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Dlrm key type #348

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Merged
ShawnXuan merged 2 commits into from
Aug 8, 2022
Merged

Dlrm key type #348

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4c82e90
add oneembedding key_type
ShawnXuan Jun 16, 2022
f44b50f
pad dense input
ShawnXuan Jun 16, 2022
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32 changes: 30 additions & 2 deletions RecommenderSystems/dlrm/dlrm_train_eval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,13 +41,24 @@ def str_list(x):

parser.add_argument("--disable_fusedmlp", action="store_true", help="disable fused MLP or not")
parser.add_argument("--embedding_vec_size", type=int, default=128)
parser.add_argument(
"--one_embedding_key_type",
type=str,
default="int64",
help="OneEmbedding key type: int32, int64",
)
parser.add_argument("--bottom_mlp", type=int_list, default="512,256,128")
parser.add_argument("--top_mlp", type=int_list, default="1024,1024,512,256")
parser.add_argument(
"--disable_interaction_padding",
action="store_true",
help="disable interaction padding or not",
)
parser.add_argument(
"--disable_dense_input_padding",
action="store_true",
help="disable dense input padding or not",
)
parser.add_argument(
"--interaction_itself", action="store_true", help="interaction itself or not"
)
Expand Down Expand Up @@ -266,6 +277,7 @@ def __init__(
table_size_array,
store_type,
cache_memory_budget_mb,
key_type,
):
assert table_size_array is not None
vocab_size = sum(table_size_array)
Expand Down Expand Up @@ -303,7 +315,7 @@ def __init__(
"sparse_embedding",
embedding_dim=embedding_vec_size,
dtype=flow.float,
key_type=flow.int64,
key_type=getattr(flow, key_type),
tables=tables,
store_options=store_options,
)
Expand All @@ -322,21 +334,33 @@ def __init__(
persistent_path=None,
table_size_array=None,
one_embedding_store_type="cached_host_mem",
one_embedding_key_type="int64",
cache_memory_budget_mb=8192,
interaction_itself=True,
interaction_padding=True,
dense_input_padding=True,
):
super(DLRMModule, self).__init__()
assert (
embedding_vec_size == bottom_mlp[-1]
), "Embedding vector size must equle to bottom MLP output size"
self.bottom_mlp = MLP(num_dense_fields, bottom_mlp, fused=use_fusedmlp)
self.num_dense_fields = (
((num_dense_fields + 8 - 1) // 8 * 8) if dense_input_padding else num_dense_fields
)
self.pad = (
[0, self.num_dense_fields - num_dense_fields]
if self.num_dense_fields > num_dense_fields
else None
)

self.bottom_mlp = MLP(self.num_dense_fields, bottom_mlp, fused=use_fusedmlp)
self.embedding = OneEmbedding(
embedding_vec_size,
persistent_path,
table_size_array,
one_embedding_store_type,
cache_memory_budget_mb,
one_embedding_key_type,
)
self.interaction = Interaction(
bottom_mlp[-1],
Expand All @@ -352,6 +376,8 @@ def __init__(
)

def forward(self, dense_fields, sparse_fields) -> flow.Tensor:
if self.pad:
dense_fields = flow.nn.functional.pad(dense_fields, self.pad, "constant")
dense_fields = flow.log(dense_fields + 1.0)
dense_fields = self.bottom_mlp(dense_fields)
embedding = self.embedding(sparse_fields)
Expand All @@ -368,9 +394,11 @@ def make_dlrm_module(args):
persistent_path=args.persistent_path,
table_size_array=args.table_size_array,
one_embedding_store_type=args.store_type,
one_embedding_key_type=args.one_embedding_key_type,
cache_memory_budget_mb=args.cache_memory_budget_mb,
interaction_itself=args.interaction_itself,
interaction_padding=not args.disable_interaction_padding,
dense_input_padding=not args.disable_dense_input_padding,
)
return model

Expand Down