From 4c7d80b96a9541471afcf784d6816f44e66efaab Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Wed, 15 Jul 2020 11:17:18 -0700 Subject: [PATCH] Fully qualifying uses of tensorflow::int64. PiperOrigin-RevId: 321399703 Change-Id: I42732ead99e062444fa5c507f9fce10f1ace765c --- .../xla/service/cpu/runtime_conv2d.cc | 36 ++++++---- .../xla/service/cpu/runtime_key_value_sort.cc | 43 +++++------- .../xla/service/cpu/runtime_matmul.cc | 56 ++++++++------- .../cpu/runtime_single_threaded_conv2d.cc | 36 ++++++---- .../cpu/runtime_single_threaded_matmul.cc | 69 ++++++++++--------- 5 files changed, 127 insertions(+), 113 deletions(-) diff --git a/tensorflow/compiler/xla/service/cpu/runtime_conv2d.cc b/tensorflow/compiler/xla/service/cpu/runtime_conv2d.cc index 84cb41a8f17..eac0371b76d 100644 --- a/tensorflow/compiler/xla/service/cpu/runtime_conv2d.cc +++ b/tensorflow/compiler/xla/service/cpu/runtime_conv2d.cc @@ -23,16 +23,18 @@ limitations under the License. #include "tensorflow/core/platform/dynamic_annotations.h" #include "tensorflow/core/platform/types.h" -using tensorflow::int64; - TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenConvF32( const void* run_options_ptr, float* out, float* lhs, float* rhs, - int64 input_batch, int64 input_rows, int64 input_cols, int64 input_channels, - int64 kernel_rows, int64 kernel_cols, int64 kernel_channels, - int64 kernel_filters, int64 output_rows, int64 output_cols, - int64 row_stride, int64 col_stride, int64 padding_top, int64 padding_bottom, - int64 padding_left, int64 padding_right, int64 lhs_row_dilation, - int64 lhs_col_dilation, int64 rhs_row_dilation, int64 rhs_col_dilation) { + tensorflow::int64 input_batch, tensorflow::int64 input_rows, + tensorflow::int64 input_cols, tensorflow::int64 input_channels, + tensorflow::int64 kernel_rows, tensorflow::int64 kernel_cols, + tensorflow::int64 kernel_channels, tensorflow::int64 kernel_filters, + tensorflow::int64 output_rows, tensorflow::int64 output_cols, + tensorflow::int64 row_stride, tensorflow::int64 col_stride, + tensorflow::int64 padding_top, tensorflow::int64 padding_bottom, + tensorflow::int64 padding_left, tensorflow::int64 padding_right, + tensorflow::int64 lhs_row_dilation, tensorflow::int64 lhs_col_dilation, + tensorflow::int64 rhs_row_dilation, tensorflow::int64 rhs_col_dilation) { const xla::ExecutableRunOptions* run_options = static_cast(run_options_ptr); XLA_LIGHTWEIGHT_CHECK(run_options->intra_op_thread_pool() != nullptr); @@ -46,13 +48,17 @@ TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenConvF32( TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenConvF16( const void* run_options_ptr, Eigen::half* out, Eigen::half* lhs, - Eigen::half* rhs, int64 input_batch, int64 input_rows, int64 input_cols, - int64 input_channels, int64 kernel_rows, int64 kernel_cols, - int64 kernel_channels, int64 kernel_filters, int64 output_rows, - int64 output_cols, int64 row_stride, int64 col_stride, int64 padding_top, - int64 padding_bottom, int64 padding_left, int64 padding_right, - int64 lhs_row_dilation, int64 lhs_col_dilation, int64 rhs_row_dilation, - int64 rhs_col_dilation) { + Eigen::half* rhs, tensorflow::int64 input_batch, + tensorflow::int64 input_rows, tensorflow::int64 input_cols, + tensorflow::int64 input_channels, tensorflow::int64 kernel_rows, + tensorflow::int64 kernel_cols, tensorflow::int64 kernel_channels, + tensorflow::int64 kernel_filters, tensorflow::int64 output_rows, + tensorflow::int64 output_cols, tensorflow::int64 row_stride, + tensorflow::int64 col_stride, tensorflow::int64 padding_top, + tensorflow::int64 padding_bottom, tensorflow::int64 padding_left, + tensorflow::int64 padding_right, tensorflow::int64 lhs_row_dilation, + tensorflow::int64 lhs_col_dilation, tensorflow::int64 rhs_row_dilation, + tensorflow::int64 rhs_col_dilation) { const xla::ExecutableRunOptions* run_options = static_cast(run_options_ptr); XLA_LIGHTWEIGHT_CHECK(run_options->intra_op_thread_pool() != nullptr); diff --git a/tensorflow/compiler/xla/service/cpu/runtime_key_value_sort.cc b/tensorflow/compiler/xla/service/cpu/runtime_key_value_sort.cc index 0d4e7055ddb..2cee58162fc 100644 --- a/tensorflow/compiler/xla/service/cpu/runtime_key_value_sort.cc +++ b/tensorflow/compiler/xla/service/cpu/runtime_key_value_sort.cc @@ -25,21 +25,16 @@ limitations under the License. #include "tensorflow/core/platform/macros.h" #include "tensorflow/core/platform/types.h" -namespace { -using tensorflow::int32; -using tensorflow::int64; -} // namespace - TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_KeyValueSort( - int64 a, int64 b, int64 c, char** values, int32 values_count, - int32* values_primitive_type_size_in_bytes, bool is_stable, - char* run_options, int64* prof_counters, + tensorflow::int64 a, tensorflow::int64 b, tensorflow::int64 c, char** values, tensorflow::int32 values_count, + tensorflow::int32* values_primitive_type_size_in_bytes, bool is_stable, + char* run_options, tensorflow::int64* prof_counters, void (*less_than)(char*, char*, char**, char**, tensorflow::int64*)) { // 'values' and 'values_primitive_type_size_in_bytes' are managed by the JIT // code, so msan can't tell they are initialized. TF_ANNOTATE_MEMORY_IS_INITIALIZED(values, values_count * sizeof(char*)); TF_ANNOTATE_MEMORY_IS_INITIALIZED(values_primitive_type_size_in_bytes, - values_count * sizeof(int32)); + values_count * sizeof(tensorflow::int32)); // High-level idea of the iteration/sorting logic: // Conceptually we have a 3-dimensional shape [a, b, c]. b corresponds to the @@ -50,16 +45,16 @@ TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_KeyValueSort( // 'base_offset' value which points to the first element in that row, and add // i * c for accessing the 'i'-th element in that row. - int64 sort_dimension_elements = b; - int64 num_iteration_elements = a * c; - int64 sort_dimension_offset = c; + tensorflow::int64 sort_dimension_elements = b; + tensorflow::int64 num_iteration_elements = a * c; + tensorflow::int64 sort_dimension_offset = c; - std::unique_ptr indices(new int64[sort_dimension_elements]); + std::unique_ptr indices(new tensorflow::int64[sort_dimension_elements]); std::unique_ptr comparison_values(new char*[2 * values_count]); std::iota(indices.get(), indices.get() + sort_dimension_elements, 0); std::unique_ptr reordered_values( new std::string[sort_dimension_elements]); - for (int64 index = 0; index < num_iteration_elements; ++index) { + for (tensorflow::int64 index = 0; index < num_iteration_elements; ++index) { // If the sort should be stable, we have to reinitialize indices to iota to // guarantee that we still keep the relative order in case of ties. if (is_stable && index > 0) { @@ -71,14 +66,14 @@ TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_KeyValueSort( // calculating the base offset, we need to multiply the index into the 'a' // dimension with 'b' * 'c'. // 'index' / 'c' * 'c' * 'b' = ('index' - 'index' % 'c') * 'b'. - int64 base_offset = + tensorflow::int64 base_offset = index % sort_dimension_offset + (index - index % sort_dimension_offset) * sort_dimension_elements; - auto compare_function = [&](int64 a, int64 b) -> bool { - for (int32 i = 0; i < values_count; ++i) { - int64 memory_index_lhs = (base_offset + a * sort_dimension_offset) * + auto compare_function = [&](tensorflow::int64 a, tensorflow::int64 b) -> bool { + for (tensorflow::int32 i = 0; i < values_count; ++i) { + tensorflow::int64 memory_index_lhs = (base_offset + a * sort_dimension_offset) * values_primitive_type_size_in_bytes[i]; - int64 memory_index_rhs = (base_offset + b * sort_dimension_offset) * + tensorflow::int64 memory_index_rhs = (base_offset + b * sort_dimension_offset) * values_primitive_type_size_in_bytes[i]; comparison_values[i * 2] = values[i] + memory_index_lhs; comparison_values[i * 2 + 1] = values[i] + memory_index_rhs; @@ -97,9 +92,9 @@ TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_KeyValueSort( } // Reorder the values according to the order defined by 'indices'. - for (int32 idx = 0; idx < values_count; ++idx) { - for (int64 i = 0; i < sort_dimension_elements; ++i) { - int64 memory_index = + for (tensorflow::int32 idx = 0; idx < values_count; ++idx) { + for (tensorflow::int64 i = 0; i < sort_dimension_elements; ++i) { + tensorflow::int64 memory_index = (base_offset + indices[i] * sort_dimension_offset) * values_primitive_type_size_in_bytes[idx]; @@ -107,8 +102,8 @@ TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_KeyValueSort( std::string(values[idx] + memory_index, values_primitive_type_size_in_bytes[idx]); } - for (int64 i = 0; i < sort_dimension_elements; ++i) { - int64 memory_index = (base_offset + i * sort_dimension_offset) * + for (tensorflow::int64 i = 0; i < sort_dimension_elements; ++i) { + tensorflow::int64 memory_index = (base_offset + i * sort_dimension_offset) * values_primitive_type_size_in_bytes[idx]; memcpy(values[idx] + memory_index, reordered_values[i].c_str(), values_primitive_type_size_in_bytes[idx]); diff --git a/tensorflow/compiler/xla/service/cpu/runtime_matmul.cc b/tensorflow/compiler/xla/service/cpu/runtime_matmul.cc index 35db15fed2c..7e19b383d6f 100644 --- a/tensorflow/compiler/xla/service/cpu/runtime_matmul.cc +++ b/tensorflow/compiler/xla/service/cpu/runtime_matmul.cc @@ -27,9 +27,6 @@ limitations under the License. #include "tensorflow/core/kernels/eigen_contraction_kernel.h" #endif -using tensorflow::int32; -using tensorflow::int64; - namespace { bool Is16BytesAligned(void* ptr) { @@ -37,19 +34,20 @@ bool Is16BytesAligned(void* ptr) { } template -void MatMul(const void* run_options_ptr, T* out, T* lhs, T* rhs, int64 m, - int64 n, int64 k, int32 transpose_lhs, int32 transpose_rhs) { +void MatMul(const void* run_options_ptr, T* out, T* lhs, T* rhs, + tensorflow::int64 m, tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, tensorflow::int32 transpose_rhs) { const xla::ExecutableRunOptions* run_options = static_cast(run_options_ptr); - int64 lhs_rows = m; - int64 lhs_cols = k; + tensorflow::int64 lhs_rows = m; + tensorflow::int64 lhs_cols = k; if (transpose_lhs) { std::swap(lhs_rows, lhs_cols); } - int64 rhs_rows = k; - int64 rhs_cols = n; + tensorflow::int64 rhs_rows = k; + tensorflow::int64 rhs_cols = n; if (transpose_rhs) { std::swap(rhs_rows, rhs_cols); } @@ -75,8 +73,9 @@ void MatMul(const void* run_options_ptr, T* out, T* lhs, T* rhs, int64 m, template void MatMulDispatch(const void* run_options_ptr, T* out, T* lhs, T* rhs, - int64 m, int64 n, int64 k, int32 transpose_lhs, - int32 transpose_rhs) { + tensorflow::int64 m, tensorflow::int64 n, + tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { bool all_buffers_16b_aligned = Is16BytesAligned(out) && Is16BytesAligned(lhs) && Is16BytesAligned(rhs); @@ -94,45 +93,52 @@ void MatMulDispatch(const void* run_options_ptr, T* out, T* lhs, T* rhs, TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenMatMulF16( const void* run_options_ptr, Eigen::half* out, Eigen::half* lhs, - Eigen::half* rhs, int64 m, int64 n, int64 k, int32 transpose_lhs, - int32 transpose_rhs) { + Eigen::half* rhs, tensorflow::int64 m, tensorflow::int64 n, + tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { MatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenMatMulF32( - const void* run_options_ptr, float* out, float* lhs, float* rhs, int64 m, - int64 n, int64 k, int32 transpose_lhs, int32 transpose_rhs) { + const void* run_options_ptr, float* out, float* lhs, float* rhs, + tensorflow::int64 m, tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, tensorflow::int32 transpose_rhs) { MatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenMatMulF64( - const void* run_options_ptr, double* out, double* lhs, double* rhs, int64 m, - int64 n, int64 k, int32 transpose_lhs, int32 transpose_rhs) { + const void* run_options_ptr, double* out, double* lhs, double* rhs, + tensorflow::int64 m, tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, tensorflow::int32 transpose_rhs) { MatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenMatMulC64( const void* run_options_ptr, std::complex* out, - std::complex* lhs, std::complex* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, int32 transpose_rhs) { + std::complex* lhs, std::complex* rhs, tensorflow::int64 m, + tensorflow::int64 n, tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { MatMulDispatch>(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenMatMulC128( const void* run_options_ptr, std::complex* out, - std::complex* lhs, std::complex* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, int32 transpose_rhs) { + std::complex* lhs, std::complex* rhs, tensorflow::int64 m, + tensorflow::int64 n, tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { MatMulDispatch>(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenMatMulS32( - const void* run_options_ptr, int32* out, int32* lhs, int32* rhs, int64 m, - int64 n, int64 k, int32 transpose_lhs, int32 transpose_rhs) { - MatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, - transpose_rhs); + const void* run_options_ptr, tensorflow::int32* out, tensorflow::int32* lhs, + tensorflow::int32* rhs, tensorflow::int64 m, tensorflow::int64 n, + tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { + MatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, + transpose_lhs, transpose_rhs); } diff --git a/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_conv2d.cc b/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_conv2d.cc index 5afccc6a86e..360ce57e808 100644 --- a/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_conv2d.cc +++ b/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_conv2d.cc @@ -19,18 +19,20 @@ limitations under the License. #include "tensorflow/core/platform/dynamic_annotations.h" #include "tensorflow/core/platform/types.h" -using tensorflow::int64; - TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenSingleThreadedConvF16( const void* run_options_ptr, Eigen::half* out, Eigen::half* lhs, - Eigen::half* rhs, int64 input_batch, int64 input_rows, int64 input_cols, - int64 input_channels, int64 kernel_rows, int64 kernel_cols, - int64 kernel_channels, int64 kernel_filters, int64 output_rows, - int64 output_cols, int64 row_stride, int64 col_stride, int64 padding_top, - int64 padding_bottom, int64 padding_left, int64 padding_right, - int64 lhs_row_dilation, int64 lhs_col_dilation, int64 rhs_row_dilation, - int64 rhs_col_dilation) { + Eigen::half* rhs, tensorflow::int64 input_batch, + tensorflow::int64 input_rows, tensorflow::int64 input_cols, + tensorflow::int64 input_channels, tensorflow::int64 kernel_rows, + tensorflow::int64 kernel_cols, tensorflow::int64 kernel_channels, + tensorflow::int64 kernel_filters, tensorflow::int64 output_rows, + tensorflow::int64 output_cols, tensorflow::int64 row_stride, + tensorflow::int64 col_stride, tensorflow::int64 padding_top, + tensorflow::int64 padding_bottom, tensorflow::int64 padding_left, + tensorflow::int64 padding_right, tensorflow::int64 lhs_row_dilation, + tensorflow::int64 lhs_col_dilation, tensorflow::int64 rhs_row_dilation, + tensorflow::int64 rhs_col_dilation) { tensorflow::xla::EigenConvImpl( Eigen::DefaultDevice(), out, lhs, rhs, input_batch, input_rows, input_cols, input_channels, kernel_rows, kernel_cols, kernel_channels, @@ -42,12 +44,16 @@ __xla_cpu_runtime_EigenSingleThreadedConvF16( TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenSingleThreadedConvF32( const void* run_options_ptr, float* out, float* lhs, float* rhs, - int64 input_batch, int64 input_rows, int64 input_cols, int64 input_channels, - int64 kernel_rows, int64 kernel_cols, int64 kernel_channels, - int64 kernel_filters, int64 output_rows, int64 output_cols, - int64 row_stride, int64 col_stride, int64 padding_top, int64 padding_bottom, - int64 padding_left, int64 padding_right, int64 lhs_row_dilation, - int64 lhs_col_dilation, int64 rhs_row_dilation, int64 rhs_col_dilation) { + tensorflow::int64 input_batch, tensorflow::int64 input_rows, + tensorflow::int64 input_cols, tensorflow::int64 input_channels, + tensorflow::int64 kernel_rows, tensorflow::int64 kernel_cols, + tensorflow::int64 kernel_channels, tensorflow::int64 kernel_filters, + tensorflow::int64 output_rows, tensorflow::int64 output_cols, + tensorflow::int64 row_stride, tensorflow::int64 col_stride, + tensorflow::int64 padding_top, tensorflow::int64 padding_bottom, + tensorflow::int64 padding_left, tensorflow::int64 padding_right, + tensorflow::int64 lhs_row_dilation, tensorflow::int64 lhs_col_dilation, + tensorflow::int64 rhs_row_dilation, tensorflow::int64 rhs_col_dilation) { tensorflow::xla::EigenConvImpl( Eigen::DefaultDevice(), out, lhs, rhs, input_batch, input_rows, input_cols, input_channels, kernel_rows, kernel_cols, kernel_channels, diff --git a/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_matmul.cc b/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_matmul.cc index c7601f939c7..a8112c1106b 100644 --- a/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_matmul.cc +++ b/tensorflow/compiler/xla/service/cpu/runtime_single_threaded_matmul.cc @@ -23,9 +23,6 @@ limitations under the License. #include "tensorflow/core/kernels/eigen_contraction_kernel.h" #endif -using tensorflow::int32; -using tensorflow::int64; - namespace { bool Is16BytesAligned(void* ptr) { @@ -33,16 +30,17 @@ bool Is16BytesAligned(void* ptr) { } template -void MatMul(const void* run_options_ptr, T* out, T* lhs, T* rhs, int64 m, - int64 n, int64 k, int32 transpose_lhs, int32 transpose_rhs) { - int64 lhs_rows = m; - int64 lhs_cols = k; +void MatMul(const void* run_options_ptr, T* out, T* lhs, T* rhs, + tensorflow::int64 m, tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, tensorflow::int32 transpose_rhs) { + tensorflow::int64 lhs_rows = m; + tensorflow::int64 lhs_cols = k; if (transpose_lhs) { std::swap(lhs_rows, lhs_cols); } - int64 rhs_rows = k; - int64 rhs_cols = n; + tensorflow::int64 rhs_rows = k; + tensorflow::int64 rhs_cols = n; if (transpose_rhs) { std::swap(rhs_rows, rhs_cols); } @@ -67,8 +65,10 @@ void MatMul(const void* run_options_ptr, T* out, T* lhs, T* rhs, int64 m, template void SingleThreadedMatMulDispatch(const void* run_options_ptr, T* out, T* lhs, - T* rhs, int64 m, int64 n, int64 k, - int32 transpose_lhs, int32 transpose_rhs) { + T* rhs, tensorflow::int64 m, + tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { bool all_buffers_16b_aligned = Is16BytesAligned(out) && Is16BytesAligned(lhs) && Is16BytesAligned(rhs); @@ -86,28 +86,27 @@ void SingleThreadedMatMulDispatch(const void* run_options_ptr, T* out, T* lhs, TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenSingleThreadedMatMulF16( const void* run_options_ptr, Eigen::half* out, Eigen::half* lhs, - Eigen::half* rhs, int64 m, int64 n, int64 k, int32 transpose_lhs, - int32 transpose_rhs) { + Eigen::half* rhs, tensorflow::int64 m, tensorflow::int64 n, + tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { SingleThreadedMatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void -__xla_cpu_runtime_EigenSingleThreadedMatMulF32(const void* run_options_ptr, - float* out, float* lhs, - float* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, - int32 transpose_rhs) { +__xla_cpu_runtime_EigenSingleThreadedMatMulF32( + const void* run_options_ptr, float* out, float* lhs, float* rhs, + tensorflow::int64 m, tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, tensorflow::int32 transpose_rhs) { SingleThreadedMatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void -__xla_cpu_runtime_EigenSingleThreadedMatMulF64(const void* run_options_ptr, - double* out, double* lhs, - double* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, - int32 transpose_rhs) { +__xla_cpu_runtime_EigenSingleThreadedMatMulF64( + const void* run_options_ptr, double* out, double* lhs, double* rhs, + tensorflow::int64 m, tensorflow::int64 n, tensorflow::int64 k, + tensorflow::int32 transpose_lhs, tensorflow::int32 transpose_rhs) { SingleThreadedMatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } @@ -115,8 +114,9 @@ __xla_cpu_runtime_EigenSingleThreadedMatMulF64(const void* run_options_ptr, TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenSingleThreadedMatMulC64( const void* run_options_ptr, std::complex* out, - std::complex* lhs, std::complex* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, int32 transpose_rhs) { + std::complex* lhs, std::complex* rhs, tensorflow::int64 m, + tensorflow::int64 n, tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { SingleThreadedMatMulDispatch>( run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } @@ -124,18 +124,19 @@ __xla_cpu_runtime_EigenSingleThreadedMatMulC64( TF_ATTRIBUTE_NO_SANITIZE_MEMORY void __xla_cpu_runtime_EigenSingleThreadedMatMulC128( const void* run_options_ptr, std::complex* out, - std::complex* lhs, std::complex* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, int32 transpose_rhs) { + std::complex* lhs, std::complex* rhs, tensorflow::int64 m, + tensorflow::int64 n, tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { SingleThreadedMatMulDispatch>( run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); } TF_ATTRIBUTE_NO_SANITIZE_MEMORY void -__xla_cpu_runtime_EigenSingleThreadedMatMulS32(const void* run_options_ptr, - int32* out, int32* lhs, - int32* rhs, int64 m, int64 n, - int64 k, int32 transpose_lhs, - int32 transpose_rhs) { - SingleThreadedMatMulDispatch(run_options_ptr, out, lhs, rhs, m, n, k, - transpose_lhs, transpose_rhs); +__xla_cpu_runtime_EigenSingleThreadedMatMulS32( + const void* run_options_ptr, tensorflow::int32* out, tensorflow::int32* lhs, + tensorflow::int32* rhs, tensorflow::int64 m, tensorflow::int64 n, + tensorflow::int64 k, tensorflow::int32 transpose_lhs, + tensorflow::int32 transpose_rhs) { + SingleThreadedMatMulDispatch( + run_options_ptr, out, lhs, rhs, m, n, k, transpose_lhs, transpose_rhs); }