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Small LSTM test cleanup: Move setting lstm_golden_output_ to SetUp() for a few tests, consistent with other tests. Drop the input/output parameters of VerifyGoldens, it already sees the member variables.

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PiperOrigin-RevId: 322710419
Change-Id: I8035f241db6de5934c47b573ef3dea8ddd25d0b9
This commit is contained in:
Robert David 2020-07-22 20:16:06 -07:00 committed by TensorFlower Gardener
parent 0b2019bdec
commit 663cd759ad
1 changed files with 54 additions and 120 deletions
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174
tensorflow/lite/kernels/lstm_test.cc
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@ -324,9 +324,7 @@ class BaseLstmOpTest : public ::testing::TestWithParam<bool> {
std::vector<std::vector<float>> lstm_golden_output_;
// Compares output up to tolerance to the result of the lstm given the input.
void VerifyGoldens(const std::vector<std::vector<float>>& input,
const std::vector<std::vector<float>>& output,
LSTMOpModel* lstm, float tolerance = 1e-5) {
void VerifyGoldens(LSTMOpModel* lstm, float tolerance = 1e-5) {
// Weights are set twice:
// - The delegate, if used, needs to know the scales and zero-points of
// quantized tensors, which are computed dynamically when weights are set,
@ -337,15 +335,15 @@ class BaseLstmOpTest : public ::testing::TestWithParam<bool> {
lstm->ApplyDelegate();
SetAllWeightsAndBiases(lstm);
const int num_batches = input.size();
const int num_batches = lstm_input_.size();
EXPECT_GT(num_batches, 0);
const int num_inputs = lstm->num_inputs();
EXPECT_GT(num_inputs, 0);
const int input_sequence_size = input[0].size() / num_inputs;
const int input_sequence_size = lstm_input_[0].size() / num_inputs;
EXPECT_GT(input_sequence_size, 0);
for (int i = 0; i < input_sequence_size; ++i) {
for (int b = 0; b < num_batches; ++b) {
const float* batch_start = input[b].data() + i * num_inputs;
const float* batch_start = lstm_input_[b].data() + i * num_inputs;
const float* batch_end = batch_start + num_inputs;
lstm->SetInput(b * lstm->num_inputs(), batch_start, batch_end);
@ -356,7 +354,8 @@ class BaseLstmOpTest : public ::testing::TestWithParam<bool> {
const int num_outputs = lstm->num_outputs();
std::vector<float> expected;
for (int b = 0; b < num_batches; ++b) {
const float* golden_start_batch = output[b].data() + i * num_outputs;
const float* golden_start_batch =
lstm_golden_output_[b].data() + i * num_outputs;
const float* golden_end_batch = golden_start_batch + num_outputs;
expected.insert(expected.end(), golden_start_batch, golden_end_batch);
}
@ -462,7 +461,7 @@ TEST_F(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, Float) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/false);
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm);
VerifyGoldens(&lstm);
}
TEST_F(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, With24Inputs) {
@ -481,7 +480,7 @@ TEST_F(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, With24Inputs) {
/*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/false);
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm);
VerifyGoldens(&lstm);
}
TEST_P(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, HybridUint8) {
@ -503,8 +502,7 @@ TEST_P(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, HybridUint8) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/GetParam());
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm,
/*tolerance=*/0.0157651);
VerifyGoldens(&lstm, /*tolerance=*/0.0157651);
}
TEST_P(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, HybridInt8) {
@ -525,8 +523,7 @@ TEST_P(NoCifg_NoPeephole_NoProjection_NoLayerNorm_LstmOpTest, HybridInt8) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/GetParam());
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm,
/*tolerance=*/0.0157651);
VerifyGoldens(&lstm, /*tolerance=*/0.0157651);
}
class Cifg_Peephole_NoProjection_NoLayerNorm_LstmOpTest
@ -592,7 +589,7 @@ TEST_F(Cifg_Peephole_NoProjection_NoLayerNorm_LstmOpTest, Float) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/false);
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm);
VerifyGoldens(&lstm);
}
TEST_P(Cifg_Peephole_NoProjection_NoLayerNorm_LstmOpTest, HybridUint8) {
@ -614,7 +611,7 @@ TEST_P(Cifg_Peephole_NoProjection_NoLayerNorm_LstmOpTest, HybridUint8) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/GetParam());
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm, /*tolerance=*/0.03573);
VerifyGoldens(&lstm, /*tolerance=*/0.03573);
}
TEST_P(Cifg_Peephole_NoProjection_NoLayerNorm_LstmOpTest, HybridInt8) {
@ -635,7 +632,7 @@ TEST_P(Cifg_Peephole_NoProjection_NoLayerNorm_LstmOpTest, HybridInt8) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/GetParam());
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm, /*tolerance=*/0.03573);
VerifyGoldens(&lstm, /*tolerance=*/0.03573);
}
class NoCifg_Peephole_Projection_NoLayerNorm_LstmOpTest
@ -1252,7 +1249,7 @@ TEST_F(NoCifg_Peephole_Projection_NoLayerNorm_LstmOpTest, Float) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/false);
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm);
VerifyGoldens(&lstm);
}
TEST_P(NoCifg_Peephole_Projection_NoLayerNorm_LstmOpTest, HybridUint8) {
@ -1273,7 +1270,7 @@ TEST_P(NoCifg_Peephole_Projection_NoLayerNorm_LstmOpTest, HybridUint8) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/GetParam());
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm, /*tolerance=*/0.00467);
VerifyGoldens(&lstm, /*tolerance=*/0.00467);
}
TEST_P(NoCifg_Peephole_Projection_NoLayerNorm_LstmOpTest, HybridInt8) {
@ -1293,7 +1290,7 @@ TEST_P(NoCifg_Peephole_Projection_NoLayerNorm_LstmOpTest, HybridInt8) {
/*model_has_legacy_20_inputs=*/true, /*is_layer_norm=*/false,
/*asymmetric_quantize_inputs=*/GetParam());
VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm, /*tolerance=*/0.0015);
VerifyGoldens(&lstm, /*tolerance=*/0.0015);
}
class NoCifg_Peephole_Projection_LayerNorm_LstmOpTest : public BaseLstmOpTest {
@ -1359,6 +1356,19 @@ class NoCifg_Peephole_Projection_LayerNorm_LstmOpTest : public BaseLstmOpTest {
0.1, 0.5, 0.2, 0.4, 0.2, // seq 1
0.6, 0.9, 0.2, 0.5, 0.7}, // seq 2
};
lstm_golden_output_ = {{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.0244077, 0.128027, -0.00170918, // seq 0
0.0137642, 0.140751, 0.0395835, // seq 1
-0.00459231, 0.155278, 0.0837377, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.00692428, 0.0848741, 0.063445, // seq 0
-0.00403912, 0.139963, 0.072681, // seq 1
0.00752706, 0.161903, 0.0561371, // seq 2
}};
}
};
@ -1368,7 +1378,7 @@ TEST_F(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, Float) {
const int n_cell = 4;
const int n_output = 3;
LSTMOpModel layer_norm_lstm(
LSTMOpModel lstm(
n_batch, n_input, n_cell, n_output,
/*use_cifg=*/false, /*use_peephole=*/true,
/*use_projection_weights=*/true,
@ -1376,21 +1386,7 @@ TEST_F(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, Float) {
/*weight_type=*/TensorType_FLOAT32, /*model_has_legacy_20_inputs=*/false,
/*is_layer_norm=*/true, /*asymmetric_quantize_inputs=*/false);
// Verify the final output.
lstm_golden_output_ = {{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.0244077, 0.128027, -0.00170918, // seq 0
0.0137642, 0.140751, 0.0395835, // seq 1
-0.00459231, 0.155278, 0.0837377, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.00692428, 0.0848741, 0.063445, // seq 0
-0.00403912, 0.139963, 0.072681, // seq 1
0.00752706, 0.161903, 0.0561371, // seq 2
}};
VerifyGoldens(lstm_input_, lstm_golden_output_, &layer_norm_lstm);
VerifyGoldens(&lstm);
}
TEST_P(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridUint8) {
@ -1403,7 +1399,7 @@ TEST_P(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridUint8) {
const int n_cell = 4;
const int n_output = 3;
LSTMOpModel layer_norm_lstm(
LSTMOpModel lstm(
n_batch, n_input, n_cell, n_output,
/*use_cifg=*/false, /*use_peephole=*/true,
/*use_projection_weights=*/true,
@ -1411,21 +1407,7 @@ TEST_P(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridUint8) {
/*weight_type=*/TensorType_UINT8, /*model_has_legacy_20_inputs=*/false,
/*is_layer_norm=*/true, /*asymmetric_quantize_inputs=*/GetParam());
lstm_golden_output_ = {{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.0244576, 0.127847, -0.00181765, // seq 0
0.0137518, 0.140892, 0.0402234, // seq 1
-0.0048839, 0.155096, 0.0840309, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.00728636, 0.0843957, 0.0634786, // seq 0
-0.00448382, 0.139278, 0.0737372, // seq 1
0.00734616, 0.161793, 0.0560238, // seq 2
}};
VerifyGoldens(lstm_input_, lstm_golden_output_, &layer_norm_lstm,
/*tolerance=*/0.0010907);
VerifyGoldens(&lstm, /*tolerance=*/0.0010907);
}
TEST_P(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridInt8) {
@ -1437,7 +1419,7 @@ TEST_P(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridInt8) {
const int n_cell = 4;
const int n_output = 3;
LSTMOpModel layer_norm_lstm(
LSTMOpModel lstm(
n_batch, n_input, n_cell, n_output,
/*use_cifg=*/false, /*use_peephole=*/true,
/*use_projection_weights=*/true,
@ -1445,22 +1427,7 @@ TEST_P(NoCifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridInt8) {
/*weight_type=*/TensorType_INT8, /*model_has_legacy_20_inputs=*/false,
/*is_layer_norm=*/true, /*asymmetric_quantize_inputs=*/GetParam());
// Goldens are calculated from weight_type=TensorType_FLOAT32.
lstm_golden_output_ = {{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.0244077, 0.128027, -0.00170918, // seq 0
0.0137642, 0.140751, 0.0395835, // seq 1
-0.00459233, 0.155278, 0.0837378, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.00692428, 0.0848741, 0.063445, // seq 0
-0.00403911, 0.139963, 0.072681, // seq 1
0.00752708, 0.161903, 0.0561371, // seq 2
}};
VerifyGoldens(lstm_input_, lstm_golden_output_, &layer_norm_lstm,
/*tolerance=*/1.06e-3);
VerifyGoldens(&lstm, /*tolerance=*/1.06e-3);
}
class Cifg_Peephole_Projection_LayerNorm_LstmOpTest : public BaseLstmOpTest {
@ -1506,6 +1473,19 @@ class Cifg_Peephole_Projection_LayerNorm_LstmOpTest : public BaseLstmOpTest {
0.1, 0.5, 0.2, 0.4, 0.2, // seq 1
0.6, 0.9, 0.2, 0.5, 0.7}, // seq 2
};
lstm_golden_output_ = {
{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.02129706, 0.140816242, 0.0112733059, // seq 0
0.0132302344, 0.152308047, 0.0346313119, // seq 1
-0.0123688057, 0.165790111, 0.0893077999, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.0226350538, 0.0916948169, 0.0769175813, // seq 0
-0.0269966982, 0.149707705, 0.094149217, // seq 1
-0.0103429332, 0.173016444, 0.0720508844, // seq 2
}};
}
};
@ -1515,7 +1495,7 @@ TEST_F(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, Float) {
const int n_cell = 4;
const int n_output = 3;
LSTMOpModel layer_norm_lstm(
LSTMOpModel lstm(
n_batch, n_input, n_cell, n_output,
/*use_cifg=*/true, /*use_peephole=*/true,
/*use_projection_weights=*/true,
@ -1523,22 +1503,7 @@ TEST_F(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, Float) {
/*weight_type=*/TensorType_FLOAT32, /*model_has_legacy_20_inputs=*/false,
/*is_layer_norm=*/true, /*asymmetric_quantize_inputs=*/false);
// Verify the final output.
lstm_golden_output_ = {
{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.02129706, 0.140816242, 0.0112733059, // seq 0
0.0132302344, 0.152308047, 0.0346313119, // seq 1
-0.0123688057, 0.165790111, 0.0893077999, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.0226350538, 0.0916948169, 0.0769175813, // seq 0
-0.0269966982, 0.149707705, 0.094149217, // seq 1
-0.0103429332, 0.173016444, 0.0720508844, // seq 2
}};
VerifyGoldens(lstm_input_, lstm_golden_output_, &layer_norm_lstm);
VerifyGoldens(&lstm);
}
TEST_P(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridUint8) {
@ -1550,7 +1515,7 @@ TEST_P(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridUint8) {
const int n_cell = 4;
const int n_output = 3;
LSTMOpModel layer_norm_lstm(
LSTMOpModel lstm(
n_batch, n_input, n_cell, n_output,
/*use_cifg=*/true, /*use_peephole=*/true,
/*use_projection_weights=*/true,
@ -1558,23 +1523,7 @@ TEST_P(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridUint8) {
/*weight_type=*/TensorType_UINT8, /*model_has_legacy_20_inputs=*/false,
/*is_layer_norm=*/true, /*asymmetric_quantize_inputs=*/GetParam());
// Verify the final output.
lstm_golden_output_ = {
{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.0212250091, 0.140474007, 0.0115012666, // seq 0
0.0130806509, 0.152660668, 0.0347516984, // seq 1
-0.0124010444, 0.166042402, 0.0898982584, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.0228835996, 0.0917588323, 0.0778886303, // seq 0
-0.0275101066, 0.148769245, 0.0938384682, // seq 1
-0.0103605557, 0.172605693, 0.0728750974, // seq 2
}};
VerifyGoldens(lstm_input_, lstm_golden_output_, &layer_norm_lstm,
/*tolerance=*/0.0009021);
VerifyGoldens(&lstm, /*tolerance=*/0.000971057);
}
TEST_P(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridInt8) {
@ -1583,7 +1532,7 @@ TEST_P(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridInt8) {
const int n_cell = 4;
const int n_output = 3;
LSTMOpModel layer_norm_lstm(
LSTMOpModel lstm(
n_batch, n_input, n_cell, n_output,
/*use_cifg=*/true, /*use_peephole=*/true,
/*use_projection_weights=*/true,
@ -1591,22 +1540,7 @@ TEST_P(Cifg_Peephole_Projection_LayerNorm_LstmOpTest, HybridInt8) {
/*weight_type=*/TensorType_INT8, /*model_has_legacy_20_inputs=*/false,
/*is_layer_norm=*/true, /*asymmetric_quantize_inputs=*/GetParam());
// Goldens are results using FLOAT32 inference.
lstm_golden_output_ = {{
// Batch0: 3 (input_sequence_size) * 3 (n_output)
0.0212971, 0.140816, 0.0112733, // seq 0
0.0132302, 0.152308, 0.0346313, // seq 1
-0.0123688, 0.16579, 0.0893078, // seq 2
},
{
// Batch1: 3 (input_sequence_size) * 3 (n_output)
-0.0226351, 0.0916948, 0.0769176, // seq 0
-0.0269967, 0.149708, 0.0941492, // seq 1
-0.0103429, 0.173016, 0.0720509, // seq 2
}};
VerifyGoldens(lstm_input_, lstm_golden_output_, &layer_norm_lstm,
/*tolerance=*/1e-3);
VerifyGoldens(&lstm, /*tolerance=*/1e-3);
}
class LSTMIntegerOpModel : public SingleOpModel {