[TensorExpr] Clang-format test/cpp/tensorexpr/*. (pytorch#36615)

Summary: Pull Request resolved: pytorch#36615

Test Plan: Imported from OSS

Differential Revision: D21027733

Pulled By: ZolotukhinM

fbshipit-source-id: e19cd85c1634f4e40805814ac71eec719d6587f8

Author: Mikhail Zolotukhin

test/cpp/tensorexpr/gtest.cpp

@@ -7,7 +7,7 @@ namespace jit {
 
 #define TENSOREXPR_GTEST(name) \
   TEST(TensorExprTest, name) { \
-    test##name();       \
+    test##name();              \
   }
 TH_FORALL_TENSOREXPR_TESTS(TENSOREXPR_GTEST)
 #undef TENSOREXPR_GTEST

test/cpp/tensorexpr/gtest_assert_float_eq.h

@@ -1,6 +1,6 @@
 #pragma once
 
-#include <cmath> 
+#include <cmath>
 // Copyright 2005, Google Inc.
 // All rights reserved.
 //
@@ -40,12 +40,12 @@ using Bits = uint32_t;
 // this avoids the "dereferencing type-punned pointer
 // will break strict-aliasing rules" error
 union Float {
-    float float_;
-    Bits bits_;
+  float float_;
+  Bits bits_;
 };
 
 // # of bits in a number.
-static const size_t kBitCount = 8*sizeof(Bits);
+static const size_t kBitCount = 8 * sizeof(Bits);
 // The mask for the sign bit.
 static const Bits kSignBitMask = static_cast<Bits>(1) << (kBitCount - 1);
 
@@ -66,23 +66,24 @@ static const Bits kSignBitMask = static_cast<Bits>(1) << (kBitCount - 1);
 //
 // Read http://en.wikipedia.org/wiki/Signed_number_representations
 // for more details on signed number representations.
-static Bits SignAndMagnitudeToBiased(const Bits &sam) {
-    if (kSignBitMask & sam) {
-        // sam represents a negative number.
-        return ~sam + 1;
-    } else {
-        // sam represents a positive number.
-        return kSignBitMask | sam;
-    }
+static Bits SignAndMagnitudeToBiased(const Bits& sam) {
+  if (kSignBitMask & sam) {
+    // sam represents a negative number.
+    return ~sam + 1;
+  } else {
+    // sam represents a positive number.
+    return kSignBitMask | sam;
+  }
 }
 
 // Given two numbers in the sign-and-magnitude representation,
 // returns the distance between them as an unsigned number.
-static Bits DistanceBetweenSignAndMagnitudeNumbers(const Bits &sam1,
-                                                    const Bits &sam2) {
-    const Bits biased1 = SignAndMagnitudeToBiased(sam1);
-    const Bits biased2 = SignAndMagnitudeToBiased(sam2);
-    return (biased1 >= biased2) ? (biased1 - biased2) : (biased2 - biased1);
+static Bits DistanceBetweenSignAndMagnitudeNumbers(
+    const Bits& sam1,
+    const Bits& sam2) {
+  const Bits biased1 = SignAndMagnitudeToBiased(sam1);
+  const Bits biased2 = SignAndMagnitudeToBiased(sam2);
+  return (biased1 >= biased2) ? (biased1 - biased2) : (biased2 - biased1);
 }
 
 // How many ULP's (Units in the Last Place) we want to tolerate when
@@ -106,13 +107,13 @@ static const size_t kMaxUlps = 4;
 //   - treats really large numbers as almost equal to infinity.
 //   - thinks +0.0 and -0.0 are 0 DLP's apart.
 inline bool AlmostEquals(float lhs, float rhs) {
-    // The IEEE standard says that any comparison operation involving
-    // a NAN must return false.
-    if (std::isnan(lhs) || std::isnan(rhs))
-      return false;
+  // The IEEE standard says that any comparison operation involving
+  // a NAN must return false.
+  if (std::isnan(lhs) || std::isnan(rhs))
+    return false;
 
-    Float l = {lhs};
-    Float r = {rhs};
+  Float l = {lhs};
+  Float r = {rhs};
 
-    return DistanceBetweenSignAndMagnitudeNumbers(l.bits_, r.bits_) <= kMaxUlps;
+  return DistanceBetweenSignAndMagnitudeNumbers(l.bits_, r.bits_) <= kMaxUlps;
 }

test/cpp/tensorexpr/test_aten.cpp

@@ -506,7 +506,8 @@ void testATenmaxInt() {
   VarHandle index = VarHandle("index", kInt);
   ExprHandle load_a = Load::make(a_buf, {index}, 1);
   ExprHandle load_b = Load::make(b_buf, {index}, 1);
-  Stmt* store_c = Store::make(c_buf, {index}, Max::make(load_a, load_b, true), 1);
+  Stmt* store_c =
+      Store::make(c_buf, {index}, Max::make(load_a, load_b, true), 1);
   Stmt* stmt = For::make(index, 0, kTotalSize, store_c);
 
   PaddedBuffer<int> a_v(kTotalSize);
@@ -538,7 +539,8 @@ void testATenmaxFloat() {
   VarHandle index = VarHandle("index", kInt);
   ExprHandle load_a = Load::make(a_buf, {index}, 1);
   ExprHandle load_b = Load::make(b_buf, {index}, 1);
-  Stmt* store_c = Store::make(c_buf, {index}, Max::make(load_a, load_b, true), 1);
+  Stmt* store_c =
+      Store::make(c_buf, {index}, Max::make(load_a, load_b, true), 1);
   Stmt* stmt = For::make(index, 0, kTotalSize, store_c);
 
   PaddedBuffer<float> a_v(kTotalSize);
@@ -570,7 +572,8 @@ void testATenminInt() {
   VarHandle index = VarHandle("index", kInt);
   ExprHandle load_a = Load::make(a_buf, {index}, 1);
   ExprHandle load_b = Load::make(b_buf, {index}, 1);
-  Stmt* store_c = Store::make(c_buf, {index}, Min::make(load_a, load_b, true), 1);
+  Stmt* store_c =
+      Store::make(c_buf, {index}, Min::make(load_a, load_b, true), 1);
   Stmt* stmt = For::make(index, 0, kTotalSize, store_c);
 
   PaddedBuffer<int> a_v(kTotalSize);
@@ -602,7 +605,8 @@ void testATenminFloat() {
   VarHandle index = VarHandle("index", kInt);
   ExprHandle load_a = Load::make(a_buf, {index}, 1);
   ExprHandle load_b = Load::make(b_buf, {index}, 1);
-  Stmt* store_c = Store::make(c_buf, {index}, Min::make(load_a, load_b, true), 1);
+  Stmt* store_c =
+      Store::make(c_buf, {index}, Min::make(load_a, load_b, true), 1);
   Stmt* stmt = For::make(index, 0, kTotalSize, store_c);
 
   PaddedBuffer<float> a_v(kTotalSize);

test/cpp/tensorexpr/test_loopnest.cpp

@@ -1,8 +1,8 @@
+#include <test/cpp/tensorexpr/test_base.h>
 #include <memory>
 #include <sstream>
 #include <stdexcept>
 #include <unordered_map>
-#include <test/cpp/tensorexpr/test_base.h>
 
 #include <test/cpp/tensorexpr/padded_buffer.h>
 #include <torch/csrc/jit/tensorexpr/bounds_inference.h>
@@ -90,8 +90,7 @@ void testExprSimple02() {
             x_inner,
             0,
             4,
-            For::make(
-                y, 0, 5, Store::make(f, {x_1, y}, func(x_1, y), 1))));
+            For::make(y, 0, 5, Store::make(f, {x_1, y}, func(x_1, y), 1))));
     ExprHandle x_2 = x_tail + x_outer_end * 4;
     For* stmt2 = For::make(
         x_tail,
@@ -159,8 +158,7 @@ void testExprSplitWithTailNone() {
             x_inner,
             0,
             4,
-            For::make(
-                y, 0, 5, Store::make(f, {x_1, y}, func(x_1, y), 1))));
+            For::make(y, 0, 5, Store::make(f, {x_1, y}, func(x_1, y), 1))));
 
     std::ostringstream oss_ref;
     oss_ref << *stmt;
@@ -705,8 +703,7 @@ void testBoundsInference_4() {
   }
   {
     // Infer bounds on the inner loop body's scope
-    const std::vector<TensorAccessBoundsInfo>& bounds_info =
-        inferBounds(body);
+    const std::vector<TensorAccessBoundsInfo>& bounds_info = inferBounds(body);
     auto bounds_info_map = convertBoundsInfoToMap(bounds_info);
 
     ASSERT_EQ(bounds_info_map.at(a.data()).kind, kLoad);
@@ -824,8 +821,7 @@ void testBoundsInference_6() {
   }
   {
     // Infer bounds on the inner loop body's scope
-    const std::vector<TensorAccessBoundsInfo>& bounds_info =
-        inferBounds(body);
+    const std::vector<TensorAccessBoundsInfo>& bounds_info = inferBounds(body);
     auto bounds_info_map = convertBoundsInfoToMap(bounds_info);
 
     ASSERT_EQ(bounds_info_map.at(a.data()).kind, kLoad);