def _create_data_specs(self):
ws = (self.window_size * 2 + 1)
space = CompositeSpace((IndexSequenceSpace(max_labels=self.vocab_size,
dim=ws),
IndexSequenceSpace(max_labels=self.total_feats,
dim=self.feat_num),
VectorSequenceSpace(dim=self.n_classes)))
source = ('words', 'features', 'targets')
self.data_specs = (space, source)
def test_np_format_as_indexsequence2indexsequence():
index_sequence_space1 = IndexSequenceSpace(max_labels=6, dim=1,
dtype='int16')
index_sequence_space2 = IndexSequenceSpace(max_labels=6, dim=1,
dtype='int32')
data = np.random.randint(low=0, high=5, size=(10, 1))
rval = index_sequence_space1.np_format_as(data, index_sequence_space2)
assert np.all(rval == data)
def test_np_format_as_indexsequence2vectorsequence():
index_sequence_space = IndexSequenceSpace(max_labels=6, dim=1)
vector_sequence_space = VectorSequenceSpace(dim=6)
data = np.array([[0], [1], [4], [3]])
rval = index_sequence_space.np_format_as(data, vector_sequence_space)
true_val = np.array([[1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0], [0, 0, 0, 1, 0, 0]])
assert np.all(rval == true_val)
def test_np_format_as_indexsequence2vectorsequence():
index_sequence_space = IndexSequenceSpace(max_labels=6, dim=1)
vector_sequence_space = VectorSequenceSpace(dim=6)
data = np.array([[0], [1], [4], [3]])
rval = index_sequence_space.np_format_as(data, vector_sequence_space)
true_val = np.array([[1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0]])
assert np.all(rval == true_val)
def test_np_format_as_indexsequence2indexsequence():
index_sequence_space1 = IndexSequenceSpace(max_labels=6,
dim=1,
dtype='int16')
index_sequence_space2 = IndexSequenceSpace(max_labels=6,
dim=1,
dtype='int32')
data = np.random.randint(low=0, high=5, size=(10, 1))
rval = index_sequence_space1.np_format_as(data, index_sequence_space2)
assert np.all(rval == data)
def test_np_format_as_sequence2other():
vector_sequence_space = VectorSequenceSpace(dim=3)
vector_space = VectorSpace(dim=3)
data = np.random.uniform(low=0.0, high=1.0, size=(10, 3))
np.testing.assert_raises(ValueError, vector_sequence_space.np_format_as,
data, vector_space)
index_sequence_space = IndexSequenceSpace(max_labels=6, dim=1)
index_space = IndexSpace(max_labels=6, dim=1)
data = np.random.randint(low=0, high=5, size=(10, 1))
np.testing.assert_raises(ValueError, index_sequence_space.np_format_as,
data, index_space)
