Merge pull request tensorflow#35548 from compnerd/r2.1-windows-build

r2.1 cherry-pick request: windows build support

Author: mihaimaruseac

.bazelrc

@@ -160,6 +160,10 @@ build:c++17 --cxxopt=-std=c++1z
 build:c++17 --cxxopt=-stdlib=libc++
 build:c++1z --config=c++17
 
+# Tensorflow uses M_* math constants that only get defined by MSVC headers if
+# _USE_MATH_DEFINES is defined.
+build:windows --copt=/D_USE_MATH_DEFINES
+
 # Default paths for TF_SYSTEM_LIBS
 build --define=PREFIX=/usr
 build --define=LIBDIR=$(PREFIX)/lib

configure.py

@@ -1233,7 +1233,7 @@ def set_windows_build_flags(environ_cp):
   # Fix winsock2.h conflicts
   write_to_bazelrc(
       'build --copt=-DWIN32_LEAN_AND_MEAN --host_copt=-DWIN32_LEAN_AND_MEAN '
-      '--copt=-DNOGDI --host_copt=-DNOGDI')
+      '--copt=-DNOGDI --host_copt=-DNOGDI --copt=-D_USE_MATH_DEFINES')
   # Output more verbose information when something goes wrong
   write_to_bazelrc('build --verbose_failures')
   # The host and target platforms are the same in Windows build. So we don't

tensorflow/cc/gradients/math_grad.cc

@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 
-#define _USE_MATH_DEFINES
 #include <cmath>
 
 #include "tensorflow/cc/ops/array_ops_internal.h"

tensorflow/compiler/xla/client/lib/math.cc

@@ -15,9 +15,7 @@ limitations under the License.
 
 #include "tensorflow/compiler/xla/client/lib/math.h"
 
-// This macro is required to make MSVC defines math constants in math.h
-#define _USE_MATH_DEFINES
-#include <math.h>
+#include <cmath>
 
 #include "tensorflow/compiler/xla/client/lib/arithmetic.h"
 #include "tensorflow/compiler/xla/client/lib/constants.h"

tensorflow/compiler/xla/client/lib/tridiagonal.cc

@@ -36,6 +36,8 @@ namespace {
 struct TridiagonalSystemShape {
   const int64 rank;
   const int64 num_equations;
+  TridiagonalSystemShape(int64 rk, int64 num_eqs)
+      : rank(rk), num_equations(num_eqs) {}
 };
 
 Status CheckSecondToLastDimension(const Shape& op_shape, int64 rank,
@@ -109,9 +111,7 @@ StatusOr<TridiagonalSystemShape> CheckSystemAndReturnShape(XlaOp lower_diagonal,
   TF_RETURN_IF_ERROR(CheckSecondToLastDimension(upper_diagonal_shape, rank, 1,
                                                 "upper diagonal"));
 
-  TridiagonalSystemShape result = {.rank = rank,
-                                   .num_equations = num_equations};
-  return result;
+  return TridiagonalSystemShape(rank, num_equations);
 }
 
 XlaOp Coefficient(XlaOp operand, int64 i) {

tensorflow/compiler/xla/service/dynamic_dimension_inference.cc

@@ -469,7 +469,7 @@ Status DynamicDimensionInferenceVisitor::HandleSetDimensionSize(
     // Propagate dynamic dimension indicated by this set dimension size
     // instruction.
     parent_->SetDynamicSize(hlo, {}, hlo->dimension(), hlo->mutable_operand(1),
-                            {.stride = 1, .multiple_of = 1});
+                            DimensionConstraint(1, 1));
   }
 
   // Also Propagate dynamic dimension already set by operands.
@@ -813,7 +813,7 @@ Status DynamicDimensionInferenceVisitor::HandleReshape(HloInstruction* hlo) {
 
           parent_->SetDynamicSize(
               reshape, {}, output_dynamic_dimension, new_dynamic_size,
-              {.stride = 1, .multiple_of = constraint.multiple_of / divisor});
+              DimensionConstraint(1, constraint.multiple_of / divisor));
         }
 
         if (input_dim_size < output_dim_size) {
@@ -850,12 +850,12 @@ Status DynamicDimensionInferenceVisitor::HandleReshape(HloInstruction* hlo) {
               hlo->parent()->AddInstruction(HloInstruction::CreateBinary(
                   output_dynamic_size->shape(), HloOpcode::kMultiply,
                   new_dynamic_size, operand_dynamic_size));
+          int64 new_multiple_of_constraint =
+              constraint.multiple_of * output_dim_size /
+              operand->shape().dimensions(input_dynamic_dimension);
           parent_->SetDynamicSize(
               reshape, {}, output_dynamic_dimension, new_dynamic_size,
-              {.stride = 1,
-               .multiple_of =
-                   constraint.multiple_of * output_dim_size /
-                   operand->shape().dimensions(input_dynamic_dimension)});
+              DimensionConstraint(1, new_multiple_of_constraint));
         }
 
         return Status::OK();
@@ -1227,7 +1227,7 @@ Status DynamicDimensionInferenceVisitor::HandleParameter(HloInstruction* hlo) {
         parent_->SetDynamicSize(target_parameter,
                                 dynamic_dimension.parameter_index,
                                 dynamic_dimension.dimension, dynamic_size,
-                                {.stride = 1, .multiple_of = 1});
+                                DimensionConstraint(1, 1));
         return Status::OK();
       });
 }

tensorflow/compiler/xla/service/dynamic_dimension_inference.h

@@ -149,6 +149,9 @@ class DynamicDimensionInference {
   //
   //
   struct DimensionConstraint {
+    explicit DimensionConstraint(int64 s, int64 m)
+        : stride(s), multiple_of(m) {}
+    DimensionConstraint() : stride(1), multiple_of(1) {}
     // Stride represents the distance of a newly placed element and the previous
     // placed element on this dynamic dimension.
     int64 stride;

tensorflow/compiler/xla/service/hlo_parser.cc

@@ -2611,18 +2611,37 @@ struct MinMaxFiniteValue<bfloat16> {
   static double min() { return -max(); }
 };
 
+// MSVC's standard C++ library does not define isnan/isfinite for integer types.
+// To work around that we will need to provide our own.
+template <typename T>
+std::enable_if_t<std::is_floating_point<T>::value, bool> IsFinite(T val) {
+  return std::isfinite(val);
+}
+template <typename T>
+std::enable_if_t<std::is_floating_point<T>::value, bool> IsNaN(T val) {
+  return std::isnan(val);
+}
+template <typename T>
+std::enable_if_t<std::is_integral<T>::value, bool> IsFinite(T val) {
+  return std::isfinite(static_cast<double>(val));
+}
+template <typename T>
+std::enable_if_t<std::is_integral<T>::value, bool> IsNaN(T val) {
+  return std::isnan(static_cast<double>(val));
+}
+
 template <typename LiteralNativeT, typename ParsedElemT>
 bool HloParserImpl::CheckParsedValueIsInRange(LocTy loc, ParsedElemT value) {
   if (std::is_floating_point<ParsedElemT>::value) {
     auto value_as_native_t = static_cast<LiteralNativeT>(value);
     auto value_double_converted = static_cast<ParsedElemT>(value_as_native_t);
-    if (!std::isfinite(value) || std::isfinite(value_double_converted)) {
+    if (!IsFinite(value) || IsFinite(value_double_converted)) {
       value = value_double_converted;
     }
   }
   PrimitiveType literal_ty =
       primitive_util::NativeToPrimitiveType<LiteralNativeT>();
-  if (std::isnan(value) ||
+  if (IsNaN(value) ||
       (std::numeric_limits<ParsedElemT>::has_infinity &&
        (std::numeric_limits<ParsedElemT>::infinity() == value ||
         -std::numeric_limits<ParsedElemT>::infinity() == value))) {

tensorflow/core/lib/random/random_distributions.h

@@ -18,10 +18,7 @@ limitations under the License.
 
 #include <string.h>
 
-#define _USE_MATH_DEFINES
-#include <math.h>
 #include <cmath>
-#undef _USE_MATH_DEFINES
 
 #include <algorithm>
 #include <type_traits>

tensorflow/core/lib/random/random_distributions_test.cc

@@ -15,8 +15,8 @@ limitations under the License.
 
 #include "tensorflow/core/lib/random/random_distributions.h"
 
-#include <math.h>
 #include <algorithm>
+#include <cmath>
 #include <functional>
 #include <numeric>
 #include <unordered_map>

tensorflow/lite/experimental/microfrontend/lib/window_util.c

@@ -14,8 +14,6 @@ limitations under the License.
 ==============================================================================*/
 #include "tensorflow/lite/experimental/microfrontend/lib/window_util.h"
 
-// This macro is required to make MSVC defines math constants in math.h
-#define _USE_MATH_DEFINES
 #include <math.h>
 #include <stdio.h>
 #include <stdlib.h>

tensorflow/tensorflow.bzl

@@ -263,6 +263,8 @@ def get_win_copts(is_external = False):
         # "/EHs-c-",
         "/wd4577",
         "/DNOGDI",
+        # Also see build:windows lines in tensorflow/opensource_only/.bazelrc
+        # where we set some other options globally.
     ]
     if is_external:
         return WINDOWS_COPTS + ["/UTF_COMPILE_LIBRARY"]