|
|
|
@ -211,7 +211,6 @@ class WideDeepModel(nn.Cell):
|
|
|
|
|
if config.deep_table_slice_mode == "column_slice":
|
|
|
|
|
self.deep_embeddinglookup = nn.EmbeddingLookup(self.vocab_size, self.emb_dim, target=target,
|
|
|
|
|
slice_mode=nn.EmbeddingLookup.TABLE_COLUMN_SLICE)
|
|
|
|
|
self.dense_layer_1.dropout.dropout_do_mask.shard(((1, get_group_size()),))
|
|
|
|
|
self.dense_layer_1.dropout.dropout.shard(((1, get_group_size()),))
|
|
|
|
|
self.dense_layer_1.matmul.shard(((1, get_group_size()), (get_group_size(), 1)))
|
|
|
|
|
self.dense_layer_1.matmul.add_prim_attr("field_size", self.field_size)
|
|
|
|
@ -233,7 +232,6 @@ class WideDeepModel(nn.Cell):
|
|
|
|
|
self.deep_mul.shard(((1, get_group_size(), 1), (1, get_group_size(), 1)))
|
|
|
|
|
self.wide_mul.shard(((1, get_group_size(), 1), (1, get_group_size(), 1)))
|
|
|
|
|
self.reduce_sum.shard(((1, get_group_size(), 1),))
|
|
|
|
|
self.dense_layer_1.dropout.dropout_do_mask.shard(((1, get_group_size()),))
|
|
|
|
|
self.dense_layer_1.dropout.dropout.shard(((1, get_group_size()),))
|
|
|
|
|
self.dense_layer_1.matmul.shard(((1, get_group_size()), (get_group_size(), 1)))
|
|
|
|
|
self.embedding_table = self.deep_embeddinglookup.embedding_table
|
|
|
|
|