blob: cb1615b4ed81c2c4167fc6211b5673d4fe1c67a4 [file] [log] [blame]
// clang-format off
// Generated file (from: batch_to_space_v1_2.mod.py). Do not edit
void CreateModel_nhwc(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type1(Type::TENSOR_FLOAT32, {4, 1, 1, 2});
OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op1 = model->addOperand(&type1);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type2);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
inline bool is_ignored_nhwc(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_relaxed(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type1(Type::TENSOR_FLOAT32, {4, 1, 1, 2});
OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op1 = model->addOperand(&type1);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type2);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
// Phase 4: set relaxed execution
model->relaxComputationFloat32toFloat16(true);
assert(model->isValid());
}
inline bool is_ignored_nhwc_relaxed(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_float16(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type3(Type::TENSOR_INT32, {2});
OperandType type6(Type::TENSOR_FLOAT16, {4, 1, 1, 2});
OperandType type7(Type::TENSOR_FLOAT16, {1, 2, 2, 2});
// Phase 1, operands
auto op1 = model->addOperand(&type6);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type7);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
inline bool is_ignored_nhwc_float16(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_quant8(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type3(Type::TENSOR_INT32, {2});
OperandType type8(Type::TENSOR_QUANT8_ASYMM, {4, 1, 1, 2}, 0.1f, 0);
OperandType type9(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 2}, 0.1f, 0);
// Phase 1, operands
auto op1 = model->addOperand(&type8);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type9);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
inline bool is_ignored_nhwc_quant8(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type10(Type::TENSOR_FLOAT32, {4, 2, 1, 1});
OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op1 = model->addOperand(&type10);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type2);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
inline bool is_ignored_nchw(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_relaxed(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type10(Type::TENSOR_FLOAT32, {4, 2, 1, 1});
OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op1 = model->addOperand(&type10);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type2);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
// Phase 4: set relaxed execution
model->relaxComputationFloat32toFloat16(true);
assert(model->isValid());
}
inline bool is_ignored_nchw_relaxed(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_float16(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type11(Type::TENSOR_FLOAT16, {4, 2, 1, 1});
OperandType type3(Type::TENSOR_INT32, {2});
OperandType type7(Type::TENSOR_FLOAT16, {1, 2, 2, 2});
// Phase 1, operands
auto op1 = model->addOperand(&type11);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type7);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
inline bool is_ignored_nchw_float16(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_quant8(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type12(Type::TENSOR_QUANT8_ASYMM, {4, 2, 1, 1}, 0.1f, 0);
OperandType type3(Type::TENSOR_INT32, {2});
OperandType type9(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 2}, 0.1f, 0);
// Phase 1, operands
auto op1 = model->addOperand(&type12);
auto param = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op4 = model->addOperand(&type9);
// Phase 2, operations
static int32_t param_init[] = {2, 2};
model->setOperandValue(param, param_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op1, param, layout}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
inline bool is_ignored_nchw_quant8(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type3(Type::TENSOR_INT32, {2});
OperandType type4(Type::TENSOR_FLOAT32, {4, 2, 2, 1});
OperandType type5(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
// Phase 1, operands
auto op11 = model->addOperand(&type4);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type5);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
assert(model->isValid());
}
inline bool is_ignored_nhwc_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_relaxed_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type3(Type::TENSOR_INT32, {2});
OperandType type4(Type::TENSOR_FLOAT32, {4, 2, 2, 1});
OperandType type5(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
// Phase 1, operands
auto op11 = model->addOperand(&type4);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type5);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
// Phase 4: set relaxed execution
model->relaxComputationFloat32toFloat16(true);
assert(model->isValid());
}
inline bool is_ignored_nhwc_relaxed_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_float16_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type13(Type::TENSOR_FLOAT16, {4, 2, 2, 1});
OperandType type14(Type::TENSOR_FLOAT16, {1, 4, 4, 1});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op11 = model->addOperand(&type13);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type14);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
assert(model->isValid());
}
inline bool is_ignored_nhwc_float16_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nhwc_quant8_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type15(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 0.5f, 128);
OperandType type16(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 0.5f, 128);
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op11 = model->addOperand(&type15);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type16);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {false};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
assert(model->isValid());
}
inline bool is_ignored_nhwc_quant8_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type17(Type::TENSOR_FLOAT32, {4, 1, 2, 2});
OperandType type18(Type::TENSOR_FLOAT32, {1, 1, 4, 4});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op11 = model->addOperand(&type17);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type18);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
assert(model->isValid());
}
inline bool is_ignored_nchw_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_relaxed_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type17(Type::TENSOR_FLOAT32, {4, 1, 2, 2});
OperandType type18(Type::TENSOR_FLOAT32, {1, 1, 4, 4});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op11 = model->addOperand(&type17);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type18);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
// Phase 4: set relaxed execution
model->relaxComputationFloat32toFloat16(true);
assert(model->isValid());
}
inline bool is_ignored_nchw_relaxed_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_float16_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type19(Type::TENSOR_FLOAT16, {4, 1, 2, 2});
OperandType type20(Type::TENSOR_FLOAT16, {1, 1, 4, 4});
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op11 = model->addOperand(&type19);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type20);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
assert(model->isValid());
}
inline bool is_ignored_nchw_float16_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
void CreateModel_nchw_quant8_2(Model *model) {
OperandType type0(Type::BOOL, {});
OperandType type21(Type::TENSOR_QUANT8_ASYMM, {4, 1, 2, 2}, 0.5f, 128);
OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 4, 4}, 0.5f, 128);
OperandType type3(Type::TENSOR_INT32, {2});
// Phase 1, operands
auto op11 = model->addOperand(&type21);
auto param1 = model->addOperand(&type3);
auto layout = model->addOperand(&type0);
auto op41 = model->addOperand(&type22);
// Phase 2, operations
static int32_t param1_init[] = {2, 2};
model->setOperandValue(param1, param1_init, sizeof(int32_t) * 2);
static bool layout_init[] = {true};
model->setOperandValue(layout, layout_init, sizeof(bool) * 1);
model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {op11, param1, layout}, {op41});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op11},
{op41});
assert(model->isValid());
}
inline bool is_ignored_nchw_quant8_2(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}