Add ResNet tests for NHWC and layout optimizer off. (#7018)

* layout off for some tests and channels last.

* 8 gpu tests channels_last

* more layout off tests.

official/resnet/keras/keras_common.py

@@ -156,6 +156,15 @@ def get_config_proto_v1():
     # OOM and performance regression.
     config.graph_options.rewrite_options.pin_to_host_optimization = (
         rewriter_config_pb2.RewriterConfig.OFF)
+  # TODO(b/76028325): Remove when generic layout optimizer will be ready.
+  if not FLAGS.enable_grappler_layout_optimizer:
+    if config is None:
+      config = tf.compat.v1.ConfigProto()
+    # Disable LayoutOptimizer in grappler, because it might de-optimize fp16
+    # graphs, and force NCHW data format in all convolutions and batch
+    # normalizations.
+    config.graph_options.rewrite_options.layout_optimizer = (
+        rewriter_config_pb2.RewriterConfig.OFF)
   return config
 
 
@@ -166,7 +175,15 @@ def set_config_v2():
     # Disable PinToHostOptimizer in grappler when enabling XLA because it
     # causes OOM and performance regression.
     tf.config.optimizer.set_experimental_options(
-        {"pin_to_host_optimization": False}
+        {'pin_to_host_optimization': False}
+    )
+  # TODO(b/76028325): Remove when generic layout optimizer will be ready.
+  if not FLAGS.enable_grappler_layout_optimizer:
+    # Disable LayoutOptimizer in grappler, because it might de-optimize fp16
+    # graphs, and force NCHW data format in all convolutions and batch
+    # normalizations.
+    tf.config.optimizer.set_experimental_options(
+        {'layout_optimizer': False}
     )
 
 
@@ -326,7 +343,15 @@ def define_keras_flags():
   flags.DEFINE_boolean(
       name='enable_get_next_as_optional', default=False,
       help='Enable get_next_as_optional behavior in DistributedIterator.')
-
+  # TODO(b/76028325): Remove when generic layout optimizer is ready.
+  flags.DEFINE_boolean(
+      name='enable_grappler_layout_optimizer',
+      default=True,
+      help='Enable Grappler layout optimizer. Currently Grappler can '
+           'de-optimize fp16 graphs byt forcing NCHW layout for all '
+           'convolutions and batch normalizations, and this flag allows to '
+           'disable it.'
+  )
 
 def get_synth_input_fn(height, width, num_channels, num_classes,
                        dtype=tf.float32, drop_remainder=True):

official/resnet/keras/keras_imagenet_benchmark.py

@@ -292,6 +292,18 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.batch_size = 128
     self._run_and_report_benchmark()
 
+  def benchmark_1_gpu_layout_off(self):
+    """Test Keras model with 1 GPU and no layout optimizer."""
+    self._setup()
+
+    FLAGS.num_gpus = 1
+    FLAGS.enable_eager = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir('benchmark_1_gpu_layout_off')
+    FLAGS.batch_size = 128
+    FLAGS.enable_grappler_layout_optimizer = False
+    self._run_and_report_benchmark()
+
   def benchmark_xla_1_gpu(self):
     """Test Keras model with XLA and 1 GPU."""
     self._setup()
@@ -304,6 +316,18 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.batch_size = 128
     self._run_and_report_benchmark()
 
+  def benchmark_xla_1_gpu_layout_off(self):
+    """Test Keras model with 1 GPU and xla w/no layout optimizer."""
+    self._setup()
+
+    FLAGS.num_gpus = 1
+    FLAGS.enable_eager = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir('benchmark_xla_1_gpu_layout_off')
+    FLAGS.batch_size = 128
+    FLAGS.enable_grappler_layout_optimizer = False
+    self._run_and_report_benchmark()
+
   def benchmark_1_gpu_fp16(self):
     """Test Keras model with 1 GPU and fp16."""
     self._setup()
@@ -316,6 +340,20 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.batch_size = 256
     self._run_and_report_benchmark()
 
+  def benchmark_1_gpu_fp16_layout_off(self):
+    """Test Keras model with 1 GPU and FP16 w/no layout optimizer."""
+    self._setup()
+
+    FLAGS.num_gpus = 1
+    FLAGS.enable_eager = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir('benchmark_1_gpu_fp16_layout_off')
+    FLAGS.dtype = 'fp16'
+    FLAGS.batch_size = 256
+    FLAGS.enable_grappler_layout_optimizer = False
+    FLAGS.data_format = 'channels_last'
+    self._run_and_report_benchmark()
+
   def benchmark_1_gpu_fp16_dynamic(self):
     """Test Keras model with 1 GPU, fp16, and dynamic loss scaling."""
     self._setup()
@@ -342,6 +380,21 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.batch_size = 256
     self._run_and_report_benchmark()
 
+  def benchmark_xla_1_gpu_fp16_layout_off(self):
+    """Test Keras model with FP16+XLA w/no layout optimizer."""
+    self._setup()
+
+    FLAGS.num_gpus = 1
+    FLAGS.enable_eager = True
+    FLAGS.enable_xla = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir('benchmark_xla_1_gpu_fp16_layout_off')
+    FLAGS.dtype = 'fp16'
+    FLAGS.batch_size = 256
+    FLAGS.enable_grappler_layout_optimizer = False
+    FLAGS.data_format = 'channels_last'
+    self._run_and_report_benchmark()
+
   def benchmark_xla_1_gpu_fp16_tweaked(self):
     """Test Keras model with XLA, 1 GPU, fp16, and manual config tuning."""
     self._setup()
@@ -358,8 +411,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_xla_1_gpu_fp16_slack(self):
-    """Test Keras model with XLA, 1 GPU, fp16, and tf.data's experimental_slack
-       functionality."""
+    """Test Keras model tf.data's experimental_slack functionality."""
     self._setup()
 
     FLAGS.num_gpus = 1
@@ -435,9 +487,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_xla_1_gpu_fp16_tweaked(self):
-    """Test Keras model in legacy graph mode with 1 GPU, fp16, XLA, and manual
-       config tuning.
-    """
+    """Test Keras model in legacy graph with 1 GPU, fp16, XLA, and tuning."""
     self._setup()
 
     FLAGS.num_gpus = 1
@@ -453,9 +503,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_xla_1_gpu_fp16_slack(self):
-    """Test Keras model in legacy graph mode with 1 GPU, fp16, XLA, and
-       tf.data's experimental_slack functionality.
-    """
+    """Test model in legacy graph with tf.data's experimental_slack."""
     self._setup()
 
     FLAGS.num_gpus = 1
@@ -556,6 +604,20 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.batch_size = 256 * 8  # 8 GPUs
     self._run_and_report_benchmark()
 
+  def benchmark_8_gpu_fp16_layout_off(self):
+    """Test Keras model with 8 GPUs, fp16, and layout off."""
+    self._setup()
+
+    FLAGS.num_gpus = 8
+    FLAGS.dtype = 'fp16'
+    FLAGS.enable_eager = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir('benchmark_8_gpu_fp16_layout_off')
+    FLAGS.batch_size = 256 * 8  # 8 GPUs
+    FLAGS.enable_grappler_layout_optimizer = False
+    FLAGS.data_format = 'channels_last'
+    self._run_and_report_benchmark()
+
   def benchmark_8_gpu_fp16_cloning(self):
     """Test Keras model with 8 GPUs, fp16 and cloning."""
     self._setup()
@@ -583,6 +645,24 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.tf_gpu_thread_mode = 'gpu_private'
     self._run_and_report_benchmark()
 
+  def benchmark_8_gpu_fp16_tweaked_layout_off(self):
+    """Test Keras model with 8 GPUs, fp16,tuning, and layout off."""
+    self._setup()
+
+    FLAGS.num_gpus = 8
+    FLAGS.dtype = 'fp16'
+    FLAGS.enable_eager = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir(
+        'benchmark_8_gpu_fp16_tweaked_layout_off')
+    FLAGS.batch_size = 256 * 8  # 8 GPUs
+    FLAGS.use_tensor_lr = True
+    FLAGS.tf_gpu_thread_mode = 'gpu_private'
+    FLAGS.data_delay_prefetch = True
+    FLAGS.enable_grappler_layout_optimizer = False
+    FLAGS.data_format = 'channels_last'
+    self._run_and_report_benchmark()
+
   def benchmark_8_gpu_fp16_cloning_tweaked(self):
     """Test Keras model with 8 GPUs, fp16, cloning, and manual config tuning."""
     self._setup()
@@ -647,6 +727,21 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.batch_size = 256 * 8  # 8 GPUs
     self._run_and_report_benchmark()
 
+  def benchmark_xla_8_gpu_fp16_layout_off(self):
+    """Test Keras model with XLA, 8 GPUs, fp16, and layout off."""
+    self._setup()
+
+    FLAGS.num_gpus = 8
+    FLAGS.dtype = 'fp16'
+    FLAGS.enable_eager = True
+    FLAGS.enable_xla = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.model_dir = self._get_model_dir('benchmark_xla_8_gpu_fp16_layout_off')
+    FLAGS.batch_size = 256 * 8  # 8 GPUs
+    FLAGS.enable_grappler_layout_optimizer = False
+    FLAGS.data_format = 'channels_last'
+    self._run_and_report_benchmark()
+
   def benchmark_xla_8_gpu_fp16_cloning(self):
     """Test Keras model with XLA, 8 GPUs, fp16 and cloning."""
     self._setup()
@@ -695,6 +790,24 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     FLAGS.data_delay_prefetch = True
     self._run_and_report_benchmark()
 
+  def benchmark_xla_8_gpu_fp16_cloning_tweaked_layout_off(self):
+    """Test with tuning, FP16+XLA, cloning, and layout_off."""
+    self._setup()
+
+    FLAGS.num_gpus = 8
+    FLAGS.dtype = 'fp16'
+    FLAGS.enable_eager = True
+    FLAGS.enable_xla = True
+    FLAGS.distribution_strategy = 'default'
+    FLAGS.clone_model_in_keras_dist_strat = True
+    FLAGS.model_dir = self._get_model_dir(
+        'benchmark_xla_8_gpu_fp16_cloning_tweaked_layout_off')
+    FLAGS.batch_size = 256 * 8
+    FLAGS.use_tensor_lr = True
+    FLAGS.enable_grappler_layout_optimizer = False
+    FLAGS.data_format = 'channels_last'
+    self._run_and_report_benchmark()
+
   def benchmark_xla_8_gpu_fp16_cloning_tweaked_optional_next(self):
     """Test with manual config tuning, XLA, 8 GPUs, fp16, and cloning.
 
@@ -882,9 +995,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_8_gpu_fp16_tweaked(self):
-    """Test Keras model in legacy graph mode with manual config tuning, 8 GPUs
-       and fp16.
-    """
+    """Test Keras model in legacy graph mode, tuning, 8 GPUs, and FP16."""
     self._setup()
 
     FLAGS.num_gpus = 8
@@ -898,9 +1009,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_xla_8_gpu_fp16_tweaked(self):
-    """Test Keras model in legacy graph mode with manual config tuning, XLA,
-       8 GPUs and fp16.
-    """
+    """Test Keras model in legacy graph tuning, XLA_FP16, 8 GPUs and fp16."""
     self._setup()
 
     FLAGS.num_gpus = 8
@@ -956,9 +1065,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_xla_8_gpu_fp16_slack(self):
-    """Test Keras model in legacy graph mode with tf.data's experimental_slack
-       functionality, XLA, 8 GPUs and fp16.
-    """
+    """Test legacy graph mode with tf.data's experimental_slack."""
     self._setup()
 
     FLAGS.num_gpus = 8
@@ -1122,9 +1229,7 @@ class TrivialKerasBenchmarkReal(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_8_gpu_tweaked(self):
-    """Test trivial Keras model (input pipeline) with manual config tuning and
-       8 GPUs.
-    """
+    """Test trivial Keras model with tuning and 8 GPUs."""
     self._setup()
 
     FLAGS.num_gpus = 8
@@ -1137,9 +1242,7 @@ class TrivialKerasBenchmarkReal(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_8_gpu(self):
-    """Test trivial Keras model (input pipeline) in legacy graph mode with 8
-       GPUs.
-    """
+    """Test trivial Keras model in legacy graph mode with 8 GPUs."""
     self._setup()
 
     FLAGS.num_gpus = 8
@@ -1150,9 +1253,7 @@ class TrivialKerasBenchmarkReal(keras_benchmark.KerasBenchmark):
     self._run_and_report_benchmark()
 
   def benchmark_graph_8_gpu_tweaked(self):
-    """Test trivial Keras model (input pipeline) in legacy graph mode with
-       manual config tuning and 8 GPUs.
-    """
+    """Test trivial Keras model in legacy graph mode with tuning and 8 GPUs."""
     self._setup()
 
     FLAGS.num_gpus = 8