Block evaluation for TensorGenerator/TensorReverse/TensorShuffling

This commit is contained in:
Eugene Zhulenev
2019-10-14 14:31:59 -07:00
parent 39fb9eeccf
commit d380c23b2c
16 changed files with 551 additions and 193 deletions

View File

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