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Remove support for calling graph directly #270

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Jan 6, 2021
Merged

Remove support for calling graph directly #270

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c781508
Remove support for calling graph directly
jakobj Jan 5, 2021
647d32d
!fixup formatting
jakobj Jan 5, 2021
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14 changes: 0 additions & 14 deletions cgp/cartesian_graph.py
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Original file line number Diff line number Diff line change
Expand Up @@ -202,20 +202,6 @@ def determine_active_regions(self) -> List[int]:

return active_regions

def __call__(self, x: List[float]) -> List[float]:
# store values of x in input nodes
for i, xi in enumerate(x):
assert isinstance(self._nodes[i], InputNode)
self._nodes[i]._output = xi

# evaluate active nodes in order
active_nodes_by_hidden_column_idx = self._determine_active_nodes()
for hidden_column_idx in sorted(active_nodes_by_hidden_column_idx):
for node in active_nodes_by_hidden_column_idx[hidden_column_idx]:
node(x, self)

return [node._output for node in self.output_nodes]

def __getitem__(self, key: int) -> Node:
return self._nodes[key]

Expand Down
16 changes: 0 additions & 16 deletions cgp/node.py
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Expand Up @@ -57,9 +57,6 @@ def __init_subclass__(cls: Type["Node"]) -> None:
super().__init_subclass__()
register(cls)

def __call__(self, x: List[float], graph: "CartesianGraph") -> None:
raise NotImplementedError

@property
def arity(self) -> int:
return self._arity
Expand Down Expand Up @@ -210,19 +207,6 @@ def initial_value(cls, parameter_name: str) -> float:
def parameter_str(self) -> List[str]:
return self._parameter_str

def __call__(self, x: List[float], graph: "CartesianGraph") -> None:
output_str = str(self._def_output)

if len(self._parameter_names) > 0:
raise RuntimeError("can not call a node that uses parameters")

for input_name in self._input_names:
idx = self._extract_index_from_input_name(input_name)
output_str = output_str.replace(input_name, f"{graph[self._input_nodes[idx]].output}")

exec_str = f"self._output = {output_str}"
exec(exec_str)

def _replace_input_names(self, output_str: str, graph: "CartesianGraph") -> str:
for input_name in self._input_names:
idx = self._extract_index_from_input_name(input_name)
Expand Down
22 changes: 0 additions & 22 deletions test/test_cartesian_graph.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,28 +7,6 @@
from cgp.genome import ID_INPUT_NODE, ID_NON_CODING_GENE, ID_OUTPUT_NODE


def test_direct_input_output():
params = {"n_inputs": 1, "n_outputs": 1, "n_columns": 3, "n_rows": 3, "levels_back": 2}
primitives = (cgp.Add, cgp.Sub)
genome = cgp.Genome(
params["n_inputs"],
params["n_outputs"],
params["n_columns"],
params["n_rows"],
params["levels_back"],
primitives,
)
genome.randomize(np.random)

genome[-2:] = [0, ID_NON_CODING_GENE] # set inputs for output node to input node
graph = cgp.CartesianGraph(genome)

x = [2.14159]
y = graph(x)

assert x[0] == pytest.approx(y[0])


def test_to_func_simple():
primitives = (cgp.Add,)
genome = cgp.Genome(2, 1, 1, 1, 1, primitives)
Expand Down
44 changes: 16 additions & 28 deletions test/test_node.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,19 +24,16 @@ def test_inputs_are_cut_to_match_arity():
assert node.input_nodes == input_nodes[:2]


def _test_graph_call_and_to_x_compilations(
def _test_to_x_compilations(
genome,
x,
y_target,
*,
test_graph_call=True,
test_to_func=True,
test_to_numpy=True,
test_to_torch=True,
test_to_sympy=True,
):
if test_graph_call:
_test_graph_call(genome, x, y_target)
if test_to_func:
_test_to_func(genome, x, y_target)
if test_to_numpy:
Expand All @@ -47,11 +44,6 @@ def _test_graph_call_and_to_x_compilations(
_test_to_sympy(genome, x, y_target)


def _test_graph_call(genome, x, y_target):
graph = cgp.CartesianGraph(genome)
assert graph(x) == pytest.approx(y_target)


def _test_to_func(genome, x, y_target):
graph = cgp.CartesianGraph(genome)
assert graph.to_func()(x) == pytest.approx(y_target)
Expand Down Expand Up @@ -107,7 +99,7 @@ def test_add():
x = [5.0, 1.5]
y_target = [x[0] + x[1]]

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_sub():
Expand Down Expand Up @@ -141,7 +133,7 @@ def test_sub():
x = [5.0, 1.5]
y_target = [x[0] - x[1]]

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_mul():
Expand Down Expand Up @@ -175,7 +167,7 @@ def test_mul():
x = [5.0, 1.5]
y_target = [x[0] * x[1]]

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_div():
Expand Down Expand Up @@ -209,7 +201,7 @@ def test_div():
x = [5.0, 1.5]
y_target = [x[0] / x[1]]

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_pow():
Expand Down Expand Up @@ -243,7 +235,7 @@ def test_pow():
x = [5.0, 1.5]
y_target = [x[0] ** x[1]]

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_constant_float():
Expand Down Expand Up @@ -273,7 +265,7 @@ def test_constant_float():
x = [1.0, 2.0]
y_target = [1.0] # by default the output value of the ConstantFloat node is 1.0

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_parameter():
Expand All @@ -292,7 +284,7 @@ def test_parameter():
x = [1.0]
y_target = [1.0] # by default the output value of the Parameter node is 1.0

_test_graph_call_and_to_x_compilations(genome, x, y_target, test_graph_call=False)
_test_to_x_compilations(genome, x, y_target)


def test_parameter_w_custom_initial_value():
Expand All @@ -316,7 +308,7 @@ class CustomParameter(cgp.Parameter):
x = [1.0]
y_target = [initial_value]

_test_graph_call_and_to_x_compilations(genome, x, y_target, test_graph_call=False)
_test_to_x_compilations(genome, x, y_target)


def test_parameter_two_nodes():
Expand Down Expand Up @@ -353,7 +345,7 @@ def test_parameter_two_nodes():
# hence the sum of two Parameter nodes is 2.0
y_target = [2.0]

_test_graph_call_and_to_x_compilations(genome, x, y_target, test_graph_call=False)
_test_to_x_compilations(genome, x, y_target)


def test_parameter_w_random_initial_value(rng_seed):
Expand Down Expand Up @@ -486,15 +478,15 @@ def test_if_else_operator():

x_0 = [1.0, 10.0, -20.0]
y_target_0 = [10.0]
_test_graph_call_and_to_x_compilations(genome, x_0, y_target_0)
_test_to_x_compilations(genome, x_0, y_target_0)

x_1 = [0.0, 10.0, -20.0]
y_target_1 = [10.0]
_test_graph_call_and_to_x_compilations(genome, x_1, y_target_1)
_test_to_x_compilations(genome, x_1, y_target_1)

x_2 = [-1.0, 10.0, -20.0]
y_target_2 = [-20.0]
_test_graph_call_and_to_x_compilations(genome, x_2, y_target_2)
_test_to_x_compilations(genome, x_2, y_target_2)


def test_raise_broken_def_output():
Expand Down Expand Up @@ -591,7 +583,7 @@ class MyScaledAdd(cgp.node.OperatorNode):
x = [5.0, 1.5]
y_target = [2 * (x[0] + x[1])]

_test_graph_call_and_to_x_compilations(genome, x, y_target)
_test_to_x_compilations(genome, x, y_target)


def test_custom_node_with_custom_atomic_operator():
Expand Down Expand Up @@ -635,9 +627,7 @@ class MyScaledAdd(cgp.node.OperatorNode):
x = [5.0, 1.5]
y_target = [2 * (x[0] + x[1])]

_test_graph_call_and_to_x_compilations(
genome, x, y_target, test_graph_call=False, test_to_sympy=False
)
_test_to_x_compilations(genome, x, y_target, test_to_sympy=False)


def test_custom_node_with_custom_atomic_operator_with_external_library():
Expand Down Expand Up @@ -683,6 +673,4 @@ class MyScaledAdd(cgp.node.OperatorNode):
x = [5.0, 1.5]
y_target = [scipy_const.golden_ratio * (x[0] + x[1])]

_test_graph_call_and_to_x_compilations(
genome, x, y_target, test_graph_call=False, test_to_sympy=False
)
_test_to_x_compilations(genome, x, y_target, test_to_sympy=False)