summaryrefslogtreecommitdiff
path: root/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp')
-rw-r--r--runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp32
1 files changed, 32 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp
new file mode 100644
index 000000000..04c4efece
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: fully_connected_float_1_nnfw.mod.py). Do not edit
+void CreateModel(Model *model) {
+ OperandType type4(Type::INT32, {});
+ OperandType type3(Type::TENSOR_FLOAT32, {1, 1});
+ OperandType type1(Type::TENSOR_FLOAT32, {1, 24});
+ OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 4, 2});
+ OperandType type2(Type::TENSOR_FLOAT32, {1});
+ // Phase 1, operands
+ auto op1 = model->addOperand(&type0);
+ auto op2 = model->addOperand(&type1);
+ auto b0 = model->addOperand(&type2);
+ auto op3 = model->addOperand(&type3);
+ auto act_relu = model->addOperand(&type4);
+ // Phase 2, operations
+ static float op2_init[] = {-0.25449711f, 0.0f, -2.1247749f, 0.0f, -1.143796f, 0.0f, -1.0299346f, 0.0f, -2.2373879f, 0.0f, -0.083096743f, 0.0f, -1.3230739f, 0.0f, 0.15294921f, 0.0f, -0.53045893f, 0.0f, -0.46075189f, 0.0f, -1.4482396f, 0.0f, -1.609534f, 0.0f};
+ model->setOperandValue(op2, op2_init, sizeof(float) * 24);
+ static float b0_init[] = {0.70098364f};
+ model->setOperandValue(b0, b0_init, sizeof(float) * 1);
+ static int32_t act_relu_init[] = {0};
+ model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1);
+ model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act_relu}, {op3});
+ // Phase 3, inputs and outputs
+ model->identifyInputsAndOutputs(
+ {op1},
+ {op3});
+ assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+ static std::set<int> ignore = {};
+ return ignore.find(i) != ignore.end();
+}