from tensorflow.python.ops import tensor_array_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variable_scope as vs
from tensorflow.python.ops import rnn
from tensorflow.python.ops import nn
from tensorflow.python.ops import init_ops
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import os | |
import numpy as np | |
from matplotlib import pyplot as plt | |
from time import time | |
from foxhound import activations | |
from foxhound import updates | |
from foxhound import inits | |
from foxhound.theano_utils import floatX, sharedX |
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# Stacked LSTMs | |
# Author: Kyle Kastner | |
# Based on script from /u/siblbombs | |
# License: BSD 3-Clause | |
import tensorflow as tf | |
from tensorflow.models.rnn import rnn | |
from tensorflow.models.rnn.rnn_cell import LSTMCell | |
import numpy as np | |
import time |
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""" | |
Beam decoder for tensorflow | |
Sample usage: | |
``` | |
from tf_beam_decoder import beam_decoder | |
decoded_sparse, decoded_logprobs = beam_decoder( | |
cell=cell, |
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from tf_logger import TFLogger | |
""" Example of using TFLogger to save train & dev statistics. To visualize | |
in tensorboard simply do: | |
tensorboard --logdir /path/to/summaries | |
This code does depend on Tensorflow, but does not require that your model | |
is built using Tensorflow. For instance, could build a model in Chainer, then |
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Note: I'm updating this gist as I encounter new reviews, so make sure you're reading the latest revision!
Just as the previous year I collected (and keep doing so) links to various summaries and takeaways from this year's NIPS.
- NIPS 2016 Symposium on People and machines: Public views on machine learning, and what this means for machine learning researchers. (Notes and panel discussion) by /u/gcr
- NIPS 2016 summary, wrap up, and links to slides by /u/beamsearch
- Post NIPS Reflections by Neil Lawrence
- [Some general take aways from #NIPS2016](https://medium.com/@IgorCarron/some-general-take-aways-from-ni
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# Copyright 2015 The TensorFlow Authors. All Rights Reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, |
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