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_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 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_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_BuildModel0(self):
"""
Test building the simplest model possible.
"""
print("\nTest 4: Building a Basic Model")
builder = StaticBuilder(scope="Basic")
in_name = builder.addInput(10)
enc_name = builder.addInner(3)
out_name = builder.addOutput()
builder.addDirectedLink(in_name, enc_name)
builder.addDirectedLink(enc_name, out_name)
self.assertEqual(
builder.num_nodes, 3, "The number of nodes has not been "
"assigned correctly")
builder.build()
inn, enc, out = (builder.nodes[in_name], builder.nodes[enc_name],
builder.nodes[out_name])
self.assertEqual(inn._oslot_to_otensor[0].shape.as_list()[-1],
enc._islot_to_itensor[0].shape.as_list()[-1],
"The input tensors have not been assigned correctly")
self.assertEqual(enc._oslot_to_otensor[0].shape.as_list()[-1],
out._islot_to_itensor[0].shape.as_list()[-1],
"The input tensors have not been assigned correctly")
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_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 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_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_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_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_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 test_build_outputs1(self):
"""
Test build
"""
print("Test 9: Building outputs")
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, [0, ctin1, 1])
cust.declareOslot(oslot=0, innernode_name=ctin2, inode_oslot_name='main')
builder.build()
X = tf.placeholder(tf.float64, [None, 10])
Y = tf.placeholder(tf.float64, [None, 5])
cust.build_outputs(imain0=X, imain1=Y)
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_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_addOutput(self):
"""
Test adding basic OutputNode
"""
print("\nTest 2: Adding OutputNode")
builder = StaticBuilder()
builder.addInput(10, name="In")
builder.addInner(3, name="Det")
o_name = builder.addOutput(name="Out")
o1 = builder.nodes[o_name]
print("\nNode keys in builder:", list(builder.nodes.keys()))
print("This node's key:", o_name)
self.assertEqual(o1.label, 2,
"The label has not been assigned correctly")
self.assertEqual(
builder.num_nodes, 3, "The number of nodes has not been "
"assigned correctly")
self.assertEqual(
o1.num_declared_outputs, 0, "The number of outputs of the "
"OutputNode has not been assigned correctly")
self.assertEqual(
o1.num_declared_inputs, 0, "The number of inputs of the "
"OutputNode has not been assigned correctly")
def test_build0(self):
"""
Test commit
"""
print("Test 4: Basic Custom build")
builder = StaticBuilder("MyModel")
i1 = builder.addInput(10)
cust = builder.createCustomNode(inputs=i1,
num_outputs=1,
name="Custom")
ctin = cust.addTransformInner(3, main_inputs=[0])
cust.declareOslot(0, ctin, 'main')
builder.build()
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("Test 2: Adding InnerNode")
try:
builder = StaticBuilder(scope='Build0')
i1 = builder.addInput(state_size=10, name="In")
enc_name = builder.addTransformInner(state_sizes=3,
main_inputs=i1,
name="In")
except AttributeError:
print("\nCAUGHT! (AttributeError exception) \n"
"Trying to assign the same name to two nodes!")
builder = StaticBuilder(scope='Build0')
i1 = builder.addInput(state_size=10, name="In")
enc_name = builder.addTransformInner(state_size=3, main_inputs=i1)
enc1 = builder.nodes[enc_name]
print('\nNode keys in builder:', list(builder.nodes.keys()))
print("This node's key:", enc_name)
print("Builder adjacency matrix", builder.adj_matrix)
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_BuildModel2(self):
"""
Builds a model with 2 inputs. Test concatenation
"""
print("Test 4: Building a Model with concat")
builder = StaticBuilder("Concat")
in1 = builder.addInput(10)
in2 = builder.addInput(20)
enc1 = builder.addTransformInner(3, main_inputs=[in1, in2])
in1, in2, enc1 = builder.nodes[in1], builder.nodes[in2], builder.nodes[
enc1]
builder.build()
print("enc1._islot_to_itensor", enc1._islot_to_itensor)
print("enc1._oslot_to_otensor", enc1._oslot_to_otensor)
def test_BuildModel0(self):
"""
Test building the simplest model possible.
"""
print("Test 3: Building a Basic Model")
builder = StaticBuilder(scope="Basic")
in_name = builder.addInput(10)
enc_name = builder.addTransformInner(3, main_inputs=in_name)
inn, enc = builder.nodes[in_name], builder.nodes[enc_name]
builder.build()
print("enc._islot_to_itensor", enc._islot_to_itensor)
self.assertEqual(inn._oslot_to_otensor['main'].shape.as_list()[-1],
enc._islot_to_itensor[0]['main'].shape.as_list()[-1],
"The input tensors have not been assigned correctly")
def test_BuildModel2(self):
"""
Builds a model with 2 inputs. Test ConcatNode
"""
print("\nTest 6: Building a Model with Concat")
builder = StaticBuilder("Concat")
in1 = builder.addInput(10)
in2 = builder.addInput(20)
enc1 = builder.addInner(3, num_islots=2)
out1 = builder.addOutput()
builder.addDirectedLink(in1, enc1, islot=0)
builder.addDirectedLink(in2, enc1, islot=1)
builder.addDirectedLink(enc1, out1)
builder.build()
def test_BuildModel1(self):
"""
Test building a model with 2 outputs. Test Cloning an output
"""
print("\nTest 5: Building a Model with cloning")
builder = StaticBuilder("Clone")
in1 = builder.addInput(10)
enc1 = builder.addInner(3)
out1 = builder.addOutput(name="Out1")
out2 = builder.addOutput(name="Out2")
builder.addDirectedLink(in1, enc1)
builder.addDirectedLink(enc1, out1)
builder.addDirectedLink(enc1, out2)
builder.build()
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 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 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_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_build_outputs(self):
"""
Test commit
"""
print("Test 8: Building outputs")
builder = StaticBuilder("MyModel")
i1 = builder.addInput(10)
cust = builder.createCustomNode(inputs=i1,
num_outputs=1,
name="Custom")
ctin = cust.addTransformInner(3, main_inputs=[0])
cust.declareOslot(0, ctin, 'main')
builder.build()
X = tf.placeholder(tf.float64, [None, 10])
cust.build_outputs(imain0=X)
def test_BuildModel1(self):
"""
Test building the simplest stochastic model possible.
"""
print("\nTest 1: Building a Model with a Stochastic Node")
builder = StaticBuilder(scope="BasicNormal")
i1 = builder.addInput(10)
in1 = builder.addTransformInner(3,
main_inputs=i1,
node_class=NormalTriLNode)
builder.build()
inn, enc = builder.nodes[i1], builder.nodes[in1]
self.assertEqual(inn._oslot_to_otensor['main'].shape.as_list()[-1],
enc._islot_to_itensor[0]['main'].shape.as_list()[-1],
"The input tensors have not been assigned correctly")
print("enc._oslot_to_otensor", enc._oslot_to_otensor)
print("enc._islot_to_itensor", enc._islot_to_itensor)
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_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)
