yaroslavvb

cd /Users/yaroslavvb/tfimmediate_hood.cpu_three
git clone https://github.com/yaroslavvb/tensorflow.git

export clonedir=/Users/yaroslavvb/tfimmediate_hood.cpu_three/tensorflow
export dev_branch=hood-devel
export pr_branch=hood

git fetch --all
git checkout $dev_branch
git pull

yaroslavvb

    import tensorflow as tf
    from tensorflow.core.framework import op_def_pb2
    from google.protobuf import text_format
    
    def get_op_types(op):
        for attr in op.attr:
            if attr.type != 'type':
                continue
            return list(attr.allowed_values.list.type)
        return []

yaroslavvb

a = tf.constant([[1,2],[3,4]])
row_to_add = tf.constant([[1, 1]])
updated_row = a[0]+row_to_add
updated_a = tf.concat(0, [updated_row, a[1:]])
sess.run(updated_a)

yaroslavvb

import tensorflow as tf
fn = "/tmp/efs/yaroslav/g/train_1/events.out.tfevents.1476852642.g-w-1-vblgv"
for summary in tf.train.summary_iterator():
  print(summary)

yaroslavvb

import tensorflow as tf
from numpy.testing.utils import nulp_diff
import time

n = 1024
v1 = tf.Variable(tf.ones_initializer((n, n)))
v2 = tf.Variable(tf.ones_initializer((n, n)))
op = v1.assign(tf.matmul(v1, v2)/n).op
norm = tf.reduce_sum(v1)

yaroslavvb

def sessrun(fetches):
  values = tf.get_default_session().run(fetches)
  return {fetches[i]: values[i] for i in range(len(values))}

a = tf.constant(1)
b = tf.constant(2)
c = tf.constant(3)

sess = tf.InteractiveSession()
result1 = sessrun([a, b])

yaroslavvb

import tensorflow as tf
a = tf.ones((10, 10))
b = tf.ones((10, 10))
c = tf.matmul(a, b)
ss = tf.contrib.stat_summarizer.NewStatSummarizer(tf.get_default_graph().as_graph_def().SerializeToString())

sess = tf.Session()
for i in range(10):
  run_metadata = tf.RunMetadata()
  run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)

yaroslavvb

# GPU picking
# http://stackoverflow.com/a/41638727/419116
# Nvidia-smi GPU memory parsing.
# must set
# CUDA_DEVICE_ORDER=PCI_BUS_ID
# see https://github.com/tensorflow/tensorflow/issues/152#issuecomment-273663277

# Tested on nvidia-smi 370.23

def run_command(cmd):

yaroslavvb

def copy_initializer(from_var, to_var):
    from tensorflow.contrib import graph_editor as ge
    assert ge.reroute_a2b_ts(from_var.initial_value, to_var.initial_value), "No copy took place"

yaroslavvb

# Try to copy "a" value to "c" while simultaneously adding vector of 1's to a.
# If the copy is started before the first assign_add, the copied value will be inconsistent.
#
# Running it on macbook my "c" ends up with a mix of values between 1 and 6
#
#
# 16.017478 copy 1 (0) starting
# 17.006894 write 1 (0) starting
# 28.431654 write 1 ending (11.4247 sec)
# 29.436692 write 1 (1) starting