diff --git a/aidge_backend_cpu/unit_tests/test_recipies.py b/aidge_backend_cpu/unit_tests/test_recipies.py
index 60949adf245f4f4a7ed316879fb307131f70739a..841c15590e9dac7596958b8392c99948978723c5 100644
--- a/aidge_backend_cpu/unit_tests/test_recipies.py
+++ b/aidge_backend_cpu/unit_tests/test_recipies.py
@@ -49,24 +49,24 @@ class test_recipies(unittest.TestCase):
np_shift = np.array([0.05]).astype(np.float32)
np_mean = np.array([0.05]).astype(np.float32)
np_var = np.array([0.05]).astype(np.float32)
- conv.input(1)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_weights))
- conv.input(2)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_bias))
- bn.input(1)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_scale))
- bn.input(2)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_shift))
- bn.input(3)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_mean))
- bn.input(4)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_var))
+ conv.input(1)[0].get_operator().set_output(0, aidge_core.Tensor(np_weights))
+ conv.input(2)[0].get_operator().set_output(0, aidge_core.Tensor(np_bias))
+ bn.input(1)[0].get_operator().set_output(0, aidge_core.Tensor(np_scale))
+ bn.input(2)[0].get_operator().set_output(0, aidge_core.Tensor(np_shift))
+ bn.input(3)[0].get_operator().set_output(0, aidge_core.Tensor(np_mean))
+ bn.input(4)[0].get_operator().set_output(0, aidge_core.Tensor(np_var))
scheduler0 = aidge_core.SequentialScheduler(graph_view)
scheduler0.forward()
for outNode in graph_view.get_output_nodes():
- output_aidge0 = outNode.get_operator().output(0)
+ output_aidge0 = outNode.get_operator().get_output(0)
aidge_core.fuse_batchnorm(graph_view)
scheduler1 = aidge_core.SequentialScheduler(graph_view)
scheduler1.forward()
for outNode in graph_view.get_output_nodes():
- output_aidge1 = outNode.get_operator().output(0)
+ output_aidge1 = outNode.get_operator().get_output(0)
self.assertTrue(aidge_core.approx_eq(output_aidge0, output_aidge1, 0.000001, 0.0001))
diff --git a/aidge_backend_cpu/unit_tests/test_scheduler.py b/aidge_backend_cpu/unit_tests/test_scheduler.py
index 3449ff513ef618e24788419c835b7277a1e751f1..2f174efed32fc814010ff61cd42c1bae1105674e 100644
--- a/aidge_backend_cpu/unit_tests/test_scheduler.py
+++ b/aidge_backend_cpu/unit_tests/test_scheduler.py
@@ -22,30 +22,30 @@ class test_scheduler(unittest.TestCase):
gv.add(relu)
gv.add(input_node)
+ input_node.add_child(relu)
+
gv.set_datatype(aidge_core.DataType.Int32)
gv.set_backend("cpu")
- input_node.add_child(relu)
-
scheduler = aidge_core.SequentialScheduler(gv)
scheduler.forward()
- out_tensor = relu.get_operator().output(0)
+ out_tensor = relu.get_operator().get_output(0)
expected_out = [0,0,0,0,1,2]
for i in range(len(expected_out)):
self.assertEqual(expected_out[i], out_tensor[i])
def test_sequential_scheduling(self):
- input_data = np.array([]).astype(np.float32)
+ input_data = np.array([0]).astype(np.float32)
input_tensor = aidge_core.Tensor(input_data)
input_node = aidge_core.Producer(input_tensor, "X")
graph_view = aidge_core.sequential([
- aidge_core.FC(50, name='0'),
- aidge_core.FC(50, name='1'),
- aidge_core.FC(10, name='2'),
+ aidge_core.FC(1, 50, name='0'),
+ aidge_core.FC(50, 50, name='1'),
+ aidge_core.FC(50, 10, name='2'),
])
EXPECTED_SCHEDULE = ['0', '1', '2']
@@ -64,14 +64,14 @@ class test_scheduler(unittest.TestCase):
def test_parallel_scheduling(self):
- input_data = np.array([]).astype(np.float32)
+ input_data = np.array([0]).astype(np.float32)
input_tensor = aidge_core.Tensor(input_data)
input_node = aidge_core.Producer(input_tensor, "X")
graph_view = aidge_core.sequential([
- aidge_core.FC(50, name='0'),
- aidge_core.parallel([aidge_core.FC(50, name='1'), aidge_core.FC(50, name='3')]),
- aidge_core.Add(name='2'),
+ aidge_core.FC(1, 50, name='0'),
+ aidge_core.parallel([aidge_core.FC(50, 50, name='1'), aidge_core.FC(50, 50, name='3')]),
+ aidge_core.Add(2, name='2'),
])
EXPECTED_SCHEDULE = [['0', '1', '3', '2'], ['0', '3', '1', '2']] # Both scheduling are valid !
diff --git a/unit_tests/scheduler/Test_Scheduler.cpp b/unit_tests/scheduler/Test_Scheduler.cpp
index 1f6c489e53d9bfbb69fbce7795912cc4e333adc5..8ea8e726f286035a1059a317471b893ce4639251 100644
--- a/unit_tests/scheduler/Test_Scheduler.cpp
+++ b/unit_tests/scheduler/Test_Scheduler.cpp
@@ -50,13 +50,11 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
Conv(1, 3, {3, 3}, "conv1"),
Conv(3, 4, {1, 1}, "conv2"),
Conv(4, 3, {1, 1}, "conv3"),
- FC(5, false, "fc")});
- g->setDataType(Aidge::DataType::Int32);
- g->setBackend("cpu");
+ FC(27, 5, false, "fc")});
- g->getNode("conv1")->getOperator()->input(0) = *inputTensor;
- g->getNode("conv1")->getOperator()->input(1) = *weight1;
- g->getNode("conv1")->getOperator()->input(2) = *bias1;
+ g->getNode("conv1")->getOperator()->setInput(0, inputTensor);
+ g->getNode("conv1")->getOperator()->setInput(1, weight1);
+ g->getNode("conv1")->getOperator()->setInput(2, bias1);
std::shared_ptr<Tensor> weight2 =
std::make_shared<Tensor>(Array4D<int, 4, 3, 1, 1>{{{{{1}}, {{2}}, {{3}}},
@@ -64,8 +62,8 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
{{{7}}, {{8}}, {{9}}},
{{{10}}, {{11}}, {{12}}}}});
std::shared_ptr<Tensor> bias2 = std::make_shared<Tensor>(Array1D<int, 4>{{1, 2, 3, 4}});
- g->getNode("conv2")->getOperator()->input(1) = *weight2;
- g->getNode("conv2")->getOperator()->input(2) = *bias2;
+ g->getNode("conv2")->getOperator()->setInput(1, weight2);
+ g->getNode("conv2")->getOperator()->setInput(2, bias2);
// *(g->getNode("conv2")->getOperator()->input(1, weight2);
std::shared_ptr<Tensor> weight3 = std::make_shared<Tensor>(
@@ -73,8 +71,8 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
{{{5}}, {{6}}, {{7}}, {{8}}},
{{{9}}, {{10}}, {{11}}, {{12}}}}});
std::shared_ptr<Tensor> bias3 = std::make_shared<Tensor>(Array1D<int, 3>{{1, 2, 3}});
- g->getNode("conv3")->getOperator()->input(1) = *weight3;
- g->getNode("conv3")->getOperator()->input(2) = *bias3;
+ g->getNode("conv3")->getOperator()->setInput(1, weight3);
+ g->getNode("conv3")->getOperator()->setInput(2, bias3);
std::shared_ptr<Tensor> weightfc = std::make_shared<Tensor>(
Array2D<int, 5, 27>{{{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
@@ -88,10 +86,12 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
{4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2,
3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}}});
std::shared_ptr<Tensor> biasfc = std::make_shared<Tensor>(Array1D<int, 5>{{1, 2, 3, 4, 5}});
- g->getNode("fc")->getOperator()->input(1) = *weightfc;
- g->getNode("fc")->getOperator()->input(2) = *biasfc;
+ g->getNode("fc")->getOperator()->setInput(1, weightfc);
+ g->getNode("fc")->getOperator()->setInput(2, biasfc);
// input->addChild(g);
+ g->setDataType(Aidge::DataType::Int32);
+ g->setBackend("cpu");
g->forwardDims();
SequentialScheduler scheduler(g);
REQUIRE_NOTHROW(scheduler.forward());
@@ -126,17 +126,17 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
Tensor expectedOutput4 = Array2D<int, 2, 5>{
{{205050376, 198925904, 181355097, 196978090, 238868348},
{598467376, 561797804, 560823897, 593043790, 698672948}}};
- Tensor other1 = g->getNode("conv1")->getOperator()->output(0);
- bool equal1 = (other1 == *expectedOutput1);
+ std::shared_ptr<Tensor> other1 = std::static_pointer_cast<OperatorTensor>(g->getNode("conv1")->getOperator())->getOutput(0);
+ bool equal1 = (*other1 == *expectedOutput1);
REQUIRE(equal1);
- Tensor other2 = g->getNode("conv2")->getOperator()->output(0);
- bool equal2 = (other2 == *expectedOutput2);
+ std::shared_ptr<Tensor> other2 = std::static_pointer_cast<OperatorTensor>(g->getNode("conv2")->getOperator())->getOutput(0);
+ bool equal2 = (*other2 == *expectedOutput2);
REQUIRE(equal2);
- Tensor other3 = g->getNode("conv3")->getOperator()->output(0);
- bool equal3 = (other3 == *expectedOutput3);
+ std::shared_ptr<Tensor> other3 = std::static_pointer_cast<OperatorTensor>(g->getNode("conv3")->getOperator())->getOutput(0);
+ bool equal3 = (*other3 == *expectedOutput3);
REQUIRE(equal3);
- Tensor other4 = g->getNode("fc")->getOperator()->output(0);
- bool equal4 = (other4 == expectedOutput4);
+ std::shared_ptr<Tensor> other4 = std::static_pointer_cast<OperatorTensor>(g->getNode("fc")->getOperator())->getOutput(0);
+ bool equal4 = (*other4 == expectedOutput4);
REQUIRE(equal4);
}
@@ -149,34 +149,32 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
Conv(3, 3, {1, 1}, "conv1.3")}),
Add(3, "add1"),
Conv(3, 2, {1, 1}, "conv2"),
- FC(5, false, "out")});
- g->setBackend("cpu");
- g->setDataType(Aidge::DataType::Int32);
+ FC(18, 5, false, "out")});
- g->getNode("inputConv")->getOperator()->input(0) = *inputTensor;
- g->getNode("inputConv")->getOperator()->input(1) = *weight1;
- g->getNode("inputConv")->getOperator()->input(2) = *bias1;
+ g->getNode("inputConv")->getOperator()->setInput(0, inputTensor);
+ g->getNode("inputConv")->getOperator()->setInput(1, weight1);
+ g->getNode("inputConv")->getOperator()->setInput(2, bias1);
std::shared_ptr<Tensor> conv11Weight = std::make_shared<Tensor>(Array4D<int, 3, 3, 1, 1>{
{{{{1}}, {{2}}, {{3}}}, {{{4}}, {{5}}, {{6}}}, {{{7}}, {{8}}, {{9}}}}});
- g->getNode("conv1.1")->getOperator()->input(1) = *conv11Weight;
- g->getNode("conv1.1")->getOperator()->input(2) = *bias1;
+ g->getNode("conv1.1")->getOperator()->setInput(1, conv11Weight);
+ g->getNode("conv1.1")->getOperator()->setInput(2, bias1);
std::shared_ptr<Tensor> conv12Weight = std::make_shared<Tensor>(Array4D<int, 3, 3, 1, 1>{
{{{{11}}, {{12}}, {{13}}}, {{{14}}, {{15}}, {{16}}}, {{{17}}, {{18}}, {{19}}}}});
- g->getNode("conv1.2")->getOperator()->input(1) = *conv12Weight;
- g->getNode("conv1.2")->getOperator()->input(2) = *bias1;
+ g->getNode("conv1.2")->getOperator()->setInput(1, conv12Weight);
+ g->getNode("conv1.2")->getOperator()->setInput(2, bias1);
std::shared_ptr<Tensor> conv13Weight = std::make_shared<Tensor>(Array4D<int, 3, 3, 1, 1>{
{{{{21}}, {{22}}, {{23}}}, {{{24}}, {{25}}, {{26}}}, {{{27}}, {{28}}, {{29}}}}});
- g->getNode("conv1.3")->getOperator()->input(1) = *conv13Weight;
- g->getNode("conv1.3")->getOperator()->input(2) = *bias1;
+ g->getNode("conv1.3")->getOperator()->setInput(1, conv13Weight);
+ g->getNode("conv1.3")->getOperator()->setInput(2, bias1);
std::shared_ptr<Tensor> conv2Weight = std::make_shared<Tensor>(
Array4D<int, 2, 3, 1, 1>{{{{{1}}, {{2}}, {{3}}}, {{{4}}, {{5}}, {{6}}}}});
std::shared_ptr<Tensor> bias2 = std::make_shared<Tensor>(Array1D<int, 2>{{1, 2}});
- g->getNode("conv2")->getOperator()->input(1) = *conv2Weight;
- g->getNode("conv2")->getOperator()->input(2) = *bias2;
+ g->getNode("conv2")->getOperator()->setInput(1, conv2Weight);
+ g->getNode("conv2")->getOperator()->setInput(2, bias2);
std::shared_ptr<Tensor> fcWeight = std::make_shared<Tensor>(
Array2D<int, 5, 18>{{{1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3},
@@ -185,19 +183,21 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
{5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2},
{3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5}}});
std::shared_ptr<Tensor> fcBias = std::make_shared<Tensor>(Array1D<int, 5>{{1, 2, 3, 4, 5}});
- g->getNode("out")->getOperator()->input(1) = *fcWeight;
- g->getNode("out")->getOperator()->input(2) = *fcBias;
+ g->getNode("out")->getOperator()->setInput(1, fcWeight);
+ g->getNode("out")->getOperator()->setInput(2, fcBias);
std::shared_ptr<Tensor> expectedOutput = std::make_shared<Tensor>(
Array2D<int, 2, 5>{{{124324368, 130692907, 133325056, 125044620, 142843879},
{369195468, 394615207, 382643056, 379441320, 416291779}}});
+ g->setBackend("cpu");
+ g->setDataType(Aidge::DataType::Int32);
g->forwardDims();
SequentialScheduler scheduler(g);
REQUIRE_NOTHROW(scheduler.forward());
scheduler.saveSchedulingDiagram("schedulingSequential");
std::shared_ptr<Tensor> result =
- std::static_pointer_cast<Tensor>(g->getNode("out")->getOperator()->getOutput(0));
+ std::static_pointer_cast<Tensor>(g->getNode("out")->getOperator()->getRawOutput(0));
bool equal = (*result == *expectedOutput);
REQUIRE(equal);
}