In [1]:

    

#Tensor Ranks, Shapes, and Types

#rank two tensor
t = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]


    

In [2]:

    

def my_image_filter(input_images):
    conv1_weights = tf.Variable(tf.random_normal([5, 5, 32, 32]),
        name="conv1_weights")
    conv1_biases = tf.Variable(tf.zeros([32]), name="conv1_biases")
    conv1 = tf.nn.conv2d(input_images, conv1_weights,
        strides=[1, 1, 1, 1], padding='SAME')
    relu1 = tf.nn.relu(conv1 + conv1_biases)

    conv2_weights = tf.Variable(tf.random_normal([5, 5, 32, 32]),
        name="conv2_weights")
    conv2_biases = tf.Variable(tf.zeros([32]), name="conv2_biases")
    conv2 = tf.nn.conv2d(relu1, conv2_weights,
        strides=[1, 1, 1, 1], padding='SAME')
    return tf.nn.relu(conv2 + conv2_biases)


    

In [3]:

    

# First call creates one set of 4 variables.
result1 = my_image_filter(image1)
# Another set of 4 variables is created in the second call.
result2 = my_image_filter(image2)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-3-e37e39f6632a> in <module>()
      1 # First call creates one set of 4 variables.
----> 2 result1 = my_image_filter(image1)
      3 # Another set of 4 variables is created in the second call.
      4 result2 = my_image_filter(image2)

NameError: name 'image1' is not defined

In [ ]:

    

variables_dict = {
    "conv1_weights": tf.Variable(tf.random_normal([5, 5, 32, 32]),
        name="conv1_weights")
    "conv1_biases": tf.Variable(tf.zeros([32]), name="conv1_biases")
    ... etc. ...
}

def my_image_filter(input_images, variables_dict):
    conv1 = tf.nn.conv2d(input_images, variables_dict["conv1_weights"],
        strides=[1, 1, 1, 1], padding='SAME')
    relu1 = tf.nn.relu(conv1 + variables_dict["conv1_biases"])

    conv2 = tf.nn.conv2d(relu1, variables_dict["conv2_weights"],
        strides=[1, 1, 1, 1], padding='SAME')
    return tf.nn.relu(conv2 + variables_dict["conv2_biases"])

# Both calls to my_image_filter() now use the same variables
result1 = my_image_filter(image1, variables_dict)
result2 = my_image_filter(image2, variables_dict)


    

In [4]:

    

def conv_relu(input, kernel_shape, bias_shape):
    # Create variable named "weights".
    weights = tf.get_variable("weights", kernel_shape,
        initializer=tf.random_normal_initializer())
    # Create variable named "biases".
    biases = tf.get_variable("biases", bias_shape,
        initializer=tf.constant_initializer(0.0))
    conv = tf.nn.conv2d(input, weights,
        strides=[1, 1, 1, 1], padding='SAME')
    return tf.nn.relu(conv + biases)


    

In [8]:

    

def my_image_filter(input_images):
    with tf.variable_scope("conv1"):
        # Variables created here will be named "conv1/weights", "conv1/biases".
        relu1 = conv_relu(input_images, [5, 5, 32, 32], [32])
    with tf.variable_scope("conv2"):
        # Variables created here will be named "conv2/weights", "conv2/biases".
        return conv_relu(relu1, [5, 5, 32, 32], [32])


    

In [ ]:

    

result1 = my_image_filter(image1)
result2 = my_image_filter(image2)
# Raises ValueError(... conv1/weights already exists ...)


    

In [9]:

    

import tensorflow as tf
with tf.variable_scope("image_filters") as scope:
    result1 = my_image_filter(image1)
    #you need to specify it by setting reuse_variables() as follows.
    scope.reuse_variables()
    result2 = my_image_filter(image2)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-9-e01590c15391> in <module>()
      1 import tensorflow as tf
      2 with tf.variable_scope("image_filters") as scope:
----> 3     result1 = my_image_filter(image1)
      4     #you need to specify it by setting reuse_variables() as follows.
      5     scope.reuse_variables()

NameError: name 'image1' is not defined

In [ ]:

    

v = tf.get_variable(name, shape, dtype, initializer)


    

In [ ]:

    

with tf.variable_scope("foo"):
    v = tf.get_variable("v", [1])
assert v.name == "foo/v:0"


    

In [ ]:

    

with tf.variable_scope("foo"):
    v = tf.get_variable("v", [1])
with tf.variable_scope("foo", reuse=True):
    v1 = tf.get_variable("v", [1])
assert v1 is v


    

In [ ]:

    

with tf.variable_scope("foo"):
    with tf.variable_scope("bar"):
        v = tf.get_variable("v", [1])
assert v.name == "foo/bar/v:0"


    

In [14]:

    

with tf.variable_scope("foo"):
    v = tf.get_variable("v", [1])
    tf.get_variable_scope().reuse_variables()
    v1 = tf.get_variable("v", [1])
assert v1 is v


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-14-7746de2095e5> in <module>()
      1 with tf.variable_scope("foo"):
----> 2     v = tf.get_variable("v", [1])
      3     tf.get_variable_scope().reuse_variables()
      4     v1 = tf.get_variable("v", [1])
      5 assert v1 is v

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    986       collections=collections, caching_device=caching_device,
    987       partitioner=partitioner, validate_shape=validate_shape,
--> 988       custom_getter=custom_getter)
    989 get_variable_or_local_docstring = (
    990     """%s

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    888           collections=collections, caching_device=caching_device,
    889           partitioner=partitioner, validate_shape=validate_shape,
--> 890           custom_getter=custom_getter)
    891 
    892   def _get_partitioned_variable(self,

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    346           reuse=reuse, trainable=trainable, collections=collections,
    347           caching_device=caching_device, partitioner=partitioner,
--> 348           validate_shape=validate_shape)
    349 
    350   def _get_partitioned_variable(

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _true_getter(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape)
    331           initializer=initializer, regularizer=regularizer, reuse=reuse,
    332           trainable=trainable, collections=collections,
--> 333           caching_device=caching_device, validate_shape=validate_shape)
    334 
    335     if custom_getter is not None:

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _get_single_variable(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape)
    637                          " Did you mean to set reuse=True in VarScope? "
    638                          "Originally defined at:\n\n%s" % (
--> 639                              name, "".join(traceback.format_list(tb))))
    640       found_var = self._vars[name]
    641       if not shape.is_compatible_with(found_var.get_shape()):

ValueError: Variable foo/v already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:

  File "<ipython-input-11-82c6eccf7fb4>", line 2, in <module>
    v = tf.get_variable("v", [1])
  File "/Users/lipingzhang/anaconda/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 "/Users/lipingzhang/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):

In [13]:

    

with tf.variable_scope("root"):
    # At start, the scope is not reusing.
    assert tf.get_variable_scope().reuse == False
    with tf.variable_scope("foo"):
        # Opened a sub-scope, still not reusing.
        assert tf.get_variable_scope().reuse == False
    with tf.variable_scope("foo", reuse=True):
        # Explicitly opened a reusing scope.
        assert tf.get_variable_scope().reuse == True
        with tf.variable_scope("bar"):
            # Now sub-scope inherits the reuse flag.
            assert tf.get_variable_scope().reuse == True
    # Exited the reusing scope, back to a non-reusing one.
    assert tf.get_variable_scope().reuse == False


    

In [11]:

    

with tf.variable_scope("foo") as foo_scope:
    v = tf.get_variable("v", [1])
with tf.variable_scope(foo_scope):
    w = tf.get_variable("w", [1])
with tf.variable_scope(foo_scope, reuse=True):
    v1 = tf.get_variable("v", [1])
    w1 = tf.get_variable("w", [1])
assert v1 is v
assert w1 is w


    

In [12]:

    

with tf.variable_scope("foo") as foo_scope:
    assert foo_scope.name == "foo"
with tf.variable_scope("bar"):
    with tf.variable_scope("baz") as other_scope:
        assert other_scope.name == "bar/baz"
        with tf.variable_scope(foo_scope) as foo_scope2:
            assert foo_scope2.name == "foo"  # Not changed.


    

In [16]:

    

with tf.variable_scope("foo", initializer=tf.constant_initializer(0.4)):
    v = tf.get_variable("v", [1])
    assert v.eval() == 0.4  # Default initializer as set above.
    w = tf.get_variable("w", [1], initializer=tf.constant_initializer(0.3))
    assert w.eval() == 0.3  # Specific initializer overrides the default.
    with tf.variable_scope("bar"):
        v = tf.get_variable("v", [1])
        assert v.eval() == 0.4  # Inherited default initializer.
    with tf.variable_scope("baz", initializer=tf.constant_initializer(0.2)):
        v = tf.get_variable("v", [1])
        assert v.eval() == 0.2  # Changed default initializer.


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-16-8bff80afc5f2> in <module>()
      1 with tf.variable_scope("foo", initializer=tf.constant_initializer(0.4)):
----> 2     v = tf.get_variable("v", [1])
      3     assert v.eval() == 0.4  # Default initializer as set above.
      4     w = tf.get_variable("w", [1], initializer=tf.constant_initializer(0.3))
      5     assert w.eval() == 0.3  # Specific initializer overrides the default.

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    986       collections=collections, caching_device=caching_device,
    987       partitioner=partitioner, validate_shape=validate_shape,
--> 988       custom_getter=custom_getter)
    989 get_variable_or_local_docstring = (
    990     """%s

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    888           collections=collections, caching_device=caching_device,
    889           partitioner=partitioner, validate_shape=validate_shape,
--> 890           custom_getter=custom_getter)
    891 
    892   def _get_partitioned_variable(self,

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    346           reuse=reuse, trainable=trainable, collections=collections,
    347           caching_device=caching_device, partitioner=partitioner,
--> 348           validate_shape=validate_shape)
    349 
    350   def _get_partitioned_variable(

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _true_getter(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape)
    331           initializer=initializer, regularizer=regularizer, reuse=reuse,
    332           trainable=trainable, collections=collections,
--> 333           caching_device=caching_device, validate_shape=validate_shape)
    334 
    335     if custom_getter is not None:

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _get_single_variable(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape)
    637                          " Did you mean to set reuse=True in VarScope? "
    638                          "Originally defined at:\n\n%s" % (
--> 639                              name, "".join(traceback.format_list(tb))))
    640       found_var = self._vars[name]
    641       if not shape.is_compatible_with(found_var.get_shape()):

ValueError: Variable foo/v already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:

  File "<ipython-input-11-82c6eccf7fb4>", line 2, in <module>
    v = tf.get_variable("v", [1])
  File "/Users/lipingzhang/anaconda/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 "/Users/lipingzhang/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):

In [17]:

    

with tf.variable_scope("foo"):
    x = 1.0 + tf.get_variable("v", [1])
assert x.op.name == "foo/add"


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-17-cd50aa2150bf> in <module>()
      1 with tf.variable_scope("foo"):
----> 2     x = 1.0 + tf.get_variable("v", [1])
      3 assert x.op.name == "foo/add"

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    986       collections=collections, caching_device=caching_device,
    987       partitioner=partitioner, validate_shape=validate_shape,
--> 988       custom_getter=custom_getter)
    989 get_variable_or_local_docstring = (
    990     """%s

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    888           collections=collections, caching_device=caching_device,
    889           partitioner=partitioner, validate_shape=validate_shape,
--> 890           custom_getter=custom_getter)
    891 
    892   def _get_partitioned_variable(self,

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    346           reuse=reuse, trainable=trainable, collections=collections,
    347           caching_device=caching_device, partitioner=partitioner,
--> 348           validate_shape=validate_shape)
    349 
    350   def _get_partitioned_variable(

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _true_getter(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape)
    331           initializer=initializer, regularizer=regularizer, reuse=reuse,
    332           trainable=trainable, collections=collections,
--> 333           caching_device=caching_device, validate_shape=validate_shape)
    334 
    335     if custom_getter is not None:

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _get_single_variable(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape)
    637                          " Did you mean to set reuse=True in VarScope? "
    638                          "Originally defined at:\n\n%s" % (
--> 639                              name, "".join(traceback.format_list(tb))))
    640       found_var = self._vars[name]
    641       if not shape.is_compatible_with(found_var.get_shape()):

ValueError: Variable foo/v already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:

  File "<ipython-input-11-82c6eccf7fb4>", line 2, in <module>
    v = tf.get_variable("v", [1])
  File "/Users/lipingzhang/anaconda/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 "/Users/lipingzhang/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):

In [18]:

    

with tf.variable_scope("foo"):
    with tf.name_scope("bar"):
        v = tf.get_variable("v", [1])
        x = 1.0 + v
assert v.name == "foo/v:0"
assert x.op.name == "foo/bar/add"


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-18-4d5ba371cdbf> in <module>()
      1 with tf.variable_scope("foo"):
      2     with tf.name_scope("bar"):
----> 3         v = tf.get_variable("v", [1])
      4         x = 1.0 + v
      5 assert v.name == "foo/v:0"

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    986       collections=collections, caching_device=caching_device,
    987       partitioner=partitioner, validate_shape=validate_shape,
--> 988       custom_getter=custom_getter)
    989 get_variable_or_local_docstring = (
    990     """%s

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    888           collections=collections, caching_device=caching_device,
    889           partitioner=partitioner, validate_shape=validate_shape,
--> 890           custom_getter=custom_getter)
    891 
    892   def _get_partitioned_variable(self,

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, custom_getter)
    346           reuse=reuse, trainable=trainable, collections=collections,
    347           caching_device=caching_device, partitioner=partitioner,
--> 348           validate_shape=validate_shape)
    349 
    350   def _get_partitioned_variable(

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _true_getter(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape)
    331           initializer=initializer, regularizer=regularizer, reuse=reuse,
    332           trainable=trainable, collections=collections,
--> 333           caching_device=caching_device, validate_shape=validate_shape)
    334 
    335     if custom_getter is not None:

/Users/lipingzhang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _get_single_variable(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape)
    637                          " Did you mean to set reuse=True in VarScope? "
    638                          "Originally defined at:\n\n%s" % (
--> 639                              name, "".join(traceback.format_list(tb))))
    640       found_var = self._vars[name]
    641       if not shape.is_compatible_with(found_var.get_shape()):

ValueError: Variable foo/v already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:

  File "<ipython-input-11-82c6eccf7fb4>", line 2, in <module>
    v = tf.get_variable("v", [1])
  File "/Users/lipingzhang/anaconda/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 "/Users/lipingzhang/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):

In [ ]: