def test_train_custom_builder(self):
"""
"""
print("Running Test 0\n")
x = 10.0 * np.random.randn(100, 2)
y = x[:,
0:1] + 1.5 * x[:,
1:] # + 3*x[:,1:]**2 + 0.5*np.random.randn(100,1)
dataset = {'train_features': x, 'train_input_response': y}
# Define a builder.
# More control on the directives of each node
builder = StaticBuilder()
enc_dirs = {
'num_layers': 2,
'num_nodes': 128,
'activation': 'leaky_relu',
'net_grow_rate': 1.0
}
input_dim, output_dim = 2, 1
in0 = builder.addInput(input_dim, name="features")
enc1 = builder.addInner(1, 10, directives=enc_dirs)
enc2 = builder.addInner(1, output_dim, directives=enc_dirs)
out0 = builder.addOutput(name="prediction")
builder.addDirectedLink(in0, enc1)
builder.addDirectedLink(enc1, enc2)
builder.addDirectedLink(enc2, out0)
# Pass the builder object to the Regression Model
reg = Regression(builder=builder)
reg.build()
reg.visualize_model_graph("two_encoders.png")
reg.train(dataset, num_epochs=50)
def test_init(self):
"""
Create a CustomNode
"""
tf.reset_default_graph()
builder = StaticBuilder()
builder.createCustomNode(1, 1, name="Custom")
def test_train_custom_node2(self):
"""
Test a custom Regression model with a CustomNode
"""
print("Test 2: with CustomNode\n")
builder = StaticBuilder("MyModel")
enc_dirs = {
'numlayers': 2,
'numnodes': 128,
'activations': 'leaky_relu',
'netgrowrate': 1.0
}
input_dim = 2
in0 = builder.addInput(input_dim, name='Features')
cust = builder.createCustomNode(inputs=[in0],
num_outputs=1,
name="Prediction")
cust_in1 = cust.addTransformInner(3,
main_inputs=[0],
directives=enc_dirs)
cust_in2 = cust.addTransformInner(1,
main_inputs=cust_in1,
directives=enc_dirs)
cust.declareOslot(oslot=0,
innernode_name=cust_in2,
inode_oslot_name='main')
reg = Regression(builder=builder, input_dim=2, output_dim=1)
# save_on_valid_improvement=True) # ok!
reg.train(dataset, num_epochs=10)
def test_addInner(self):
"""
Test adding basic Deterministic InnerNode.
NOTE: The DeterministicNode belongs to the class of nodes that starts with a
known final number of outputs.
"""
print("\nTest 1: Adding InnerNode")
try:
builder = StaticBuilder()
builder.addInput(10, name="In")
enc_name = builder.addInner(3, name="In")
except AttributeError:
print("\nCAUGHT! Trying to assign the same name to two nodes! "
"AttributeError exception\n")
builder = StaticBuilder()
builder.addInput(10, name="In")
enc_name = builder.addInner(3, name="Det")
enc1 = builder.nodes[enc_name]
print('\nNode keys in builder:', list(builder.nodes.keys()))
print("This node's key:", enc_name)
self.assertEqual(enc1.label, 1,
"The label has not been assigned correctly")
self.assertEqual(
builder.num_nodes, 2, "The number of nodes has not been "
"assigned correctly")
self.assertEqual(
enc1.num_declared_outputs, 0, "The number of outputs of the "
"DeterministicNode has not been assigned correctly")
self.assertEqual(
enc1.num_declared_inputs, 0, "The number of inputs of the "
"DeterministicNode has not been assigned correctly")
def test_merge_init(self):
"""
Test Merge Node initialization
"""
builder = StaticBuilder(scope='Main')
in1 = builder.addInner([[3]], num_inputs=1, node_class=NormalTriLNode)
in2 = builder.addInner([[3]], num_inputs=1, node_class=NormalTriLNode)
builder.addMergeNode(node_list=[in1, in2],
merge_class=MergeNormals)
def test_addDirectedLinks(self):
"""
Test adding DirectedLinks
"""
print("\nTest 3: Adding DirectedLinks")
builder = StaticBuilder()
in1 = builder.addInput(10, name="In")
enc1 = builder.addInner(3, name="Det")
out1 = builder.addOutput(name="Out")
builder.addDirectedLink(in1, enc1)
builder.addDirectedLink(enc1, out1)
enc1 = builder.nodes[enc1]
print('\nNode keys in builder:', list(builder.nodes.keys()))
self.assertEqual(
builder.num_nodes, 3, "The number of nodes has not been "
"assigned correctly")
self.assertEqual(
enc1.num_declared_outputs, 1, "The number of outputs of the "
"DeterministicNode has not been assigned correctly")
self.assertEqual(
enc1.num_declared_inputs, 1, "The number of inputs of the "
"DeterministicNode has not been assigned correctly")
self.assertIn(
1, builder.adj_list[0], "Node 1 has not been added to the "
"adjacency list of Node 0")
self.assertIn(
2, builder.adj_list[1], "Node 2 has not been added to the "
"adjacency list of Node 1")
def test_init(self):
"""
Create a CustomNode
"""
print("Test 0: Initialization")
builder = StaticBuilder(scope='BuildCust')
i1 = builder.addInput([[3]], name='In1')
cust = builder.createCustomNode(i1, 3, name="Custom")
print("cust.name", cust.name)
print("cust.num_expected_inputs", cust.num_expected_inputs)
print("cust.num_expected_outputs", cust.num_expected_outputs)
def declare_cell_encoder(self):
"""
"""
if self.builder is None:
builder = StaticBuilder(scope='Main')
else:
builder = self.builder
enc_name = builder.addInner(self.state_dim,
num_inputs=2,
node_class=NormalTriLNode,
name='NormalTrilCell')
return builder.nodes[enc_name]
def test_add_encoder0(self):
"""
Test commit
"""
print("Test 1: Adding nodes to Custom")
builder = StaticBuilder("MyModel")
i1 = builder.addInput(10)
cust = builder.createCustomNode(inputs=i1,
num_outputs=1,
name="Custom")
cust.addTransformInner(3, main_inputs=[0])
print("cust.in_builder.inode_to_innernode", cust.in_builder.islot_to_innernode_names)
def test_CallCustom(self):
"""
Test, calling a CustomNode
"""
print("\nTest 1: Build")
builder = StaticBuilder("MyModel")
cust = builder.createCustomNode(num_inputs=1,
num_outputs=1,
name="Custom")
cust_in1 = cust.addInner(3)
cust_in2 = cust.addInner(4)
cust.addDirectedLink(cust_in1, cust_in2, islot=0)
cust.declareIslot(islot=0, innernode_name=cust_in1, inode_islot=0)
cust.declareOslot(oslot='main',
innernode_name=cust_in2,
inode_oslot='main')
in1 = builder.addInput(10)
builder.addDirectedLink(in1, cust, islot=0)
builder.build()
X = tf.placeholder(tf.float32, [1, 10], 'X')
Y = cust(X) # pylint: disable=unpacking-non-sequence
print('Y', Y)
self.assertEqual(Y[0].shape[-1], 4, "")
def test_add_encoder1(self):
"""
Test commit
"""
print("Test 2: Adding more nodes to Custom")
builder = StaticBuilder("MyModel")
i1 = builder.addInput(10)
cust = builder.createCustomNode(inputs=i1,
num_outputs=1,
name="Custom")
ctin1 = cust.addTransformInner(3, [0])
cust.addTransformInner(4, [ctin1])
print("cust.in_builder._inode_to_innernode", cust.in_builder.islot_to_innernode_names)
print("cust.in_builder.input_nodes", cust.in_builder.input_nodes)
def test_add_encoder2(self):
"""
Test commit
"""
print("Test 3: Declaring multiple inputs to the Custom Node")
builder = StaticBuilder("MyModel")
i1 = builder.addInput(10)
i2 = builder.addInput(5)
cust = builder.createCustomNode(inputs=[i1,i2],
num_outputs=1,
name="Custom")
ctin1 = cust.addTransformInner(3, [0])
cust.addTransformInner(3, [1, ctin1])
print("cust.in_builder._inode_to_innernode", cust.in_builder.islot_to_innernode_names)
print("cust.in_builder.input_nodes", cust.in_builder.input_nodes)
def test_train_custom_node2(self):
"""
Test commit
"""
print("Test 1: with CustomNode\n")
builder = StaticBuilder("MyModel")
enc_dirs = {
'loc_numlayers': 2,
'loc_numnodes': 64,
'loc_activations': 'softplus',
'loc_netgrowrate': 1.0
}
input_dim = 10
in0 = builder.addInput(input_dim, name='Observation')
# Define Custom Recognition Model
cust_rec = builder.createCustomNode(inputs=[in0],
num_outputs=1,
name="Recognition")
cust_in2 = cust_rec.addTransformInner(3,
main_inputs=[0],
node_class=NormalTriLNode,
**enc_dirs)
cust_rec.declareOslot(oslot=0,
innernode_name=cust_in2,
inode_oslot_name='main')
# Define Custom Generative Model
cust_gen = builder.createCustomNode(inputs=cust_rec.name,
num_outputs=1,
name="Generative")
cust_ginn1 = cust_gen.addTransformInner(16, main_inputs=[0])
cust_ginn2 = cust_gen.addTransformInner(10,
main_inputs=cust_ginn1,
node_class=NormalTriLNode,
**enc_dirs)
cust_gen.declareOslot(oslot=0,
innernode_name=cust_ginn2,
inode_oslot_name='main')
# Define VAE and train
vae = VariationalAutoEncoder(builder=builder)
vae.train(dataset, num_epochs=10)
def test_train_custom_builder2(self):
"""
Build a custom Regression model whose Model graph has the rhombic design
"""
print("Test 1: Rhombic Design\n")
# Define the builder
builder = StaticBuilder('CustBuild')
enc_dirs = {
'numlayers': 2,
'numnodes': 128,
'activations': 'leaky_relu',
'netgrowrate': 1.0
}
input_dim = 2
in0 = builder.addInput(input_dim, name="Features")
enc1 = builder.addTransformInner(10,
main_inputs=in0,
directives=enc_dirs)
enc2 = builder.addTransformInner(10,
main_inputs=in0,
directives=enc_dirs)
builder.addTransformInner(1,
main_inputs=[enc1, enc2],
numlayers=1,
activations='linear',
name='Prediction')
reg = Regression(input_dim=2, output_dim=1, builder=builder)
# save_on_valid_improvement=True) # OK!
reg.train(dataset, num_epochs=10)
def test_init(self):
"""
Create a Custom Cell
"""
print("Test 0: Custom cell init")
builder = StaticBuilder(scope='BuildCell')
cell = BasicEncoderCell(builder, state_sizes=[[5]])
print("cell.encoder", cell.encoder)
def test_merge_build1(self):
"""
Test Merge Node build
"""
builder = StaticBuilder(scope='Main')
i1 = builder.addInput([[1]])
in1 = builder.addInner([[3]], node_class=NormalTriLNode)
in2 = builder.addInner([[3]], node_class=NormalTriLNode)
builder.addDirectedLink(i1, in1, islot=0)
builder.addDirectedLink(i1, in2, islot=0)
m1 = builder.addMergeNode([in1, in2],
merge_class=MergeNormals)
builder.build()
m1 = builder.nodes[m1]
self.assertIn('loc', m1._oslot_to_otensor)
self.assertIn('main', m1._oslot_to_otensor)
self.assertIn('cov', m1._oslot_to_otensor)
def test0_init(self):
"""
Test adding basic InputNode
"""
print("\nTest 0: Initialization")
builder = StaticBuilder()
in1_name = builder.addInput(10)
in1 = builder.input_nodes[in1_name]
print('Node keys in builder:', list(builder.input_nodes.keys()))
self.assertEqual(in1.label, 0,
"The label has not been assigned correctly")
self.assertEqual(
builder.num_nodes, 1, "The number of nodes has not been "
"assigned correctly")
self.assertEqual(
in1.num_declared_outputs, 0, "The number of outputs of "
"the InputNode has not been assigned correctly")
self.assertEqual(
in1.num_declared_inputs, 0, "The number of outputs of "
"the InputNode has not been assigned correctly")
def test_train_custom_builder(self):
"""
"""
print("Test 0: Chain of Encoders\n")
# Define a builder. Get more control on the directives of each node
enc_dirs = {
'numlayers': 2,
'numnodes': 128,
'activations': 'leaky_relu',
'netgrowrate': 1.0
}
input_dim, output_dim = 2, 1
builder = StaticBuilder('CustBuild')
in0 = builder.addInput(input_dim, name="Features")
enc1 = builder.addTransformInner(5, main_inputs=in0, **enc_dirs)
builder.addTransformInner(state_size=1,
main_inputs=enc1,
directives=enc_dirs,
name='Prediction')
# Pass the builder object to the Regression Model
reg = Regression(builder=builder, output_dim=output_dim)
# save_on_valid_improvement=True) # ok!
reg.train(dataset, num_epochs=10)
def build(self):
"""
Builds the Regression.
=> E =>
"""
if self._is_built:
raise ValueError("Node is already built")
builder = self.builder
ftrs_dirs = self.directives['ftrs']
enc_dirs = self.directives['enc']
tr_dirs = self.directives['tr']
if builder is None:
self.builder = builder = StaticBuilder(scope=self._main_scope)
in0 = builder.addInput(self.input_dim,
name="Features",
**ftrs_dirs)
builder.addTransformInner(state_size=1,
main_inputs=in0,
name='Prediction',
**enc_dirs)
else:
self._check_custom_build()
builder.scope = self._main_scope
builder.addInput(self.output_dim, name="Observation")
# build the tensorflow graph
builder.build()
self.nodes = builder.nodes
self.otensor_names = builder.otensor_names
self.dummies = self.builder.dummies
# Define cost and trainer attribute
cost_declare = ('mse', ('Prediction', 'Observation'))
cost_func = self.summaries_dict[cost_declare[0]]
self.cost = cost_func(self.nodes, cost_declare[1])
self.otensor_names['cost'] = self.cost.name
# trainer object
self.trainer = GDTrainer(model=self,
keep_logs=self.keep_logs,
**tr_dirs)
if self.save: # save
self.save_otensor_names()
print("\nThe following names are available for evaluation:")
for name in sorted(self.otensor_names.keys()):
print('\t', name)
self._is_built = True
def test_call(self):
"""
Call a Custom Cell Node
"""
print("Test 1: Custom cell call")
builder = StaticBuilder(scope='BuildCell')
cell = BasicEncoderCell(builder, state_sizes=[[5]])
print("cell.encoder", cell.encoder)
X = tf.placeholder(tf.float64, [None, 5])
Y = tf.placeholder(tf.float64, [None, 10])
Z = cell(X, Y)
print("Z", Z)
def test_NormalTriLCell(self):
"""
Test the NormalTriLCell Node
"""
print("Test 2: ")
builder = StaticBuilder(scope='BuildCell')
cell = NormalTriLCell(builder, state_sizes=[[5]])
print("cell.encoder", cell.encoder)
X = tf.placeholder(tf.float64, [None, 5])
Y = tf.placeholder(tf.float64, [None, 10])
Z = cell(X, Y)
print("Z", Z)
def test_init1(self):
"""
Test adding basic InputNode
"""
print("Test 1: Simple build")
builder = StaticBuilder(scope='Build')
in1_name = builder.addInput(state_size=10, iclass=NormalInputNode)
in1 = builder.input_nodes[in1_name]
print('Node keys in builder:', list(builder.input_nodes.keys()))
self.assertEqual(in1.label, 0,
"The label has not been assigned correctly")
self.assertEqual(
builder.num_nodes, 1, "The number of nodes has not been "
"assigned correctly")
self.assertEqual(
in1.num_declared_outputs, 0, "The number of outputs of "
"the InputNode has not been assigned correctly")
self.assertEqual(
in1.num_declared_inputs, 0, "The number of outputs of "
"the InputNode has not been assigned correctly")
builder.build()
print('in1._oslot_to_otensor', in1._oslot_to_otensor)
def test_train_custom_node2(self):
"""
Test commit
"""
print("Test 2: with CustomNode\n")
input_dim = 2
x = 10.0 * np.random.randn(100, input_dim)
y = x[:,
0:1] + 1.5 * x[:,
1:] # + 3*x[:,1:]**2 + 0.5*np.random.randn(100,1)
dataset = {'train_features': x, 'train_input_response': y}
builder = StaticBuilder("MyModel")
enc_dirs = {
'num_layers': 2,
'num_nodes': 128,
'activation': 'leaky_relu',
'net_grow_rate': 1.0
}
in0 = builder.addInput(input_dim, name='features')
cust = builder.createCustomNode(1, 1, name="Custom")
cust_in1 = cust.addInner(3, directives=enc_dirs)
cust_in2 = cust.addInner(1, directives=enc_dirs)
cust.addDirectedLink(cust_in1, cust_in2)
cust.addInput(islot=0, inode_name=cust_in1, inode_islot=0)
cust.addOutput(oslot=0, inode_name=cust_in2, inode_oslot=0)
cust.commit()
out0 = builder.addOutput(name='prediction')
builder.addDirectedLink(in0, cust)
builder.addDirectedLink(cust, out0)
# Pass the builder object to the Regression Model
reg = Regression(input_dim=2, output_dim=1, builder=builder)
reg.build()
reg.visualize_model_graph("two_encoders.png")
reg.train(dataset, num_epochs=50)
def test_add_encoder0(self):
"""
Test commit
"""
tf.reset_default_graph()
builder = StaticBuilder("MyModel")
builder.addInput(10)
cust = builder.createCustomNode(1, 1, name="Custom")
cust_in1 = cust.addInner(3)
cust_in2 = cust.addInner(4)
cust.addDirectedLink(cust_in1, cust_in2)
cust.commit()
builder.addOutput()
def addInputSequence(self,
state_size,
name=None,
node_class=PlaceholderInputNode,
**dirs):
"""
Add an InputSequence
"""
node_name = StaticBuilder.addInput(self,
state_size=state_size,
iclass=node_class,
name=name,
is_sequence=True,
**dirs)
self.input_sequences[node_name] = self.input_nodes[node_name]
return node_name
def addInputSequence(self,
num_features,
name=None,
node_class=PlaceholderInputNode,
**dirs):
"""
Add an InputSequence
"""
node_name = StaticBuilder.addInput(self,
num_features=num_features,
name=name,
iclass=node_class,
max_steps=self.max_steps,
is_sequence=True,
**dirs)
self.input_sequences[node_name] = self.input_nodes[node_name]
return node_name
def test_CallDeterministic(self):
"""
Test Calling a DeterministicNode
"""
print("\nTest 0: Calling a Deterministic Node")
builder = StaticBuilder(scope="Basic")
in_name = builder.addInput(10)
enc_name = builder.addInner(3)
builder.addDirectedLink(in_name, enc_name, islot=0)
self.assertEqual(
builder.num_nodes, 2, "The number of nodes has not been "
"assigned correctly")
builder.build()
X = tf.placeholder(tf.float32, [1, 10], 'X')
enc = builder.nodes[enc_name]
Y = enc((X))
print('Y', Y)
self.assertEqual(Y.shape[-1], 3, "")
def test_BuildModel3(self):
"""
Try to break it, the algorithm... !! Guess not mdrfkr.
"""
print("Test 7: Building a more complicated Model")
builder = StaticBuilder("BreakIt")
in1 = builder.addInput(10)
in2 = builder.addInput(20)
enc1 = builder.addTransformInner(3, main_inputs=in1)
enc2 = builder.addTransformInner(5, main_inputs=[in2, enc1])
builder.build()
enc1, enc2 = builder.nodes[enc1], builder.nodes[enc2]
print("enc1._islot_to_itensor", enc1._islot_to_itensor)
print("enc1._islot_to_itensor", enc2._islot_to_itensor)
print("enc1._oslot_to_otensor", enc1._oslot_to_otensor)
print("enc1._oslot_to_otensor", enc2._oslot_to_otensor)
def test_build3(self):
"""
Test build
"""
print("Test 7: Slightly more complicated Custom build")
builder = StaticBuilder("MyModel")
i1 = builder.addInput(10)
i2 = builder.addInput(5)
cust = builder.createCustomNode(inputs=[i1,i2],
num_outputs=1,
name="Custom")
ctin1 = cust.addTransformInner(3, [0])
ctin2 = cust.addTransformInner(3, [1, ctin1])
cust.declareOslot(oslot=0, innernode_name=ctin2, inode_oslot_name='main')
builder.build()
def test_merge_build2(self):
"""
Test Merge Node build
"""
builder = StaticBuilder(scope='Main')
i1 = builder.addInput([[3]], iclass=NormalInputNode, name='N1')
i2 = builder.addInput([[3]], iclass=NormalInputNode, name='N2')
m1 = builder.addMergeNode(node_list=[i1, i2],
merge_class=MergeNormals)
builder.build()
sess = tf.Session(graph=tf.get_default_graph())
sess.run(tf.global_variables_initializer())
s3 = builder.eval_node_oslot(sess, m1,
oslot='cov')
print("merge output", s3)
print("merge output shape", s3.shape)