runtime/test/generated/spec_V1_2/vts_V1_2/instance_normalization.model.cpp

// Generated from instance_normalization.mod.py
// DO NOT EDIT
// clang-format off
#include "GeneratedTests.h"

namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_all_inputs_as_internal() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_all_inputs_as_internal(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_all_inputs_as_internal_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_all_inputs_as_internal_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_all_inputs_as_internal() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_all_inputs_as_internal(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_all_inputs_as_internal_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_all_inputs_as_internal_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_all_inputs_as_internal() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_all_inputs_as_internal(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_all_inputs_as_internal_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_all_inputs_as_internal_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_all_inputs_as_internal() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_all_inputs_as_internal(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_all_inputs_as_internal_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_all_inputs_as_internal_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_all_inputs_as_internal() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_all_inputs_as_internal(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_all_inputs_as_internal_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 128, 63, 0, 0, 0, 0, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_all_inputs_as_internal_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_all_inputs_as_internal() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 1, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_all_inputs_as_internal(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_all_inputs_as_internal_dynamic_output_shape() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 60, 0, 0, 142, 6, 1, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_all_inputs_as_internal_dynamic_output_shape(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_all_inputs_as_internal_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_all_inputs_as_internal_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_all_inputs_as_internal_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_all_inputs_as_internal_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_all_inputs_as_internal_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_all_inputs_as_internal_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_relaxed_all_inputs_as_internal_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nhwc_relaxed_all_inputs_as_internal_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_all_inputs_as_internal_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_all_inputs_as_internal_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nhwc_float16_all_inputs_as_internal_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nhwc_float16_all_inputs_as_internal_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_all_inputs_as_internal_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_all_inputs_as_internal_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_all_inputs_as_internal_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_all_inputs_as_internal_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_all_inputs_as_internal_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_all_inputs_as_internal_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_relaxed_all_inputs_as_internal_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 4},
        },
        {
            .type = OperandType::FLOAT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 8, .length = 4},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 12, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT32,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 13, .length = 4},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 17, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 0, 0, 64, 0, 0, 32, 65, 23, 183, 209, 56, 1, 0, 0, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
        .relaxComputationFloat32toFloat16 = true,
    };
}

bool is_ignored_nchw_relaxed_all_inputs_as_internal_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {0};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 1
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_all_inputs_as_internal_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 1, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_all_inputs_as_internal_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization
namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization {

Model createTestModel_nchw_float16_all_inputs_as_internal_dynamic_output_shape_2() {
    const std::vector<Operand> operands = {
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 0, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 2, .length = 2},
        },
        {
            .type = OperandType::FLOAT16,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 4, .length = 2},
        },
        {
            .type = OperandType::BOOL,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 6, .length = 1},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {0, 0, 0, 0},
            .numberOfConsumers = 0,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_OUTPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {2, 2, 2, 2},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::MODEL_INPUT,
            .location = {.poolIndex = 0, .offset = 0, .length = 0},
        },
        {
            .type = OperandType::TENSOR_FLOAT16,
            .dimensions = {1},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 7, .length = 2},
        },
        {
            .type = OperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = 1,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = OperandLifeTime::CONSTANT_COPY,
            .location = {.poolIndex = 0, .offset = 9, .length = 4},
        }
    };

    const std::vector<Operation> operations = {
        {
            .type = OperationType::ADD,
            .inputs = {6, 7, 8},
            .outputs = {0},
        },
        {
            .type = OperationType::INSTANCE_NORMALIZATION,
            .inputs = {0, 1, 2, 3, 4},
            .outputs = {5},
        }
    };

    const std::vector<uint32_t> inputIndexes = {6};
    const std::vector<uint32_t> outputIndexes = {5};
    std::vector<uint8_t> operandValues = {
      0, 64, 0, 73, 142, 6, 1, 0, 0, 0, 0, 0, 0
    };
    const std::vector<hidl_memory> pools = {};

    return {
        .operands = operands,
        .operations = operations,
        .inputIndexes = inputIndexes,
        .outputIndexes = outputIndexes,
        .operandValues = operandValues,
        .pools = pools,
    };
}

bool is_ignored_nchw_float16_all_inputs_as_internal_dynamic_output_shape_2(int i) {
  static std::set<int> ignore = {};
  return ignore.find(i) != ignore.end();
}

} // namespace android::hardware::neuralnetworks::V1_2::generated_tests::instance_normalization