def create_structure(input_shape=[(2, ), (2, ), (2, )],
output_shape=(1, ),
*args,
**kwargs):
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
cell1 = create_cell_1(input_nodes)
network.add_cell(cell1)
cell2 = create_cell_2([cell1.output])
network.add_cell(cell2)
cell3 = Cell(input_nodes + [cell1.output] + [cell2.output])
cnode = VariableNode(name='SkipCo')
nullNode = ConstantNode(op=Tensor([]), name='None')
cnode.add_op(Connect(cell3.graph, nullNode, cnode)) # SAME
cnode.add_op(Connect(cell3.graph, input_nodes[0], cnode))
cnode.add_op(Connect(cell3.graph, input_nodes[1], cnode))
cnode.add_op(Connect(cell3.graph, input_nodes[2], cnode))
cnode.add_op(Connect(cell3.graph, cell1.output, cnode))
cnode.add_op(Connect(cell3.graph, cell2.output, cnode)) # SAME
cnode.add_op(Connect(cell3.graph, input_nodes, cnode))
cnode.add_op(Connect(cell3.graph, [input_nodes[0], input_nodes[1]], cnode))
cnode.add_op(Connect(cell3.graph, [input_nodes[1], input_nodes[2]], cnode))
cnode.add_op(Connect(cell3.graph, [input_nodes[0], input_nodes[2]], cnode))
block = Block()
block.add_node(cnode)
cell3.add_block(block)
network.add_cell(cell3)
return network
def create_struct_full_skipco(input_shape, output_shape, create_cell, num_cells):
"""
Create a SequentialStructure object.
Args:
input_shape (tuple): shape of input tensor
output_shape (tuple): shape of output tensor
create_cell (function): function that create a cell, take one argument (inputs: list(None))
num_cells (int): number of cells in the sequential structure
Return:
KerasStructure: the corresponding built structure.
"""
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
func = lambda: create_cell(input_nodes)
network.add_cell_f(func)
func = lambda x: create_cell(x)
for i in range(num_cells-1):
network.add_cell_f(func, num=None)
return network
def create_structure(input_shape=[(2,), (2,), (2,)], output_shape=(1,),
num_cell=8, *args, **kwargs):
# , output_op=AddByPadding)
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
# CELL 1
cell1 = create_cell_1(input_nodes)
network.add_cell(cell1)
# CELL Middle
inputs_skipco = [input_nodes, input_nodes[0],
input_nodes[1], input_nodes[2], cell1.output]
pred_cell = cell1
n = num_cell
for i in range(n):
cell_i = Cell(input_nodes + [cell1.output])
block1 = create_mlp_block(cell_i, pred_cell.output)
cell_i.add_block(block1)
cnode = VariableNode(name='SkipCo')
nullNode = ConstantNode(op=Tensor([]), name='None')
cnode.add_op(Connect(cell_i.graph, nullNode, cnode)) # SAME
for inpt in inputs_skipco:
cnode.add_op(Connect(cell_i.graph, inpt, cnode))
block2 = Block()
block2.add_node(cnode)
cell_i.add_block(block2)
# set_cell_output_add(cell2)
cell_i.set_outputs()
network.add_cell(cell_i)
# prep. for next iter
inputs_skipco.append(cell_i.output)
pred_cell = cell_i
# CELL LAST
cell_last = Cell([pred_cell.output])
block1 = create_mlp_block(cell_last, pred_cell.output)
cell_last.add_block(block1)
# set_cell_output_add(cell3)
cell_last.set_outputs()
network.add_cell(cell_last)
return network
def create_structure(input_shape=[(2, ), (2, ), (2, )],
output_shape=(1, ),
*args,
**kwargs):
# , output_op=AddByPadding)
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
# CELL 1
cell1 = create_cell_1(input_nodes)
network.add_cell(cell1)
# CELL 2
cell2 = Cell(input_nodes + [cell1.output])
block1 = create_mlp_block(cell2, cell1.output)
cell2.add_block(block1)
cnode = VariableNode(name='SkipCo')
nullNode = ConstantNode(op=Tensor([]), name='None')
cnode.add_op(Connect(cell2.graph, nullNode, cnode)) # SAME
cnode.add_op(Connect(cell2.graph, input_nodes[0], cnode))
cnode.add_op(Connect(cell2.graph, input_nodes[1], cnode))
cnode.add_op(Connect(cell2.graph, input_nodes[2], cnode))
cnode.add_op(Connect(cell2.graph, cell1.output, cnode))
cnode.add_op(Connect(cell2.graph, input_nodes, cnode))
cnode.add_op(Connect(cell2.graph, [input_nodes[0], input_nodes[1]], cnode))
cnode.add_op(Connect(cell2.graph, [input_nodes[1], input_nodes[2]], cnode))
cnode.add_op(Connect(cell2.graph, [input_nodes[0], input_nodes[2]], cnode))
block2 = Block()
block2.add_node(cnode)
cell2.add_block(block2)
# set_cell_output_add(cell2)
cell2.set_outputs()
network.add_cell(cell2)
# CELL 3
cell3 = Cell([cell2.output])
block1 = create_mlp_block(cell3, cell2.output)
cell3.add_block(block1)
# set_cell_output_add(cell3)
cell3.set_outputs()
network.add_cell(cell3)
return network
def create_structure(input_shape=[(2,), (2,), (2,)], output_shape=(1,), *args, **kwargs):
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
func = lambda: create_cell_1(input_nodes)
network.add_cell_f(func)
func = lambda x: create_cell_2(x)
network.add_cell_f(func, num=1)
return network
def create_structure(input_shape=[(2, ), (2, ), (2, )],
output_shape=(1, ),
*args,
**kwargs):
# , output_op=AddByPadding)
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
# CELL 1
cell1 = create_cell_1(input_nodes)
network.add_cell(cell1)
# CELL 2
cell2 = Cell([cell1.output])
block1 = create_mlp_block(cell2, cell1.output)
cell2.add_block(block1)
cell2.set_outputs()
network.add_cell(cell2)
return network
def create_seq_struct(input_shape, output_shape, create_cell, num_cells):
"""
Create a KerasStructure object.
Args:
input_tensor (tensor): a tensorflow tensor object
create_cell (function): function that create a cell, take one argument (inputs: list(None))
num_cells (int): number of cells in the sequential structure
Return:
KerasStructure: the corresponding built structure.
"""
network = KerasStructure(input_shape, output_shape)
input_nodes = network.input_nodes
func = lambda: create_cell(input_nodes)
network.add_cell_f(func)
func = lambda x: create_cell(x)
for _ in range(num_cells-1):
network.add_cell_f(func, num=1)
return network