5.0 MiB
5.0 MiB
train_file ='train/in.tsv.xz'
test_file = 'dev-0/in.tsv.xz'
out_file = 'dev-0/out.tsv'
from itertools import islice
import regex as re
import sys
from torchtext.vocab import build_vocab_from_iterator
import lzma
import pickle
import re
import torch
from torch import nn
from torch.utils.data import IterableDataset
import itertools
from torch.utils.data import DataLoader
import yaml
epochs = 3
embed_size = 200
device = 'cuda'
vocab_size = 30000
batch_s = 1600
learning_rate = 0.01
k = 20 #top k words
wildcard_minweight = 0.01
params = {
'epochs': 3,
'embed_size': 100,
'device': 'cuda',
'vocab_size': 30000,
'batch_size': 3200,
'learning_rate': 0.0001,
'k': 15, #top k words
'wildcard_minweight': 0.01
}
params = yaml.load(open('config/params.yaml'))
#then, entire code should go about those params with params[epochs] etc
/tmp/ipykernel_37433/1141171476.py:1: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. params = yaml.load(open('config/params.yaml'))
params
{'epochs': 3, 'embed_size': 100, 'device': 'cuda', 'vocab_size': 30000, 'batch_size': 3200, 'learning_rate': 0.0001, 'k': 15, 'wildcard_minweight': 0.01}
def get_words_from_line(line):
line = line.rstrip()
yield '<s>'
line = preprocess(line)
for t in line.split(' '):
yield t
yield '</s>'
def get_word_lines_from_file(file_name):
n = 0
with lzma.open(file_name, 'r') as fh:
for line in fh:
n+=1
if n%1000==0:
print(n)
yield get_words_from_line(line.decode('utf-8'))
def look_ahead_iterator(gen):
prev2 = None
prev1 = None
for item in gen:
if prev2 is not None and prev1 is not None:
yield (prev2, prev1, item)
prev2 = prev1
prev1 = item
class Trigrams(IterableDataset):
def __init__(self, text_file, vocabulary_size):
self.vocab = build_vocab_from_iterator(
get_word_lines_from_file(text_file),
max_tokens = vocabulary_size,
specials = ['<unk>'])
self.vocab.set_default_index(self.vocab['<unk>'])
self.vocabulary_size = vocabulary_size
self.text_file = text_file
def __iter__(self):
return look_ahead_iterator(
(self.vocab[t] for t in itertools.chain.from_iterable(get_word_lines_from_file(self.text_file))))
vocab = build_vocab_from_iterator(
get_word_lines_from_file(train_file),
max_tokens = params['vocab_size'],
specials = ['<unk>'])
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with open('filename.pickle', 'wb') as handle:
pickle.dump(vocab, handle, protocol=pickle.HIGHEST_PROTOCOL)
with open('filename.pickle','rb') as handle:
vocab = pickle.load(handle)
train_dataset = Trigrams(train_file, params['vocab_size'])
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data = DataLoader(train_dataset, batch_size=params['batch_size']) #load data
class SimpleTrigramNeuralLanguageModel(nn.Module):
def __init__(self, vocabulary_size, embedding_size):
super(SimpleTrigramNeuralLanguageModel, self).__init__()
self.embeddings = nn.Embedding(vocabulary_size, embedding_size)
self.linear = nn.Linear(2*embedding_size, vocabulary_size)
self.linear_matrix_2 = nn.Linear(embedding_size*2, embedding_size*2)
self.relu = nn.ReLU()
self.softmax = nn.Softmax()
#for each word in vocabulary theres a separate embedding vector, consisting of embedding_size entries
#self.linear is linear layer consisting of concatenated embeddings of left, and right context words
#self.linear_matrix_2 is linear layer
def forward(self, x): #x is list of prev and following embeddings
emb_left = self.embeddings(x[0])
emb_right = self.embeddings(x[1])
#create two embeddings vectors, for word before and after, respectively
first_layer_size_2 = self.linear_matrix_2(torch.cat((emb_left, emb_right), dim=1))
first_relu = self.relu(first_layer_size_2)
concated = self.linear(first_relu)
out = self.softmax(concated)
return out
import gc
torch.cuda.empty_cache()
gc.collect()
0
device = 'cuda'
model = SimpleTrigramNeuralLanguageModel(params['vocab_size'], params['embed_size']).to(device)
optimizer = torch.optim.Adam(model.parameters(), lr=params['learning_rate'])
criterion = torch.nn.NLLLoss()
torch.autograd.set_detect_anomaly(True)
model.load_state_dict(torch.load(f'model-tri-2following-40000.bin'))
for i in range(params['epochs']):
print('epoch: =', i)
model.train()
step = 0
for x, y, z in data: # word, following, 2nd_following words
x = x.to(device)
y = y.to(device)
z = z.to(device)
optimizer.zero_grad()
ypredicted = model([y, z]) #following, 2nd_following word
loss = criterion(torch.log(ypredicted), x) #x is to_predict
if step % 100 == 0:
print(step, loss)
step += 1
# if step % 10000 == 0:
# torch.save(model.state_dict(), f'model-tri-2following-{step}.bin')
loss.backward()
optimizer.step()
# torch.save(model.state_dict(), f'model-tri-2following-{i}.bin')
# torch.save(model.state_dict(), f'model-tri-2following-final.bin')
epoch: = 0 0 tensor(5.3414, device='cuda:0', grad_fn=<NllLossBackward0>)
/tmp/ipykernel_37433/606935597.py:22: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument. out = self.softmax(concated)
1000 100 tensor(5.4870, device='cuda:0', grad_fn=<NllLossBackward0>) 200 tensor(5.3542, device='cuda:0', grad_fn=<NllLossBackward0>) 2000 300 tensor(5.3792, device='cuda:0', grad_fn=<NllLossBackward0>) 3000 400 tensor(5.5982, device='cuda:0', grad_fn=<NllLossBackward0>) 4000 500 tensor(5.4045, device='cuda:0', grad_fn=<NllLossBackward0>) 5000 600 tensor(5.5620, device='cuda:0', grad_fn=<NllLossBackward0>) 6000 700 tensor(5.5428, device='cuda:0', grad_fn=<NllLossBackward0>) 7000 800 tensor(5.3684, device='cuda:0', grad_fn=<NllLossBackward0>) 8000 900 tensor(5.4198, device='cuda:0', grad_fn=<NllLossBackward0>) 9000 1000 tensor(5.4100, device='cuda:0', grad_fn=<NllLossBackward0>) 10000 1100 tensor(5.4554, device='cuda:0', grad_fn=<NllLossBackward0>) 11000 1200 tensor(5.5284, device='cuda:0', grad_fn=<NllLossBackward0>) 12000 1300 tensor(5.5495, device='cuda:0', grad_fn=<NllLossBackward0>)
/home/gedin/.local/lib/python3.10/site-packages/torch/autograd/__init__.py:200: UserWarning: Error detected in LogBackward0. Traceback of forward call that caused the error: File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "/usr/lib/python3.10/runpy.py", line 86, in _run_code exec(code, run_globals) File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel_launcher.py", line 17, in <module> app.launch_new_instance() File "/home/gedin/.local/lib/python3.10/site-packages/traitlets/config/application.py", line 1043, in launch_instance app.start() File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/kernelapp.py", line 725, in start self.io_loop.start() File "/home/gedin/.local/lib/python3.10/site-packages/tornado/platform/asyncio.py", line 195, in start self.asyncio_loop.run_forever() File "/usr/lib/python3.10/asyncio/base_events.py", line 600, in run_forever self._run_once() File "/usr/lib/python3.10/asyncio/base_events.py", line 1896, in _run_once handle._run() File "/usr/lib/python3.10/asyncio/events.py", line 80, in _run self._context.run(self._callback, *self._args) File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/kernelbase.py", line 513, in dispatch_queue await self.process_one() File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/kernelbase.py", line 502, in process_one await dispatch(*args) File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/kernelbase.py", line 409, in dispatch_shell await result File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/kernelbase.py", line 729, in execute_request reply_content = await reply_content File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/ipkernel.py", line 422, in do_execute res = shell.run_cell( File "/home/gedin/.local/lib/python3.10/site-packages/ipykernel/zmqshell.py", line 540, in run_cell return super().run_cell(*args, **kwargs) File "/home/gedin/.local/lib/python3.10/site-packages/IPython/core/interactiveshell.py", line 3009, in run_cell result = self._run_cell( File "/home/gedin/.local/lib/python3.10/site-packages/IPython/core/interactiveshell.py", line 3064, in _run_cell result = runner(coro) File "/home/gedin/.local/lib/python3.10/site-packages/IPython/core/async_helpers.py", line 129, in _pseudo_sync_runner coro.send(None) File "/home/gedin/.local/lib/python3.10/site-packages/IPython/core/interactiveshell.py", line 3269, in run_cell_async has_raised = await self.run_ast_nodes(code_ast.body, cell_name, File "/home/gedin/.local/lib/python3.10/site-packages/IPython/core/interactiveshell.py", line 3448, in run_ast_nodes if await self.run_code(code, result, async_=asy): File "/home/gedin/.local/lib/python3.10/site-packages/IPython/core/interactiveshell.py", line 3508, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "/tmp/ipykernel_37433/1707264841.py", line 13, in <module> loss = criterion(torch.log(ypredicted), x) #x is to_predict (Triggered internally at ../torch/csrc/autograd/python_anomaly_mode.cpp:114.) Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[0;31m---------------------------------------------------------------------------[0m [0;31mRuntimeError[0m Traceback (most recent call last) Cell [0;32mIn[26], line 19[0m [1;32m 16[0m step [38;5;241m+[39m[38;5;241m=[39m [38;5;241m1[39m [1;32m 17[0m [38;5;66;03m# if step % 10000 == 0:[39;00m [1;32m 18[0m [38;5;66;03m# torch.save(model.state_dict(), f'model-tri-2following-{step}.bin')[39;00m [0;32m---> 19[0m [43mloss[49m[38;5;241;43m.[39;49m[43mbackward[49m[43m([49m[43m)[49m [1;32m 20[0m optimizer[38;5;241m.[39mstep() [1;32m 21[0m [38;5;66;03m# torch.save(model.state_dict(), f'model-tri-2following-{i}.bin') [39;00m [1;32m 22[0m [38;5;66;03m# torch.save(model.state_dict(), f'model-tri-2following-final.bin')[39;00m File [0;32m~/.local/lib/python3.10/site-packages/torch/_tensor.py:487[0m, in [0;36mTensor.backward[0;34m(self, gradient, retain_graph, create_graph, inputs)[0m [1;32m 477[0m [38;5;28;01mif[39;00m has_torch_function_unary([38;5;28mself[39m): [1;32m 478[0m [38;5;28;01mreturn[39;00m handle_torch_function( [1;32m 479[0m Tensor[38;5;241m.[39mbackward, [1;32m 480[0m ([38;5;28mself[39m,), [0;32m (...)[0m [1;32m 485[0m inputs[38;5;241m=[39minputs, [1;32m 486[0m ) [0;32m--> 487[0m [43mtorch[49m[38;5;241;43m.[39;49m[43mautograd[49m[38;5;241;43m.[39;49m[43mbackward[49m[43m([49m [1;32m 488[0m [43m [49m[38;5;28;43mself[39;49m[43m,[49m[43m [49m[43mgradient[49m[43m,[49m[43m [49m[43mretain_graph[49m[43m,[49m[43m [49m[43mcreate_graph[49m[43m,[49m[43m [49m[43minputs[49m[38;5;241;43m=[39;49m[43minputs[49m [1;32m 489[0m [43m[49m[43m)[49m File [0;32m~/.local/lib/python3.10/site-packages/torch/autograd/__init__.py:200[0m, in [0;36mbackward[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)[0m [1;32m 195[0m retain_graph [38;5;241m=[39m create_graph [1;32m 197[0m [38;5;66;03m# The reason we repeat same the comment below is that[39;00m [1;32m 198[0m [38;5;66;03m# some Python versions print out the first line of a multi-line function[39;00m [1;32m 199[0m [38;5;66;03m# calls in the traceback and some print out the last line[39;00m [0;32m--> 200[0m [43mVariable[49m[38;5;241;43m.[39;49m[43m_execution_engine[49m[38;5;241;43m.[39;49m[43mrun_backward[49m[43m([49m[43m [49m[38;5;66;43;03m# Calls into the C++ engine to run the backward pass[39;49;00m [1;32m 201[0m [43m [49m[43mtensors[49m[43m,[49m[43m [49m[43mgrad_tensors_[49m[43m,[49m[43m [49m[43mretain_graph[49m[43m,[49m[43m [49m[43mcreate_graph[49m[43m,[49m[43m [49m[43minputs[49m[43m,[49m [1;32m 202[0m [43m [49m[43mallow_unreachable[49m[38;5;241;43m=[39;49m[38;5;28;43;01mTrue[39;49;00m[43m,[49m[43m [49m[43maccumulate_grad[49m[38;5;241;43m=[39;49m[38;5;28;43;01mTrue[39;49;00m[43m)[49m [0;31mRuntimeError[0m: Function 'LogBackward0' returned nan values in its 0th output.
torch.save(model.state_dict(), f'model-tri-2following-final.bin')
def get_first_word(text):
"""Return the first word of a string."""
word = ""
for i in range(len(text)-1):
# if text[i] in [' ', ',', '.']
if text[i] == ' ':
return word.rstrip()
else:
word += text[i]
return word.rstrip()
def get_values_from_model(context: list, model, vocab, k=10):
words = [vocab.forward([word]) for word in context]
ixs = torch.tensor(words).to(device)
out = model(ixs)
top = torch.topk(out[0], k)
top_indices = top.indices.tolist()
top_probs = top.values.tolist()
top_words = vocab.lookup_tokens(top_indices)
return list(zip(top_words, top_probs))
def summarize_probs_unk(dic, const_wildcard=True):
'''
dic: dictionary of probabilities returned by model
returns: tab of probabilities, with <unk> specificly as last element
'''
if const_wildcard or '<unk>' not in dic.keys():
if '<unk>' in dic.keys():
del dic['<unk>']
probsum = sum(float(val) for key, val in dic.items())
for key in dic:
dic[key] = dic[key]/probsum*(1-wildcard_minweight) ###leave some space for wildcard
tab = [(key, val) for key, val in dic.items()]
tab.append(('<unk>', wildcard_minweight))
else:
probsum = sum(float(val) for key, val in dic.items())
for key in dic:
dic[key] = dic[key]/probsum*(1-wildcard_minweight) ###leave some space for wildcard
wildcard_value = dic['<unk>']
del dic['<unk>']
tab = [(key, val) for key, val in dic.items()]
tab.append(('<unk>', wildcard_value))
return tab
def gonito_format(dic, const_wildcard = True):
tab = summarize_probs_unk(dic, const_wildcard)
result = ''
for element in tab[:-1]:
result+=str(element[0])+':'+str(element[1])+'\t'
result+=':'+ str(tab[-1][1]) + '\n'
return result
###preprocessing
def preprocess(line):
line = get_rid_of_header(line)
line = replace_endline(line)
return line
def get_rid_of_header(line):
line = line.split('\t')[6:]
return " ".join(line)
def replace_endline(line):
line = line.replace("\\\\n", " ")
return line
ixs = torch.tensor([vocab.forward(['met']), vocab.forward(['the'])]).to(device)
out = model(ixs)
top = torch.topk(out[0], 10)
top_indices = top.indices.tolist()
top_probs = top.values.tolist()
top_words = vocab.lookup_tokens(top_indices)
list(zip(top_words, top_indices, top_probs))
/tmp/ipykernel_4654/606935597.py:22: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument. out = self.softmax(concated)
[('<unk>', 0, 0.09396536648273468), ('he', 20, 0.06469981372356415), ('I', 25, 0.05796860530972481), ('have', 28, 0.03896494582295418), ('had', 35, 0.03859648108482361), ('who', 46, 0.03718526288866997), ('and', 3, 0.03539585694670677), ('we', 51, 0.028498027473688126), ('they', 41, 0.027544576674699783), ('has', 36, 0.02714056707918644)]
model.load_state_dict(torch.load(f'model-tri-2following-final.bin'))
<All keys matched successfully>
with lzma.open(test_file, 'rt') as file:
predict_words = []
results = []
for line in file:
line = replace_endline(line) #get only relevant
line = line.split('\t')[6:]
context = line[1].rstrip().split(" ")[:2]
predict_words.append(context) #get_first_word(split[1cd
vocab = train_dataset.vocab
for context_words in predict_words:
results.append(dict(get_values_from_model(context_words, model, vocab, k=10)))
with open(out_file, 'w') as outfile:
for elem in results:
outfile.write(gonito_format(elem, const_wildcard=True))
/tmp/ipykernel_4654/606935597.py:22: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument. out = self.softmax(concated)
results = list(results)
print(results)
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0.05791188730775565, 'must': 0.03736759196683877, 'not': 0.03732847217089754, 'can': 0.022563579465426035}, {'for': 0.29880295097886284, 'of': 0.23521417875690956, 'in': 0.10120854908978043, 'and': 0.08756899169941268, 'about': 0.037516559020850264, 'or': 0.0373172381005537, 'the': 0.034009964763976025, 'In': 0.026186487549353755, 'with': 0.024273471498715463}, {'away': 0.0679735989764273, 'and': 0.06486700873008125, 'came': 0.06416702814193669, 'miles': 0.048245404529676864, 'come': 0.0381726122640827, 'taken': 0.03568621456041879, 'up': 0.03327777259285882, 'feet': 0.03239676598620461, 'him': 0.028186941122704444}, {'and': 0.15583586102196975, 'but': 0.0531878422272761, 'of': 0.042633036675895505, 'so': 0.04255053735048843, 'that': 0.033070532170823404, 'as': 0.03206741431304825, 'all': 0.02912100233701174, 'is': 0.02489494115539264, 'fact': 0.024004004711740523}, {'a': 0.6049586850989631, 'the': 0.10837557392100772, 'A': 0.07504596716557109, 'certain': 0.024518602042049656, 'one': 0.024477810850675817, 'described': 0.016462957670037245, 'every': 0.015454334616557961, 'large': 0.01458455104623642, 'this': 0.014284522825975032}, {'the': 0.21195178259180028, 'and': 0.14779761286609255, 'a': 0.1086663106626236, 'all': 0.09157946913620676, 'these': 0.06045425371261992, 'or': 0.045888408726680596, 'These': 0.040993793901491486, 'that': 0.0400303305553942, 'of': 0.03786876773315876}, {'and': 0.10374866557881515, 'to': 0.07894435680409345, 'of': 0.05311400426784597, 'the': 0.046994634518881806, 'which': 0.028593217248287985, 'that': 0.02740946640045343, 're-': 0.02403737335499887, 'in': 0.02399436233146011, 'for': 0.02338838299982415}, {'ten': 0.11176147059106618, '10': 0.10201644629749677, '50': 0.09568995253336776, 'fifty': 0.09217512657187875, '20': 0.07315968177888976, 'three': 0.05765254819170143, 'five': 0.057025423977026306, '25': 0.05311566123049631, '5': 0.05194525932914015}, {'they': 0.1526364760205744, 'who': 0.0734903762880743, 'there': 0.06796953496356017, 'we': 0.06675967996448004, 'which': 0.051515065498583236, 'and': 0.04885033962872441, 'you': 0.04459834097877737, 'There': 0.03870682391240855, 'They': 0.03657499609252005}, {'made': 0.11823418626004677, 'and': 0.0789977476665022, 'caused': 0.02880030290591601, 'shown': 0.028142486758012716, 'up': 0.027498938630273775, 'ed': 0.027340908793671036, 'out': 0.026363857841631404, 'taken': 0.02600336957321174, 'done': 0.025174220994246873}, {'of': 0.4406759278670095, 'to': 0.10901582374751623, 'in': 0.08223775706096222, 'by': 0.07235949351281654, 'and': 0.062035605301096156, 'that': 0.052927195000574204, 'for': 0.044779295998827635, 'with': 0.02981627094826492, 'from': 0.021882852202500767}, {'on': 0.18822380851794948, 'of': 0.18550294693602234, 'and': 0.13775550986075136, 'to': 0.09290377430568626, 'On': 0.08422691802573472, 'all': 0.05560600372835125, 'with': 0.053992266041829225, 'in': 0.051745693465751676, 'that': 0.04239106999069966}, {'the': 0.5523771878034239, 'a': 0.2109009255690132, 'The': 0.07953556821219258, 'tho': 0.03724424548072484, 'of': 0.01928170861091495, 'and': 0.01602299243018358, 'our': 0.013849683476314477, 'that': 0.011975640491550883, 'A': 0.011817065024800861}, {'of': 0.30055091846439536, 'in': 0.1012831941133368, 'to': 0.1004160622839226, 'for': 0.09722509092516014, 'with': 0.08024296354614054, 'and': 0.04987863673701685, 'by': 0.04431325748041365, 'from': 0.04202419208775427, 'at': 0.037434597071017484}, {'hundred': 0.014297493055956937, ';': 0.011716326943571356, 'him': 0.010284589058729107, 'one': 0.009592078784322543, 'feet': 0.009461243780120606, 'up': 0.008791389241780788, 'mile': 0.00789364634221846, 'feet,': 0.007530166543155784, 'time': 0.007214592318027827}, {'is': 0.38520148421124667, 'was': 0.1234155928280963, 'he': 0.07416500653831193, 'and': 0.07102494542231634, 'be': 0.06626103178757331, 'Is': 0.0648126617177738, 'I': 0.06035624029529363, 'He': 0.0517554132922303, 'are': 0.04671551368202216, 'generally': 0.04629211022513552}, {'covered': 0.05327819432327435, 'and': 0.04717958233299251, 'filled': 0.033868125000495415, 'up': 0.02696031276814869, 'it': 0.016883759373213916, 'made': 0.016768752181766804, 'together': 0.012706641528155477, 'loaded': 0.012500149147626462, 'trimmed': 0.011281706361580743}, {'and': 0.0941004168750069, 'days': 0.05796086974782947, 'was': 0.05522297741294859, 'or': 0.04407822092225418, 'time': 0.0435884420075973, 'that': 0.042897300417212854, 'never': 0.040325237062531556, 'long': 0.03994520629830473, 'be': 0.037416175620997257}, {'a': 0.48554591941583286, 'the': 0.1436223933771941, 'young': 0.06341823487224103, 'that': 0.03203687862172138, 'of': 0.029706816448486998, 'any': 0.02752553897274009, 'every': 0.023821254749299005, 'old': 0.02213054762902863, 'white': 0.01924067046758059}, {'of': 0.18010136763568654, 'in': 0.11739699790840726, 'for': 0.09920190770589164, 'to': 0.08960534741711827, 'with': 0.08137629733689157, 'and': 0.06998737387314882, 'by': 0.06545482944112892, 'was': 0.058302830235176836, 'is': 0.05592669998837037}, {'of': 0.1582559933891888, 'the': 0.09407817952359815, 'in': 0.057873491356385934, 'and': 0.04702176872006862, 'that': 0.03743136021928463, 'to': 0.031011104865684532, 'The': 0.026454772604923092, 'for': 0.022924280922302677, 'Mr.': 0.019774204214003416}, {'the': 0.22002078442885264, 'and': 0.0978652377545059, 'of': 0.09237163457148333, 'this': 0.03546410067784806, 'or': 0.023805728874019758, 'that': 0.023421207510896738, 'The': 0.023292480177525502, 'an': 0.02070409101105062, 'a': 0.020595237317112682}, {'the': 0.44066522970800676, 'on': 0.1521561708271809, 'a': 0.06011912152885559, 'in': 0.056949306160646244, 'of': 0.046204487871766904, 'said': 0.04259887839550075, 'this': 0.030406938455862037, 'tho': 0.027985719690233002, 'his': 0.023188850913156932}, {'of': 0.10776331440563258, '.': 0.06887448943766818, 'to': 0.06332695733813179, '&': 0.05286010783975914, '<s>': 0.03804834674430753, 'at': 0.034192202108931154, 'and': 0.03403734752795568, 'the': 0.02434677228994448, 'from': 0.02133187286475779}, {'to': 0.5637638327797678, 'I': 0.09724982986394734, 'and': 0.08884305548927114, 'not': 0.04731483442700547, 'will': 0.036577971819677965, 'would': 0.023645230214079903, 'you': 0.022939302852635887, 'should': 0.02062486187056683, 'we': 0.019238071390510408}, {'it': 0.1809100698164205, 'they': 0.09292308780786662, 'as': 0.09158354830523434, 'It': 0.08467492316292669, 'which': 0.07203260002234574, 'that': 0.05969967202048104, 'he': 0.053577596284784215, 'and': 0.045662859511485396, 'you': 0.04553454468153112}, {'the': 0.37256744284446697, 'of': 0.09254578616504334, 'a': 0.06852873988182347, 'and': 0.05870324008750741, 'to': 0.04089003122517616, 'in': 0.03216461595683171, 'tho': 0.021153992970400843, 'The': 0.016884419846065694, 'or': 0.014871176413326264}, {'they': 0.16211713451616194, 'there': 0.10364499156602504, 'There': 0.07822147948358303, 'we': 0.07007789537849672, 'who': 0.06532497812126191, 'and': 0.06270851911061485, 'They': 0.04343146986079208, 'which': 0.036684619569670396, 'you': 0.03543630638979793}, {'of': 0.10398904370693374, 'the': 0.08394355307891771, 'and': 0.05449271790887418, 'in': 0.04771367310837412, 'to': 0.046082842951780605, 'a': 0.040347548217566705, 'be': 0.023013223213841378, 'for': 0.022544300513585993, 'was': 0.020049460156710927}, {'and': 0.10374866557881515, 'to': 0.07894435680409345, 'of': 0.05311400426784597, 'the': 0.046994634518881806, 'which': 0.028593217248287985, 'that': 0.02740946640045343, 're-': 0.02403737335499887, 'in': 0.02399436233146011, 'for': 0.02338838299982415}, {'the': 0.3594175899301673, 'a': 0.09291103349672013, 'of': 0.0634050648876147, 'The': 0.05217027650011919, 'and': 0.03668418008460235, 'tho': 0.03360635862324214, 'his': 0.02248112715506704, 'our': 0.02208122354222172, 'to': 0.020189935922263848}, {'the': 0.19442491530078018, 'his': 0.1474380322620141, 'of': 0.13038289458929453, 'and': 0.1017352971719862, 'their': 0.07907611022652392, 'to': 0.058883837829108936, 'my': 0.052370164391239905, 'with': 0.04864551682544399, 'her': 0.04178545631982414}, {'and': 0.10374866557881515, 'to': 0.07894435680409345, 'of': 0.05311400426784597, 'the': 0.046994634518881806, 'which': 0.028593217248287985, 'that': 0.02740946640045343, 're-': 0.02403737335499887, 'in': 0.02399436233146011, 'for': 0.02338838299982415}, {'is': 0.09425654696090477, 'and': 0.06420615503990568, 'was': 0.04812966316028736, 'simply': 0.04545945708344311, 'not': 0.04113121313293958, 'it': 0.03838416179614672, 'but': 0.024524819092946747, 'that': 0.019357954647456974, 'it,': 0.017386137124468872}, {'and': 0.12370942622396933, 'of': 0.10031615253897223, 'to': 0.08379626910040477, 'the': 0.07838319077632402, 'on': 0.030474003467624057, 'in': 0.03046767298180709, '<s>': 0.027023968557944873, 'that': 0.02560546517887483, 'from': 0.021982516781050954}, {'and': 0.10374866557881515, 'to': 0.07894435680409345, 'of': 0.05311400426784597, 'the': 0.046994634518881806, 'which': 0.028593217248287985, 'that': 0.02740946640045343, 're-': 0.02403737335499887, 'in': 0.02399436233146011, 'for': 0.02338838299982415}, {'be': 0.28820107634587366, 'was': 0.1376861657767604, 'been': 0.10973700645050177, 'is': 0.07447944290333641, 'and': 0.05474693936062983, 'were': 0.05241143707937301, 'are': 0.05091640398885752, 'being': 0.032349791287590815, 'he': 0.01972716886121003}, {'the': 0.3496437471110996, 'such': 0.087363836035252, 'these': 0.060097759658854485, 'best': 0.05329728299714431, 'his': 0.05121436336594276, 'our': 0.048054608040942144, 'other': 0.04799256187050334, 'business': 0.047331254361942306, 'their': 0.04624458588492853}, {';': 0.053647131015120614, 'it,': 0.021112187845918465, 'him,': 0.0141396237568865, 'and': 0.013326708890879072, 'is': 0.012436374957192317, 'them,': 0.010568221538485939, 'time,': 0.010213841685748364, ',': 0.006801416280472233, 'nothing': 0.006512847852575416}, {'the': 0.195398314687806, 'a': 0.15774091434179371, 'of': 0.10967706689635727, 'and': 0.06741656424559908, 'at': 0.046491919400976654, 'to': 0.04629568349165812, 'in': 0.036089949811656884, 'for': 0.03251502567997375, 'an': 0.023676279315906903}, {'to': 0.19112264078135405, 'I': 0.163563399358123, 'would': 0.09659749437148875, 'we': 0.09421220256007046, 'they': 0.08928246540265528, 'who': 0.07773544000171703, 'could': 0.0620484044376064, 'must': 0.057561736239765786, 'should': 0.05076921186044456}, {'to': 0.7125930962735687, 'not': 0.058433225980668864, 'will': 0.04850477002995723, 'would': 0.04116417065937847, 'and': 0.02998861843430332, 'can': 0.022760309309053893, 'may': 0.02125455501301959, 'could': 0.018330643151309087, 'To': 0.01644334539941386}, {'a': 0.4704942920077657, 'the': 0.2918964316893771, 'The': 0.04411878236980895, 'of': 0.03568369735529486, 'his': 0.027132592160400603, 'this': 0.025599330296284268, 'any': 0.022061251948951154, 'A': 0.01949431381091716, 'no': 0.01741830382704421}, {'the': 0.13076105450013367, 'of': 0.07932046947702465, 'and': 0.06342011000830029, 'a': 0.04719279250755952, 'to': 0.03434272517566016, 'in': 0.02287173009664328, 'at': 0.01565478400803208, '.': 0.013742326351524834, '<s>': 0.013617783682502283}, {'part': 0.07196025971506713, 'one': 0.07000355279264338, 'some': 0.04307302051471967, 'out': 0.035392916858036194, 'members': 0.02550305881294491, 'and': 0.022215776852222372, 'tion': 0.0216911631781865, 'portion': 0.020842143848213566, 'side': 0.020717751768984743}, {'to': 0.5068158114110013, 'will': 0.10942208005303328, 'and': 0.08660151037093049, 'would': 0.061040409632925875, 'not': 0.041926384722674605, 'I': 0.028237709645744367, 'could': 0.022623315708161486, 'they': 0.02199346958920226, 'we': 0.020081939693797277}, {'and': 0.10374866557881515, 'to': 0.07894435680409345, 'of': 0.05311400426784597, 'the': 0.046994634518881806, 'which': 0.028593217248287985, 'that': 0.02740946640045343, 're-': 0.02403737335499887, 'in': 0.02399436233146011, 'for': 0.02338838299982415}, {'be': 0.19837397734669796, 'was': 0.19332705535905054, 'been': 0.128607633019512, 'is': 0.07349528236667124, 'were': 0.07295922889563712, 'and': 0.061156946771258436, 'Action': 0.056895786256212055, 'are': 0.049190682316400614, 'being': 0.03507153777962458}, {'of': 0.25459997162291187, 'in': 0.12454060740427482, 'to': 0.11577494447504205, 'for': 0.09147832614164343, 'and': 0.08163300447693299, 'at': 0.06314948975773016, 'with': 0.05062750492712211, 'by': 0.04326022434400931, 'from': 0.041387187628682785}, {'of': 0.2901092184395097, 'to': 0.1151989145878489, 'for': 0.10465278746982609, 'by': 0.07849215463819675, 'and': 0.07051994304796563, 'that': 0.06715960027976421, 'with': 0.05770812631797145, 'in': 0.05742574434678843, 'at': 0.03724045968567429}, {'had': 0.32781353385074047, 'have': 0.21074741528326482, 'has': 0.1274628046736833, 'was': 0.08114141849349137, 'be': 0.041028513592198126, 'been': 0.03926601445210578, 'and': 0.03874110965931702, 'were': 0.02476302272036118, 'he': 0.02353210406915849}, {'a': 0.7997003668472945, 'that': 0.036997345015831885, 'of': 0.026465388157290666, 'A': 0.02593377145285708, 'and': 0.022162228714508035, 'the': 0.018585022449008847, 'as': 0.012550619618988658, 'is': 0.010620290773649137, 'in': 0.009788574463724579}, {'more': 0.029519035443280186, 'due': 0.02754754160700531, 'public': 0.02534454228612663, 'good': 0.025339007119605534, 'in': 0.02440310410951072, 'time': 0.020142994793444242, 'it': 0.017278865133190182, 'risk': 0.017154588082171615, 'large': 0.015512658212836799}, {'the': 0.19473684077600603, 'of': 0.11914353719686512, 'a': 0.08353845808744192, 'to': 0.06932727805844617, 'and': 0.06218758340304158, 'be': 0.04485973874295811, 'in': 0.03346067556757769, 'is': 0.0318807376806023, 'not': 0.028897524413415428}, {'the': 0.3045364618598062, 'Supreme': 0.13320396463221834, 'District': 0.06625223541744862, 'said': 0.052519528136724024, 'Circuit': 0.0489173865750182, 'County': 0.041556894284942955, 'this': 0.030421969747549616, 'tho': 0.025752762464114832, 'of': 0.02219410967004564}, {'and': 0.08903943567055478, 'recorded': 0.03556921935003545, 'was': 0.03406255031302123, 'made': 0.032946556190601356, 'that': 0.03266426711779562, "o'clock": 0.029519677782270576, 'up': 0.02712379263357393, 'is': 0.024027854253131364, 'found': 0.023595246573781124}, {'the': 0.13908679504865662, 'of': 0.11018424169065659, 'and': 0.08819897668254238, 'to': 0.08229164611286616, 'a': 0.04169362818372944, 'be': 0.029216682148986695, 'or': 0.029131339800605442, 'his': 0.02429855075103291, 'on': 0.02238479204228481}, {'to': 0.3182472590091048, 'will': 0.12161080721986511, 'be-': 0.10632294261891069, 'had': 0.06950859491164059, 'has': 0.06528401096846545, 'have': 0.0637382064646983, 'not': 0.044969966880465416, 'would': 0.04271566582143969, 'I': 0.03632949682391563}]
for elem in results:
print(gonito_format(elem, const_wildcard=False), end='')
the:0.2075982821656445 of:0.18641195492052776 to:0.16375589974544083 and:0.1419768336902786 in:0.07235947734331605 a:0.058097948235152734 was:0.05579373084177645 be:0.05459636692777878 is:0.04940950613008435 :0.01 hundred:0.6757441672297904 dred:0.05507351954564642 eight:0.04366350604170379 degrees:0.04027646004808544 due:0.03587563285715768 north:0.035232990910443074 long:0.03521327274265905 men:0.03510510305220571 dollars:0.03381534757230845 :0.01 a:0.3910634709171287 the:0.3617063481722642 this:0.04575074218211916 other:0.04101326388674283 of:0.03622302244589748 and:0.0333782246961355 his:0.030199108590644053 The:0.027090666394293545 tho:0.023575152714774478 :0.01 it:0.17675553355714846 they:0.14081408629938666 and:0.1369251675661277 which:0.11277892922943723 he:0.10500778470392592 you:0.08516978500368706 It:0.08279808722888964 I:0.07644183587914444 who:0.07330879053225287 :0.01 able:0.16135098933162126 and:0.13044751689027728 order:0.12047644195204926 enough:0.11219570761860198 is:0.10659258286384826 him:0.09695424037295979 right:0.09323820669708727 was:0.0846236042426778 attempt:0.08412071003087702 :0.01 is:0.2784631131670363 be:0.2196228014885983 are:0.1428621781409449 was:0.11935922336568351 and:0.07678327398015508 been:0.040350769140349345 Is:0.038101361203158074 not:0.03740134506575619 were:0.03705593444831832 :0.01 and:0.32434810589817087 was:0.11832549081564547 held:0.10061653345026712 Beginning:0.08194282066246006 is:0.07787052591190631 look:0.07433840727139066 arrived:0.07348439933321943 that:0.0714853472708103 interest:0.06758836938612982 :0.01 and:0.2587876600214367 of:0.23664575608429053 is:0.09115271670092913 are:0.08347312003595064 it:0.08171945044538946 after:0.0791007002479149 in:0.06860735831467818 that:0.04611888559063895 was:0.044394352558771576 :0.01 of:0.37283592046886466 in:0.16738772624345097 and:0.10531868082220948 to:0.0830809911982244 with:0.0755945266870176 for:0.06860498426928782 that:0.044648284417965 In:0.038973812694768954 on:0.03355507319821109 :0.01 and:0.2819688105509132 that:0.2301418702249719 as:0.22505597689475598 but:0.06927514817526978 even:0.0553432991736943 or:0.03504039921417471 But:0.0347013310889262 And:0.029575321440918265 and,:0.028897843236375672 :0.01 the:0.3075460484664369 of:0.18655934707330316 and:0.14916218212617383 a:0.11099602176871066 to:0.08077305174479381 in:0.05379361798284004 at:0.03681957888509467 .:0.032321536273197685 <s>:0.032028615679449264 :0.01 the:0.6703324500442436 a:0.11290303879098454 be-:0.058279759387684996 The:0.04380947101890577 tho:0.03462946324204335 be¬:0.02023698384973438 be:0.0183781341280763 no:0.015831493411717704 and:0.015599206126609378 :0.01 of:0.2713041771166653 and:0.15897929210516643 to:0.12162346150241224 the:0.11747449277509675 for:0.07788114196389266 a:0.06946714391215615 be:0.06248668139168508 in:0.06238027507401627 was:0.048403334158909184 :0.01 <s>:0.24728533594793464 and:0.20253763753382348 made:0.0988615075741576 was:0.09538551140811594 recorded:0.07923243876425153 that:0.07572633810967984 be:0.06754695020072057 is:0.06282737303055098 o'clock:0.06059690743076549 :0.01 to:0.46053881942473246 and:0.10535183777274285 we:0.08865165438156905 I:0.07208324939001232 will:0.06869363719909811 not:0.065685400729279 would:0.05375849885166945 they:0.03833966692398743 you:0.036897235326909306 :0.01 and:0.24375788641111382 of:0.16889976715177063 to:0.13815148594694573 the:0.12733864558157276 <s>:0.07151276384945796 a:0.06478624793209892 his:0.0607373117827336 in:0.0592015500274423 at:0.05561434131686416 :0.01 of:0.41423916949970646 to:0.15132104071022856 and:0.10874929347751575 for:0.07131192514304915 with:0.07117782824129337 by:0.0641198672951466 that:0.03758189736686034 from:0.03750168565790937 on:0.033997292608290354 :0.01 and:0.26958579283201645 them:0.11612667884598861 put:0.11344325375628718 out:0.1013617992958137 carry:0.08227680625552684 was:0.07994197358382521 work:0.07720203559131127 it:0.07531599500828415 that:0.07474566483094668 :0.01 of:0.3241150061345983 and:0.1774251949735989 in:0.10544507048740555 to:0.10116454824675855 that:0.07659656642832684 on:0.06455299454022724 for:0.06273561211239223 things:0.04287039325002043 those:0.03509461382667204 :0.01 the:0.3075460484664369 of:0.18655934707330316 and:0.14916218212617383 a:0.11099602176871066 to:0.08077305174479381 in:0.05379361798284004 at:0.03681957888509467 .:0.032321536273197685 <s>:0.032028615679449264 :0.01 and:0.24738383723470325 of:0.19203822110083657 as:0.10987989596377462 that:0.09956181767917707 all:0.09205302262274494 but:0.08064260519657017 for:0.07500863673578351 so:0.05332938232021526 fact:0.04010258114619455 :0.01 to:0.3654474410099953 will:0.2003951863899563 not:0.09837915490302267 may:0.06278904609064165 the:0.05736604149022529 and:0.05539018039091507 shall:0.05437404002895165 a:0.04877939372652326 would:0.04707951596976878 :0.01 with-:0.14105775367139364 and:0.13434116781737443 find:0.13400974181205136 pointed:0.11694065988780132 go:0.10421914379622045 carry:0.10315983714917693 get:0.08609281170529563 brought:0.08534438894165561 went:0.08483449521903062 :0.01 and:0.18784336682063277 as:0.15114329179679575 went:0.11423878004667354 him:0.10666558228731275 them:0.09110223752457797 up:0.08733803455919151 is:0.0868948054425366 go:0.08340199801381315 able:0.08137190350846597 :0.01 and:0.2322863021107167 to:0.15124778176563825 will:0.10855322503039304 not:0.10165334863627778 I:0.09539587338510726 the:0.09261715385794266 would:0.0717232282216183 he:0.06932636746394916 is:0.06719671952835693 :0.01 of:0.39682473134093704 to:0.12105455152149053 in:0.11970850544947412 and:0.07118670401723742 on:0.0640901196671133 by:0.062343526513008625 for:0.06145043362162674 with:0.04685578811775423 that:0.046485639751357964 :0.01 the:0.4450542207523196 of:0.16450133778327172 a:0.1156910986974663 and:0.06433713111281826 by:0.0567674140666121 for:0.05396616187638563 to:0.04261884665193784 The:0.025852380388849166 with:0.021211408670339455 :0.01 and:0.20921559173314935 it:0.2002507861785411 to:0.1281696310205618 that:0.10104121777462508 is:0.0948109607295494 It:0.07189786648918096 of:0.06256452819378282 was:0.06243893496665761 which:0.05961048291395182 :0.01 the:0.3323475914517543 of:0.30429733953970206 his:0.05912057999500091 to:0.05787339399165412 in:0.05315061670519715 their:0.05271140435322497 good:0.050581384808583985 public:0.04169566223407192 perfect:0.03822202692081057 :0.01 was:0.16000634436631433 looked:0.12992216642528343 and:0.12861012418271928 held:0.12413082898767072 arrived:0.11539053322824105 presided:0.09299934296655213 laughed:0.08829151807731832 called:0.07818764169862265 be:0.07246150006727811 :0.01 to:0.20561394749759682 the:0.2035124044356328 of:0.16642006910341298 and:0.13092953679922395 in:0.07409286695411728 be:0.0618425766741021 was:0.054477010016655565 that:0.04738715030533824 for:0.04572443821392009 :0.01 we:0.19518728513705555 I:0.14104367184427397 they:0.11186642990136639 and:0.10943603382182511 he:0.10263725464971135 who:0.09758694134273097 which:0.09634607648504812 it:0.09240949941809264 that:0.0434868073998958 :0.01 the:0.4688302487407949 a:0.19140895771735264 at:0.07410696944848191 of:0.05992745776733672 The:0.059309912437552736 an:0.03885462192770621 for:0.038173998968084516 and:0.033152147814163195 tho:0.026235685178527417 :0.01 the:0.30066537045736186 of:0.18083337303704702 and:0.14849071523579158 to:0.13697527746982274 for:0.05023447445190032 in:0.049590724586391306 be:0.04591187306033971 is:0.04039018647411833 was:0.03690800522722708 :0.01 and:0.15898645693009783 men:0.13092657476152608 in:0.12116039789715445 ;:0.11579251612560522 there:0.09958744460946345 to:0.09498754381929934 :0.09015686854101437 right:0.08926479398275061 man:0.08913740333308875 :0.01 of:0.2759248916315242 and:0.1697610281212568 or:0.14188210103775667 the:0.09977216595042722 about:0.07533567221551868 to:0.07029508950663647 for:0.06430139578657754 by:0.051465790463847985 in:0.04126186528645438 :0.01 and:0.18256157749026333 to:0.16433979570443547 of:0.15457884979586445 the:0.1277827385426324 was:0.08436879473166353 be:0.0802923412409957 for:0.07572785229194459 is:0.06129413214409847 in:0.05905391805810186 :0.01 feet;:0.2807567469855497 ;:0.10987123625000587 running:0.10412492020173009 feet,:0.10313000520156666 2;:0.09803596238770867 3;:0.08433886765739775 4;:0.07636036253895638 5;:0.06697745013470016 feet::0.06640444864238465 :0.01 No.:0.29488140101299964 and:0.18171527787482267 the:0.13267233967362788 section:0.10393674592608021 Section:0.07795009570498498 Book:0.06493809786746192 lot:0.047013880490497297 .:0.04540097440663386 of:0.04149118704289178 :0.01 of:0.2778400933265141 in:0.16678880995056908 and:0.14055969554398734 by:0.11453096564935437 for:0.07941601014808067 are:0.06593218379247984 In:0.06357414218267705 is:0.046327342760806946 with:0.03503075664553061 :0.01 the:0.3218467846617875 of:0.1828529761416146 and:0.1232207420947663 a:0.09674086771067118 to:0.08641160396374103 in:0.0783857202791078 be:0.0377967086794569 for:0.032157504111148996 was:0.030587092357705764 :0.01 this:0.3929356176836259 the:0.36424601323021805 said:0.09414190068706371 that:0.03753440582408945 York:0.026231767757883453 a:0.02237588191203227 The:0.017941106112704355 tho:0.017415915087168058 of:0.017177391705214543 :0.01 the:0.37187944314166066 of:0.21822276201447038 and:0.09870390738986175 live:0.07494301272908574 a:0.07333997548628592 The:0.05779809301703656 tho:0.03267097363620426 capital:0.031927562906532876 his:0.030514269678861828 :0.01 to:0.7024000589479982 and:0.06996025561352545 not:0.05701693970580414 will:0.050513955150583975 would:0.030838828714624823 they:0.02300760969384441 may:0.021181127051492252 shall:0.017902742252210103 the:0.01717848286991666 :0.01 the:0.29819298779611636 and:0.18265256702547322 of:0.13010962881005228 was:0.08121404933282633 a:0.07950844863130475 be:0.07306667256403139 Mr.:0.04983112978909311 is:0.048908826139216106 The:0.04651568991188633 :0.01 the:0.3604816967038009 an:0.18810788842905138 any:0.10104650430676647 that:0.07110430009798853 last:0.06476138138830902 such:0.05560260855085649 and:0.05210506746450436 of:0.04857506406351707 a:0.04821548899520581 :0.01 the:0.3141697498569716 of:0.13596872111181624 The:0.13148451940784603 Mr.:0.12071271065510487 and:0.08466951013671548 that:0.08137847559446529 a:0.05140346651734129 Mrs.:0.04087284649549475 his:0.029340000224244486 :0.01 of:0.4462011261961158 in:0.12615857041583559 to:0.10151451743748324 for:0.07791159196235205 by:0.060895391762437356 at:0.05259110860597668 with:0.04542090039680382 from:0.04507390992515402 In:0.03423288329784133 :0.01 and:0.14196626315420005 is:0.13191941841171387 necessary:0.12661393014455413 as:0.11766702610463461 enough:0.10630327272751415 able:0.10295740592408963 order:0.09495553892699914 was:0.0844179777274438 have:0.0831991668788506 :0.01 the:0.30337617970676906 of:0.18860457588018728 and:0.13106174082947405 to:0.09776108092070786 a:0.08095665544599281 in:0.055741965423345904 be:0.05114324002429872 was:0.04187976514053473 is:0.03947479662868964 :0.01 It:0.3518094924334861 it:0.2678488056688095 which:0.1196257858703605 there:0.07504565876367791 that:0.04329008572208309 There:0.038763618378575275 he:0.037870743173773994 and:0.029959160005544043 who:0.02578664998368973 :0.01 to:0.339998491568882 and:0.17862942938941825 in:0.09645871574618903 of:0.07300886513584802 know:0.06978339603776378 that:0.060659395822263235 or:0.060017894017237394 determine:0.05572191288296831 question:0.05572189939943004 :0.01 part:0.21496902104278678 one:0.20912369233988043 some:0.12867331343811736 out:0.1057303116879626 members:0.07618604502434112 and:0.06636584999188522 tion:0.06479865598258486 portion:0.06226235532256281 side:0.061890755169878825 :0.01 the:0.7485433708759772 a:0.07685791523846566 his:0.034234262117647 tho:0.0265248312460864 The:0.024179040699663493 of:0.023399957872552522 and:0.02195502056078829 this:0.01738796356752577 said:0.016917637821293633 :0.01 of:0.38584408291504757 to:0.14069506157967437 in:0.11555995124509574 on:0.0666740960500469 by:0.06293274185329573 and:0.0611615714351081 for:0.059066043181918604 that:0.049725150575367416 from:0.04834130116444544 :0.01 the:0.7559393270397994 a:0.058884612386848785 The:0.0520373620001795 of:0.04540461220436005 tho:0.037409900764266195 and:0.013279028057778999 in:0.01040631584700489 tbe:0.009951186756089638 by:0.006687654943672375 :0.01 the:0.22381119370846944 a:0.20871162620806843 of:0.11693573883522197 and:0.10350678467831491 to:0.09964853259846065 from:0.0657361923996471 is:0.06400838781527757 are:0.05526362168574228 electric:0.052377922070797674 :0.01 to:0.22988122603357508 and:0.20058956339280717 the:0.13943594362559414 of:0.11588460464002817 in:0.08564574985575985 not:0.08091011806611492 I:0.05163104866330221 a:0.044341704528836644 or:0.041680041193981845 :0.01 the:0.3141697498569716 of:0.13596872111181624 The:0.13148451940784603 Mr.:0.12071271065510487 and:0.08466951013671548 that:0.08137847559446529 a:0.05140346651734129 Mrs.:0.04087284649549475 his:0.029340000224244486 :0.01 one:0.27929136428031115 part:0.16196919833982198 out:0.12945893165806713 some:0.08533442500483848 members:0.08355762137942169 side:0.08132005735050905 portion:0.059925805134896065 office:0.055564050621792475 member:0.053578546230341986 :0.01 and:0.19458744861213628 as:0.14324513006329825 able:0.11959067928157642 order:0.1089229649511284 began:0.10194159028383548 enough:0.10140718155181282 time:0.08476846183095126 right:0.0703634981771008 going:0.06517304524816034 :0.01 I:0.3309237919371256 they:0.13482461165699694 he:0.13255422255073715 and:0.0940476098420605 we:0.09149059453040209 that:0.05898483932147132 it:0.055089524674295294 We:0.04944456604673864 who:0.0426402394401724 :0.01 the:0.5267678717722712 court:0.16022203691487596 a:0.10324996762491358 The:0.04400523312772195 his:0.04296167922209614 school:0.039716940384348136 tho:0.03011769607907944 dwelling:0.022520855248790706 opera:0.020437719625902812 :0.01 the:0.19682318224879045 a:0.15449655009044305 was:0.13562407021699657 is:0.12840370160083583 are:0.09888365426369451 be:0.07894663002375656 and:0.07466819829273663 were:0.06893001972466437 his:0.053223993538081944 :0.01 his:0.21894703158796283 the:0.18264790899453054 her:0.13827523905799824 John-:0.11311727555833886 sea-:0.08476136834117008 Jack-:0.06970482862575639 of:0.06344104957190784 per-:0.061688531563803585 per:0.05741676669853159 :0.01 and:0.44041259200264676 that:0.159931933011043 but:0.14586877621092428 But:0.05901469057608011 time:0.053670320440024406 And:0.043181375110983154 or:0.0330580108512853 even:0.030784353672919505 day:0.024077948124093418 :0.01 and:0.27831826245921804 the:0.1874591621891938 a:0.1089904285490432 of:0.09221883337514625 to:0.08219757499755052 in:0.07839460045959269 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and:0.14916218212617383 a:0.11099602176871066 to:0.08077305174479381 in:0.05379361798284004 at:0.03681957888509467 .:0.032321536273197685 <s>:0.032028615679449264 :0.01 part:0.21496902104278678 one:0.20912369233988043 some:0.12867331343811736 out:0.1057303116879626 members:0.07618604502434112 and:0.06636584999188522 tion:0.06479865598258486 portion:0.06226235532256281 side:0.061890755169878825 :0.01 to:0.5582773489168229 will:0.1205326814783067 and:0.09539493546476666 would:0.0672383877917962 not:0.04618354515711836 I:0.031104936597419988 could:0.0249204630812482 they:0.024226663058436848 we:0.022121038454084224 :0.01 and:0.2503779956113223 to:0.19051743664518075 of:0.12818071300755096 the:0.11341275889843264 which:0.06900438075771528 that:0.06614761953644578 re-:0.058009703804947514 in:0.057905904745916295 for:0.056443486992488516 :0.01 be:0.22597535338754082 was:0.22022621232109554 been:0.1465018532603573 is:0.08372127547808164 were:0.08311063655168735 and:0.06966620745111651 Action:0.06481215720668473 are:0.05603497983203548 being:0.03995132451140055 :0.01 of:0.29090380880773137 in:0.1422990615992337 to:0.13228348808371382 for:0.1045223741712512 and:0.09327319156944214 at:0.07215408147019345 with:0.05784656581009074 by:0.04942877232597752 from:0.04728865616236608 :0.01 of:0.3269275520734347 to:0.1298190362591836 for:0.11793447932887922 by:0.08845374893933523 and:0.07946976823777345 that:0.0756829577350082 with:0.06503197855401054 in:0.06471375892939778 at:0.041966719942977286 :0.01 had:0.35487899448723775 have:0.22814747746370512 has:0.13798659080901685 was:0.08784074491369062 be:0.04441597477038501 been:0.04250795738234945 and:0.041939714567971874 were:0.026807546656898194 he:0.025474998948745015 :0.01 a:0.8222895687316497 that:0.038042412056431794 of:0.027212958148273327 A:0.026666324823166065 and:0.022788247007600647 the:0.019109995103180587 as:0.012905138001248224 is:0.010920282998614974 in:0.010065073129834784 :0.01 more:0.14449914668263036 due:0.13484845272350116 public:0.12406451221768598 good:0.12403741692723917 in:0.11945606173369773 time:0.09860232611184282 it:0.08458207491866443 risk:0.0839737241526334 large:0.07593628453210496 :0.01 the:0.28859300820277245 of:0.176566445622439 a:0.12380099638058098 to:0.10274053766955328 and:0.09215976646035769 be:0.0664805226347077 in:0.0495875201634372 is:0.04724610892476859 not:0.042825093941383084 :0.01 the:0.41564608671913017 Supreme:0.18180321100710317 District:0.09042425402687575 said:0.07168119118824547 Circuit:0.06676481423033424 County:0.05671885849152854 this:0.041521375137266156 tho:0.03514861529239232 of:0.03029159390712423 :0.01 and:0.26829833195078745 recorded:0.10717905104111183 was:0.10263907629409648 made:0.09927630384100071 that:0.09842569549211198 o'clock:0.08895025276229458 up:0.08173084504592747 is:0.07240199994443214 found:0.0710984436282374 :0.01 the:0.2430700290993388 of:0.19255952245263241 and:0.1541377657113866 to:0.1438140321537308 a:0.07286436798209919 be:0.051059482517056685 or:0.05091033703493395 his:0.042464487272563516 on:0.03911997577625805 :0.01 to:0.36267412465842147 will:0.13858750329788957 be-:0.12116547449766985 had:0.07921189610338437 has:0.07439756623795972 have:0.07263596961952425 not:0.05124771042827552 would:0.04867871214108111 I:0.04140104301579408 :0.01
a='hundred:0.16310519953665284 ;:0.13365936507111417 him:0.11732615948902898 one:0.10942603140040545 feet:0.10793347117441225 up:0.10029179877010726 mile:0.09005038552425718 feet,:0.085903823261794 time:0.08230376577222767 :0.01'
elems = a.split('\t')
elems
['hundred:0.16310519953665284', ';:0.13365936507111417', 'him:0.11732615948902898', 'one:0.10942603140040545', 'feet:0.10793347117441225', 'up:0.10029179877010726', 'mile:0.09005038552425718', 'feet,:0.085903823261794', 'time:0.08230376577222767', ':0.01']
print(sum([float(entry.split(':')[1]) for entry in elems]))
0.9999999999999998
for x in elems:
a = x.split(':')[1]
print(a)
0.1631051995366529 0.1336593650711142 0.11732615948902901 0.10942603140040548 0.10793347117441228 0.10029179877010727 0.09005038552425719 0.08590382326179401 0.0823037657722277 0.01