def relabel_graph(X):
G = state.GRAPH
n = len(G.nodes)
for i in range(n):
num = np.argmax(X[:,i])
G.nodes[num]['label'] = i
solver.render()
import sys
import numpy as np
sys.path.append('..')
import core.solver as solver
from fft import fft_example
from dct import dct_example
from matmult import matmult, strassen_matmult
# dct_example(3)
# solver.render("dct.png")
# matmult(2)
# solver.render("matmult.png")
# strassen_matmult(1)
# solver.render("strassen.png")
a = np.array(solver.transform_array([1, 2]))
b = np.array(solver.transform_array([1, 2]))
np.dot(a, b)
solver.render("dot.png")
M2 = strassen_helper(A_mats[1][0] + A_mats[1][1], B_mats[0][0])
M3 = strassen_helper(A_mats[0][0], B_mats[0][1] - B_mats[1][1])
M4 = strassen_helper(A_mats[1][1], B_mats[1][0] - B_mats[0][0])
M5 = strassen_helper(A_mats[0][0] + A_mats[0][1], B_mats[1][1])
M6 = strassen_helper(A_mats[1][0] - A_mats[0][0],
B_mats[0][0] + B_mats[0][1])
M7 = strassen_helper(A_mats[0][1] - A_mats[1][1],
B_mats[1][0] + B_mats[1][1])
if alltogether:
C11 = sum_matrices([M1, M4, M5, M7]) #((M1 + M4) - M5) + M7
C12 = M3 + M5
C21 = M2 + M4
C22 = sum_matrices([M1, M2, M3, M6]) # ((M1 - M2) + M3) + M6
else:
C11 = ((M1 + M4) - M5) + M7
C12 = M3 + M5
C21 = M2 + M4
C22 = ((M1 - M2) + M3) + M6
if isinstance(C11, np.ndarray):
first_row = np.concatenate([C11, C12], axis=1)
second_row = np.concatenate([C21, C22], axis=1)
return np.concatenate([first_row, second_row], axis=0)
else:
return np.array([[C11, C12], [C21, C22]])
if __name__ == "__main__":
strassen_matmult(1, alltogether=True)
solver.render("strassen_mamult_out.png")
import numpy as np
import sys
sys.path.append('..')
import core.solver as solver
from convolve import convolve
import core.state as state
from fft import fft_example
from matmult import matmult
def relabel_graph(X):
G = state.GRAPH
n = len(G.nodes)
for i in range(n):
num = np.argmax(X[:,i])
G.nodes[num]['label'] = i
solver.render()
filename = "results/matmult/5.gz"
X = np.loadtxt(filename)
print(X)
matmult(2)
# convolve(3)
# fft_example(2)
relabel_graph(X)
solver.render("pics/matmult5.png")
neighbors.append(cp)
neighboring_nodes = [nodes[stringify_binary(u)] for u in neighbors]
if len(neighboring_nodes) > 0:
new_node = solver.genop(neighboring_nodes, np.sum) # stand in for the DP step
else:
new_node = solver.DataNode(0)
nodes[stringify_binary(curr_encoding)] = new_node
def tsp(n):
nodes = {}
start_enc = np.zeros(n)
curr_list = [start_enc]
queued = set([stringify_binary(start_enc)])
while len(curr_list) > 0:
curr_enc = curr_list.pop(0)
tsp_helper(curr_enc, nodes)
for i in range(len(curr_enc)):
if curr_enc[i] == 0:
cp = np.copy(curr_enc)
cp[i] = 1
cp_str = stringify_binary(cp)
if cp_str not in queued:
curr_list.append(cp)
queued.add(cp_str)
assert len(queued) == 2**n
if __name__ == "__main__":
tsp(5)
# strassen_matmult(1, alltogether=True)
solver.render("hypercube.png")