def context_fn(ind_sent_list):
index = ind_sent_list[0]
sent_list = ind_sent_list[1]
env_matrix = context_fn.env_matrix
temp_dir = context_fn.temp_dir
# Very slow in SciPy v. 0.7.2. Same for dok_matrix.
# mem_matrix = lil_matrix(env_matrix.shape)
# Occupies too much memory
# mem_matrix = np.zeros(env_matrix.shape, dtype=np.float32)
# So, using dictionary as temporary sparse matrix
mem_matrix = dict()
print 'Training on chunk of sentences', index
for sent in sent_list:
for i,word in enumerate(sent):
if word not in mem_matrix:
mem_matrix[word] = np.zeros(env_matrix.shape[1], dtype=np.float32)
# Left context
for ctxword in sent[:i]:
mem_matrix[word] += env_matrix[ctxword,:]
# mem_matrix[word,:] += env_matrix[ctxword,:]
# Right context
for ctxword in sent[i+1:]:
mem_matrix[word] += env_matrix[ctxword,:]
# mem_matrix[word,:] += env_matrix[ctxword,:]
print 'Chunk of sentences', index
# print mem_matrix
tmp_file =\
os.path.join(temp_dir, 'context-' + str(index) + '.tmp.npy')
print 'Dumping to temp file\n'\
' ', tmp_file
dump_matrix(mem_matrix, tmp_file)
return tmp_file
def order_fn(ind_sent_list):
index = ind_sent_list[0]
sent_list = ind_sent_list[1]
env_matrix = order_fn.env_matrix
lmbda = order_fn.lmbda
temp_dir = order_fn.temp_dir
left_permutation = order_fn.left_permutation
right_permutation = order_fn.right_permutation
placeholder = order_fn.placeholder
# Very slow in SciPy v. 0.7.2. Same for dok_matrix.
# mem_matrix = lil_matrix(env_matrix.shape)
# Occupies too much memory
# mem_matrix = np.zeros(env_matrix.shape, dtype=np.float32)
# So, using dictionary as temporary sparse matrix
mem_matrix = dict()
print 'Training on chunk of sentences', index
for sent in sent_list:
for k in xrange(1, lmbda):
for i,word in enumerate(sent):
a = i - k
left = 0 if a < 0 else a
b = i + k
right = len(sent) if b > len(sent) else b
vector_list = ([env_matrix[w] for w in sent[left:i]]
+ [placeholder]
+ [env_matrix[w] for w in sent[i+1:right]])
def f(vector_list):
if len(vector_list) == 0:
return np.zeros(self.dimension)
elif len(vector_list) == 1:
return vector_list[0]
else:
v1 = dual.fft(left_permutation(f(vector_list[:-1])))
v2 = dual.fft(right_permutation(vector_list[len(vector_list)-1]))
return dual.ifft(v1 * v2)
order_vector = f(vector_list)
if word not in mem_matrix:
mem_matrix[word] = np.zeros(env_matrix.shape[1], dtype=np.float32)
mem_matrix[word] += order_vector
print 'Chunk of sentences', index, '\n', mem_matrix
tmp_file =\
os.path.join(temp_dir, 'order-' + str(index) + '.tmp.npy')
print 'Dumping to temp file\n'\
' ', tmp_file
dump_matrix(mem_matrix, tmp_file)
return tmp_file
def dump_matrix(self, filename):
dump_matrix(self.matrix, filename)
