m--> 419\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m \u001b[43mssl_wrap_socket\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 420\u001b[0m \u001b[43m \u001b[49m\u001b[43msock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 421\u001b[0m \u001b[43m \u001b[49m\u001b[43mkeyfile\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkey_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 422\u001b[0m \u001b[43m \u001b[49m\u001b[43mcertfile\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcert_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 423\u001b[0m \u001b[43m \u001b[49m\u001b[43mkey_password\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkey_password\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 424\u001b[0m \u001b[43m \u001b[49m\u001b[43mca_certs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mca_certs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 425\u001b[0m \u001b[43m \u001b[49m\u001b[43mca_cert_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mca_cert_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 426\u001b[0m \u001b[43m \u001b[49m\u001b[43mca_cert_data\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mca_cert_data\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 427\u001b[0m \u001b[43m \u001b[49m\u001b[43mserver_hostname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mserver_hostname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 428\u001b[0m \u001b[43m \u001b[49m\u001b[43mssl_context\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 429\u001b[0m \u001b[43m \u001b[49m\u001b[43mtls_in_tls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtls_in_tls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 430\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 432\u001b[0m \u001b[38;5;66;03m# If we're using all defaults and the connection\u001b[39;00m\n\u001b[1;32m 433\u001b[0m \u001b[38;5;66;03m# is TLSv1 or TLSv1.1 we throw a DeprecationWarning\u001b[39;00m\n\u001b[1;32m 434\u001b[0m \u001b[38;5;66;03m# for the host.\u001b[39;00m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/util/ssl_.py:449\u001b[0m, in \u001b[0;36mssl_wrap_socket\u001b[0;34m(sock, keyfile, certfile, cert_reqs, ca_certs, server_hostname, ssl_version, ciphers, ssl_context, ca_cert_dir, key_password, ca_cert_data, tls_in_tls)\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m send_sni:\n\u001b[0;32m--> 449\u001b[0m ssl_sock \u001b[38;5;241m=\u001b[39m \u001b[43m_ssl_wrap_socket_impl\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 450\u001b[0m \u001b[43m \u001b[49m\u001b[43msock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtls_in_tls\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mserver_hostname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mserver_hostname\u001b[49m\n\u001b[1;32m 451\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 452\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/util/ssl_.py:493\u001b[0m, in \u001b[0;36m_ssl_wrap_socket_impl\u001b[0;34m(sock, ssl_context, tls_in_tls, server_hostname)\u001b[0m\n\u001b[1;32m 492\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m server_hostname:\n\u001b[0;32m--> 493\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mssl_context\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrap_socket\u001b[49m\u001b[43m(\u001b[49m\u001b[43msock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mserver_hostname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mserver_hostname\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 494\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/ssl.py:501\u001b[0m, in \u001b[0;36mSSLContext.wrap_socket\u001b[0;34m(self, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, session)\u001b[0m\n\u001b[1;32m 495\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrap_socket\u001b[39m(\u001b[38;5;28mself\u001b[39m, sock, server_side\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m 496\u001b[0m do_handshake_on_connect\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 497\u001b[0m suppress_ragged_eofs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 498\u001b[0m server_hostname\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, session\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 499\u001b[0m \u001b[38;5;66;03m# SSLSocket class handles server_hostname encoding before it calls\u001b[39;00m\n\u001b[1;32m 500\u001b[0m \u001b[38;5;66;03m# ctx._wrap_socket()\u001b[39;00m\n\u001b[0;32m--> 501\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msslsocket_class\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 502\u001b[0m \u001b[43m \u001b[49m\u001b[43msock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msock\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 503\u001b[0m \u001b[43m \u001b[49m\u001b[43mserver_side\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mserver_side\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 504\u001b[0m \u001b[43m \u001b[49m\u001b[43mdo_handshake_on_connect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdo_handshake_on_connect\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 505\u001b[0m \u001b[43m \u001b[49m\u001b[43msuppress_ragged_eofs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msuppress_ragged_eofs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 506\u001b[0m \u001b[43m \u001b[49m\u001b[43mserver_hostname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mserver_hostname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 507\u001b[0m \u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 508\u001b[0m \u001b[43m \u001b[49m\u001b[43msession\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msession\u001b[49m\n\u001b[1;32m 509\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/ssl.py:1041\u001b[0m, in \u001b[0;36mSSLSocket._create\u001b[0;34m(cls, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, context, session)\u001b[0m\n\u001b[1;32m 1040\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdo_handshake_on_connect should not be specified for non-blocking sockets\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 1041\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdo_handshake\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1042\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mOSError\u001b[39;00m, \u001b[38;5;167;01mValueError\u001b[39;00m):\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/ssl.py:1310\u001b[0m, in \u001b[0;36mSSLSocket.do_handshake\u001b[0;34m(self, block)\u001b[0m\n\u001b[1;32m 1309\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msettimeout(\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m-> 1310\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sslobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdo_handshake\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1311\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
"\u001b[0;31mSSLError\u001b[0m: [SSL: WRONG_VERSION_NUMBER] wrong version number (_ssl.c:1129)",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mMaxRetryError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/requests/adapters.py:487\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m 486\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 487\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43murlopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 488\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 489\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 490\u001b[0m \u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 491\u001b[0m \u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 492\u001b[0m \u001b[43m \u001b[49m\u001b[43mredirect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 493\u001b[0m \u001b[43m \u001b[49m\u001b[43massert_same_host\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 494\u001b[0m \u001b[43m \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 495\u001b[0m \u001b[43m \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 496\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmax_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 497\u001b[0m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 498\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 499\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 501\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (ProtocolError, \u001b[38;5;167;01mOSError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/connectionpool.py:787\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m 785\u001b[0m e \u001b[38;5;241m=\u001b[39m ProtocolError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnection aborted.\u001b[39m\u001b[38;5;124m\"\u001b[39m, e)\n\u001b[0;32m--> 787\u001b[0m retries \u001b[38;5;241m=\u001b[39m \u001b[43mretries\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mincrement\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 788\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merror\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43me\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_pool\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_stacktrace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msys\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexc_info\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 789\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 790\u001b[0m retries\u001b[38;5;241m.\u001b[39msleep()\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/urllib3/util/retry.py:592\u001b[0m, in \u001b[0;36mRetry.increment\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m 591\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m new_retry\u001b[38;5;241m.\u001b[39mis_exhausted():\n\u001b[0;32m--> 592\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m MaxRetryError(_pool, url, error \u001b[38;5;129;01mor\u001b[39;00m ResponseError(cause))\n\u001b[1;32m 594\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIncremented Retry for (url=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m): \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, url, new_retry)\n",
"\u001b[0;31mMaxRetryError\u001b[0m: HTTPSConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /predict (Caused by SSLError(SSLError(1, '[SSL: WRONG_VERSION_NUMBER] wrong version number (_ssl.c:1129)')))",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mSSLError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[59], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mrequests\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mput\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhttps://localhost:8000/predict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mwav\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfake_wav\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/requests/api.py:130\u001b[0m, in \u001b[0;36mput\u001b[0;34m(url, data, **kwargs)\u001b[0m\n\u001b[1;32m 118\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mput\u001b[39m(url, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 119\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Sends a PUT request.\u001b[39;00m\n\u001b[1;32m 120\u001b[0m \n\u001b[1;32m 121\u001b[0m \u001b[38;5;124;03m :param url: URL for the new :class:`Request` object.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 127\u001b[0m \u001b[38;5;124;03m :rtype: requests.Response\u001b[39;00m\n\u001b[1;32m 128\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 130\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mput\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/requests/api.py:59\u001b[0m, in \u001b[0;36mrequest\u001b[0;34m(method, url, **kwargs)\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[38;5;66;03m# By using the 'with' statement we are sure the session is closed, thus we\u001b[39;00m\n\u001b[1;32m 56\u001b[0m \u001b[38;5;66;03m# avoid leaving sockets open which can trigger a ResourceWarning in some\u001b[39;00m\n\u001b[1;32m 57\u001b[0m \u001b[38;5;66;03m# cases, and look like a memory leak in others.\u001b[39;00m\n\u001b[1;32m 58\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m sessions\u001b[38;5;241m.\u001b[39mSession() \u001b[38;5;28;01mas\u001b[39;00m session:\n\u001b[0;32m---> 59\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msession\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/requests/sessions.py:587\u001b[0m, in \u001b[0;36mSession.request\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m 582\u001b[0m send_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 583\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeout\u001b[39m\u001b[38;5;124m\"\u001b[39m: timeout,\n\u001b[1;32m 584\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_redirects\u001b[39m\u001b[38;5;124m\"\u001b[39m: allow_redirects,\n\u001b[1;32m 585\u001b[0m }\n\u001b[1;32m 586\u001b[0m send_kwargs\u001b[38;5;241m.\u001b[39mupdate(settings)\n\u001b[0;32m--> 587\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprep\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msend_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 589\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/requests/sessions.py:701\u001b[0m, in \u001b[0;36mSession.send\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m 698\u001b[0m start \u001b[38;5;241m=\u001b[39m preferred_clock()\n\u001b[1;32m 700\u001b[0m \u001b[38;5;66;03m# Send the request\u001b[39;00m\n\u001b[0;32m--> 701\u001b[0m r \u001b[38;5;241m=\u001b[39m \u001b[43madapter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 703\u001b[0m \u001b[38;5;66;03m# Total elapsed time of the request (approximately)\u001b[39;00m\n\u001b[1;32m 704\u001b[0m elapsed \u001b[38;5;241m=\u001b[39m preferred_clock() \u001b[38;5;241m-\u001b[39m start\n",
"File \u001b[0;32m~/anaconda3/envs/void/lib/python3.9/site-packages/requests/adapters.py:518\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m 514\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ProxyError(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[1;32m 516\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, _SSLError):\n\u001b[1;32m 517\u001b[0m \u001b[38;5;66;03m# This branch is for urllib3 v1.22 and later.\u001b[39;00m\n\u001b[0;32m--> 518\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m SSLError(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[1;32m 520\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mConnectionError\u001b[39;00m(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[1;32m 522\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ClosedPoolError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
"\u001b[0;31mSSLError\u001b[0m: HTTPSConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /predict (Caused by SSLError(SSLError(1, '[SSL: WRONG_VERSION_NUMBER] wrong version number (_ssl.c:1129)')))"
]
}
],
"source": [
"requests.put(\"https://localhost:8000/predict\", data={\"wav\": fake_wav})"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "e82ff937",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" 0% [ ] 0 / 18421\r",
" 44% [.................................. ] 8192 / 18421\r",
" 88% [..................................................................... ] 16384 / 18421\r",
"100% [..............................................................................] 18421 / 18421"
]
}
],
"source": [
"filename = wget.download(\"https://cdn.filestackcontent.com/eWof5DcWRKGLO1OjDNkG\")"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "712979c5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'temp'"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filename"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "638c538e",
"metadata": {},
"outputs": [],
"source": [
"audio, sr = librosa.load(filename)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "1a7ee3d2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Audio(audio, rate=sr)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "86de764c",
"metadata": {},
"outputs": [],
"source": [
"wavfile.write('temp.wav', sr, audio)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "53f3c571",
"metadata": {},
"outputs": [],
"source": [
"audio, sr = torchaudio.load('temp.wav')"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "c09f9d10",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Audio(audio, rate=sr)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "30cdf6d7",
"metadata": {},
"outputs": [],
"source": [
"os.remove('temp')\n",
"os.remove('temp.wav')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "10659b82",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.9.16"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|