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Just want to confirm if this failure is intended #26248

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Just want to confirm if this failure is intended #26248

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82 changes: 82 additions & 0 deletions tensorflow/lite/interpreter_test.cc
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Expand Up @@ -14,6 +14,7 @@ limitations under the License.
==============================================================================*/

#include "tensorflow/lite/interpreter.h"
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "tensorflow/lite/core/api/error_reporter.h"
#include "tensorflow/lite/kernels/internal/compatibility.h"
Expand Down Expand Up @@ -47,6 +48,7 @@ namespace ops {
namespace builtin {
TfLiteRegistration* Register_PADV2();
TfLiteRegistration* Register_NEG();
TfLiteRegistration* Register_ADD();
} // namespace builtin
} // namespace ops
namespace {
Expand Down Expand Up @@ -815,6 +817,86 @@ TEST(BasicInterpreter, DynamicTensorsResizeDescendants) {
ASSERT_EQ(interpreter.tensor(3)->bytes, sizeof(float) * 10 * 14);
}

TEST(BasicInterpreter, DecendantsDependOnDyanmicTensorAndEarlyIntermediate) {
// The difference between this test and DynamicTensorsResizeDescendants is,
// the final op depends on both dynamic tensor and an intermediate output
// produced earlier.
//
// tensor[0] -------\
// tensor[1] ---------> PAD ---> tensor[2] ---> ADD ---> tensor[3]
// tensor[4] ---> NEG ---> tensor[5] -------/

Interpreter interpreter;
interpreter.AddTensors(6);
interpreter.SetInputs({0, 1, 4});
interpreter.SetOutputs({3});
TfLiteQuantizationParams quant;
interpreter.SetTensorParametersReadWrite(0, kTfLiteFloat32, "", {2, 2, 1, 1},
quant);
interpreter.SetTensorParametersReadWrite(1, kTfLiteInt32, "", {4, 2}, quant);
interpreter.SetTensorParametersReadWrite(2, kTfLiteFloat32, "", {}, quant);
interpreter.SetTensorParametersReadWrite(3, kTfLiteFloat32, "", {}, quant);
interpreter.SetTensorParametersReadWrite(4, kTfLiteFloat32, "", {1}, quant);
interpreter.SetTensorParametersReadWrite(5, kTfLiteFloat32, "", {1}, quant);

TfLiteRegistration* pad_op = tflite::ops::builtin::Register_PADV2();
TfLiteRegistration* neg_op = tflite::ops::builtin::Register_NEG();
TfLiteRegistration* add_op = tflite::ops::builtin::Register_ADD();
TfLiteAddParams *params = (TfLiteAddParams*)malloc(sizeof(TfLiteAddParams));
params->activation = kTfLiteActNone;

// PAD is the second node to make sure tensor[5] is produced first.
interpreter.AddNodeWithParameters({4}, {5}, nullptr, 0, nullptr, neg_op);
interpreter.AddNodeWithParameters({0, 1}, {2}, nullptr, 0, nullptr, pad_op);
interpreter.AddNodeWithParameters({2, 5}, {3}, nullptr, 0, params, add_op);
ASSERT_EQ(interpreter.AllocateTensors(), kTfLiteOk);

// Fill any float into the third input.
interpreter.typed_tensor<float>(4)[0] = 1.0f;

// Configure [[2,2],[2,2]] padding and execute the graph.
interpreter.typed_tensor<int>(1)[0] = 2;
interpreter.typed_tensor<int>(1)[1] = 2;
interpreter.typed_tensor<int>(1)[2] = 2;
interpreter.typed_tensor<int>(1)[3] = 2;
interpreter.typed_tensor<int>(1)[4] = 0;
interpreter.typed_tensor<int>(1)[5] = 0;
interpreter.typed_tensor<int>(1)[6] = 0;
interpreter.typed_tensor<int>(1)[7] = 0;
ASSERT_EQ(interpreter.Invoke(), kTfLiteOk);

using ::testing::ElementsAreArray;

auto getShape = [](TfLiteTensor *tensor) {
std::vector<int> result;
for (int i = 0; i < tensor->dims->size; ++i) {
result.push_back(tensor->dims->data[i]);
}
return result;
};

// Both the output and intermediate tensor dims should reflect the output
// from the dynamic pad operation.
EXPECT_THAT(getShape(interpreter.tensor(2)), ElementsAreArray({6, 6, 1, 1}));
EXPECT_THAT(getShape(interpreter.tensor(3)), ElementsAreArray({6, 6, 1, 1}));

// Now configure [[4,4],[6,6]] padding and execute the graph.
interpreter.typed_tensor<int>(1)[0] = 4;
interpreter.typed_tensor<int>(1)[1] = 4;
interpreter.typed_tensor<int>(1)[2] = 6;
interpreter.typed_tensor<int>(1)[3] = 6;
interpreter.typed_tensor<int>(1)[4] = 0;
interpreter.typed_tensor<int>(1)[5] = 0;
interpreter.typed_tensor<int>(1)[6] = 0;
interpreter.typed_tensor<int>(1)[7] = 0;
ASSERT_EQ(interpreter.Invoke(), kTfLiteOk);

// Again, the output and intermediate tensor dims should reflect the *new*
// resize from the latest pad operation.
EXPECT_THAT(getShape(interpreter.tensor(2)), ElementsAreArray({10, 14, 1, 1}));
EXPECT_THAT(getShape(interpreter.tensor(3)), ElementsAreArray({10, 14, 1, 1}));
}

TEST(InterpreterTensorsCapacityTest, TestWithinHeadroom) {
Interpreter interpreter;
ASSERT_EQ(interpreter.AddTensors(Interpreter::kTensorsReservedCapacity),
Expand Down