rm usless comments

Author: ShawnXuan

ClickThroughRate/WideDeepLearning/wdl_train_eval_with_hybrid_embd.py

@@ -155,19 +155,17 @@ def _hybrid_embedding(name, ids, embedding_size, vocab_size, hf_vocab_size):
             dtype=flow.float,
             initializer=flow.random_uniform_initializer(minval=-0.05, maxval=0.05),
             )
-    hf_embedding = flow.gather(params=hf_embedding_table, indices=hf_ids)#, no_duplicates_in_indices=True)
+    hf_embedding = flow.gather(params=hf_embedding_table, indices=hf_ids)
     lf_ids = lf_ids - hf_vocab_size_constant
     with flow.scope.placement('cpu', '0:0'):
         lf_embedding_table = flow.get_variable(
                 name=f'lf_{name}',
                 shape=(vocab_size - hf_vocab_size, embedding_size),
-                #shape=(vocab_size, embedding_size),
                 dtype=flow.float,
                 initializer=flow.random_uniform_initializer(minval=-0.05, maxval=0.05),
                 )
-        lf_embedding = flow.gather(params=lf_embedding_table, indices=lf_ids)#, no_duplicates_in_indices=True)
+        lf_embedding = flow.gather(params=lf_embedding_table, indices=lf_ids)
     unique_embedding = flow.reshape(flow.zeros_like(unique_ids, dtype=flow.float), (-1, 1)) * flow.constant(0.0, dtype=flow.float, shape=(1,embedding_size))
-    # unique_embedding = flow.constant(0.0, dtype=flow.float, shape=(b*s, embedding_size))
     unique_embedding = flow.tensor_scatter_nd_update(params=unique_embedding, updates=hf_embedding, indices=hf_indices)
     unique_embedding = flow.tensor_scatter_nd_update(params=unique_embedding, updates=lf_embedding, indices=lf_indices)
     unique_embedding = flow.gather(params=unique_embedding, indices=unique_ids_idx)
@@ -309,8 +307,6 @@ def print_args(args):
     for arg in vars(args):
         print("{} = {}".format(arg, getattr(args, arg)))
     print("-".ljust(66, "-"))
-    #print("Time stamp: {}".format(
-    #    str(datetime.now().strftime("%Y-%m-%d-%H:%M:%S"))))
 
 
 def main():
@@ -320,8 +316,6 @@ def main():
     flow.config.enable_model_io_v2(True)
     flow.config.enable_debug_mode(True)
     flow.config.collective_boxing.nccl_enable_all_to_all(True)
-    #flow.config.enable_numa_aware_cuda_malloc_host(True)
-    #flow.config.collective_boxing.enable_fusion(False)
     check_point = flow.train.CheckPoint()
     check_point.init()
     for i in range(FLAGS.max_iter):