[XLA] Add exhaustive tests for log1p and expm1.

PiperOrigin-RevId: 235284387

tensorflow/compiler/xla/tests/exhaustive_op_test.cc

@@ -486,6 +486,15 @@ XLA_TEST_P(ExhaustiveOpTest, Log) {
   Run(Log, std::log);
 }
 
+XLA_TEST_P(ExhaustiveOpTest, Log1p) {
+  if (platform_ != "Host" && platform_ != "CUDA" && ty_ == F32) {
+    abs_err_ = 0.001;
+    rel_err_ = 0.001;
+  }
+
+  Run(Log1p, std::log1p);
+}
+
 XLA_TEST_P(ExhaustiveOpTest, Exp) {
   if (platform_ == "Host" && ty_ == F32) {
     // TODO(b/73142289): The vectorized Exp implementation gives results outside
@@ -504,6 +513,25 @@ XLA_TEST_P(ExhaustiveOpTest, Exp) {
   Run(Exp, std::exp);
 }
 
+XLA_TEST_P(ExhaustiveOpTest, Expm1) {
+  // Expm1 has the same erroneous behavior on CPU as Exp.
+  if (platform_ == "Host" && ty_ == F32) {
+    // TODO(b/73142289): The vectorized Exp implementation gives results outside
+    // our error spec in this range.
+    known_incorrect_begin_ = 1107296256 + 11583654;
+    known_incorrect_end_ = 1107296256 + 11629080;
+  } else if (platform_ == "Host" && ty_ == BF16) {
+    // TODO(jlebar): Is this a rounding error?  Why doesn't it occur on XLA:GPU?
+    //
+    // Mismatch on 88.5 (0x42b1).
+    //   Expected 2.72491739e+38 (0x7f4d), but got inf (0x7f80).
+    known_incorrect_begin_ = 0x42b1;
+    known_incorrect_end_ = 0x42b2;
+  }
+
+  Run(Expm1, std::expm1);
+}
+
 // It feels a little overkill to exhaustively test sqrt and pow(x, 0.5), but
 // this *did* find a bug, namely that some backends were assuming sqrt(x) ==
 // pow(x, 0.5), but this is not true for x == -inf.