From e2856cfa21a640c0d9f8a04d2ec4d4fc2b2f2293 Mon Sep 17 00:00:00 2001
From: Ryan Hill <ryanhill@microsoft.com>
Date: Wed, 5 May 2021 18:53:46 -0700
Subject: [PATCH] Undo edit to file

---
 .../contrib_ops/cpu/bert/embed_layer_norm.cc  | 89 +++++++++----------
 1 file changed, 43 insertions(+), 46 deletions(-)

diff --git a/onnxruntime/contrib_ops/cpu/bert/embed_layer_norm.cc b/onnxruntime/contrib_ops/cpu/bert/embed_layer_norm.cc
index 5bc974711d..952ad156c1 100644
--- a/onnxruntime/contrib_ops/cpu/bert/embed_layer_norm.cc
+++ b/onnxruntime/contrib_ops/cpu/bert/embed_layer_norm.cc
@@ -10,7 +10,6 @@
 
 namespace onnxruntime {
 namespace contrib {
-
 // These ops are internal-only, so register outside of onnx
 #define REGISTER_KERNEL_TYPED(T)                                  \
   ONNX_OPERATOR_TYPED_KERNEL_EX(                                  \
@@ -73,53 +72,51 @@ Status EmbedLayerNorm<T>::Compute(OpKernelContext* context) const {
     std::atomic_bool failed{false};
 
     int n = batch_size * sequence_length;
-    concurrency::ThreadPool::TryBatchParallelFor(
-        context->GetOperatorThreadPool(), n, [=, &failed](ptrdiff_t index) {
-          int word_col_index = input_ids_data[index];
-          if (word_col_index < 0 || word_col_index >= word_embedding_length) {
-            failed.store(true, std::memory_order_release);
-            return;
-          }
-          int position_col_index = index % sequence_length;
-          if (position_col_index >= position_embedding_length) {
-            failed.store(true, std::memory_order_release);
-            return;
-          }
-          int segment_col_index = 0;
-          if (nullptr != segment_ids_data) {
-            segment_col_index = segment_ids_data[index];
-            if (segment_col_index < 0 || segment_col_index >= segment_embedding_length) {
-              failed.store(true, std::memory_order_release);
-              return;
-            }
-          }
+    concurrency::ThreadPool::TryBatchParallelFor(context->GetOperatorThreadPool(), n, [=, &failed](ptrdiff_t index) {
+      int word_col_index = input_ids_data[index];
+      if (word_col_index < 0 || word_col_index >= word_embedding_length) {
+        failed.store(true, std::memory_order_release);
+        return;
+      }
+      int position_col_index = index % sequence_length;
+      if (position_col_index >= position_embedding_length) {
+        failed.store(true, std::memory_order_release);
+        return;
+      }
+      int segment_col_index = 0;
+      if (nullptr != segment_ids_data) {
+        segment_col_index = segment_ids_data[index];
+        if (segment_col_index < 0 || segment_col_index >= segment_embedding_length) {
+          failed.store(true, std::memory_order_release);
+          return;
+        }
+      }
 
-          T* y = output_data + index * hidden_size;
-          const T* input_word_embedding = word_embedding_data + word_col_index * hidden_size;
-          const T* input_position_embedding = position_embedding_data + position_col_index * hidden_size;
-          const T* input_segment_embedding = (nullptr == segment_embedding_data) ? nullptr : segment_embedding_data + segment_col_index * hidden_size;
+      T* y = output_data + index * hidden_size;
+      const T* input_word_embedding = word_embedding_data + word_col_index * hidden_size;
+      const T* input_position_embedding = position_embedding_data + position_col_index * hidden_size;
+      const T* input_segment_embedding = (nullptr == segment_embedding_data) ? nullptr : segment_embedding_data + segment_col_index * hidden_size;
 
-          T sum = static_cast<T>(0);
-          for (int i = 0; i < hidden_size; i++) {
-            T subtotal = input_word_embedding[i] + input_position_embedding[i];
-            if (nullptr != segment_embedding_data)
-              subtotal += input_segment_embedding[i];
-            y[i] = subtotal;
-            sum += subtotal;
-          }
-          T mean = sum / hidden_size;
-          sum = 0;
-          for (int i = 0; i < hidden_size; i++) {
-            T a = y[i] - mean;
-            y[i] = a;
-            sum += a * a;
-          }
-          T e = sqrt(sum / hidden_size + static_cast<T>(epsilon_));
-          for (int i = 0; i < hidden_size; i++) {
-            y[i] = y[i] / e * gamma_data[i] + beta_data[i];
-          }
-        },
-        0);
+      T sum = static_cast<T>(0);
+      for (int i = 0; i < hidden_size; i++) {
+        T subtotal = input_word_embedding[i] + input_position_embedding[i];
+        if (nullptr != segment_embedding_data)
+          subtotal += input_segment_embedding[i];
+        y[i] = subtotal;
+        sum += subtotal;
+      }
+      T mean = sum / hidden_size;
+      sum = 0;
+      for (int i = 0; i < hidden_size; i++) {
+        T a = y[i] - mean;
+        y[i] = a;
+        sum += a * a;
+      }
+      T e = sqrt(sum / hidden_size + static_cast<T>(epsilon_));
+      for (int i = 0; i < hidden_size; i++) {
+        y[i] = y[i] / e * gamma_data[i] + beta_data[i];
+      }
+    }, 0);
 
     if (failed.load(std::memory_order_acquire)) {
       return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "input index out of range");