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hub / github.com/DeepRec-AI/DeepRec / __init__

Method __init__

modelzoo/dlrm/train.py:69–113  ·  view source on GitHub ↗
(self,
                 dense_column=None,
                 sparse_column=None,
                 mlp_bot=[512, 256, 64, 16],
                 mlp_top=[512, 256],
                 optimizer_type='adam',
                 learning_rate=0.1,
                 inputs=None,
                 interaction_op='dot',
                 bf16=False,
                 stock_tf=None,
                 adaptive_emb=False,
                 input_layer_partitioner=None,
                 dense_layer_partitioner=None)

Source from the content-addressed store, hash-verified

67
68class DLRM():
69 def __init__(self,
70 dense_column=None,
71 sparse_column=None,
72 mlp_bot=[512, 256, 64, 16],
73 mlp_top=[512, 256],
74 optimizer_type='adam',
75 learning_rate=0.1,
76 inputs=None,
77 interaction_op='dot',
78 bf16=False,
79 stock_tf=None,
80 adaptive_emb=False,
81 input_layer_partitioner=None,
82 dense_layer_partitioner=None):
83 if not inputs:
84 raise ValueError('Dataset is not defined.')
85 self._feature = inputs[0]
86 self._label = inputs[1]
87
88 if not dense_column or not sparse_column:
89 raise ValueError('Dense column or sparse column is not defined.')
90 self._dense_column = dense_column
91 self._sparse_column = sparse_column
92
93 self.tf = stock_tf
94 self.bf16 = False if self.tf else bf16
95 self.is_training = True
96 self._adaptive_emb = adaptive_emb
97
98 self._mlp_bot = mlp_bot
99 self._mlp_top = mlp_top
100 self._learning_rate = learning_rate
101 self._input_layer_partitioner = input_layer_partitioner
102 self._dense_layer_partitioner = dense_layer_partitioner
103 self._optimizer_type = optimizer_type
104 self.interaction_op = interaction_op
105 if self.interaction_op not in ['dot', 'cat']:
106 print("Invaild interaction op, must be 'dot' or 'cat'.")
107 sys.exit()
108
109 self._create_model()
110 with tf.name_scope('head'):
111 self._create_loss()
112 self._create_optimizer()
113 self._create_metrics()
114
115 # used to add summary in tensorboard
116 def _add_layer_summary(self, value, tag):

Callers

nothing calls this directly

Calls 6

_create_modelMethod · 0.95
_create_lossMethod · 0.95
_create_optimizerMethod · 0.95
_create_metricsMethod · 0.95
exitMethod · 0.80
name_scopeMethod · 0.45

Tested by

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