Merge "Fix invalid tests for relaxed computation."
diff --git a/nn/runtime/test/for-cts/TestGeneratedOneFile.cpp b/nn/runtime/test/for-cts/TestGeneratedOneFile.cpp
index 4c6263d..0fea551 100644
--- a/nn/runtime/test/for-cts/TestGeneratedOneFile.cpp
+++ b/nn/runtime/test/for-cts/TestGeneratedOneFile.cpp
@@ -62,6 +62,7 @@
#include "../generated/tests/embedding_lookup.mod.py.cpp"
#include "../generated/tests/floor.mod.py.cpp"
#include "../generated/tests/fully_connected_float_2.mod.py.cpp"
+#include "../generated/tests/fully_connected_float_3.mod.py.cpp"
#include "../generated/tests/fully_connected_float_large.mod.py.cpp"
#include "../generated/tests/fully_connected_float_large_weights_as_inputs.mod.py.cpp"
#include "../generated/tests/fully_connected_float.mod.py.cpp"
diff --git a/nn/runtime/test/generated/all_generated_V1_0_vts_tests.cpp b/nn/runtime/test/generated/all_generated_V1_0_vts_tests.cpp
index b6310f9..77939bc 100644
--- a/nn/runtime/test/generated/all_generated_V1_0_vts_tests.cpp
+++ b/nn/runtime/test/generated/all_generated_V1_0_vts_tests.cpp
@@ -916,6 +916,21 @@
fully_connected_float_2::examples);
}
+namespace fully_connected_float_3 {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_3 test
+#include "examples/fully_connected_float_3.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_3.model.cpp"
+} // namespace fully_connected_float_3
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_3) {
+ generated_tests::Execute(device,
+ fully_connected_float_3::createTestModel,
+ fully_connected_float_3::is_ignored,
+ fully_connected_float_3::examples);
+}
+
namespace fully_connected_float_large {
std::vector<MixedTypedExample> examples = {
// Generated fully_connected_float_large test
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp
index d8c887d..2a98ea4 100644
--- a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp
@@ -4,7 +4,7 @@
//Input(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {10, 21, 100, 0, 10, 22, 200, 0, 10, 23, 300, 0, 10, 24, 400, 0}}},
+ {{0, {10, 21, 10, 0, 10, 22, 20, 0, 10, 23, 30, 0, 10, 24, 40, 0}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
@@ -13,7 +13,7 @@
//Output(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {600010, 700046, 830000, 900000}}},
+ {{0, {6010, 7046, 11000, 9000}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp
index 9b6e342..c79d2b7 100644
--- a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp
@@ -4,7 +4,7 @@
//Input(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {10, 21, 100, 10, 22, 200, 10, 23, 300, 10, 24, 400}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {600000, 700000, 800000, 900000}}},
+ {{0, {10, 21, 10, 0, 10, 22, 20, 0, 10, 23, 30, 0, 10, 24, 40, 0}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {6000, 7000, 8000, 9000}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
@@ -13,7 +13,7 @@
//Output(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {600010, 700046, 830000, 900000}}},
+ {{0, {6010, 7046, 11000, 9000}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp
index 131bc5f..e125276 100644
--- a/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp
+++ b/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp
@@ -4,7 +4,7 @@
//Input(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {1, 10, 100, 1000, 10000}}},
+ {{0, {1, 10, 100, 500, 1000}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
@@ -13,7 +13,7 @@
//Output(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {965432}}},
+ {{0, {9832}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp
index 990fd44..09ece5d 100644
--- a/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp
+++ b/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp
@@ -4,7 +4,7 @@
//Input(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {1, 10, 100, 1000, 10000}}, {1, {2, 3, 4, 5, 6}}, {2, {900000}}},
+ {{0, {1, 10, 100, 500, 1000}}, {1, {2, 3, 4, 5, 6}}, {2, {900}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
@@ -13,7 +13,7 @@
//Output(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
// int -> FLOAT32 map
- {{0, {965432}}},
+ {{0, {9832}}},
// int -> INT32 map
{},
// int -> QUANT8_ASYMM map
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp
index f736d8f..724e3cc 100644
--- a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp
@@ -16,7 +16,7 @@
// Phase 2, operations
static float op2_init[] = {0.25f, 0.0f, 10.0f, 100.0f, 0.25f, 1.0f, 20.0f, 100.0f, 0.25f, 0.0f, 30.0f, 100.0f, 0.25f, 1.0f, 40.0f, 100.0f};
model->setOperandValue(op2, op2_init, sizeof(float) * 16);
- static float op3_init[] = {600000.0f, 700000.0f, 800000.0f, 900000.0f};
+ static float op3_init[] = {6000.0f, 7000.0f, 8000.0f, 9000.0f};
model->setOperandValue(op3, op3_init, sizeof(float) * 4);
static int32_t pad0_init[] = {0};
model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
index d24074c..0516ef4 100644
--- a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
@@ -1,19 +1,18 @@
// Generated file (from: depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py). Do not edit
void CreateModel(Model *model) {
- OperandType type3(Type::INT32, {});
- OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 4});
- OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
- OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
- OperandType type2(Type::TENSOR_FLOAT32, {4});
+ OperandType type2(Type::INT32, {});
+ OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 4});
+ OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+ OperandType type1(Type::TENSOR_FLOAT32, {4});
// Phase 1, operands
auto op1 = model->addOperand(&type0);
- auto op2 = model->addOperand(&type1);
- auto op3 = model->addOperand(&type2);
- auto pad0 = model->addOperand(&type3);
- auto act = model->addOperand(&type3);
- auto stride = model->addOperand(&type3);
- auto channelMultiplier = model->addOperand(&type3);
- auto op4 = model->addOperand(&type4);
+ auto op2 = model->addOperand(&type0);
+ auto op3 = model->addOperand(&type1);
+ auto pad0 = model->addOperand(&type2);
+ auto act = model->addOperand(&type2);
+ auto stride = model->addOperand(&type2);
+ auto channelMultiplier = model->addOperand(&type2);
+ auto op4 = model->addOperand(&type3);
// Phase 2, operations
static int32_t pad0_init[] = {0};
model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
diff --git a/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp
index a4a719f..98ca877 100644
--- a/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp
+++ b/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp
@@ -13,7 +13,7 @@
// Phase 2, operations
static float op2_init[] = {2.0f, 3.0f, 4.0f, 5.0f, 6.0f};
model->setOperandValue(op2, op2_init, sizeof(float) * 5);
- static float b0_init[] = {900000.0f};
+ static float b0_init[] = {900.0f};
model->setOperandValue(b0, b0_init, sizeof(float) * 1);
static int32_t act_init[] = {0};
model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp
index 81fc552..ae0fd8c 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp
@@ -87,7 +87,7 @@
const std::vector<uint32_t> inputIndexes = {0};
const std::vector<uint32_t> outputIndexes = {7};
std::vector<uint8_t> operandValues = {
- 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 32, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 160, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 240, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 32, 66, 0, 0, 200, 66, 0, 124, 18, 73, 0, 230, 42, 73, 0, 80, 67, 73, 0, 186, 91, 73, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
+ 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 32, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 160, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 240, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 32, 66, 0, 0, 200, 66, 0, 128, 187, 69, 0, 192, 218, 69, 0, 0, 250, 69, 0, 160, 12, 70, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
};
const std::vector<hidl_memory> pools = {};
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
index e205e2d..4c8415b 100644
--- a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
@@ -4,7 +4,7 @@
const std::vector<Operand> operands = {
{
.type = OperandType::TENSOR_FLOAT32,
- .dimensions = {1, 2, 2, 3},
+ .dimensions = {1, 2, 2, 4},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_3.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_3.model.cpp
new file mode 100644
index 0000000..cec2a49
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_3.model.cpp
@@ -0,0 +1,81 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+ const std::vector<Operand> operands = {
+ {
+ .type = OperandType::TENSOR_FLOAT32,
+ .dimensions = {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, 2},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::CONSTANT_COPY,
+ .location = {.poolIndex = 0, .offset = 0, .length = 8},
+ },
+ {
+ .type = OperandType::TENSOR_FLOAT32,
+ .dimensions = {1},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::CONSTANT_COPY,
+ .location = {.poolIndex = 0, .offset = 8, .length = 4},
+ },
+ {
+ .type = OperandType::TENSOR_FLOAT32,
+ .dimensions = {2, 1},
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::MODEL_OUTPUT,
+ .location = {.poolIndex = 0, .offset = 0, .length = 0},
+ },
+ {
+ .type = OperandType::INT32,
+ .dimensions = {},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::CONSTANT_COPY,
+ .location = {.poolIndex = 0, .offset = 12, .length = 4},
+ }
+ };
+
+ const std::vector<Operation> operations = {
+ {
+ .type = OperationType::FULLY_CONNECTED,
+ .inputs = {0, 1, 2, 4},
+ .outputs = {3},
+ }
+ };
+
+ const std::vector<uint32_t> inputIndexes = {0};
+ const std::vector<uint32_t> outputIndexes = {3};
+ std::vector<uint8_t> operandValues = {
+ 0, 0, 0, 64, 0, 0, 128, 64, 0, 0, 128, 63, 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(int i) {
+ static std::set<int> ignore = {};
+ return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp
index 9a33140..712d47c 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp
@@ -60,7 +60,7 @@
const std::vector<uint32_t> inputIndexes = {0};
const std::vector<uint32_t> outputIndexes = {3};
std::vector<uint8_t> operandValues = {
- 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64, 0, 186, 91, 73, 0, 0, 0, 0
+ 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64, 0, 0, 97, 68, 0, 0, 0, 0
};
const std::vector<hidl_memory> pools = {};
diff --git a/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_relaxed.mod.py b/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_relaxed.mod.py
index 0d39d12..a878b60 100644
--- a/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_relaxed.mod.py
+++ b/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_relaxed.mod.py
@@ -17,7 +17,7 @@
model = Model()
i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_in = 4
f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, 10, 100, .25, 1, 20, 100, .25, 0, 30, 100, .25, 1, 40, 100]) # depth_out = 4
-b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [600000, 700000, 800000, 900000]) # depth_out = 4
+b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [6000, 7000, 8000, 9000]) # depth_out = 4
pad0 = Int32Scalar("pad0", 0)
act = Int32Scalar("act", 0)
stride = Int32Scalar("stride", 1)
@@ -34,14 +34,14 @@
# Example 1. Input in operand 0,
input0 = {
i1: [ # input 0
- 10, 21, 100, 0,
- 10, 22, 200, 0,
- 10, 23, 300, 0,
- 10, 24, 400, 0],
+ 10, 21, 10, 0,
+ 10, 22, 20, 0,
+ 10, 23, 30, 0,
+ 10, 24, 40, 0],
}
# (i1 (conv) f1) + b1
output0 = {output: # output 0
- [600010, 700046, 830000, 900000]}
+ [6010, 7046, 11000, 9000]}
# Instantiate an example
Example((input0, output0))
diff --git a/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py b/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py
index c383512..26d1f09 100644
--- a/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py
+++ b/nn/runtime/test/specs/V1_1/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py
@@ -15,7 +15,7 @@
#
model = Model()
-i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 3}") # depth_in = 3
+i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_in = 4
f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_out = 4
b1 = Input("op3", "TENSOR_FLOAT32", "{4}") # depth_out = 4
pad0 = Int32Scalar("pad0", 0)
@@ -34,21 +34,21 @@
# Example 1. Input in operand 0,
input0 = {
i1: [ # input 0
- 10, 21, 100,
- 10, 22, 200,
- 10, 23, 300,
- 10, 24, 400],
+ 10, 21, 10, 0,
+ 10, 22, 20, 0,
+ 10, 23, 30, 0,
+ 10, 24, 40, 0],
f1: [
.25, 0, 10, 100,
.25, 1, 20, 100,
.25, 0, 30, 100,
.25, 1, 40, 100],
b1:
- [600000, 700000, 800000, 900000]
+ [6000, 7000, 8000, 9000]
}
# (i1 (conv) f1) + b1
output0 = {output: # output 0
- [600010, 700046, 830000, 900000]}
+ [6010, 7046, 11000, 9000]}
# Instantiate an example
Example((input0, output0))
diff --git a/nn/runtime/test/specs/V1_1/fully_connected_float_large_relaxed.mod.py b/nn/runtime/test/specs/V1_1/fully_connected_float_large_relaxed.mod.py
index d898534..e170f68 100644
--- a/nn/runtime/test/specs/V1_1/fully_connected_float_large_relaxed.mod.py
+++ b/nn/runtime/test/specs/V1_1/fully_connected_float_large_relaxed.mod.py
@@ -17,7 +17,7 @@
model = Model()
in0 = Input("op1", "TENSOR_FLOAT32", "{1, 5}") # batch = 1, input_size = 5
weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 5}", [2, 3, 4, 5, 6]) # num_units = 1, input_size = 5
-bias = Parameter("b0", "TENSOR_FLOAT32", "{1}", [900000])
+bias = Parameter("b0", "TENSOR_FLOAT32", "{1}", [900])
out0 = Output("op3", "TENSOR_FLOAT32", "{1, 1}") # batch = 1, number_units = 1
act = Int32Scalar("act", 0)
model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
@@ -25,9 +25,9 @@
# Example 1. Input in operand 0,
input0 = {in0: # input 0
- [1, 10, 100, 1000, 10000]}
+ [1, 10, 100, 500, 1000]}
output0 = {out0: # output 0
- [965432]}
+ [9832]}
# Instantiate an example
Example((input0, output0))
diff --git a/nn/runtime/test/specs/V1_1/fully_connected_float_large_weights_as_inputs_relaxed.mod.py b/nn/runtime/test/specs/V1_1/fully_connected_float_large_weights_as_inputs_relaxed.mod.py
index d3f24c5..01f71ba 100644
--- a/nn/runtime/test/specs/V1_1/fully_connected_float_large_weights_as_inputs_relaxed.mod.py
+++ b/nn/runtime/test/specs/V1_1/fully_connected_float_large_weights_as_inputs_relaxed.mod.py
@@ -25,13 +25,13 @@
# Example 1. Input in operand 0,
input0 = {in0: # input 0
- [1, 10, 100, 1000, 10000],
+ [1, 10, 100, 500, 1000],
weights:
[2, 3, 4, 5, 6],
bias:
- [900000]}
+ [900]}
output0 = {out0: # output 0
- [965432]}
+ [9832]}
# Instantiate an example
Example((input0, output0))
