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https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Block evaluation for TensorGenerator/TensorReverse/TensorShuffling
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@@ -139,23 +139,50 @@ static void VerifyBlockEvaluator(Expression expr, GenBlockParams gen_block) {
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// Evaluate TensorBlock expression into a tensor.
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Tensor<T, NumDims, Layout> block(block_params.desc.dimensions());
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// Dimensions for the potential destination buffer.
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DSizes<Index, NumDims> dst_dims;
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if (internal::random<bool>()) {
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dst_dims = block_params.desc.dimensions();
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} else {
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for (int i = 0; i < NumDims; ++i) {
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Index extent = internal::random<Index>(0, 5);
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dst_dims[i] = block_params.desc.dimension(i) + extent;
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}
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}
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// Maybe use this tensor as a block desc destination.
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Tensor<T, NumDims, Layout> dst(block_params.desc.dimensions());
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Tensor<T, NumDims, Layout> dst(dst_dims);
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dst.setZero();
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if (internal::random<bool>()) {
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block_params.desc.template AddDestinationBuffer(
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dst.data(), internal::strides<Layout>(dst.dimensions()),
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dst.dimensions().TotalSize() * sizeof(T));
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}
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auto tensor_block = eval.blockV2(block_params.desc, scratch);
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auto b_expr = tensor_block.expr();
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const bool root_of_expr = internal::random<bool>();
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auto tensor_block = eval.blockV2(block_params.desc, scratch, root_of_expr);
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// We explicitly disable vectorization and tiling, to run a simple coefficient
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// wise assignment loop, because it's very simple and should be correct.
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using BlockAssign = TensorAssignOp<decltype(block), const decltype(b_expr)>;
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using BlockExecutor = TensorExecutor<const BlockAssign, Device, false,
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internal::TiledEvaluation::Off>;
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BlockExecutor::run(BlockAssign(block, b_expr), d);
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if (tensor_block.kind() == internal::TensorBlockKind::kMaterializedInOutput) {
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// Copy data from destination buffer.
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if (dimensions_match(dst.dimensions(), block.dimensions())) {
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block = dst;
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} else {
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DSizes<Index, NumDims> offsets;
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for (int i = 0; i < NumDims; ++i) offsets[i] = 0;
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block = dst.slice(offsets, block.dimensions());
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}
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} else {
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// Assign to block from expression.
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auto b_expr = tensor_block.expr();
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// We explicitly disable vectorization and tiling, to run a simple coefficient
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// wise assignment loop, because it's very simple and should be correct.
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using BlockAssign = TensorAssignOp<decltype(block), const decltype(b_expr)>;
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using BlockExecutor = TensorExecutor<const BlockAssign, Device, false,
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internal::TiledEvaluation::Off>;
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BlockExecutor::run(BlockAssign(block, b_expr), d);
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}
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// Cleanup temporary buffers owned by a tensor block.
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tensor_block.cleanup();
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@@ -375,17 +402,16 @@ static void test_eval_tensor_generator() {
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Tensor<T, NumDims, Layout> input(dims);
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input.setRandom();
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auto generator = [](const array<Index, NumDims>& dims) -> T {
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auto generator = [](const array<Index, NumDims>& coords) -> T {
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T result = static_cast<T>(0);
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for (int i = 0; i < NumDims; ++i) {
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result += static_cast<T>((i + 1) * dims[i]);
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result += static_cast<T>((i + 1) * coords[i]);
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}
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return result;
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};
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.generate(generator),
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[&dims]() { return FixedSizeBlock(dims); });
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input.generate(generator), [&dims]() { return FixedSizeBlock(dims); });
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.generate(generator),
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@@ -403,12 +429,63 @@ static void test_eval_tensor_reverse() {
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for (int i = 0; i < NumDims; ++i) reverse[i] = internal::random<bool>();
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.reverse(reverse),
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[&dims]() { return FixedSizeBlock(dims); });
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input.reverse(reverse), [&dims]() { return FixedSizeBlock(dims); });
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VerifyBlockEvaluator<T, NumDims, Layout>(input.reverse(reverse), [&dims]() {
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return RandomBlock<Layout>(dims, 1, 10);
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});
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}
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template <typename T, int NumDims, int Layout>
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static void test_eval_tensor_slice() {
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DSizes<Index, NumDims> dims = RandomDims<NumDims>(10, 20);
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Tensor<T, NumDims, Layout> input(dims);
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input.setRandom();
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// Pick a random slice of an input tensor.
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DSizes<Index, NumDims> slice_start = RandomDims<NumDims>(5, 10);
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DSizes<Index, NumDims> slice_size = RandomDims<NumDims>(5, 10);
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// Make sure that slice start + size do not overflow tensor dims.
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for (int i = 0; i < NumDims; ++i) {
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slice_start[i] = numext::mini(dims[i] - 1, slice_start[i]);
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slice_size[i] = numext::mini(slice_size[i], dims[i] - slice_start[i]);
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}
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.reverse(reverse),
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[&dims]() { return RandomBlock<Layout>(dims, 1, 10); });
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input.slice(slice_start, slice_size),
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[&slice_size]() { return FixedSizeBlock(slice_size); });
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.slice(slice_start, slice_size),
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[&slice_size]() { return RandomBlock<Layout>(slice_size, 1, 10); });
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}
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template <typename T, int NumDims, int Layout>
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static void test_eval_tensor_shuffle() {
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DSizes<Index, NumDims> dims = RandomDims<NumDims>(5, 15);
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Tensor<T, NumDims, Layout> input(dims);
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input.setRandom();
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DSizes<Index, NumDims> shuffle;
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for (int i = 0; i < NumDims; ++i) shuffle[i] = i;
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do {
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DSizes<Index, NumDims> shuffled_dims;
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for (int i = 0; i < NumDims; ++i) shuffled_dims[i] = dims[shuffle[i]];
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.shuffle(shuffle),
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[&shuffled_dims]() { return FixedSizeBlock(shuffled_dims); });
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VerifyBlockEvaluator<T, NumDims, Layout>(
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input.shuffle(shuffle), [&shuffled_dims]() {
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return RandomBlock<Layout>(shuffled_dims, 1, 5);
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});
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break;
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} while (std::next_permutation(&shuffle[0], &shuffle[0] + NumDims));
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}
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template <typename T, int Layout>
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@@ -564,7 +641,7 @@ static void test_assign_to_tensor_chipping() {
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Index chip_dim = internal::random<int>(0, NumDims - 1);
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Index chip_offset = internal::random<Index>(0, dims[chip_dim] - 2);
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DSizes < Index, NumDims - 1 > chipped_dims;
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DSizes<Index, NumDims - 1> chipped_dims;
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for (Index i = 0; i < chip_dim; ++i) {
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chipped_dims[i] = dims[i];
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}
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@@ -587,42 +664,111 @@ static void test_assign_to_tensor_chipping() {
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[&chipped_dims]() { return FixedSizeBlock(chipped_dims); });
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}
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template <typename T, int NumDims, int Layout>
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static void test_assign_to_tensor_slice() {
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DSizes<Index, NumDims> dims = RandomDims<NumDims>(10, 20);
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Tensor<T, NumDims, Layout> tensor(dims);
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// Pick a random slice of tensor.
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DSizes<Index, NumDims> slice_start = RandomDims<NumDims>(5, 10);
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DSizes<Index, NumDims> slice_size = RandomDims<NumDims>(5, 10);
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// Make sure that slice start + size do not overflow tensor dims.
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for (int i = 0; i < NumDims; ++i) {
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slice_start[i] = numext::mini(dims[i] - 1, slice_start[i]);
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slice_size[i] = numext::mini(slice_size[i], dims[i] - slice_start[i]);
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}
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TensorMap<Tensor<T, NumDims, Layout>> map(tensor.data(), dims);
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VerifyBlockAssignment<T, NumDims, Layout>(
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tensor, map.slice(slice_start, slice_size),
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[&slice_size]() { return RandomBlock<Layout>(slice_size, 1, 10); });
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VerifyBlockAssignment<T, NumDims, Layout>(
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tensor, map.slice(slice_start, slice_size),
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[&slice_size]() { return SkewedInnerBlock<Layout>(slice_size); });
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VerifyBlockAssignment<T, NumDims, Layout>(
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tensor, map.slice(slice_start, slice_size),
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[&slice_size]() { return FixedSizeBlock(slice_size); });
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}
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template <typename T, int NumDims, int Layout>
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static void test_assign_to_tensor_shuffle() {
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DSizes<Index, NumDims> dims = RandomDims<NumDims>(5, 15);
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Tensor<T, NumDims, Layout> tensor(dims);
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DSizes<Index, NumDims> shuffle;
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for (int i = 0; i < NumDims; ++i) shuffle[i] = i;
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TensorMap<Tensor<T, NumDims, Layout>> map(tensor.data(), dims);
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do {
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DSizes<Index, NumDims> shuffled_dims;
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for (int i = 0; i < NumDims; ++i) shuffled_dims[i] = dims[shuffle[i]];
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VerifyBlockAssignment<T, NumDims, Layout>(
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tensor, map.shuffle(shuffle),
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[&shuffled_dims]() { return FixedSizeBlock(shuffled_dims); });
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VerifyBlockAssignment<T, NumDims, Layout>(
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tensor, map.shuffle(shuffle), [&shuffled_dims]() {
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return RandomBlock<Layout>(shuffled_dims, 1, 5);
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});
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} while (std::next_permutation(&shuffle[0], &shuffle[0] + NumDims));
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}
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// -------------------------------------------------------------------------- //
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#define CALL_SUBTESTS_DIMS_LAYOUTS(NAME) \
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CALL_SUBTEST((NAME<float, 1, RowMajor>())); \
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CALL_SUBTEST((NAME<float, 2, RowMajor>())); \
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CALL_SUBTEST((NAME<float, 4, RowMajor>())); \
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CALL_SUBTEST((NAME<float, 5, RowMajor>())); \
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CALL_SUBTEST((NAME<float, 1, ColMajor>())); \
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CALL_SUBTEST((NAME<float, 2, ColMajor>())); \
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CALL_SUBTEST((NAME<float, 4, ColMajor>())); \
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CALL_SUBTEST((NAME<float, 5, ColMajor>()))
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#define CALL_SUBTEST_PART(PART) \
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CALL_SUBTEST_##PART
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#define CALL_SUBTESTS_LAYOUTS(NAME) \
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CALL_SUBTEST((NAME<float, RowMajor>())); \
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CALL_SUBTEST((NAME<float, ColMajor>()))
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#define CALL_SUBTESTS_DIMS_LAYOUTS(PART, NAME) \
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CALL_SUBTEST_PART(PART)((NAME<float, 1, RowMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 2, RowMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 3, RowMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 4, RowMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 5, RowMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 1, ColMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 2, ColMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 4, ColMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 4, ColMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, 5, ColMajor>()))
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#define CALL_SUBTESTS_LAYOUTS(PART, NAME) \
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CALL_SUBTEST_PART(PART)((NAME<float, RowMajor>())); \
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CALL_SUBTEST_PART(PART)((NAME<float, ColMajor>()))
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EIGEN_DECLARE_TEST(cxx11_tensor_block_eval) {
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// clang-format off
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_unary_expr_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_binary_expr_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_binary_with_unary_expr_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_broadcast);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_reshape);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_cast);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_select);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_padding);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_chipping);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_generator);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_eval_tensor_reverse);
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CALL_SUBTESTS_DIMS_LAYOUTS(1, test_eval_tensor_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(1, test_eval_tensor_unary_expr_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(1, test_eval_tensor_binary_expr_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(2, test_eval_tensor_binary_with_unary_expr_block);
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CALL_SUBTESTS_DIMS_LAYOUTS(2, test_eval_tensor_broadcast);
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CALL_SUBTESTS_DIMS_LAYOUTS(2, test_eval_tensor_reshape);
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CALL_SUBTESTS_DIMS_LAYOUTS(3, test_eval_tensor_cast);
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CALL_SUBTESTS_DIMS_LAYOUTS(3, test_eval_tensor_select);
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CALL_SUBTESTS_DIMS_LAYOUTS(3, test_eval_tensor_padding);
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CALL_SUBTESTS_DIMS_LAYOUTS(4, test_eval_tensor_chipping);
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CALL_SUBTESTS_DIMS_LAYOUTS(4, test_eval_tensor_generator);
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CALL_SUBTESTS_DIMS_LAYOUTS(4, test_eval_tensor_reverse);
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CALL_SUBTESTS_DIMS_LAYOUTS(5, test_eval_tensor_slice);
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CALL_SUBTESTS_DIMS_LAYOUTS(5, test_eval_tensor_shuffle);
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CALL_SUBTESTS_LAYOUTS(test_eval_tensor_reshape_with_bcast);
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CALL_SUBTESTS_LAYOUTS(test_eval_tensor_forced_eval);
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CALL_SUBTESTS_LAYOUTS(6, test_eval_tensor_reshape_with_bcast);
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CALL_SUBTESTS_LAYOUTS(6, test_eval_tensor_forced_eval);
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CALL_SUBTESTS_DIMS_LAYOUTS(7, test_assign_to_tensor);
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CALL_SUBTESTS_DIMS_LAYOUTS(7, test_assign_to_tensor_reshape);
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CALL_SUBTESTS_DIMS_LAYOUTS(7, test_assign_to_tensor_chipping);
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CALL_SUBTESTS_DIMS_LAYOUTS(8, test_assign_to_tensor_slice);
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CALL_SUBTESTS_DIMS_LAYOUTS(8, test_assign_to_tensor_shuffle);
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// Force CMake to split this test.
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// EIGEN_SUFFIXES;1;2;3;4;5;6;7;8
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CALL_SUBTESTS_DIMS_LAYOUTS(test_assign_to_tensor);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_assign_to_tensor_reshape);
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CALL_SUBTESTS_DIMS_LAYOUTS(test_assign_to_tensor_chipping);
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// clang-format on
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}
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