def main():
# loop = tf.while_loop(
# cond = lambda i: i < tf.Variable(100, name='Const100'),
# # cond = lambda i: i < tf.constant(5, name='Const5') + tf.constant(100, name='Const100'),
# body = lambda i: i + tf.constant(1, name='Const1' ),
# loop_vars=[ tf.placeholder(tf.int32, name='INPUT') ],
# parallel_iterations=1
# )
#
# y = tf.identity(loop, 'OUTPUT')
# x = tf.Variable(0, name='Const0')
# y = tf.cond(
# x < tf.constant(1, name='Const1'),
# lambda: tf.identity( tf.constant(2, name='Const2') ),
# lambda: tf.Variable(3, name='Const3')
# )
# INPUT = tf.constant(
# # np.column_stack([
# np.arange(4),
# # np.arange(1000,2000)
# # ]),
# name='INPUT'
# )
# OUTPUT = tf.map_fn(lambda x: x*1337, INPUT, parallel_iterations=1)
# # OUTPUT = tf.map_fn(lambda x: tf.Print(x*1337, [x]), INPUT, parallel_iterations=1)
# OUTPUT = tf.identity(OUTPUT, name='OUTPUT')
# OUTPUT = tf.TensorArray(tf.float64, size=4)
INPUT = tf.constant(np.random.rand(40, 20, 50), name='INPUT')
OUTPUT = tf.identity(INPUT, name='OUTPUT')
# MAP_FN = tf.map_fn( lambda i: tf.multiply(i,i, name='I_TIMES_I'), INPUT, name='MAP_FN' )
# OUTPUT = tf.identity(MAP_FN, name='OUTPUT')
cfg = tf.ConfigProto(device_count={'GPU': 0})
with tf.Session(config=cfg) as sess:
# sess.run( tf.global_variables_initializer() )
# print( sess.run(y, feed_dict = {'INPUT:0': 0}) )
# print( sess.run(OUTPUT) )
dot = tf2dot(OUTPUT, sess=sess)
dot.format = 'pdf'
dot.attr(root='INPUT')
# dot.attr( splines='true')
# dot.attr( rank='same' )
# dot.attr( ranksep='0.01', nodesep='0.01' )
# dot.attr( rankdir='LR' )
# dot.attr(splines='ortho', layout='circo')
tmpdir = mkdtemp()
help(dot.render)
dot.render(directory=tmpdir, view=True)
Created on Dec 1, 2018
@author: Dirk Toewe
'''
import tensorflow as tf
from tf2x import tf2dot
from tempfile import mkdtemp
with tf.Graph().as_default() as graph:
tf_a = tf.constant([1, 2, 3], dtype=tf.float32, name='a')
tf_b = tf.constant([4, 5, 6], dtype=tf.float32, name='b')
tf_c = tf.placeholder(shape=[], dtype=tf.bool, name='c')
tf_d = tf.cond(tf_c, lambda: tf_a, lambda: tf_b, name='d')
tf_e = tf.identity(tf_d, name='e')
with tf.Session() as sess:
dot = tf2dot(graph, sess=sess)
result_e = sess.run(tf_d, feed_dict={tf_c: False})
print('E(false):', result_e)
result_e = sess.run(tf_d, feed_dict={tf_c: True})
print('E(true):', result_e)
tmpdir = mkdtemp()
dot.format = 'png'
dot.attr(root='c:0')
dot.render(directory=tmpdir, view=True)
'''
Created on Dec 1, 2018
@author: Dirk Toewe
'''
import tensorflow as tf
from tf2x import tf2dot
from tempfile import mkdtemp
tf_loop = tf.while_loop(cond=lambda i: i < tf.constant(16, name='iMax'),
body=lambda i: i + 1,
loop_vars=(tf.constant(0, name='i0'), ))
tf_out = tf.identity(tf_loop, name='out')
with tf.Session() as sess:
dot = tf2dot(tf_out, sess=sess)
tmpdir = mkdtemp()
dot.format = 'png'
dot.attr(root='i0')
dot.attr(newrank='true')
dot.render(directory=tmpdir, view=True)
'''
Created on Dec 1, 2018
@author: Dirk Toewe
'''
import tensorflow as tf
from tf2x import tf2dot
from tempfile import mkdtemp
tf_a = tf.constant([1, 2, 3], dtype=tf.float32, name='a')
tf_b = tf.placeholder(dtype=tf.float32, name='b')
tf_c = tf.add(tf_a, tf_b, name='c')
with tf.Session() as sess:
dot = tf2dot(tf_c, sess=sess)
tmpdir = mkdtemp()
dot.format = 'png'
dot.render(directory=tmpdir, view=True)