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// clang-format off
// Generated file (from: lstm_float.mod.py). Do not edit
// clang-format off
// Generated file (from: lstm_float.mod.py). Do not edit
// clang-format off
// Generated file (from: lstm_float.mod.py). Do not edit
#include "../../TestGenerated.h"
namespace lstm_float {
// Generated lstm_float test
#include "-"
// Generated model constructor
#include "-"
} // namespace lstm_float
void CreateModel(Model *model) {
OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
OperandType type1(Type::TENSOR_FLOAT32, {4, 2});
OperandType type2(Type::TENSOR_FLOAT32, {4, 4});
OperandType type3(Type::TENSOR_FLOAT32, {0});
OperandType type4(Type::TENSOR_FLOAT32, {4});
OperandType type5(Type::TENSOR_FLOAT32, {0, 0});
OperandType type6(Type::TENSOR_FLOAT32, {1, 4});
OperandType type7(Type::INT32, {});
OperandType type8(Type::FLOAT32, {});
OperandType type9(Type::TENSOR_FLOAT32, {1, 16});
// Phase 1, operands
auto input = model->addOperand(&type0);
auto input_to_input_weights = model->addOperand(&type1);
auto input_to_forget_weights = model->addOperand(&type1);
auto input_to_cell_weights = model->addOperand(&type1);
auto input_to_output_weights = model->addOperand(&type1);
auto recurrent_to_intput_weights = model->addOperand(&type2);
auto recurrent_to_forget_weights = model->addOperand(&type2);
auto recurrent_to_cell_weights = model->addOperand(&type2);
auto recurrent_to_output_weights = model->addOperand(&type2);
auto cell_to_input_weights = model->addOperand(&type3);
auto cell_to_forget_weights = model->addOperand(&type3);
auto cell_to_output_weights = model->addOperand(&type3);
auto input_gate_bias = model->addOperand(&type4);
auto forget_gate_bias = model->addOperand(&type4);
auto cell_gate_bias = model->addOperand(&type4);
auto output_gate_bias = model->addOperand(&type4);
auto projection_weights = model->addOperand(&type5);
auto projection_bias = model->addOperand(&type3);
auto output_state_in = model->addOperand(&type6);
auto cell_state_in = model->addOperand(&type6);
auto activation_param = model->addOperand(&type7);
auto cell_clip_param = model->addOperand(&type8);
auto proj_clip_param = model->addOperand(&type8);
auto scratch_buffer = model->addOperand(&type9);
auto output_state_out = model->addOperand(&type6);
auto cell_state_out = model->addOperand(&type6);
auto output = model->addOperand(&type6);
// Phase 2, operations
static int32_t activation_param_init[] = {4};
model->setOperandValue(activation_param, activation_param_init, sizeof(int32_t) * 1);
static float cell_clip_param_init[] = {0.0f};
model->setOperandValue(cell_clip_param, cell_clip_param_init, sizeof(float) * 1);
static float proj_clip_param_init[] = {0.0f};
model->setOperandValue(proj_clip_param, proj_clip_param_init, sizeof(float) * 1);
model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in},
{scratch_buffer, output_state_out, cell_state_out, output});
// Phase 4: set relaxed execution
model->relaxComputationFloat32toFloat16(true);
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {0};
return ignore.find(i) != ignore.end();
}
std::vector<MixedTypedExample> examples = {
// Begin of an example
{
//Input(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
{{0, {2.0f, 3.0f}}, {1, {-0.45018822f, -0.02338299f, -0.0870589f, -0.34550029f, 0.04266912f, -0.15680569f, -0.34856534f, 0.43890524f}}, {2, {0.09701663f, 0.20334584f, -0.50592935f, -0.31343272f, -0.40032279f, 0.44781327f, 0.01387155f, -0.35593212f}}, {3, {-0.50013041f, 0.1370284f, 0.11810488f, 0.2013163f, -0.20583314f, 0.44344562f, 0.22077113f, -0.29909778f}}, {4, {-0.25065863f, -0.28290087f, 0.04613829f, 0.40525138f, 0.44272184f, 0.03897077f, -0.1556896f, 0.19487578f}}, {5, {-0.0063535f, -0.2042388f, 0.31454784f, -0.35746509f, 0.28902304f, 0.08183324f, -0.16555229f, 0.02286911f, -0.13566875f, 0.03034258f, 0.48091322f, -0.12528998f, 0.24077177f, -0.51332325f, -0.33502164f, 0.10629296f}}, {6, {-0.48684245f, -0.06655136f, 0.42224967f, 0.2112639f, 0.27654213f, 0.20864892f, -0.07646349f, 0.45877004f, 0.00141793f, -0.14609534f, 0.36447752f, 0.09196436f, 0.28053468f, 0.01560611f, -0.20127171f, -0.01140004f}}, {7, {-0.3407414f, 0.24443203f, -0.2078532f, 0.26320225f, 0.05695659f, -0.00123841f, -0.4744786f, -0.35869038f, -0.06418842f, -0.13502428f, -0.501764f, 0.22830659f, -0.46367589f, 0.26016325f, -0.03894562f, -0.16368064f}}, {8, {0.43385774f, -0.17194885f, 0.2718237f, 0.09215671f, 0.24107647f, -0.39835793f, 0.18212086f, 0.01301402f, 0.48572797f, -0.50656658f, 0.20047462f, -0.20607421f, -0.51818722f, -0.15390486f, 0.0468148f, 0.39922136f}}, {9, {}}, {10, {}}, {11, {}}, {12, {0.0f, 0.0f, 0.0f, 0.0f}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {0.0f, 0.0f, 0.0f, 0.0f}}, {19, {0.0f, 0.0f, 0.0f, 0.0f}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
{}
},
//Output(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
{{0, {0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f}}, {1, {-0.0297319f, 0.122947f, 0.208851f, -0.153588f}}, {2, {-0.145439f, 0.157475f, 0.293663f, -0.277353f}}, {3, {-0.02973187f, 0.1229473f, 0.20885126f, -0.15358765f}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
{}
}
}, // End of an example
};
TEST_F(GeneratedTests, lstm_float) {
execute(lstm_float::CreateModel,
lstm_float::is_ignored,
lstm_float::examples);
}
#include "../generated/tests/lstm_float.mod.py.cpp"
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