In [1]:

    

%%javascript
var kernel = IPython.notebook.kernel;
var body = document.body,  
    attribs = body.attributes;
var command = "__filename__ = " + "'" + decodeURIComponent(attribs['data-notebook-name'].value) + "'";
kernel.execute(command);


    

    






<IPython.core.display.Javascript object>

In [2]:

    

print(__filename__)


    

    




Training Evaluation.ipynb

In [3]:

    

import os, sys, numpy as np, tensorflow as tf
from pathlib import Path

import time
try:
    print(__file__)
    __current_dir__ = str(Path(__file__).resolve().parents[0])
    __filename__ = os.path.basename(__file__)

except NameError:
    # jupyter notebook automatically sets the working 
    # directory to where the notebook is.
    __current_dir__ = str(Path(os.getcwd()))

module_parent_dir = str(Path(__current_dir__).resolve().parents[0])

sys.path.append(module_parent_dir)
import convnet

__package__ = 'convnet'
from . import network

from tensorflow.examples.tutorials.mnist import input_data

mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

BATCH_SIZE = 250
SCRIPT_DIR = __current_dir__
FILENAME = __filename__
SUMMARIES_DIR = SCRIPT_DIR
SAVE_PATH = SCRIPT_DIR + "/network.ckpt"

### configure devices for this eval script.
USE_DEVICE = '/gpu:0'
session_config = tf.ConfigProto(log_device_placement=True)
session_config.gpu_options.allow_growth = True
# this is required if want to use GPU as device.
# see: https://github.com/tensorflow/tensorflow/issues/2292
session_config.allow_soft_placement = True


    

    




Extracting MNIST_data/train-images-idx3-ubyte.gz
Extracting MNIST_data/train-labels-idx1-ubyte.gz
Extracting MNIST_data/t10k-images-idx3-ubyte.gz
Extracting MNIST_data/t10k-labels-idx1-ubyte.gz
Extracting MNIST_data/train-images-idx3-ubyte.gz
Extracting MNIST_data/train-labels-idx1-ubyte.gz
Extracting MNIST_data/t10k-images-idx3-ubyte.gz
Extracting MNIST_data/t10k-labels-idx1-ubyte.gz

In [4]:

    

if __name__ == "__main__":
    with tf.Graph().as_default() as g, tf.device(USE_DEVICE):
        # inference()
        input, logits = network.inference()
        labels, loss_op = network.loss(logits)
        train = network.training(loss_op, 1e-1)
        eval = network.evaluation(logits, labels)

        init = tf.initialize_all_variables()

        with tf.Session(config=session_config) as sess:
            # Merge all the summaries and write them out to /tmp/mnist_logs (by default)
            # to see the tensor graph, fire up the tensorboard with --logdir="./train"
            merged = tf.merge_all_summaries()
            train_writer = tf.train.SummaryWriter(SUMMARIES_DIR + '/summaries/train', sess.graph)
            test_writer = tf.train.SummaryWriter(SUMMARIES_DIR + '/summaries/test')

            saver = tf.train.Saver()

            sess.run(init)
            saver.restore(sess, SAVE_PATH)

            # now let's test!
            TEST_BATCH_SIZE = np.shape(mnist.test.labels)[0]

            output, loss_value, accuracy = sess.run([logits, loss_op, eval], feed_dict={
                input: mnist.test.images,
                labels: mnist.test.labels
            })
            print("- MNIST Test accuracy is ", accuracy / TEST_BATCH_SIZE)


    

    





InternalErrorTraceback (most recent call last)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
    714     try:
--> 715       return fn(*args)
    716     except errors.OpError as e:

/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
    696                                  feed_dict, fetch_list, target_list,
--> 697                                  status, run_metadata)
    698 

/usr/lib/python3.4/contextlib.py in __exit__(self, type, value, traceback)
     65             try:
---> 66                 next(self.gen)
     67             except StopIteration:

/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/errors.py in raise_exception_on_not_ok_status()
    449           compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 450           pywrap_tensorflow.TF_GetCode(status))
    451   finally:

InternalError: Blas SGEMM launch failed : a.shape=(10000, 3136), b.shape=(3136, 1024), m=10000, n=1024, k=3136
	 [[Node: MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](Reshape_1, Variable_4/read)]]

During handling of the above exception, another exception occurred:

InternalErrorTraceback (most recent call last)
<ipython-input-4-f46b3c2c3452> in <module>()
     26             output, loss_value, accuracy = sess.run([logits, loss_op, eval], feed_dict={
     27                 input: mnist.test.images,
---> 28                 labels: mnist.test.labels
     29             })
     30             print("- MNIST Test accuracy is ", accuracy / TEST_BATCH_SIZE)

/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    370     try:
    371       result = self._run(None, fetches, feed_dict, options_ptr,
--> 372                          run_metadata_ptr)
    373       if run_metadata:
    374         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
    634     try:
    635       results = self._do_run(handle, target_list, unique_fetches,
--> 636                              feed_dict_string, options, run_metadata)
    637     finally:
    638       # The movers are no longer used. Delete them.

/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
    706     if handle is None:
    707       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
--> 708                            target_list, options, run_metadata)
    709     else:
    710       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
    726         except KeyError:
    727           pass
--> 728       raise type(e)(node_def, op, message)
    729 
    730   def _extend_graph(self):

InternalError: Blas SGEMM launch failed : a.shape=(10000, 3136), b.shape=(3136, 1024), m=10000, n=1024, k=3136
	 [[Node: MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](Reshape_1, Variable_4/read)]]
Caused by op 'MatMul', defined at:
  File "/usr/lib/python3.4/runpy.py", line 170, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.4/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/usr/local/lib/python3.4/dist-packages/traitlets/config/application.py", line 596, in launch_instance
    app.start()
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/ioloop.py", line 162, in start
    super(ZMQIOLoop, self).start()
  File "/usr/lib/python3/dist-packages/tornado/ioloop.py", line 866, in start
    handler_func(fd_obj, events)
  File "/usr/lib/python3/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/usr/lib/python3/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/usr/local/lib/python3.4/dist-packages/ipykernel/zmqshell.py", line 498, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/usr/local/lib/python3.4/dist-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/usr/local/lib/python3.4/dist-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-4-f46b3c2c3452>", line 4, in <module>
    input, logits = network.inference()
  File "/home/ubuntu/pynb/deep_learning_notes/Proj - Adversarial Hardening of LeNet/convnet/network.py", line 48, in inference
    h_fc1 = tf.nn.relu(tf.matmul(stage_3_pool_flat, W_fc1) + b_fc1)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/math_ops.py", line 1209, in matmul
    name=name)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 1178, in _mat_mul
    transpose_b=transpose_b, name=name)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/op_def_library.py", line 704, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 2260, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 1230, in __init__
    self._traceback = _extract_stack()

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