Tensorflow : FailedPreconditionError: Attempting to use uninitialized value conv2d_transpose/bias - python

I am trying to build a model that uses transposed convolution operation ,But when I try to pass the weights and bias as a parameter to the model function it gives an error.
import tensorflow as tf
import cv2
class WeighsTest:
def __model_1(self, plh_var1,weights,bias):
conv = tf.nn.conv2d(plh_var1, weights["v1"], [1, 1, 1, 1], padding="SAME")
conv = tf.add(conv, bias["b1"])
conv = tf.nn.relu(conv)
tran_conv = tf.layers.conv2d_transpose(conv,32, 4, 3, padding="valid")
return tran_conv
def train(self, input_img):
plh = tf.placeholder(dtype=tf.float32, shape=(None, 84, 150, 3), name="input_img")
with tf.variable_scope("test", reuse=tf.AUTO_REUSE):
var_dict_1 = {
"v1": tf.get_variable("v1", shape=(2, 2, 3, 32), initializer=tf.contrib.layers.xavier_initializer())
}
bias_1 = {
"b1": tf.get_variable("b1", shape=32, initializer=tf.contrib.layers.xavier_initializer())
}
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
out_p = sess.run([self.__model_1(plh, var_dict_1, bias_1)], feed_dict={plh: [input_img]})
return out_p
if __name__ == '__main__':
obj = WeighsTest()
img = cv2.imread('./1.jpg')
output = obj.train(img)
traceback is given below
Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
return fn(*args)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
target_list, run_metadata)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value conv2d_transpose/bias
[[{{node conv2d_transpose/bias/read}}]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/strange/DEV/Python_Projects/slmv/testing_unit.py", line 43, in <module>
output = obj.train(img)
File "/home/strange/DEV/Python_Projects/slmv/testing_unit.py", line 36, in train
out_p = sess.run([self.__model_1(x1, var_dict_1, bias_1)], feed_dict={x1: [input_img]})
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 956, in run
run_metadata_ptr)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 1180, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
run_metadata)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value conv2d_transpose/bias
[[node conv2d_transpose/bias/read (defined at usr/local/lib/python3.7/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]
Original stack trace for 'conv2d_transpose/bias/read':
File "home/strange/DEV/Python_Projects/slmv/testing_unit.py", line 43, in <module>
output = obj.train(img)
File "home/strange/DEV/Python_Projects/slmv/testing_unit.py", line 36, in train
out_p = sess.run([self.__model_1(x1, var_dict_1, bias_1)], feed_dict={x1: [input_img]})
File "home/strange/DEV/Python_Projects/slmv/testing_unit.py", line 10, in __model_1
tran_conv = tf.layers.conv2d_transpose(conv,32, 4, 3, padding="valid")
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/layers/convolutional.py", line 1279, in conv2d_transpose
return layer.apply(inputs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/keras/engine/base_layer.py", line 1700, in apply
return self.__call__(inputs, *args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/layers/base.py", line 548, in __call__
outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/keras/engine/base_layer.py", line 824, in __call__
self._maybe_build(inputs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/keras/engine/base_layer.py", line 2146, in _maybe_build
self.build(input_shapes)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/keras/layers/convolutional.py", line 787, in build
dtype=self.dtype)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/layers/base.py", line 461, in add_weight
**kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/keras/engine/base_layer.py", line 529, in add_weight
aggregation=aggregation)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/training/tracking/base.py", line 712, in _add_variable_with_custom_getter
**kwargs_for_getter)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variable_scope.py", line 1500, in get_variable
aggregation=aggregation)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variable_scope.py", line 1243, in get_variable
aggregation=aggregation)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variable_scope.py", line 567, in get_variable
aggregation=aggregation)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variable_scope.py", line 519, in _true_getter
aggregation=aggregation)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variable_scope.py", line 933, in _get_single_variable
aggregation=aggregation)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variables.py", line 258, in __call__
return cls._variable_v1_call(*args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variables.py", line 219, in _variable_v1_call
shape=shape)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variables.py", line 197, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variable_scope.py", line 2519, in default_variable_creator
shape=shape)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variables.py", line 262, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variables.py", line 1688, in __init__
shape=shape)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/variables.py", line 1872, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/util/dispatch.py", line 180, in wrapper
return target(*args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/array_ops.py", line 203, in identity
ret = gen_array_ops.identity(input, name=name)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/gen_array_ops.py", line 4239, in identity
"Identity", input=input, name=name)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
op_def=op_def)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
attrs, op_def, compute_device)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
op_def=op_def)
File "usr/local/lib/python3.7/dist-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
self._traceback = tf_stack.extract_stack()
It is important to pass the bias and weights as parameters to the model.
I used tensorflow-cpu 1.15.2 for the model.
Any idea how to solve this ?
Thank you

The model needed to be called before the tf.global_variabels_initializer() is used
ie. the train function is changed as below
def train(self, input_img):
plh = tf.placeholder(dtype=tf.float32, shape=(None, 84, 150, 3), name="input_img")
with tf.variable_scope("test", reuse=tf.AUTO_REUSE):
var_dict_1 = {
"v1": tf.get_variable("v1", shape=(2, 2, 3, 32), initializer=tf.contrib.layers.xavier_initializer())
}
bias_1 = {
"b1": tf.get_variable("b1", shape=32, initializer=tf.contrib.layers.xavier_initializer())
}
"""model is called before variable initialization"""
model = self.__model_1(plh, var_dict_1, bias_1)
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
out_p = sess.run([model], feed_dict={plh: [input_img]})
return out_p
the line given below:
out_p = sess.run([self.__model_1(plh, var_dict_1, bias_1)], feed_dict={plh: [input_img]})
is changed into
out_p = sess.run([model], feed_dict={plh: [input_img]})

Related

FailedPreconditionError when running output layer in session?

In tensorflow, I am experiencing an issue where I try to get the output of my last neuron by running it in a session but it gives me an error. I am running Python 3.8.5 and TensorFlow 1.15 (because of some hardware issues)
Here is my code:
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import tensorflow as tf
def main():
x_inputs = tf.Variable(np.array([[1, 2 ,3], [1, 2, 3]]), dtype=tf.float32)
y_outputs = tf.Variable(np.array([[1, 2, 4], [2, 3, 4]]), dtype=tf.float32)
model = create_model(x_inputs, y_outputs)
def create_model(x: np.array, y: np.array):
var_init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(var_init)
x_val = sess.run(x).flatten()
y_val = sess.run(y).flatten()
# neural network architecture
input_layer = tf.layers.dense(x, units=len(x_val), activation=tf.nn.sigmoid)
hidden_layer = tf.layers.dense(input_layer, units=5, activation=tf.nn.relu)
output_layer = tf.layers.dense(hidden_layer, units=2, activation=tf.nn.softmax)
print(sess.run(output_layer))
if __name__ == "__main__":
main()
Here's the error:
Traceback (most recent call last):
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1350, in _do_call
return fn(*args)
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1327, in _run_fn
return tf_session.TF_Run(session, options,
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/errors_impl.py", line 470, in __exit__
raise _make_specific_exception(
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value dense_2/bias
[[Node: dense_2/bias/read = Identity[T=DT_FLOAT, _class=["loc:#dense_2/bias"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](dense_2/bias)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "learning.py", line 29, in <module>
main()
File "learning.py", line 10, in main
model = create_model(x_inputs, y_outputs)
File "learning.py", line 26, in create_model
print(sess.run(output_layer))
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 894, in run
result = self._run(None, fetches, feed_dict, options_ptr,
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1127, in _run
results = self._do_run(handle, final_targets, final_fetches,
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1343, in _do_run
return self._do_call(_run_fn, self._session, feeds, fetches, targets,
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1363, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value dense_2/bias
[[Node: dense_2/bias/read = Identity[T=DT_FLOAT, _class=["loc:#dense_2/bias"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](dense_2/bias)]]
Caused by op 'dense_2/bias/read', defined at:
File "learning.py", line 29, in <module>
main()
File "learning.py", line 10, in main
model = create_model(x_inputs, y_outputs)
File "learning.py", line 24, in create_model
output_layer = tf.layers.dense(hidden_layer, units=2, activation=tf.nn.softmax)
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/layers/core.py", line 253, in dense
return layer.apply(inputs)
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/layers/base.py", line 762, in apply
return self.__call__(inputs, *args, **kwargs)
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/layers/base.py", line 636, in __call__
self.build(input_shapes)
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/layers/core.py", line 139, in build
self.bias = self.add_variable('bias',
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/layers/base.py", line 498, in add_variable
variable = vs.get_variable(name,
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variable_scope.py", line 1256, in get_variable
return get_variable_scope().get_variable(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variable_scope.py", line 1091, in get_variable
return var_store.get_variable(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variable_scope.py", line 429, in get_variable
return _true_getter(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variable_scope.py", line 399, in _true_getter
return self._get_single_variable(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variable_scope.py", line 798, in _get_single_variable
v = variables.Variable(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variables.py", line 220, in __init__
self._init_from_args(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/variables.py", line 376, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py", line 127, in identity
return gen_array_ops.identity(input, name=name)
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2133, in identity
_, _, _op = _op_def_lib._apply_op_helper(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/op_def_library.py", line 785, in _apply_op_helper
op = g.create_op(op_type_name, inputs, output_types, name=scope,
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 3152, in create_op
ret = Operation(
File "/Applications/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 1625, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value dense_2/bias
[[Node: dense_2/bias/read = Identity[T=DT_FLOAT, _class=["loc:#dense_2/bias"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](dense_2/bias)]]
Please help me I'm really struggling.
Thanks in advance!

How to access/manipulate elements of tensor in keras model?

I want to test a new network structure which requires changing some of the elements of a tensor in a keras model. If I could find a way to convert/copy the tensor to a numpy array and then later transform it back into a tensor, then I should be able to make the model work.
I tried using the .eval() method to convert the tensor to a numpy array, but it gives me errors. I am also using this model with a DQN Agent from keras-rl, so it is possible the error is from how keras-rl uses the model. Here is my code:
def Filter_Features(F):
sess = Session()
with sess.as_default():
F_np = F.eval()
min_pos = np.argmin(F_np)
F_np[min_pos] = 0
return convert_to_tensor(F_np)
def create_model(nb_actions, num_frames=4):
inputs = Input(shape = (num_frames,84,84))
F = Conv2D(16,(8,8), activation='relu', strides=(4,4), data_format = "channels_first")(inputs)
...
F_k = Lambda(Filter_Features)(F)
actions = Dense(nb_actions, activation = 'linear')(F_k)
nnf_model = Model(inputs = inputs, outputs = actions)
return nnf_model
Note that the code runs if I remove the lambda layer, so the issue must be originating there. I received the error:
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1356, in _do_call
return fn(*args)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1341, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1429, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value conv2d_1/bias
[[{{node conv2d_1/bias/read}}]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "Atari_Test.py", line 32, in <module>
model = Model_StackExchange.create_model(nb_actions = nb_actions)
File "/Users/j/deep-rl/Model_StackExchange.py", line 26, in create_model
F_k = Lambda(Filter_Features)(F)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/base_layer.py", line 457, in __call__
output = self.call(inputs, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/layers/core.py", line 687, in call
return self.function(inputs, **arguments)
File "/Users/j/deep-rl/Model_StackExchange.py", line 11, in Filter_Features
F_np = F.eval()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 731, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 5579, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 950, in run
run_metadata_ptr)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1350, in _do_run
run_metadata)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1370, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value conv2d_1/bias
[[node conv2d_1/bias/read (defined at /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:402) ]]
Original stack trace for 'conv2d_1/bias/read':
File "Atari_Test.py", line 32, in <module>
model = Model_StackExchange.create_model(nb_actions = nb_actions)
File "/Users/j/deep-rl/Model_StackExchange.py", line 21, in create_model
F = Conv2D(16,(8,8), activation='relu', strides=(4,4), data_format = "channels_first")(inputs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/base_layer.py", line 431, in __call__
self.build(unpack_singleton(input_shapes))
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/layers/convolutional.py", line 147, in build
constraint=self.bias_constraint)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/engine/base_layer.py", line 252, in add_weight
constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py", line 402, in variable
v = tf.Variable(value, dtype=tf.as_dtype(dtype), name=name)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variables.py", line 259, in __call__
return cls._variable_v1_call(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variables.py", line 220, in _variable_v1_call
shape=shape)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variables.py", line 198, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variable_scope.py", line 2511, in default_variable_creator
shape=shape)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variables.py", line 263, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variables.py", line 1568, in __init__
shape=shape)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/variables.py", line 1755, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py", line 180, in wrapper
return target(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py", line 86, in identity
ret = gen_array_ops.identity(input, name=name)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 4253, in identity
"Identity", input=input, name=name)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 3616, in create_op
op_def=op_def)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 2005, in __init__
self._traceback = tf_stack.extract_stack()
Please let me know if you know how to access and change the elements of a tensor within a keras model. Thank you.

Tensorflow: Graph is finalized and cannot be modified

I am trying to build a custom object detection model using the Tensorflow Object Detection API. Specifically, I want to add a distance estimation to each detected object. So, I extended the SSDMetaArch class and adapted/added some crucial parts. Among other things:
added distance to the input
adapted protos to handle distance
created a new prediction head for distance estimations
created new loss taking distances into account
adapted postprocessing step to output distances
After all these steps the training seems to work and the losses (including the distance loss) go down.
But when I want to evaluate the model I get a
RuntimeError: Graph is finalized and cannot be modified.
Specifically the following line in the (adapted) visualize_boxes_and_labels_on_image_array() method in visualization_utils.py (around line 700) causes the error
#the follwing line throws the error
display_str = '{}: {}% -> {}'.format(display_str, int(100 * scores[i]), int(distances[i]))
#No error is thrown using the original code
#display_str = '{}: {}%'.format(display_str, int(100 * scores[i]))
It seems that just by printing the value the above exception is thrown.
My Question: I do not understand why printing a value will modify the graph. Could you help me understand why this is the case and if possible give me hint how I can avoid this modification to the graph.
Find the complete error below
INFO:tensorflow:Restoring parameters from E:/Data/OD_DE/tensorflow/models/model\model.ckpt-5103
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
2019-04-01 13:14:30.795741: W tensorflow/core/framework/op_kernel.cc:1261]
Unknown: RuntimeError: Graph is finalized and cannot be modified.
Traceback (most recent call last):
File "..\lib\site-packages\tensorflow\python\ops\script_ops.py", line 206, in __call__
ret = func(*args)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 271, in _visualize_boxes
image, boxes, classes, scores, category_index=category_index, **kwargs)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 730, in visualize_boxes_and_labels_on_image_array
print("We were definitely here:" + str(int(distances[i])))
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 525, in _slice_helper
name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 6037, in __exit__
self._name_scope.__exit__(type_arg, value_arg, traceback_arg)
File "C:\Users\JD\AppData\Local\Continuum\Anaconda3\Lib\contextlib.py", line 77, in __exit__
self.gen.throw(type, value, traceback)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 4016, in name_scope
yield "" if new_stack is None else new_stack + "/"
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 500, in _slice_helper
packed_begin, packed_end, packed_strides = (stack(begin), stack(end),
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 863, in stack
return ops.convert_to_tensor(values, name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1050, in convert_to_tensor
as_ref=False)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1146, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 229, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
name=name).outputs[0]
File "..\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 3246, in create_op
self._check_not_finalized()
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 2919, in _check_not_finalized
raise RuntimeError("Graph is finalized and cannot be modified.")
RuntimeError: Graph is finalized and cannot be modified.
Traceback (most recent call last):
File "..\lib\site-packages\tensorflow\python\client\session.py", line 1334, in _do_call
return fn(*args)
File "..\lib\site-packages\tensorflow\python\client\session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "..\lib\site-packages\tensorflow\python\client\session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.UnknownError: RuntimeError: Graph is finalized and cannot be modified.
Traceback (most recent call last):
File "..\lib\site-packages\tensorflow\python\ops\script_ops.py", line 206, in __call__
ret = func(*args)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 271, in _visualize_boxes
image, boxes, classes, scores, category_index=category_index, **kwargs)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 730, in visualize_boxes_and_labels_on_image_array
print("We were definitely here:" + str(int(distances[i])))
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 525, in _slice_helper
name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 6037, in __exit__
self._name_scope.__exit__(type_arg, value_arg, traceback_arg)
File "C:\Users\JD\AppData\Local\Continuum\Anaconda3\Lib\contextlib.py", line 77, in __exit__
self.gen.throw(type, value, traceback)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 4016, in name_scope
yield "" if new_stack is None else new_stack + "/"
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 500, in _slice_helper
packed_begin, packed_end, packed_strides = (stack(begin), stack(end),
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 863, in stack
return ops.convert_to_tensor(values, name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1050, in convert_to_tensor
as_ref=False)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1146, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 229, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
name=name).outputs[0]
File "..\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 3246, in create_op
self._check_not_finalized()
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 2919, in _check_not_finalized
raise RuntimeError("Graph is finalized and cannot be modified.")
RuntimeError: Graph is finalized and cannot be modified.
[[{{node map_1/while/PyFunc}} = PyFunc[Tin=[DT_UINT8, DT_FLOAT, DT_INT64, DT_FLOAT], Tout=[DT_UINT8], _class=["loc:#map_1/while/TensorArrayWrite/TensorArrayWriteV3"], token="pyfunc_1", _device="/job:localhost/replica:0/task:0/device:CPU:0"](map_1/while/Squeeze/_2907, map_1/while/TensorArrayReadV3_3/_2909, map_1/while/TensorArrayReadV3_4/_2911, map_1/while/TensorArrayReadV3_5/_2913)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm Community Edition 2017.2\helpers\pydev\pydevd.py", line 1596, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "C:\Program Files\JetBrains\PyCharm Community Edition 2017.2\helpers\pydev\pydevd.py", line 1023, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "C:\Program Files\JetBrains\PyCharm Community Edition 2017.2\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/JD/tensorflowod/Lib/site-packages/tensorflow/models/research/object_detection/model_main.py", line 110, in <module>
tf.app.run()
File "..\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "C:/Users/JD/tensorflowod/Lib/site-packages/tensorflow/models/research/object_detection/model_main.py", line 105, in main
tf.estimator.train_and_evaluate(estimator, train_spec, eval_specs[0])
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 471, in train_and_evaluate
return executor.run()
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 610, in run
return self.run_local()
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 711, in run_local
saving_listeners=saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 354, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1207, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1241, in _train_model_default
saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1471, in _train_with_estimator_spec
_, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 671, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1156, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1255, in run
raise six.reraise(*original_exc_info)
File "c:\users\JD\appdata\local\continuum\anaconda3\lib\site-packages\six.py", line 686, in reraise
raise value
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1240, in run
return self._sess.run(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1320, in run
run_metadata=run_metadata))
File "..\lib\site-packages\tensorflow\python\training\basic_session_run_hooks.py", line 582, in after_run
if self._save(run_context.session, global_step):
File "..\lib\site-packages\tensorflow\python\training\basic_session_run_hooks.py", line 607, in _save
if l.after_save(session, step):
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 517, in after_save
self._evaluate(global_step_value) # updates self.eval_result
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 537, in _evaluate
self._evaluator.evaluate_and_export())
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 912, in evaluate_and_export
hooks=self._eval_spec.hooks)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 478, in evaluate
return _evaluate()
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 467, in _evaluate
output_dir=self.eval_dir(name))
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1591, in _evaluate_run
config=self._session_config)
File "..\lib\site-packages\tensorflow\python\training\evaluation.py", line 274, in _evaluate_once
session.run(eval_ops, feed_dict)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 671, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1156, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1255, in run
raise six.reraise(*original_exc_info)
File "c:\users\JD\appdata\local\continuum\anaconda3\lib\site-packages\six.py", line 686, in reraise
raise value
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1240, in run
return self._sess.run(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1312, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1076, in run
return self._sess.run(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\client\session.py", line 929, in run
run_metadata_ptr)
File "..\lib\site-packages\tensorflow\python\client\session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "..\lib\site-packages\tensorflow\python\client\session.py", line 1328, in _do_run
run_metadata)
File "..\lib\site-packages\tensorflow\python\client\session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnknownError: RuntimeError: Graph is finalized and cannot be modified.
Traceback (most recent call last):
File "..\lib\site-packages\tensorflow\python\ops\script_ops.py", line 206, in __call__
ret = func(*args)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 271, in _visualize_boxes
image, boxes, classes, scores, category_index=category_index, **kwargs)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 730, in visualize_boxes_and_labels_on_image_array
print("We were definitely here:" + str(int(distances[i])))
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 525, in _slice_helper
name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 6037, in __exit__
self._name_scope.__exit__(type_arg, value_arg, traceback_arg)
File "C:\Users\JD\AppData\Local\Continuum\Anaconda3\Lib\contextlib.py", line 77, in __exit__
self.gen.throw(type, value, traceback)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 4016, in name_scope
yield "" if new_stack is None else new_stack + "/"
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 500, in _slice_helper
packed_begin, packed_end, packed_strides = (stack(begin), stack(end),
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 863, in stack
return ops.convert_to_tensor(values, name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1050, in convert_to_tensor
as_ref=False)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1146, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 229, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
name=name).outputs[0]
File "..\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 3246, in create_op
self._check_not_finalized()
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 2919, in _check_not_finalized
raise RuntimeError("Graph is finalized and cannot be modified.")
RuntimeError: Graph is finalized and cannot be modified.
[[node map_1/while/PyFunc (defined at ..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py:439) = PyFunc[Tin=[DT_UINT8, DT_FLOAT, DT_INT64, DT_FLOAT], Tout=[DT_UINT8], _class=["loc:#map_1/while/TensorArrayWrite/TensorArrayWriteV3"], token="pyfunc_1", _device="/job:localhost/replica:0/task:0/device:CPU:0"](map_1/while/Squeeze/_2907, map_1/while/TensorArrayReadV3_3/_2909, map_1/while/TensorArrayReadV3_4/_2911, map_1/while/TensorArrayReadV3_5/_2913)]]
Caused by op 'map_1/while/PyFunc', defined at:
File "C:\Program Files\JetBrains\PyCharm Community Edition 2017.2\helpers\pydev\pydevd.py", line 1596, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "C:\Program Files\JetBrains\PyCharm Community Edition 2017.2\helpers\pydev\pydevd.py", line 1023, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "C:\Program Files\JetBrains\PyCharm Community Edition 2017.2\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/JD/tensorflowod/Lib/site-packages/tensorflow/models/research/object_detection/model_main.py", line 110, in <module>
tf.app.run()
File "..\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "C:/Users/JD/tensorflowod/Lib/site-packages/tensorflow/models/research/object_detection/model_main.py", line 105, in main
tf.estimator.train_and_evaluate(estimator, train_spec, eval_specs[0])
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 471, in train_and_evaluate
return executor.run()
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 610, in run
return self.run_local()
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 711, in run_local
saving_listeners=saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 354, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1207, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1241, in _train_model_default
saving_listeners)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1471, in _train_with_estimator_spec
_, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 671, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1156, in run
run_metadata=run_metadata)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1240, in run
return self._sess.run(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1320, in run
run_metadata=run_metadata))
File "..\lib\site-packages\tensorflow\python\training\basic_session_run_hooks.py", line 582, in after_run
if self._save(run_context.session, global_step):
File "..\lib\site-packages\tensorflow\python\training\basic_session_run_hooks.py", line 607, in _save
if l.after_save(session, step):
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 517, in after_save
self._evaluate(global_step_value) # updates self.eval_result
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 537, in _evaluate
self._evaluator.evaluate_and_export())
File "..\lib\site-packages\tensorflow\python\estimator\training.py", line 912, in evaluate_and_export
hooks=self._eval_spec.hooks)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 478, in evaluate
return _evaluate()
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 460, in _evaluate
self._evaluate_build_graph(input_fn, hooks, checkpoint_path))
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1484, in _evaluate_build_graph
self._call_model_fn_eval(input_fn, self.config))
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1520, in _call_model_fn_eval
features, labels, model_fn_lib.ModeKeys.EVAL, config)
File "..\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1195, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\model_lib.py", line 443, in model_fn
eval_dict)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 931, in get_estimator_eval_metric_ops
images = self.images_from_evaluation_dict(eval_dict)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 995, in images_from_evaluation_dict
self._min_score_thresh, self._use_normalized_coordinates)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 547, in draw_side_by_side_evaluation_image
eval_dict[input_data_fields.groundtruth_distances][indx], axis=0) if input_data_fields.groundtruth_distances in eval_dict else None
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 442, in draw_bounding_boxes_on_image_tensors
images = tf.map_fn(draw_boxes, elems, dtype=tf.uint8, back_prop=False)
File "..\lib\site-packages\tensorflow\python\ops\functional_ops.py", line 494, in map_fn
maximum_iterations=n)
File "..\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3291, in while_loop
return_same_structure)
File "..\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3004, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "..\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 2939, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "..\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3260, in <lambda>
body = lambda i, lv: (i + 1, orig_body(*lv))
File "..\lib\site-packages\tensorflow\python\ops\functional_ops.py", line 483, in compute
packed_fn_values = fn(packed_values)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 439, in draw_boxes
tf.uint8)
File "..\lib\site-packages\tensorflow\python\ops\script_ops.py", line 457, in py_func
func=func, inp=inp, Tout=Tout, stateful=stateful, eager=False, name=name)
File "..\lib\site-packages\tensorflow\python\ops\script_ops.py", line 281, in _internal_py_func
input=inp, token=token, Tout=Tout, name=name)
File "..\lib\site-packages\tensorflow\python\ops\gen_script_ops.py", line 132, in py_func
"PyFunc", input=input, token=token, Tout=Tout, name=name)
File "..\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "..\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 3274, in create_op
op_def=op_def)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
UnknownError (see above for traceback): RuntimeError: Graph is finalized and cannot be modified.
Traceback (most recent call last):
File "..\lib\site-packages\tensorflow\python\ops\script_ops.py", line 206, in __call__
ret = func(*args)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 271, in _visualize_boxes
image, boxes, classes, scores, category_index=category_index, **kwargs)
File "..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py", line 730, in visualize_boxes_and_labels_on_image_array
print("We were definitely here:" + str(int(distances[i])))
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 525, in _slice_helper
name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 6037, in __exit__
self._name_scope.__exit__(type_arg, value_arg, traceback_arg)
File "C:\Users\JD\AppData\Local\Continuum\Anaconda3\Lib\contextlib.py", line 77, in __exit__
self.gen.throw(type, value, traceback)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 4016, in name_scope
yield "" if new_stack is None else new_stack + "/"
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 500, in _slice_helper
packed_begin, packed_end, packed_strides = (stack(begin), stack(end),
File "..\lib\site-packages\tensorflow\python\ops\array_ops.py", line 863, in stack
return ops.convert_to_tensor(values, name=name)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1050, in convert_to_tensor
as_ref=False)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 1146, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 229, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "..\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
name=name).outputs[0]
File "..\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 3246, in create_op
self._check_not_finalized()
File "..\lib\site-packages\tensorflow\python\framework\ops.py", line 2919, in _check_not_finalized
raise RuntimeError("Graph is finalized and cannot be modified.")
RuntimeError: Graph is finalized and cannot be modified.
[[node map_1/while/PyFunc (defined at ..\Lib\site-packages\tensorflow\models\research\object_detection\utils\visualization_utils.py:439) = PyFunc[Tin=[DT_UINT8, DT_FLOAT, DT_INT64, DT_FLOAT], Tout=[DT_UINT8], _class=["loc:#map_1/while/TensorArrayWrite/TensorArrayWriteV3"], token="pyfunc_1", _device="/job:localhost/replica:0/task:0/device:CPU:0"](map_1/while/Squeeze/_2907, map_1/while/TensorArrayReadV3_3/_2909, map_1/while/TensorArrayReadV3_4/_2911, map_1/while/TensorArrayReadV3_5/_2913)]]
It appears that in your case distances is a tensor and calling distances[0] attempts to create an array_slice operation on a finalized graph. The right way of handling that would be to feed distances tensor to your distances_np = session.run(distances) or call distances_np = distances.eval() providing necessary parameters to acquire some sort of numpy array and only then do indexing and/or printing on distances_np.

input and filter must have the same depth: 32 vs 16 when using MKL and channels first format

I compiled tensorflow from source with MKL in order to accelerate my DNN learning progress. And I have a ResNet model which is copy from tensorflow/models. The dataset is CIFAR-10. When I run the model with channels last format, everything goes ok. But in order to use MKL which is said only accelerate only for channels first format, I add some code to transpose the data into NCHW format, and run it. Then I get:
Caused by op 'stage/residual_v1/conv2d/Conv2D', defined at:
File "main.py", line 182, in <module>
main(args)
File "main.py", line 83, in main
tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)
File "/home/holmescn/.pyenv/versions/anaconda35.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/training.py", line 447, in train_and_evaluate
return executor.run()
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/training.py", line 531, in run
return self.run_local()
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/training.py", line 669, in run_local
hooks=train_hooks)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 366, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1119, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1132, in _train_model_default
features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1107, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "/home/holmescn/Work/deep-learning-practice/tensorflow/estimator/utils.py", line 18, in _model_fn
logits = build_model(input_layer, mode == tf.estimator.ModeKeys.TRAIN, params=params, args=args)
File "/home/holmescn/Work/deep-learning-practice/tensorflow/estimator/estimators/resnet.py", line 175, in build_model
return resnet.build_model(input_layer, args.num_layers)
File "/home/holmescn/Work/deep-learning-practice/tensorflow/estimator/estimators/resnet.py", line 56, in build_model
x = res_func(x, 3, filters[i], filters[i + 1], strides[i])
File "/home/holmescn/Work/deep-learning-practice/tensorflow/estimator/estimators/resnet.py", line 79, in _residual_v1
x = self._conv(x, kernel_size, out_filter, stride)
File "/home/holmescn/Work/deep-learning-practice/tensorflow/estimator/estimators/base.py", line 59, in _conv
name=name)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/layers/convolutional.py", line 427, in conv2d
return layer.apply(inputs)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 759, in apply
return self.__call__(inputs, *args, **kwargs)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 329, in __call__
outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 688, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/keras/layers/convolutional.py", line 184, in call
outputs = self._convolution_op(inputs, self.kernel)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 868, in __call__
return self.conv_op(inp, filter)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 520, in __call__
return self.call(inp, filter)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 204, in __call__
name=self.name)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 956, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3414, in create_op
op_def=op_def)
File "/home/holmescn/.pyenv/versions/anaconda3-5.2.0/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1740, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): input and filter must have the same depth: 32 vs 16
[[Node: stage/residual_v1/conv2d/Conv2D = _MklConv2D[T=DT_FLOAT, _kernel="MklOp", data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Relu, conv2d/kernel/read, Relu:1, DMT/_6)]]
the last trackback said input and filter must have the same depth, which IMO means the depth dim for both input tensor and filter should be same? But how could I do that if I want to generate more feature maps? What should I do?
No need to transpose the data for changing the dataformat.
You can pass the data format as channels first or channels last as argument
For example,
python cifar10_main.py --data-dir=${PWD}/cifar-10-data --data-format=channels_first --job-dir=/tmp/cifar10

How to initialize variables in an LSTM?

I'm having difficulty when I try to run this LSTM model in TensorFlow. I'm relatively new to the library, so forgive me.
from tensorflow.contrib import ffmpeg, rnn
import tensorflow as tf
import os
import time
# hyperparameters
learning_rate = 0.01
total_iterations = 100
layer_width = 5
network_depth = 10
# path variables
mp3_output_path = "/Users/espresso/Documents/Projects/Martin/ouput"
mp3_input_path = "/Users/espresso/Documents/Projects/Martin/input/Caravan.mp3"
# Function Definitions
def import_audio(mp3_location):
binary_audio = tf.read_file(mp3_location)
audio_tensor = ffmpeg.decode_audio(binary_audio, file_format="mp3", samples_per_second=int(44100/2), channel_count=1)
reformatted_audio_tensor = tf.reshape(audio_tensor, [1, tf.shape(audio_tensor)[0], 1])
return reformatted_audio_tensor
def export_audio(audio_tensor, mp3_target_dest):
encoded_audio = ffmpeg.encode_audio(audio_tensor, file_format="mp3", samples_per_second=(44100/2))
mus_file = open(mp3_target_dest, 'wb+')
mus_file.write(encoded_audio)
mus_file.close()
print("Export complete. File located at {}".format(mp3_target_dest))
return 0
def lstm_layer(cell_quantity):
return rnn.LSTMCell(cell_quantity)
def stacked_lstm(layer_width, depth):
if type(layer_width) == list:
lstm_layer_lib = [lstm_layer(layer_width[element]) for element in layer_width]
else:
lstm_layer_lib = [lstm_layer(layer_width) for element in range(depth)]
lstm_layer_lib.insert(0, lstm_layer(3))
lstm_layer_lib.append(lstm_layer(1))
return rnn.MultiRNNCell(lstm_layer_lib)
def inaccuracy(net_loss):
return net_loss
# variable definitions
input = tf.placeholder(dtype=tf.float32, shape=[1, 5282816, 1], name="Audio_Input")
y_labels = tf.placeholder(dtype=tf.float32, shape=[1, 5282816, 1], name="Y_Labels")
init_op = tf.global_variables_initializer()
network_outline = stacked_lstm(layer_width, network_depth)
hypothesis, state = tf.nn.dynamic_rnn(network_outline, input, dtype=tf.float32)
cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(labels=y_labels, logits=hypothesis))
optimizer = tf.train.AdamOptimizer(learning_rate).minimize(cross_entropy)
with tf.Session() as sess:
sess.run(init_op)
input_mp3_tensor = sess.run(import_audio(mp3_input_path))
vector_size = int(sess.run(tf.shape(input_mp3_tensor))[1]) - 1
y_labels_tensor = sess.run(tf.convert_to_tensor([input_mp3_tensor[0][element+1][0] for element in range(vector_size)] + [0]))
reformatted_y_labels_tensor = sess.run(tf.reshape(y_labels_tensor, [1, tf.shape(y_labels_tensor)[0], 1]))
for iteration in range(total_iterations):
loss, _ = sess.run([cross_entropy, optimizer], feed_dict={input: input_mp3_tensor, y_labels: reformatted_y_labels_tensor})
As you can see, I have declared tf.global_variables_intilizer() in the variable init_op and I execute it before executing any another operation in the Session. Still, once the code completes, the following error message is returned:
Caused by op 'rnn/multi_rnn_cell/cell_4/lstm_cell/bias/read', defined at:
File "martin.py", line 41, in <module>
hypothesis, state = tf.nn.dynamic_rnn(network_outline, input, dtype=tf.float32)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py", line 635, in dynamic_rnn
dtype=dtype)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py", line 832, in _dynamic_rnn_loop
swap_memory=swap_memory)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 3202, in while_loop
result = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2940, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2877, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 3178, in <lambda>
body = lambda i, lv: (i + 1, orig_body(*lv))
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py", line 803, in _time_step
(output, new_state) = call_cell()
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py", line 789, in <lambda>
call_cell = lambda: cell(input_t, state)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 191, in __call__
return super(RNNCell, self).__call__(inputs, state)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 714, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 1242, in call
cur_inp, new_state = cell(cur_inp, cur_state)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 298, in __call__
*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 696, in __call__
self.build(input_shapes)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 730, in build
initializer=init_ops.zeros_initializer(dtype=self.dtype))
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 546, in add_variable
partitioner=partitioner)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/training/checkpointable.py", line 415, in _add_variable_with_custom_getter
**kwargs_for_getter)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 1297, in get_variable
constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 1093, in get_variable
constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 431, in get_variable
return custom_getter(**custom_getter_kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 194, in _rnn_get_variable
variable = getter(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 408, in _true_getter
use_resource=use_resource, constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 800, in _get_single_variable
use_resource=use_resource)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 2157, in variable
use_resource=use_resource)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 2147, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 2130, in default_variable_creator
constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variables.py", line 235, in __init__
constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variables.py", line 388, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 142, in identity
return gen_array_ops.identity(input, name=name)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3053, in identity
"Identity", input=input, name=name)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
op_def=op_def)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1654, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value rnn/multi_rnn_cell/cell_4/lstm_cell/bias
[[Node: rnn/multi_rnn_cell/cell_4/lstm_cell/bias/read = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](rnn/multi_rnn_cell/cell_4/lstm_cell/bias)]]
I'm not entirely sure if I'm actually supposed to create weights and pass them into TensorFlow functions as a parameter. But I have no other idea as to why the program is unsuccessful.
The reason of the error is that you defined the init_op before defining your variables (i.e. before calling stacked_lstm and tf.nn.dynamic_rnn. This means that the variables you defined after having called init_op won't be initialised.
You should do something like:
network_outline = stacked_lstm(layer_width, network_depth)
hypothesis, state = tf.nn.dynamic_rnn(network_outline, input, dtype=tf.float32)
cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(labels=y_labels, logits=hypothesis))
optimizer = tf.train.AdamOptimizer(learning_rate).minimize(cross_entropy)
init_op = tf.global_variables_initializer()

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