Merged commit includes the following changes: (#7357)

261202754  by hongkuny<hongkuny@google.com>:

    Use enable_xla flag for classifier and squad, so xla option is exposed to users.

--

PiperOrigin-RevId: 261202754

official/bert/benchmark/bert_benchmark.py

@@ -33,7 +33,6 @@ from official.bert import modeling
 from official.bert import run_classifier
 from official.bert.benchmark import benchmark_utils
 from official.utils.misc import distribution_utils
-from official.utils.misc import keras_utils
 
 # pylint: disable=line-too-long
 PRETRAINED_CHECKPOINT_PATH = 'gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16/bert_model.ckpt'
@@ -55,7 +54,7 @@ class BertClassifyBenchmarkBase(benchmark_utils.BertBenchmarkBase):
     self.num_steps_per_epoch = None
 
   @flagsaver.flagsaver
-  def _run_bert_classifier(self, callbacks=None, use_ds=True, enable_xla=False):
+  def _run_bert_classifier(self, callbacks=None, use_ds=True):
     """Starts BERT classification task."""
     with tf.io.gfile.GFile(FLAGS.input_meta_data_path, 'rb') as reader:
       input_meta_data = json.loads(reader.read().decode('utf-8'))
@@ -73,8 +72,6 @@ class BertClassifyBenchmarkBase(benchmark_utils.BertBenchmarkBase):
     strategy = distribution_utils.get_distribution_strategy(
         distribution_strategy='mirrored' if use_ds else 'off',
         num_gpus=self.num_gpus)
-    # TODO(hongkuny): Enable XLA once we are confident with its performance.
-    keras_utils.set_config_v2(enable_xla)
 
     steps_per_loop = 1
 
@@ -119,13 +116,10 @@ class BertClassifyBenchmarkReal(BertClassifyBenchmarkBase):
                                 training_summary_path,
                                 min_accuracy=0,
                                 max_accuracy=1,
-                                use_ds=True,
-                                enable_xla=False):
+                                use_ds=True):
     """Starts BERT performance benchmark test."""
-
     start_time_sec = time.time()
-    self._run_bert_classifier(
-        callbacks=[self.timer_callback], use_ds=use_ds, enable_xla=enable_xla)
+    self._run_bert_classifier(callbacks=[self.timer_callback], use_ds=use_ds)
     wall_time_sec = time.time() - start_time_sec
 
     with tf.io.gfile.GFile(training_summary_path, 'rb') as reader:
@@ -168,9 +162,10 @@ class BertClassifyBenchmarkReal(BertClassifyBenchmarkBase):
     FLAGS.bert_config_file = self.bert_config_file
     FLAGS.train_batch_size = 4
     FLAGS.eval_batch_size = 4
+    FLAGS.enable_xla = True
 
     summary_path = os.path.join(FLAGS.model_dir, 'training_summary.txt')
-    self._run_and_report_benchmark(summary_path, enable_xla=True)
+    self._run_and_report_benchmark(summary_path)
 
   def benchmark_1_gpu_mrpc_no_dist_strat(self):
     """Test BERT model performance with 1 GPU, no distribution strategy."""
@@ -253,13 +248,11 @@ class BertClassifyAccuracy(BertClassifyBenchmarkBase):
   def _run_and_report_benchmark(self,
                                 training_summary_path,
                                 min_accuracy=0.84,
-                                max_accuracy=0.88,
-                                enable_xla=False):
+                                max_accuracy=0.88):
     """Starts BERT accuracy benchmark test."""
 
     start_time_sec = time.time()
-    self._run_bert_classifier(
-        callbacks=[self.timer_callback], enable_xla=enable_xla)
+    self._run_bert_classifier(callbacks=[self.timer_callback])
     wall_time_sec = time.time() - start_time_sec
 
     with tf.io.gfile.GFile(training_summary_path, 'rb') as reader:
@@ -296,9 +289,9 @@ class BertClassifyAccuracy(BertClassifyBenchmarkBase):
     """Run BERT model accuracy test with 8 GPUs with XLA."""
     self._setup()
     FLAGS.model_dir = self._get_model_dir('benchmark_8_gpu_mrpc_xla')
-
+    FLAGS.enable_xla = True
     summary_path = os.path.join(FLAGS.model_dir, 'training_summary.txt')
-    self._run_and_report_benchmark(summary_path, enable_xla=True)
+    self._run_and_report_benchmark(summary_path)
 
 
 if __name__ == '__main__':

official/bert/benchmark/bert_squad_benchmark.py

@@ -32,7 +32,6 @@ from official.bert import run_squad
 from official.bert.benchmark import benchmark_utils
 from official.bert.benchmark import squad_evaluate_v1_1
 from official.utils.misc import distribution_utils
-from official.utils.misc import keras_utils
 
 # pylint: disable=line-too-long
 PRETRAINED_CHECKPOINT_PATH = 'gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16/bert_model.ckpt'
@@ -131,10 +130,8 @@ class BertSquadBenchmarkReal(BertSquadBenchmarkBase):
 
   def _run_and_report_benchmark(self,
                                 use_ds=True,
-                                enable_xla=False,
                                 run_eagerly=False):
     """Runs the benchmark and reports various metrics."""
-    keras_utils.set_config_v2(enable_xla)
     start_time_sec = time.time()
     self._train_squad(use_ds=use_ds, run_eagerly=run_eagerly)
     wall_time_sec = time.time() - start_time_sec
@@ -164,8 +161,9 @@ class BertSquadBenchmarkReal(BertSquadBenchmarkBase):
     self.num_gpus = 1
     FLAGS.model_dir = self._get_model_dir('benchmark_1_gpu_xla_squad')
     FLAGS.train_batch_size = 4
+    FLAGS.enable_xla = True
 
-    self._run_and_report_benchmark(enable_xla=True)
+    self._run_and_report_benchmark()
 
   def benchmark_1_gpu_no_dist_strat(self):
     """Tests BERT SQuAD model performance with 1 GPU without DS."""
@@ -291,10 +289,8 @@ class BertSquadAccuracy(BertSquadBenchmarkBase):
 
   def _run_and_report_benchmark(self,
                                 use_ds=True,
-                                enable_xla=False,
                                 run_eagerly=False):
     """Runs the benchmark and reports various metrics."""
-    keras_utils.set_config_v2(enable_xla)
     start_time_sec = time.time()
     self._train_squad(use_ds=use_ds, run_eagerly=run_eagerly)
     self._evaluate_squad()
@@ -348,8 +344,9 @@ class BertSquadAccuracy(BertSquadBenchmarkBase):
     self.num_gpus = 8
     FLAGS.model_dir = self._get_model_dir('benchmark_8_gpu_squad_xla')
     FLAGS.train_batch_size = 32
+    FLAGS.enable_xla = True
 
-    self._run_and_report_benchmark(enable_xla=True)
+    self._run_and_report_benchmark()
 
 
 if __name__ == '__main__':

official/bert/common_flags.py

@@ -58,7 +58,7 @@ def define_common_bert_flags():
       loss_scale=True,
       all_reduce_alg=False,
       num_packs=False,
-      enable_xla=False
+      enable_xla=True
   )
 
 

official/bert/run_classifier.py

@@ -36,6 +36,7 @@ from official.bert import model_training_utils
 from official.bert import modeling
 from official.bert import optimization
 from official.bert import tpu_lib
+from official.utils.misc import keras_utils
 
 flags.DEFINE_enum(
     'mode', 'train_and_eval', ['train_and_eval', 'export_only'],
@@ -174,6 +175,8 @@ def run_bert(strategy, input_meta_data):
 
   if FLAGS.mode != 'train_and_eval':
     raise ValueError('Unsupported mode is specified: %s' % FLAGS.mode)
+  # Enables XLA in Session Config. Should not be set for TPU.
+  keras_utils.set_config_v2(FLAGS.enable_xla)
 
   bert_config = modeling.BertConfig.from_json_file(FLAGS.bert_config_file)
   epochs = FLAGS.num_train_epochs

official/bert/run_squad.py

@@ -37,6 +37,7 @@ from official.bert import optimization
 from official.bert import squad_lib
 from official.bert import tokenization
 from official.bert import tpu_lib
+from official.utils.misc import keras_utils
 
 flags.DEFINE_bool('do_train', False, 'Whether to run training.')
 flags.DEFINE_bool('do_predict', False, 'Whether to run eval on the dev set.')
@@ -181,6 +182,8 @@ def train_squad(strategy,
   if strategy:
     logging.info('Training using customized training loop with distribution'
                  ' strategy.')
+  # Enables XLA in Session Config. Should not be set for TPU.
+  keras_utils.set_config_v2(FLAGS.enable_xla)
 
   use_float16 = common_flags.use_float16()
   if use_float16: