],
# use generator as decoder
[
category_feature(vocab_size=2, reduce_input="sum"),
sequence_feature(vocab_size=10, max_len=5, decoder="generator"),
number_feature(),
],
# Generator decoder and reduce_input = None
[
category_feature(vocab_size=2, reduce_input="sum"),
sequence_feature(max_len=5, decoder="generator",
reduce_input=None),
number_feature(normalization="minmax"),
],
# output features with dependencies single dependency
generate_output_features_with_dependencies("number_feature",
["category_feature"]),
# output features with dependencies multiple dependencies
generate_output_features_with_dependencies(
"number_feature", ["category_feature", "sequence_feature"]),
# output features with dependencies multiple dependencies
generate_output_features_with_dependencies(
"sequence_feature", ["category_feature", "number_feature"]),
# output features with dependencies
generate_output_features_with_dependencies("category_feature",
["sequence_feature"]),
generate_output_features_with_dependencies_complex(),
],
)
def test_experiment_multiple_seq_seq(csv_filename, output_features):
input_features = [
text_feature(vocab_size=100, min_len=1, encoder="stacked_cnn"),
[
category_feature(vocab_size=2, reduce_input='sum'),
sequence_feature(vocab_size=10, max_len=5, decoder='generator'),
numerical_feature()
],
# Generator decoder and reduce_input = None
[
category_feature(vocab_size=2, reduce_input='sum'),
sequence_feature(max_len=5, decoder='generator',
reduce_input=None),
numerical_feature(normalization='minmax')
],
# output features with dependencies single dependency
generate_output_features_with_dependencies('feat3', ['feat1']),
# output features with dependencies multiple dependencies
generate_output_features_with_dependencies('feat3',
['feat1', 'feat2']),
# output features with dependencies multiple dependencies
generate_output_features_with_dependencies('feat2',
['feat1', 'feat3']),
# output features with dependencies
generate_output_features_with_dependencies('feat1', ['feat2'])
])
def test_experiment_multiple_seq_seq(csv_filename, output_features):
input_features = [
text_feature(vocab_size=100, min_len=1, encoder='stacked_cnn'),
numerical_feature(),
],
# use generator as decoder
[
category_feature(vocab_size=2, reduce_input="sum"),
sequence_feature(vocab_size=10, max_len=5, decoder="generator"),
numerical_feature(),
],
# Generator decoder and reduce_input = None
[
category_feature(vocab_size=2, reduce_input="sum"),
sequence_feature(max_len=5, decoder="generator", reduce_input=None),
numerical_feature(normalization="minmax"),
],
# output features with dependencies single dependency
generate_output_features_with_dependencies("feat3", ["feat1"]),
# output features with dependencies multiple dependencies
generate_output_features_with_dependencies("feat3", ["feat1", "feat2"]),
],
)
def test_experiment_multiple_seq_seq(csv_filename, output_features):
input_features = [
text_feature(vocab_size=100, min_len=1, encoder="stacked_cnn"),
numerical_feature(normalization="zscore"),
category_feature(vocab_size=10, embedding_size=5),
set_feature(),
sequence_feature(vocab_size=10, max_len=10, encoder="embed"),
]
output_features = output_features
rel_path = generate_data(input_features, output_features, csv_filename)
