Add docstring notes
@@ -45,6 +45,7 @@ def build_bow_text_classifier(
no_output_layer: bool,
nO: Optional[int] = None,
) -> Model:
+ # Don't document this yet, I'm not sure it's right.
with Model.define_operators({">>": chain}):
sparse_linear = SparseLinear(nO)
model = extract_ngrams(ngram_size, attr=ORTH) >> sparse_linear
@@ -69,6 +70,7 @@ def build_text_classifier(
dropout: Optional[float],
nO: Optional[int] = None,
) -> Model:
+ # Don't document this yet, I'm not sure it's right.
cols = [ORTH, LOWER, PREFIX, SUFFIX, SHAPE, ID]
with Model.define_operators({">>": chain, "|": concatenate, "**": clone}):
lower = HashEmbed(
@@ -160,6 +162,7 @@ def build_text_classifier_lowdata(
dropout: Optional[float],
nO: Optional[int] = None,
) -> Model:
+ # Don't document this yet, I'm not sure it's right.
# Note, before v.3, this was the default if setting "low_data" and "pretrained_dims"
with Model.define_operators({">>": chain, "**": clone}):
model = (
