yaroslavvb

#!/usr/bin/env python
# Benchmark transferring data, part of troubleshooting https://github.com/tensorflow/tensorflow/issues/6116
#
# Take a independent workers communicating with b parameter shards
# Each worker tries to add to variables stored on parameter server as fast as
# possible.
# 
# macbook
# ps=1: 1.6 GB/s
# ps=2: 2.6 GB/s

noahcoad

# convert yaml to json
# pip3 install pyyaml
# http://pyyaml.org/wiki/PyYAMLDocumentation
# py3 yaml2json.py < ~/code/manpow/homeland/heartland/puphpet/config.yaml
# gist https://gist.github.com/noahcoad/51934724e0896184a2340217b383af73

import yaml, json, sys
sys.stdout.write(json.dumps(yaml.load(sys.stdin), sort_keys=True, indent=2))

nikitakit

"""
Beam decoder for tensorflow

Sample usage:

```
from tf_beam_decoder import  beam_decoder

decoded_sparse, decoded_logprobs = beam_decoder(
    cell=cell,

danijar

# 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):

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

karpathy

"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:
  
  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):

mbostock

license: gpl-3.0