Problem with Exercise of 01_Simple_Linear_Model

[Saqhas]

This is my Codes that i am using:

`def begin(reg = 0):

x = tf.placeholder(tf.float32, [None, img_size_flat])
y_true = tf.placeholder(tf.float32, [None, num_classes]) # This will store the one-hot encoded labels for the image
y_true_cls = tf.placeholder(tf.int64, [None])
weights = tf.Variable(tf.zeros([img_size_flat, num_classes])) # This when multiply with x will give the probability of the image belonging to a particular class.
biases = tf.Variable(tf.zeros([num_classes]))
logits = tf.matmul(x, weights) + biases
y_pred = tf.nn.softmax(logits)
y_pred_cls = tf.argmax(y_pred, axis=1)
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=logits,labels=y_true)
loss = tf.reduce_mean(cross_entropy)
regularizer = tf.nn.l2_loss(weights)
cost = tf.reduce_mean(loss + reg * regularizer)
`

`def optimize(num_iterations,batch_size = 100,lr = 0.5,print_loss = False,reg_lambda = 0,beta = 0):

begin(reg_lambda)
correct_prediction = tf.equal(y_pred_cls, y_true_cls)
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
eff_loss = []
session = tf.Session()
session.run(tf.global_variables_initializer())
optimizer = tf.train.AdamOptimizer(learning_rate=lr).minimize(cost)

for i in range(num_iterations):
    # Get a batch of training examples.
    # x_batch now holds a batch of images and
    # y_true_batch are the true labels for those images.
    x_batch, y_true_batch = data.train.next_batch(batch_size) # 
    
    # Put the batch into a dict with the proper names
    # for placeholder variables in the TensorFlow graph.
    # Note that the placeholder for y_true_cls is not set
    # because it is not used during training.
    feed_dict_train = {x: x_batch,
                       y_true: y_true_batch}

    # Run the optimizer using this batch of training data.
    # TensorFlow assigns the variables in feed_dict_train
    # to the placeholder variables and then runs the optimizer.
    session.run(optimizer,feed_dict = feed_dict_train)
    eff_loss.append(loss)
    if print_loss and num_iterations % 10000 == 0:
        #loss = tf.reduce_mean(cross_entropy)
        print('The Loss is :',loss)
feed_dict_test = {x: data.test.images,
            y_true: data.test.labels,
            y_true_cls: data.test.cls}
# Use TensorFlow to compute the accuracy.
acc = session.run(accuracy, feed_dict=feed_dict_test)

# Print the accuracy.
print("Accuracy on test-set: {0:.1%}".format(acc))
plt.plot(np.arange(num_iterations),eff_loss)
plt.show()
session.close()

`

On running the below in jupyter notebook:
optimize(500,batch_size = 100,lr = 0.8,reg_lambda = 2,beta = 0.9)

I get the below error:

`
FailedPreconditionError Traceback (most recent call last)
~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1326 try:
-> 1327 return fn(*args)
1328 except errors.OpError as e:

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1305 feed_dict, fetch_list, target_list,
-> 1306 status, run_metadata)
1307

~/anaconda3/envs/tensorflow/lib/python3.5/contextlib.py in exit(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:

FailedPreconditionError: Attempting to use uninitialized value beta1_power_7
[[Node: beta1_power_7/read = IdentityT=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"]]

During handling of the above exception, another exception occurred:

FailedPreconditionError Traceback (most recent call last)
in ()
----> 1 optimize(500,batch_size = 100,lr = 0.8,reg_lambda = 2,beta = 0.9)

in optimize(num_iterations, batch_size, lr, print_loss, reg_lambda, beta)
24 # TensorFlow assigns the variables in feed_dict_train
25 # to the placeholder variables and then runs the optimizer.
---> 26 session.run(optimizer,feed_dict = feed_dict_train)
27 eff_loss.append(loss)
28 if print_loss and num_iterations % 10000 == 0:

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
893 try:
894 result = self._run(None, fetches, feed_dict, options_ptr,
--> 895 run_metadata_ptr)
896 if run_metadata:
897 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1122 if final_fetches or final_targets or (handle and feed_dict_tensor):
1123 results = self._do_run(handle, final_targets, final_fetches,
-> 1124 feed_dict_tensor, options, run_metadata)
1125 else:
1126 results = []

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1319 if handle is None:
1320 return self._do_call(_run_fn, self._session, feeds, fetches, targets,
-> 1321 options, run_metadata)
1322 else:
1323 return self._do_call(_prun_fn, self._session, handle, feeds, fetches)

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1338 except KeyError:
1339 pass
-> 1340 raise type(e)(node_def, op, message)
1341
1342 def _extend_graph(self):

FailedPreconditionError: Attempting to use uninitialized value beta1_power_7
[[Node: beta1_power_7/read = IdentityT=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"]]

Caused by op 'beta1_power_7/read', defined at:
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel_launcher.py", line 16, in
app.launch_new_instance()
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 478, in start
self.io_loop.start()
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 281, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 232, in dispatch_shell
handler(stream, idents, msg)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 397, in execute_request
user_expressions, allow_stdin)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2728, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2856, in run_ast_nodes
if self.run_code(code, result):
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2910, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
optimize(500,batch_size = 100,lr = 0.8,reg_lambda = 2,beta = 0.9)
File "", line 8, in optimize
optimizer = tf.train.AdamOptimizer(learning_rate=0.5).minimize(cost)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/training/optimizer.py", line 325, in minimize
name=name)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/training/optimizer.py", line 446, in apply_gradients
self._create_slots([_get_variable_for(v) for v in var_list])
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/training/adam.py", line 126, in _create_slots
trainable=False)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/variable_scope.py", line 1679, in variable
caching_device=caching_device, name=name, dtype=dtype)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 199, in init
expected_shape=expected_shape)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 330, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1400, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/saquib/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1204, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

FailedPreconditionError (see above for traceback): Attempting to use uninitialized value beta1_power_7
[[Node: beta1_power_7/read = IdentityT=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"]]

`

Thank You for the Help

[Hvass-Labs]

This is not the code from my tutorial. This is your own code - perhaps copy-pasted from my tutorial but modified by yourself. It is a bit much to ask me to help you with this. If you look at the view-count of that video it is approaching 100.000 views. Imagine if everybody asked me a question about THEIR code.

If you read the error message you find this: FailedPreconditionError: Attempting to use uninitialized value beta1_power_7 If you do a google search for this, you will probably find that you have made a new variable in the TensorFlow graph which you forgot to initialize.

[Saqhas]

Thank you sir

…

On Dec 28, 2017 2:00 PM, "Hvass-Labs" ***@***.***> wrote: Closed #57 <#57>. — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#57 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AVV-LFajB5r6jkc2hKGdiOwt1e-Nz5I0ks5tE1GTgaJpZM4RM8tY> .