Add specialization of method Array::FillRandom() for complex64 type.

Fix comments.

PiperOrigin-RevId: 285447090
Change-Id: I6a328bedbdd19f7892a6cbe2dbde42067e252880

tensorflow/compiler/xla/BUILD

@@ -522,6 +522,7 @@ cc_library(
 
 cc_library(
     name = "array",
+    srcs = ["array.cc"],
     hdrs = ["array.h"],
     deps = [
         ":status",

tensorflow/compiler/xla/array.cc

@@ -0,0 +1,32 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/compiler/xla/array.h"
+
+namespace xla {
+
+// Specialization of FillRandom() method for complex64 type. Uses real part of
+// the stddev parameter as the standard deviation value.
+template <>
+void Array<complex64>::FillRandom(const complex64& stddev, const double mean,
+                                  const int seed) {
+  std::mt19937 g(seed);
+  std::normal_distribution<double> distribution(mean, std::real(stddev));
+  for (int64 i = 0; i < num_elements(); ++i) {
+    values_[i] = complex64(distribution(g), distribution(g));
+  }
+}
+
+}  // namespace xla

tensorflow/compiler/xla/array.h

@@ -575,6 +575,12 @@ class Array {
   std::unique_ptr<T[]> values_;
 };
 
+// Specialization of FillRandom() method for complex64 type. Uses real part of
+// the stddev parameter as the standard deviation value.
+template <>
+void Array<complex64>::FillRandom(const complex64& stddev, const double mean,
+                                  const int seed);
+
 }  // namespace xla
 
 #endif  // TENSORFLOW_COMPILER_XLA_ARRAY_H_

tensorflow/compiler/xla/service/hlo_instructions.h

@@ -1103,8 +1103,7 @@ class HloConvolutionInstruction : public HloInstruction {
   void set_feature_group_count(int64 num_feature_groups) {
     feature_group_count_ = num_feature_groups;
   }
-  // The number of feature groups. Must be a divisor of the input batch
+  // The number of batch groups. Must be a divisor of the input batch dimension.
-  // dimension.
   int64 batch_group_count() const { return batch_group_count_; }
   void set_batch_group_count(int64 num_batch_groups) {
     batch_group_count_ = num_batch_groups;
@@ -1138,8 +1137,7 @@ class HloConvolutionInstruction : public HloInstruction {
   // The number of feature groups. Must be a divisor of the input feature
   // dimension and output feature dimension.
   int64 feature_group_count_;
-  // The number of feature groups. Must be a divisor of the input batch
+  // The number of batch groups. Must be a divisor of the input batch dimension.
-  // dimension.
   int64 batch_group_count_;
   // Describes the window used for a convolution.
   Window window_;