Pytorch-2-Datasets.ipynb

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Packages and Classes"],"metadata":{"id":"5TdGjA-p3jdo"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"BdvVhpM94mJq"},"outputs":[],"source":["import torch\n","from torch.utils.data import Dataset\n","from torch.utils.data import DataLoader\n","import torchvision\n","import matplotlib.pyplot as plt\n","import os"]},{"cell_type":"markdown","source":["Making the dataset files"],"metadata":{"id":"JnXhagD93nfa"}},{"cell_type":"code","source":["!mkdir /content/mydataset\n","!mkdir /content/mydataset/train/\n","!mkdir /content/mydataset/valid/\n","!mkdir /content/mydataset/test/"],"metadata":{"id":"cdsICr_V49Cn"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["for i in range(80):\n","    with open(f'/content/mydataset/train/{str(i)}.txt','w', encoding='utf-8') as file:\n","        file.write(f'training file #{str(i)}')\n","for i in range(10):\n","    with open(f'/content/mydataset/valid/{str(i)}.txt', 'w', encoding='utf-8') as file:\n","        file.write(f'validation file #{str(i)}')\n","for i in range(10):\n","    with open(f'/content/mydataset/test/{str(i)}.txt', 'w', encoding='utf-8') as file:\n","        file.write(f'testing file #{str(i)}')"],"metadata":{"id":"lGAFUK2Y5Gua"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Loading it into a Dataset object recognizable by Pytorch"],"metadata":{"id":"qJxzqe0x3qFT"}},{"cell_type":"code","source":["class MyTextDataset(Dataset):\n","    def __init__(self, path):\n","        def sort_key(item):\n","            return int(item.replace('.txt',''))\n","            \n","        files_lst = os.listdir(path)\n","        files_lst = sorted([item for item in files_lst if item.endswith('.txt')], key=sort_key)\n","        self.texts = []\n","        for file_name in files_lst:\n","            with open(path+file_name, 'r') as file:\n","                file_content = file.read()\n","                self.texts.append(file_content)\n","    def __len__(self):\n","        return len(self.texts)\n","    def __getitem__(self, idx):\n","        original_item = self.texts[idx]\n","        tokens = original_item.split()\n","        length_lst = [len(token) for token in tokens]\n","        length_lst = length_lst[:20] if len(length_lst) >= 20 else length_lst + [0 for i in range(20-len(length_lst))]\n","        return torch.Tensor(length_lst)"],"metadata":{"id":"c-P2ZMJK6Qfm"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["train_dataset = MyTextDataset('/content/mydataset/train/')"],"metadata":{"id":"b8QAAcbR6KRf"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Working with the dataset"],"metadata":{"id":"-vo9wuig_ckS"}},{"cell_type":"code","source":["len(train_dataset)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YgfvHmqK5b99","executionInfo":{"status":"ok","timestamp":1652710784674,"user_tz":-270,"elapsed":641,"user":{"displayName":"Arman 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shuffle=True)"],"metadata":{"id":"YowgVTT45dLs","executionInfo":{"status":"ok","timestamp":1652710934933,"user_tz":-270,"elapsed":601,"user":{"displayName":"Arman Malekzadeh","userId":"13206128678526609465"}}},"execution_count":11,"outputs":[]},{"cell_type":"code","source":["for idx, batch in enumerate(iter(train_dataloader)):\n","    print(f'Batch {str(idx)} : {str(batch.size())}')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KX1v6_DW-Be6","executionInfo":{"status":"ok","timestamp":1652710936289,"user_tz":-270,"elapsed":5,"user":{"displayName":"Arman Malekzadeh","userId":"13206128678526609465"}},"outputId":"ac6bc19d-4ab1-4d83-8cdb-fc28325971ff"},"execution_count":12,"outputs":[{"output_type":"stream","name":"stdout","text":["Batch 0 : torch.Size([32, 20])\n","Batch 1 : torch.Size([32, 20])\n","Batch 2 : torch.Size([16, 20])\n"]}]},{"cell_type":"markdown","source":["MNIST Dataset"],"metadata":{"id":"eLLzRaAiB1Zj"}},{"cell_type":"code","source":["mnist_dataset = torchvision.datasets.MNIST('/', train=True, download=True,\n","                             transform=torchvision.transforms.Compose([\n","                               torchvision.transforms.ToTensor()\n","                             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Malekzadeh","userId":"13206128678526609465"}},"outputId":"f1a314d3-bb08-4705-d589-0805008c348c"},"execution_count":13,"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n","Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to /MNIST/raw/train-images-idx3-ubyte.gz\n"]},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9912422 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f8169018ae794abc94ab196d8125bf61"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Extracting /MNIST/raw/train-images-idx3-ubyte.gz to /MNIST/raw\n","\n","Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n","Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to /MNIST/raw/train-labels-idx1-ubyte.gz\n"]},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/28881 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"20a781dc8b4c4a358f3c17a20bf9f06e"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Extracting /MNIST/raw/train-labels-idx1-ubyte.gz to /MNIST/raw\n","\n","Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n","Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to /MNIST/raw/t10k-images-idx3-ubyte.gz\n"]},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/1648877 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"47f3e099c41c4ff4b1425888c84b6c93"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Extracting /MNIST/raw/t10k-images-idx3-ubyte.gz to /MNIST/raw\n","\n","Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n","Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to /MNIST/raw/t10k-labels-idx1-ubyte.gz\n"]},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/4542 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"72444c5fc0d54669ad6a00cb103d0f90"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Extracting /MNIST/raw/t10k-labels-idx1-ubyte.gz to /MNIST/raw\n","\n"]}]},{"cell_type":"code","source":["mnist_dataloader = torch.utils.data.DataLoader(mnist_dataset, batch_size=64, shuffle=True)"],"metadata":{"id":"CPMxgn7cCkM_","executionInfo":{"status":"ok","timestamp":1652711125384,"user_tz":-270,"elapsed":376,"user":{"displayName":"Arman 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Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["The shape of this data point"],"metadata":{"id":"YElS1NX9FWrK"}},{"cell_type":"code","source":["mnist_dataset[50][0].shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kkAaY3QUD-gL","executionInfo":{"status":"ok","timestamp":1652711160379,"user_tz":-270,"elapsed":497,"user":{"displayName":"Arman Malekzadeh","userId":"13206128678526609465"}},"outputId":"c7138a90-192d-4f11-c9d0-7c8bf6387a27"},"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/plain":["torch.Size([1, 28, 28])"]},"metadata":{},"execution_count":17}]},{"cell_type":"code","source":["mnist_dataset[50][1]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XijGI055EQwo","executionInfo":{"status":"ok","timestamp":1652711182883,"user_tz":-270,"elapsed":590,"user":{"displayName":"Arman Malekzadeh","userId":"13206128678526609465"}},"outputId":"d097f38e-c215-4f57-9ba7-e8433cd5f969"},"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["3"]},"metadata":{},"execution_count":18}]},{"cell_type":"markdown","source":["What about the batches?"],"metadata":{"id":"nMleRr7BF84x"}},{"cell_type":"code","source":["for idx, batch in enumerate(iter(mnist_dataloader)):\n","    print(f'Batch {str(idx)} : {batch[0].size()}')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_CIR453KCBAf","executionInfo":{"status":"ok","timestamp":1652711238698,"user_tz":-270,"elapsed":7109,"user":{"displayName":"Arman Malekzadeh","userId":"13206128678526609465"}},"outputId":"6b18c2b4-50eb-42c1-cfec-b459b863493e"},"execution_count":21,"outputs":[{"output_type":"stream","name":"stdout","text":["Batch 0 : torch.Size([64, 1, 28, 28])\n","Batch 1 : torch.Size([64, 1, 28, 28])\n","Batch 2 : torch.Size([64, 1, 28, 28])\n","Batch 3 : torch.Size([64, 1, 28, 28])\n","Batch 4 : torch.Size([64, 1, 28, 28])\n","Batch 5 : torch.Size([64, 1, 28, 28])\n","Batch 6 : torch.Size([64, 1, 28, 28])\n","Batch 7 : torch.Size([64, 1, 28, 28])\n","Batch 8 : torch.Size([64, 1, 28, 28])\n","Batch 9 : torch.Size([64, 1, 28, 28])\n","Batch 10 : torch.Size([64, 1, 28, 28])\n","Batch 11 : torch.Size([64, 1, 28, 28])\n","Batch 12 : torch.Size([64, 1, 28, 28])\n","Batch 13 : torch.Size([64, 1, 28, 28])\n","Batch 14 : torch.Size([64, 1, 28, 28])\n","Batch 15 : torch.Size([64, 1, 28, 28])\n","Batch 16 : torch.Size([64, 1, 28, 28])\n","Batch 17 : torch.Size([64, 1, 28, 28])\n","Batch 18 : torch.Size([64, 1, 28, 28])\n","Batch 19 : torch.Size([64, 1, 28, 28])\n","Batch 20 : torch.Size([64, 1, 28, 28])\n","Batch 21 : torch.Size([64, 1, 28, 28])\n","Batch 22 : torch.Size([64, 1, 28, 28])\n","Batch 23 : torch.Size([64, 1, 28, 28])\n","Batch 24 : torch.Size([64, 1, 28, 28])\n","Batch 25 : torch.Size([64, 1, 28, 28])\n","Batch 26 : torch.Size([64, 1, 28, 28])\n","Batch 27 : torch.Size([64, 1, 28, 28])\n","Batch 28 : torch.Size([64, 1, 28, 28])\n","Batch 29 : torch.Size([64, 1, 28, 28])\n","Batch 30 : torch.Size([64, 1, 28, 28])\n","Batch 31 : torch.Size([64, 1, 28, 28])\n","Batch 32 : torch.Size([64, 1, 28, 28])\n","Batch 33 : torch.Size([64, 1, 28, 28])\n","Batch 34 : torch.Size([64, 1, 28, 28])\n","Batch 35 : torch.Size([64, 1, 28, 28])\n","Batch 36 : torch.Size([64, 1, 28, 28])\n","Batch 37 : torch.Size([64, 1, 28, 28])\n","Batch 38 : torch.Size([64, 1, 28, 28])\n","Batch 39 : torch.Size([64, 1, 28, 28])\n","Batch 40 : torch.Size([64, 1, 28, 28])\n","Batch 41 : torch.Size([64, 1, 28, 28])\n","Batch 42 : torch.Size([64, 1, 28, 28])\n","Batch 43 : torch.Size([64, 1, 28, 28])\n","Batch 44 : torch.Size([64, 1, 28, 28])\n","Batch 45 : torch.Size([64, 1, 28, 28])\n","Batch 46 : torch.Size([64, 1, 28, 28])\n","Batch 47 : torch.Size([64, 1, 28, 28])\n","Batch 48 : torch.Size([64, 1, 28, 28])\n","Batch 49 : torch.Size([64, 1, 28, 28])\n","Batch 50 : torch.Size([64, 1, 28, 28])\n","Batch 51 : torch.Size([64, 1, 28, 28])\n","Batch 52 : torch.Size([64, 1, 28, 28])\n","Batch 53 : torch.Size([64, 1, 28, 28])\n","Batch 54 : torch.Size([64, 1, 28, 28])\n","Batch 55 : torch.Size([64, 1, 28, 28])\n","Batch 56 : torch.Size([64, 1, 28, 28])\n","Batch 57 : torch.Size([64, 1, 28, 28])\n","Batch 58 : torch.Size([64, 1, 28, 28])\n","Batch 59 : torch.Size([64, 1, 28, 28])\n","Batch 60 : torch.Size([64, 1, 28, 28])\n","Batch 61 : torch.Size([64, 1, 28, 28])\n","Batch 62 : torch.Size([64, 1, 28, 28])\n","Batch 63 : torch.Size([64, 1, 28, 28])\n","Batch 64 : torch.Size([64, 1, 28, 28])\n","Batch 65 : torch.Size([64, 1, 28, 28])\n","Batch 66 : torch.Size([64, 1, 28, 28])\n","Batch 67 : torch.Size([64, 1, 28, 28])\n","Batch 68 : torch.Size([64, 1, 28, 28])\n","Batch 69 : torch.Size([64, 1, 28, 28])\n","Batch 70 : torch.Size([64, 1, 28, 28])\n","Batch 71 : torch.Size([64, 1, 28, 28])\n","Batch 72 : torch.Size([64, 1, 28, 28])\n","Batch 73 : torch.Size([64, 1, 28, 28])\n","Batch 74 : torch.Size([64, 1, 28, 28])\n","Batch 75 : torch.Size([64, 1, 28, 28])\n","Batch 76 : torch.Size([64, 1, 28, 28])\n","Batch 77 : torch.Size([64, 1, 28, 28])\n","Batch 78 : torch.Size([64, 1, 28, 28])\n","Batch 79 : torch.Size([64, 1, 28, 28])\n","Batch 80 : torch.Size([64, 1, 28, 28])\n","Batch 81 : torch.Size([64, 1, 28, 28])\n","Batch 82 : torch.Size([64, 1, 28, 28])\n","Batch 83 : torch.Size([64, 1, 28, 28])\n","Batch 84 : torch.Size([64, 1, 28, 28])\n","Batch 85 : torch.Size([64, 1, 28, 28])\n","Batch 86 : torch.Size([64, 1, 28, 28])\n","Batch 87 : torch.Size([64, 1, 28, 28])\n","Batch 88 : torch.Size([64, 1, 28, 28])\n","Batch 89 : torch.Size([64, 1, 28, 28])\n","Batch 90 : torch.Size([64, 1, 28, 28])\n","Batch 91 : torch.Size([64, 1, 28, 28])\n","Batch 92 : torch.Size([64, 1, 28, 28])\n","Batch 93 : torch.Size([64, 1, 28, 28])\n","Batch 94 : torch.Size([64, 1, 28, 28])\n","Batch 95 : torch.Size([64, 1, 28, 28])\n","Batch 96 : torch.Size([64, 1, 28, 28])\n","Batch 97 : torch.Size([64, 1, 28, 28])\n","Batch 98 : torch.Size([64, 1, 28, 28])\n","Batch 99 : torch.Size([64, 1, 28, 28])\n","Batch 100 : torch.Size([64, 1, 28, 28])\n","Batch 101 : torch.Size([64, 1, 28, 28])\n","Batch 102 : torch.Size([64, 1, 28, 28])\n","Batch 103 : torch.Size([64, 1, 28, 28])\n","Batch 104 : torch.Size([64, 1, 28, 28])\n","Batch 105 : torch.Size([64, 1, 28, 28])\n","Batch 106 : torch.Size([64, 1, 28, 28])\n","Batch 107 : torch.Size([64, 1, 28, 28])\n","Batch 108 : torch.Size([64, 1, 28, 28])\n","Batch 109 : torch.Size([64, 1, 28, 28])\n","Batch 110 : torch.Size([64, 1, 28, 28])\n","Batch 111 : torch.Size([64, 1, 28, 28])\n","Batch 112 : torch.Size([64, 1, 28, 28])\n","Batch 113 : torch.Size([64, 1, 28, 28])\n","Batch 114 : torch.Size([64, 1, 28, 28])\n","Batch 115 : torch.Size([64, 1, 28, 28])\n","Batch 116 : torch.Size([64, 1, 28, 28])\n","Batch 117 : torch.Size([64, 1, 28, 28])\n","Batch 118 : torch.Size([64, 1, 28, 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