def testScopeRestore(self):
c1 = conv.Conv2D(16,
8,
4,
name='conv_2d_0',
padding=conv.VALID,
initializers={
'w':
initializers.restore_initializer(
_checkpoint(),
'w',
scope='agent/conv_net_2d/conv_2d_0'),
'b':
initializers.restore_initializer(
_checkpoint(),
'b',
scope='agent/conv_net_2d/conv_2d_0')
})
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
outputs = c1(inputs)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
o = session.run(outputs)
self.assertAllClose(np.linalg.norm(o),
_ONE_CONV_LAYER,
atol=_TOLERANCE)
def testFromDifferentScope(self):
sub = functools.partial(re.sub, r'^[^/]+/', 'agent/')
restore_initializers = {
'w': initializers.restore_initializer(_checkpoint(), 'w', sub),
'b': initializers.restore_initializer(_checkpoint(), 'b', sub)
}
with tf.variable_scope('some_random_scope'):
c = convnet.ConvNet2D(output_channels=(16, 32),
kernel_shapes=(8, 4),
strides=(4, 2),
paddings=[conv.VALID],
activation=tf.nn.relu,
activate_final=True,
initializers=restore_initializers)
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
outputs = c(inputs)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
o = session.run(outputs)
self.assertAllClose(np.linalg.norm(o),
_TWO_CONV_LAYERS_RELU,
atol=_TOLERANCE)
def testFromDifferentScope(self):
sub = functools.partial(re.sub, r'^[^/]+/', 'agent/')
restore_initializers = {
'w': initializers.restore_initializer(_checkpoint(), 'w', sub),
'b': initializers.restore_initializer(_checkpoint(), 'b', sub)
}
with tf.variable_scope('some_random_scope'):
c = convnet.ConvNet2D(
output_channels=(16, 32),
kernel_shapes=(8, 4),
strides=(4, 2),
paddings=[conv.VALID],
activation=tf.nn.relu,
activate_final=True,
initializers=restore_initializers)
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
outputs = c(inputs)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
o = session.run(outputs)
self.assertAllClose(
np.linalg.norm(o), _TWO_CONV_LAYERS_RELU, atol=_TOLERANCE)
def testMoreMultipleRestore(self):
restore_initializers = {
'w': initializers.restore_initializer(_checkpoint(), 'w'),
'b': initializers.restore_initializer(_checkpoint(), 'b')
}
with tf.variable_scope('agent'):
c = convnet.ConvNet2D(output_channels=(16, 32),
kernel_shapes=(8, 4),
strides=(4, 2),
paddings=[conv.VALID],
activation=tf.nn.relu,
activate_final=True,
initializers=restore_initializers)
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
outputs = c(inputs)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
o = session.run(outputs)
self.assertAllClose(np.linalg.norm(o),
_TWO_CONV_LAYERS_RELU,
atol=_TOLERANCE)
def testScopeRestore(self):
c1 = conv.Conv2D(
16,
8,
4,
name='conv_2d_0',
padding=conv.VALID,
initializers={
'w':
initializers.restore_initializer(
_checkpoint(), 'w', scope='agent/conv_net_2d/conv_2d_0'),
'b':
initializers.restore_initializer(
_checkpoint(), 'b', scope='agent/conv_net_2d/conv_2d_0')
})
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
outputs = c1(inputs)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
o = session.run(outputs)
self.assertAllClose(np.linalg.norm(o), _ONE_CONV_LAYER, atol=_TOLERANCE)
def testMoreMultipleRestore(self):
restore_initializers = {
'w': initializers.restore_initializer(_checkpoint(), 'w'),
'b': initializers.restore_initializer(_checkpoint(), 'b')
}
with tf.variable_scope('agent'):
c = convnet.ConvNet2D(
output_channels=(16, 32),
kernel_shapes=(8, 4),
strides=(4, 2),
paddings=[conv.VALID],
activation=tf.nn.relu,
activate_final=True,
initializers=restore_initializers)
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
outputs = c(inputs)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
o = session.run(outputs)
self.assertAllClose(
np.linalg.norm(o), _TWO_CONV_LAYERS_RELU, atol=_TOLERANCE)
def testTopLevelVariable(self):
save_path = os.path.join(self.get_temp_dir(), 'toplevel_variable')
g1 = tf.Graph()
g2 = tf.Graph()
with g1.as_default():
var1 = tf.get_variable('var1',
shape=[],
initializer=tf.constant_initializer(42))
with g2.as_default():
var2 = tf.get_variable(
'var2',
shape=[],
initializer=initializers.restore_initializer(
save_path, 'var1'))
with self.test_session(graph=g1) as session:
tf.global_variables_initializer().run()
save = tf.train.Saver([var1])
save.save(session, save_path)
with self.test_session(graph=g2) as session:
tf.global_variables_initializer().run()
v2 = session.run(var2)
self.assertAllEqual(v2, 42)
def testPartitionedVariable(self):
save_path = os.path.join(self.get_temp_dir(), 'partitioned_variable')
var_name = 'my_partitioned_var'
g1 = tf.Graph()
with g1.as_default():
def initializer1(shape, dtype, partition_info):
_ = partition_info # Not used for creation.
return tf.constant(True, dtype, shape)
partitioned_var1 = tf.create_partitioned_variables(
[1 << 3, 10], [4, 1], initializer1, dtype=tf.bool, name=var_name)
with self.test_session(graph=g1) as session:
with tf.device('/cpu:0'):
tf.global_variables_initializer().run()
pv1 = session.run(partitioned_var1)
save = tf.train.Saver(partitioned_var1)
save.save(session, save_path)
g2 = tf.Graph()
with g2.as_default():
initializer2 = initializers.restore_initializer(save_path, var_name, '')
partitioned_var2 = tf.create_partitioned_variables(
[1 << 3, 10], [4, 1], initializer2, dtype=tf.bool, name=var_name)
with self.test_session(graph=g2) as session:
tf.global_variables_initializer().run()
pv2 = session.run(partitioned_var2)
self.assertAllEqual(pv1, pv2)
def testPartitionedVariable(self):
save_path = os.path.join(self.get_temp_dir(), 'partitioned_variable')
var_name = 'my_partitioned_var'
g1 = tf.Graph()
with g1.as_default():
def initializer1(shape, dtype, partition_info):
_ = partition_info # Not used for creation.
return tf.constant(True, dtype, shape)
partitioned_var1 = tf.create_partitioned_variables(
[1 << 3, 10], [4, 1], initializer1, dtype=tf.bool, name=var_name)
with self.test_session(graph=g1) as session:
with tf.device('/cpu:0'):
tf.global_variables_initializer().run()
pv1 = session.run(partitioned_var1)
save = tf.train.Saver(partitioned_var1)
save.save(session, save_path)
g2 = tf.Graph()
with g2.as_default():
initializer2 = initializers.restore_initializer(save_path, var_name, '')
partitioned_var2 = tf.create_partitioned_variables(
[1 << 3, 10], [4, 1], initializer2, dtype=tf.bool, name=var_name)
with self.test_session(graph=g2) as session:
tf.global_variables_initializer().run()
pv2 = session.run(partitioned_var2)
self.assertAllEqual(pv1, pv2)
def testMultipleRestore(self):
g = tf.Graph()
restore_initializers = {
'w': initializers.restore_initializer(_checkpoint(), 'w'),
'b': initializers.restore_initializer(_checkpoint(), 'b')
}
with g.as_default():
with tf.variable_scope('agent/conv_net_2d'):
c1 = conv.Conv2D(16,
8,
4,
name='conv_2d_0',
padding=conv.VALID,
initializers=restore_initializers)
c2 = conv.Conv2D(32,
4,
2,
name='conv_2d_1',
padding=conv.VALID,
initializers=restore_initializers)
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
intermediate_1 = c1(inputs)
intermediate_2 = c2(tf.nn.relu(intermediate_1))
outputs = tf.nn.relu(intermediate_2)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
i1, i2, o = session.run(
[intermediate_1, intermediate_2, outputs])
self.assertAllClose(np.linalg.norm(i1),
_ONE_CONV_LAYER,
rtol=0.001,
atol=0.001)
self.assertAllClose(np.linalg.norm(i2),
_TWO_CONV_LAYERS,
rtol=0.001,
atol=0.001)
self.assertAllClose(np.linalg.norm(o),
_TWO_CONV_LAYERS_RELU,
rtol=0.001,
atol=0.001)
def testSimpleRestore(self):
with tf.variable_scope('agent/conv_net_2d/conv_2d_0'):
bias = tf.get_variable(
'b',
shape=[16],
initializer=initializers.restore_initializer(_checkpoint(), 'b'))
with self.test_session() as session:
session.run(tf.global_variables_initializer())
b = session.run(bias)
self.assertAllClose(np.linalg.norm(b), 3.9685926, atol=_TOLERANCE)
def testSimpleRestore(self):
with tf.variable_scope('agent/conv_net_2d/conv_2d_0'):
bias = tf.get_variable(
'b',
shape=[16],
initializer=initializers.restore_initializer(_checkpoint(), 'b'))
with self.test_session() as session:
session.run(tf.global_variables_initializer())
b = session.run(bias)
self.assertAllClose(np.linalg.norm(b), 3.9685926, atol=_TOLERANCE)
def testMultipleRestore(self):
g = tf.Graph()
restore_initializers = {
'w': initializers.restore_initializer(_checkpoint(), 'w'),
'b': initializers.restore_initializer(_checkpoint(), 'b')
}
with g.as_default():
with tf.variable_scope('agent/conv_net_2d'):
c1 = conv.Conv2D(
16,
8,
4,
name='conv_2d_0',
padding=conv.VALID,
initializers=restore_initializers)
c2 = conv.Conv2D(
32,
4,
2,
name='conv_2d_1',
padding=conv.VALID,
initializers=restore_initializers)
inputs = tf.constant(1 / 255.0, shape=[1, 86, 86, 3])
intermediate_1 = c1(inputs)
intermediate_2 = c2(tf.nn.relu(intermediate_1))
outputs = tf.nn.relu(intermediate_2)
init = tf.global_variables_initializer()
tf.get_default_graph().finalize()
with self.test_session() as session:
session.run(init)
i1, i2, o = session.run([intermediate_1, intermediate_2, outputs])
self.assertAllClose(np.linalg.norm(i1), _ONE_CONV_LAYER, atol=_TOLERANCE)
self.assertAllClose(np.linalg.norm(i2), _TWO_CONV_LAYERS, atol=_TOLERANCE)
self.assertAllClose(
np.linalg.norm(o), _TWO_CONV_LAYERS_RELU, atol=_TOLERANCE)
def testTopLevelVariable(self):
save_path = os.path.join(self.get_temp_dir(), 'toplevel_variable')
g1 = tf.Graph()
g2 = tf.Graph()
with g1.as_default():
var1 = tf.get_variable(
'var1', shape=[], initializer=tf.constant_initializer(42))
with g2.as_default():
var2 = tf.get_variable(
'var2',
shape=[],
initializer=initializers.restore_initializer(save_path, 'var1'))
with self.test_session(graph=g1) as session:
tf.global_variables_initializer().run()
save = tf.train.Saver([var1])
save.save(session, save_path)
with self.test_session(graph=g2) as session:
tf.global_variables_initializer().run()
v2 = session.run(var2)
self.assertAllEqual(v2, 42)
