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https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Remove V2 suffix from TensorBlock
This commit is contained in:
Eugene Zhulenev
@@ -19,7 +19,7 @@ using Eigen::Tensor;
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using Eigen::Index;
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using Eigen::RowMajor;
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using Eigen::ColMajor;
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using Eigen::internal::TensorBlockV2ShapeType;
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using Eigen::internal::TensorBlockShapeType;
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template<typename T>
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@@ -27,10 +27,10 @@ static const T& choose(int layout, const T& col, const T& row) {
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return layout == ColMajor ? col : row;
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}
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static TensorBlockV2ShapeType RandomShape() {
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static TensorBlockShapeType RandomShape() {
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return internal::random<bool>()
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? TensorBlockV2ShapeType::kUniformAllDims
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: TensorBlockV2ShapeType::kSkewedInnerDims;
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? TensorBlockShapeType::kUniformAllDims
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: TensorBlockShapeType::kSkewedInnerDims;
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}
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template <int NumDims>
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@@ -67,13 +67,13 @@ static void Debug(DSizes<Index, NumDims> dims) {
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template <int Layout>
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static void test_block_mapper_sanity()
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{
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typedef internal::TensorBlockV2Mapper<2, Layout> TensorBlockMapper;
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typedef internal::TensorBlockMapper<2, Layout> TensorBlockMapper;
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DSizes<Index, 2> tensor_dims(100, 100);
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// Test uniform blocks.
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TensorBlockMapper uniform_block_mapper(
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tensor_dims, {TensorBlockV2ShapeType::kUniformAllDims, 100});
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tensor_dims, {TensorBlockShapeType::kUniformAllDims, 100});
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VERIFY_IS_EQUAL(uniform_block_mapper.blockCount(), 100);
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VERIFY_IS_EQUAL(uniform_block_mapper.blockTotalSize(), 100);
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@@ -85,7 +85,7 @@ static void test_block_mapper_sanity()
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// Test skewed to inner dims blocks.
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TensorBlockMapper skewed_block_mapper(
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tensor_dims, {TensorBlockV2ShapeType::kSkewedInnerDims, 100});
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tensor_dims, {TensorBlockShapeType::kSkewedInnerDims, 100});
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VERIFY_IS_EQUAL(skewed_block_mapper.blockCount(), 100);
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VERIFY_IS_EQUAL(skewed_block_mapper.blockTotalSize(), 100);
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@@ -121,7 +121,7 @@ static void UpdateCoeffSet(
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template <typename T, int NumDims, int Layout>
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static void test_block_mapper_maps_every_element() {
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typedef internal::TensorBlockV2Mapper<NumDims, Layout> TensorBlockMapper;
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typedef internal::TensorBlockMapper<NumDims, Layout> TensorBlockMapper;
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DSizes<Index, NumDims> dims = RandomDims<NumDims>();
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DSizes<Index, NumDims> strides = internal::strides<Layout>(dims);
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@@ -227,14 +227,14 @@ template <int Layout>
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static void test_uniform_block_shape()
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{
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typedef internal::TensorBlockDescriptor<5> TensorBlock;
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typedef internal::TensorBlockV2Mapper<5, Layout> TensorBlockMapper;
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typedef internal::TensorBlockMapper<5, Layout> TensorBlockMapper;
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{
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// Test shape 'UniformAllDims' with uniform 'max_coeff count'.
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 5 * 5 * 5 * 5 * 5;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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for (int i = 0; i < 5; ++i) {
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@@ -249,7 +249,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 7 * 5 * 5 * 5 * 5;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[0]);
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@@ -261,7 +261,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 5 * 5 * 5 * 5 * 6;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(6, block.dimensions()[4]);
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@@ -277,7 +277,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 11 * 5 * 5 * 5 * 5;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(11, block.dimensions()[0]);
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@@ -289,7 +289,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 5 * 5 * 5 * 5 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -305,7 +305,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(7, 5, 6, 17, 7);
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const Index max_coeff_count = 7 * 5 * 6 * 7 * 5;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[0]);
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@@ -318,7 +318,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(7, 5, 6, 9, 7);
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const Index max_coeff_count = 5 * 5 * 5 * 6 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -334,7 +334,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(7, 5, 6, 17, 7);
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const Index max_coeff_count = 7 * 5 * 6 * 17 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[0]);
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@@ -347,7 +347,7 @@ static void test_uniform_block_shape()
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DSizes<Index, 5> dims(7, 5, 6, 9, 7);
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const Index max_coeff_count = 7 * 5 * 6 * 9 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kUniformAllDims,
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block_mapper(dims, {TensorBlockShapeType::kUniformAllDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -363,14 +363,14 @@ template <int Layout>
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static void test_skewed_inner_dim_block_shape()
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{
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typedef internal::TensorBlockDescriptor<5> TensorBlock;
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typedef internal::TensorBlockV2Mapper<5, Layout> TensorBlockMapper;
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typedef internal::TensorBlockMapper<5, Layout> TensorBlockMapper;
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// Test shape 'SkewedInnerDims' with partial allocation to inner-most dim.
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if (Layout == ColMajor) {
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 10 * 1 * 1 * 1 * 1;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(10, block.dimensions()[0]);
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@@ -382,7 +382,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 1 * 1 * 1 * 1 * 6;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(6, block.dimensions()[4]);
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@@ -397,7 +397,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 11 * 1 * 1 * 1 * 1;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(11, block.dimensions()[0]);
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@@ -409,7 +409,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 1 * 1 * 1 * 1 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -425,7 +425,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 11 * 3 * 1 * 1 * 1;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(11, block.dimensions()[0]);
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@@ -438,7 +438,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 1 * 1 * 1 * 15 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -455,7 +455,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 11 * 5 * 5 * 1 * 1;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(11, block.dimensions()[0]);
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@@ -469,7 +469,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 1 * 1 * 5 * 17 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -486,7 +486,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 11 * 5 * 6 * 17 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(11, block.dimensions()[0]);
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@@ -499,7 +499,7 @@ static void test_skewed_inner_dim_block_shape()
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DSizes<Index, 5> dims(11, 5, 6, 17, 7);
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const Index max_coeff_count = 11 * 5 * 6 * 17 * 7;
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TensorBlockMapper
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block_mapper(dims, {TensorBlockV2ShapeType::kSkewedInnerDims,
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block_mapper(dims, {TensorBlockShapeType::kSkewedInnerDims,
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max_coeff_count});
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TensorBlock block = block_mapper.blockDescriptor(0);
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VERIFY_IS_EQUAL(7, block.dimensions()[4]);
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@@ -512,7 +512,7 @@ static void test_skewed_inner_dim_block_shape()
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}
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template <int Layout>
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static void test_empty_dims(const internal::TensorBlockV2ShapeType block_shape)
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static void test_empty_dims(const internal::TensorBlockShapeType block_shape)
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{
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// Test blocking of tensors with zero dimensions:
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// - we must not crash on asserts and divisions by zero
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@@ -520,7 +520,7 @@ static void test_empty_dims(const internal::TensorBlockV2ShapeType block_shape)
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// (recipe for overflows/underflows, divisions by zero and NaNs later)
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// - total block count must be zero
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{
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typedef internal::TensorBlockV2Mapper<1, Layout> TensorBlockMapper;
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typedef internal::TensorBlockMapper<1, Layout> TensorBlockMapper;
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DSizes<Index, 1> dims(0);
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for (size_t max_coeff_count = 0; max_coeff_count < 2; ++max_coeff_count) {
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@@ -531,7 +531,7 @@ static void test_empty_dims(const internal::TensorBlockV2ShapeType block_shape)
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}
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{
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typedef internal::TensorBlockV2Mapper<2, Layout> TensorBlockMapper;
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typedef internal::TensorBlockMapper<2, Layout> TensorBlockMapper;
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for (int dim1 = 0; dim1 < 3; ++dim1) {
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for (int dim2 = 0; dim2 < 3; ++dim2) {
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@@ -573,8 +573,8 @@ EIGEN_DECLARE_TEST(cxx11_tensor_block_access) {
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TEST_LAYOUTS_AND_DIMS(float, test_block_mapper_maps_every_element);
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TEST_LAYOUTS(test_uniform_block_shape);
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TEST_LAYOUTS(test_skewed_inner_dim_block_shape);
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TEST_LAYOUTS_WITH_ARG(test_empty_dims, TensorBlockV2ShapeType::kUniformAllDims);
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TEST_LAYOUTS_WITH_ARG(test_empty_dims, TensorBlockV2ShapeType::kSkewedInnerDims);
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TEST_LAYOUTS_WITH_ARG(test_empty_dims, TensorBlockShapeType::kUniformAllDims);
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TEST_LAYOUTS_WITH_ARG(test_empty_dims, TensorBlockShapeType::kSkewedInnerDims);
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}
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#undef TEST_LAYOUTS
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@@ -61,9 +61,9 @@ static TensorBlockParams<NumDims> RandomBlock(DSizes<Index, NumDims> dims,
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template <int Layout, int NumDims>
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static TensorBlockParams<NumDims> SkewedInnerBlock(
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DSizes<Index, NumDims> dims) {
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using BlockMapper = internal::TensorBlockV2Mapper<NumDims, Layout, Index>;
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using BlockMapper = internal::TensorBlockMapper<NumDims, Layout, Index>;
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BlockMapper block_mapper(dims,
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{internal::TensorBlockV2ShapeType::kSkewedInnerDims,
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{internal::TensorBlockShapeType::kSkewedInnerDims,
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internal::random<size_t>(1, dims.TotalSize())});
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Index total_blocks = block_mapper.blockCount();
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@@ -158,7 +158,7 @@ static void VerifyBlockEvaluator(Expression expr, GenBlockParams gen_block) {
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}
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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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auto tensor_block = eval.block(block_params.desc, scratch, root_of_expr);
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if (tensor_block.kind() == internal::TensorBlockKind::kMaterializedInOutput) {
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// Copy data from destination buffer.
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@@ -596,7 +596,7 @@ static void VerifyBlockAssignment(Tensor<T, NumDims, Layout>& tensor,
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tensor.setZero();
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// Use evaluator to write block into a tensor.
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eval.writeBlockV2(block_params.desc, blk);
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eval.writeBlock(block_params.desc, blk);
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// Make a copy of the result after assignment.
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Tensor<T, NumDims, Layout> block_assigned = tensor;
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@@ -22,10 +22,10 @@ static DSizes<Index, NumDims> RandomDims(Index min, Index max) {
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return DSizes<Index, NumDims>(dims);
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}
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static internal::TensorBlockV2ShapeType RandomBlockShape() {
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static internal::TensorBlockShapeType RandomBlockShape() {
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return internal::random<bool>()
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? internal::TensorBlockV2ShapeType::kUniformAllDims
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: internal::TensorBlockV2ShapeType::kSkewedInnerDims;
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? internal::TensorBlockShapeType::kUniformAllDims
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: internal::TensorBlockShapeType::kSkewedInnerDims;
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}
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template <int NumDims>
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@@ -60,7 +60,7 @@ static Index GetInputIndex(Index output_index,
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template <typename T, int NumDims, int Layout>
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static void test_block_io_copy_data_from_source_to_target() {
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using TensorBlockIO = internal::TensorBlockIOV2<T, Index, NumDims, Layout>;
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using TensorBlockIO = internal::TensorBlockIO<T, Index, NumDims, Layout>;
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using IODst = typename TensorBlockIO::Dst;
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using IOSrc = typename TensorBlockIO::Src;
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@@ -74,7 +74,7 @@ static void test_block_io_copy_data_from_source_to_target() {
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// Construct a tensor block mapper.
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using TensorBlockMapper =
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internal::TensorBlockV2Mapper<NumDims, Layout, Index>;
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internal::TensorBlockMapper<NumDims, Layout, Index>;
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TensorBlockMapper block_mapper(dims, {RandomBlockShape(),
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RandomTargetBlockSize(dims)});
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@@ -145,7 +145,7 @@ static void test_block_io_copy_using_reordered_dimensions() {
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// Construct a tensor block mapper.
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// NOTE: Tensor block mapper works with shuffled dimensions.
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using TensorBlockMapper =
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internal::TensorBlockV2Mapper<NumDims, Layout, Index>;
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internal::TensorBlockMapper<NumDims, Layout, Index>;
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TensorBlockMapper block_mapper(output_tensor_dims, {RandomBlockShape(),
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RandomTargetBlockSize(output_tensor_dims)});
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@@ -169,7 +169,7 @@ static void test_block_io_copy_using_reordered_dimensions() {
|
||||
|
||||
// NOTE: Block dimensions are in the same order as output dimensions.
|
||||
|
||||
using TensorBlockIO = internal::TensorBlockIOV2<T, Index, NumDims, Layout>;
|
||||
using TensorBlockIO = internal::TensorBlockIO<T, Index, NumDims, Layout>;
|
||||
using IODst = typename TensorBlockIO::Dst;
|
||||
using IOSrc = typename TensorBlockIO::Src;
|
||||
|
||||
@@ -181,7 +181,7 @@ static void test_block_io_copy_using_reordered_dimensions() {
|
||||
IODst dst(blk_dims, blk_strides, block_data, 0);
|
||||
IOSrc src(input_strides, input_data, first_coeff_index);
|
||||
|
||||
// TODO(ezhulenev): Remove when fully switched to TensorBlockV2.
|
||||
// TODO(ezhulenev): Remove when fully switched to TensorBlock.
|
||||
DSizes<int, NumDims> dim_map;
|
||||
for (int j = 0; j < NumDims; ++j)
|
||||
dim_map[j] = static_cast<int>(output_to_input_dim_map[j]);
|
||||
@@ -199,7 +199,7 @@ static void test_block_io_copy_using_reordered_dimensions() {
|
||||
IODst dst(dst_dims, input_strides, output_data, first_coeff_index);
|
||||
IOSrc src(blk_strides, block_data, 0);
|
||||
|
||||
// TODO(ezhulenev): Remove when fully switched to TensorBlockV2.
|
||||
// TODO(ezhulenev): Remove when fully switched to TensorBlock.
|
||||
DSizes<int, NumDims> dim_map;
|
||||
for (int j = 0; j < NumDims; ++j)
|
||||
dim_map[j] = static_cast<int>(input_to_output_dim_map[j]);
|
||||
@@ -235,7 +235,7 @@ static void test_block_io_copy_using_reordered_dimensions_do_not_squeeze() {
|
||||
float* tensor_data = tensor.data();
|
||||
float* block_data = block.data();
|
||||
|
||||
using TensorBlockIO = internal::TensorBlockIOV2<float, Index, 3, Layout>;
|
||||
using TensorBlockIO = internal::TensorBlockIO<float, Index, 3, Layout>;
|
||||
using IODst = typename TensorBlockIO::Dst;
|
||||
using IOSrc = typename TensorBlockIO::Src;
|
||||
|
||||
@@ -283,7 +283,7 @@ static void test_block_io_copy_using_reordered_dimensions_squeeze() {
|
||||
float* tensor_data = tensor.data();
|
||||
float* block_data = block.data();
|
||||
|
||||
using TensorBlockIO = internal::TensorBlockIOV2<float, Index, 4, Layout>;
|
||||
using TensorBlockIO = internal::TensorBlockIO<float, Index, 4, Layout>;
|
||||
using IODst = typename TensorBlockIO::Dst;
|
||||
using IOSrc = typename TensorBlockIO::Src;
|
||||
|
||||
@@ -334,7 +334,7 @@ static void test_block_io_zero_stride() {
|
||||
Tensor<float, 5, Layout> output(output_tensor_dims);
|
||||
output.setRandom();
|
||||
|
||||
using TensorBlockIO = internal::TensorBlockIOV2<float, Index, 5, Layout>;
|
||||
using TensorBlockIO = internal::TensorBlockIO<float, Index, 5, Layout>;
|
||||
using IODst = typename TensorBlockIO::Dst;
|
||||
using IOSrc = typename TensorBlockIO::Src;
|
||||
|
||||
@@ -360,7 +360,7 @@ static void test_block_io_zero_stride() {
|
||||
|
||||
template <int Layout>
|
||||
static void test_block_io_squeeze_ones() {
|
||||
using TensorBlockIO = internal::TensorBlockIOV2<float, Index, 5, Layout>;
|
||||
using TensorBlockIO = internal::TensorBlockIO<float, Index, 5, Layout>;
|
||||
using IODst = typename TensorBlockIO::Dst;
|
||||
using IOSrc = typename TensorBlockIO::Src;
|
||||
|
||||
|
||||
Reference in New Issue
Block a user