Clarify dropout and seed in Tok2Vec
@@ -263,20 +263,20 @@ def build_Tok2Vec_model(
cols = [ID, NORM, PREFIX, SUFFIX, SHAPE, ORTH]
with Model.define_operators({">>": chain, "|": concatenate, "**": clone}):
norm = HashEmbed(
- nO=width, nV=embed_size, column=cols.index(NORM), dropout=dropout,
+ nO=width, nV=embed_size, column=cols.index(NORM), dropout=None,
seed=0
)
if subword_features:
prefix = HashEmbed(
- nO=width, nV=embed_size // 2, column=cols.index(PREFIX), dropout=dropout,
+ nO=width, nV=embed_size // 2, column=cols.index(PREFIX), dropout=None,
seed=1
)
suffix = HashEmbed(
- nO=width, nV=embed_size // 2, column=cols.index(SUFFIX), dropout=dropout,
+ nO=width, nV=embed_size // 2, column=cols.index(SUFFIX), dropout=None,
seed=2
)
shape = HashEmbed(
- nO=width, nV=embed_size // 2, column=cols.index(SHAPE), dropout=dropout,
+ nO=width, nV=embed_size // 2, column=cols.index(SHAPE), dropout=None,
seed=3
)
else:
@@ -296,7 +296,7 @@ def build_Tok2Vec_model(
>> Maxout(
nO=width,
nI=width * columns,
- nP=maxout_pieces,
+ nP=3,
dropout=0.0,
normalize=True,
),
@@ -309,7 +309,7 @@ def build_Tok2Vec_model(
>> Maxout(
nO=width,
nI=width * columns,
- nP=maxout_pieces,
+ nP=3,
dropout=0.0,
normalize=True,
),
@@ -322,7 +322,7 @@ def build_Tok2Vec_model(
>> Maxout(
nO=width,
nI=width * columns,
- nP=maxout_pieces,
+ nP=3,
dropout=0.0,
normalize=True,
),
@@ -335,7 +335,7 @@ def build_Tok2Vec_model(
reduce_dimensions = Maxout(
nO=width,
nI=nM * nC + width,
- nP=maxout_pieces,
+ nP=3,
dropout=0.0,
normalize=True,
)
