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echo 'deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64 /' > /etc/apt/sources.list.d/cuda.list
echo 'deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1404/x86_64 /' > /etc/apt/sources.list.d/nvidia-ml.list

apt-get update
apt-get install --force-yes -y nvidia-352
apt-get install --force-yes -y cuda-7-5 cuda-command-line-tools-7-5 cuda-core-7-5 cuda-cublas-7-5 cuda-cublas-dev-7-5 cuda-cudart-7-5 cuda-cudart-dev-7-5 cuda-cufft-7-5 cuda-cufft-dev-7-5 cuda-curand-7-5 cuda-curand-dev-7-5 cuda-cusolver-7-5 cuda-cusolver-dev-7-5 cuda-cusparse-7-5 cuda-cusparse-dev-7-5 cuda-documentation-7-5 cuda-driver-dev-7-5 cuda-gdb-src-7-5 cuda-ld-conf-7-5 cuda-license-7-5 cuda-minimal-build-7-5 cuda-misc-headers-7-5 cuda-npp-7-5 cuda-npp-dev-7-5 cuda-nvrtc-7-5 cuda-nvrtc-dev-7-5 cuda-runtime-7-5 cuda-samples-7-5 cuda-toolkit-7-5 cuda-visual-tools-7-5
apt-get install -y build-essential python-dev python-virtualenv python-pip
apt-get install -y libatlas-dev liblapack-dev
ap

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import 'package:flutter/material.dart';
import 'package:flutter_hooks/flutter_hooks.dart';

void main() {
  runApp(MyApp());
}

enum ChildType { a, b }

class ChildState<T> {

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 session_config = tf.ConfigProto(
            intra_op_parallelism_threads=64,
            inter_op_parallelism_threads=4,
    )
...
    run_config = tpu.RunConfig(
        session_config=session_config,

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from tensorflow.core.protobuf import rewriter_config_pb2
config = tf.ConfigProto()
config.graph_options.rewrite_options.memory_optimization = (
      rewriter_config_pb2.RewriterConfig.NO_MEM_OPT)
off = rewriter_config_pb2.RewriterConfig.OFF
config.graph_options.rewrite_options.layout_optimizer = off
config.graph_options.rewrite_options.constant_folding = off
config.graph_options.rewrite_options.arithmetic_optimization = off
config.graph_options.rewrite_options.dependency_optimization = off
config.graph_options.rewrite_options.loop_optimization = off

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import tensorflow as tf
import sys
from tensorflow.contrib.tpu.python.tpu import session_support
 
def reset_tpu(name):
  print('Resetting: %s' % name) 
  resolver = tf.contrib.cluster_resolver.TPUClusterResolver(tpu=name, job_name='worker')
  address = resolver.master()
  cluster_def = resolver.cluster_spec().as_cluster_def()
 

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# Copyright 2017 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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# Copyright 2017 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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import numpy as np

from keras.models import Sequential
from keras.layers.core import Dense, Activation, Dropout, TimeDistributedDense
from keras.layers.recurrent import LSTM

text = open('/home/russellp/w/data/citation-graph/abstracts.txt', 'r').read()
char_to_idx = { ch: i for (i, ch) in enumerate(sorted(list(set(text)))) }
idx_to_char = { i: ch for (ch, i) in char_to_idx.items() }
vocab_size = len(char_to_idx)

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