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{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"Collecting torchtext\n",
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"\u001b[?25hCollecting tqdm\n",
" Using cached tqdm-4.65.0-py3-none-any.whl (77 kB)\n",
"Requirement already satisfied: numpy in /home/gedin/.local/lib/python3.10/site-packages (from torchtext) (1.24.3)\n",
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"\u001b[?25hRequirement already satisfied: requests in /usr/lib/python3/dist-packages (from torchtext) (2.25.1)\n",
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"\u001b[?25hCollecting nvidia-cudnn-cu11==8.5.0.96\n",
" Using cached nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB)\n",
"Collecting nvidia-cuda-cupti-cu11==11.7.101\n",
" Using cached nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl (11.8 MB)\n",
"Collecting nvidia-cusparse-cu11==11.7.4.91\n",
" Using cached nvidia_cusparse_cu11-11.7.4.91-py3-none-manylinux1_x86_64.whl (173.2 MB)\n",
"Collecting networkx\n",
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"Collecting nvidia-cufft-cu11==10.9.0.58\n",
" Using cached nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl (168.4 MB)\n",
"Collecting filelock\n",
" Downloading filelock-3.12.0-py3-none-any.whl (10 kB)\n",
"Collecting nvidia-cuda-runtime-cu11==11.7.99\n",
" Using cached nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB)\n",
"Collecting triton==2.0.0\n",
" Downloading triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (63.3 MB)\n",
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"\u001b[?25hCollecting nvidia-cusolver-cu11==11.4.0.1\n",
" Using cached nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl (102.6 MB)\n",
"Requirement already satisfied: jinja2 in /home/gedin/.local/lib/python3.10/site-packages (from torch==2.0.1->torchtext) (3.1.2)\n",
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" Using cached nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB)\n",
"Collecting typing-extensions\n",
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"Collecting nvidia-nccl-cu11==2.14.3\n",
" Using cached nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl (177.1 MB)\n",
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" Using cached nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB)\n",
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" Using cached nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl (54.6 MB)\n",
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" Using cached nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl (98 kB)\n",
"Requirement already satisfied: urllib3>=1.25 in /usr/lib/python3/dist-packages (from torchdata==0.6.1->torchtext) (1.26.5)\n",
"Requirement already satisfied: wheel in /usr/lib/python3/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch==2.0.1->torchtext) (0.37.1)\n",
"Requirement already satisfied: setuptools in /usr/lib/python3/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch==2.0.1->torchtext) (59.6.0)\n",
"Collecting lit\n",
" Downloading lit-16.0.5.tar.gz (138 kB)\n",
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25ldone\n",
"\u001b[?25hCollecting cmake\n",
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"Building wheels for collected packages: lit\n",
" Building wheel for lit (setup.py) ... \u001b[?25ldone\n",
"\u001b[?25h Created wheel for lit: filename=lit-16.0.5-py3-none-any.whl size=88192 sha256=f6c57a31a147cbfe0af3d6bf4b856390ad14c28a9ddb38c8044ec29331b35c26\n",
" Stored in directory: /home/gedin/.cache/pip/wheels/eb/02/84/d82f0b1a6098209edf7e3607be6cc592ebbc015a8a3127c68d\n",
"Successfully built lit\n",
"Installing collected packages: mpmath, lit, cmake, typing-extensions, tqdm, sympy, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, networkx, filelock, nvidia-cusolver-cu11, nvidia-cudnn-cu11, triton, torch, torchdata, torchtext\n",
"Successfully installed cmake-3.26.3 filelock-3.12.0 lit-16.0.5 mpmath-1.3.0 networkx-3.1 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 sympy-1.12 torch-2.0.1 torchdata-0.6.1 torchtext-0.15.2 tqdm-4.65.0 triton-2.0.0 typing-extensions-4.6.3\n"
]
}
],
"source": [
"!pip install torchtext"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"train_file ='train/in.tsv.xz'\n",
"test_file = 'test-A/in.tsv.xz'\n",
"out_file = 'test-A/out.tsv'"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"from itertools import islice\n",
"import regex as re\n",
"import sys\n",
"from torchtext.vocab import build_vocab_from_iterator\n",
"import lzma\n",
"import pickle\n",
"import re\n",
"import torch\n",
"from torch import nn\n",
"from torch.utils.data import IterableDataset\n",
"import itertools\n",
"from torch.utils.data import DataLoader\n",
"import gc"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"embed_size = 300\n",
"device = 'cuda'\n",
"vocab_size = 25000\n",
"batch_s = 3200\n",
"learning_rate = 0.0001\n",
"epochs = 4\n",
"k = 20 #top k words\n",
"wildcard_minweight = 0.001"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"###preprocessing\n",
"def preprocess(line):\n",
" line = get_rid_of_header(line)\n",
" line = replace_endline(line)\n",
" return line\n",
"\n",
"def get_rid_of_header(line):\n",
" line = line.split('\\t')[6:]\n",
" return \"\".join(line)\n",
" \n",
"def replace_endline(line):\n",
" line = line.replace(\"\\\\n\", \" \")\n",
" return line\n",
"\n",
"\n",
"def get_last_word(text):\n",
" \"\"\"Return the last word of a string.\"\"\"\n",
" last_word = \"\"\n",
" for i in range(len(text)-1, -1, -1):\n",
" if text[i] == ' ':\n",
" return last_word[::-1].rstrip()\n",
" else:\n",
" last_word += text[i]\n",
" return last_word[::-1].rstrip()\n",
"\n",
"def get_first_word(text):\n",
" \"\"\"Return the first word of a string.\"\"\"\n",
" word = \"\"\n",
" for i in range(len(text)-1):\n",
" if text[i] == ' ':\n",
" return word\n",
" else:\n",
" word += text[i]\n",
" return word\n",
"\n",
"\n",
"def get_words_from_line(line):\n",
" line = line.rstrip()\n",
" yield '<s>'\n",
" line = preprocess(line)\n",
" for t in line.split(' '):\n",
" yield t\n",
" yield '</s>'\n",
"\n",
"\n",
"def get_word_lines_from_file(file_name):\n",
" n = 0\n",
" with lzma.open(file_name, 'r') as fh:\n",
" for line in fh:\n",
" n+=1\n",
" if n%1000==0:\n",
" print(n)\n",
" yield get_words_from_line(line.decode('utf-8'))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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]
}
],
"source": [
"vocab = build_vocab_from_iterator(\n",
" get_word_lines_from_file(train_file),\n",
" max_tokens = vocab_size,\n",
" specials = ['<unk>'])\n",
"\n",
"with open('filename.pickle', 'wb') as handle:\n",
" pickle.dump(vocab, handle, protocol=pickle.HIGHEST_PROTOCOL)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'vocab' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/ipykernel_20466/3224446201.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvocab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlookup_tokens\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2000\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'vocab' is not defined"
]
}
],
"source": [
"vocab.lookup_tokens([0, 1, 2, 10, 2000])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Definicja sieci\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Naszą prostą sieć neuronową zaimplementujemy używając frameworku PyTorch.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"class SimpleBigramNeuralLanguageModel(nn.Module):\n",
" def __init__(self, vocabulary_size, embedding_size):\n",
" super(SimpleBigramNeuralLanguageModel, self).__init__()\n",
" self.model = nn.Sequential(\n",
" nn.Embedding(vocabulary_size, embedding_size),\n",
" nn.Linear(embedding_size, vocabulary_size),\n",
" nn.Softmax()\n",
" )\n",
" \n",
" def forward(self, x):\n",
" return self.model(x)\n",
"\n",
"with open('filename.pickle','rb') as handle:\n",
" vocab = pickle.load(handle)\n",
"\n",
"vocab.set_default_index(vocab['<unk>'])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on Vocab in module torchtext.vocab.vocab object:\n",
"\n",
"class Vocab(torch.nn.modules.module.Module)\n",
" | Vocab(vocab) -> None\n",
" | \n",
" | Base class for all neural network modules.\n",
" | \n",
" | Your models should also subclass this class.\n",
" | \n",
" | Modules can also contain other Modules, allowing to nest them in\n",
" | a tree structure. You can assign the submodules as regular attributes::\n",
" | \n",
" | import torch.nn as nn\n",
" | import torch.nn.functional as F\n",
" | \n",
" | class Model(nn.Module):\n",
" | def __init__(self):\n",
" | super().__init__()\n",
" | self.conv1 = nn.Conv2d(1, 20, 5)\n",
" | self.conv2 = nn.Conv2d(20, 20, 5)\n",
" | \n",
" | def forward(self, x):\n",
" | x = F.relu(self.conv1(x))\n",
" | return F.relu(self.conv2(x))\n",
" | \n",
" | Submodules assigned in this way will be registered, and will have their\n",
" | parameters converted too when you call :meth:`to`, etc.\n",
" | \n",
" | .. note::\n",
" | As per the example above, an ``__init__()`` call to the parent class\n",
" | must be made before assignment on the child.\n",
" | \n",
" | :ivar training: Boolean represents whether this module is in training or\n",
" | evaluation mode.\n",
" | :vartype training: bool\n",
" | \n",
" | Method resolution order:\n",
" | Vocab\n",
" | torch.nn.modules.module.Module\n",
" | builtins.object\n",
" | \n",
" | Methods defined here:\n",
" | \n",
" | __contains__(self, token: str) -> bool\n",
" | Args:\n",
" | token: The token for which to check the membership.\n",
" | \n",
" | Returns:\n",
" | Whether the token is member of vocab or not.\n",
" | \n",
" | __getitem__(self, token: str) -> int\n",
" | Args:\n",
" | token: The token used to lookup the corresponding index.\n",
" | \n",
" | Returns:\n",
" | The index corresponding to the associated token.\n",
" | \n",
" | __init__(self, vocab) -> None\n",
" | Initializes internal Module state, shared by both nn.Module and ScriptModule.\n",
" | \n",
" | __len__(self) -> int\n",
" | Returns:\n",
" | The length of the vocab.\n",
" | \n",
" | __prepare_scriptable__(self)\n",
" | Return a JITable Vocab.\n",
" | \n",
" | append_token(self, token: str) -> None\n",
" | Args:\n",
" | token: The token used to lookup the corresponding index.\n",
" | \n",
" | Raises:\n",
" | RuntimeError: If `token` already exists in the vocab\n",
" | \n",
" | forward(self, tokens: List[str]) -> List[int]\n",
" | Calls the `lookup_indices` method\n",
" | \n",
" | Args:\n",
" | tokens: a list of tokens used to lookup their corresponding `indices`.\n",
" | \n",
" | Returns:\n",
" | The indices associated with a list of `tokens`.\n",
" | \n",
" | get_default_index(self) -> Union[int, NoneType]\n",
" | Returns:\n",
" | Value of default index if it is set.\n",
" | \n",
" | get_itos(self) -> List[str]\n",
" | Returns:\n",
" | List mapping indices to tokens.\n",
" | \n",
" | get_stoi(self) -> Dict[str, int]\n",
" | Returns:\n",
" | Dictionary mapping tokens to indices.\n",
" | \n",
" | insert_token(self, token: str, index: int) -> None\n",
" | Args:\n",
" | token: The token used to lookup the corresponding index.\n",
" | index: The index corresponding to the associated token.\n",
" | Raises:\n",
" | RuntimeError: If `index` is not in range [0, Vocab.size()] or if `token` already exists in the vocab.\n",
" | \n",
" | lookup_indices(self, tokens: List[str]) -> List[int]\n",
" | Args:\n",
" | tokens: the tokens used to lookup their corresponding `indices`.\n",
" | \n",
" | Returns:\n",
" | The 'indices` associated with `tokens`.\n",
" | \n",
" | lookup_token(self, index: int) -> str\n",
" | Args:\n",
" | index: The index corresponding to the associated token.\n",
" | \n",
" | Returns:\n",
" | token: The token used to lookup the corresponding index.\n",
" | \n",
" | Raises:\n",
" | RuntimeError: If `index` not in range [0, itos.size()).\n",
" | \n",
" | lookup_tokens(self, indices: List[int]) -> List[str]\n",
" | Args:\n",
" | indices: The `indices` used to lookup their corresponding`tokens`.\n",
" | \n",
" | Returns:\n",
" | The `tokens` associated with `indices`.\n",
" | \n",
" | Raises:\n",
" | RuntimeError: If an index within `indices` is not int range [0, itos.size()).\n",
" | \n",
" | set_default_index(self, index: Union[int, NoneType]) -> None\n",
" | Args:\n",
" | index: Value of default index. This index will be returned when OOV token is queried.\n",
" | \n",
" | ----------------------------------------------------------------------\n",
" | Readonly properties defined here:\n",
" | \n",
" | is_jitable\n",
" | \n",
" | ----------------------------------------------------------------------\n",
" | Data and other attributes defined here:\n",
" | \n",
" | __jit_unused_properties__ = ['is_jitable']\n",
" | \n",
" | ----------------------------------------------------------------------\n",
" | Methods inherited from torch.nn.modules.module.Module:\n",
" | \n",
" | __call__ = _call_impl(self, *args, **kwargs)\n",
" | \n",
" | __delattr__(self, name)\n",
" | Implement delattr(self, name).\n",
" | \n",
" | __dir__(self)\n",
" | Default dir() implementation.\n",
" | \n",
" | __getattr__(self, name: str) -> Union[torch.Tensor, ForwardRef('Module')]\n",
" | \n",
" | __repr__(self)\n",
" | Return repr(self).\n",
" | \n",
" | __setattr__(self, name: str, value: Union[torch.Tensor, ForwardRef('Module')]) -> None\n",
" | Implement setattr(self, name, value).\n",
" | \n",
" | __setstate__(self, state)\n",
" | \n",
" | add_module(self, name: str, module: Union[ForwardRef('Module'), NoneType]) -> None\n",
" | Adds a child module to the current module.\n",
" | \n",
" | The module can be accessed as an attribute using the given name.\n",
" | \n",
" | Args:\n",
" | name (str): name of the child module. The child module can be\n",
" | accessed from this module using the given name\n",
" | module (Module): child module to be added to the module.\n",
" | \n",
" | apply(self: ~T, fn: Callable[[ForwardRef('Module')], NoneType]) -> ~T\n",
" | Applies ``fn`` recursively to every submodule (as returned by ``.children()``)\n",
" | as well as self. Typical use includes initializing the parameters of a model\n",
" | (see also :ref:`nn-init-doc`).\n",
" | \n",
" | Args:\n",
" | fn (:class:`Module` -> None): function to be applied to each submodule\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> @torch.no_grad()\n",
" | >>> def init_weights(m):\n",
" | >>> print(m)\n",
" | >>> if type(m) == nn.Linear:\n",
" | >>> m.weight.fill_(1.0)\n",
" | >>> print(m.weight)\n",
" | >>> net = nn.Sequential(nn.Linear(2, 2), nn.Linear(2, 2))\n",
" | >>> net.apply(init_weights)\n",
" | Linear(in_features=2, out_features=2, bias=True)\n",
" | Parameter containing:\n",
" | tensor([[1., 1.],\n",
" | [1., 1.]], requires_grad=True)\n",
" | Linear(in_features=2, out_features=2, bias=True)\n",
" | Parameter containing:\n",
" | tensor([[1., 1.],\n",
" | [1., 1.]], requires_grad=True)\n",
" | Sequential(\n",
" | (0): Linear(in_features=2, out_features=2, bias=True)\n",
" | (1): Linear(in_features=2, out_features=2, bias=True)\n",
" | )\n",
" | \n",
" | bfloat16(self: ~T) -> ~T\n",
" | Casts all floating point parameters and buffers to ``bfloat16`` datatype.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | buffers(self, recurse: bool = True) -> Iterator[torch.Tensor]\n",
" | Returns an iterator over module buffers.\n",
" | \n",
" | Args:\n",
" | recurse (bool): if True, then yields buffers of this module\n",
" | and all submodules. Otherwise, yields only buffers that\n",
" | are direct members of this module.\n",
" | \n",
" | Yields:\n",
" | torch.Tensor: module buffer\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> for buf in model.buffers():\n",
" | >>> print(type(buf), buf.size())\n",
" | <class 'torch.Tensor'> (20L,)\n",
" | <class 'torch.Tensor'> (20L, 1L, 5L, 5L)\n",
" | \n",
" | children(self) -> Iterator[ForwardRef('Module')]\n",
" | Returns an iterator over immediate children modules.\n",
" | \n",
" | Yields:\n",
" | Module: a child module\n",
" | \n",
" | cpu(self: ~T) -> ~T\n",
" | Moves all model parameters and buffers to the CPU.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | cuda(self: ~T, device: Union[int, torch.device, NoneType] = None) -> ~T\n",
" | Moves all model parameters and buffers to the GPU.\n",
" | \n",
" | This also makes associated parameters and buffers different objects. So\n",
" | it should be called before constructing optimizer if the module will\n",
" | live on GPU while being optimized.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Args:\n",
" | device (int, optional): if specified, all parameters will be\n",
" | copied to that device\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | double(self: ~T) -> ~T\n",
" | Casts all floating point parameters and buffers to ``double`` datatype.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | eval(self: ~T) -> ~T\n",
" | Sets the module in evaluation mode.\n",
" | \n",
" | This has any effect only on certain modules. See documentations of\n",
" | particular modules for details of their behaviors in training/evaluation\n",
" | mode, if they are affected, e.g. :class:`Dropout`, :class:`BatchNorm`,\n",
" | etc.\n",
" | \n",
" | This is equivalent with :meth:`self.train(False) <torch.nn.Module.train>`.\n",
" | \n",
" | See :ref:`locally-disable-grad-doc` for a comparison between\n",
" | `.eval()` and several similar mechanisms that may be confused with it.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | extra_repr(self) -> str\n",
" | Set the extra representation of the module\n",
" | \n",
" | To print customized extra information, you should re-implement\n",
" | this method in your own modules. Both single-line and multi-line\n",
" | strings are acceptable.\n",
" | \n",
" | float(self: ~T) -> ~T\n",
" | Casts all floating point parameters and buffers to ``float`` datatype.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | get_buffer(self, target: str) -> 'Tensor'\n",
" | Returns the buffer given by ``target`` if it exists,\n",
" | otherwise throws an error.\n",
" | \n",
" | See the docstring for ``get_submodule`` for a more detailed\n",
" | explanation of this method's functionality as well as how to\n",
" | correctly specify ``target``.\n",
" | \n",
" | Args:\n",
" | target: The fully-qualified string name of the buffer\n",
" | to look for. (See ``get_submodule`` for how to specify a\n",
" | fully-qualified string.)\n",
" | \n",
" | Returns:\n",
" | torch.Tensor: The buffer referenced by ``target``\n",
" | \n",
" | Raises:\n",
" | AttributeError: If the target string references an invalid\n",
" | path or resolves to something that is not a\n",
" | buffer\n",
" | \n",
" | get_extra_state(self) -> Any\n",
" | Returns any extra state to include in the module's state_dict.\n",
" | Implement this and a corresponding :func:`set_extra_state` for your module\n",
" | if you need to store extra state. This function is called when building the\n",
" | module's `state_dict()`.\n",
" | \n",
" | Note that extra state should be picklable to ensure working serialization\n",
" | of the state_dict. We only provide provide backwards compatibility guarantees\n",
" | for serializing Tensors; other objects may break backwards compatibility if\n",
" | their serialized pickled form changes.\n",
" | \n",
" | Returns:\n",
" | object: Any extra state to store in the module's state_dict\n",
" | \n",
" | get_parameter(self, target: str) -> 'Parameter'\n",
" | Returns the parameter given by ``target`` if it exists,\n",
" | otherwise throws an error.\n",
" | \n",
" | See the docstring for ``get_submodule`` for a more detailed\n",
" | explanation of this method's functionality as well as how to\n",
" | correctly specify ``target``.\n",
" | \n",
" | Args:\n",
" | target: The fully-qualified string name of the Parameter\n",
" | to look for. (See ``get_submodule`` for how to specify a\n",
" | fully-qualified string.)\n",
" | \n",
" | Returns:\n",
" | torch.nn.Parameter: The Parameter referenced by ``target``\n",
" | \n",
" | Raises:\n",
" | AttributeError: If the target string references an invalid\n",
" | path or resolves to something that is not an\n",
" | ``nn.Parameter``\n",
" | \n",
" | get_submodule(self, target: str) -> 'Module'\n",
" | Returns the submodule given by ``target`` if it exists,\n",
" | otherwise throws an error.\n",
" | \n",
" | For example, let's say you have an ``nn.Module`` ``A`` that\n",
" | looks like this:\n",
" | \n",
" | .. code-block:: text\n",
" | \n",
" | A(\n",
" | (net_b): Module(\n",
" | (net_c): Module(\n",
" | (conv): Conv2d(16, 33, kernel_size=(3, 3), stride=(2, 2))\n",
" | )\n",
" | (linear): Linear(in_features=100, out_features=200, bias=True)\n",
" | )\n",
" | )\n",
" | \n",
" | (The diagram shows an ``nn.Module`` ``A``. ``A`` has a nested\n",
" | submodule ``net_b``, which itself has two submodules ``net_c``\n",
" | and ``linear``. ``net_c`` then has a submodule ``conv``.)\n",
" | \n",
" | To check whether or not we have the ``linear`` submodule, we\n",
" | would call ``get_submodule(\"net_b.linear\")``. To check whether\n",
" | we have the ``conv`` submodule, we would call\n",
" | ``get_submodule(\"net_b.net_c.conv\")``.\n",
" | \n",
" | The runtime of ``get_submodule`` is bounded by the degree\n",
" | of module nesting in ``target``. A query against\n",
" | ``named_modules`` achieves the same result, but it is O(N) in\n",
" | the number of transitive modules. So, for a simple check to see\n",
" | if some submodule exists, ``get_submodule`` should always be\n",
" | used.\n",
" | \n",
" | Args:\n",
" | target: The fully-qualified string name of the submodule\n",
" | to look for. (See above example for how to specify a\n",
" | fully-qualified string.)\n",
" | \n",
" | Returns:\n",
" | torch.nn.Module: The submodule referenced by ``target``\n",
" | \n",
" | Raises:\n",
" | AttributeError: If the target string references an invalid\n",
" | path or resolves to something that is not an\n",
" | ``nn.Module``\n",
" | \n",
" | half(self: ~T) -> ~T\n",
" | Casts all floating point parameters and buffers to ``half`` datatype.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | ipu(self: ~T, device: Union[int, torch.device, NoneType] = None) -> ~T\n",
" | Moves all model parameters and buffers to the IPU.\n",
" | \n",
" | This also makes associated parameters and buffers different objects. So\n",
" | it should be called before constructing optimizer if the module will\n",
" | live on IPU while being optimized.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Arguments:\n",
" | device (int, optional): if specified, all parameters will be\n",
" | copied to that device\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | load_state_dict(self, state_dict: Mapping[str, Any], strict: bool = True)\n",
" | Copies parameters and buffers from :attr:`state_dict` into\n",
" | this module and its descendants. If :attr:`strict` is ``True``, then\n",
" | the keys of :attr:`state_dict` must exactly match the keys returned\n",
" | by this module's :meth:`~torch.nn.Module.state_dict` function.\n",
" | \n",
" | Args:\n",
" | state_dict (dict): a dict containing parameters and\n",
" | persistent buffers.\n",
" | strict (bool, optional): whether to strictly enforce that the keys\n",
" | in :attr:`state_dict` match the keys returned by this module's\n",
" | :meth:`~torch.nn.Module.state_dict` function. Default: ``True``\n",
" | \n",
" | Returns:\n",
" | ``NamedTuple`` with ``missing_keys`` and ``unexpected_keys`` fields:\n",
" | * **missing_keys** is a list of str containing the missing keys\n",
" | * **unexpected_keys** is a list of str containing the unexpected keys\n",
" | \n",
" | Note:\n",
" | If a parameter or buffer is registered as ``None`` and its corresponding key\n",
" | exists in :attr:`state_dict`, :meth:`load_state_dict` will raise a\n",
" | ``RuntimeError``.\n",
" | \n",
" | modules(self) -> Iterator[ForwardRef('Module')]\n",
" | Returns an iterator over all modules in the network.\n",
" | \n",
" | Yields:\n",
" | Module: a module in the network\n",
" | \n",
" | Note:\n",
" | Duplicate modules are returned only once. In the following\n",
" | example, ``l`` will be returned only once.\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> l = nn.Linear(2, 2)\n",
" | >>> net = nn.Sequential(l, l)\n",
" | >>> for idx, m in enumerate(net.modules()):\n",
" | ... print(idx, '->', m)\n",
" | \n",
" | 0 -> Sequential(\n",
" | (0): Linear(in_features=2, out_features=2, bias=True)\n",
" | (1): Linear(in_features=2, out_features=2, bias=True)\n",
" | )\n",
" | 1 -> Linear(in_features=2, out_features=2, bias=True)\n",
" | \n",
" | named_buffers(self, prefix: str = '', recurse: bool = True, remove_duplicate: bool = True) -> Iterator[Tuple[str, torch.Tensor]]\n",
" | Returns an iterator over module buffers, yielding both the\n",
" | name of the buffer as well as the buffer itself.\n",
" | \n",
" | Args:\n",
" | prefix (str): prefix to prepend to all buffer names.\n",
" | recurse (bool, optional): if True, then yields buffers of this module\n",
" | and all submodules. Otherwise, yields only buffers that\n",
" | are direct members of this module. Defaults to True.\n",
" | remove_duplicate (bool, optional): whether to remove the duplicated buffers in the result. Defaults to True.\n",
" | \n",
" | Yields:\n",
" | (str, torch.Tensor): Tuple containing the name and buffer\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> for name, buf in self.named_buffers():\n",
" | >>> if name in ['running_var']:\n",
" | >>> print(buf.size())\n",
" | \n",
" | named_children(self) -> Iterator[Tuple[str, ForwardRef('Module')]]\n",
" | Returns an iterator over immediate children modules, yielding both\n",
" | the name of the module as well as the module itself.\n",
" | \n",
" | Yields:\n",
" | (str, Module): Tuple containing a name and child module\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> for name, module in model.named_children():\n",
" | >>> if name in ['conv4', 'conv5']:\n",
" | >>> print(module)\n",
" | \n",
" | named_modules(self, memo: Union[Set[ForwardRef('Module')], NoneType] = None, prefix: str = '', remove_duplicate: bool = True)\n",
" | Returns an iterator over all modules in the network, yielding\n",
" | both the name of the module as well as the module itself.\n",
" | \n",
" | Args:\n",
" | memo: a memo to store the set of modules already added to the result\n",
" | prefix: a prefix that will be added to the name of the module\n",
" | remove_duplicate: whether to remove the duplicated module instances in the result\n",
" | or not\n",
" | \n",
" | Yields:\n",
" | (str, Module): Tuple of name and module\n",
" | \n",
" | Note:\n",
" | Duplicate modules are returned only once. In the following\n",
" | example, ``l`` will be returned only once.\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> l = nn.Linear(2, 2)\n",
" | >>> net = nn.Sequential(l, l)\n",
" | >>> for idx, m in enumerate(net.named_modules()):\n",
" | ... print(idx, '->', m)\n",
" | \n",
" | 0 -> ('', Sequential(\n",
" | (0): Linear(in_features=2, out_features=2, bias=True)\n",
" | (1): Linear(in_features=2, out_features=2, bias=True)\n",
" | ))\n",
" | 1 -> ('0', Linear(in_features=2, out_features=2, bias=True))\n",
" | \n",
" | named_parameters(self, prefix: str = '', recurse: bool = True, remove_duplicate: bool = True) -> Iterator[Tuple[str, torch.nn.parameter.Parameter]]\n",
" | Returns an iterator over module parameters, yielding both the\n",
" | name of the parameter as well as the parameter itself.\n",
" | \n",
" | Args:\n",
" | prefix (str): prefix to prepend to all parameter names.\n",
" | recurse (bool): if True, then yields parameters of this module\n",
" | and all submodules. Otherwise, yields only parameters that\n",
" | are direct members of this module.\n",
" | remove_duplicate (bool, optional): whether to remove the duplicated\n",
" | parameters in the result. Defaults to True.\n",
" | \n",
" | Yields:\n",
" | (str, Parameter): Tuple containing the name and parameter\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> for name, param in self.named_parameters():\n",
" | >>> if name in ['bias']:\n",
" | >>> print(param.size())\n",
" | \n",
" | parameters(self, recurse: bool = True) -> Iterator[torch.nn.parameter.Parameter]\n",
" | Returns an iterator over module parameters.\n",
" | \n",
" | This is typically passed to an optimizer.\n",
" | \n",
" | Args:\n",
" | recurse (bool): if True, then yields parameters of this module\n",
" | and all submodules. Otherwise, yields only parameters that\n",
" | are direct members of this module.\n",
" | \n",
" | Yields:\n",
" | Parameter: module parameter\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> for param in model.parameters():\n",
" | >>> print(type(param), param.size())\n",
" | <class 'torch.Tensor'> (20L,)\n",
" | <class 'torch.Tensor'> (20L, 1L, 5L, 5L)\n",
" | \n",
" | register_backward_hook(self, hook: Callable[[ForwardRef('Module'), Union[Tuple[torch.Tensor, ...], torch.Tensor], Union[Tuple[torch.Tensor, ...], torch.Tensor]], Union[NoneType, Tuple[torch.Tensor, ...], torch.Tensor]]) -> torch.utils.hooks.RemovableHandle\n",
" | Registers a backward hook on the module.\n",
" | \n",
" | This function is deprecated in favor of :meth:`~torch.nn.Module.register_full_backward_hook` and\n",
" | the behavior of this function will change in future versions.\n",
" | \n",
" | Returns:\n",
" | :class:`torch.utils.hooks.RemovableHandle`:\n",
" | a handle that can be used to remove the added hook by calling\n",
" | ``handle.remove()``\n",
" | \n",
" | register_buffer(self, name: str, tensor: Union[torch.Tensor, NoneType], persistent: bool = True) -> None\n",
" | Adds a buffer to the module.\n",
" | \n",
" | This is typically used to register a buffer that should not to be\n",
" | considered a model parameter. For example, BatchNorm's ``running_mean``\n",
" | is not a parameter, but is part of the module's state. Buffers, by\n",
" | default, are persistent and will be saved alongside parameters. This\n",
" | behavior can be changed by setting :attr:`persistent` to ``False``. The\n",
" | only difference between a persistent buffer and a non-persistent buffer\n",
" | is that the latter will not be a part of this module's\n",
" | :attr:`state_dict`.\n",
" | \n",
" | Buffers can be accessed as attributes using given names.\n",
" | \n",
" | Args:\n",
" | name (str): name of the buffer. The buffer can be accessed\n",
" | from this module using the given name\n",
" | tensor (Tensor or None): buffer to be registered. If ``None``, then operations\n",
" | that run on buffers, such as :attr:`cuda`, are ignored. If ``None``,\n",
" | the buffer is **not** included in the module's :attr:`state_dict`.\n",
" | persistent (bool): whether the buffer is part of this module's\n",
" | :attr:`state_dict`.\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> self.register_buffer('running_mean', torch.zeros(num_features))\n",
" | \n",
" | register_forward_hook(self, hook: Union[Callable[[~T, Tuple[Any, ...], Any], Union[Any, NoneType]], Callable[[~T, Tuple[Any, ...], Dict[str, Any], Any], Union[Any, NoneType]]], *, prepend: bool = False, with_kwargs: bool = False) -> torch.utils.hooks.RemovableHandle\n",
" | Registers a forward hook on the module.\n",
" | \n",
" | The hook will be called every time after :func:`forward` has computed an output.\n",
" | \n",
" | If ``with_kwargs`` is ``False`` or not specified, the input contains only\n",
" | the positional arguments given to the module. Keyword arguments won't be\n",
" | passed to the hooks and only to the ``forward``. The hook can modify the\n",
" | output. It can modify the input inplace but it will not have effect on\n",
" | forward since this is called after :func:`forward` is called. The hook\n",
" | should have the following signature::\n",
" | \n",
" | hook(module, args, output) -> None or modified output\n",
" | \n",
" | If ``with_kwargs`` is ``True``, the forward hook will be passed the\n",
" | ``kwargs`` given to the forward function and be expected to return the\n",
" | output possibly modified. The hook should have the following signature::\n",
" | \n",
" | hook(module, args, kwargs, output) -> None or modified output\n",
" | \n",
" | Args:\n",
" | hook (Callable): The user defined hook to be registered.\n",
" | prepend (bool): If ``True``, the provided ``hook`` will be fired\n",
" | before all existing ``forward`` hooks on this\n",
" | :class:`torch.nn.modules.Module`. Otherwise, the provided\n",
" | ``hook`` will be fired after all existing ``forward`` hooks on\n",
" | this :class:`torch.nn.modules.Module`. Note that global\n",
" | ``forward`` hooks registered with\n",
" | :func:`register_module_forward_hook` will fire before all hooks\n",
" | registered by this method.\n",
" | Default: ``False``\n",
" | with_kwargs (bool): If ``True``, the ``hook`` will be passed the\n",
" | kwargs given to the forward function.\n",
" | Default: ``False``\n",
" | \n",
" | Returns:\n",
" | :class:`torch.utils.hooks.RemovableHandle`:\n",
" | a handle that can be used to remove the added hook by calling\n",
" | ``handle.remove()``\n",
" | \n",
" | register_forward_pre_hook(self, hook: Union[Callable[[~T, Tuple[Any, ...]], Union[Any, NoneType]], Callable[[~T, Tuple[Any, ...], Dict[str, Any]], Union[Tuple[Any, Dict[str, Any]], NoneType]]], *, prepend: bool = False, with_kwargs: bool = False) -> torch.utils.hooks.RemovableHandle\n",
" | Registers a forward pre-hook on the module.\n",
" | \n",
" | The hook will be called every time before :func:`forward` is invoked.\n",
" | \n",
" | \n",
" | If ``with_kwargs`` is false or not specified, the input contains only\n",
" | the positional arguments given to the module. Keyword arguments won't be\n",
" | passed to the hooks and only to the ``forward``. The hook can modify the\n",
" | input. User can either return a tuple or a single modified value in the\n",
" | hook. We will wrap the value into a tuple if a single value is returned\n",
" | (unless that value is already a tuple). The hook should have the\n",
" | following signature::\n",
" | \n",
" | hook(module, args) -> None or modified input\n",
" | \n",
" | If ``with_kwargs`` is true, the forward pre-hook will be passed the\n",
" | kwargs given to the forward function. And if the hook modifies the\n",
" | input, both the args and kwargs should be returned. The hook should have\n",
" | the following signature::\n",
" | \n",
" | hook(module, args, kwargs) -> None or a tuple of modified input and kwargs\n",
" | \n",
" | Args:\n",
" | hook (Callable): The user defined hook to be registered.\n",
" | prepend (bool): If true, the provided ``hook`` will be fired before\n",
" | all existing ``forward_pre`` hooks on this\n",
" | :class:`torch.nn.modules.Module`. Otherwise, the provided\n",
" | ``hook`` will be fired after all existing ``forward_pre`` hooks\n",
" | on this :class:`torch.nn.modules.Module`. Note that global\n",
" | ``forward_pre`` hooks registered with\n",
" | :func:`register_module_forward_pre_hook` will fire before all\n",
" | hooks registered by this method.\n",
" | Default: ``False``\n",
" | with_kwargs (bool): If true, the ``hook`` will be passed the kwargs\n",
" | given to the forward function.\n",
" | Default: ``False``\n",
" | \n",
" | Returns:\n",
" | :class:`torch.utils.hooks.RemovableHandle`:\n",
" | a handle that can be used to remove the added hook by calling\n",
" | ``handle.remove()``\n",
" | \n",
" | register_full_backward_hook(self, hook: Callable[[ForwardRef('Module'), Union[Tuple[torch.Tensor, ...], torch.Tensor], Union[Tuple[torch.Tensor, ...], torch.Tensor]], Union[NoneType, Tuple[torch.Tensor, ...], torch.Tensor]], prepend: bool = False) -> torch.utils.hooks.RemovableHandle\n",
" | Registers a backward hook on the module.\n",
" | \n",
" | The hook will be called every time the gradients with respect to a module\n",
" | are computed, i.e. the hook will execute if and only if the gradients with\n",
" | respect to module outputs are computed. The hook should have the following\n",
" | signature::\n",
" | \n",
" | hook(module, grad_input, grad_output) -> tuple(Tensor) or None\n",
" | \n",
" | The :attr:`grad_input` and :attr:`grad_output` are tuples that contain the gradients\n",
" | with respect to the inputs and outputs respectively. The hook should\n",
" | not modify its arguments, but it can optionally return a new gradient with\n",
" | respect to the input that will be used in place of :attr:`grad_input` in\n",
" | subsequent computations. :attr:`grad_input` will only correspond to the inputs given\n",
" | as positional arguments and all kwarg arguments are ignored. Entries\n",
" | in :attr:`grad_input` and :attr:`grad_output` will be ``None`` for all non-Tensor\n",
" | arguments.\n",
" | \n",
" | For technical reasons, when this hook is applied to a Module, its forward function will\n",
" | receive a view of each Tensor passed to the Module. Similarly the caller will receive a view\n",
" | of each Tensor returned by the Module's forward function.\n",
" | \n",
" | .. warning ::\n",
" | Modifying inputs or outputs inplace is not allowed when using backward hooks and\n",
" | will raise an error.\n",
" | \n",
" | Args:\n",
" | hook (Callable): The user-defined hook to be registered.\n",
" | prepend (bool): If true, the provided ``hook`` will be fired before\n",
" | all existing ``backward`` hooks on this\n",
" | :class:`torch.nn.modules.Module`. Otherwise, the provided\n",
" | ``hook`` will be fired after all existing ``backward`` hooks on\n",
" | this :class:`torch.nn.modules.Module`. Note that global\n",
" | ``backward`` hooks registered with\n",
" | :func:`register_module_full_backward_hook` will fire before\n",
" | all hooks registered by this method.\n",
" | \n",
" | Returns:\n",
" | :class:`torch.utils.hooks.RemovableHandle`:\n",
" | a handle that can be used to remove the added hook by calling\n",
" | ``handle.remove()``\n",
" | \n",
" | register_full_backward_pre_hook(self, hook: Callable[[ForwardRef('Module'), Union[Tuple[torch.Tensor, ...], torch.Tensor]], Union[NoneType, Tuple[torch.Tensor, ...], torch.Tensor]], prepend: bool = False) -> torch.utils.hooks.RemovableHandle\n",
" | Registers a backward pre-hook on the module.\n",
" | \n",
" | The hook will be called every time the gradients for the module are computed.\n",
" | The hook should have the following signature::\n",
" | \n",
" | hook(module, grad_output) -> Tensor or None\n",
" | \n",
" | The :attr:`grad_output` is a tuple. The hook should\n",
" | not modify its arguments, but it can optionally return a new gradient with\n",
" | respect to the output that will be used in place of :attr:`grad_output` in\n",
" | subsequent computations. Entries in :attr:`grad_output` will be ``None`` for\n",
" | all non-Tensor arguments.\n",
" | \n",
" | For technical reasons, when this hook is applied to a Module, its forward function will\n",
" | receive a view of each Tensor passed to the Module. Similarly the caller will receive a view\n",
" | of each Tensor returned by the Module's forward function.\n",
" | \n",
" | .. warning ::\n",
" | Modifying inputs inplace is not allowed when using backward hooks and\n",
" | will raise an error.\n",
" | \n",
" | Args:\n",
" | hook (Callable): The user-defined hook to be registered.\n",
" | prepend (bool): If true, the provided ``hook`` will be fired before\n",
" | all existing ``backward_pre`` hooks on this\n",
" | :class:`torch.nn.modules.Module`. Otherwise, the provided\n",
" | ``hook`` will be fired after all existing ``backward_pre`` hooks\n",
" | on this :class:`torch.nn.modules.Module`. Note that global\n",
" | ``backward_pre`` hooks registered with\n",
" | :func:`register_module_full_backward_pre_hook` will fire before\n",
" | all hooks registered by this method.\n",
" | \n",
" | Returns:\n",
" | :class:`torch.utils.hooks.RemovableHandle`:\n",
" | a handle that can be used to remove the added hook by calling\n",
" | ``handle.remove()``\n",
" | \n",
" | register_load_state_dict_post_hook(self, hook)\n",
" | Registers a post hook to be run after module's ``load_state_dict``\n",
" | is called.\n",
" | \n",
" | It should have the following signature::\n",
" | hook(module, incompatible_keys) -> None\n",
" | \n",
" | The ``module`` argument is the current module that this hook is registered\n",
" | on, and the ``incompatible_keys`` argument is a ``NamedTuple`` consisting\n",
" | of attributes ``missing_keys`` and ``unexpected_keys``. ``missing_keys``\n",
" | is a ``list`` of ``str`` containing the missing keys and\n",
" | ``unexpected_keys`` is a ``list`` of ``str`` containing the unexpected keys.\n",
" | \n",
" | The given incompatible_keys can be modified inplace if needed.\n",
" | \n",
" | Note that the checks performed when calling :func:`load_state_dict` with\n",
" | ``strict=True`` are affected by modifications the hook makes to\n",
" | ``missing_keys`` or ``unexpected_keys``, as expected. Additions to either\n",
" | set of keys will result in an error being thrown when ``strict=True``, and\n",
" | clearing out both missing and unexpected keys will avoid an error.\n",
" | \n",
" | Returns:\n",
" | :class:`torch.utils.hooks.RemovableHandle`:\n",
" | a handle that can be used to remove the added hook by calling\n",
" | ``handle.remove()``\n",
" | \n",
" | register_module(self, name: str, module: Union[ForwardRef('Module'), NoneType]) -> None\n",
" | Alias for :func:`add_module`.\n",
" | \n",
" | register_parameter(self, name: str, param: Union[torch.nn.parameter.Parameter, NoneType]) -> None\n",
" | Adds a parameter to the module.\n",
" | \n",
" | The parameter can be accessed as an attribute using given name.\n",
" | \n",
" | Args:\n",
" | name (str): name of the parameter. The parameter can be accessed\n",
" | from this module using the given name\n",
" | param (Parameter or None): parameter to be added to the module. If\n",
" | ``None``, then operations that run on parameters, such as :attr:`cuda`,\n",
" | are ignored. If ``None``, the parameter is **not** included in the\n",
" | module's :attr:`state_dict`.\n",
" | \n",
" | register_state_dict_pre_hook(self, hook)\n",
" | These hooks will be called with arguments: ``self``, ``prefix``,\n",
" | and ``keep_vars`` before calling ``state_dict`` on ``self``. The registered\n",
" | hooks can be used to perform pre-processing before the ``state_dict``\n",
" | call is made.\n",
" | \n",
" | requires_grad_(self: ~T, requires_grad: bool = True) -> ~T\n",
" | Change if autograd should record operations on parameters in this\n",
" | module.\n",
" | \n",
" | This method sets the parameters' :attr:`requires_grad` attributes\n",
" | in-place.\n",
" | \n",
" | This method is helpful for freezing part of the module for finetuning\n",
" | or training parts of a model individually (e.g., GAN training).\n",
" | \n",
" | See :ref:`locally-disable-grad-doc` for a comparison between\n",
" | `.requires_grad_()` and several similar mechanisms that may be confused with it.\n",
" | \n",
" | Args:\n",
" | requires_grad (bool): whether autograd should record operations on\n",
" | parameters in this module. Default: ``True``.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | set_extra_state(self, state: Any)\n",
" | This function is called from :func:`load_state_dict` to handle any extra state\n",
" | found within the `state_dict`. Implement this function and a corresponding\n",
" | :func:`get_extra_state` for your module if you need to store extra state within its\n",
" | `state_dict`.\n",
" | \n",
" | Args:\n",
" | state (dict): Extra state from the `state_dict`\n",
" | \n",
" | share_memory(self: ~T) -> ~T\n",
" | See :meth:`torch.Tensor.share_memory_`\n",
" | \n",
" | state_dict(self, *args, destination=None, prefix='', keep_vars=False)\n",
" | Returns a dictionary containing references to the whole state of the module.\n",
" | \n",
" | Both parameters and persistent buffers (e.g. running averages) are\n",
" | included. Keys are corresponding parameter and buffer names.\n",
" | Parameters and buffers set to ``None`` are not included.\n",
" | \n",
" | .. note::\n",
" | The returned object is a shallow copy. It contains references\n",
" | to the module's parameters and buffers.\n",
" | \n",
" | .. warning::\n",
" | Currently ``state_dict()`` also accepts positional arguments for\n",
" | ``destination``, ``prefix`` and ``keep_vars`` in order. However,\n",
" | this is being deprecated and keyword arguments will be enforced in\n",
" | future releases.\n",
" | \n",
" | .. warning::\n",
" | Please avoid the use of argument ``destination`` as it is not\n",
" | designed for end-users.\n",
" | \n",
" | Args:\n",
" | destination (dict, optional): If provided, the state of module will\n",
" | be updated into the dict and the same object is returned.\n",
" | Otherwise, an ``OrderedDict`` will be created and returned.\n",
" | Default: ``None``.\n",
" | prefix (str, optional): a prefix added to parameter and buffer\n",
" | names to compose the keys in state_dict. Default: ``''``.\n",
" | keep_vars (bool, optional): by default the :class:`~torch.Tensor` s\n",
" | returned in the state dict are detached from autograd. If it's\n",
" | set to ``True``, detaching will not be performed.\n",
" | Default: ``False``.\n",
" | \n",
" | Returns:\n",
" | dict:\n",
" | a dictionary containing a whole state of the module\n",
" | \n",
" | Example::\n",
" | \n",
" | >>> # xdoctest: +SKIP(\"undefined vars\")\n",
" | >>> module.state_dict().keys()\n",
" | ['bias', 'weight']\n",
" | \n",
" | to(self, *args, **kwargs)\n",
" | Moves and/or casts the parameters and buffers.\n",
" | \n",
" | This can be called as\n",
" | \n",
" | .. function:: to(device=None, dtype=None, non_blocking=False)\n",
" | :noindex:\n",
" | \n",
" | .. function:: to(dtype, non_blocking=False)\n",
" | :noindex:\n",
" | \n",
" | .. function:: to(tensor, non_blocking=False)\n",
" | :noindex:\n",
" | \n",
" | .. function:: to(memory_format=torch.channels_last)\n",
" | :noindex:\n",
" | \n",
" | Its signature is similar to :meth:`torch.Tensor.to`, but only accepts\n",
" | floating point or complex :attr:`dtype`\\ s. In addition, this method will\n",
" | only cast the floating point or complex parameters and buffers to :attr:`dtype`\n",
" | (if given). The integral parameters and buffers will be moved\n",
" | :attr:`device`, if that is given, but with dtypes unchanged. When\n",
" | :attr:`non_blocking` is set, it tries to convert/move asynchronously\n",
" | with respect to the host if possible, e.g., moving CPU Tensors with\n",
" | pinned memory to CUDA devices.\n",
" | \n",
" | See below for examples.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Args:\n",
" | device (:class:`torch.device`): the desired device of the parameters\n",
" | and buffers in this module\n",
" | dtype (:class:`torch.dtype`): the desired floating point or complex dtype of\n",
" | the parameters and buffers in this module\n",
" | tensor (torch.Tensor): Tensor whose dtype and device are the desired\n",
" | dtype and device for all parameters and buffers in this module\n",
" | memory_format (:class:`torch.memory_format`): the desired memory\n",
" | format for 4D parameters and buffers in this module (keyword\n",
" | only argument)\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | Examples::\n",
" | \n",
" | >>> # xdoctest: +IGNORE_WANT(\"non-deterministic\")\n",
" | >>> linear = nn.Linear(2, 2)\n",
" | >>> linear.weight\n",
" | Parameter containing:\n",
" | tensor([[ 0.1913, -0.3420],\n",
" | [-0.5113, -0.2325]])\n",
" | >>> linear.to(torch.double)\n",
" | Linear(in_features=2, out_features=2, bias=True)\n",
" | >>> linear.weight\n",
" | Parameter containing:\n",
" | tensor([[ 0.1913, -0.3420],\n",
" | [-0.5113, -0.2325]], dtype=torch.float64)\n",
" | >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA1)\n",
" | >>> gpu1 = torch.device(\"cuda:1\")\n",
" | >>> linear.to(gpu1, dtype=torch.half, non_blocking=True)\n",
" | Linear(in_features=2, out_features=2, bias=True)\n",
" | >>> linear.weight\n",
" | Parameter containing:\n",
" | tensor([[ 0.1914, -0.3420],\n",
" | [-0.5112, -0.2324]], dtype=torch.float16, device='cuda:1')\n",
" | >>> cpu = torch.device(\"cpu\")\n",
" | >>> linear.to(cpu)\n",
" | Linear(in_features=2, out_features=2, bias=True)\n",
" | >>> linear.weight\n",
" | Parameter containing:\n",
" | tensor([[ 0.1914, -0.3420],\n",
" | [-0.5112, -0.2324]], dtype=torch.float16)\n",
" | \n",
" | >>> linear = nn.Linear(2, 2, bias=None).to(torch.cdouble)\n",
" | >>> linear.weight\n",
" | Parameter containing:\n",
" | tensor([[ 0.3741+0.j, 0.2382+0.j],\n",
" | [ 0.5593+0.j, -0.4443+0.j]], dtype=torch.complex128)\n",
" | >>> linear(torch.ones(3, 2, dtype=torch.cdouble))\n",
" | tensor([[0.6122+0.j, 0.1150+0.j],\n",
" | [0.6122+0.j, 0.1150+0.j],\n",
" | [0.6122+0.j, 0.1150+0.j]], dtype=torch.complex128)\n",
" | \n",
" | to_empty(self: ~T, *, device: Union[str, torch.device]) -> ~T\n",
" | Moves the parameters and buffers to the specified device without copying storage.\n",
" | \n",
" | Args:\n",
" | device (:class:`torch.device`): The desired device of the parameters\n",
" | and buffers in this module.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | train(self: ~T, mode: bool = True) -> ~T\n",
" | Sets the module in training mode.\n",
" | \n",
" | This has any effect only on certain modules. See documentations of\n",
" | particular modules for details of their behaviors in training/evaluation\n",
" | mode, if they are affected, e.g. :class:`Dropout`, :class:`BatchNorm`,\n",
" | etc.\n",
" | \n",
" | Args:\n",
" | mode (bool): whether to set training mode (``True``) or evaluation\n",
" | mode (``False``). Default: ``True``.\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | type(self: ~T, dst_type: Union[torch.dtype, str]) -> ~T\n",
" | Casts all parameters and buffers to :attr:`dst_type`.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Args:\n",
" | dst_type (type or string): the desired type\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | xpu(self: ~T, device: Union[int, torch.device, NoneType] = None) -> ~T\n",
" | Moves all model parameters and buffers to the XPU.\n",
" | \n",
" | This also makes associated parameters and buffers different objects. So\n",
" | it should be called before constructing optimizer if the module will\n",
" | live on XPU while being optimized.\n",
" | \n",
" | .. note::\n",
" | This method modifies the module in-place.\n",
" | \n",
" | Arguments:\n",
" | device (int, optional): if specified, all parameters will be\n",
" | copied to that device\n",
" | \n",
" | Returns:\n",
" | Module: self\n",
" | \n",
" | zero_grad(self, set_to_none: bool = True) -> None\n",
" | Sets gradients of all model parameters to zero. See similar function\n",
" | under :class:`torch.optim.Optimizer` for more context.\n",
" | \n",
" | Args:\n",
" | set_to_none (bool): instead of setting to zero, set the grads to None.\n",
" | See :meth:`torch.optim.Optimizer.zero_grad` for details.\n",
" | \n",
" | ----------------------------------------------------------------------\n",
" | Data descriptors inherited from torch.nn.modules.module.Module:\n",
" | \n",
" | __dict__\n",
" | dictionary for instance variables (if defined)\n",
" | \n",
" | __weakref__\n",
" | list of weak references to the object (if defined)\n",
" | \n",
" | ----------------------------------------------------------------------\n",
" | Data and other attributes inherited from torch.nn.modules.module.Module:\n",
" | \n",
" | T_destination = ~T_destination\n",
" | \n",
" | __annotations__ = {'__call__': typing.Callable[..., typing.Any], '_bac...\n",
" | \n",
" | call_super_init = False\n",
" | \n",
" | dump_patches = False\n",
"\n"
]
}
],
"source": [
"help(vocab)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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}
],
"source": [
"def look_ahead_iterator(gen):\n",
" prev = None\n",
" for item in gen:\n",
" if prev is not None:\n",
" yield (prev, item)\n",
" prev = item\n",
"\n",
"class Bigrams(IterableDataset):\n",
" def __init__(self, text_file, vocabulary_size):\n",
" self.vocab = build_vocab_from_iterator(\n",
" get_word_lines_from_file(text_file),\n",
" max_tokens = vocabulary_size,\n",
" specials = ['<unk>'])\n",
" self.vocab.set_default_index(self.vocab['<unk>'])\n",
" self.vocabulary_size = vocabulary_size\n",
" self.text_file = text_file\n",
"\n",
" def __iter__(self):\n",
" return look_ahead_iterator(\n",
" (self.vocab[t] for t in itertools.chain.from_iterable(get_word_lines_from_file(self.text_file))))\n",
"\n",
"train_dataset = Bigrams(train_file, vocab_size)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<__main__.Bigrams object at 0x7fdd26d23940>\n"
]
}
],
"source": [
"print(train_dataset)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"'|===========================================================================|\\n| PyTorch CUDA memory summary, device ID 0 |\\n|---------------------------------------------------------------------------|\\n| CUDA OOMs: 1 | cudaMalloc retries: 1 |\\n|===========================================================================|\\n| Metric | Cur Usage | Peak Usage | Tot Alloc | Tot Freed |\\n|---------------------------------------------------------------------------|\\n| Allocated memory | 699613 KiB | 1903 MiB | 3735 MiB | 3052 MiB |\\n| from large pool | 699414 KiB | 1903 MiB | 3734 MiB | 3051 MiB |\\n| from small pool | 199 KiB | 1 MiB | 1 MiB | 1 MiB |\\n|---------------------------------------------------------------------------|\\n| Active memory | 699613 KiB | 1903 MiB | 3735 MiB | 3052 MiB |\\n| from large pool | 699414 KiB | 1903 MiB | 3734 MiB | 3051 MiB |\\n| from small pool | 199 KiB | 1 MiB | 1 MiB | 1 MiB |\\n|---------------------------------------------------------------------------|\\n| Requested memory | 699611 KiB | 1903 MiB | 3735 MiB | 3052 MiB |\\n| from large pool | 699413 KiB | 1903 MiB | 3734 MiB | 3051 MiB |\\n| from small pool | 197 KiB | 1 MiB | 1 MiB | 1 MiB |\\n|---------------------------------------------------------------------------|\\n| GPU reserved memory | 710656 KiB | 1918 MiB | 1918 MiB | 1224 MiB |\\n| from large pool | 708608 KiB | 1916 MiB | 1916 MiB | 1224 MiB |\\n| from small pool | 2048 KiB | 2 MiB | 2 MiB | 0 MiB |\\n|---------------------------------------------------------------------------|\\n| Non-releasable memory | 11043 KiB | 19364 KiB | 28939 KiB | 17896 KiB |\\n| from large pool | 9194 KiB | 17514 KiB | 25954 KiB | 16760 KiB |\\n| from small pool | 1849 KiB | 1950 KiB | 2985 KiB | 1136 KiB |\\n|---------------------------------------------------------------------------|\\n| Allocations | 10 | 17 | 38 | 28 |\\n| from large pool | 5 | 7 | 10 | 5 |\\n| from small pool | 5 | 11 | 28 | 23 |\\n|---------------------------------------------------------------------------|\\n| Active allocs | 10 | 17 | 38 | 28 |\\n| from large pool | 5 | 7 | 10 | 5 |\\n| from small pool | 5 | 11 | 28 | 23 |\\n|---------------------------------------------------------------------------|\\n| GPU reserved segments | 5 | 7 | 7 | 2 |\\n| from large pool | 4 | 6 | 6 | 2 |\\n| from small pool | 1 | 1 | 1 | 0 |\\n|---------------------------------------------------------------------------|\\n| Non-releasable allocs | 6 | 8 | 20 | 14 |\\n| from large pool | 4 | 6 | 9 | 5 |\\n| from small pool | 2 | 3 | 11 | 9 |\\n|---------------------------------------------------------------------------|\\n| Oversize allocations | 0 | 0 | 0 | 0 |\\n|---------------------------------------------------------------------------|\\n| Oversize GPU segments | 0 | 0 | 0 | 0 |\\n|===========================================================================|\\n'"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"torch.cuda.memory_summary(device=None, abbreviated=False)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"os.environ[\"PYTORCH_CUDA_ALLOC_CONF\"] = \"max_split_size_mb:256\""
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"device = 'cuda'\n",
"model = SimpleBigramNeuralLanguageModel(vocab_size, embed_size).to(device)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"epoch: = 1\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/gedin/.local/lib/python3.8/site-packages/torch/nn/modules/container.py:217: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
" input = module(input)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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},
{
"name": "stdout",
"output_type": "stream",
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},
{
"name": "stdout",
"output_type": "stream",
"text": [
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},
{
"name": "stdout",
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]
},
{
"name": "stdout",
"output_type": "stream",
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]
}
],
"source": [
"data = DataLoader(train_dataset, batch_size=batch_s)\n",
"optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)\n",
"criterion = torch.nn.NLLLoss()\n",
"torch.cuda.empty_cache()\n",
"gc.collect()\n",
"\n",
"model.load_state_dict(torch.load('model-bigram_final.bin'))\n",
"for i in range(1, epochs+1):\n",
" print('epoch: =', i)\n",
" model.train()\n",
" step = 0\n",
" for x, y in data: # prev, predicting, following words\n",
" x = x.to(device)\n",
" y = y.to(device)\n",
" optimizer.zero_grad()\n",
" ypredicted = model(x) #previous, following word\n",
" loss = criterion(torch.log(ypredicted), y)\n",
" if step % 100 == 0:\n",
" print(step, loss)\n",
" step += 1\n",
" loss.backward()\n",
" optimizer.step()\n",
" torch.save(model.state_dict(), f'model-bigram_2nd-run{i}.bin') \n",
"torch.save(model.state_dict(), f'model-bigram_final.bin') "
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[('be', 11, 0.2570849657058716),\n",
" ('<unk>', 0, 0.07411641627550125),\n",
" ('not', 22, 0.05940083786845207),\n",
" ('have', 28, 0.02751326560974121),\n",
" ('bo', 167, 0.014936885796487331),\n",
" ('make', 116, 0.013943656347692013),\n",
" ('give', 193, 0.011286991648375988),\n",
" ('take', 153, 0.011171611957252026),\n",
" ('do', 86, 0.010088067501783371),\n",
" ('he', 20, 0.009703895077109337)]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"device = 'cuda'\n",
"torch.cuda.empty_cache()\n",
"model = SimpleBigramNeuralLanguageModel(vocab_size, embed_size).to(device)\n",
"model.load_state_dict(torch.load(f'model-bigram_final.bin'))\n",
"model.eval()\n",
"\n",
"ixs = torch.tensor(vocab.forward(['will'])).to(device)\n",
"\n",
"out = model(ixs)\n",
"top = torch.topk(out[0], 10)\n",
"top_indices = top.indices.tolist()\n",
"top_probs = top.values.tolist()\n",
"top_words = vocab.lookup_tokens(top_indices)\n",
"list(zip(top_words, top_indices, top_probs))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[('<unk>', 0, 0.19996878504753113),\n",
" ('and', 3, 0.05288130044937134),\n",
" ('of', 2, 0.042051784694194794),\n",
" ('the', 1, 0.026572922244668007),\n",
" ('to', 4, 0.022689413279294968),\n",
" ('in', 6, 0.015904497355222702),\n",
" ('The', 17, 0.012827681377530098),\n",
" ('a', 5, 0.00961760152131319),\n",
" ('for', 8, 0.008938422426581383),\n",
" ('</s>', 32, 0.00840282253921032)]"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vocab = train_dataset.vocab\n",
"ixs = torch.tensor(vocab.forward(['cerned.'])).to(device)\n",
"\n",
"out = model(ixs)\n",
"top = torch.topk(out[0], 10)\n",
"top_indices = top.indices.tolist()\n",
"top_probs = top.values.tolist()\n",
"top_words = vocab.lookup_tokens(top_indices)\n",
"list(zip(top_words, top_indices, top_probs))"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[('<unk>', 0, 1.0),\n",
" ('particular,', 14538, 0.24527804553508759),\n",
" ('revolution.', 20446, 0.23776617646217346),\n",
" ('Territory.', 14189, 0.23417341709136963),\n",
" ('or-', 2261, 0.22888363897800446),\n",
" ('3', 479, 0.2288265973329544),\n",
" ('speak.', 13722, 0.2252315878868103),\n",
" ('attend.', 19397, 0.22110989689826965),\n",
" ('say,', 1455, 0.22106117010116577),\n",
" ('Lee.', 15326, 0.21764159202575684)]"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cos = nn.CosineSimilarity(dim=1, eps=1e-6)\n",
"\n",
"embeddings = model.model[0].weight\n",
"\n",
"vec = embeddings[vocab['cerned.']]\n",
"\n",
"similarities = cos(vec, embeddings)\n",
"\n",
"top = torch.topk(similarities, 10)\n",
"\n",
"top_indices = top.indices.tolist()\n",
"top_probs = top.values.tolist()\n",
"top_words = vocab.lookup_tokens(top_indices)\n",
"list(zip(top_words, top_indices, top_probs))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"\n",
"vocab = train_dataset.vocab\n",
"# ixs = torch.tensor(vocab.forward(['a'])).to(device)\n",
"ixs = torch.tensor(vocab.forward(['of'])).to(device)\n",
"# ixs = torch.tensor(vocab.forward(['that'])).to(device)\n",
"# ixs = torch.tensor(vocab.forward(['church'])).to(device)\n",
"# ixs = torch.tensor(vocab.forward(['wait'])).to(device)\n",
"\n",
"out = model(ixs)\n",
"top = torch.topk(out[0], 10)\n",
"top_indices = top.indices.tolist()\n",
"top_probs = top.values.tolist()\n",
"top_words = vocab.lookup_tokens(top_indices)\n",
"list(zip(top_words, top_indices, top_probs))"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"def get_values_from_model(presc_word, model, vocab, k):\n",
" ixs = torch.tensor(vocab.forward([presc_word])).to(device)\n",
" out = model(ixs)\n",
" top = torch.topk(out[0], k)\n",
" top_indices = top.indices.tolist()\n",
" top_probs = top.values.tolist()\n",
" top_words = vocab.lookup_tokens(top_indices)\n",
" return list(zip(top_words, top_probs))\n",
"\n",
"def gonito_format(dic):\n",
" tab = summarize_probs_unk(dic)\n",
" result = ''\n",
" for element in tab[:-1]:\n",
" result+=str(element[0])+':'+str(element[1])+'\\t'\n",
" result+=':'+ str(tab[-1][1])+'\\n'\n",
" return result\n",
"\n",
"def summarize_probs_unk(dic):\n",
" if '<unk>' in dic.keys():\n",
" del dic['<unk>']\n",
" probsum = sum(float(val) for key, val in dic.items())\n",
"# if \"<unk>\" in dic.keys():\n",
"# for key in dic:\n",
"# dic[key] = dic[key]/probsum #normalize to 1\n",
"# wildcard = dic['<unk>'] \n",
"# else: #no unk in first 10 entries\n",
" for key in dic:\n",
" dic[key] = dic[key]/probsum*(1-wildcard_minweight) ###leave some space for wildcard\n",
" wildcard = wildcard_minweight\n",
" tab = [(key, val) for key, val in dic.items()]\n",
" tab.append(('<unk>', wildcard))\n",
" return tab\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Present,\n",
"maintenance.\n",
"-\n",
"on\n",
"after.\n",
"included.\n",
"Delaware.\n",
"body.\n",
"route.\n",
"under\n",
"bership.\n",
"call*\n",
"waterscape.\n",
"?\n",
"soles.\n",
"simple.\"\n",
"public.\n",
"them.-\n",
"months.\n",
"icy.\"\n",
"E\n",
"level.\n",
"4t—36\n",
"financial\n",
"steady.\n",
"mlnicars.\n",
"his\n",
"circumstances.\n",
"corner.\n",
"science.\n",
"insurance.\"\n",
"fair.\n",
"scalded.\n",
"ria.\n",
"it,\n",
"mlngtonlan.\n",
"possession.\n",
"of\n",
"pray!”\n",
"occurred.\n",
"euro,\n",
"way.\n",
"185.\n",
"destruction.\n",
"conditions.\n",
"Hood.\n",
"s.\n",
"case.\n",
"Roy\n",
"country.\n",
"ccjulinalf\n",
"side.\n",
"against\n",
"servation.\n",
"Detroit.\n",
"North\n",
"country.\n",
"\"\n",
"bones.\n",
"sold.\n",
"Brown\n",
"bill.\n",
"Springer,\n",
"gaged.\n",
"their\n",
"character.\n",
"cu\n",
"former\n",
"cities.\n",
"accumulated\n",
"corporal.\n",
"^\n",
"-\n",
"o\n",
".<!.\n",
"them.\n",
"wounded.\n",
"by.\n",
"of\n",
"remedy.\n",
"debate.\n",
"22-28).\n",
"\"\n",
"book.\"\n",
"contract,\n",
"presentation.\n",
"Ellsha\n",
"praise.\n",
"opin-\n",
"proof.\n",
"lows:\n",
"come\n",
"dispensation.\n",
"point.\n",
"theirjfnmiliea.\n",
"ull.\n",
"Magazine.\n",
"rnUnil.\n",
"order.\n",
"morrow\n",
"nrL\n",
"is\n",
"'death.\n",
"caucus.\n",
"east\n",
"-\n",
"service.\n",
"cor-\n",
"ton\n",
"answer.\n",
"bay.\n",
"same.\n",
":\n",
"Arkansas.\n",
"lives.\n",
"the\n",
"t\n",
".1\n",
"P\n",
"lems?\n",
"4,\n",
"know,'\n",
"his\n",
"arouth.\"\n",
"offer.\n",
"horizontal!'.\n",
"two-thir-\n",
"city.\n",
"come\n",
"here.\n",
"STORY\n",
"auxiliaries.\n",
"property.\n",
"respected.\n",
"stopped.\n",
"JanlO\n",
"honesty.\n",
"civilian\n",
"servation.\n",
"army.\n",
"Harbaugh.\n",
"ear.\n",
"beginning.\n",
"State%\n",
"nA.a\n",
"operation.\n",
"cash.\n",
"upon.\n",
"drugs.\n",
"kind.\n",
"out.\n",
"f\n",
"st.\n",
"season.\n",
"WUK\n",
"over,\n",
"offriends.\n",
"Inger-\n",
"recovery,-\n",
"separately.\n",
"bachelor.\n",
"offer.\n",
"Colony.\n",
"and\n",
"wi\n",
"we\n",
"i\n",
"them.\n",
"rons\n",
"’<>(.\n",
"descendants\n",
"notes.\n",
"Courier.\n",
"town\n",
"E\n",
"awake,\n",
"d\n",
"circumstances.\n",
"board.\n",
"-\n",
"union.\n",
"the\n",
"en-\n",
"children\n",
"Tre--\n",
"date.\n",
"Monday.\n",
"been\n",
"now\n",
"slaughter.”\n",
"art.\n",
"shape.\n",
"ai\n",
"Magazine.\n",
"License.\n",
"K\n",
"P.iU--\n",
"failures\n",
"v\n",
"cause.\n",
"Russian\n",
"prayed.\n",
"tariff.\n",
"action.\n",
"direction.\n",
"Tacomans\n",
"to-\n",
"cellence.\n",
"power\n",
"25\n",
"alty.\n",
"July.\"\n",
"crime.\n",
"of\n",
"conviction.\n",
"been\n",
"d\n",
"unnatural\n",
"s,\n",
"-\n",
"scccdo.\n",
"e-\n",
"Harrisburg.\n",
"cash.\n",
"Peter\n",
"OTTirn\n",
"lor\n",
"MacAuley.\n",
"O\n",
"style.\n",
"road.\n",
"YOU.\n",
"nations.\"\n",
"r.o\n",
"made.\n",
"Democratic.\n",
"......\n",
"Ocean.\n",
"r\n",
"and\n",
"bless\n",
"jaSl\n",
"Krapt.\n",
"states.\n",
"It.\n",
"river.\n",
"fag-\n",
"ShorteU.\n",
"fabric.\"\n",
"returned.\n",
"tra.\n",
"member.\n",
"both.\n",
"I\n",
"place.\"\n",
"our\n",
".»\n",
"17\n",
"1911.\n",
"an\n",
"Age.\n",
"It\n",
"Gland--\n",
"tl\n",
"-\n",
"be-\n",
"air.\n",
"crude.\n",
"remedy.\n",
":\n",
"Uny\n",
"tunnel.\n",
"n\n",
"Gulf.”\n",
"war.\n",
"...\n",
"contest\n",
"History.\n",
"aear.\n",
"tees.\n",
"residence.\n",
"friend,\n",
"h\n",
"\"\n",
"him.\n",
"government.\n",
"facilities.\"\n",
"remedy.\n",
"r\n",
"eent\n",
"law.\n",
"the\n",
"Representative\n",
"w\n",
"n\n",
"1S44.\n",
"adopted.\n",
"favor.\n",
"Sciurier.\n",
"bein\n",
"market.\n",
".1\n",
"marshes.\n",
"Newark.\n",
"years\n",
"Preeton.\"\n",
"lti-\n",
"Trumpet\n",
"said.\n",
"appoint\n",
"oi\n",
"tbe\n",
"Federahi,\n",
"1858.\n",
"hereof.\n",
"treatment.\n",
"dawdling\n",
"dence.\n",
"L\n",
"requirements.\n",
"in\n",
"e\n",
"projects?\n",
"goes:\n",
"W\n",
"w\n",
"thereof.\n",
"It\n",
"injury.\"\n",
"water.\"\n",
"played\n",
"famoti'\n",
"nnd\n",
"there.'\n",
"win.\"\n",
"used.\n",
".by\n",
"'\n",
"Woman.\n",
"viz:\n",
"causing\n",
"quarter.\n",
"i.\n",
"police.\n",
"run.\n",
"children.'\n",
"debate.\n",
"Blannerhasset\n",
"pa-\n",
"with\n",
"elbow.\n",
"J\n",
"aid.\n",
"States.\n",
"graii\n",
"terday.\n",
"was\n",
"mlngo\n",
"night.\n",
"reason.\n",
"Thlinget.\n",
"111.\n",
"'\n",
"anarled.\n",
"personally.\n",
"man.\n",
"nonresidents\n",
"man.\n",
"sently.\n",
"st\n",
"time.\n",
"shrine.\n",
"communicable\n",
"anf\n",
"Th.-\n",
"lose\n",
"thereon.\n",
"application.\n",
"disappear.\n",
"forfeited.\n",
"collis-\n",
"sirl\n",
"(\n",
"reconstructed.\n",
"(ban.)\n",
"the\n",
"tion.\n",
"afte\n",
"co-urts.\"\n",
"18W2.\n",
"attuck.\n",
"too\n",
"void.\n",
"presented,\n",
"shallton.\n",
"pnst\n",
"here.\n",
"mentioned.\n",
"session.\n",
"b\n",
"s\n",
"river.\n",
"capac\n",
"firm.\n",
"bombardment,\n",
"other.\n",
"worship.\n",
"The\n",
"liberties.\n",
"respousihiliiics,\n",
"Times.\n",
"other.\n",
"following:\n",
"consid­\n",
"arroya.\n",
"owno-\n",
"is\n",
"14.\n",
"name.\n",
"night\n",
"adjourned.\n",
"morning.^\n",
"paint.\n",
"post-nat-\n",
"union.\n",
"or-\n",
"Jiuili\n",
"said.\n",
"splurge.\n",
"him.\n",
"work.\"\n",
"-te-\n",
"tfo\n",
"there\n",
".\n",
"rising.\n",
"Gen.\n",
"11\n",
"yours,\n",
"Farmer.\n",
"acquaintanceship,\n",
"hand.\n",
"high-cla-\n",
"nights.\n",
"AfcC-i-\n",
"elections.\n",
"way.\"\n",
"once.\n",
".\n",
"comfortable.\n",
"rality.\n",
".be-\n",
"approval,\n",
"sto-\n",
"cure.\n",
"27,000.\n",
"spoils.”\n",
"deeds.\n",
"now\n",
"1.\n",
"da\n",
"...11.11-\n",
"d\n",
"berry.\n",
"congratulations.\n",
"coast\n",
"Wednesday\n",
"ferences.\n",
"point.\"\n",
"preservation.\n",
"gowns.\n",
"curanhalted.\n",
"JBarmsT.\n",
"surroundings.\n",
"treat\n",
"ted.\n",
"tfrith\n",
"blossoms.\n",
"here.\"\n",
"Minnesota.\n",
"rope.\n",
"—\n",
"him:\n",
"*\n",
"is”\n",
"feet\n",
"music-\n",
"Newark.\n",
"given\n",
"country\n",
"sick.\n",
"black.\n",
"so.\n",
"archdiocese.\n",
"form.\"\n",
"k\n",
"propose.\n",
"ed.\n",
".\n",
"healthy.\n",
"cannons.\n",
"auxiliaries\n",
"by\n",
"to\n",
"shoute,\n",
"thel.-\n",
"\"Short\n",
"side.\n",
"Koine.\n",
"thanks.\n",
"le.\n",
"communicable.\n",
"[Sigued]\n",
"ion.\n",
"remedy.\n",
"Monthly.\n",
"enterprises.\"\n",
"nlieht**.i\n",
"harmed.\"\n",
"retreat.\n",
"what\n",
"d\n",
"over\n",
"wounded.\n",
"-\n",
".\n",
"mobiles.\"\n",
"mill.\n",
"college.\n",
"B.\n",
"Manassas.\n",
"fea-\n",
"fatigue.\n",
"\"Quartermaster\n",
"Williams.'\n",
"visible.\n",
"Cox,\n",
"bo\n",
"stitution.\n",
"said\n",
"c-\n",
"be\n",
"hat.\n",
"Sing.\n",
"penalty.\n",
"at\n",
"prison!\n",
"salt.\n",
"consider.\"\n",
"mo\n",
"TWENTY-EIGHT-\n",
"Hazen's\n",
"F\n",
"Pennsylvania\n",
"mand.\n",
"Class.”\n",
"years.\n",
"shore.\n",
"posterity.\n",
"1000.\n",
"tern-\n",
"meeting.\n",
"logical.\n",
"said:\n",
"stamps.\n",
"trol.\"\n",
"misdeeds.\n",
"Middletown.\n",
"nnd\n",
"law.\n",
"sure\n",
"recover.\n",
"e\n",
"move.\n",
"remedy.\n",
"days.\n",
"efficiency.\n",
"provement.\n",
"be\n",
"i\n",
"fall.\n",
"East\n",
"really\n",
"-\n",
"uever\n",
"leg-\n",
"deny\n",
"reason\n",
"ous\n",
"of\n",
"agencies.\n",
"eloped.\"\n",
"scale.\n",
"Colonel\n",
"company.\n",
"watera\n",
"|\n",
"enterprises,\n",
"to-day.\n",
"In\n",
"enuffforme.\n",
"justly\n",
"finitum.\"\n",
"negan.\n",
"OTTO\n",
"interests.\n",
"mo-\n",
"determined.\n",
"iasu\n",
"void.\n",
"nights\n",
"come.\"\n",
".\n",
"pild.\n",
"(\n",
"her\n",
"from\n",
"Russians.\n",
"things.\n",
"talk.\n",
"constituted,\n",
"lows:\n",
"dustry.\n",
"state.\n",
"sections.\n",
"cent..\n",
"cm'\n",
"mile*.\n",
"liberty,\n",
"judgment.\n",
"a-t\n",
"illusion.\n",
"With\n",
"States.\n",
"and\n",
"kind.\n",
"preference\n",
"lunch.\n",
"tary.\n",
"”\n",
"the\n",
"Democratic\n",
"»ball\n",
"ribbon.\n",
"and\n",
"of\n",
".\n",
"route.\n",
"prayed.\n",
"The\n",
"live.\n",
"train.\n",
"holi-\n",
"follow.\n",
"a\n",
"quail.”\n",
"uuu\n",
"oath.\n",
"Cohce.\n",
"',\n",
"record.\n",
"it.'\n",
"the\n",
"have\n",
"Kinley.\n",
"purchase.\n",
"violcuce.\n",
"gates-wor-e\n",
"placed\n",
"taste.\n",
"at-\n",
"servation.\n",
"\"\n",
"views.\n",
"one.\n",
"description.\n",
"lized\n",
"egress.\n",
"flames.\n",
"e\n",
"704c.\n",
"height.\n",
"office.\n",
"Pa.,\n",
"preserves\n",
"voice.\n",
"Ledger.\n",
"later.\n",
"eminent\n",
"powerfully.\"\n",
"d\n",
"g\n",
"Iremain\n",
"mi-\n",
"Constitu-\n",
"charges.\n",
"llnllrond\n",
"llWi\n",
"n,\n",
"wel-\n",
"eternity.\n",
"of\n",
"it.\n",
"on-\n",
"n-\n",
"sure.\"\n",
"n-\n",
"feform.\n",
"it.\n",
"man.\n",
"popularity.\n",
"PUGH.\n",
"dollars.\n",
"w-elfare.\n",
"motionless.\n",
"ago\n",
"call.\n",
"emergencies.\n",
"45.\n",
"again.\n",
"to\n",
"Smith,\n",
"a\n",
"h\n",
"Client\n",
"for.\n",
"gone.\n",
"thereof.\n",
"per-\n",
"herlivin?.\n",
"d\n",
"Th-\n",
"them,\n",
"nbllWiM\n",
"Measures,\n",
"dreary,\n",
"crime.\"\n",
"^ffsouJ.\n",
"obser-\n",
"home.\n",
"him.\n",
"bcr.\n",
"C.\n",
"were\n",
"purchaser.\n",
"the\n",
"tu-\n",
"policy.\n",
"Dalty!\"\n",
"enl-\n",
"win.\"\n",
"dissolution.\n",
"health.\n",
"exception.\n",
"16'h.\n",
"1859.\n",
"boat.\n",
"'\n",
"home.\n",
"eausees.\n",
"Congress.\"\n",
"few.\n",
"’'\n",
"cost:\n",
"demand.\n",
"them.\n",
"Vlr\n",
"at\n",
"Saint\n",
"which\n",
"all.\n",
"consider.\n",
"list.\n",
"on\n",
"menu.\n",
"V.rk.\n",
"onstrate.\n",
"nor\n",
"as\n",
"county.\"\n",
"Iowu,\n",
"grade.\n",
"organization.\n",
"Wyman.\n",
"Unsportsmanlike\n",
"pioneers.\n",
"spring.\n",
"appertaining.\n",
"porch.\n",
"James\n",
"we\n",
"\"\n",
"it.\n",
"hand.\"\n",
"farew-ell.\"\n",
"advantages.\n",
"all\n",
"-\n",
"secured\n",
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"water\n",
"igoV\n",
"State.\n",
"cattle\n",
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"-\n",
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",\n",
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"d\n",
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"determine.\n",
"him.\n",
"comic,\n",
"Inquiry.\n",
"girls,\n",
"rations.\n",
"living.\n",
"delinquents.\n",
"performed.\n",
"or\n",
"Mr,\n",
"plaint.\n",
"ters\n",
"e\n",
"constructed\n",
"slaughterinj\n",
"cent.\n",
"Commerce.\n",
"trated.\n",
"Tfrnoney.\n",
"factions.\n",
"rejected.\n",
"s\n",
"brave.\"\n",
"statute.\n",
"flight\n",
"kbrsf\n",
"future.\n",
":\n",
"oflloe.\n",
"’08.\"\n",
"dustries?\"\n",
"at\n",
"parly.\n",
"insured.\n",
"tluics.\n",
"court.\n",
"lows.”\n",
"woman.\n",
"7\n",
"complaint.\n",
"expected.\n",
"anthem\n",
"the\n",
"sundown.\n",
"same.\n",
".\n",
"yen.\"\n",
"copy.\n",
"strong.\n",
"Government,\n",
"nlng.\n",
"prloes,\n",
"Astoria.\n",
"?\n",
"They\n",
"Figaro.\n",
"buy-\n",
"it.\n",
"plane.\n",
"Nelson,\n",
"decision.\n",
"injunction,\n",
"peace.\n",
"wid\n",
"give\n",
"departments.\"\n",
"costs.\n",
"sufficient\n",
"DOCK\n",
"incurred.\n",
"out\n",
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"tho-\n",
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"trade.\n",
"-\n",
"Regis.\n",
"ages.\n",
"them.\n",
"Mcllvalne.\n",
"newspaper.\n",
"matter.\n",
"er\n",
"improved\n",
"be\n",
"pastures.\n",
"himself.\n",
".\n",
"shapes.\n",
"adopted,\n",
"and\n",
":\n",
"Robert\n",
"the\n",
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"lasttwelrty8®*'\n",
"Miss\n",
"~\n",
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"circumstances.\n",
"tomorrow's\n",
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"would.\n",
"Union.\n",
"street.\n",
"tru.--\n",
"n\n",
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"the\n",
"speed.\n",
"be\n",
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"obtained.\n",
"able.\n",
"ards.\"\n",
"situation.\n",
"accussed\n",
"sleep.\n",
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"support.\n",
"home.\n",
"else.\n",
"spread\n",
"ploying.\n",
"and\n",
"the\n",
"Coun-\n",
"shot-makin-\n",
"guarded.\n",
"an\n",
"Hoursfrom9a.M..to5e.m.\n",
"Lake\n",
"1\n",
"rip-rapping.\n",
"publication.\n",
"Stanton's\n",
"Invigorated.\n",
"rendered.\n",
"strike,\n",
"cnn-\n",
"instruction.\n",
"territory.\n",
"ly.\n",
"the\n",
"ascertained.\n",
"service.\n",
"unrelenting.\n",
"York.\n",
"to-\n",
"pursuits.\n",
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"ever\n",
"plates.\n",
"Meade.\n",
"superior\n",
"Dusinesa.\n",
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"derson.\n",
"like\n",
"Flag.\n",
"night.\n",
"hla\n",
"May.\n",
"r\n",
"Health.\n",
"*\n",
"term\n",
"provinces.\n",
"off.\n",
"transao-\n",
"ferine.\n",
"the\n",
"preserves\n",
"father\n",
"them.\n",
"hopeful.\n",
"\"\n",
"it.\n",
"jfciow.\n",
"stopped.\n",
"other,\n",
"sentiments.\n",
"action,\"\n",
"harlequinade.\n",
"water.\n",
"\"detective.\"\n",
"tutlon.\n",
"institutions.(12)\n",
"dreary.\n",
"was\n",
"say\n",
"maker.\n",
"nies.\n",
"vagabond.\n",
"here.\n",
"fault.\n",
"and\n",
"EU.\n",
";\n",
"fur.\n",
"agreement.\n",
"11,012\n",
"provide.\n",
"Sovereign.\n",
"life.\n",
"law.\n",
"immeiatly\n",
"ity.\n",
"law.\n",
"I\n",
"faction.\n",
"nificance.\n",
"mac\n",
"7p.m.\n",
"James\n",
"individuals.\n",
"sure.\n",
">n»v.\n",
"city.\n",
"brane.\n",
"relations.\n",
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"Press.\n",
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"colors.\n",
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"postponed.\n",
"and\n",
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"Vlmndcaler.\n",
"supervision.\n",
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"-\n",
"ceptance:\n",
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"Mass.\n",
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"of.\"\n",
"State.\n",
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"cir-\n",
"Itnddmus,\n",
"was\n",
"invited.\n",
"damageB.\n",
"study.\n",
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"the\n",
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"1\n",
"service.\n",
"damage.\n",
"zens.\n",
"Science.\n",
"superior.\n",
"directions.\n",
"known\n",
"unsuccessful.\n",
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"pay.\n",
"In\n",
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"Sun.\n",
"—,\n",
"statute.\n",
"each.\n",
"viciously.\n",
"Small's\n",
"Galveston\n",
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"two\n",
"passed.\n",
"cent.\n",
"death.\n",
"ex-\n",
"proof\n",
"low-c-\n",
"arbitration.\n",
"times.\n",
"deans.\n",
"directed.\n",
"saloon.\n",
"The-\n",
"me.\n",
"home.\n",
"men.\n",
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"plies.\n",
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"ones.\n",
"location.\n",
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"s\n",
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"1902,\n",
"whose\n",
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"outlaws.\n",
"roots.\n",
"work.\n",
"physicians.\n",
"however.\n",
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"teachings\n",
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"10%<\n",
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"name?’\n",
"course.\n",
"oiu.\n",
"clergy.\n",
"peace\n",
"to\n",
"saved.\n",
"government.\n",
"commonplaces.\"\n",
"week\n",
"meet.\n",
"1858.\n",
"Air«.\n",
"Mass.,\n",
"county.\n",
"associations.\n",
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"contractor.\n",
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"Cemetery.\n",
"country\n",
"tale.\n",
"stops.\"\n",
"rocks.\n",
"medicine.\"\n",
"men.\n",
"Zipf.\n",
"Socle'y.\n",
"erased\n",
"Mountains.-\n",
"30.\n",
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"no\n",
"Opinion.\n",
"it.\n",
"have\n",
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"Brnc#.\n",
"discussions.\n",
"day?\n",
"not\n",
"ewYork.\n",
"measure.\n",
"and\n",
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"president.\n",
"prim\n",
"drops.\n",
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"Southwestern.\n",
"dollars.\n",
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"Mr.\n",
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"once.\n",
"yield.\n",
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"capital.\n",
"missionaries\n",
"plastered.\n",
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"No.\n",
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"body.\n",
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"relation.\n",
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"School,.\n",
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"do.\n",
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"impossible.\n",
"feats.\n",
"rights,\n",
"detectives.\n",
"two\n",
"nalinns.\n",
"home.\n",
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"of.\n",
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"case.\n",
"If\n",
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"hero.\n",
"infidels.\n",
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"section.\n",
"preserves.\n",
"mine.\n",
"road.\n",
"-\n",
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"ones.\n",
"investigation.\n",
"available.\n",
",\n",
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"western\n",
"for\n",
"people.\n",
"dition.\n",
"preserved.”\n",
"theless.\"\n",
"concerned.\n",
"others.\n",
"supply\n",
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"died.\n",
"season.\n",
"city.\"\n",
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"arrested.\n",
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"ning.\n",
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"die.\n",
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"Tost.”\n",
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"persons.\n",
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"me.\n",
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"Messenger.\n",
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"Ledger.\n",
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"room.\n",
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"the\n",
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"Arthur-\n",
"sufferers.\n",
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"Philadelphia.\n",
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"Jersey.\n",
"Del.;\n",
"go.\n",
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"many\n",
"of\n",
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"progress.\n",
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"III.\n",
"4,300.\n",
"and\n",
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"\".Exchange.\n",
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"163.\n",
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"me.\n",
"date\n",
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"him.\"\n",
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"--Moines;\n",
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"him.\n",
"Ward.\n",
"Ipring?\n",
"two-thir-\n",
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"railway\n",
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"Journal.\n",
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"use.\n",
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"columns.\n",
"moment,\n",
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"slgs.\n",
"remedy.\n",
"•\n",
"week.\n",
"Plague.\n",
"lived.\n",
"stop.\n",
"conclusions.\n",
"and\n",
"State.\n",
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"appearance.\n",
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"191--\n",
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"season.\"\n",
"add.\n",
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"Co.,\n",
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"large\n",
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"existence\n",
"Booud.\"\n",
"?\n",
"Meade.*\n",
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"critics.\n",
"-\n",
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"nomination.\n",
"S.\"\n",
"of\n",
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"Police\n",
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"said.\n",
"mental\n",
"perceptible.”\n",
"recommitted.\n",
"legislation,\n",
"palling.\n",
"health.\n",
"MOB.\n",
"on\n",
"of\n",
",\n",
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"Constitution.\n",
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"-\n",
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"imagination.\n",
"Infantry;\n",
"Blackbird.\n",
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"*tiy.\n",
"oblige\n",
"weeks.\n",
"ma-\n",
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"-\n",
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"time.\"\n",
"clothes.\n",
"and\n",
"hours.\n",
"inch.\"\n",
"Company.\n",
"$200.\n",
"judgment.\n",
"n\n",
"membership.\n",
"than\n",
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"Clerk\n",
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"House.\n",
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"Section\n",
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"Pa.,\n",
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"example.\n",
"eflprts.\n",
"edbyi\n",
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"liberties\n",
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"St.\n",
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"is\n",
"spring.\n",
"medicine\n",
"16^0.\n",
"of\n",
"Newark.\n",
"house.\n",
"work.\n",
"popular.\n",
"oent.\n",
"Rbelms.\n",
"madhouse.\n",
"4\n",
"ge.\"\n",
"d\n",
"again?\n",
"portation.\n",
"parties.\n",
"dent.\n",
"sensation.\n",
"Church.\n",
"too.\n",
"aloresmd.\n",
"university.\n",
"proceedings.\n",
"two\n",
"company.\n",
"ft.)\n",
"ernor.\n",
"North-\n",
"C.\n",
"\"\n",
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"Bhe\n",
"it\n",
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"trial.\n",
"Phlludelphla.\n",
"dollars.\n",
"association.\n",
"amusement\n",
"D.li,toA.8.\n",
"articles.\n",
"drunken.\n",
"cedure.\n",
"them.\"\n",
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"character.\n",
"votes.\n",
"feet.\n",
"point.\n",
"she\n",
"ty.\n",
"n\n",
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"rs.\n",
"plans.\n",
"Papist.'\n",
"Bulletin.\n",
"World;\n",
"deserves\n",
"tables.\n",
"l»Hi.\n",
"Is\n",
"ropulsivess.\n",
"not\n",
"statute.\n",
"itanced.\n",
"natives\n",
"that\n",
"fare.\n",
"forefathers.\n",
"-\n",
"i\n",
"law.\n",
"likely.\n",
"re.\n",
"beginning.\n",
"hands.\"\n",
"peninsula.\n",
"ber.\n",
"650\n",
"day.\n",
"turpentine.\n",
"benefac\n",
"lOO/alOtt1,.\n",
"x\n",
"toastmaster.\n",
"struggle.\n",
"forms\n",
"ss\n",
"ago.\n",
"sell.\n",
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"Kronch\n",
"work.\n",
"faithful\n",
"and\n",
"out.\n",
"a\n",
"order.\n",
"and\n",
"uu.\n",
"shock.\n",
"things.\n",
"daily.\n",
"But\n",
"of\n",
"o\n",
"Island.\n",
"It.\n",
"and\n",
"Senatorial\n",
"death.\n",
"-\n",
",\n",
"advance.\n",
"lives.\n",
"country.\"\n",
"hi\n",
"desire,\n",
"applicatant.\n",
"”\n",
"iron\n",
"ill-fat-\n",
"win.\n",
"them.\n",
"utmost\n",
"Governor.\n",
"ity\n",
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"Wilmington.\n",
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"sion.\n",
"m.\n",
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"flow­\n",
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"set\n",
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"equullj-\n",
"example.\n",
"eoniMder.iltle\n",
"Sunday.\n",
"Taylor\n",
"origin.\n",
"work.\n",
"emergency.\n",
"of\n",
"peck.\n",
"dlence.\n",
"air.\n",
"country.\n",
"-\n",
"October\n",
"volunteering.\n",
"Elmwood.\n",
"line.\n",
".\n",
"manner\n",
"christian\n",
"exists.”\n",
",\n",
"straw-\n",
"-\n",
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"st\n",
"heart.\n",
"occasion,\n",
".\n",
"Brown.\n",
"schools.\n",
"9.\n",
"reins.\n",
"caretaker\n",
"months.\n",
"Senate.\n",
"ago\n",
"d\n",
"of\n",
"work.\n",
"trad.\n",
"ed\n",
"Journal\n",
"world.\n",
"Arcadia.\n",
"instruction.\n",
"S.\n",
"ved.\n",
"them.\n",
"murderer.’\n",
"intorests\n",
"Democrats\n",
"rc\n",
"lime.\n",
"tnblo.\n",
"excellence.\n",
"116th.\n",
"whole.\"\n",
"Orleans.\n",
"becoming\n",
"another.\n",
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"e\n",
"Kt»\n",
"rules.\n",
"*ac.\n",
"'\n",
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"lives.\n",
"other.\n",
"Science.\n",
"chance.\n",
"Catawlssa,\n",
"aeain.\n",
"Magazine.\n",
"ifidvnce.\n",
"mine.\"\n",
"offer\n",
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".to\n",
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"Mount\n",
"Age.\n",
"schedule.\n",
"a^t«sh\n",
"sustained.\n",
"14th.\n",
"drops\n",
"communicable\n",
"Slate.originally\n",
"In\n",
"t\n",
"tiller.\n",
"State.\n",
"father\n",
"effective.\n",
"tive\n",
"high\n",
"e\n",
"ernments.\n",
"food\n",
"rock!\n",
"tape'\n",
"distribution.\n",
"same.\n",
"Capitol.\n",
"Iceland.\"\n",
"afore-\n",
"know.\n",
"bushel\n",
"name.\"\n",
"new\n",
";\n",
"yours,\n",
"made.\n",
"be¬\n",
"State*.\n",
"her.\n",
"President-Wilson'-\n",
"arrangement.\n",
"Advertiser.\n",
",an-\n",
"Schamyl’s\n",
"selling.\"\n",
"mentioned.\n",
"diagram:\n",
"list.\n",
"character.\"\n",
"ed\n",
"appurtenances.\n",
"de-\n",
"maintenance\n",
"time.\n",
"legislature.\n",
"I>*s7.\n",
"combination.\n",
"loco-\n",
"elae.'\n",
"Stat*.\n",
"follows:\n",
"windpipe.\n",
"e-\n",
"Church.\n",
"November,\n",
"shall\n",
"streets.\n",
"dlea\n",
"d\n",
"5:18).\n",
"Journal.\n",
"usual.\n",
"remedy.\n",
"guilt.\n",
"the\n",
"Jr.,\n",
"of\n",
"for.\n",
"information.\n",
"experiences.\n",
"cerned.\n",
"certain-.\n",
"10,0(58.'\n",
"Republic.\n",
"hundred\n",
"and\n",
"citizens.\"\n",
"weaken.\"\n",
"tion.\n",
"facte\n",
"y,\n",
"zation.\"\n",
"us.\n",
"will-trem-ble\n",
"e\n",
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"copy.\n",
"Jer-\n",
"the\n",
"Mrs.\n",
"White.\n",
"feet\n",
"If\n",
"charges.\n",
"country.\"\n",
"suffer.\n",
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"flag.\n",
"two.\n",
"at\n",
"act.\n",
"city.\n",
"rita'es,\n",
"A\n",
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"ner.\n",
"camp.\n",
"remedy.\n",
"(13)\n",
"trouble\n",
"pastures.\n",
"and\n",
"street.\n",
"Jersey.\n",
"honor.\"\n",
"decision?\n",
"hours.\n",
"bunker.\n",
"neighbors.\n",
"more.\n",
"“\n",
"It\n",
"Polynesian.\n",
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"Page's\n",
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":\n",
"of\n",
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"States.\n",
"davs.\n",
"donations.\n",
"Curtis-Wright.\n",
"time!\"\n",
"armies.\n",
"hot\n",
"terday:\n",
"never\n",
"treasury.\n",
"health.\n",
"^\n",
"sanitariums.\n",
"it.\"\n",
"house.\n",
"s\n",
"old.\n",
"life.\n",
"arrest..\n",
".\n",
"Co.,\n",
"of\n",
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"coirered.\"\n",
"the\n",
"friends\n",
"order.\n",
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"district,\n",
"protection.\n",
"pulpit\n",
"lost.\n",
"grown.\n",
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"Judges.\n",
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"Mr.\n",
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"I'arlors.\n",
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"now.\n",
"dear.\"\n",
"day.\n",
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"Herald.\n",
"washes!\n",
"full.\n",
"blood.\n",
"there\n",
"leaaantly,\n",
"plating.\n",
"wholesale.\n",
"wti-x\n",
"c\n",
"to\n",
"and\n",
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"wire.\n",
"morality.\n",
"beginning.\n",
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"Leroux,\n",
"propriations.\n",
"union.’’\n",
"Dlspatcl.\n",
"Conference.\n",
"Sart\n",
",\n",
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"o\n",
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"bales.\n",
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"change,\n",
"happiness.\n",
"e\n",
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"see\n",
"cf\n",
"*1.392,180,294.\n",
"expenses.\n",
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"862,000.\n",
"him.\n",
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"pany.\n",
"Raleiffh\n",
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"days;\n",
"feet.\n",
"ago:\n",
"proof.\n",
"Union.\n",
"of\n",
"tests.\n",
"injuries.\n",
"determined.\n",
"the\n",
"-\n",
"1916.\n",
"Dr.\n",
",\n",
"persons.\n",
"each.\n",
"bu-\n",
"gerous?\n",
"yesterday.\n",
"winter.\n",
"22\n",
"tion,\n",
"increases.\n",
"fash-\n",
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"needless.\n",
".\n",
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"Preference.\n",
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"per.\n",
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"year.\n",
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"Judge.\n",
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"could\n",
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"Weekly.\n",
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"$43,000\n",
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":\n",
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"(4)\n",
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"days.\n",
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"to\n",
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"ter\n",
"street.\n",
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"lives.\n",
"tively.\n",
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"BARNABE.\n",
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"Matter.\n",
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"County\n",
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"future.\n",
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"pendent.\n",
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"unknown.\n",
"market.\n",
"Theatre.\n",
"d\n",
"M.\n",
"settlement:\n",
"Press.\n",
"IMS.\n",
"mass\n",
"'localV*\n",
"mentioned.\n",
"73%c.\n",
"those.\n",
"today.\n",
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"millions.\n",
"made.\n",
"decisively.\n",
"earth.\n",
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"Atkin«m\n",
"precisely\n",
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"Pl'tff\n",
"people.\n",
"death.\n",
"States.\n",
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"ment,\n",
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"Congress.\n",
"^\n",
"ity.\"\n",
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"to.\n",
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"Interests.\n",
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"tion.\n",
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"Advt.\n",
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"a!\n",
"passenger.\n",
"Commlaaloner*.\n",
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"shirt\n",
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"district\n",
"energy,\n",
"perience\n",
"Shortell.\n",
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"Monday.\n",
"once.\n",
"forcements.\n",
"Allegheny.\n",
"$5.\n",
"1919.\n",
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"days.\n",
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"Central.\n",
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"urgent.\n",
"then\n",
"town!\n",
"S3.1\n",
"water.\n",
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"importance.\n",
".\n",
"street.\n",
"years.\n",
"Hospital.\n",
"public,\n",
"Atlantic.\n",
"year*.\n",
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"Mink.\n",
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"flowers.\n",
"facilities.\"\n",
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"1891,\n",
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"Me.\"\n",
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"river.\n",
"confusion.\n",
"buildings.\n",
"Angnstly-beautiful-\n",
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"June]!).\n",
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"Cultivator.\n",
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"Agent,\n",
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"v\n",
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"kissed.\n",
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"may\n",
"this\n",
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"capstone.\n",
"minister.\n",
"laud.\n",
"future.\n",
"doomed.\n",
"philosopher.\n",
"roads.\n",
"people.\n",
"debt.\"\n",
"although\n",
"demanded\n",
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"over,\n",
"r\n",
"quired,-'\n",
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"Sangston.\n",
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"them.\n",
"ments.\n",
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"tions.\n",
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"Century.\n",
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"Church.\n",
"Smith.\n",
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"Medlfer-\n",
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"both.\n",
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"time.\n",
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"them.\n",
"groceries.\n",
"c\n",
"me.\n",
"umphantly.\n",
"sunbeam.\n",
"DallaaCo.,\n",
"officers\n",
"covered.\n",
"laws.\n",
"risen.\n",
"within.\n",
"rnment.\n",
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"MARTYR\n",
"which\n",
"supply.\n",
"road.\n",
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"good.\n",
"Nar-I\n",
"Sts.\n",
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"second.\n",
"available.\n",
"evening.\n",
"uway.\"\n",
"Kitty!\n",
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"55\n",
"Incumbents.\n",
"of\n",
"girl.\n",
"fertilizer.\n",
"people\n",
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"95.\n",
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"therein.\n",
"it\n",
"to\n",
"gentleman\n",
"it.\n",
"bottle.\n",
"officials.\n",
"question.\n",
"waters.\n",
"State.\n",
"laws.\n",
"Herald\n",
"had\n",
"West.\n",
"work\n",
"Vermonler.\n",
"resolution:\n",
"desirable.\n",
"21st.\n",
"Lincoln\n",
"Store.\n",
"months.\n",
"ordinance.\n",
"school.\n",
"It\n",
"state\n",
"Wilmington.\n",
"cnmpcm-ntioi-\n",
"possoselon.\n",
"11\n",
"l'\n",
"classes.\n",
"41\n",
"occurrence.\n",
"breeze.\n",
"war.\n",
"purposes.\n",
"aim.\n",
"ness.\n",
"{140,000,000\n",
"reply.\n",
"birth.\n",
"par\n",
"enduring.'\"\n",
"out\n",
"finished.\n",
"but\n",
"which\n",
"barrel.\n",
"teams.\n",
"s.nVI\n",
"the\n",
"complaint.\n",
"sorrow\n",
"Hoffecker.\n",
"lit.\n",
"by\n",
"was\n",
"possible.\n",
"safe-\n",
"instructions.\n",
"afterward.\n",
"seemed\n",
"about.\n",
"serious.\n",
"fighting.\n",
"deemed,\n",
"ages.\n",
"rule.\n",
"1860.\n",
"Jdn.\n",
"the\n",
"Hadlej.\n",
"ng\n",
"idea.\n",
"interest.\n",
"beginning.\n",
"remain.\n",
"vices.\n",
"perhaps,\n",
"bankers.\n",
"1)\n",
"extension.\n",
"tight.\"\n",
"only.\n",
"“\n",
"didate.\n",
"th\n",
"son*.\n",
"paper.\n",
"his\n",
"music.\n",
"disin-teime-\n",
"his\n",
"re\n",
"England.\n",
"route.\n",
"[Alta.\n",
"ordinance.\n",
"grade.\n",
"t\n",
"round.\n",
"Leonardt.\n",
"mischief,\n",
"grave.\n",
"$24.\n",
"merchandise.\n",
"action.\n",
"aforesaid.\n",
"Century.\n",
"did\n",
"Impies-slvo-\n",
"yet.\n",
"faith.\n",
"ton.\"\n",
"October\n",
"digestion.\n",
"death.\n",
"method.\n",
"waitress.\n",
"offences.\n",
"the\n",
"nour.\"\n",
"Rapublicaoa\n",
":\n",
"Navy.\n",
"appear\n",
"vantages\n",
"them.\n",
"for\n",
"policy.\n",
"contract.”\n",
"adjourn.\n",
"crime.\n",
"a\n",
"speculators.\n",
"Cooper.\n",
"work.\n",
"shrine.\n",
"1877.\n",
"construction,\n",
"represent.\n",
"night.\n",
"damaged.\n",
"Christ.\"\n",
"chairman\n",
"stolen\n",
"~a.\n",
"past\n",
"delivery.\n",
"wound.\n",
"otherwise.\n",
"prosper\n",
"examination.\n",
"Hitters.\n",
"instruction.\n",
"fsalad-\n",
"remedy.\n",
"friends\n",
"World,\n",
"nutritious\n",
"Chapter,\n",
"war.\"\n",
"o\n",
"t'\n",
"certlflcales.\n",
"a\n",
"issued\n",
"wildcats.\n",
"advertising\n",
"century\n",
"school.\n",
"er.\n",
"an\n",
"Court.\n",
"thither.\n",
"that\n",
"politicians\n",
"understood.\n",
"Brigham,\n",
"^ashiiiKtou.\n",
"(SEAL)\n",
"raa-\n",
"fort.\n",
"things.\"\n",
"old.\n",
"rates.\n",
"line.\"\n",
"dcMdtw\n",
"rule.\n",
"stories.\n",
"Issue.\n",
"I\n",
"barbarism.\"\n",
"Montgomery\n",
"...\n",
".\n",
"Home.\n",
"Congress,\n",
"esteem,\n",
"amirnach.\n",
"help.\n",
"nature\n",
"seems\n",
"cause.\n",
"Barker\n",
"i\n",
"the\n",
"occasion,\n",
"g\n",
"street;\n",
"ment:\n",
"death.\n",
"ladies!\n",
"men.\n",
"it\n",
"above.\n",
"is\n",
"so.\n",
"twlE.\n",
"brances.\n",
"Advocate.\n",
"simulation.\n",
"\"\n",
"e\n",
"?\n",
"I\n",
"canal.\n",
"blis\n",
"here.\n",
"Tuesday.\n",
"tory.\n",
"be\n",
"appoint­\n",
"has-\n",
"curds.”\n",
"author­\n",
"tim.\n",
"(¦mis\n",
"financially.\n",
"bard.,\n",
"order,\n",
"days.\n",
"\"\n",
"cor-\n",
"n\n",
"fo\n",
"tooth\n",
"common\n",
"edy.\"\n",
"r\n",
"exit.\n",
"be\n",
"Senate.\n",
".\n",
"2\n",
"pose.\n",
"out.'\n",
"Congress.\n",
"Glory.\"\n",
"Chronicle\n",
"It\n",
"to\n",
"Sev-\n",
"them.\n",
"wrench.\n",
"leisure.\n",
"be.\n",
"evidences.\n",
"navy.\n",
"to-day.\n",
"gTMtlT.\n",
"dissipation.\n",
"date\n",
"m.\n",
"cirtificates\n",
"weal\n",
"west.\n",
"Appomattox.\n",
"miles.\n",
"utility.\n",
"up.\n",
"j\n",
"canyon.\n",
"error.\n",
"left.\n",
"Bolshevik\n",
"Transportation,\n",
"tho\n",
"living.\n",
"trial.\n",
"k-.\n",
"go\n",
"bounded.\n",
"churches.\n",
"o’clock.\n",
"resolvents.\n",
"the\n",
"Fislihigcrock..-\n",
"L\n",
"ISIMI\n",
"labor.\n",
"said:\n",
"aid.\n",
"order.\n",
"enormously.\n",
"reason.\n",
"year.\n",
"pos-\n",
"\\\\\n",
"mnn.\n",
"tinues.\n",
"board\n",
"mili\n",
"ones.\"\n",
"acquaintance\n",
"promised.\n",
"parts.\n",
"Tnecranwra\n",
"bidder.\n",
"vigor.\n",
"write.\n",
"property.\n",
"action.\n",
"suit.\n",
"gentlemen,\n",
"by.”\n",
"the\n",
"was,-\n",
"of\n",
"Agnes,\n",
"Racine.\n",
"Mamer.\n",
"heavy,\n",
"eto.\n",
"storv.\n",
"b\n",
"fitness.\n",
"College,\n",
"Intellectuals\n",
"maximum\n",
"man.\n",
"lasts.\n",
"the\n",
"from.\"\n",
"*\n",
"program.\n",
"cause.\n",
"fering.\n",
"Sun.\n",
"two\n",
"that\n",
"givci\n",
"carried\n",
"Adams\n",
"-\n",
"faces,\n",
"meeting.\n",
"boats.\n",
"installments\n",
"vantage.\"\n",
"tance.\n",
"her.\n",
"this\n",
"here.\n",
"in*.\"\n",
"Gazette.\n",
"s\n",
"it\n",
"meeting.\n",
"rooster\n",
"brick.\"\n",
"Agent,\n",
"World.\n",
"the\n",
"flesh.\"\n",
"Mifflin.\n",
"con-\n",
"speedily.\n",
"also.\n",
"etubjrrae\n",
"months.\n",
"1912,\n",
"groups.\n",
"them.\n",
"were\n",
"gov-\n",
"dent.\n",
"charges.\n",
"like.\n",
"bo-\n",
"acre.\n",
"1866.\n",
"painful.\n",
"domination.\n",
"county.\n",
"this\n",
"admirably.\n",
"work\n",
"Graphic.\n",
"tion.\n",
"cure.\n",
"be\n",
"ner.\n",
"y-tw-\n",
"employed.\n",
"here.\"\n",
"God.\n",
"»\n",
"means.\n",
"testation.\n",
"that?\n",
"noon.\n",
"games.\n",
"years.\n",
"(14)\n",
"crat.\n",
"jail.\n",
"both.\n",
"o\n",
"re—\n",
"were\n",
"!?\".\n",
"therefor.\n",
"fruitfulness.\n",
"nitnii,\n",
"shrritf.\n",
"Addlcks.\n",
"dol­\n",
"DEPARTMENT.\n",
"Job,\n",
"December,\n",
"a\n",
"despots,\n",
"Times.\n",
"time.\n",
"iMimiitfli\n",
"country,\n",
"museum.\n",
"reform.\n",
"t:\n",
"brother.\n",
"ence.\n",
"come.\n",
"(hem.\n",
"of\n",
"tervenes.\n",
"bins.\n",
"by\n",
"employed\n",
"laborer\n",
"January\n",
"north.\n",
"ored.\n",
"ores.\n",
"church.\n",
"bht\n",
"Palmer.\n",
"which\n",
"Sn\n",
"that\n",
"tales.\n",
"facilities.\"\n",
"times\n",
"environment.\n",
"tiser.\n",
"earth.\n",
"wl»?l«\n",
"emoluments.\n",
"which\n",
"sluice-\n",
"will\n",
"l\n",
"cop).\n",
"attendance.\"\n",
"fruits.\n",
"by\n",
"Conkllng.\n",
"noise.\n",
"croam.\n",
"political\n",
"de\n",
"sttat-\n",
"restaurant\n",
"which\n",
"him.\n",
"clear.\n",
"them.\n",
"test.\n",
"the\n",
"Kihn.\"\n",
"o\n",
"overwhelming.\n",
"streets.\n",
"Brown.\n",
"for\n",
".\n",
"1917.\n",
"r\n",
"matter.\n",
"school.\n",
"now\n",
"'\n",
"merit.;\n",
"bettor.\n",
"hid.\n",
"officers\n",
"tomorrow\n",
"the\n",
"the\n",
"country.\n",
"demand.-\n",
"States.\n",
";\n",
"structure.\n",
"p.\n",
"bliss.\n",
"ately.\n",
"de\n",
",\n",
"the\n",
"camp.\n",
"$3,000,000.\n",
"business\n",
"Tribune:\n",
"cp.\n",
"city.\n",
"cure.\n",
"Jury.\n",
"roundings.\n",
"me.\n",
"duty.\n",
"politics.\"\n",
"putation\n",
"Max.\"\n",
"this.\n",
"interest\n",
"-\n",
"'\n",
"cattle.\n",
"all.\n",
"canal.\n",
"public\n",
"T.\n",
"*«\n",
"time.\n",
"in\n",
"aver\n",
"ruin.\n",
"I\n",
"and\n",
"them.\n",
"?\n",
"subject.\n",
"of\n",
"In.”\n",
"ramble.\"\n",
"d\n",
"mended,\n",
"explained.\n",
"husking.\n",
"rA\n",
"much.\n",
"destroyed.\n",
"the\n",
"-\n",
"many.\n",
"trw-Dr-\n",
"tnauuer.\n",
".A»i,n\n",
"M.\n",
"delightful.\n",
"in\n",
"their-merr-\n",
"July,\n",
"-\n",
"them.\"\n",
"Mas­\n",
"tonishing.\n",
"uratiou.\"\n",
"erally.\n",
"values.\n",
"theoountry.\n",
"right.\n",
"thereof.\n",
"dollars.\n",
"house.\n",
"Josefa.\n",
"adopted.\n",
"elimination\n",
"Makpm,\n",
"b\n",
"morning\n",
"enter?\n",
"s\n",
"which\n",
"Philadelphia.\n",
"prosperity.\n",
"carried.out.\n",
"waru.\n",
"there.\n",
"1891,\n",
"4.\n",
"Congress\n",
"throughout\n",
"whisper.\n",
"developments\n",
"country.\n",
"con-\n",
"cc\n",
"into\n",
"consumption.\n",
"you.\n",
"time.\n",
"said\n",
"pound.\n",
"disorganized\n",
"o'clock.\n",
"taxed.\n",
"companions\n",
"success\n",
"means.\n",
"so\n",
"abadauLt.\n",
"State.\n",
"excursions.\n",
"All\n",
"band.\n",
"reside.\n",
"doctors.\"\n",
"management.\n",
"and\n",
"health.\"\n",
"haven.\n",
"d\n",
"operation.\n",
"suit.\n",
"with\n",
"and\n",
"system,\n",
"skill*.\n",
"office.\n",
"law.\n",
"A\n",
"rope.\n",
"Leady.\n",
"spent.\n",
"compared\n",
"a\n",
"most\n",
"--\n",
"surface.\n",
"-\n",
"'wife.\n",
"assumption.\n",
"instances.”\n",
"ight.\"\n",
"favor.\n",
"advance.\n",
"t\n",
"fering.\n",
"exercises.\n",
"detstood.\n",
"hand.\n",
"Britain\n",
"tai\n",
"cneap.\n",
"grain.\n",
"nt\n",
"»\n",
"iine.\n",
"rest.\n",
"J24-3t\n",
"permit.\n",
"avenue:\n",
"Hon.\n",
"inink\n",
"fast.\n",
"tor.”\n",
"was\n",
"action.\n",
"Ion.\n",
"follows:\n",
"infamy.\n",
"exceptions,\n",
"board.\n",
"Ac,\n",
"fession\n",
"Fairmont.\n",
"hearings.\n",
"speculation.\n",
"Lords.\n",
"bridge.\n",
"manner.'\n",
"signature.\n",
"by\n",
"will.\n",
"W\n",
"Borough.\n",
"re-\n",
"en\n",
"prepared\n",
"Europe\n",
"Commonwealth.\n",
"examina-\n",
"Shafer.\n",
"hungry.\n",
"UIUU\n",
"1\n",
"con-\n",
"pleased.\n",
"bad.\n",
"affair.\"\n",
"destroyed.”\n",
"dealings.\n",
"cess.\n",
"bouse.\n",
"Garrett,\n",
"«1.782\n",
"imported.\n",
"f-\n",
"sending-\n",
",\n",
"granted.\n",
"society.\n",
"applause.]\n",
"river.\n",
"assignable.\n",
"Advocate.\n",
"field.”\n",
"Hamburg.\n",
"classified.\n",
"advantage.\n",
"the\n",
"Union.\n",
".\"\n",
"witness-\n",
"session.\n",
"sleep.\n",
"prelcrred,\n",
"brain.\n",
"list.\n",
"army.\n",
"map.\n",
"them.\"\n",
"details.\n",
"htar-in-\n",
"town.\n",
"hue.\"\n",
"was\n",
"doubt.\n",
"painter.\n",
"6.\n",
"said,\n",
"Basin.\n",
"G:iz'tle\n",
"tho\n",
"appears-\n",
"1*.M*\n",
"later.\n",
"aim.\n",
"safe.\"\n",
"Weekly.\n",
"sense.\n",
"N.,\n",
"work.\n",
"circuinstan\n",
"Ridge,\n",
"few.\n",
"100,000.\n",
"they\n",
"substitute.\n",
"divorce.\n",
"Paper.\n",
"Piepenbrtng,\n",
"lorever.\n",
"needy.\n",
"Russia.\n",
"\"Five-Twenty-\n",
"•\n",
"music.\n",
"Ataine.)\n",
"possible.\n",
"hint.\n",
"work.\n",
"column.\n",
"S.\n",
"accounts,\n",
"tho\n",
"of\n",
"penalty.\n",
"old\n",
"two-thir-\n",
"to-day.\n",
"shrine.\n",
"believing.\n",
"rapidly.\n",
"eternity\n",
"Breckinridge.\n",
"wide.\n",
"papers\n",
"representative.\n",
"[Oheera.]\n",
"young.\"\n",
"C\n",
"documents.\n",
"meet-\n",
"s.\n",
"k\n",
"co.,\n",
"If\n",
"r\n",
"action.\n",
"veranda.\n",
"—\n",
"well.\n",
"power.\n",
"teresting.\n",
"nights.\n",
"1930.\n",
"fair-mind-\n",
"about\n",
"\"\n",
"lUtnamlnl,\n",
"to.\n",
"hai\n",
"on.\n",
"14%.:\n",
"atockhold\n",
"lives.\n",
"Inailments\n",
"so\n",
"consumption.\n",
"said\n",
"Services.\"\n",
"Polk!\n",
"a\n",
"appearance.\n",
"scene.\"\n",
"-,\n",
"llelknap.\n",
"1\n",
"cash.\n",
"prosperous.\n",
"g\n",
"superintendent's\n",
"stars.\n",
"county.\n",
"the\n",
"Ami\n",
"ven\n",
"Htraid.\n",
"time.\"\n",
"Unite\n",
"so.\n",
"\"\n",
"hibited.\n",
"\"\"\n",
"M.\n",
"\"\n",
"bosses.\n",
"that\n",
"d\n",
"settees,\n",
"American.\n",
"given.\n",
"sight.\n",
"the\n",
"hearing.\n",
"Skc.\n",
"w?»t-\n",
"Coinylaiut.\n",
"government.\n",
"great\n",
"triumphani.\n",
"friends.\n",
"minutes.\n",
"notes.\n",
"pelerfcy.\n",
"rearino-\n",
"me:\n",
"hv\n",
"1012\n",
"fall.\n",
"arooad\n",
"work\n",
"Bradley.\n",
"wel\n",
"fire.\n",
"people.\n",
"finely.\n",
"-\n",
"follows:\n",
"vandal.\n",
"time.\n",
"place.\"\n",
"knowledge.\n",
"woman\n",
"thence\n",
"t\n",
"it\n",
"seven.\n",
"prices.\n",
"prevail.\n",
"a\n",
"toilow.\n",
"wine.\n",
"thorn.\n",
"the\n",
"whereabouts.\n",
"pasted\n",
"2S°-.,\n",
"impregnable.\n",
"then.\n",
"-\n",
"widt\n",
"d\n",
"creditable\n",
"agent.\n",
"deavor.\n",
"collected.\n",
"severely.\n",
"forthcoming.\n",
"appear.\n",
"a\n",
"practice.\n",
"you.\n",
"brances.\n",
"Kenuett\n",
"1912.\n",
"Union.\"\n",
"possible.\n",
"ComImloner*.\n",
"«fcc.\n",
"was\n",
"advertisement\n",
"pig-\n",
"light.\n",
"M.\n",
"work.\n",
"stone.\n",
"bjdrug-\n",
"Clerk\n",
"Eagle,\n",
"Messrs.\n",
"000.\n",
"largest\n",
"night.\n",
"-\n",
"passed.\n",
"eagerly\n",
"e\n",
"required.\n",
"k\n",
"Castle.\n",
"$3.25?\n",
"such\n",
"possibilities,\n",
"Journal.\n",
"elevation.\n",
"renovate,\n",
"the\n",
"Tho\n",
".\n",
"the\n",
"cemetery\n",
"n-\n",
"the\n",
"ard.\"\n",
"beyond?\n",
".\n",
".\n",
"thm\n",
"most\n",
"feet.\n",
"cheek.\n",
"known.\n",
"n\n",
"useless,\n",
"Marr\n",
",7\n",
"Tribune\n",
"over.\n",
"slightly\n",
"Saturday\n",
"execution.\n",
"burn-\n",
"N.\n",
"autmal\n",
"holes.\n",
"acted,\n",
"Oregon.\n",
"servation.\n",
"be-\n",
"prevent\n",
"sort.\n",
"Mary\n",
"offer.\n",
"feet.\n",
".\n",
"bushel.\"\n",
"for\n",
"Montgomery\n",
"pered:\n",
"he\n",
"Wheeling,\n",
"co-owner\n",
":\n",
"railway.\n",
"es\n",
"gage.\n",
"il\n",
"(father-in-la-\n",
"Gundelflnger.\n",
"III.\n",
"ng\n",
"our\n",
"Jlotmil.\n",
"admiration.\n",
"him.”\n",
"thorn\n",
"professions.\n",
"felt.\n",
"¬\n",
"ih»\n",
"out-\n",
"her,\n",
"jecture.\n",
"service.\n",
"wood.\"\n",
"resort.\n",
"Butt**\n",
"shrine.\n",
"Instruction,\n",
"f\n",
"non.\n",
"up.”\n",
"WTIC,\n",
"sec.”\n",
"rt\n",
"flora.\"\n",
"business.\n",
"s\n",
"for\n",
"Hour*-\n",
"proteet\n",
"little\n",
"cheated\n",
"Result\n",
"»ked.\n",
"Telegram.\n",
"should\n",
"it\n",
"to8p.m.\n",
"v\n",
"wrong.\n",
"continent.\n",
"j\n",
"fire.\n",
"Cradock.\n",
"beer-garde-\n",
"automobile.\n",
"provid\n",
"tired.\n",
"readmittei\n",
"applause.\n",
"removed.\n",
"owners.\n",
"tl\n",
"their\n",
"have.\n",
"Pleas.\n",
"tions.\n",
"is\n",
"while,\n",
"Dawson.\"\n",
"Marne'.\n",
"call.\n",
"weeks.\n",
"M.\n",
"at\n",
"-\n",
"respect.\n",
"court.\"\n",
"Gazette.\n",
"wall.\n",
"water.\n",
"i,\n",
"1902.\n",
"employed.\n",
"excitement.\n",
"declined.\n",
"paid.\n",
"freedom.\n",
"toguardthr\n",
"as\n",
"position.\n",
"boxes.\n",
".struggle.\n",
"Constitution.\n",
"lUalUc.\n",
"as\n",
"breakfast.\n",
"r-\n",
"lows:\n",
"slave-trade-\n",
"tenni.\n",
"to\n",
"more.\n",
".\n",
"deserved.\n",
"reference.\n",
"world.\n",
"States\n",
"stantia-\n",
"expedient.\n",
"welcome.\n",
"bright\n",
"and\n",
"fice.\n",
"s\n",
"toe,\n",
"started.\n",
"Cuba.\n",
"taken.\n",
"Union.\n",
"that.\"\n",
"Nicaragua.\n",
"dition.\n",
"Newark.\n",
"andItoldhimsoandhesaidhe\n",
"d-\n",
"Ac.,\n",
"obligation.\n",
"Rivers.\n",
"happened.\n",
"possible.\n",
"loyally.\n",
"Union.\n",
"vessel.\"\n",
"me.\n",
"saries.\n",
"tliu\n",
"-\n",
"n\n",
"at\n",
"people.\n",
"brother,\n",
"civilization.\n",
"would\n",
"distress.\n",
"simplicity.\n",
"gentle\n",
"week.\n",
"state.\"\n",
"exactly.\n",
"Island\n",
"he\n",
"Ward.\n",
"our\n",
"-\n",
"cents!\n",
"cused.\n",
"s\n",
"s,\n",
"security.\n",
"school.\n",
"broad\n",
"to\n",
"Nov\n",
"Delaware,\n",
"Bonds.\n",
"o.\n",
"reality.\n",
"sound;\n",
"written.\n",
"5005peg\n",
"himself.\n",
"peace,\n",
"bereavement.\n",
"iiresular,\n",
"be\n",
"promises.\n",
"home.\n",
"over.\n",
"itself.\n",
"I).,\n",
"unfortunate\n",
"gogue.\n",
"the\n",
"contract\n",
"lrienu,\n",
"reported.\n",
"price.\n",
"enterprise.\n",
"of\n",
"game.\n",
"baud*,\n",
"American\n",
"this\n",
"want.\n",
"Jcpson\n",
"attempts.\n",
"however.\n",
"problem.\n",
"ilianki.\"\n",
"73\n",
"ago.\n",
"noon.\n",
"with\n",
"privilege.\n",
"railroads.\n",
"a\n",
"!\n",
"law.\n",
"muon.\n",
"place.\n",
"season.\n",
"grind.\n",
"ever\n",
"ground\n",
"Esq.\n",
"a\n",
"California.\n",
"of.\n",
"public.\n",
"weather.\n",
"vestigation.\n",
"summary:\n",
"feet.\"\n",
"heads.\n",
"'\n",
"nhaae.\n",
"ruWKiM\n",
"■,,'\n",
"for\n",
"by.\n",
"Calvin\n",
"charge.\n",
"mountains.\n",
"arc\n",
"of\n",
"larger,\n",
"debater.”\n",
"war.\n",
"said:\n",
"1370,\n",
"Chesapeake.\n",
".\n",
"fort.\n",
"by\n",
"e\n",
"Is.\n",
"1903.\n",
"high.\n",
"UK,\n",
"majority.\n",
"and\n",
"result.\n",
"er\n",
"?\"\n",
"Lancaster,\n",
"slam.\"\n",
"(Signed)\n",
"Weekly.\n",
"'\n",
"tables.\"\n",
"Moines.\n",
"ObBorver,\n",
"one.\n",
"thought.\n",
"forfeited.\n",
"to\n",
"It\n",
"is\n",
"Chronicle.\n",
"it.\n",
"World.\n",
"d\n",
"way\n",
"night.\n",
"\"Congress.\"\n",
"hkeecape.\n",
"Calhoun',\n",
".\n",
"should\n",
"the\n",
"and\n",
"1\n",
"elsewhere.\n",
"ion.\n",
"vonom\n",
"climate.\n",
"both.\n",
"Lawrence.\n",
"iionne-\n",
"co!\n",
"expedition.\n",
"contains.\n",
"and\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Burgess)\n",
"cheap.\n",
"ENOUGH\n",
",\n",
"lor\n",
"by\n",
"over.\n",
"JAA41»\n",
"tory\n",
"belonging,\n",
"on\n",
"style:\n",
"L'XJK'IulitUrfH.\n",
"bill!\n",
"subscription\n",
"in-\n",
"crats.\n",
"them.\n",
"tho\n",
"velt\n",
"furnished.\n",
"acts.\n",
"ers.\n",
"wasted\n",
"Nevada,\n",
"harbor.\n",
"surrendered\n",
"see\n",
"knives.\n",
"evei\n",
"world:\n",
".\n",
"Promotions.\n",
"\"\n",
"ways.\n",
"buried\n",
"extra.\n",
"J.\n",
"promote.\n",
"nay.\n",
"dr.\n",
"less.\n",
"'coop.'\n",
"Country.\n",
"wife.\n",
"rot.\"\n",
"calculated.\n",
"education.\n",
"person,\n",
"»\n",
"children.\n",
"ILLY,\n",
"Bear.\n",
"ways.\n",
"!«-\n",
"and\n",
"management.\n",
"ants.\n",
"commodity.\n",
"scenes\n",
"tribune.\n",
"wide-sprea-\n",
"costs.\n",
"success.\"\n",
"ter\n",
"indopen-deuce-\n",
"a\n",
"La'jle.\n",
"after\n",
"pose.\n",
"lauding.\n",
"llowers,\n",
"Hoursfrom9a.m..todr.m.\n",
"year.\n",
"Keswick's\n",
"forever\n",
"us,\n",
"witness\n",
"Spetoh\n",
"living-situation.\n",
"e\n",
".\n",
"other.\n",
"helpful.\n",
"another.\n",
"exhib.:\n",
"best\n",
"so\n",
"animated.\n",
"says\n",
"arrests.\n",
"abiding\n",
"America.\n",
"¬\n",
"t\n",
"says:\n",
"efface.\n",
"hereafter.\n",
"fit.”\n",
"Iwentv-tdne\n",
"eorners\n",
"I.\n",
"the\n",
"night.\n",
"immediately.\n",
"law.\n",
"club.'\n",
"editors.\n",
"McDonough\n",
"Stomp,\"\n",
"?\n",
"as\n",
"erty.\"\n",
"evening,\n",
"manafar-\n",
"C.\n",
"distress.\n",
"(SKAL.I\n",
"States.\n",
"without.\n",
"e\n",
"school.\n",
"dealers.\n",
"gs\n",
"thing.\n",
"names.\n",
"fo\n",
"opposed.\n",
"parent\n",
"greatly\n",
"ber\n",
"lce.\n",
"their\n",
"privilege.\n",
"Cost*.\n",
"Wlikes-Barr-\n",
"Sentinel.\n",
"13.\n",
"Patriot.\n",
"night.\n",
"under\n",
"war.\n",
"com-\n",
"tion.\n",
"y\n",
".\n",
"victim\n",
"sharks.\n",
"by\n",
"day.\n",
"graved.\n",
"other\n",
"one\n",
"Department.\n",
"the\n",
"Trado\n",
"monuments\n",
"accident.\n",
"port.\n",
"anticipated.\n",
"through\n",
"society.\n",
"soon.\n",
"llechuanas.\n",
"holidays\n",
"rr\n",
"insisted\n",
"snry,\n",
"Tribune.\n",
"can\n",
"father-in-la-\n",
"hoards.\n",
"Assembly.\n",
"e\n",
"fortunate.\n",
"East.\n",
"Gregory,\n",
"floners\n",
"more\n",
"These\n",
"stove.\n",
"overabundance\n",
"a\n",
"your-icou-\n",
"period.\n",
"ago.\n",
"them.\n",
"tug.\n",
"them.\n",
"work.\n",
"tbo\n",
"s\n",
"here.\n",
"semi-annuall-\n",
"tion.\n",
"desirable.\n",
"country.\n",
"board\n",
"cincts.\n",
"President.\n",
"lf\n",
"period.\n",
"pit.\n",
"sleep.\n",
"here.\"\n",
"do,\n",
"a\n",
"cousin\n",
"lookout.\n",
"days.\n",
"wages?\"'\n",
"DosAngcs,\n",
"t\n",
"female,\n",
"him.\n",
"Secretary\n",
"Sampson.\n",
"A\n",
"time.\n",
"President?\n",
"lost.”\n",
"mistross.\n",
"vote.\n",
"tearful.\n",
"Juneau.\n",
"you?\n",
"concerned.\n",
"perseverence.\n",
"a\n",
"Amrrian.\n",
"flattery.\"\n",
"market.\n",
"love.\n",
"years.\n",
"battle:\n",
"oi\n",
"without\n",
"-\n",
"papers\n",
"wealthy.\n",
"Newt.\n",
"tin.\n",
"Interest\n",
"fashion\n",
"togetner,\n",
"lution^\n",
"shore.\n",
"re-\n",
".\n",
"lectators.\n",
"death.\n",
"such\n",
"betteer.\n",
"control.\n",
"thereof.\n",
"standing\n",
"nt\n",
"crystal.\n",
"payroll.\n",
"opinion.\n",
"is\n",
"’\n",
"membership.\n",
"Keehn.\n",
"premises.\n",
"people,\n",
"suspended\n",
"name.\n",
"deserted,Ibrlio\n",
"consumption.\n",
"not\n",
"accruing\n",
"Hepnblio,\n",
"iury.\n",
"as\n",
"shrine.\n",
"H\n",
"world/'\n",
"revoked,\n",
"points.\n",
"hand.\n",
"Porcupine\n",
"ago.\n",
"reasonable.\n",
"were\n",
"geese.\n",
"there,\n",
"geography.\n",
"fering.\n",
"etc.,\n",
"-w-\n",
"\"cause.\"\n",
"ble\n",
"in\n",
"Observer.\n",
"15,1888.\n",
"fire.\n",
"standpoint.\n",
"and\n",
"iut-.\n",
"accident\n",
"contented.\n",
"she\n",
"s\n",
"Dukes.\n",
"fur.\n",
"s,\n",
"rifle.\n",
"some\n",
"panies\n",
"drive.\n",
"i\n",
"roads.\n",
"the\n",
"it.\n",
"Science.\n",
"lion.\n",
"f,\n",
"to\n",
"be-\n",
"ty\n",
"u-\n",
"In.\"\n",
"-\n",
"to\n",
"reach\n",
"provided-\n",
"convention.\n",
"line.\n",
"4th\n",
"achieve¬\n",
"Gazette.\n",
"*50.000.\n",
"methods.\n",
"nodded.\n",
"two\n",
"vassals\n",
"origin.\n",
"sword.\n",
"Loos.\n",
"Paris\n",
"6\n",
"Record.\n",
"'2o.\n",
"<\n",
"ear.\"\n",
"stated.\n",
"people\".\n",
"investigation,\n",
"attraction.\n",
"highways.\n",
"court.\n",
"senseless!\n",
"Magazine.\n",
"ashes.\n",
"once\n",
"quences.\n",
"corners.\n",
"are\n",
"city.\n",
"school\n",
"dis-\n",
"leader.\n",
"Slates\n",
"spring.\n",
"potior.\n",
"the\n",
"beginning.\n",
"ford*.\n",
"14.\n",
"us.\n",
"disgust.\n",
"fork\n",
"launched.\n",
"cc\n",
"market.\n",
".\n",
"fee\n",
"etc.\n",
"now.\"\n",
"rate\n",
"it.\n",
"4.\n",
"oliM-rvi-\n",
"notwithstanding.\"\n",
"High.\n",
"back.\n",
"habit.\n",
"taller.\n",
"candidate.\n",
"doctors.\"\n",
"just.\n",
"work.\n",
"hi-\n",
".\n",
"We\n",
"fair\n",
"cards.\n",
"banks\n",
"X.\n",
"terrible.\n",
"-\n",
"tlon.\n",
"ago,\n",
"city.\n",
"water.\n",
"when\n",
"anybody.\n",
"cease.\n",
"telescopes\n",
"said\n",
"circumstance,\n",
"coun­\n",
"s\n",
"Iceland\n",
"advancing.\n",
"Prineviile.\n",
"remedy.\n",
"say.\n",
"on-\n",
"Mr.\n",
"carried.\n",
"paid,\n",
"future.\"\n",
"graced.\n",
"truth.\n",
"yeat--\n",
"?”\n",
"preserves\n",
"such\n",
"home.\n",
"d\n",
"waa\n",
"phy.\"\n",
"Times:\n",
"in-\n",
"footprints\n",
"funeral.\n",
"present.\n",
"crossing\n",
"robber,\n",
"diamonds\n",
"sort.\n",
"friends\n",
":\n",
"Times.\n",
"Post.\n",
"societies.\n",
"hunger,\n",
"avarice.\n",
"it.\n",
"right*\n",
"e\n",
"taken.\n",
"\"liome-tralner-\n",
"again.\n",
"conception.\n",
"good.\n",
"Science.\n",
"feeling.\n",
"remarked,\n",
"Smith.\n",
"present.\n",
"ingredients.\n",
"pre-\n",
"ju\n",
"sold:\n",
"580pm.\n",
"ten-\n",
"somo-\n",
"lf\n",
"shall\n",
"Mexican\n",
"life.\n",
"cure.\n",
"married\n",
"high-cla-\n",
"day.\n",
"a\n",
",\n",
"me.\n",
"lino\n",
"spot.\n",
"at-\n",
"by\n",
"aeason.\n",
"accepted.\n",
"justice.\n",
"The\n",
"nations.\n",
"away.\n",
"to.\n",
"Cal.,\n",
"country.\n",
"confessed.,\n",
"issue.\n",
"end.\n",
"al\n",
"Christ.\n",
"Auguit\n",
"nations.\n",
"c\n",
"trackage.\n",
"mine-\n",
"desperado.\n",
"won.\n",
"thereby.\n",
"ravenous.\n",
"shot.\n",
"newspapers\n",
"b62.\n",
"suf-\n",
"are\n",
"friends\n",
"defrauded.\n",
"contracted.\n",
"lesson.\n",
"remunerative\n",
"Kempls:\n",
"institutions.\n",
"icate.\n",
"y\n",
"pleasant.'\n",
"continuously.\n",
"tell.\n",
"goest.\n",
"producer.\n",
"thank\n",
"•\n",
"States.\n",
"cured.\"\n",
"Navy\n",
"M.\n",
"asser\n",
"Judgment\n",
"course.\n",
"1862.\n",
"township\n",
"case.\n",
".\n",
"y\n",
"a\n",
"made.\n",
"made.\n",
"n\n",
"acres,\"\n",
"them.\n",
"wonderlngs.\n",
"mind\n",
"collts-tlv-\n",
"ter.\n",
"nature.\n",
"tion.\n",
"improved.\n",
"the\n",
"\"\n",
"to-w-\n",
"Paper,\n",
"broidery.\n",
"the\n",
"X'llt.\n",
"an\n",
"often.\n",
"that\n",
"of\n",
"cemetery.\n",
"depression\n",
"\"\n",
"it.\n",
"hotel.\n",
"IS\n",
"a\n",
"m.\n",
"render.\n",
"back-\n",
"themselves.\n",
"c-\n",
"a\n",
"*ore’\n",
"companies.\n",
"the\n",
"”\n",
"manner.\n",
"tha\n",
"Granger.\n",
"difficol'7>\n",
"Lake\n",
"placed\n",
"lf\n",
"for\n",
"lllll\n",
".\n",
"learn.\n",
"so.\n",
"the\n",
"-\n",
"again.\n",
"sec-\n",
"tlmo.\n",
"isfied.”\n",
"'\n",
"GrIL\n",
"government.\n",
"democrats,\n",
"pit.\n",
"even.\n",
"McCausland.\n",
"consideration.\n",
"fragments.\n",
"the-\n",
"Colombia\n",
"defendant.\n",
"like\n",
"outrage-\n",
"yours.\n",
"Adjourned.\n",
"1\n",
"church.\"\n",
",\n",
"People.\n",
"STORY\n",
"revolver\n",
"contract\n",
"-\n",
"nttii-\n",
"Adjourned.\n",
"him.\"\n",
"dee.\"\n",
"mous.\n",
"bars\n",
"24:10.\n",
"inde-\n",
"road.\"\n",
"is.\n",
"a.\n",
"-\n",
"remedy.\n",
"in\n",
"s\n",
"match.”\n",
"Laughter.\n",
"that\n",
"aforeiaii’,\n",
"accident.\n",
"—Exchange.\n",
"and\n",
"whiter.\n",
"frc--\n",
"week.\n",
"party.\n",
"Collins\n",
"st\n",
"•\n",
".\n",
"departure.\n",
";\n",
"stock-raisin-\n",
"of\n",
"large.\n",
"completed\n",
"wrong.\n",
"mines.\n",
"outside.\n",
"lower\n",
"avoided.\n",
"me\n",
"means.\n",
"Hcdjuz,\n",
"tier?\n",
"towns—wht'je\n",
"quality.\n",
"cure.\n",
"which,\n",
"ever.\n",
"of\n",
"shall\n",
"\"\n",
"—Am,\n",
"bellovo\n",
"14.\n",
"im-\n",
"expenses.\n",
"called\n",
"43,4■\n",
"Herald.\n",
"rain,\n",
"mo-\n",
"money-mak-\n",
"celebration.\n",
"es\n",
"-\n",
"miles.\n",
"friends.\n",
"m.\n",
"their\n",
"dustry,\n",
"opposition.-\n",
"damage.\n",
"atten-\n",
"ance\n",
"bargain,?\n",
"17.\n",
"yourself.\n",
"no\n",
"M\n",
"allirmod.\n",
"yours,\n",
"the-\n",
"enjoyed.\n",
"Taj.\n",
"largely.\"\n",
"d\n",
"pl-\n",
"vore.\n",
"march.\n",
"houses.\n",
"onth■\n",
"nfitasfwl\n",
"1876.\n",
"44.\n",
"tense\n",
"times.\n",
"or\n",
"1878.\n",
"23\n",
"accommodations.\n",
"Tops-ha-\n",
"such\n",
"hats.\n",
"doc-\n",
"plant.\"\n",
"e\n",
"he\n",
"truth.\n",
"him\n",
"PUUH,\n",
"SOUTH\n",
"it.\"\n",
"-ce\n",
"at\n",
"are\n",
"granjes.\n",
"co-couuaei.\n",
"former.\n",
"of\n",
"it\n",
"prayed.\n",
"mentioned,\n",
"them.\n",
"1890.\n",
"m,\n",
"ery.\n",
"full.\n",
"votes.\n",
">\n",
"flna\n",
"Inent.\n",
"revc-\n",
"75\n",
"lefL\n",
"repealed.\n",
"toQO.\n",
"camps.\n",
"herder.\n",
"Centre.\n",
"error.\n",
"mommy\n",
"School.\n",
"Week.\n",
"sea.\n",
"night.\n",
"troops.\n",
"work,and\n",
"serv't\n",
"production.\"\n",
"clBe.\n",
"majority.\n",
"holidays.\n",
"year.\n",
"d\n",
"cients.\n",
"&c.,\n",
"1893.\"\n",
"chargo\n",
"cattle.\"\n",
"Now\n",
".\n",
"on.\"\n",
"executive\n",
"goods.\n",
"Asam.\n",
"property.\n",
"p\n",
"have\n",
"analgin*.\n",
"the\n",
"kc.\n",
"$700,000,000.\n",
"taklrg\n",
"it,\n",
"wan\n",
"ioint.\n",
"cause.\n",
".!\n",
"f<\n",
"h\n",
"quantities.\n",
"services\n",
"when.\n",
"*t\n",
"tea,\n",
"ments.\n",
"ngovern-\n",
"state.\n",
"Post.\n",
"city.\n",
"In-\n",
"charges.\"\n",
"trip.\n",
"2.\n",
"a\n",
"tho\n",
"yet.\n",
"race.\n",
",\n",
"postage.\n",
"thanksgiving\n",
"that;,\n",
"was\n",
"190D.\n",
"York.\n",
"abdomen,\n",
"conventions\n",
"back.\n",
"Affiux.\n",
"baken,\n",
":\n",
"sites.\n",
"wa-\n",
"io-\n",
"msgizines.\n",
"time.\n",
"alone,\n",
"craiy.\"\n",
"drugs.\n",
"liking.\n",
"season.\"\n",
"tower.\n",
".\n",
"silenced.\n",
"from.\n",
"court;\n",
"Alaska.\"\n",
"effective.\n",
"neck.\n",
"not\n",
"paid.\n",
"short\n",
"Esq.\n",
"herein.\n",
"thorti.\n",
"l\n",
"void.\n",
"over.\n",
"difficulty.\n",
"it.\n",
"cities.\n",
"Investigate\n",
"confusion.\n",
"insurance\n",
"otm.\n",
"t\n",
"since.\n",
".\n",
"away.\n",
"bers.\n",
"Harding,\n",
"fear.”\n",
"persevering,\n",
"Philippines.\n",
"alley,\n",
"house.\n",
"ores.\n",
".\n",
"easier\n",
"Wot\n",
"him.\n",
"treatment\n",
"tbe\n",
"flub;\n",
"patriotism.\n",
"cheap.\n",
"boa\n",
"....\n",
"for\n",
"cordingly.\n",
"1\n",
"lAdtfree..\n",
"land.\n",
"a,\n",
"glory.\n",
"ao\n",
"aloe\n",
"grain.\n",
"him.\n",
"demanded.\n",
"John\n",
"cash.\n",
".\n",
"Bussians.\n",
"expenditures.\n",
"forenoon.\n",
"weak.\n",
"sarcastically.\n",
"state.\n",
"of\n",
"N.Y.\n",
"Ms.\n",
"s\n",
"on\n",
"him\n",
"lake.\n",
"per-\n",
"cial.\n",
"Lorraine.\n",
"th\n",
"husband\n",
"\"Deaconesses.\"\n",
"—I'hicai/o\n",
"$75.\n",
"o\n",
"it.\n",
"!\n",
"them.\n",
"satisfied.\n",
"rifle.\n",
"trfct.\n",
"liberal\n",
"rules!\n",
"printer.\n",
"spring.\n",
"four\n",
"are\n",
"that\n",
"fair.\n",
"governor-elect.\n",
"advantages.\n",
"specifications\n",
"localities.\n",
"midnight.\n",
"explanatory\n",
"1852.\n",
"ino.\n",
"presents.\n",
"wharfage.\n",
"rs\n",
"cu\n",
"of\n",
"15\n",
"paper.\n",
"it.\n",
"experience.\n",
"vacation.\n",
"are.\"\n",
"goods.\n",
"home\n",
"bear-tra-\n",
"themselves,\n",
"besides.\n",
"Labor..\n",
"I\n",
"hits.\n",
"admitted\n",
"full\n",
"trT\"\"\n",
"to\n",
">\n",
"rough.\"\n",
"verse\n",
"approve.\n",
"intheh11.\n",
"Pickett.\n",
"on\n",
"doubtful\n",
"revive^ller,\n",
"pan\n",
"busi¬\n",
"remarks:\n",
"fail\n",
"hand.\n",
"thcui.\n",
"ago.\n",
"g\n",
"defeated.\n",
"Wo\n",
"-\n",
"investigating\n",
"pounds.\n",
"!\n",
"commissioners.\n",
"inten-\n",
"Rankin\n",
"single-dro-\n",
"Shorten.\n",
"five\n",
"seven\n",
"schools.\n",
"stored.\n",
"conveyed.\n",
"to\n",
"mission\n",
"up.\"\n",
"timbers.\n",
"remedy.\n",
"a\n",
"copy.\n",
"followsi\n",
"Home.\n",
"beginning.\n",
"\"Darling,\n",
"Comuion-\n",
"above.\n",
"Taxes\n",
"gloom\n",
"In.\n",
"writing.\"\n",
"day.\n",
"corrected.\"\n",
"Gregg,\n",
"tho\n",
"vested.\n",
"him.\n",
"havo\n",
"again.\n",
"$1,155,000.\n",
"Newark.\n",
"profess.\n",
"follows:\n",
"having.\n",
"members?\n",
"of\n",
"It\n",
"Men.\"\n",
"copy.\n",
"truly,\n",
"integrity.\n",
"system.\n",
"follows:\n",
"now\n",
"army.\n",
")\n",
"went.\n",
"expected.\n",
"2\n",
"center.\n",
"llrvi<v\\\\\n",
"Express.\n",
"Esq.\n",
"church.\n",
"power.\n",
"abuses.\n",
"18/.'I.\n",
"people.\n",
"c.il\n",
"locality.\n",
"estate.\n",
"\"\n",
"ness.\n",
"\"book.\n",
"price.\n",
"crowd.\n",
"a\n",
"had.\n",
"landlord.\"\n",
"a\n",
"tlj!(\n",
"control.\n",
"Gray-\n",
"pie.\n",
"mine.\n",
"edition,\n",
"»—■\n",
"in\n",
"us.\n",
"crime.\n",
"personal\n",
"the\n",
"dollars.\"\n",
"following:\n",
"Their\n",
"hist\n",
"pioneering.\n",
"him\n",
"r\n",
"no-\n",
"s\n",
".\n",
"30\n",
"Times.\n",
"State\n",
",,\n",
"ordinance.\n",
"a\n",
"welfare.\n",
"o\n",
"Aat..\n",
"world.\"\n",
"impelled\n",
"Germany.\n",
"s\n",
"case.\n",
"the\n",
"scat-\n",
"Commission.-\n",
"15.\n",
"along.\"\n",
"loss.\n",
"mothers.\n",
"seemed\n",
"finances.\n",
"fail.\n",
"shape.\n",
"It\n",
"it.\n",
"Ted.\n",
"Uuildim.*'.\n",
"Pa.\n",
"others.\n",
"twenty-\n",
"Ward.\n",
"Guyton.\n",
"reward.\n",
"denominations\n",
"schedule.\n",
"to\n",
"who\n",
"looked\n",
"her:\n",
"jt\n",
"-\n",
"t\n",
"memory\n",
"dismissed.\n",
"lie.\n",
"\"\n",
"heads.\n",
"drsas\n",
"firm.\n",
"feelings.\n",
"vnpir\n",
"address;\n",
"fering.\n",
"forfeited.\n",
"purose.\n",
"summer.\n",
"aforesaid.\n",
"given.\n",
"ground\n",
"him.\n",
"bu-\n",
"relatives\n",
"tion.\n",
"instruments,Btruddaa.\n",
"York.\n",
"high.\n",
"yours,\n",
"I\n",
"denial.\n",
"t-~»\n",
"communicable.\n",
"pe*s,\n",
"er.\n",
"complaint.\n",
"Judgment.\n",
"d\n",
"Lode.\n",
"installed.\n",
"so.\n",
"y\n",
"be.\n",
"fou\n",
"strip.\n",
"2inthiOi\n",
"Division,\"\n",
"to\n",
"objections.\n",
"”\n",
"pealed.\n",
"of\n",
"assist\n",
"two.\n",
"-\n",
"h\n",
"brium.\n",
"Willis.\n",
"more.\n",
"etc.,\n",
"ages.'\n",
"good.”\n",
"the\n",
"Positive\n",
"witness.\"\n",
"therefor.\n",
"it\n",
"explo-\n",
",\n",
"u\n",
"robber*.\n",
"deed,\n",
"e\n",
".\n",
"Digger.\n",
"—Balti-\n",
"Adjourned.\n",
"$22,-\n",
"liiinlc\n",
"land\n",
"about\n",
"epee.\n",
"days.\"\n",
"in.\n",
"murders.\n",
"confidence.\n",
"approved.\n",
"played.\n",
"away.\n",
"festival.\n",
"evil.\n",
"but-\n",
"woo-\n",
".\n",
"tiroes,\n",
"offering\n",
"avenue.\n",
"legs.\n",
"sleep\n",
"health.\n",
"suehftft,\n",
"Davidson.\n",
"work,\n",
"»\n",
"it.\"\n",
"forth.\n",
"proportionate\n",
"Italy\n",
"it.\n",
"force.\n",
"In\n",
"more.\n",
"with\n",
"oh-\n",
"great.\n",
"gentleman.\n",
"fright.\n",
"harem.\n",
"fallen.\n",
"ladies.\n",
"days.\n",
"management?\n",
"adjourned.\n",
"duties.\n",
"military.\n",
"llv\n",
"ight\n",
"In\n",
"paid\n",
"mate.\n",
"prince?'\n",
"apology.\n",
"Democrat.\n",
"love.\n",
"SIOO.\n",
"of\n",
"effect.\n",
"experience.\n",
"E.\n",
"coupon\n",
"Art\n",
"land.\n",
"and\n",
"America.\n",
"Register.\n",
"g\n",
"nent.\n",
"community.\n",
"aadertak-\n",
"lino\n",
"lishment.\n",
"party.\n",
"not\n",
"question.\n",
"coat-front.\n",
"i\n",
"st\n",
"to.\n",
"fail.\n",
"conveniences\n",
"occurs,\n",
"buildings.\n",
"e\n",
"sufferers.\n",
"filing.\n",
"inortgag-e-\n",
"adjourned.\n",
"Schindeldecker,\n",
"govern-\n",
"Slates.\n",
"and\n",
"discarded.\n",
"snow.\n",
"righteousness\n",
"toui.\"\n",
"Government.\"\n",
"the\n",
"others,\n",
"Scribner's.\n",
"Senator,\n",
"assisted.\n",
"ikoro.\n",
"custody.\n",
"ing\n",
"exercises\n",
"Paris.\n",
"answer.\n",
"him.\"\n",
"s\n",
"War.\n",
"purpose.\n",
"State.\n",
"Comment.\n",
"health.\n",
"follies.\n",
"Mrs.\n",
"results.\n",
"-\n",
",\n",
"to\n",
"follow,\n",
"tlic\n",
".*---V\n",
"said.\n",
"wicked-\n",
"following\n",
"to\n",
"iniform.\n",
"ly\n",
"theory.\n",
"theory.\n",
"three-fourth-\n",
"water.\n",
"Jr.,\n",
"it.\n",
"Valley.\n",
"Thee.\"\n",
"communicable.\n",
"health.\n",
"date\n",
"nn\n",
"sions.\n",
"matter.\n",
"perquisites.\n",
"tucky\n",
"«fec.,\n",
"ing.\n",
"them.\n",
"business.\n",
"down.\n",
"each.\n",
"-\n",
"inferior\n",
"home.\n",
"4t—36\n",
"thereat.\n",
"newest.\n",
"t\n",
"Navy.\n",
"filled.\n",
"and\n",
"land.\"\n",
"delay.\n",
"load.\"\n",
"family.\n",
"Uaicllt,\n",
"118\n",
".\n",
"ones.\n",
"relatives.\n",
"work,\n",
"same.\n",
"gathered.\n",
"American.\n",
"died?\"\n",
"Honor.\n",
"A.\n",
"tho\n",
"population,\n",
"years.\n",
"eternal\n",
"maoleod\n",
"court.\n",
"kind.”\n",
"lefthim.\n",
"st.,\n",
"valor.\n",
"shippers.\n",
"wire\n",
"the\n",
"day.\n",
"Xvavs.\n",
"ers.\n",
"equipment\n",
"commendable.\n",
"Huntsfcille:\n",
"man.\"\n",
"Guild.\n",
"ment\n",
"printer.\n",
"remedy.\n",
"souvenir\n",
"here\n",
"Seat-\n",
"stock.\n",
"msue\n",
"appearance.\n",
"ooo-\n",
"the\n",
"vestigation.\n",
"wait.\n",
"privileges.\n",
"a\n",
"\"stuck\"\n",
"Ameri-\n",
"circles.\n",
"seded.\n",
"text\n",
"Bill\n",
"relief\n",
"exporti\n",
"no1\n",
"ing.\n",
"could\n",
"streets\n",
"Bank-wher-\n",
"*'\n",
"destructive\n",
"pound.\n",
"world.\n",
"notv\n",
"preserves.\n",
"School.\n",
"smile.\n",
"delay.\n",
"King.\"\n",
"wed.\n",
"res--\n",
"Sugarloaf.\n",
"Baltimore.\n",
"relief.\n",
"contracted-\n",
"information.\n",
"tobacco.\n",
"past.\n",
"The\n",
"Company\n",
"the\n",
"head\n",
"parlor.\n",
"assistance.\n",
"inator.\n",
"And\n",
"couple.\n",
"!\n",
"time.\n",
"it.\n",
"re-\n",
"slavery,.\n",
"powers.\n",
"kennel.\n",
"Clerk\n",
",\n",
"him.\n",
"yellow.\n",
"cured.\"\n",
"Chester.\n",
"eliminated\n",
"and\n",
"success.\n",
"*\n",
"center.\"\n",
"!\n",
"him.\n",
"Gazette.\n",
"antagonists.\n",
"law.\n",
"UDion.\"\n",
"ble.\n",
"’\n",
"Iar?e.\n",
"estant\n",
"best.,\n",
"--\n",
"ruin\n",
"will\n",
"the\n",
"ment*.\n",
"measure.\"\n",
"Aboliuosisa^\n",
"bones.\n",
"firtther.\"\n",
"American.\n",
"it\n",
"it.\"\n",
"circus\n",
"thanlrRo-Itrlnf-\n",
"but\n",
"Fisherman.\n",
"9\n",
"containing\n",
"Ibom.\n",
"sal-\n",
"Bnff.ilo\n",
"News\n",
"investigation.\"\n",
"retract.\n",
"affairs.\n",
"up-\n",
"events.\n",
"settled\n",
"aggrandizement.\n",
"iug.\"\n",
"expenditures.\n",
"up\n",
"\"Yes.\"\n",
"had\n",
"s,\n",
"remedy.\n",
"surpassod.\n",
"easy\n",
"herself.\n",
"-rtrick.\"\n",
",\n",
"mc\n",
"Cemetery.\n",
"Weston.\n",
"colter-\n",
"fol-\n",
"sea.\n",
"good-night!\"\n",
"potatoes,\n",
"power\n",
"*\n",
"stand\n",
"if\n",
"laws.\n",
"follows:\n",
"Herbert........\n",
"mentioned.\n",
"us.\n",
"N.\n",
"winter.\n",
"the\n",
"a\n",
"Tennessee.\n",
"by\n",
"being\n",
"worse\n",
"machinery.\"\n",
"affirmed.\n",
"on--\n",
"statesmen\n",
"Creek\n",
"street\n",
"co-partnership..\n",
"'\n",
"pppreciato.\n",
"e\n",
"on\n",
"tion.\n",
"d.\n",
"1887.\n",
"faithfully,\n",
"existing.\n",
"Ing\n",
"clock.\n",
"committees.\n",
"1'.\n",
"show.\"\n",
"consistency.\n",
"rupee.\n",
"discovered\n",
"done.\n",
"Cod.’\n",
"&Enq.\n",
"of\n",
"upon.\n",
"offer.\n",
"as\n",
"evolved.\n",
"sutreested.\n",
"himself.\n",
"known\n",
"and\n",
"1\n",
"children.\n",
"and\n",
"his\n",
"c\n",
"increased.\n",
"at\n",
"e\n",
"fashionable.\n",
"months.\n",
"6o\n",
"fire.\n",
"mise\n",
"it\n",
"preserves.\n",
"passage.\n",
"slavery,\n",
"BnoxiiKiw.\n",
"the\n",
"follows:\n",
"coin.\n",
"IT.-:\n",
"what\n",
"peace,\"\n",
"country.\n",
"Esq.,\n",
"life.\"\n",
"innocence.\n",
"clipper\n",
"complaint.\n",
"i\n",
"man\n",
"property.\n",
"art.-\n",
"-\n",
"forgets.\"\n",
"i.i\n",
"German-Prussia-\n",
"1H90.\n",
"a\n",
"corporations.\n",
"k.\n",
"place.\n",
"West.\n",
"campaign.\n",
"congress\n",
"debt.\"\n",
"result.\n",
"-\n",
"patriots.\n",
"h\n",
"town.\n",
"and\n",
"the\n",
"detected.\n",
"ftatp\n",
"I\n",
"syndicates.\n",
"dignity.\n",
"it.\n",
"\"commercial\n",
"health.\n",
"question.\n",
"you,\n",
"Bird\n",
"guidance,\n",
"night.\n",
"a\n",
"13,425,000.\n",
"Connaught.\n",
"onous.\n",
"areeu.\n",
"of\n",
"st\n",
"pupils\n",
"elevens.\n",
"known.\"\n",
"tioae\n",
"tion\n",
"army;\n",
"O'Neil.\n",
"y\n",
"forever.\n",
"-\n",
"Skchvo-\n",
"task.\n",
"practiced.\n",
".\n",
"finances.\n",
"guilty.\n",
"United\n",
"suit\n",
"degree.\"\n",
"architecture.\n",
"yours.\"\n",
"people.\n",
"bill).\n",
"killed.\n",
"besides.\n",
"spells.\n",
"from.\n",
"purchasers.\n",
"set.\n",
"(1\n",
"Inches.\n",
"remains.\n",
"-\n",
"reflected.\n",
"being,\n",
"line.\n",
"-\n",
"be\n",
"government\n",
"Smith.\n",
"game.\n",
"you'\n",
"people.\n",
"»\n",
"Wells.\n",
"Meeker,\n",
"pleas\n",
"ticket.\n",
"thirty-\n",
"authority\n",
",\n",
"leadership.\n",
"it\n",
"im-\n",
"nincycara.\n",
"experienced\n",
"towns.\n",
"I860.\n",
"M.\n",
"midst.\n",
"reasons.”\n",
"July,\n",
"for\n",
"improvement?\n",
"ground\n",
"\"\n",
"administered.\n",
"reconstruction.\n",
"victory.\n",
"experience.\n",
"Alaska.\n",
"artery\n",
"granted.\n",
"exclaimed,\n",
"somevheionn'\n",
"h,\n",
"uttered\n",
"slopes.\n",
"\"\n",
"thinking.\n",
"invader.\n",
"costs.\n",
"Lots.\n",
"in\n",
"csntidvncs.\n",
"however,\n",
"him.\n",
"full.\n",
"another.\n",
"mankind.”\n",
"blessed.\n",
"pos-\n",
"fire.\n",
"and\n",
"his-\n",
"c\n",
"e\n",
"to\n",
"purposes.\n",
"Treasurer.\n",
"ge\n",
"beating.”\n",
"press.\n",
"the\n",
"-\n",
"oa.\"\n",
"said:\n",
"reclaimed.\n",
"reside.\n",
"farther.\n",
":\n",
"Trust.\n",
"count\n",
"brought\n",
"dignity.\n",
"lb.\n",
"all.\n",
"it.\n",
"details.\n",
"or\n",
"fallen!\"\n",
"more.\n",
"ancestors.\n",
"tion.\n",
"\"Twollne.\"\n",
"ng-\n",
"empire.\n",
"o\n",
"York.\"\n",
"vention.\n",
"life-time.\n",
"molestation.\n",
"ate.\n",
"1862.\n",
"had-submitted.\n",
"Livingstone.\n",
"lists.’\n",
"nt\n",
"months.\n",
"Baker's\n",
"Demacrtt.\n",
"afternoon.\n",
"money.\n",
"discredit.\n",
"un-\n",
"official.\n",
"Douglas.\n",
"patience.\n",
"He\n",
"Utah.\"\n",
"cent.\n",
"day*.\n",
"unanimous.\n",
"vices.\n",
"Marvel.\n",
"wards.\n",
"as\n",
"work,\n",
"1\n",
"the\n",
"Baptist.\n",
"remedy.\n",
"tight\n",
"the\n",
"re\n",
"America.\n",
"not.\n",
"company.\n",
"own.\n",
"other.\n",
"end.\n",
"the\n",
"in-law.\n",
"m.\n",
"Railroad.\n",
"sand.\n",
"in\n",
"it.\"\n",
"warranted.\n",
"coata.\n",
"congress.\n",
"money.\n",
"arrived.\n",
"by\n",
"of\n",
"eight.\n",
"«\n",
"men.\n",
"if\n",
"I».I.\n",
"did\n",
"eager\n",
"both.\n",
"that\n",
"reach.\n",
"statement.\n",
"water.\n",
"measures.\n",
"leg-\n",
"of\n",
"dresses.\n",
"tone!\n",
"poopjo.\n",
"t\n",
"city,\n",
"'\n",
"renew-\n",
"urofceslonal\n",
"other.\n",
"them.\n",
"American.\n",
"con-\n",
"bv\n",
"have\n",
".\n",
"war.\n",
"APPROPRIATIONS\n",
"State.\n",
"missionary,\n",
"under.\n",
"hurt.\n",
"e\n",
"vacated.\n",
"later.\n",
"uruius,\n",
"toa\n",
"■financing.\n",
"him.'\n",
"tools.\n",
"nnemlnn.\n",
"west.”\n",
"and\n",
">\n",
"Secretary.\n",
"tho\n",
"virtues.\n",
"1840.\n",
"God-Saviour.\n",
"God.\n",
"eat.\n",
"Oroville,\n",
"county.\n",
"live.\n",
"party,\n",
"globe\n",
"ar*\n",
"congregation.\n",
"bearing\n",
"!».\n",
"above\n",
"ideas\n",
"prayed.\n",
"Bluffs.\n",
"investigation.\n",
"traveler.\n",
"oil\n",
"fines.\n",
"oiteus.\n",
"disposal.\n",
"fol-\n",
";\n",
"w&y\n",
"blood\n",
"dance\n",
"protection.\n",
"Californian.\n",
"almost\n",
"them.\n",
"rot-\n",
".Mr.\n",
"pag.--\n",
"purchaser.\n",
"each\n",
"penalties.\n",
"dismissed.\n",
"denoted\n",
"excuse.\n",
"o\n",
"Herald.\n",
"Gentleman.\n",
"success.\n",
"it.\n",
"methods.\n",
"factory.\n",
"St.\n",
"tion.,\n",
"an\n",
"P.\n",
"cause.\n",
"Septembers.\n",
"log.\n",
"the\n",
"70^\n",
"them.\n",
"ninth.\n",
"ation.\n",
"beat.\n",
"situations.\n",
"for\n",
"oi\n",
"Ghost.\"\n",
"with\n",
"Cross.\n",
"troops.\n",
"avoided.\n",
",\n",
"sacrifice\n",
"former.\n",
"\"Othello\"\n",
"Philadelphia.\n",
"power.\n",
"would\n",
"gb\n",
"y\n",
".\n",
"chief.\n",
"Nicholaieviteh.\n",
"tho\n",
"tiling.\n",
"brnshlng.\n",
"city.\"\n",
"consum\n",
"reform.\n",
"inteuiioti.\n",
"bricklaying.\n",
"forfeited.\n",
"mate.\n",
"them.\n",
"elected\n",
"Oroville,\n",
"terms.\n",
"e\n",
"order.\n",
"old\n",
"favor.\n",
"them.\n",
"out.\n",
"consumption.\n",
"a.\n",
"e\n",
"°r\n",
"trade.\"\n",
"$1.\n",
"just.\n",
"two\n",
"charge.\n",
"adopted.\n",
"nation.\n",
"tion.”\n",
"lew\n",
"beginning.\n",
"worth.\n",
"Wood.\n",
"business.\n",
"IbOo.\n",
"l.\n",
"Iowa..\n",
"destruction\n",
"to\n",
"Interment\n",
"a\n",
"Country,\n",
"says.\n",
"these\n",
"field.\n",
"on.\n",
",\n",
"water.\n",
"gether.\n",
"Trustees.\n",
"office.\n",
"said:\n",
"arrived.-\n",
"wares?\"\n",
"operations.\n",
"going.\n",
"a\n",
"thl\n",
"consideration.\n",
"r.\n",
"are!\n",
"done.\n",
"rules.\n",
"specimen,\"\n",
"altetnoon.\n",
"\"\n",
"aud\n",
"mentioned.\n",
"How?\n",
"cured.\"\n",
"mention.\n",
"Tur\n",
"shrieking,\n",
"And\n",
"city.\n",
"to-day.\n",
"politics,\n",
"an\n",
"Newark.\n",
"ordeal.\n",
"primary.\n",
"men,\"\n",
"d\n",
"them.\n",
"...\n",
"wit:\n",
"?\n",
"mind\n",
"plasters.\n",
"there.\n",
"resource*.\n",
"Yours,\n",
"him.\n",
"district\n",
"ican.\n",
"west.'''\n",
"opportunities\n",
"infinitum.\n",
"by.”\n",
"devices.\n",
"health.\n",
"course,\n",
"voters.\n",
"nlfi'clnd.\n",
"a\n",
"of\n",
"ss\n",
"Passaic\n",
"Express.\n",
"he\n",
"wh\n",
"prisonment.\n",
"Trustees.\n",
"j,\n",
"appurtenances.\n",
"p-\n",
"color.\n",
"tentiary.\n",
"commerce.\n",
"named.\n",
"occurred.\n",
"behalf.\n",
"Science.\n",
".\n",
"branch\n",
"as\n",
"attended.\n",
"legislation.\n",
"\"effective.\"\n",
"sil\n",
"I\n",
"nt,\n",
"luth.\n",
"friends\n",
"Hannah.\n",
"Department.\n",
"banks.\n",
",0c\n",
"him*\n",
"Edith,\n",
"law.\n",
"the\n",
"their\n",
"y,\n",
"harm.\n",
"ins.'\n",
"nominated.\n",
"answer.\n",
"degree.\n",
"drifted.\n",
"Ostf-ta-\n",
"nationalities.\n",
"n.e\n",
"n»A>..J!.\n",
"sides.\n",
"$2,250,000.\n",
"lodge.\n",
"described:\n",
"Fos\n",
"M.\n",
"state\n",
"e\n",
"the\n",
"or\n",
"--\n",
"da\n",
"indigestion.\n",
"continued:\n",
"K\"venuuonl.\n",
"court.\n",
"tion.\n",
"Kllevlts\n",
"man.\n",
"told.\n",
"numb'--\n",
"were\n",
"carpet-baggers.-\n",
"quality.\n",
"on\n",
"events\n",
"more.\n",
"'twos.\"\n",
"Idler.\n",
"roots.\n",
"ginning.\n",
"world\n",
"in\n",
"remedv.\n",
">.\n",
"Bi.ll.\n",
"Presldeot-\n",
"died?\"\n",
"supervisors.\n",
"Cascades.\n",
"twelve\n",
"Atlantic.\n",
"Glentworth.\n",
"nationality.\n",
"up?\n",
"r(\n",
"one.\n",
"to-morrow.\n",
"News.\n",
"vance.\n",
"e\n",
"tustc.\n",
"Herald.\n",
"show.\n",
"the\n",
"de-\n",
"Bottomley.\n",
"estate.\n",
"bargain.\n",
"He\n",
"list.\n",
"strikes,\n",
"No.\"\n",
"beginning.\n",
"mio-\n",
"did.\n",
"the\n",
"1860.\n",
"right.\n",
"renown.\n",
"co.,\n",
"relense.\n",
"Micbigau.\n",
"5\n",
"country.\n",
"tor\n",
"house.\"\n",
"avenue.\n",
"conference.\n",
"o\n",
"undischarged.\n",
"gamuts.\n",
"time.\n",
"supporters.\n",
"copy.\n",
"conipauies.\n",
"minutet.\"\n",
"Number.\n",
"the\n",
"again,\n",
"lea.\n",
"1:474.\n",
"regretted\n",
"thence\n",
"district.\n",
"cation.\n",
"d\n",
"statements.\n",
"Lyra,\n",
"short-live-\n",
"f\n",
"s-.\n",
"a-\n",
"cats.\n",
"d,\n",
"product,\n",
"work.\n",
"absurdity\n",
"SOft.\n",
"city.\n",
"Times.\n",
"the\n",
"hut.\n",
"Veterans.\n",
"income!\n",
"y\n",
"year.\n",
"minister.\n",
"filing.\n",
"Press.\n",
"them.\n",
"sad\n",
"S.\n",
"to!d\n",
"known.\n",
"to.\"\n",
"often\n",
"tbe\n",
"dealers.\n",
"Jcnn\n",
"less.\n",
"pression.\n",
"expected.\n",
"members\n",
"sustain\n",
"r-\n",
"claimants.\n",
"P.\n",
"order.\n",
"had\n",
"'\n",
"seventies.\n",
"authorizing\n",
"notice.\n",
"self-government.\n",
"Street.\n",
"redressed.\n",
",\n",
"Appleby\n",
"seed.\n",
"places.\n",
"wisdom.\n",
"removed.\n",
"kinds\n",
"Virginia.\n",
"7a9%c.\n",
"away.\n",
"tin\n",
"Center.\n",
"clerk.\n",
"loving,\n",
"y\n",
"now.\n",
"it\n",
"continued.\n",
"tli\n",
"vision,\n",
"Int.\n",
"Investigations,\n",
"the\n",
"nillllu.\"\n",
"b-\n",
"pioneer.\n",
"ed.\n",
"Tobeauroliolathoh\n",
"pjndlcutc.\n",
"others.\n",
"cusable.\n",
"other\n",
"con*\n",
"stomachs.\"\n",
"borer.\n",
"ships.\n",
"are\n",
"youngsters.\n",
"the-\n",
"Record.\n",
"Tiki\n",
"on.—Southron\n",
"complaint.\n",
"\\\\\n",
"her.\n",
"remedy.\n",
"neighbors.\n",
"own\n",
"children.\"\n",
"Tobolsk.\n",
"our\n",
"U.I\n",
"from.\n",
"centuries.\n",
"pigeons.\n",
"Brown's.\n",
"emetic.\n",
"plays.\n",
"disclosed.\n",
"itr\n",
"money.\n",
"ways.\n",
"discovered,\n",
"man\n",
"Iniallmetita\n",
"calls.\n",
"election.\n",
"exclaiming.\n",
"BarrlngtonBrown\n",
"said,\n",
"was\n",
"nityasafeme’\n",
"\"Gee,\n",
"lazy.\n",
"story.\n",
"era.\"\n",
"again,\n",
"Harrl-\n",
"Sim.\n",
"walls.\n",
"Jr.,\n",
"scandal.\n",
"ers\n",
"ringing.\n",
"police.\n",
"ones.\n",
"the\n",
"er\n",
"nence.\n",
"them.\n",
"tr\n",
"trap.\n",
"people.\n",
".\n",
"hlr\n",
"ployment.\n",
"hills.\n",
"•\n",
"aforesaid\n",
"E.VzS.E.\n",
"1917.\n",
"it.\n",
"Thurmont\n",
"harm.\n",
"afford.\n",
"life.\n",
"moments.\n",
"home!”\n",
"purpose.\"\n",
"earth.\n",
"purpose.\n",
"In.\n",
"While\n",
"perlenced.\n",
"salo.\n",
"of.\n",
"it.\n",
"on\n",
"minimum.\"\n",
"Burgess)\n",
"Territory.\n",
"Lothian\n",
"hand.\n",
"life.\n",
"yachtsmen\n",
"taken.\n",
"person.\n",
"M.\n",
"motions.\n",
"rivalry\n",
",\n",
"other.\n",
"ous\n",
"prosjierity.\n",
"Abbott.\n",
"gone.\n",
"claims.\n",
"morality.\n",
"de\n",
"Co.\n",
"foothills.\n",
"ult.\n",
"Proctor.\n",
"ii.\n",
"End.\n",
"heed.\n",
"T\n",
"Commissioner\n",
".\n",
"others.\n",
"able-bodi-\n",
"lOWL.\n",
"filing.\n",
"transfer.\n",
"pig.\n",
"life\n",
"1,000.\n",
"g\n",
"crime.\n",
"brothers.\n",
"atTVVc\n",
"the\n",
"little.\n",
"dc-\n",
"s\n",
"he\n",
"cure.\n",
"fund.\n",
"of\n",
"manner\n",
"7\n",
"Post.\n",
"avoided.\n",
"it.\n",
"over.\n",
"Advocate\n",
"population.”\n",
"box.\n",
"Patriot.\n",
"in\n",
"failure.\n",
"backers.\n",
"affection.\n",
"Office.\n",
"have.\n",
"--\n",
"setting.\n",
"ailment.\n",
"long.\n",
"ta\n",
"justified.\n",
"Con\n",
"In\n",
"taW\n",
"yet.\n",
"fruit.\n",
"diseases.\n",
"exposed.\n",
"them.\n",
"servant,\n",
"geiu'ratlou.\n",
"Justice.\n",
"spotless,\n",
"air.\n",
"this.\"\n",
"silver\n",
"L................................\n",
"needed.\n",
"rate.\n",
"Intelligencer.\n",
"have\n",
"aostroyed.\n",
"the\n",
"ten\n",
"meanness.”\n",
"at\n",
"figures.\n",
"strawberries,\n",
"follow\n",
"system\n",
"remain\n",
"man.\n",
"prosecutions\n",
"registry-\n",
".\"\n",
"Hevlew.\n",
"is\n",
"of\n",
"ge-\n",
"alone.\n",
"uaryL\n",
"the\n",
"him.\n",
"n\n",
"like\n",
"artists.\n",
"Americans.”\n",
"interest:\n",
"Delaware.\n",
"loa's.\n",
"fering.\n",
"winner.\"\n",
"look.\n",
"up.\n",
"California.\n",
".\n",
"the\n",
"respect.\n",
"fed.\n",
"Lyman.\n",
"quiredi\n",
"-\n",
"tobacco\n",
"height\n",
"dinner.\"\n",
"tors.\n",
"basin.\n",
"$400.-\n",
"ad-\n",
"Chronicle.\n",
"practices.\n",
"rality.\n",
"-\n",
"people.\n",
"believe\n",
".\n",
"decline.\n",
"Liverpool,\n",
"onlj\n",
"sort.\n",
"course.\n",
"Vou\n",
"In\n",
"why.\n",
"since.\n",
"plication.\n",
"Tesreau.\n",
"association.\n",
"-\n",
"parlors.\n",
"across\n",
"tippurunning.\n",
"the\n",
"Post.\n",
"1880.\n",
"lows:\n",
"party.\n",
"bejth.\n",
"now.\n",
"10CO\n",
"fulminations.\n",
"says:\n",
"ago.\n",
"employ.\n",
".\n",
"haste.\n",
"dispensation.\n",
"might\n",
"the\n",
"seat\n",
"erful\n",
"convenience\n",
"tion.\n",
"possessed.\n",
"write.\n",
"lata.\n",
"was-no-\n",
"miner.\n",
"g\n",
"replied.\n",
"handsome.\n",
"th\"ir\n",
"enter.\n",
"i\n",
"that?\n",
"r.\n",
"both.\n",
"inherited\n",
"place.\n",
"g\n",
"ccptance.\n",
"hue.\n",
"nope\n",
"my\n",
"heaven.\n",
"feet.\n",
"Egj-pt-\n",
"from\n",
"another.\n",
"baggers.\n",
"75(380c.\n",
"to\n",
"Causey,\n",
"^\n",
"13.\n",
"most\n",
"destiny-\n",
"week\n",
"the\n",
"?\n",
"principal.\n",
"drugs.\n",
"14-th.\n",
"do.\n",
"tii\n",
"service.\n",
"tives.\n",
"follows\n",
"Darien.\n",
"Ui\n",
"y\n",
"Benwood.\n",
"greenbacks.\n",
"artillery.\n",
"died.\n",
"R«ncy.\n",
"tube.\n",
"once.'\n",
"high.\"\n",
"house.\"\n",
"pcuuiles\n",
"explorer.\n",
"Appeal.\n",
"development.\n",
"game?’’\n",
"Journal.\n",
"him.”\n",
"^y\n",
"the\n",
"Amerlrnn.\n",
"lands.\n",
"jl\n",
"HI\"\n",
"came\n",
"customers.\n",
"aforesaid.\n",
"them.\n",
"them.\n",
"Matthews.\n",
"Babbitt.\"\n",
"officers.\n",
"show.\n",
"pursuit.\n",
"there\n",
"it.\n",
"ever.\n",
"opin-\n",
"fnrnishlnj-\n",
"haud.\n",
"Solnt.\n",
"iu\n",
"payments.\n",
"wage*.\n",
"lawlessness.\n",
"removed.\n",
"census-taker-s\n",
"worst--\n",
"today',\n",
"captivity.\n",
"Ot.\n",
"sum.\n",
"is.\"\n",
"therefore,\n",
"up\n",
"dimensions.\n",
"spot.\n",
"of\n",
"Celluloid.\n",
"tion,\n",
"fools.\n",
"Saturdays.\n",
"attention.\n",
"something\n",
"forks.\n",
"amy.\n",
"?\n",
"har­\n",
"Medical\n",
"living\n",
"perienced.\n",
"er\n",
"hut\n",
"istrar*.\n",
"of\n",
"expo-\n",
"t\n",
"New-Cen-\n",
"nnuoyc-d-\n",
"dry\n",
"scandal.\"\n",
"pass.\n",
"A\n",
"make\n",
"President.\n",
"team.\n",
"ts\n",
"s\n",
"discussion.\n",
"MiningCompan-,\n",
"M»5.\n",
"‘ltion\n",
"be-\n",
"Asia\n",
"Thejr\n",
"him.\n",
"and\n",
"fine-looki-\n",
"Involved.\n",
"land.\n",
"weeks.\n",
"State.\n",
"missionary\n",
"heart.\n",
"yours,\n",
"liberty.\n",
"g\"\n",
"life-an-\n",
"anew.\n",
"line.!\n",
"ninjf.\n",
"day.\n",
"that\n",
"my\n",
"logs.'\n",
"Tress.\n",
"matter.\n",
"they\n",
"a\n",
"wires\n",
"months.\n",
"¬\n",
"SECRETS,\n",
"recover.\n",
"ifian.\n",
"admin-\n",
"isa\n",
"consequence.\n",
"50.\n",
",\n",
"for\n",
"pray.\n",
"banner.\n",
"those\n",
"Beecher,\n",
"“\n",
"oi\n",
"ph.\"\n",
"says:\n",
".\n",
"commissioners.\n",
"repair.\n",
"conjecture.\n",
"-\n",
"ley.\n",
"Duffy,\n",
"time.\n",
"evenings.\n",
"shot\n",
"boor.\n",
"operate\n",
"\"gibbet,\"\n",
"ing.\n",
"murdoror.\n",
"theud-\n",
"°l\n",
"nomination.\n",
"unflinchingly.\n",
"suddenness.\n",
"aimnch\n",
"cup.\n",
"bnJge.\n",
"road.\n",
"clients.\n",
"division.\n",
"hat\n",
"-\n",
"tirm.\n",
"Age,\n",
"tunate,\n",
"ju-Jifice.\n",
"be\n",
"particular.\n",
"enterprise.\n",
"tl..-\n",
"Bhortatl.\n",
"influence.\n",
"preserves.\n",
"-\n",
"vlllago\n",
"respon-dbl-\n",
"survivors.\n",
"8,000.\n",
"position.\n",
"Railroad-:\n",
"Khln.\n",
"printed.\n",
"State,\n",
"eat.\n",
"appertaining.\n",
"match.\n",
"Ii\n",
"mines.\n",
"or\n",
"them.”\n",
"afternoons.\n",
"directed\n",
"claims.\n",
"d,\n",
"D.\n",
"with\n",
"demanded.\n",
"Brown,\n",
"for\n",
"iron.\n",
"law.\n",
"out\n",
"interest.\n",
"44\n",
".1\n",
"Donehoo.\n",
"onto-\n",
"health.\n",
"labor.'\n",
"o:\n",
"vehicles.\n",
"II...\n",
"solid.\n",
"term.\n",
"Germany.\n",
"telling\n",
"church.\n",
"inoffeusive.\n",
"performed,\n",
"folly.\n",
"outing.\n",
"gency.\n",
"within.\n",
"of\n",
"Hanker.\n",
"leaders.\n",
"be,\n",
"car.\n",
"then\n",
"made.\n",
"enco.\n",
"sunshine.\n",
"Hamilton.\n",
"Prospect\n",
"lay.\n",
"aueatinn\n",
"cneap.\n",
"member­\n",
"Catholio-ity-\n",
"peace.\n",
"air.\n",
"its\n",
"preachers.\"\n",
"license.\n",
"wick,\"\n",
"blight.\n",
"of\n",
"Duncan,\n",
"provisions.\"\n",
"in\n",
"on.\n",
"reclamation\n",
"Jnly,\n",
"made.\n",
"joke?\n",
"Agency.\n",
"clut-\n",
"-poli-\n",
"passage.\n",
"system.\n",
"|kj1.uo\n",
"troops.”\n",
"work.\n",
"estab­\n",
"disease.\n",
"y\n",
"vots.\n",
"yet.\n",
"regular\n",
"Ptttl\n",
"murder.\n",
"lap.\n",
"Science.\n",
"gentleman.\n",
"tions.\n",
"anywhere.\n",
"therf-\n",
"Congress.\n",
"reduction\n",
"of\n",
"Senators.\n",
"C;\n",
"garchy.\n",
"lunatics.\n",
"sale.\n",
"work.\n",
"1860.\n",
"Toledo.\n",
"-I\n",
"her.\n",
"Magazine.\n",
"mind.\n",
"State.\n",
"McClurc.\n",
"view.\n",
"It.\n",
"laid\n",
"to-day.\n",
"coals.\"\n",
"health.”\n",
"forfeited.\n",
"people.\n",
"sioner.\n",
"tion.\n",
"Tehtiacan.\n",
"jear.\n",
"provisions.\n",
"prostration.\n",
"mented\n",
"neau.\n",
"rates.\n",
"TTVe-\n",
"properties.”\n",
"is\n",
"favo.-\n",
"Philadelphia.\n",
"ing\n",
"prices.\n",
"accident.\n",
"send\n",
"music.\n",
"$1200.\n",
"him.\n",
"appetites\n",
"shoes.\n",
"existence.\n",
"beginning.\n",
"fact.\n",
"food.\n",
"transportation.\n",
"forever!\n",
"otTer.\n",
"Plalnville-Farmingto-\n",
"3--\n",
"collision.\n",
"sentiment,\n",
"At^et\n",
"anoth\n",
"direction.\n",
"reduction,\n",
"service.\n",
"America,-\n",
"health.\n",
"sums.\n",
"good.\"\n",
"Plant\n",
"thing.\n",
"News.\n",
"no\n",
"Washington.\n",
"Times.\n",
"Democratic\n",
"prevailed.\n",
"agreement.\n",
"specially\n",
"allowed.\n",
"we\n",
"treated.\n",
"d«ir\n",
"connection.\n",
"irvnn.\n",
"offer.\n",
"ways.\n",
"st\n",
"summit.\n",
"men.\n",
"trade.\n",
"injured.\n",
"branch\n",
"case.\n",
"night.\n",
"ibute.\n",
"e\n",
"lf\n",
"power.\n",
"simple\n",
"ths\n",
"world.''\n",
"ini-\n",
"with\n",
".\n",
"surface.\"\n",
"men.\"\n",
"Nome.\n",
"things.\"\n",
"Hie\n",
"Mountain.\n",
"1858.\n",
"wishes\n",
"damages.\n",
"settlement.\"\n",
"________\n",
"Y.\n",
"sermons.\n",
"costs.\n",
"contain.\n",
"uncertain.\n",
"delay.\n",
"cheese\n",
"we\n",
"A\n",
"homes.\n",
"-\n",
"button.\n",
"fate.\n",
"n\n",
"district.\n",
"up.\n",
"said:\n",
"other.\n",
"latter.\n",
"lat*\n",
"de-\n",
"c\n",
"off.\"\n",
"1874.\"\n",
"t.\n",
"on\n",
"the-\n",
"proposed.\n",
"#\n",
"distance.\n",
"will.\n",
"rooms.\n",
"paid\n",
"suggest-th-\n",
"oligarchy.\n",
"sea.\n",
"rt\n",
"eleven\n",
"tion.\n",
"recent\n",
"information.\n",
"otllcliils.\n",
"shock.\n",
"home.\n",
"Kensington.\n",
"heart.\n",
"by\n",
"place.\n",
"Equalization.\n",
"Parker.\n",
"come.\n",
"upon.\n",
"yours,\n",
"placed\n",
"and\n",
"elections.\n",
"tices.\n",
"Louis,\n",
"supply.\n",
"Taft.\n",
"days.\n",
"Tuttle\n",
"common\n",
"voices\n",
".\n",
"avail.\n",
"siasm.\n",
"<\n",
"sup*\n",
"navies\n",
"things.\"\n",
"safety.\n",
"my-\n",
"-\n",
"follows:\n",
"rub.\n",
"effected.\n",
"nation.”\n",
"her.\n",
"street,\n",
"ena-\n",
"date.\n",
"nnd\n",
"Informants.\n",
"Porter,\n",
"mad.\n",
"vengeance.\n",
"l._\n",
"you.\n",
"railroad\n",
"iuy\n",
"considered.\n",
"storm.\n",
"qualities.\n",
"Monday.\n",
"let-\n",
"and\n",
"Newark.\n",
"at-\n",
"vote.\n",
"all.\n",
"industries.\n",
"ama.\n",
"nations,\n",
"e\n",
"city.\n",
"the.GMeeï\n",
"don't\n",
"w\n",
"started\n",
"effected.\n",
"Ohio.\n",
"systun.\n",
"i\n",
"armies\n",
"and\n",
"family.\n",
"Is\n",
"sleep.\n",
"Bazar.\n",
"the\n",
"Lodge,\n",
"consumption.\n",
"no\n",
"St\n",
"puzzler.\n",
"repaired.\n",
"\"\n",
"organs\n",
"long\n",
"time.\n",
"important.\n",
"terms.\n",
"n-\n",
"can\n",
"\\\\\n",
"his\n",
"som--\n",
"street.\n",
"a\n",
"law.\n",
";\n",
"pa;\n",
"\"setback.\"\n",
"waters.\n",
"naked\n",
"unskilled\n",
"generally.\n",
"bier.\"\n",
"Us.”\n",
"land\n",
"rroiirl«torofferi«.\n",
"values.\n",
"left.\n",
"3\n",
"file.\n",
"observed.''\n",
"ring.\n",
"president.\n",
"i3.\n",
"them.\n",
"wbicn\n",
"year.\n",
"us.\n",
"phalanx\n",
"bow.\n",
"j\n",
"afterward.\"\n",
"Liens.\n",
"Congress.\n",
"yore.\n",
":\n",
"HUH.\n",
"ger.\n",
"intellectual\n",
"onions.\n",
"possible.'\n",
"be.\n",
"»SS».\n",
"\"\n",
"Titus.\n",
"conspirators.\n",
"toys,\n",
"de-\n",
"7414\n"
]
}
],
"source": [
"\n",
"with lzma.open(test_file, 'rt') as file:\n",
" predict_words = []\n",
" results = []\n",
" for line in file:\n",
"# print(line)\n",
" line = preprocess(line) #get only relevant\n",
" split = line.split('\\t')\n",
" print(get_last_word(split[0]))\n",
" predict_words.append(get_last_word(split[0])) #get_first_word(split[1])\n",
" print(len(predict_words))\n",
" vocab = train_dataset.vocab\n",
" for presc_word in predict_words:\n",
" results.append(dict(get_values_from_model(presc_word, model, vocab, k=k)))\n",
" \n",
" \n",
" with open(out_file, 'w') as outfile:\n",
" for elem in results:\n",
" \n",
" outfile.write(gonito_format(elem))\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"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": "3.10.6"
},
"org": null
},
"nbformat": 4,
"nbformat_minor": 1
}
Reference in New Issue View Git Blame Copy Permalink