DCGAN

In [1]:

    

import numpy as np
import tensorflow as tf
from six.moves import cPickle as pickle
import matplotlib.pyplot as plt
import random
import operator
import time
import os
import math
import deepdish as dd
from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
from math import *
import time
from dcgan import DCGAN
from datetime import datetime


    

In [2]:

    

wd = os.getcwd()
os.chdir('..')
file_name = 'resized_depth_data2.h5'

save = dd.io.load(file_name)

train_objects = save['train_objects']
train_orientations = save['train_orientations']
train_values = save['train_values']
valid_objects = save['valid_objects']
valid_orientations = save['valid_orientations']
valid_values = save['valid_values']
test_objects = save['test_objects']
test_orientations = save['test_orientations']
test_values = save['test_values']
value2object = save['value2object']
object2value = save['object2value']
del save

os.chdir(wd)

print('training dataset', train_objects.shape, train_orientations.shape, train_values.shape)
print('validation dataset', valid_objects.shape, valid_orientations.shape, valid_values.shape)
print('testing dataset', test_objects.shape, test_orientations.shape, test_values.shape)


    

    




('training dataset', (427680, 11), (427680, 10), (427680, 48, 48))
('validation dataset', (71226, 11), (71226, 10), (71226, 48, 48))
('testing dataset', (71280, 11), (71280, 10), (71280, 48, 48))

In [3]:

    

image_size = 48

def randomize(dataset, classes, angles):
    permutation = np.random.permutation(classes.shape[0])
    shuffled_dataset = dataset[permutation,:,:]
    shuffled_classes = classes[permutation]
    shuffled_angles = angles[permutation]
    return shuffled_dataset, shuffled_classes, shuffled_angles

train_dataset, train_classes, train_angles = randomize(train_values, train_objects, train_orientations)
valid_dataset, valid_classes, valid_angles = randomize(valid_values, valid_objects, valid_orientations)
test_dataset, test_classes, test_angles = randomize(test_values, test_objects, test_orientations)

train_dataset = train_dataset[:150000,:,:]
train_angles = train_angles[:150000,:]
train_classes = train_classes[:150000,:]

valid_dataset = valid_dataset[:5000,:,:]
valid_angles = valid_angles[:5000,:]
valid_classes = valid_classes[:5000,:]

test_dataset = test_dataset[:5000,:,:]
test_angles = test_angles[:5000,:]
test_classes = test_classes[:5000,:]

train_dataset = train_dataset.reshape(-1,image_size,image_size,1)
test_dataset = test_dataset.reshape(-1,image_size,image_size,1)
n_samples = train_dataset.shape[0]


    

In [4]:

    

FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string('logdir', 'logdir',
                           """Directory where to write event logs and checkpoint.""")
tf.app.flags.DEFINE_integer('max_steps', 80000,
                            """Number of batches to run.""")
tf.app.flags.DEFINE_string('images_dir', 'images',
                           """Directory where to write generated images.""")


    

In [5]:

    

np.random.seed(0)
tf.set_random_seed(0)
s_size = 3 # s_size*2**4 == image_size

dcgan = DCGAN(s_size=s_size)
batch_size = dcgan.batch_size #128
min_queue_examples = 5000

train_images = tf.train.shuffle_batch([train_dataset], \
                                      batch_size=batch_size, \
                                      capacity=min_queue_examples + 3 * batch_size, \
                                      min_after_dequeue=min_queue_examples, \
                                      enqueue_many = True)

test_images = tf.train.shuffle_batch([test_dataset], \
                                     batch_size=batch_size, \
                                     capacity=min_queue_examples + 3 * batch_size, \
                                     min_after_dequeue=min_queue_examples, \
                                     enqueue_many = True)

losses = dcgan.loss(train_images)


    

In [6]:

    

# feature matching
graph = tf.get_default_graph()
features_g = tf.reduce_mean(graph.get_tensor_by_name('dg/d/conv4/outputs:0'), 0)
features_t = tf.reduce_mean(graph.get_tensor_by_name('dt/d/conv4/outputs:0'), 0)
losses[dcgan.g] += tf.multiply(tf.nn.l2_loss(features_g - features_t), 0.05)

tf.summary.scalar('g loss', losses[dcgan.g])
tf.summary.scalar('d loss', losses[dcgan.d])
train_op = dcgan.train(losses, learning_rate=0.0001)
summary_op = tf.summary.merge_all()

g_saver = tf.train.Saver(dcgan.g.variables, max_to_keep=15)
d_saver = tf.train.Saver(dcgan.d.variables, max_to_keep=15)
g_checkpoint_path = os.path.join(FLAGS.logdir, '/g.ckpt')
d_checkpoint_path = os.path.join(FLAGS.logdir, '/d.ckpt')

config = tf.ConfigProto()
config.gpu_options.allow_growth=True
config.log_device_placement = True
config.gpu_options.allocator_type = 'BFC'


    

    




INFO:tensorflow:Summary name g loss is illegal; using g_loss instead.
INFO:tensorflow:Summary name d loss is illegal; using d_loss instead.

In [7]:

    

with tf.Session(config=config) as sess:
    summary_writer = tf.summary.FileWriter(FLAGS.logdir, graph=sess.graph)
    # restore or initialize generator
    sess.run(tf.global_variables_initializer())
    '''
    if os.path.exists(g_checkpoint_path):
        print('restore variables:')
        for v in dcgan.g.variables:
            print('  ' + v.name)
        g_saver.restore(sess, g_checkpoint_path)
    if os.path.exists(d_checkpoint_path):
        print('restore variables:')
        for v in dcgan.d.variables:
            print('  ' + v.name)
        d_saver.restore(sess, d_checkpoint_path)
    '''
        
    try: 
        g_saver.restore(sess, './logdir/g.ckpt')
        print ('restore variables:')
        for v in dcgan.g.variables:
            print('  ' + v.name)
    except:
        print "g using random initialization"
            
    try: 
        d_saver.restore(sess, './logdir/d.ckpt')
        print('restore variables:')
        for v in dcgan.d.variables:
            print('  ' + v.name)
    except:
        print "d using random initialization"
        
    # setup for monitoring
    sample_z = sess.run(tf.random_uniform([dcgan.batch_size, dcgan.z_dim], minval=-1.0, maxval=1.0))
    images = dcgan.sample_images(5, 5, inputs=sample_z)

    # start training
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(sess=sess, coord=coord)
    
    dcgan.retrain
    
    for step in range(FLAGS.max_steps):
        start_time = time.time()
        _, g_loss, d_loss = sess.run([train_op, losses[dcgan.g], losses[dcgan.d]])
        duration = time.time() - start_time
        
        if step%20 == 0:
            print('{}: step {:5d}, loss = (G: {:.8f}, D: {:.8f}) ({:.3f} sec/batch)'.format(
                datetime.now(), step, g_loss, d_loss, duration))

        # save generated images
        if step % 100 == 0:
            # summary
            summary_str = sess.run(summary_op)
            summary_writer.add_summary(summary_str, step)
            # sample images
            filename = os.path.join(FLAGS.images_dir, '%05d.jpg' % step)
            with open(filename, 'wb') as f:
                f.write(sess.run(images))
        # save variables
        if (step+1) == FLAGS.max_steps:
            g_saver.save(sess, './logdir/g.ckpt')
            d_saver.save(sess, './logdir/d.ckpt')
            
    coord.request_stop()
    coord.join(threads)


    

    




g using random initialization
d using random initialization
INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.InternalError'>, Dst tensor is not initialized.
	 [[Node: shuffle_batch/Const = Const[dtype=DT_FLOAT, value=Tensor<type: float shape: [150000,48,48,1] values: [[[-0.0024799407][-0.047286831][-0.062222458]]]...>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

Caused by op u'shuffle_batch/Const', defined at:
  File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/home/zhiang/.local/lib/python2.7/site-packages/traitlets/config/application.py", line 653, in launch_instance
    app.start()
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 162, in start
    super(ZMQIOLoop, self).start()
  File "/home/zhiang/.local/lib/python2.7/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/home/zhiang/.local/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/zhiang/.local/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/zhiang/.local/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-5-26936c89bad2>", line 9, in <module>
    train_images = tf.train.shuffle_batch([train_dataset],                                       batch_size=batch_size,                                       capacity=min_queue_examples + 3 * batch_size,                                       min_after_dequeue=min_queue_examples,                                       enqueue_many = True)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 1165, in shuffle_batch
    name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 716, in _shuffle_batch
    tensor_list = _validate(tensor_list)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 533, in _validate
    tensor_list = ops.convert_n_to_tensor_or_indexed_slices(tensor_list)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 925, in convert_n_to_tensor_or_indexed_slices
    values=values, dtype=dtype, name=name, as_ref=False)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 896, in internal_convert_n_to_tensor_or_indexed_slices
    value, dtype=dtype, name=n, as_ref=as_ref))
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 857, in internal_convert_to_tensor_or_indexed_slices
    as_ref=as_ref)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 702, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 110, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 103, in constant
    attrs={"value": tensor_value, "dtype": dtype_value}, name=name).outputs[0]
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2327, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1226, in __init__
    self._traceback = _extract_stack()

InternalError (see above for traceback): Dst tensor is not initialized.
	 [[Node: shuffle_batch/Const = Const[dtype=DT_FLOAT, value=Tensor<type: float shape: [150000,48,48,1] values: [[[-0.0024799407][-0.047286831][-0.062222458]]]...>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]







    




---------------------------------------------------------------------------
OutOfRangeError                           Traceback (most recent call last)
<ipython-input-7-d20489516151> in <module>()
     44     for step in range(FLAGS.max_steps):
     45         start_time = time.time()
---> 46         _, g_loss, d_loss = sess.run([train_op, losses[dcgan.g], losses[dcgan.d]])
     47         duration = time.time() - start_time
     48 

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
    765     try:
    766       result = self._run(None, fetches, feed_dict, options_ptr,
--> 767                          run_metadata_ptr)
    768       if run_metadata:
    769         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
    963     if final_fetches or final_targets:
    964       results = self._do_run(handle, final_targets, final_fetches,
--> 965                              feed_dict_string, options, run_metadata)
    966     else:
    967       results = []

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1013     if handle is None:
   1014       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1015                            target_list, options, run_metadata)
   1016     else:
   1017       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
   1033         except KeyError:
   1034           pass
-> 1035       raise type(e)(node_def, op, message)
   1036 
   1037   def _extend_graph(self):

OutOfRangeError: RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 128, current size 0)
	 [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]
	 [[Node: shuffle_batch/_163 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_1237_shuffle_batch", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

Caused by op u'shuffle_batch', defined at:
  File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/home/zhiang/.local/lib/python2.7/site-packages/traitlets/config/application.py", line 653, in launch_instance
    app.start()
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 162, in start
    super(ZMQIOLoop, self).start()
  File "/home/zhiang/.local/lib/python2.7/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/home/zhiang/.local/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/zhiang/.local/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/zhiang/.local/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/zhiang/.local/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/zhiang/.local/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/zhiang/.local/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-5-26936c89bad2>", line 9, in <module>
    train_images = tf.train.shuffle_batch([train_dataset],                                       batch_size=batch_size,                                       capacity=min_queue_examples + 3 * batch_size,                                       min_after_dequeue=min_queue_examples,                                       enqueue_many = True)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 1165, in shuffle_batch
    name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 739, in _shuffle_batch
    dequeued = queue.dequeue_many(batch_size, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/data_flow_ops.py", line 458, in dequeue_many
    self._queue_ref, n=n, component_types=self._dtypes, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1310, in _queue_dequeue_many_v2
    timeout_ms=timeout_ms, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2327, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1226, in __init__
    self._traceback = _extract_stack()

OutOfRangeError (see above for traceback): RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 128, current size 0)
	 [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]
	 [[Node: shuffle_batch/_163 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_1237_shuffle_batch", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]