5.6 MiB
5.6 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')
a = results[5]
print(a)
{'is': 0.11248013377189636, 'be': 0.0887126550078392, 'are': 0.05770659074187279, 'was': 0.04821299761533737, 'and': 0.031015213578939438, '<unk>': 0.02695723995566368, 'been': 0.016298962756991386, 'Is': 0.01539035513997078, 'not': 0.015107596293091774, 'were': 0.014968073926866055}
b={'is': 0.2, 'the': 0.2, '<unk>': 0.4}
b={'is': 0.2, 'the': 0.2}
results_summ = summarize_probs_unk(b, const_wildcard = False)
print(results_summ)
[('is', 0.25), ('the', 0.25), ('<unk>', 0.5)]
print(b)
{'is': 0.495, 'the': 0.495}
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:
wildcard_value = dic['<unk>']
del dic['<unk>']
probsum = sum([float(val) for key, val in dic.items()])
for key in dic:
dic[key] = dic[key]/(probsum+wildcard_value)
tab = [(key, val) for key, val in dic.items()]
tab.append(('<unk>', 1-sum([val for val in dic.values()])))
return tab
def gonito_format(dic, const_wildcard = True):
tab = summarize_probs_unk(dic, const_wildcard=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(['twenty']), vocab.forward(['dollars'])]).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)
[('and', 3, 0.16225862503051758), ('<unk>', 0, 0.09216757118701935), ('than', 57, 0.07570096850395203), ('about', 81, 0.05731402337551117), ('of', 2, 0.05304272100329399), ('or', 19, 0.05177469179034233), ('for', 8, 0.04992656409740448), ('to', 4, 0.03527023643255234), ('number', 212, 0.013216206803917885), ('least', 433, 0.012247467413544655)]
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:
predicted_distribution = get_values_from_model(context_words, model, vocab, k=10)
distribution_as_dict = dict(predicted_distribution)
# print(distribution_as_dict)
results.append(distribution_as_dict)
# with open(out_file, 'w') as outfile:
# for elem in results:
# outfile.write(gonito_format(elem, const_wildcard=False))
/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)
with open(out_file, 'w') as outfile:
for elem in results:
outfile.write(gonito_format(elem, const_wildcard=False))
a = results[1065]
print(a)
{'to': 0.2240549474954605, 'will': 0.1578778624534607, 'should': 0.06777101010084152, 'may': 0.059202395379543304, 'would': 0.0574687235057354, 'can': 0.05198880657553673, 'could': 0.04070327803492546, 'must': 0.03686462715268135, 'shall': 0.03472733497619629, 'not': 0.032116860151290894}
results_summ = summarize_probs_unk(a, const_wildcard = False)
results_summ = [summarize_probs_unk(result, const_wildcard = False) for result in results]
results_summ
[('a', 0.32235596453720317), ('the', 0.29815671218498524), ('this', 0.037712611177471045), ('other', 0.03380747940487517), ('of', 0.029858854655014522), ('and', 0.027513870807796215), ('his', 0.02489330633482702), ('The', 0.022330998789039776), ('tho', 0.01943313977820608), ('<unk>', 0.18393706233058182)]
for idx, element in enumerate(results_summ):
print(idx, ': ', sum([float(entry[1]) for entry in element]))
0 : 1.0 1 : 1.0 2 : 1.0 3 : 1.0 4 : 1.0 5 : 1.0 6 : 1.0 7 : 1.0 8 : 1.0 9 : 1.0 10 : 1.0 11 : 1.0 12 : 1.0 13 : 1.0 14 : 1.0 15 : 1.0 16 : 1.0 17 : 1.0 18 : 1.0 19 : 1.0 20 : 1.0 21 : 1.0 22 : 1.0 23 : 1.0 24 : 1.0 25 : 1.0 26 : 1.0 27 : 1.0 28 : 1.0 29 : 1.0 30 : 1.0 31 : 1.0 32 : 1.0 33 : 1.0 34 : 1.0 35 : 1.0 36 : 1.0 37 : 1.0 38 : 1.0 39 : 1.0 40 : 1.0 41 : 1.0 42 : 1.0 43 : 1.0 44 : 1.0 45 : 1.0 46 : 1.0 47 : 1.0 48 : 1.0 49 : 1.0 50 : 1.0 51 : 1.0 52 : 1.0 53 : 1.0 54 : 1.0 55 : 1.0 56 : 1.0 57 : 1.0 58 : 1.0 59 : 1.0 60 : 1.0 61 : 1.0 62 : 1.0 63 : 1.0 64 : 1.0 65 : 1.0 66 : 1.0 67 : 1.0 68 : 1.0 69 : 1.0 70 : 1.0 71 : 1.0 72 : 1.0 73 : 1.0 74 : 1.0 75 : 1.0 76 : 1.0 77 : 1.0 78 : 1.0 79 : 1.0 80 : 1.0 81 : 1.0 82 : 1.0 83 : 1.0 84 : 1.0 85 : 1.0 86 : 1.0 87 : 1.0 88 : 1.0 89 : 1.0 90 : 1.0 91 : 1.0 92 : 1.0 93 : 1.0 94 : 1.0 95 : 1.0 96 : 1.0 97 : 1.0 98 : 1.0 99 : 1.0 100 : 1.0 101 : 1.0 102 : 1.0 103 : 1.0 104 : 1.0 105 : 1.0 106 : 1.0 107 : 1.0 108 : 1.0 109 : 1.0 110 : 1.0 111 : 1.0 112 : 1.0 113 : 1.0 114 : 1.0 115 : 1.0 116 : 1.0 117 : 1.0 118 : 1.0 119 : 1.0 120 : 1.0 121 : 1.0 122 : 1.0 123 : 1.0 124 : 1.0 125 : 1.0 126 : 1.0 127 : 1.0 128 : 1.0 129 : 1.0 130 : 1.0 131 : 1.0 132 : 1.0 133 : 1.0 134 : 1.0 135 : 1.0 136 : 1.0 137 : 1.0 138 : 1.0 139 : 1.0 140 : 1.0 141 : 1.0 142 : 1.0 143 : 1.0 144 : 1.0 145 : 1.0 146 : 1.0 147 : 1.0 148 : 1.0 149 : 1.0 150 : 1.0 151 : 1.0 152 : 1.0 153 : 1.0 154 : 1.0 155 : 1.0 156 : 1.0 157 : 1.0 158 : 1.0 159 : 1.0 160 : 1.0 161 : 1.0 162 : 1.0 163 : 1.0 164 : 1.0 165 : 1.0 166 : 1.0 167 : 1.0 168 : 1.0 169 : 1.0 170 : 1.0 171 : 1.0 172 : 1.0 173 : 1.0 174 : 1.0 175 : 1.0 176 : 1.0 177 : 1.0 178 : 1.0 179 : 1.0 180 : 1.0 181 : 1.0 182 : 1.0 183 : 1.0 184 : 1.0 185 : 1.0 186 : 1.0 187 : 1.0 188 : 1.0 189 : 1.0 190 : 1.0 191 : 1.0 192 : 1.0 193 : 1.0 194 : 1.0 195 : 1.0 196 : 1.0 197 : 1.0 198 : 1.0 199 : 1.0 200 : 1.0 201 : 1.0 202 : 1.0 203 : 1.0 204 : 1.0 205 : 1.0 206 : 1.0 207 : 1.0 208 : 1.0 209 : 1.0 210 : 1.0 211 : 1.0 212 : 1.0 213 : 1.0 214 : 1.0 215 : 1.0 216 : 1.0 217 : 1.0 218 : 1.0 219 : 1.0 220 : 1.0 221 : 1.0 222 : 1.0 223 : 1.0 224 : 1.0 225 : 1.0 226 : 1.0 227 : 1.0 228 : 1.0 229 : 1.0 230 : 1.0 231 : 1.0 232 : 1.0 233 : 1.0 234 : 1.0 235 : 1.0 236 : 1.0 237 : 1.0 238 : 1.0 239 : 1.0 240 : 1.0 241 : 1.0 242 : 1.0 243 : 1.0 244 : 1.0 245 : 1.0 246 : 1.0 247 : 1.0 248 : 1.0 249 : 1.0 250 : 1.0 251 : 1.0 252 : 1.0 253 : 1.0 254 : 1.0 255 : 1.0 256 : 1.0 257 : 1.0 258 : 1.0 259 : 1.0 260 : 1.0 261 : 1.0 262 : 1.0 263 : 1.0 264 : 1.0 265 : 1.0 266 : 1.0 267 : 1.0 268 : 1.0 269 : 1.0 270 : 1.0 271 : 1.0 272 : 1.0 273 : 1.0 274 : 1.0 275 : 1.0 276 : 1.0 277 : 1.0 278 : 1.0 279 : 1.0 280 : 1.0 281 : 1.0 282 : 1.0 283 : 1.0 284 : 1.0 285 : 1.0 286 : 1.0 287 : 1.0 288 : 1.0 289 : 1.0 290 : 1.0 291 : 1.0 292 : 1.0 293 : 1.0 294 : 1.0 295 : 1.0 296 : 1.0 297 : 1.0 298 : 1.0 299 : 1.0 300 : 1.0 301 : 1.0 302 : 1.0 303 : 1.0 304 : 1.0 305 : 1.0 306 : 1.0 307 : 1.0 308 : 1.0 309 : 1.0 310 : 1.0 311 : 1.0 312 : 1.0 313 : 1.0 314 : 1.0 315 : 1.0 316 : 1.0 317 : 1.0 318 : 1.0 319 : 1.0 320 : 1.0 321 : 1.0 322 : 1.0 323 : 1.0 324 : 1.0 325 : 1.0 326 : 1.0 327 : 1.0 328 : 1.0 329 : 1.0 330 : 1.0 331 : 1.0 332 : 1.0 333 : 1.0 334 : 1.0 335 : 1.0 336 : 1.0 337 : 1.0 338 : 1.0 339 : 1.0 340 : 1.0 341 : 1.0 342 : 1.0 343 : 1.0 344 : 1.0 345 : 1.0 346 : 1.0 347 : 1.0 348 : 1.0 349 : 1.0 350 : 1.0 351 : 1.0 352 : 1.0 353 : 1.0 354 : 1.0 355 : 1.0 356 : 1.0 357 : 1.0 358 : 1.0 359 : 1.0 360 : 1.0 361 : 1.0 362 : 1.0 363 : 1.0 364 : 1.0 365 : 1.0 366 : 1.0 367 : 1.0 368 : 1.0 369 : 1.0 370 : 1.0 371 : 1.0 372 : 1.0 373 : 1.0 374 : 1.0 375 : 1.0 376 : 1.0 377 : 1.0 378 : 1.0 379 : 1.0 380 : 1.0 381 : 1.0 382 : 1.0 383 : 1.0 384 : 1.0 385 : 1.0 386 : 1.0 387 : 1.0 388 : 1.0 389 : 1.0 390 : 1.0 391 : 1.0 392 : 1.0 393 : 1.0 394 : 1.0 395 : 1.0 396 : 1.0 397 : 1.0 398 : 1.0 399 : 1.0 400 : 1.0 401 : 1.0 402 : 1.0 403 : 1.0 404 : 1.0 405 : 1.0 406 : 1.0 407 : 1.0 408 : 1.0 409 : 1.0 410 : 1.0 411 : 1.0 412 : 1.0 413 : 1.0 414 : 1.0 415 : 1.0 416 : 1.0 417 : 1.0 418 : 1.0 419 : 1.0 420 : 1.0 421 : 1.0 422 : 1.0 423 : 1.0 424 : 1.0 425 : 1.0 426 : 1.0 427 : 1.0 428 : 1.0 429 : 1.0 430 : 1.0 431 : 1.0 432 : 1.0 433 : 1.0 434 : 1.0 435 : 1.0 436 : 1.0 437 : 1.0 438 : 1.0 439 : 1.0 440 : 1.0 441 : 1.0 442 : 1.0 443 : 1.0 444 : 1.0 445 : 1.0 446 : 1.0 447 : 1.0 448 : 1.0 449 : 1.0 450 : 1.0 451 : 1.0 452 : 1.0 453 : 1.0 454 : 1.0 455 : 1.0 456 : 1.0 457 : 1.0 458 : 1.0 459 : 1.0 460 : 1.0 461 : 1.0 462 : 1.0 463 : 1.0 464 : 1.0 465 : 1.0 466 : 1.0 467 : 1.0 468 : 1.0 469 : 1.0 470 : 1.0 471 : 1.0 472 : 1.0 473 : 1.0 474 : 1.0 475 : 1.0 476 : 1.0 477 : 1.0 478 : 1.0 479 : 1.0 480 : 1.0 481 : 1.0 482 : 1.0 483 : 1.0 484 : 1.0 485 : 1.0 486 : 1.0 487 : 1.0 488 : 1.0 489 : 1.0 490 : 1.0 491 : 1.0 492 : 1.0 493 : 1.0 494 : 1.0 495 : 1.0 496 : 1.0 497 : 1.0 498 : 1.0 499 : 1.0 500 : 1.0 501 : 1.0 502 : 1.0 503 : 1.0 504 : 1.0 505 : 1.0 506 : 1.0 507 : 1.0 508 : 1.0 509 : 1.0 510 : 1.0 511 : 1.0 512 : 1.0 513 : 1.0 514 : 1.0 515 : 1.0 516 : 1.0 517 : 1.0 518 : 1.0 519 : 1.0 520 : 1.0 521 : 1.0 522 : 1.0 523 : 1.0 524 : 1.0 525 : 1.0 526 : 1.0 527 : 1.0 528 : 1.0 529 : 1.0 530 : 1.0 531 : 1.0 532 : 1.0 533 : 1.0 534 : 1.0 535 : 1.0 536 : 1.0 537 : 1.0 538 : 1.0 539 : 1.0 540 : 1.0 541 : 1.0 542 : 1.0 543 : 1.0 544 : 1.0 545 : 1.0 546 : 1.0 547 : 1.0 548 : 1.0 549 : 1.0 550 : 1.0 551 : 1.0 552 : 1.0 553 : 1.0 554 : 1.0 555 : 1.0 556 : 1.0 557 : 1.0 558 : 1.0 559 : 1.0 560 : 1.0 561 : 1.0 562 : 1.0 563 : 1.0 564 : 1.0 565 : 1.0 566 : 1.0 567 : 1.0 568 : 1.0 569 : 1.0 570 : 1.0 571 : 1.0 572 : 1.0 573 : 1.0 574 : 1.0 575 : 1.0 576 : 1.0 577 : 1.0 578 : 1.0 579 : 1.0 580 : 1.0 581 : 1.0 582 : 1.0 583 : 1.0 584 : 1.0 585 : 1.0 586 : 1.0 587 : 1.0 588 : 1.0 589 : 1.0 590 : 1.0 591 : 1.0 592 : 1.0 593 : 1.0 594 : 1.0 595 : 1.0 596 : 1.0 597 : 1.0 598 : 1.0 599 : 1.0 600 : 1.0 601 : 1.0 602 : 1.0 603 : 1.0 604 : 1.0 605 : 1.0 606 : 1.0 607 : 1.0 608 : 1.0 609 : 1.0 610 : 1.0 611 : 1.0 612 : 1.0 613 : 1.0 614 : 1.0 615 : 1.0 616 : 1.0 617 : 1.0 618 : 1.0 619 : 1.0 620 : 1.0 621 : 1.0 622 : 1.0 623 : 1.0 624 : 1.0 625 : 1.0 626 : 1.0 627 : 1.0 628 : 1.0 629 : 1.0 630 : 1.0 631 : 1.0 632 : 1.0 633 : 1.0 634 : 1.0 635 : 1.0 636 : 1.0 637 : 1.0 638 : 1.0 639 : 1.0 640 : 1.0 641 : 1.0 642 : 1.0 643 : 1.0 644 : 1.0 645 : 1.0 646 : 1.0 647 : 1.0 648 : 1.0 649 : 1.0 650 : 1.0 651 : 1.0 652 : 1.0 653 : 1.0 654 : 1.0 655 : 1.0 656 : 1.0 657 : 1.0 658 : 1.0 659 : 1.0 660 : 1.0 661 : 1.0 662 : 1.0 663 : 1.0 664 : 1.0 665 : 1.0 666 : 1.0 667 : 1.0 668 : 1.0 669 : 1.0 670 : 1.0 671 : 1.0 672 : 1.0 673 : 1.0 674 : 1.0 675 : 1.0 676 : 1.0 677 : 1.0 678 : 1.0 679 : 1.0 680 : 1.0 681 : 1.0 682 : 1.0 683 : 1.0 684 : 1.0 685 : 1.0 686 : 1.0 687 : 1.0 688 : 1.0 689 : 1.0 690 : 1.0 691 : 1.0 692 : 1.0 693 : 1.0 694 : 1.0 695 : 1.0 696 : 1.0 697 : 1.0 698 : 1.0 699 : 1.0 700 : 1.0 701 : 1.0 702 : 1.0 703 : 1.0 704 : 1.0 705 : 1.0 706 : 1.0 707 : 1.0 708 : 1.0 709 : 1.0 710 : 1.0 711 : 1.0 712 : 1.0 713 : 1.0 714 : 1.0 715 : 1.0 716 : 1.0 717 : 1.0 718 : 1.0 719 : 1.0 720 : 1.0 721 : 1.0 722 : 1.0 723 : 1.0 724 : 1.0 725 : 1.0 726 : 1.0 727 : 1.0 728 : 1.0 729 : 1.0 730 : 1.0 731 : 1.0 732 : 1.0 733 : 1.0 734 : 1.0 735 : 1.0 736 : 1.0 737 : 1.0 738 : 1.0 739 : 1.0 740 : 1.0 741 : 1.0 742 : 1.0 743 : 1.0 744 : 1.0 745 : 1.0 746 : 1.0 747 : 1.0 748 : 1.0 749 : 1.0 750 : 1.0 751 : 1.0 752 : 1.0 753 : 1.0 754 : 1.0 755 : 1.0 756 : 1.0 757 : 1.0 758 : 1.0 759 : 1.0 760 : 1.0 761 : 1.0 762 : 1.0 763 : 1.0 764 : 1.0 765 : 1.0 766 : 1.0 767 : 1.0 768 : 1.0 769 : 1.0 770 : 1.0 771 : 1.0 772 : 1.0 773 : 1.0 774 : 1.0 775 : 1.0 776 : 1.0 777 : 1.0 778 : 1.0 779 : 1.0 780 : 1.0 781 : 1.0 782 : 1.0 783 : 1.0 784 : 1.0 785 : 1.0 786 : 1.0 787 : 1.0 788 : 1.0 789 : 1.0 790 : 1.0 791 : 1.0 792 : 1.0 793 : 1.0 794 : 1.0 795 : 1.0 796 : 1.0 797 : 1.0 798 : 1.0 799 : 1.0 800 : 1.0 801 : 1.0 802 : 1.0 803 : 1.0 804 : 1.0 805 : 1.0 806 : 1.0 807 : 1.0 808 : 1.0 809 : 1.0 810 : 1.0 811 : 1.0 812 : 1.0 813 : 1.0 814 : 1.0 815 : 1.0 816 : 1.0 817 : 1.0 818 : 1.0 819 : 1.0 820 : 1.0 821 : 1.0 822 : 1.0 823 : 1.0 824 : 1.0 825 : 1.0 826 : 1.0 827 : 1.0 828 : 1.0 829 : 1.0 830 : 1.0 831 : 1.0 832 : 1.0 833 : 1.0 834 : 1.0 835 : 1.0 836 : 1.0 837 : 1.0 838 : 1.0 839 : 1.0 840 : 1.0 841 : 1.0 842 : 1.0 843 : 1.0 844 : 1.0 845 : 1.0 846 : 1.0 847 : 1.0 848 : 1.0 849 : 1.0 850 : 1.0 851 : 1.0 852 : 1.0 853 : 1.0 854 : 1.0 855 : 1.0 856 : 1.0 857 : 1.0 858 : 1.0 859 : 1.0 860 : 1.0 861 : 1.0 862 : 1.0 863 : 1.0 864 : 1.0 865 : 1.0 866 : 1.0 867 : 1.0 868 : 1.0 869 : 1.0 870 : 1.0 871 : 1.0 872 : 1.0 873 : 1.0 874 : 1.0 875 : 1.0 876 : 1.0 877 : 1.0 878 : 1.0 879 : 1.0 880 : 1.0 881 : 1.0 882 : 1.0 883 : 1.0 884 : 1.0 885 : 1.0 886 : 1.0 887 : 1.0 888 : 1.0 889 : 1.0 890 : 1.0 891 : 1.0 892 : 1.0 893 : 1.0 894 : 1.0 895 : 1.0 896 : 1.0 897 : 1.0 898 : 1.0 899 : 1.0 900 : 1.0 901 : 1.0 902 : 1.0 903 : 1.0 904 : 1.0 905 : 1.0 906 : 1.0 907 : 1.0 908 : 1.0 909 : 1.0 910 : 1.0 911 : 1.0 912 : 1.0 913 : 1.0 914 : 1.0 915 : 1.0 916 : 1.0 917 : 1.0 918 : 1.0 919 : 1.0 920 : 1.0 921 : 1.0 922 : 1.0 923 : 1.0 924 : 1.0 925 : 1.0 926 : 1.0 927 : 1.0 928 : 1.0 929 : 1.0 930 : 1.0 931 : 1.0 932 : 1.0 933 : 1.0 934 : 1.0 935 : 1.0 936 : 1.0 937 : 1.0 938 : 1.0 939 : 1.0 940 : 1.0 941 : 1.0 942 : 1.0 943 : 1.0 944 : 1.0 945 : 1.0 946 : 1.0 947 : 1.0 948 : 1.0 949 : 1.0 950 : 1.0 951 : 1.0 952 : 1.0 953 : 1.0 954 : 1.0 955 : 1.0 956 : 1.0 957 : 1.0 958 : 1.0 959 : 1.0 960 : 1.0 961 : 1.0 962 : 1.0 963 : 1.0 964 : 1.0 965 : 1.0 966 : 1.0 967 : 1.0 968 : 1.0 969 : 1.0 970 : 1.0 971 : 1.0 972 : 1.0 973 : 1.0 974 : 1.0 975 : 1.0 976 : 1.0 977 : 1.0 978 : 1.0 979 : 1.0 980 : 1.0 981 : 1.0 982 : 1.0 983 : 1.0 984 : 1.0 985 : 1.0 986 : 1.0 987 : 1.0 988 : 1.0 989 : 1.0 990 : 1.0 991 : 1.0 992 : 1.0 993 : 1.0 994 : 1.0 995 : 1.0 996 : 1.0 997 : 1.0 998 : 1.0 999 : 1.0 1000 : 1.0 1001 : 1.0 1002 : 1.0 1003 : 1.0 1004 : 1.0 1005 : 1.0 1006 : 1.0 1007 : 1.0 1008 : 1.0 1009 : 1.0 1010 : 1.0 1011 : 1.0 1012 : 1.0 1013 : 1.0 1014 : 1.0 1015 : 1.0 1016 : 1.0 1017 : 1.0 1018 : 1.0 1019 : 1.0 1020 : 1.0 1021 : 1.0 1022 : 1.0 1023 : 1.0 1024 : 1.0 1025 : 1.0 1026 : 1.0 1027 : 1.0 1028 : 1.0 1029 : 1.0 1030 : 1.0 1031 : 1.0 1032 : 1.0 1033 : 1.0 1034 : 1.0 1035 : 1.0 1036 : 1.0 1037 : 1.0 1038 : 1.0 1039 : 1.0 1040 : 1.0 1041 : 1.0 1042 : 1.0 1043 : 1.0 1044 : 1.0 1045 : 1.0 1046 : 1.0 1047 : 1.0 1048 : 1.0 1049 : 1.0 1050 : 1.0 1051 : 1.0 1052 : 1.0 1053 : 1.0 1054 : 1.0 1055 : 1.0 1056 : 1.0 1057 : 1.0 1058 : 1.0 1059 : 1.0 1060 : 1.0 1061 : 1.0 1062 : 1.0 1063 : 1.0 1064 : 1.0 1065 : 0.9999999999999999 1066 : 1.0 1067 : 1.0 1068 : 1.0 1069 : 1.0 1070 : 1.0 1071 : 1.0 1072 : 1.0 1073 : 1.0 1074 : 1.0 1075 : 1.0 1076 : 1.0 1077 : 1.0 1078 : 1.0 1079 : 1.0 1080 : 1.0 1081 : 1.0 1082 : 1.0 1083 : 1.0 1084 : 1.0 1085 : 1.0 1086 : 1.0 1087 : 1.0 1088 : 1.0 1089 : 1.0 1090 : 1.0 1091 : 1.0 1092 : 1.0 1093 : 1.0 1094 : 1.0 1095 : 1.0 1096 : 1.0 1097 : 1.0 1098 : 1.0 1099 : 1.0 1100 : 1.0 1101 : 1.0 1102 : 1.0 1103 : 1.0 1104 : 1.0 1105 : 1.0 1106 : 1.0 1107 : 1.0 1108 : 1.0 1109 : 1.0 1110 : 1.0 1111 : 1.0 1112 : 1.0 1113 : 1.0 1114 : 1.0 1115 : 1.0 1116 : 1.0 1117 : 1.0 1118 : 1.0 1119 : 1.0 1120 : 1.0 1121 : 1.0 1122 : 1.0 1123 : 1.0 1124 : 1.0 1125 : 1.0 1126 : 1.0 1127 : 1.0 1128 : 1.0 1129 : 1.0 1130 : 1.0 1131 : 1.0 1132 : 1.0 1133 : 1.0 1134 : 1.0 1135 : 1.0 1136 : 1.0 1137 : 1.0 1138 : 1.0 1139 : 1.0 1140 : 1.0 1141 : 1.0 1142 : 1.0 1143 : 1.0 1144 : 1.0 1145 : 1.0 1146 : 1.0 1147 : 1.0 1148 : 1.0 1149 : 1.0 1150 : 1.0 1151 : 1.0 1152 : 1.0 1153 : 1.0 1154 : 1.0 1155 : 1.0 1156 : 1.0 1157 : 1.0 1158 : 1.0 1159 : 1.0 1160 : 1.0 1161 : 1.0 1162 : 1.0 1163 : 1.0 1164 : 1.0 1165 : 1.0 1166 : 1.0 1167 : 1.0 1168 : 1.0 1169 : 1.0 1170 : 1.0 1171 : 1.0 1172 : 1.0 1173 : 1.0 1174 : 1.0 1175 : 1.0 1176 : 1.0 1177 : 1.0 1178 : 1.0 1179 : 1.0 1180 : 1.0 1181 : 1.0 1182 : 1.0 1183 : 1.0 1184 : 1.0 1185 : 1.0 1186 : 1.0 1187 : 1.0 1188 : 1.0 1189 : 1.0 1190 : 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10257 : 1.0 10258 : 1.0 10259 : 1.0 10260 : 1.0 10261 : 1.0 10262 : 1.0 10263 : 1.0 10264 : 1.0 10265 : 1.0 10266 : 1.0 10267 : 1.0 10268 : 1.0 10269 : 1.0 10270 : 1.0 10271 : 1.0 10272 : 1.0 10273 : 1.0 10274 : 1.0 10275 : 1.0 10276 : 1.0 10277 : 1.0 10278 : 1.0 10279 : 1.0 10280 : 1.0 10281 : 1.0 10282 : 1.0 10283 : 1.0 10284 : 1.0 10285 : 1.0 10286 : 1.0 10287 : 1.0 10288 : 1.0 10289 : 1.0 10290 : 1.0 10291 : 1.0 10292 : 1.0 10293 : 1.0 10294 : 1.0 10295 : 1.0 10296 : 1.0 10297 : 1.0 10298 : 1.0 10299 : 1.0 10300 : 1.0 10301 : 1.0 10302 : 1.0 10303 : 1.0 10304 : 1.0 10305 : 1.0 10306 : 1.0 10307 : 1.0 10308 : 1.0 10309 : 1.0 10310 : 1.0 10311 : 1.0 10312 : 1.0 10313 : 1.0 10314 : 1.0 10315 : 1.0 10316 : 1.0 10317 : 1.0 10318 : 1.0 10319 : 1.0 10320 : 1.0 10321 : 1.0 10322 : 1.0 10323 : 1.0 10324 : 1.0 10325 : 1.0 10326 : 1.0 10327 : 1.0 10328 : 1.0 10329 : 1.0 10330 : 1.0 10331 : 1.0 10332 : 1.0 10333 : 1.0 10334 : 1.0 10335 : 1.0 10336 : 1.0 10337 : 1.0 10338 : 1.0 10339 : 1.0 10340 : 1.0 10341 : 1.0 10342 : 1.0 10343 : 1.0 10344 : 1.0 10345 : 1.0 10346 : 1.0 10347 : 1.0 10348 : 1.0 10349 : 1.0 10350 : 1.0 10351 : 1.0 10352 : 1.0 10353 : 1.0 10354 : 1.0 10355 : 1.0 10356 : 1.0 10357 : 1.0 10358 : 1.0 10359 : 1.0 10360 : 1.0 10361 : 1.0 10362 : 1.0 10363 : 1.0 10364 : 1.0 10365 : 1.0 10366 : 1.0 10367 : 1.0 10368 : 1.0 10369 : 1.0 10370 : 1.0 10371 : 1.0 10372 : 1.0 10373 : 1.0 10374 : 1.0 10375 : 1.0 10376 : 1.0 10377 : 1.0 10378 : 1.0 10379 : 1.0 10380 : 1.0 10381 : 1.0 10382 : 1.0 10383 : 1.0 10384 : 1.0 10385 : 1.0 10386 : 1.0 10387 : 1.0 10388 : 1.0 10389 : 1.0 10390 : 1.0 10391 : 1.0 10392 : 1.0 10393 : 1.0 10394 : 1.0 10395 : 1.0 10396 : 1.0 10397 : 1.0 10398 : 1.0 10399 : 1.0 10400 : 1.0 10401 : 1.0 10402 : 1.0 10403 : 1.0 10404 : 1.0 10405 : 1.0 10406 : 1.0 10407 : 1.0 10408 : 1.0 10409 : 1.0 10410 : 1.0 10411 : 1.0 10412 : 1.0 10413 : 1.0 10414 : 1.0 10415 : 1.0 10416 : 1.0 10417 : 1.0 10418 : 1.0 10419 : 1.0 10420 : 1.0 10421 : 1.0 10422 : 1.0 10423 : 1.0 10424 : 1.0 10425 : 1.0 10426 : 1.0 10427 : 1.0 10428 : 1.0 10429 : 1.0 10430 : 1.0 10431 : 1.0 10432 : 1.0 10433 : 1.0 10434 : 1.0 10435 : 1.0 10436 : 1.0 10437 : 1.0 10438 : 1.0 10439 : 1.0 10440 : 1.0 10441 : 1.0 10442 : 1.0 10443 : 1.0 10444 : 1.0 10445 : 1.0 10446 : 1.0 10447 : 1.0 10448 : 1.0 10449 : 1.0 10450 : 1.0 10451 : 1.0 10452 : 1.0 10453 : 1.0 10454 : 1.0 10455 : 1.0 10456 : 1.0 10457 : 1.0 10458 : 1.0 10459 : 1.0 10460 : 1.0 10461 : 1.0 10462 : 1.0 10463 : 1.0 10464 : 1.0 10465 : 1.0 10466 : 1.0 10467 : 1.0 10468 : 1.0 10469 : 1.0 10470 : 1.0 10471 : 1.0 10472 : 1.0 10473 : 1.0 10474 : 1.0 10475 : 1.0 10476 : 1.0 10477 : 1.0 10478 : 1.0 10479 : 1.0 10480 : 1.0 10481 : 1.0 10482 : 1.0 10483 : 1.0 10484 : 1.0 10485 : 1.0 10486 : 1.0 10487 : 1.0 10488 : 1.0 10489 : 1.0 10490 : 1.0 10491 : 1.0 10492 : 1.0 10493 : 1.0 10494 : 1.0 10495 : 1.0 10496 : 1.0 10497 : 1.0 10498 : 1.0 10499 : 1.0 10500 : 1.0 10501 : 1.0 10502 : 1.0 10503 : 1.0 10504 : 1.0 10505 : 1.0 10506 : 1.0 10507 : 1.0 10508 : 1.0 10509 : 1.0 10510 : 1.0 10511 : 1.0 10512 : 1.0 10513 : 1.0 10514 : 1.0 10515 : 1.0 10516 : 1.0 10517 : 1.0 10518 : 1.0
tab = results_summ
result = ''
for element in tab[:-1]:
result+=str(element[0])+':'+str(element[1])+'\t'
result += ':'+ str(tab[-1][1]) + '\n'
print(result, end='')
a:0.32235596453720317 the:0.29815671218498524 this:0.037712611177471045 other:0.03380747940487517 of:0.029858854655014522 and:0.027513870807796215 his:0.02489330633482702 The:0.022330998789039776 tho:0.01943313977820608 :0.18393706233058182
gonito_format(results[2], const_wildcard = False)
'a:0.3910634709171287\tthe:0.3617063481722642\tthis:0.04575074218211916\tother:0.041013263886742826\tof:0.03622302244589748\tand:0.033378224696135494\this:0.030199108590644053\tThe:0.027090666394293545\ttho:0.023575152714774474\t:0.01\n'
print(predict_words)
[['Northeasterly', 'hv'], ['and', 'design,'], ['Democrat', 'enlisting'], ['will', 'preserve'], ['to', 'run'], ['sufficient', 'to'], ['at', 'the'], ['being', 'all'], ['all', 'kinds'], ['if', 'I'], ['opera*', 'pretiinn'], ['cause', 'of'], ['', 'low,'], ['In', 'the'], ['look', 'forward'], ['!', 'His'], ['God', 'lo'], ['on', 'their'], ['which', 'are'], ['lillliiuited', 'frolu'], ['tbat', 'is'], ['produce', 'strong'], ['out', 'they'], ['to', 'hesileul'], ['le', 'to'], ['the', 'townships,'], ['telephone', 'and'], ['?', 'Just'], ['health', ':'], ['at', 'by'], ['', 'once'], ['shall', 'have'], ['Everv', 'moment'], ['', 'It'], ['and', 'other'], ['eight', 'psnds'], ['', 'better'], ['thence', 'N'], ['16', 'of'], ['making', 'the'], ['rte', '-'], ['city,', '(who'], ['stock', 'standing'], ['confer', 'similar'], ['Haidee', 'finally'], ['elec-', 'ted'], ['Roard', 'was'], ['the', 'farmers.'], ['to', 'manage'], ['temptation.', 'The'], ['seems', 'now'], ['whether', 'contagious'], ['ot', 'the'], ['fifth', 'district,'], ['the', 'birth'], ['flames', 'east'], ['light', 'to'], ['treasures,', 'your'], ['^fcc—this', 'was'], ['of', 'the'], ['to', 'call'], ['would,', 'perhaps,'], ['house', ';'], ['shot.', 'They'], ['son,', 'and'], ['when', 'it'], ['', 'look'], ['condition', 'that'], ['cottage', 'in'], ['to', 'other'], ['and', 'headed'], ['so', 'slight'], ['in', 'tbe'], ['yet', 'been'], ['Mortgage,', 'and'], ['wi', 'far'], ['of', 'a'], ['citizens', 'to'], ['or', 'the'], ['', 'ground'], ['of', 'property'], ['same', 'condition.'], ['mines', 'and'], ['l', 'city,'], ['The', 'most'], ['become', 'a'], ['thinker,', 'and'], ['hia', 'face.'], ['', 'and'], ['its', 'object'], ['know', 'whether'], ['Julv,', '1896,'], ['without', 'the'], ['are', 'now'], ['§IBO,OOO.', 'I'], ['most', 'innocent'], ['the', 'receipts,'], ['national', 'debt'], ['make', 'any'], ['with', 'the'], ['', 'Ih-turbthe'], ['', 'holding'], ['it', 'all'], ['referred', "'«"], ['the', 'machinery'], ['sequels', 'to'], ['treasury', 'all'], ['The', 'licence'], ['blot', 'these'], ['with', 'teams'], ['to', 'tho'], ['of', 'benefit'], ['natal', 'air'], ['men', 'pre'], ['come', 'the'], ['to', 'ex-'], ['Court', 'intermediate'], ['of', 'filters'], ['are', 'satisfied,'], ['the', 'labor'], ["a'jout", 'five'], ['', 'vices'], ['in', 'Know-'], ['to', 'revive'], ['also', 'in'], ['a', 'raw'], ['every', 'kind'], ['the', 'dis'], ['love', 'and'], ['Is', 'it'], ['feet,', 'twenty'], ['or', 'taint'], ['strength', 'of'], ['melodious', 'voire,'], ['may', 'lead'], ['in', 'time,is'], ['are', 'you'], ['re-', 'bellion'], ['lake', 'the'], ['at', 'Malvern.'], ['', 'the'], ['as', 'if'], ['', 'he'], ['this', 'State'], ['thrown', 'uponit,'], ['', 'Therefore'], ['lower', 'temperatures'], ['Baker,', 'the'], ['roof', 'were'], ['ail', 'unite'], ['of', 'keys,'], ['person', 'desirous'], ['', 'a'], ['', 'There'], ['justly', 'he'], ['fall.', 'Our'], ['and', 'the'], ['', 'them'], ['to', 'prevent'], ['fellow', 'citizens,'], ['of', 'Ins'], ['Angeles.', 'On'], ['', 'the'], ['Merinoes,', 'White,'], ['D', '.'], ['will', 'agree'], ['be', 'had'], ['side', 'of'], ['of', 'this'], ['school', 'is'], ['(I', 'r.Lnnidaiitly'], ['of', 'the'], ['Htate', 'shall'], ['thought', 'of'], ['is', 'not'], ['', 'certain'], ['section', '1'], ['thence', 'S.'], ['every', 'ship,'], ['we', 'receive'], ['lines', 'and'], ['of', 'it'], ['Convention', 'has'], ['corner', 'of'], ['years', 'covering'], ['fleet', 'would'], ['and', 'sent'], ['Keen,', 'J.'], ['hours,', 'pepper'], ['had', 'read'], ['aside', 'localities.'], ['', 'could'], ['', 'with'], ['he', 'believed'], ['their', 'case'], ['of', 'its'], ['lawfulfoundations', 'of'], ['of', 'tho'], ['and', 'have'], ['the', 'rioters,'], ['Bhowlng', 'a'], ['Legislature.', 'By'], ['seeking', 'posi\xad'], ['.', 'Finney'], ['courts', 'supply'], ['three', 'hundred'], ['at', 'a'], ['are', 'both'], ['throufh', 'tbe'], ['cleared', 'of'], ['the', 'obituary'], ['does', 'the'], ['sullen', 'and'], ['have', 'boen'], ['out', 'of'], ['ol', 'its'], ['are', 'placed'], ['his', 'knowledge'], ['at-', 'tend'], ['', 'also'], ['con', 'do'], ['at', 'certain'], ['dav', 'refuses'], ['Interest', 'now'], ['the', 'street.'], ['is', 'another'], ['the', 'next'], ['Mortgage', 'on'], ['authorisinglthe', 'building'], ['present', 'duties,'], ['been', 'on'], ['terms', '01'], ['to', 'prepare'], ['upon', 'a'], ['and', 'that'], ['a', 'Coun'], ['', 'occurs'], ['vested', 'in'], ['', 'fashion.'], ['distinct', 'organization,'], ['will', 'in'], ['', 'sion,'], ['at', 'night.'], ['', 'Dress'], ['pushed', 'her'], ['Richmond.', 'Mr.'], ['of', 'his'], ['will', 'limru'], ['wouneed.', 'Through'], ['was', '195'], ['Columbia,', 'the'], ['always', 'make'], ['gentry,', 'were'], ['heretofore', 'quiet'], [',948,199', '40,'], ['I', 'have'], ['', 'sary'], ['of', 'Fifth'], ['I', 'have'], ['4th', 'Thursday'], ['to’', 'her.'], ['', 'original'], ['', 'for'], ['cut', 'off'], ['in', 'incipient'], ['term,', 'whereas,'], ['inducements;—land', 'is'], ['Dr.', 'R'], ['medicine', 'to'], ['lie', 'retired,'], ['the', 'history'], ['bis', 'is'], ['has', 'no'], ['11.027', 'plates'], ['have', 'tho'], ['had', 'come'], ['labor', 'higher,'], ['troops', 'wero'], ['this', 'very'], ['decided', 'by'], ['great', 'American'], ['care', 'of'], ['up', 'the'], ['power', 're-'], ['will', 'he'], ['give', 'of'], ['vety', 'trilling'], ['in', 'the'], ['first', 'day'], ['ihe', 'cause'], ['Prior', 'to'], ['the', 'ancient'], ['this', 'can'], ['of', 'beginning,'], ['room', 'frontson'], ['on', 'it.'], ['go', 'on'], ['', 'put'], ['', 'now'], ['first,', 'that'], ['before', 'the'], ['', 'the'], ['our', 'political'], ['use', 'of'], ['<•«', 'is'], ['instrument;', 'and'], ['needy', 'contractors'], ['the', 'lau-'], ['', 'one'], ['think', '1'], ['raised', 'it'], ['and', 'perform'], ['', 'day'], ['', 'rights'], ['ami', 'firmly'], ['', 'and'], ['', 'Loma'], ['and', 'often'], ['this', 'Court,'], ['that', 'party,'], ['with', 'the'], ['Buttermilk', 'falls,'], ['vital', 'c'], ['eye.', 'shall'], ['he', 'knew'], ['the', 'haul.'], ['of', 'the'], ['the', 'Castle'], ['the', 'injunction'], ['rheumatism,', 'and'], ['objective', 'of'], ['my', 'ambition'], [';', 'those'], ['long', 'searching'], ['respectability', 'and'], ['<>l', 'hi,'], ['reported', 'as'], ['at', 'various'], ['By', 'Mr.'], ['different', 'language.'], ['25', 'to'], ['crops.', 'Shriveled'], ['"f', 'gloom'], ['To', 'this'], ['disappointing', 'and'], ['', 'of'], ['of', 'James'], ['deemed', 'advisable'], ['', 'committee,'], ['and', 'the'], ['emotions.', 'Allegiance'], ['', 'in'], ['of', 'dollars'], ['by', 'wise'], ['be', 'borne'], ['into', 'the'], ['less', 'engaged'], ['maiden,', 'though'], ['and', 'beneficence'], ['she', 'had'], ['.', 'Allwlucb'], ['of', 'his'], ['that', 'bis'], ['Special', 'Commissioner'], ['with', 'a'], ['whilst', '('], ['amendment', 'to'], ['opposite,', 'in'], ['Union?', 'and'], ['to', 'wsesuch'], ['of', 'a'], ['In', 'this'], ['proves', 'to'], ['', 'ii":'], ['ol', 'Louisiana,'], ['greatest', 'ambition'], ['upon', 'us,'], ['just', 'at'], ['I', 'iru'], ['us,', 'that'], ['the', 'best'], ['for', '25'], ['any', 'effort'], ['and', 'with'], ['', 'cording'], ['-el', 'a'], ['"', 'The'], ['a', 'Democratic'], ['McKoewn,', 'Clyde'], ['under', 'the'], ['lire', 'men'], ['the', 'plain'], ['some', 'one'], ['$5;', 'Mrs.'], ['ponds', 'until'], ['the', 'rush'], ['it', 'were,with'], ['', 'wealth'], ['', 'from'], ['E', '.,'], ['of', 'the'], ['', 'Panama,'], ['in', 'all'], ['scene', 'in'], ['13cents,', 'keg."'], ['stated', 'that'], ['the', 'Council'], ['immediately', 'entered'], ['all', 'American'], ['thence', 'N.'], ['West', 'by'], ['little', 'track,'], ['draft', 'ed.'], ['the', 'Elks,'], ['Janies', 'riv'], ['removed.', 'This'], ['', 'could'], ['', 'as'], ['be', 'more'], ['', 'other'], ['prosperous', 'indus-'], ['have', 'to'], ['6n', 'the'], ['', 'And'], ['', 'that'], ['be', 'lieve'], ['Ills', 'term'], ['casket', 'I'], ['as', 'may'], ['of', 'electing'], ['high', 'as'], ['Cabinet', 'making,'], ['not', 'the'], ['along', 'up'], ['', 'Island'], ['visiting', 'the'], ['Brazo', 'de'], ['instructor', 'of'], ['tin', 'many'], ['majority', 'ol'], ['', '"Do'], ['the', 'Clerk,'], ['upon', 'every'], ['', 'be'], ['or', 'acceptable'], ['the', 'Gallatin,'], ['of', 'a'], ['a', 'contract'], ['is', 'a'], ['of', 'the'], ['a', 'singlo'], ['work,', 'and'], ['we', 'might'], ['on', 'range'], ['county', 'called'], ['in', 'review'], ['off', 'crusts'], ['of', 'plain'], ['in', 'my'], ['', 'wear'], ['and', 'created,'], ['of', 'the'], ['3d.', 'That'], ['and', 'the'], ['gold.', 'Indeed,'], ['and', 'has'], ['awe', 'the'], ['that', 'high'], ['the', 'beauties'], ['has', 'turned'], ['tne', 'press,'], ['happily', 'ever'], ['is', 'nearly'], ['the', 'Pearce,'], ['', 'its'], ['the', 'full'], [':.t', 'the'], ['the', 'Hriiish'], ['stump', 'of'], ['into', 'the'], ['on', 'with'], ['coasts', 'of'], ['kinds', 'be'], ['No.', '259'], ['official', 'position'], ['working', 'classes'], ['this', 'second'], ['', 'January'], ['for', 'upwards'], ['and', 'sauntered'], ['Temple', 'of'], ['', 'soldier,'], ['conveyance', 'which'], ['and', 'the'], ['military', 'loan,'], ['for', '<7,000,'], ['but,', 'on'], ['', 'ily'], ['Board', 'to'], ['to', 'realize'], ['good', 'will'], ['present', 'at'], ['difficult', 'for'], ['ti', 'e'], ['barriers', 'against'], ['are', 'Maggie'], ['source', 'proceeds'], ['troublesome', 'to'], ['', 'from'], ['', 'F.'], ['after', 'the'], ['', 'them'], ['are', 'accused'], ['cooking', 'stove,'], ['eye', 'caught'], ['dollars,', 'and'], ['Mexican', 'campaign.'], ['two', 'looked'], ['lobby', 'or'], ['duties,', 'and'], ['considered', 'by'], ['their', 'extraordl-'], ['by', 'what'], ['hoped', 'to'], ['con-', 'tended'], ['the', 'hell'], ['in', 'some'], ['great', 'necessity.'], ['an', 'undivided'], ['a', 'brief'], ['is', 'to'], ['strait,', 'and'], ['the', 'new'], ['', 'Ferry,'], ['he', 'was'], ['went', 'to'], ['the', 'said'], ['the', 'president'], ['has', 'been'], ['', 'guard'], ['and', 'mas-'], ['only', 'way'], ['as', 'they'], ['was', 'not'], ['tho', 'side'], ['Greene,', 'Mr'], ['especially', 'in'], ['V.', 'was'], ['of', 'the'], ['', 'the'], ['we', 'know'], ['on', 'the'], ['to', 'allow'], ['land.', 'Tip-piala-natzit-kan'], ['', 'this'], ['for', 'miles'], ['would', 'offer'], ['not', 'think'], ['crop', 'developed'], ['on', 'the'], ['county', 'took'], ['great', 'worth'], ['', 'grafted'], ['', 'erally'], ['a', 'lover'], ['which', 'are'], ['tract', 'in'], ['will', 'be'], ['their', 'ze'], ['Republican', 'caucus'], ['is', 'a'], ['good', 'joke'], ['of', 'evidences'], ['but,', 'finding'], ['add', 'an'], ['the', 'Superior'], ['Gould,', 'Mrs.'], ['', 'acres;'], ['mature,', 'and'], ['tabtn', 'a'], ['stockholders', 'who'], ['would', 'be'], ['do', 'not'], ['food', 'is'], ['', 'tleman'], ['what', 'was'], ['', 'quired'], ['have', 'just'], ['lastseasou.is', 'now'], ['in', 'geography.'], ['', 'night.'], ['then', 'they'], ['the', "pauper's"], ['disguised.', 'He'], ['and', 'it'], ['floating', 'vessels'], ['od', 'a'], ['', 'questions'], ['less', 'than'], ['But', 'it'], ['could', 'dispose'], ['was', 'in'], ['measures', 'urged'], ['thinking', 'lie'], ['I', 'did'], ['time', 'of'], ['Lincoln', 'that'], ['were', 'no'], ['man', 'is'], ['', 'thorities,'], ['com\xad', 'pany.'], ['when', 'I'], ['respect', 'the'], ['the', 'depth'], ['country', 'which'], ['increased', 'rigor'], ['made,', 'viz:'], ['accuracy', 'of'], ['weight', 'of'], ['the', 'sweet'], ['out', 'of'], ['him,', 'lie'], ['to', 'allow'], ['and', 'consoli'], ['in', 'our'], ['to', 'the'], ['on', 'hand.'], ['good', 'to'], ['letter', 'was'], ['only', 'for'], ['American', 'decisions'], ['to', 'a'], ['shines', 'with'], ['competent', 'in'], ['than', 'made'], ['inadvisable', 'to'], ['', 'had'], ['public', 'restaurant,'], ['spot', 'leas'], ['the', 'joint'], ['raided', 'in'], ['', 'city'], ['and', 'a'], ['what', 'he'], ['and', 'there'], ['which', 'was'], ['feet', 'and'], ['of', 'follower?'], ['which,', 'on'], ['time', 'she'], 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print(results)
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0.019691226071633493, 'no': 0.017594246289943646}, {'the': 0.13208187323245826, 'of': 0.08012168634042893, 'and': 0.06406071718010131, 'a': 0.047669487381373256, 'to': 0.03468962138955572, 'in': 0.02310275767337705, 'at': 0.015812913139426343, '.': 0.013881137728812965, '<s>': 0.013755337053032609}, {'part': 0.07268713102532033, 'one': 0.07071065938650846, 'some': 0.043508101530019876, 'out': 0.03575042106872343, 'members': 0.025760665467621124, 'and': 0.022440178638608456, 'tion': 0.02191026583655202, 'portion': 0.021052670553751075, 'side': 0.02092702198887348}, {'to': 0.5119351630414154, 'will': 0.1105273535889225, 'and': 0.08747627310194998, 'would': 0.061656979427197854, 'not': 0.042349883558257174, 'I': 0.02852293903610542, 'could': 0.022851834048647966, 'they': 0.02221562584767905, 'we': 0.0202847875694922}, {'and': 0.10479663189779309, 'to': 0.07974177454958935, 'of': 0.053650509361460576, 'the': 0.04746932779685031, 'which': 0.028882037624533317, 'that': 0.02768632969742771, 're-': 0.024280175106059468, 'in': 0.024236729627737486, 'for': 0.023624629292751668}, {'be': 0.20037775489565451, 'was': 0.19527985389803085, 'been': 0.12990670001970908, 'is': 0.07423765895623358, 'were': 0.07369619080367386, 'and': 0.061774693708341856, 'Action': 0.057470491167890964, 'are': 0.04968755789535415, 'being': 0.035425795736994524}, {'of': 0.25717168850799177, 'in': 0.12579859333765134, 'to': 0.11694438835862833, 'for': 0.09240234963802367, 'and': 0.0824575802797303, 'at': 0.06378736339164663, 'with': 0.05113889386577991, 'by': 0.04369719630708011, 'from': 0.04180524002897251}, {'of': 0.2930396145853633, 'to': 0.11636253998772615, 'for': 0.10570988633315767, 'by': 0.07928500468504723, 'and': 0.07123226570501578, 'that': 0.06783798008056992, 'with': 0.05829103668481965, 'in': 0.05800580237049337, 'at': 0.03761662594512555}, {'had': 0.3311247816674146, 'have': 0.21287617705380285, 'has': 0.12875030775119525, 'was': 0.08196102878130442, 'be': 0.04144294302242235, 'been': 0.03966264086071291, 'and': 0.03913243399931012, 'were': 0.02501315426299109, 'he': 0.02376980209005908}, {'a': 0.8077781483306005, 'that': 0.03737105557154736, 'of': 0.026732715310394613, 'A': 0.026195728740259678, 'and': 0.02238608961061418, 'the': 0.018772749948493785, 'as': 0.012677393554533997, 'is': 0.010727566438029431, 'in': 0.00988744895325715}, {'more': 0.029817207518464835, 'due': 0.027825799603035665, 'public': 0.025600547763764272, 'good': 0.025594956686470237, 'in': 0.024649600110616888, 'time': 0.020346459387317415, 'it': 0.017453399124434527, 'risk': 0.017327866749668297, 'large': 0.01566935173013818}, {'the': 0.19670387957172328, 'of': 0.12034700726956073, 'a': 0.08438228089640598, 'to': 0.07002755359439007, 'and': 0.06281574081115311, 'be': 0.0453128674171294, 'in': 0.03379866218947241, 'is': 0.03220276533394172, 'not': 0.029189418599409524}, {'the': 0.307612587737178, 'Supreme': 0.13454945922446296, 'District': 0.06692144991661478, 'said': 0.05305002842093336, 'Circuit': 0.04941150159092748, 'County': 0.04197666089388177, 'this': 0.03072926237126224, 'tho': 0.026012891377893768, 'of': 0.0224182925960057}, {'and': 0.08993882390965129, 'recorded': 0.03592850439397521, 'was': 0.034406616477799225, 'made': 0.03327934968747612, 'that': 0.032994209209894564, "o'clock": 0.029817856345727856, 'up': 0.027397770336943364, 'is': 0.024270559851647843, 'found': 0.02383358239775871}, {'the': 0.14049171217036022, 'of': 0.11129721382894606, 'and': 0.08908987543691149, 'to': 0.08312287486148097, 'a': 0.04211477594316105, 'be': 0.02951180015049161, 'or': 0.029425595758187317, 'his': 0.024543990657609, 'on': 0.02261090105281294}, {'to': 0.32146187778697455, 'will': 0.12283919921198497, 'be-': 0.10739691173627343, 'had': 0.0702107019309501, 'has': 0.06594344542269237, 'have': 0.06438202673201848, 'not': 0.045424208970167086, 'would': 0.043147137193373424, 'I': 0.03669646143829862}]
for elem in results:
print(gonito_format(elem, const_wildcard=False), end='')
the:0.10147410000115062 of:0.09111821715327291 to:0.0800439308707209 and:0.06939831712209747 in:0.03536933332669831 a:0.028398293798845314 was:0.02727199167456622 be:0.0266867198491962 is:0.02415138080020866 :0.5160877154032434 hundred:0.20899361853515802 dred:0.017033094318071044 eight:0.013504214417413191 degrees:0.012456671526657324 due:0.011095587193587319 north:0.010896831403482672 long:0.010890732984234812 men:0.010857278348412578 dollars:0.010458383799497265 :0.6938135874734858 a:0.39106347091712873 the:0.36170634817226427 this:0.045750742182119164 other:0.04101326388674283 of:0.036223022445897486 and:0.033378224696135494 his:0.030199108590644057 The:0.02709066639429355 tho:0.023575152714774478 :0.01 it:0.12438046964611195 they:0.09908896108784665 and:0.09635238176428093 which:0.0793610016130424 he:0.07389255269764594 you:0.059932821593910154 It:0.0582638900637266 I:0.05379108227004911 who:0.05158640078808042 :0.30335043847530585 able:0.08041847285999441 and:0.06501596389430095 order:0.06004630970980249 enough:0.05591913322322703 is:0.0531264962652024 him:0.048322678282867015 right:0.046470580848894764 was:0.04217700213240034 attempt:0.04192635610481366 :0.5065770066784969 is:0.26351219754795635 be:0.2078310710301647 are:0.13519178924723887 was:0.1129507276169888 and:0.07266071628417264 been:0.03818430286149086 Is:0.03605566750304204 not:0.03539323581294185 were:0.03506637057818147 :0.06315392151782241 and:0.11582081944112449 was:0.04225261395959518 held:0.03592895762799326 Beginning:0.02926079870317736 is:0.027806631077598554 look:0.026545353863800903 arrived:0.026240397869270526 that:0.0255265603479058 interest:0.024134996272950678 :0.6464828708365833 and:0.17128521616957315 of:0.15663003206239498 is:0.06033175145704086 are:0.055248814447034236 it:0.0540881034808143 after:0.052354816840982296 in:0.04540953072793188 that:0.030524961225887097 was:0.02938353503450492 :0.3447432385538363 of:0.3321050614817467 in:0.14910127502055798 and:0.09381302886709715 to:0.07400471943570397 with:0.06733612174895594 for:0.06111015936998158 that:0.039770634822513175 In:0.034716076833201 on:0.02988931332984859 :0.11815360909039395 and:0.19354989935298222 that:0.1579746913565372 as:0.15448361679314834 but:0.0475520605658099 even:0.037988917866489995 or:0.024052538746895356 But:0.02381979456009173 And:0.020301183230292875 and,:0.019836146554616362 :0.320441150973136 the:0.13208187323245826 of:0.08012168634042893 and:0.06406071718010131 a:0.047669487381373256 to:0.03468962138955572 in:0.02310275767337705 at:0.015812913139426343 .:0.013881137728812965 <s>:0.013755337053032609 :0.5748244688814336 the:0.6457688471739997 a:0.10876582984709046 be-:0.056144161051548985 The:0.042204120646873455 tho:0.0333605042611211 be¬:0.0194954216076803 be:0.017704687410423973 no:0.015251365570699942 and:0.0150275902002734 :0.046277472230288594 of:0.15945765284713104 and:0.09343927188959995 to:0.07148357208661185 the:0.06904503677902835 for:0.0457742458321099 a:0.040828961190166144 be:0.0367262297794992 in:0.03666369000645223 was:0.028448813936381198 :0.4181325256530201 <s>:0.05426565324719795 and:0.044445972365426564 made:0.021694712583539576 was:0.020931920880133754 recorded:0.017387201838834423 that:0.01661780384100564 be:0.014822874002807063 is:0.01378718404889997 o'clock:0.013297718418623995 :0.782748958773531 to:0.4279840414289704 and:0.09790467904153906 we:0.0823850058263962 I:0.06698779579928948 will:0.06383779006001988 not:0.06104220118102934 would:0.04995839358000613 they:0.035629495072022926 you:0.034289026737185334 :0.07998157127354125 and:0.0666672222818591 of:0.046193698533595215 to:0.037784114220044525 the:0.03482682720566339 <s>:0.019558576724369486 a:0.017718890064596274 his:0.01661151532382775 in:0.016191488009760443 at:0.01521039466340531 :0.7292372729728785 of:0.33016872699590255 to:0.120610215203289 and:0.08667846604786278 for:0.05683906611859967 with:0.05673218437827495 by:0.051106646881204115 that:0.02995459658412562 from:0.02989066395827932 on:0.027097492579813573 :0.21092194125264843 and:0.08065115970908836 them:0.034741264455021924 put:0.03393847235235448 out:0.030324100456217955 carry:0.024614501276048497 was:0.023915996504260528 work:0.023096297608759246 it:0.022532056597830582 that:0.022361432657540006 :0.7038247183828784 of:0.12642654347255788 and:0.06920770004749957 in:0.04113063429839098 to:0.039460944154770555 that:0.029877787057406513 on:0.02517998801676788 for:0.024471087243369164 things:0.01672232242668383 those:0.013689248065138443 :0.6138337452174152 the:0.13208187323245826 of:0.08012168634042893 and:0.06406071718010131 a:0.047669487381373256 to:0.03468962138955572 in:0.02310275767337705 at:0.015812913139426343 .:0.013881137728812965 <s>:0.013755337053032609 :0.5748244688814336 and:0.09908218571238031 of:0.0769151570275628 as:0.04400910091636531 that:0.03987650373371493 all:0.036869080797058966 but:0.032298979891867606 for:0.03004246258835539 so:0.021359486626302743 fact:0.0160618876200197 :0.6034851550863722 to:0.34970354222480854 will:0.19176192979129858 not:0.09414086703025835 may:0.06008402130311699 the:0.05489464601832695 and:0.05300390730234811 shall:0.052031543443419134 a:0.0466779209798249 would:0.0450512759245379 :0.052650345982060545 with-:0.07980306238892035 and:0.07600317116707721 find:0.07581566775452665 pointed:0.06615887843051825 go:0.058961713326761415 carry:0.058362413307848963 get:0.04870678743233526 brought:0.04828336917317886 went:0.047994898107255365 :0.4399100389115777 and:0.04440005379124634 as:0.03572535139008519 went:0.027002326805406957 him:0.025212269516833957 them:0.02153360171858815 up:0.020643866738997867 is:0.020539101811950334 go:0.019713515897778196 able:0.019233667677612948 :0.7659962446515001 and:0.07496744927759343 to:0.04881329766255247 will:0.035034172559629914 not:0.032807325221249406 I:0.030787804680282135 the:0.029891008298762914 would:0.023147759574589904 he:0.022374203253604744 is:0.021686886471943872 :0.6804900929997912 of:0.34120922445500185 to:0.1040885972550642 in:0.10293120130657726 and:0.061209794024558055 on:0.055107805284584685 by:0.053605999453237824 for:0.0528380747026686 with:0.04028888792001937 that:0.03997061633295227 :0.1487497992653359 the:0.3939590666536084 of:0.1456155013805246 a:0.10240899903373575 and:0.056950804963789584 by:0.05025014126192817 for:0.04777049126230001 to:0.037725922518988236 The:0.02288435694767419 with:0.01877619933150951 :0.12365851664594152 and:0.0603443515981216 it:0.057758619942490125 to:0.036968149526691425 that:0.02914346259179048 is:0.027346460663969292 It:0.020737604203570945 of:0.018045576123751305 was:0.018009351090075742 which:0.017193536629341824 :0.7144528876301973 the:0.29029291752996095 of:0.2657920946732921 his:0.05163956680968951 to:0.05055019750801179 in:0.0464250320710032 their:0.04604139686994079 good:0.0441809062152359 public:0.03641956719289069 perfect:0.0333854795224581 :0.13527284160751696 was:0.07650751245762076 looked:0.06212267273319501 and:0.061495315807971525 held:0.05935352740393193 arrived:0.05517432882686205 presided:0.04446791418641999 laughed:0.04221685362511652 called:0.03738565489374883 be:0.03464768313438387 :0.5266285369307495 to:0.08931606283397064 the:0.0884031794695147 of:0.0722907445228048 and:0.05687411227644874 in:0.03218499153857406 be:0.026863622488952545 was:0.02366411475909885 that:0.020584370592096474 for:0.019862109775457847 :0.5699566917430813 we:0.14061076615510062 I:0.10160630465978483 they:0.08058734155978471 and:0.07883651104557017 he:0.07393874556028772 who:0.07030055558844002 which:0.06940665023896395 it:0.06657078356340392 that:0.031327416136994024 :0.28681492549167004 the:0.4044287728989089 a:0.1651158177173993 at:0.06392716937058537 of:0.05169544472202966 The:0.05116272930828495 an:0.03351730633822887 for:0.032930178035168345 and:0.028598159985317107 tho:0.022631786219878082 :0.14599263540419943 the:0.15378903668702737 of:0.09249548824970906 and:0.07595235865820654 to:0.07006226204227813 for:0.02569471643071183 in:0.025365441158559817 be:0.023483724513089645 is:0.020659405704139575 was:0.018878285055910545 :0.4936192815003675 and:0.0120864997976485 men:0.009953325899059158 in:0.009210879674555108 ;:0.008802801507405584 there:0.007570856363255082 to:0.007221161797799322 :0.006853923248674552 right:0.00678610578059497 man:0.0067764212634914955 :0.9247380246675162 of:0.1978328667254137 and:0.12171540832325842 or:0.10172675114359758 the:0.0715347335742929 about:0.054014235225233305 to:0.05040023388824486 for:0.04610287019661807 by:0.03689998682449155 in:0.029583967752202928 :0.2901889463466467 and:0.09289682875398107 to:0.08362463815713578 of:0.07865776104634967 the:0.06502250552004986 was:0.04293123221278658 be:0.040856920591184086 for:0.03853427113734677 is:0.031189643383301092 in:0.030049705904780007 :0.4962364932930851 feet;:0.1338014044916582 ;:0.05236178963222644 running:0.0496232440187462 feet,:0.04914909326083571 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:0.4531492073438318 and:0.06208548553749389 of:0.059861363642291034 to:0.0594353799968304 I:0.038039420185191325 for:0.036810863436358254 the:0.02472440294479202 in:0.02410707614225612 wi:0.02262174361695196 is:0.022237981505279097 :0.6500762829925559 hundred:0.024173689727291232 up:0.0056779925577832265 men:0.005557899537168564 Hundred:0.0049284889476935035 John:0.004575624030095375 William:0.004547287494524766 him:0.004160062976896217 ;:0.004139643508979887 due:0.0038538925362626643 :0.9383854186833046 of:0.2656297374079294 and:0.1603316062050206 in:0.11745389224660788 for:0.08540704797531658 to:0.0798527609542191 that:0.05815698726272474 with:0.057819922772087785 all:0.04632594767190936 on:0.032150794480396636 :0.09687130302378795 it:0.17179737676551296 he:0.125829304720175 It:0.12209201472181 I:0.05849427898476466 He:0.055779185057685615 which:0.05343899164929195 and:0.04479014026557512 who:0.038085293062393825 there:0.03504686283043146 :0.2946465519423594 he:0.3763075052589377 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:0.5116500281112223 to:0.1372314543028761 and:0.10296039174025212 the:0.0980193011297537 of:0.07362193552282163 in:0.035390626948473516 a:0.020251090807030078 <s>:0.017746817217017118 not:0.01702205167118406 that:0.01610815514958733 :0.4816481755110043 and:0.08993882390965129 recorded:0.03592850439397521 was:0.034406616477799225 made:0.03327934968747612 that:0.032994209209894564 o'clock:0.029817856345727856 up:0.027397770336943364 is:0.024270559851647843 found:0.02383358239775871 :0.6681327273891259 the:0.5411502921123026 high:0.08308356211598286 and:0.06552151089161959 The:0.0495428269491904 low:0.047646349693965265 tho:0.032775629143080215 in:0.03072188077245258 of:0.02779091427612231 a:0.02538972630365791 :0.09637730774162627 and:0.08010061911956774 the:0.06342492458561132 of:0.06128617556768118 a:0.0549726386574644 to:0.03897501736850034 that:0.03211159626684709 in:0.024357629728291356 for:0.020270934482351444 her:0.018141288010487547 :0.6063591762131976 of:0.20185370990858556 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which:0.028882037624533317 that:0.02768632969742771 re-:0.024280175106059468 in:0.024236729627737486 for:0.023624629292751668 :0.5856318550457971 is:0.0952086332938432 and:0.06485470206051079 was:0.04861582137402764 simply:0.045918643518629405 not:0.04154667993226221 it:0.0387718806021684 but:0.024772544538330048 that:0.019553489542885834 it,:0.01756175467118068 :0.6031958504661618 and:0.1249590163878478 of:0.10132944700906286 to:0.08464269606101492 the:0.07917494017810507 on:0.030781821684468746 in:0.030775427254350597 <s>:0.027296937937318053 that:0.025864106241287706 from:0.022204562405101973 :0.47297104484144226 and:0.10479663189779309 to:0.07974177454958935 of:0.053650509361460576 the:0.04746932779685031 which:0.028882037624533317 that:0.02768632969742771 re-:0.024280175106059468 in:0.024236729627737486 for:0.023624629292751668 :0.5856318550457971 be:0.2911121983291653 was:0.1390769351280408 been:0.1108454610611129 is:0.07523176050842062 and:0.05529993874811094 were:0.05294084553472021 are:0.051430711099856086 being:0.03267655685615234 he:0.019926433193141444 :0.17145915954127935 the:0.3531755021324238 such:0.08824629902550707 these:0.06070480773621665 best:0.05383563939105486 his:0.05173168016761895 our:0.04854000812216378 other:0.04847733522273064 business:0.04780934784034577 their:0.046711702914069224 :0.20076767744786927 ;:0.05418902122739456 it,:0.02132544226860451 him,:0.014282448239279294 and:0.013461322111999062 is:0.012561994906254866 them,:0.010674971250995898 time,:0.010317011803786226 ,:0.006870117455022458 nothing:0.006578634194520623 :0.8497390365421426 the:0.19737203503818787 a:0.15933425691090275 of:0.11078491605692653 and:0.06809753964201927 at:0.046961534748461264 to:0.046763316658240524 in:0.036454494759249376 for:0.032843460282801766 an:0.023915433652431217 :0.27747301225077947 to:0.19305317250641824 I:0.16521555490719494 would:0.09757322663786742 we:0.09516384096976814 they:0.09018430848753058 who:0.07852064646638084 could:0.06267515599758222 must:0.05814316791895534 should:0.05128203218226723 :0.10818889392603503 to:0.719791006336938 not:0.05902346058653421 will:0.048994717201977 would:0.041579970363008555 and:0.030291533772023555 can:0.02299021142328676 may:0.021469247487898576 could:0.018515801162938474 To:0.01660943979738774 :0.020734611868007062 a:0.47524675960380375 the:0.29484488049432034 The:0.044564426636170655 of:0.03604413874272208 his:0.027406658747879398 this:0.02585790939018613 any:0.02228409287772844 A:0.019691226071633493 no:0.017594246289943646 :0.03646566114561209 the:0.13208187323245826 of:0.08012168634042893 and:0.06406071718010131 a:0.047669487381373256 to:0.03468962138955572 in:0.02310275767337705 at:0.015812913139426343 .:0.013881137728812965 <s>:0.013755337053032609 :0.5748244688814336 part:0.07268713102532033 one:0.07071065938650846 some:0.043508101530019876 out:0.03575042106872343 members:0.025760665467621124 and:0.022440178638608456 tion:0.02191026583655202 portion:0.021052670553751075 side:0.02092702198887348 :0.6652528845040218 to:0.5119351630414154 will:0.1105273535889225 and:0.08747627310194998 would:0.061656979427197854 not:0.042349883558257174 I:0.02852293903610542 could:0.022851834048647966 they:0.02221562584767905 we:0.0202847875694922 :0.09217916078033246 and:0.10479663189779309 to:0.07974177454958935 of:0.053650509361460576 the:0.04746932779685031 which:0.028882037624533317 that:0.02768632969742771 re-:0.024280175106059468 in:0.024236729627737486 for:0.023624629292751668 :0.5856318550457971 be:0.20037775489565451 was:0.19527985389803085 been:0.12990670001970908 is:0.07423765895623358 were:0.07369619080367386 and:0.061774693708341856 Action:0.057470491167890964 are:0.04968755789535415 being:0.035425795736994524 :0.12214330291811663 of:0.25717168850799177 in:0.12579859333765134 to:0.11694438835862833 for:0.09240234963802367 and:0.0824575802797303 at:0.06378736339164663 with:0.05113889386577991 by:0.04369719630708011 from:0.04180524002897251 :0.1247967062844954 of:0.2930396145853633 to:0.11636253998772615 for:0.10570988633315767 by:0.07928500468504723 and:0.07123226570501578 that:0.06783798008056992 with:0.05829103668481965 in:0.05800580237049337 at:0.03761662594512555 :0.11261924362268136 had:0.3311247816674146 have:0.21287617705380285 has:0.12875030775119525 was:0.08196102878130442 be:0.04144294302242235 been:0.03966264086071291 and:0.03913243399931012 were:0.02501315426299109 he:0.02376980209005908 :0.07626673051078735 a:0.8077781483306005 that:0.03737105557154736 of:0.026732715310394613 A:0.026195728740259678 and:0.02238608961061418 the:0.018772749948493785 as:0.012677393554533997 is:0.010727566438029431 in:0.00988744895325715 :0.02747110354226936 more:0.029817207518464835 due:0.027825799603035665 public:0.025600547763764272 good:0.025594956686470237 in:0.024649600110616888 time:0.020346459387317415 it:0.017453399124434527 risk:0.017327866749668297 large:0.01566935173013818 :0.7957148113260897 the:0.19670387957172328 of:0.12034700726956073 a:0.08438228089640598 to:0.07002755359439007 and:0.06281574081115311 be:0.0453128674171294 in:0.03379866218947241 is:0.03220276533394172 not:0.029189418599409524 :0.3252198243168138 the:0.307612587737178 Supreme:0.13454945922446296 District:0.06692144991661478 said:0.05305002842093336 Circuit:0.04941150159092748 County:0.04197666089388177 this:0.03072926237126224 tho:0.026012891377893768 of:0.0224182925960057 :0.26731786587084 and:0.08993882390965129 recorded:0.03592850439397521 was:0.034406616477799225 made:0.03327934968747612 that:0.032994209209894564 o'clock:0.029817856345727856 up:0.027397770336943364 is:0.024270559851647843 found:0.02383358239775871 :0.6681327273891259 the:0.14049171217036022 of:0.11129721382894606 and:0.08908987543691149 to:0.08312287486148097 a:0.04211477594316105 be:0.02951180015049161 or:0.029425595758187317 his:0.024543990657609 on:0.02261090105281294 :0.4277912601400393 to:0.32146187778697455 will:0.12283919921198497 be-:0.10739691173627343 had:0.0702107019309501 has:0.06594344542269237 have:0.06438202673201848 not:0.045424208970167086 would:0.043147137193373424 I:0.03669646143829862 :0.12249802957726698
a='able:0.08041847285999441 and:0.06501596389430095 order:0.06004630970980249 enough:0.05591913322322703 is:0.0531264962652024 him:0.048322678282867015 right:0.046470580848894764 was:0.04217700213240034 attempt:0.04192635610481366 :0.5065770066784969'
elems = a.split('\t')
elems
['able:0.08041847285999441', 'and:0.06501596389430095', 'order:0.06004630970980249', 'enough:0.05591913322322703', 'is:0.0531264962652024', 'him:0.048322678282867015', 'right:0.046470580848894764', 'was:0.04217700213240034', 'attempt:0.04192635610481366', ':0.5065770066784969']
print(sum([float(entry.split(':')[1]) for entry in elems]))
1.0
for x in elems:
a = x.split(':')[1]
print(a)
0.08041847285999441 0.06501596389430095 0.06004630970980249 0.05591913322322703 0.0531264962652024 0.048322678282867015 0.046470580848894764 0.04217700213240034 0.04192635610481366 0.5065770066784969
entry = {'the': 0.10045935900113911, 'of': 0.09020703498174018, 'to': 0.07924349156201368, 'and': 0.0687043339508765, 'in': 0.035015639993431324, 'a': 0.02811431086085686, 'was': 0.026999271757820558, 'be': 0.026419852650704238, 'is': 0.023909866992206572}
summarize_probs_unk(entry, const_wildcard=False)
[('the', 0.2075982821656445), ('of', 0.18641195492052778), ('to', 0.16375589974544083), ('and', 0.14197683369027864), ('in', 0.07235947734331606), ('a', 0.05809794823515274), ('was', 0.055793730841776454), ('be', 0.054596366927778785), ('is', 0.04940950613008436), ('<unk>', 0.01)]
b = dict(get_values_from_model(['le', 'to'], model, vocab, k=10))
[('<unk>', 0.23124052584171295), ('and', 0.025475040078163147), ('to', 0.016587475314736366), ('will', 0.01190512627363205), ('not', 0.011148410849273205), ('I', 0.010462148115038872), ('the', 0.010157403536140919), ('would', 0.007865948602557182), ('he', 0.0076030828058719635), ('is', 0.007369522470980883)]
/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)
b
{'<unk>': 0.23124052584171295, 'and': 0.025475040078163147, 'to': 0.016587475314736366, 'will': 0.01190512627363205, 'not': 0.011148410849273205, 'I': 0.010462148115038872, 'the': 0.010157403536140919, 'would': 0.007865948602557182, 'he': 0.0076030828058719635, 'is': 0.007369522470980883}