dataset = ArxivAbstracts(
categories='stat.ML cs.NE cs.LG math.OC',
keywords='neural network deep')
max_length = 50
sampling_temperature = 0.5
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#!/usr/bin/python3 | |
"""Move or delete directories via your text editor. | |
Installation: | |
- Install sh.py via `pip3 install sh`. | |
- Save this file into a directory in your $PATH, for example `~/bin`. | |
""" | |
import argparse | |
import tempfile |
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"""Character based language modeling with multi-layer GRUs. | |
To train the model: | |
python3 tf_char_rnn.py --mode training \ | |
--logdir path/to/logdir --corpus path/to/corpus.txt | |
To generate text from seed words: | |
python3 tf_char_rnn.py --mode sampling \ |
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import numpy as np | |
class Network: | |
def __init__(self, num_inputs, num_hidden, num_output, | |
init_weight_scale=0.5): | |
self.w1 = np.random.normal( | |
0, init_weight_scale, (num_inputs + 1, num_hidden)) | |
self.w2 = np.random.normal( |
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algorithms: | |
- config: | |
| frame_skip: 6 | |
| history: 6 | |
| replay_capacity: 5e4 | |
name: DQN | |
train_steps: 200000 | |
type: DQN | |
envs: | |
- SimpleGather-v0 |
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keygen | |
uprises | |
non-infected | |
counter-weight | |
pipetted | |
quispel | |
rooster-whistles | |
moisturisers | |
enfeoffing | |
pre-adolescents |
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# Working example for my blog post at: | |
# http://danijar.com/variable-sequence-lengths-in-tensorflow/ | |
import functools | |
import sets | |
import tensorflow as tf | |
from tensorflow.models.rnn import rnn_cell | |
from tensorflow.models.rnn import rnn | |
def lazy_property(function): |
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# Working example for my blog post at: | |
# http://danijar.com/variable-sequence-lengths-in-tensorflow/ | |
import functools | |
import sets | |
import tensorflow as tf | |
from tensorflow.models.rnn import rnn_cell | |
from tensorflow.models.rnn import rnn | |
def lazy_property(function): |
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import argparse | |
import collections | |
import re | |
TOKEN_REGEX = re.compile(r'[A-Za-z]+') | |
BLACKLIST = set([ | |
'pdf', 'and', 'the', 'proceedings', 'conference', 'ieee', 'for', | |
'about', 'details', 'data', 'with', 'arxiv', 'preprint', 'advances']) | |
def tokenize(line): |
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# Example for my blog post at: | |
# http://danijar.com/introduction-to-recurrent-networks-in-tensorflow/ | |
import functools | |
import sets | |
import tensorflow as tf | |
def lazy_property(function): | |
attribute = '_' + function.__name__ |