diff options
Diffstat (limited to 'runtimes/tests/neural_networks_test/generated/models')
91 files changed, 2779 insertions, 12 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp new file mode 100644 index 000000000..6c6d5900c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp new file mode 100644 index 000000000..e074783e5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp new file mode 100644 index 000000000..892274029 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/cast_ex_float32_to_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/cast_ex_float32_to_int32.model.cpp new file mode 100644 index 000000000..d28671b22 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/cast_ex_float32_to_int32.model.cpp @@ -0,0 +1,20 @@ +// Generated file (from: cast_ex_float32_to_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2, 3}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + // Phase 2, operations + model->addOperationEx(ANEURALNETWORKS_CAST_EX, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/cast_ex_int32_to_float32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/cast_ex_int32_to_float32.model.cpp new file mode 100644 index 000000000..af435bff8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/cast_ex_int32_to_float32.model.cpp @@ -0,0 +1,20 @@ +// Generated file (from: cast_ex_int32_to_float32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type0(Type::TENSOR_INT32, {2, 3}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + // Phase 2, operations + model->addOperationEx(ANEURALNETWORKS_CAST_EX, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/concat_float_4D_axis3_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/concat_float_4D_axis3_1_nnfw.model.cpp new file mode 100644 index 000000000..82ef41dc9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/concat_float_4D_axis3_1_nnfw.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: concat_float_4D_axis3_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 3, 6}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto op3 = model->addOperand(&type0); + auto axis0 = model->addOperand(&type1); + auto result = model->addOperand(&type2); + // Phase 2, operations + static int32_t axis0_init[] = {3}; + model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, op2, op3, axis0}, {result}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2, op3}, + {result}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp b/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp index 19de70509..38e56eaad 100644 --- a/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp @@ -1,19 +1,18 @@ // Generated file (from: depthwise_conv2d_float_large_2_weights_as_inputs.mod.py). Do not edit void CreateModel(Model *model) { - OperandType type3(Type::INT32, {}); - OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 4}); - OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3}); - OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4}); - OperandType type2(Type::TENSOR_FLOAT32, {4}); + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 4}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 4}); + OperandType type1(Type::TENSOR_FLOAT32, {4}); // Phase 1, operands auto op1 = model->addOperand(&type0); - auto op2 = model->addOperand(&type1); - auto op3 = model->addOperand(&type2); - auto pad0 = model->addOperand(&type3); - auto act = model->addOperand(&type3); - auto stride = model->addOperand(&type3); - auto channelMultiplier = model->addOperand(&type3); - auto op4 = model->addOperand(&type4); + auto op2 = model->addOperand(&type0); + auto op3 = model->addOperand(&type1); + auto pad0 = model->addOperand(&type2); + auto act = model->addOperand(&type2); + auto stride = model->addOperand(&type2); + auto channelMultiplier = model->addOperand(&type2); + auto op4 = model->addOperand(&type3); // Phase 2, operations static int32_t pad0_init[] = {0}; model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); diff --git a/runtimes/tests/neural_networks_test/generated/models/div.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div.model.cpp new file mode 100644 index 000000000..31213de0f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: div.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/div_.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div_.model.cpp new file mode 100644 index 000000000..137a8b90b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div_.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: div_.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp new file mode 100644 index 000000000..e6f442d09 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: div_broadcast_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type1(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_2d_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_2d_nnfw.model.cpp new file mode 100644 index 000000000..0234e403f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_2d_nnfw.model.cpp @@ -0,0 +1,21 @@ +// Generated file (from: embedding_lookup_2d_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_FLOAT32, {3, 2}); + OperandType type0(Type::TENSOR_INT32, {3}); + // Phase 1, operands + auto index = model->addOperand(&type0); + auto value = model->addOperand(&type1); + auto output = model->addOperand(&type1); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_EMBEDDING_LOOKUP, {index, value}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {index, value}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_4d_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_4d_nnfw.model.cpp new file mode 100644 index 000000000..2acd291ae --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_4d_nnfw.model.cpp @@ -0,0 +1,22 @@ +// Generated file (from: embedding_lookup_4d_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {3, 2, 4, 2}); + OperandType type0(Type::TENSOR_INT32, {3}); + OperandType type1(Type::TENSOR_INT32, {5, 2, 4, 2}); + // Phase 1, operands + auto index = model->addOperand(&type0); + auto value = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_EMBEDDING_LOOKUP, {index, value}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {index, value}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/floor_.model.cpp b/runtimes/tests/neural_networks_test/generated/models/floor_.model.cpp new file mode 100644 index 000000000..b54e9fc8f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/floor_.model.cpp @@ -0,0 +1,19 @@ +// Generated file (from: floor_.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_FLOOR, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} 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(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp new file mode 100644 index 000000000..15275251f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type1(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {1}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); + // 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 = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {2.0f, 4.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 2); + static float b0_init[] = {1.0f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 1); + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {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(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp new file mode 100644 index 000000000..aa645d966 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_4d_simple.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_FLOAT32, {3, 10}); + OperandType type2(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 5, 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 = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 30); + static float b0_init[] = {1.0f, 2.0f, 3.0f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 3); + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {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(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_1D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_1D_float.model.cpp new file mode 100644 index 000000000..8ad160990 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_1D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_1D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_1D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_1D_int32.model.cpp new file mode 100644 index 000000000..ae7fa6685 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_1D_int32.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: gather_1D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_1D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_1D_quant8.model.cpp new file mode 100644 index 000000000..4984c167b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_1D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_1D_uint8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_2D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_2D_float.model.cpp new file mode 100644 index 000000000..3d80c4496 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_2D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_2D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2,4}); + OperandType type0(Type::TENSOR_FLOAT32, {3,4}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_2D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_2D_int32.model.cpp new file mode 100644 index 000000000..50411d5a7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_2D_int32.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_2D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_INT32, {2,4}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_INT32, {3,4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_2D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_2D_quant8.model.cpp new file mode 100644 index 000000000..d7aa0aba7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_2D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_2D_uint8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2,4}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3,4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp new file mode 100644 index 000000000..7d26f9fa8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 2, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp new file mode 100644 index 000000000..e14f6888a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_axis01_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp new file mode 100644 index 000000000..26afa5aa5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_axis01_2_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 2, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp new file mode 100644 index 000000000..7a3ce25a5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 0, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp new file mode 100644 index 000000000..9838db48b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp new file mode 100644 index 000000000..bbc6c101e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {4}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 0.8, 5); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 3, 2}, 0.8, 5); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 0, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp new file mode 100644 index 000000000..dec9d81ca --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3, 1}, 0.8, 5); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 3, 2}, 0.8, 5); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp new file mode 100644 index 000000000..b8a4120f1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: mul_broadcast_3D_1D_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3, 1, 4}); + OperandType type1(Type::TENSOR_FLOAT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp new file mode 100644 index 000000000..c5d215fb8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: mul_broadcast_3D_1D_2_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3, 2, 4}); + OperandType type1(Type::TENSOR_FLOAT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp b/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp new file mode 100644 index 000000000..97e173e21 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: pad.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type1(Type::TENSOR_INT32, {4, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t op2_init[] = {0, 0, 1, 1, 1, 1, 0, 0}; + model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); + model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {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(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp new file mode 100644 index 000000000..61ae0b766 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: pad_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 7, 1}); + OperandType type1(Type::TENSOR_INT32, {4, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t op2_init[] = {0, 0, 0, 2, 1, 3, 0, 0}; + model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); + model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {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(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp new file mode 100644 index 000000000..4064c94a9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + OperandType type3(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp new file mode 100644 index 000000000..f4dfab99f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {4, 2, 2, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp new file mode 100644 index 000000000..44dee00ce --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 5, 2, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 2, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 0, 2, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp new file mode 100644 index 000000000..f2fa99042 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 2, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 4, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 1, 2, 4}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp new file mode 100644 index 000000000..cfd56c2e7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp new file mode 100644 index 000000000..8ab61a116 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 5, 2, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {6, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 0, 2, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp new file mode 100644 index 000000000..7ee388441 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 4, 2, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {6, 2, 4, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 1, 2, 4}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp new file mode 100644 index 000000000..806a10c61 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {4, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {1, 2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_2D_float_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_2D_float_1_nnfw.model.cpp new file mode 100644 index 000000000..4d6621e21 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_2D_float_1_nnfw.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_2D_float_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {4, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {1}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp new file mode 100644 index 000000000..2277e38e6 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 24, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 24}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp new file mode 100644 index 000000000..f122d43f5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 24, 1}, 1.0, 0); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 24}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp new file mode 100644 index 000000000..5f1b875c2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, 2}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_1.model.cpp new file mode 100644 index 000000000..1385693c8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_10.model.cpp new file mode 100644 index 000000000..5da568959 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_2.model.cpp new file mode 100644 index 000000000..84c3fe65d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_3.model.cpp new file mode 100644 index 000000000..a6067409d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_4.model.cpp new file mode 100644 index 000000000..497ed4ba7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_5.model.cpp new file mode 100644 index 000000000..568e03013 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_6.model.cpp new file mode 100644 index 000000000..8333a4334 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_7.model.cpp new file mode 100644 index 000000000..34f2d13fa --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_ex_float_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_8.model.cpp new file mode 100644 index 000000000..6027abb1c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_9.model.cpp new file mode 100644 index 000000000..de18b9d76 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp new file mode 100644 index 000000000..fcd2f6dac --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp new file mode 100644 index 000000000..1463f13ab --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp new file mode 100644 index 000000000..2197b502a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_11.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {1, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {1}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp new file mode 100644 index 000000000..47179ca53 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp new file mode 100644 index 000000000..113c775a3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp new file mode 100644 index 000000000..af5ffa891 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp new file mode 100644 index 000000000..a0280d3a8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp new file mode 100644 index 000000000..cb40c8527 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp new file mode 100644 index 000000000..1580128a1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_float_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp new file mode 100644 index 000000000..0dd388435 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp new file mode 100644 index 000000000..22e0e7028 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp new file mode 100644 index 000000000..a6eec78a4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_qaunt8_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp new file mode 100644 index 000000000..170dc7e0f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_qaunt8_11.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {1, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {1}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp new file mode 100644 index 000000000..7f8e602eb --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp new file mode 100644 index 000000000..e6042147e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp new file mode 100644 index 000000000..2cc75a461 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp new file mode 100644 index 000000000..2fe2277d6 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp new file mode 100644 index 000000000..1ed3ed107 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp new file mode 100644 index 000000000..73da2fc3a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp new file mode 100644 index 000000000..089388bf2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_quant8_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp new file mode 100644 index 000000000..ef55fc15f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp new file mode 100644 index 000000000..37bb2898e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/sub.model.cpp b/runtimes/tests/neural_networks_test/generated/models/sub.model.cpp new file mode 100644 index 000000000..40a0247c8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/sub.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: sub.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp new file mode 100644 index 000000000..cf1f61a85 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: sub_broadcast_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type1(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/tanh_.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tanh_.model.cpp new file mode 100644 index 000000000..c221ea627 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tanh_.model.cpp @@ -0,0 +1,19 @@ +// Generated file (from: tanh_.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_TANH, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_float.model.cpp new file mode 100644 index 000000000..7d365de9e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_float.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: tensorflowmax_ex_2D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3, 4}); + OperandType type2(Type::TENSOR_FLOAT32, {3}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t axis_init[] = {1}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TENSORFLOW_MAX_EX, {input, axis}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_int32.model.cpp new file mode 100644 index 000000000..efb5923ae --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_int32.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: tensorflowmax_ex_2D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_INT32, {3, 4}); + OperandType type2(Type::TENSOR_INT32, {3}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t axis_init[] = {1}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TENSORFLOW_MAX_EX, {input, axis}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_float.model.cpp new file mode 100644 index 000000000..23168320c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_1D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type3(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_int32.model.cpp new file mode 100644 index 000000000..5d11fed89 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_int32.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: topk_v2_1D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_quant8.model.cpp new file mode 100644 index 000000000..ff60c1d74 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_1D_quant8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type3(Type::TENSOR_INT32, {2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_float.model.cpp new file mode 100644 index 000000000..17097cd11 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_2D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_FLOAT32, {3,2}); + OperandType type0(Type::TENSOR_FLOAT32, {3,4}); + OperandType type3(Type::TENSOR_INT32, {3,2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_int32.model.cpp new file mode 100644 index 000000000..36e137e46 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_int32.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: topk_v2_2D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_INT32, {3,2}); + OperandType type0(Type::TENSOR_INT32, {3,4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_quant8.model.cpp new file mode 100644 index 000000000..a0ffc8946 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_2D_quant8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type3(Type::TENSOR_INT32, {3,2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {3,2}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3,4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp new file mode 100644 index 000000000..e4c741456 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp @@ -0,0 +1,23 @@ +// Generated file (from: transpose.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t perms_init[] = {0, 2, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp new file mode 100644 index 000000000..f6d0d08e3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: transpose_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {2, 3, 4, 5}); + OperandType type2(Type::TENSOR_FLOAT32, {4, 2, 3, 5}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t perms_init[] = {2, 0, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp new file mode 100644 index 000000000..808ad2b38 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: transpose_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {4}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3, 4, 5}, 1.0, 0); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {4, 2, 3, 5}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t perms_init[] = {2, 0, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} |