[feat]: format backbone code, add recurrent and sequential layer

easy_rec/python/layers/common_layers.py

@@ -91,7 +91,11 @@ def __init__(self, config, input_layer, feature_dict):
     self._input_layer = input_layer
     self._feature_dict = feature_dict
 
-  def __call__(self, group, is_training, *args, **kwargs):
+  def __call__(self, group, is_training, **kwargs):
+    with tf.name_scope('input_' + group):
+      return self.call(group, is_training)
+
+  def call(self, group, is_training):
     if self._config.output_seq_and_normal_feature:
       seq_features, target_feature, target_features = self._input_layer(
           self._feature_dict, group, is_combine=False)

easy_rec/python/layers/keras/mask_net.py

@@ -60,12 +60,13 @@ class MaskNet(tf.keras.layers.Layer):
   Refer: https://arxiv.org/pdf/2102.07619.pdf
   """
 
-  def __init__(self, params, name='mask_net', l2_reg=None, **kwargs):
+  def __init__(self, params, name='mask_net', **kwargs):
     super(MaskNet, self).__init__(name, **kwargs)
     self.config = params.get_pb_config()
     if self.config.HasField('mlp'):
       p = Parameter.make_from_pb(self.config.mlp)
-      self.mlp = MLP(p, name='%s/mlp' % name, l2_reg=l2_reg)
+      p.l2_regularizer = params.l2_regularizer
+      self.mlp = MLP(p, name='%s/mlp' % name)
     else:
       self.mlp = None
 
@@ -75,7 +76,7 @@ def call(self, inputs, training=None, **kwargs):
       for i, block_conf in enumerate(self.config.mask_blocks):
         params = Parameter.make_from_pb(block_conf)
         mask_layer = MaskBlock(
-            params, name='%s/block_%d' % (self.name, i), reuse=self.reuse)
+            params, name='%s/block_%d' % (self.name, i))
         mask_outputs.append(mask_layer((inputs, inputs)))
       all_mask_outputs = tf.concat(mask_outputs, axis=1)
 
@@ -89,7 +90,7 @@ def call(self, inputs, training=None, **kwargs):
       for i, block_conf in enumerate(self.config.mask_blocks):
         params = Parameter.make_from_pb(block_conf)
         mask_layer = MaskBlock(
-            params, name='%s/block_%d' % (self.name, i), reuse=self.reuse)
+            params, name='%s/block_%d' % (self.name, i))
         net = mask_layer((net, inputs))
 
       if self.mlp is not None:

easy_rec/version.py

@@ -1,3 +1,3 @@
 # -*- encoding:utf-8 -*-
 # Copyright (c) Alibaba, Inc. and its affiliates.
-__version__ = '0.6.3'
+__version__ = '1.0.0'

examples/configs/masknet_on_movielens.config

@@ -17,9 +17,8 @@ train_config {
     }
     use_moving_average: false
   }
-  save_checkpoints_steps: 100
+  save_checkpoints_steps: 2000
   sync_replicas: True
-  num_steps: 2500
 }
 
 eval_config {

examples/readme.md

@@ -220,7 +220,7 @@ python -m easy_rec.python.train_eval --pipeline_config_path examples/configs/dee
   | DCN (Backbone)      | 1     | 0.8770 |
   | AutoInt             | 1     | 0.8513 |
   | MaskNet             | 1     | 0.8872 |
-  | FibiNet             | 1     | 0.8879 |
+  | FibiNet             | 1     | 0.8893 |
 
   备注：`MovieLens-1M` 数据集较小，评估指标方差较大，以上结果仅供参考。