From ede580ccdac3b964bdfcf12d55560a268c366c3c Mon Sep 17 00:00:00 2001 From: Benoit Steiner Date: Thu, 16 Aug 2018 10:49:47 -0700 Subject: Avoid using the auto keyword to make the tensor block access test more portable --- unsupported/test/cxx11_tensor_block_access.cpp | 56 +++++++++++++------------- 1 file changed, 28 insertions(+), 28 deletions(-) (limited to 'unsupported/test/cxx11_tensor_block_access.cpp') diff --git a/unsupported/test/cxx11_tensor_block_access.cpp b/unsupported/test/cxx11_tensor_block_access.cpp index 417b72201..da093166b 100644 --- a/unsupported/test/cxx11_tensor_block_access.cpp +++ b/unsupported/test/cxx11_tensor_block_access.cpp @@ -104,7 +104,7 @@ static void test_block_mapper_sanity() VERIFY_IS_EQUAL(uniform_block_mapper.block_dims_total_size(), 100); // 10x10 blocks - auto uniform_b0 = uniform_block_mapper.GetBlockForIndex(0, NULL); + typename TensorBlockMapper::Block uniform_b0 = uniform_block_mapper.GetBlockForIndex(0, NULL); VERIFY_IS_EQUAL(uniform_b0.block_sizes().at(0), 10); VERIFY_IS_EQUAL(uniform_b0.block_sizes().at(1), 10); // Depending on a layout we stride by cols rows. @@ -122,7 +122,7 @@ static void test_block_mapper_sanity() VERIFY_IS_EQUAL(skewed_block_mapper.block_dims_total_size(), 100); // 1x100 (100x1) rows/cols depending on a tensor layout. - auto skewed_b0 = skewed_block_mapper.GetBlockForIndex(0, NULL); + typename TensorBlockMapper::Block skewed_b0 = skewed_block_mapper.GetBlockForIndex(0, NULL); VERIFY_IS_EQUAL(skewed_b0.block_sizes().at(0), choose(Layout, 100, 1)); VERIFY_IS_EQUAL(skewed_b0.block_sizes().at(1), choose(Layout, 1, 100)); // Depending on a layout we stride by cols rows. @@ -203,7 +203,7 @@ static void test_slice_block_mapper_maps_every_element() { // Keep track of elements indices available via block access. std::set coeff_set; - auto total_coeffs = static_cast(tensor_slice_extents.TotalSize()); + int total_coeffs = static_cast(tensor_slice_extents.TotalSize()); // Pick a random dimension sizes for the tensor blocks. DSizes block_sizes; @@ -237,7 +237,7 @@ static void test_block_io_copy_data_from_source_to_target() { TensorBlockWriter; DSizes input_tensor_dims = RandomDims(); - const auto input_tensor_size = input_tensor_dims.TotalSize(); + const Index input_tensor_size = input_tensor_dims.TotalSize(); T* input_data = GenerateRandomData(input_tensor_size); T* output_data = new T[input_tensor_size]; @@ -316,7 +316,7 @@ static void test_block_io_copy_using_reordered_dimensions() { TensorBlockWriter; DSizes input_tensor_dims = RandomDims(); - const auto input_tensor_size = input_tensor_dims.TotalSize(); + const Index input_tensor_size = input_tensor_dims.TotalSize(); // Create a random input tensor. T* input_data = GenerateRandomData(input_tensor_size); @@ -339,8 +339,8 @@ static void test_block_io_copy_using_reordered_dimensions() { TensorBlockMapper block_mapper(output_tensor_dims, RandomShape(), RandomTargetSize(input_tensor_dims)); - auto* block_data = new T[block_mapper.block_dims_total_size()]; - auto* output_data = new T[input_tensor_size]; + T* block_data = new T[block_mapper.block_dims_total_size()]; + T* output_data = new T[input_tensor_size]; array input_tensor_strides = ComputeStrides(input_tensor_dims); @@ -382,8 +382,8 @@ static void test_block_io_zero_stride() input_tensor_dims[0] = 1; input_tensor_dims[2] = 1; input_tensor_dims[4] = 1; - const auto input_tensor_size = input_tensor_dims.TotalSize(); - auto* input_data = GenerateRandomData(input_tensor_size); + const Index input_tensor_size = input_tensor_dims.TotalSize(); + float* input_data = GenerateRandomData(input_tensor_size); DSizes output_tensor_dims = rnd_dims; @@ -424,7 +424,7 @@ static void test_block_io_zero_stride() }; { - auto* output_data = new float[output_tensor_dims.TotalSize()]; + float* output_data = new float[output_tensor_dims.TotalSize()]; TensorBlock read_block(0, output_tensor_dims, output_tensor_strides, input_tensor_strides_with_zeros, output_data); TensorBlockReader::Run(&read_block, input_data); @@ -433,7 +433,7 @@ static void test_block_io_zero_stride() } { - auto* output_data = new float[output_tensor_dims.TotalSize()]; + float* output_data = new float[output_tensor_dims.TotalSize()]; TensorBlock write_block(0, output_tensor_dims, input_tensor_strides_with_zeros, output_tensor_strides, input_data); @@ -456,14 +456,14 @@ static void test_block_io_squeeze_ones() { // Total size > 1. { DSizes block_sizes(1, 2, 1, 2, 1); - const auto total_size = block_sizes.TotalSize(); + const Index total_size = block_sizes.TotalSize(); // Create a random input tensor. - auto* input_data = GenerateRandomData(total_size); + float* input_data = GenerateRandomData(total_size); DSizes strides(ComputeStrides(block_sizes)); { - auto* output_data = new float[block_sizes.TotalSize()]; + float* output_data = new float[block_sizes.TotalSize()]; TensorBlock read_block(0, block_sizes, strides, strides, output_data); TensorBlockReader::Run(&read_block, input_data); for (int i = 0; i < total_size; ++i) { @@ -473,7 +473,7 @@ static void test_block_io_squeeze_ones() { } { - auto* output_data = new float[block_sizes.TotalSize()]; + float* output_data = new float[block_sizes.TotalSize()]; TensorBlock write_block(0, block_sizes, strides, strides, input_data); TensorBlockWriter::Run(write_block, output_data); for (int i = 0; i < total_size; ++i) { @@ -486,14 +486,14 @@ static void test_block_io_squeeze_ones() { // Total size == 1. { DSizes block_sizes(1, 1, 1, 1, 1); - const auto total_size = block_sizes.TotalSize(); + const Index total_size = block_sizes.TotalSize(); // Create a random input tensor. - auto* input_data = GenerateRandomData(total_size); + float* input_data = GenerateRandomData(total_size); DSizes strides(ComputeStrides(block_sizes)); { - auto* output_data = new float[block_sizes.TotalSize()]; + float* output_data = new float[block_sizes.TotalSize()]; TensorBlock read_block(0, block_sizes, strides, strides, output_data); TensorBlockReader::Run(&read_block, input_data); for (int i = 0; i < total_size; ++i) { @@ -503,7 +503,7 @@ static void test_block_io_squeeze_ones() { } { - auto* output_data = new float[block_sizes.TotalSize()]; + float* output_data = new float[block_sizes.TotalSize()]; TensorBlock write_block(0, block_sizes, strides, strides, input_data); TensorBlockWriter::Run(write_block, output_data); for (int i = 0; i < total_size; ++i) { @@ -524,7 +524,7 @@ static void test_block_cwise_binary_io_basic() { DSizes block_sizes = RandomDims(); DSizes strides(ComputeStrides(block_sizes)); - const auto total_size = block_sizes.TotalSize(); + const Index total_size = block_sizes.TotalSize(); // Create a random input tensors. T* left_data = GenerateRandomData(total_size); @@ -553,13 +553,13 @@ static void test_block_cwise_binary_io_squeeze_ones() { DSizes block_sizes(1, 2, 1, 3, 1); DSizes strides(ComputeStrides(block_sizes)); - const auto total_size = block_sizes.TotalSize(); + const Index total_size = block_sizes.TotalSize(); // Create a random input tensors. - auto* left_data = GenerateRandomData(total_size); - auto* right_data = GenerateRandomData(total_size); + float* left_data = GenerateRandomData(total_size); + float* right_data = GenerateRandomData(total_size); - auto* output_data = new float[total_size]; + float* output_data = new float[total_size]; BinaryFunctor functor; TensorBlockCwiseBinaryIO::Run(functor, block_sizes, strides, output_data, strides, left_data, strides, right_data); @@ -600,14 +600,14 @@ static void test_block_cwise_binary_io_zero_strides() { right_strides[3] = 0; // Generate random data. - auto* left_data = GenerateRandomData(left_sizes.TotalSize()); - auto* right_data = GenerateRandomData(right_sizes.TotalSize()); + float* left_data = GenerateRandomData(left_sizes.TotalSize()); + float* right_data = GenerateRandomData(right_sizes.TotalSize()); DSizes output_sizes = rnd_dims; DSizes output_strides(ComputeStrides(output_sizes)); - const auto output_total_size = output_sizes.TotalSize(); - auto* output_data = new float[output_total_size]; + const Index output_total_size = output_sizes.TotalSize(); + float* output_data = new float[output_total_size]; BinaryFunctor functor; TensorBlockCwiseBinaryIO::Run(functor, output_sizes, output_strides, -- cgit v1.2.3