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synced 2025-04-23 10:09:36 +08:00
Fixed a bug when chipping tensors laid out in row major order.
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@ -157,6 +157,8 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
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eigen_assert(NumInputDims > m_dim.actualDim());
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const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
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eigen_assert(op.offset() < input_dims[m_dim.actualDim()]);
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int j = 0;
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for (int i = 0; i < NumInputDims; ++i) {
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if (i != m_dim.actualDim()) {
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@ -246,7 +248,9 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar* data() const {
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Scalar* result = m_impl.data();
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if (m_dim.actualDim() == NumDims && result) {
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if (((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == NumDims) ||
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(static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == 0)) &&
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result) {
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return result + m_inputOffset;
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} else {
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return NULL;
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@ -340,11 +340,9 @@ static void test_chip_as_lvalue()
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}
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}
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template<int DataLayout>
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static void test_chip_raw_data()
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static void test_chip_raw_data_col_major()
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{
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Tensor<float, 5, DataLayout> tensor(2,3,5,7,11);
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Tensor<float, 5, ColMajor> tensor(2,3,5,7,11);
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tensor.setRandom();
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typedef TensorEvaluator<decltype(tensor.template chip<4>(3)), DefaultDevice> Evaluator4;
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@ -353,12 +351,7 @@ static void test_chip_raw_data()
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 5; ++k) {
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for (int l = 0; l < 7; ++l) {
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int chip_index;
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if (DataLayout == ColMajor) {
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chip_index = i + 2 * (j + 3 * (k + 5 * l));
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} else {
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chip_index = 11 * (l + 7 * (k + 5 * (j + 3 * i)));
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}
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int chip_index = i + 2 * (j + 3 * (k + 5 * l));
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VERIFY_IS_EQUAL(chip.data()[chip_index], tensor(i,j,k,l,3));
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}
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}
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@ -382,6 +375,41 @@ static void test_chip_raw_data()
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VERIFY_IS_EQUAL(chip3.data(), static_cast<float*>(0));
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}
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static void test_chip_raw_data_row_major()
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{
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Tensor<float, 5, RowMajor> tensor(11,7,5,3,2);
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tensor.setRandom();
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typedef TensorEvaluator<decltype(tensor.template chip<0>(3)), DefaultDevice> Evaluator0;
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auto chip = Evaluator0(tensor.template chip<0>(3), DefaultDevice());
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for (int i = 0; i < 7; ++i) {
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for (int j = 0; j < 5; ++j) {
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for (int k = 0; k < 3; ++k) {
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for (int l = 0; l < 2; ++l) {
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int chip_index = l + 2 * (k + 3 * (j + 5 * i));
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VERIFY_IS_EQUAL(chip.data()[chip_index], tensor(3,i,j,k,l));
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}
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}
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}
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}
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typedef TensorEvaluator<decltype(tensor.template chip<1>(0)), DefaultDevice> Evaluator1;
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auto chip1 = Evaluator1(tensor.template chip<1>(0), DefaultDevice());
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VERIFY_IS_EQUAL(chip1.data(), static_cast<float*>(0));
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typedef TensorEvaluator<decltype(tensor.template chip<2>(0)), DefaultDevice> Evaluator2;
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auto chip2 = Evaluator2(tensor.template chip<2>(0), DefaultDevice());
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VERIFY_IS_EQUAL(chip2.data(), static_cast<float*>(0));
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typedef TensorEvaluator<decltype(tensor.template chip<3>(0)), DefaultDevice> Evaluator3;
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auto chip3 = Evaluator3(tensor.template chip<3>(0), DefaultDevice());
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VERIFY_IS_EQUAL(chip3.data(), static_cast<float*>(0));
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typedef TensorEvaluator<decltype(tensor.template chip<4>(0)), DefaultDevice> Evaluator4;
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auto chip4 = Evaluator4(tensor.template chip<4>(0), DefaultDevice());
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VERIFY_IS_EQUAL(chip4.data(), static_cast<float*>(0));
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}
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void test_cxx11_tensor_chipping()
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{
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CALL_SUBTEST(test_simple_chip<ColMajor>());
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@ -392,6 +420,6 @@ void test_cxx11_tensor_chipping()
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CALL_SUBTEST(test_chip_in_expr<RowMajor>());
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CALL_SUBTEST(test_chip_as_lvalue<ColMajor>());
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CALL_SUBTEST(test_chip_as_lvalue<RowMajor>());
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CALL_SUBTEST(test_chip_raw_data<ColMajor>());
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CALL_SUBTEST(test_chip_raw_data<RowMajor>());
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CALL_SUBTEST(test_chip_raw_data_col_major());
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CALL_SUBTEST(test_chip_raw_data_row_major());
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}
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