fix #898 (#900)

Author: fsx950223

efficientdet/hparams_config.py

@@ -204,7 +204,7 @@ def default_detection_configs():
   h.max_level = 7
   h.num_scales = 3
   # ratio w/h: 2.0 means w=1.4, h=0.7. Can be computed with k-mean per dataset.
-  h.aspect_ratios = [1.0, 2.0, 0.5]
+  h.aspect_ratios = [1.0, 2.0, 0.5]  #[[0.7, 1.4], [1.0, 1.0], [1.4, 0.7]]
   h.anchor_scale = 4.0
   # is batchnorm training mode
   h.is_training_bn = True
@@ -238,8 +238,8 @@ def default_detection_configs():
   h.weight_decay = 4e-5
   h.strategy = None  # 'tpu', 'gpus', None
   h.mixed_precision = False  # If False, use float32.
-  h.loss_scale = 2**10  # If False, use float32.
-  h.model_optimizations = {}  # 'prune'
+  h.loss_scale = None  # set to 2**16 enables dynamic loss scale
+  h.model_optimizations = {}  # 'prune':{}
 
   # For detection.
   h.box_class_repeats = 3

efficientdet/utils.py

@@ -112,7 +112,7 @@ def get_ckpt_var_map(ckpt_path, ckpt_scope, var_scope, skip_mismatch=None):
   ckpt_var_names = set(reader.get_variable_to_shape_map().keys())
 
   if tf.distribute.get_replica_context():
-    replica_id = tf.keras.backend.get_value(
+    replica_id = tf.get_static_value(
       tf.distribute.get_replica_context().replica_id_in_sync_group)
   else:
     replica_id = 0