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/****************************************************************************
*
* Copyright (c) 2022 Vivante Corporation
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*
*****************************************************************************/
#include "tim/vx/context.h"
#include "tim/vx/graph.h"
#include "tim/vx/ops/bidirectional_sequence_lstm.h"
#include "gtest/gtest.h"
#include "test_utils.h"
std::shared_ptr<tim::vx::Tensor> make_empty_tensor(
std::shared_ptr<tim::vx::Graph> graph, const tim::vx::ShapeType& shape,
const tim::vx::TensorAttribute& role); //, const float& default_value)
TEST(Bidirectional_LSTM_CELL, shape_in_2_cell_4_out_4_float32) {
// NoCifg_NoPeephole_NoProjection_NoLayerNorm
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
uint32_t n_batch, n_step, n_cell, n_input, n_output;
n_batch = 1, n_step = 3, n_cell = 4, n_input = 2, n_output = 4;
tim::vx::ShapeType input_shape, cell_shape, state_shape;
input_shape = {n_batch, n_step, n_input}; // non-time-major
tim::vx::TensorSpec lstm_input_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_step, n_batch}), tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec fw_weight_i2i_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_i2f_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_i2c_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_i2o_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_r2i_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_r2f_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_r2c_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_weight_r2o_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_bias_i_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_bias_f_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_bias_c_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_bias_o_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_i2i_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_i2f_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_i2c_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_i2o_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_input, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_r2i_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_r2f_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_r2c_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_weight_r2o_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_bias_i_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_bias_f_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_bias_c_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec bw_bias_o_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_cell}), tim::vx::TensorAttribute::CONSTANT);
tim::vx::TensorSpec fw_output_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_step, n_batch}), tim::vx::TensorAttribute::OUTPUT);
tim::vx::TensorSpec bw_output_spec(tim::vx::DataType::FLOAT32, tim::vx::ShapeType({n_output, n_step, n_batch}), tim::vx::TensorAttribute::OUTPUT);
auto lstm_input = graph->CreateTensor(lstm_input_spec);
std::vector<float> lstm_input_data = {2., 3., 3., 4., 1., 1.};
lstm_input->CopyDataToTensor(lstm_input_data.data(), lstm_input_data.size() * 4);
auto fw_output_tensor = graph->CreateTensor(fw_output_spec);
auto bw_output_tensor = graph->CreateTensor(bw_output_spec);
std::vector<float> fw_weight_i2i = {-0.45018822, -0.02338299, -0.0870589,
-0.34550029, 0.04266912, -0.15680569,
-0.34856534, 0.43890524};
std::vector<float> fw_weight_i2f = {0.09701663, 0.20334584, -0.50592935,
-0.31343272, -0.40032279, 0.44781327,
0.01387155, -0.35593212};
std::vector<float> fw_weight_i2c = {-0.50013041, 0.1370284, 0.11810488, 0.2013163,
-0.20583314, 0.44344562, 0.22077113,
-0.29909778};
std::vector<float> fw_weight_i2o = {-0.25065863, -0.28290087, 0.04613829,
0.40525138, 0.44272184, 0.03897077, -0.1556896,
0.19487578};
auto fw_weight_i2i_tensor = graph->CreateTensor(fw_weight_i2i_spec, fw_weight_i2i.data());
auto fw_weight_i2f_tensor = graph->CreateTensor(fw_weight_i2f_spec, fw_weight_i2f.data());
auto fw_weight_i2c_tensor = graph->CreateTensor(fw_weight_i2c_spec, fw_weight_i2c.data());
auto fw_weight_i2o_tensor = graph->CreateTensor(fw_weight_i2o_spec, fw_weight_i2o.data());
std::vector<float> fw_weight_r2i = {
-0.0063535, -0.2042388, 0.31454784, -0.35746509,
0.28902304, 0.08183324, -0.16555229, 0.02286911,
-0.13566875, 0.03034258, 0.48091322, -0.12528998,
0.24077177, -0.51332325, -0.33502164, 0.10629296};
std::vector<float> fw_weight_r2f = {
-0.48684245, -0.06655136, 0.42224967, 0.2112639,
0.27654213, 0.20864892, -0.07646349, 0.45877004,
0.00141793, -0.14609534, 0.36447752, 0.09196436,
0.28053468, 0.01560611, -0.20127171, -0.01140004};
std::vector<float> fw_weight_r2c = {
-0.3407414, 0.24443203, -0.2078532, 0.26320225,
0.05695659, -0.00123841, -0.4744786, -0.35869038,
-0.06418842, -0.13502428, -0.501764, 0.22830659,
-0.46367589, 0.26016325, -0.03894562, -0.16368064};
std::vector<float> fw_weight_r2o = {
0.43385774, -0.17194885, 0.2718237, 0.09215671,
0.24107647, -0.39835793, 0.18212086, 0.01301402,
0.48572797, -0.50656658, 0.20047462, -0.20607421,
-0.51818722, -0.15390486, 0.0468148, 0.39922136};
auto fw_weight_r2i_tensor = graph->CreateTensor(fw_weight_r2i_spec, fw_weight_r2i.data());
auto fw_weight_r2f_tensor = graph->CreateTensor(fw_weight_r2f_spec, fw_weight_r2f.data());
auto fw_weight_r2c_tensor = graph->CreateTensor(fw_weight_r2c_spec, fw_weight_r2c.data());
auto fw_weight_r2o_tensor = graph->CreateTensor(fw_weight_r2o_spec, fw_weight_r2o.data());
std::vector<float> fw_bias_i = {0.0, 0.0, 0.0, 0.0};
std::vector<float> fw_bias_f = {1., 1., 1., 1.};
std::vector<float> fw_bias_c = {0.0, 0.0, 0.0, 0.0};
std::vector<float> fw_bias_o = {0.0, 0.0, 0.0, 0.0};
auto fw_bias_i_tensor = graph->CreateTensor(fw_bias_i_spec, fw_bias_i.data());
auto fw_bias_f_tensor = graph->CreateTensor(fw_bias_f_spec, fw_bias_f.data());
auto fw_bias_c_tensor = graph->CreateTensor(fw_bias_c_spec, fw_bias_c.data());
auto fw_bias_o_tensor = graph->CreateTensor(fw_bias_o_spec, fw_bias_o.data());
std::vector<float> bw_weight_i2i = {-0.45018822, -0.02338299, -0.0870589,
-0.34550029, 0.04266912, -0.15680569,
-0.34856534, 0.43890524};
std::vector<float> bw_weight_i2f = {0.09701663, 0.20334584, -0.50592935,
-0.31343272, -0.40032279, 0.44781327,
0.01387155, -0.35593212};
std::vector<float> bw_weight_i2c = {-0.50013041, 0.1370284, 0.11810488, 0.2013163,
-0.20583314, 0.44344562, 0.22077113,
-0.29909778};
std::vector<float> bw_weight_i2o = {-0.25065863, -0.28290087, 0.04613829,
0.40525138, 0.44272184, 0.03897077, -0.1556896,
0.19487578};
auto bw_weight_i2i_tensor = graph->CreateTensor(bw_weight_i2i_spec, bw_weight_i2i.data());
auto bw_weight_i2f_tensor = graph->CreateTensor(bw_weight_i2f_spec, bw_weight_i2f.data());
auto bw_weight_i2c_tensor = graph->CreateTensor(bw_weight_i2c_spec, bw_weight_i2c.data());
auto bw_weight_i2o_tensor = graph->CreateTensor(bw_weight_i2o_spec, bw_weight_i2o.data());
std::vector<float> bw_weight_r2i = {
-0.0063535, -0.2042388, 0.31454784, -0.35746509,
0.28902304, 0.08183324, -0.16555229, 0.02286911,
-0.13566875, 0.03034258, 0.48091322, -0.12528998,
0.24077177, -0.51332325, -0.33502164, 0.10629296};
std::vector<float> bw_weight_r2f = {
-0.48684245, -0.06655136, 0.42224967, 0.2112639,
0.27654213, 0.20864892, -0.07646349, 0.45877004,
0.00141793, -0.14609534, 0.36447752, 0.09196436,
0.28053468, 0.01560611, -0.20127171, -0.01140004};
std::vector<float> bw_weight_r2c = {
-0.3407414, 0.24443203, -0.2078532, 0.26320225,
0.05695659, -0.00123841, -0.4744786, -0.35869038,
-0.06418842, -0.13502428, -0.501764, 0.22830659,
-0.46367589, 0.26016325, -0.03894562, -0.16368064};
std::vector<float> bw_weight_r2o = {
0.43385774, -0.17194885, 0.2718237, 0.09215671,
0.24107647, -0.39835793, 0.18212086, 0.01301402,
0.48572797, -0.50656658, 0.20047462, -0.20607421,
-0.51818722, -0.15390486, 0.0468148, 0.39922136};
auto bw_weight_r2i_tensor = graph->CreateTensor(bw_weight_r2i_spec, bw_weight_r2i.data());
auto bw_weight_r2f_tensor = graph->CreateTensor(bw_weight_r2f_spec, bw_weight_r2f.data());
auto bw_weight_r2c_tensor = graph->CreateTensor(bw_weight_r2c_spec, bw_weight_r2c.data());
auto bw_weight_r2o_tensor = graph->CreateTensor(bw_weight_r2o_spec, bw_weight_r2o.data());
std::vector<float> bw_bias_i = {0.0, 0.0, 0.0, 0.0};
std::vector<float> bw_bias_f = {1., 1., 1., 1.};
std::vector<float> bw_bias_c = {0.0, 0.0, 0.0, 0.0};
std::vector<float> bw_bias_o = {0.0, 0.0, 0.0, 0.0};
auto bw_bias_i_tensor = graph->CreateTensor(bw_bias_i_spec, bw_bias_i.data());
auto bw_bias_f_tensor = graph->CreateTensor(bw_bias_f_spec, bw_bias_f.data());
auto bw_bias_c_tensor = graph->CreateTensor(bw_bias_c_spec, bw_bias_c.data());
auto bw_bias_o_tensor = graph->CreateTensor(bw_bias_o_spec, fw_bias_o.data());
auto bidirectional_lstm = graph->CreateOperation<tim::vx::ops::BidirectionalSequenceLstm>(
0.0, 0.0, tim::vx::ops::BidirectionalSequenceLstm::ActivationType::kTANH, 0.0, false,
tim::vx::ops::BidirectionalSequenceLstm::kSIGMOID, true);
(*bidirectional_lstm)
.BindInputs({
lstm_input,
fw_weight_i2i_tensor,
fw_weight_i2f_tensor,
fw_weight_i2c_tensor,
fw_weight_i2o_tensor,
fw_weight_r2i_tensor,
fw_weight_r2f_tensor,
fw_weight_r2c_tensor,
fw_weight_r2o_tensor,
graph->CreateTensorPlaceHolder(), /*fw_weight_c2i*/
graph->CreateTensorPlaceHolder(), /*fw_weight_c2f*/
graph->CreateTensorPlaceHolder(), /*fw_weight_c2o*/
fw_bias_i_tensor,
fw_bias_f_tensor,
fw_bias_c_tensor,
fw_bias_o_tensor,
// optional for projection
graph->CreateTensorPlaceHolder(), /*fw_weight_prj*/
graph->CreateTensorPlaceHolder(), /*fw_bias_prj*/
bw_weight_i2i_tensor,
bw_weight_i2f_tensor,
bw_weight_i2c_tensor,
bw_weight_i2o_tensor,
bw_weight_r2i_tensor,
bw_weight_r2f_tensor,
bw_weight_r2c_tensor,
bw_weight_r2o_tensor,
graph->CreateTensorPlaceHolder(), /*bw_weight_c2i*/
graph->CreateTensorPlaceHolder(), /*bw_weight_c2f*/
graph->CreateTensorPlaceHolder(), /*bw_weight_c2o*/
bw_bias_i_tensor,
bw_bias_f_tensor,
bw_bias_c_tensor,
bw_bias_o_tensor,
// optional for projection
graph->CreateTensorPlaceHolder(), /*bw_weight_prj*/
graph->CreateTensorPlaceHolder(), /*bw_bias_prj*/
graph->CreateTensorPlaceHolder(), /*fw_h_state*/
graph->CreateTensorPlaceHolder(), /*fw_c_state*/
graph->CreateTensorPlaceHolder(), /*bw_h_state*/
graph->CreateTensorPlaceHolder(), /*bw_c_state*/
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(), // AUX
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(),
graph->CreateTensorPlaceHolder(), // Layer_norm
})
.BindOutputs({
fw_output_tensor,
make_empty_tensor(
graph, tim::vx::ShapeType({n_output, n_batch}), tim::vx::TensorAttribute::OUTPUT), /*fw_h_state*/
make_empty_tensor(
graph, tim::vx::ShapeType({n_cell, n_batch}), tim::vx::TensorAttribute::OUTPUT), /*fw_c_state*/
bw_output_tensor,
make_empty_tensor(
graph, tim::vx::ShapeType({n_output, n_batch}), tim::vx::TensorAttribute::OUTPUT), /*bw_h_state*/
make_empty_tensor(
graph, tim::vx::ShapeType({n_cell, n_batch}), tim::vx::TensorAttribute::OUTPUT), /*bw_c_state*/
});
graph->Compile();
graph->Run();
std::vector<float> lstm_fw_golden_output = {
-0.02973187, 0.1229473, 0.20885126, -0.15358765,
-0.03716109, 0.12507336, 0.41193449, -0.20860538,
-0.15053082, 0.09120187, 0.24278517, -0.12222792};
std::vector<float> lstm_bw_golden_output = {
-0.02973187, 0.1229473, 0.20885126, -0.15358765,
-0.03716109, 0.12507336, 0.41193449, -0.20860538,
-0.15053082, 0.09120187, 0.24278517, -0.12222792};
std::vector<float> fw_output(lstm_fw_golden_output.size());
std::vector<float> bw_output(lstm_bw_golden_output.size());
fw_output_tensor->CopyDataFromTensor(fw_output.data());
bw_output_tensor->CopyDataFromTensor(bw_output.data());
EXPECT_TRUE(ArraysMatch(lstm_fw_golden_output, fw_output, 1e-4f));
EXPECT_TRUE(ArraysMatch(lstm_bw_golden_output, bw_output, 1e-4f));
}
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