import submission
import pickle
import time
# How to run your implementation for Part 1
with open('./toy_example/Data_File', 'rb') as f:
Data_File = pickle.load(f, encoding='bytes')
with open('./toy_example/Centroids_File', 'rb') as f:
Centroids_File = pickle.load(f, encoding='bytes')
start = time.time()
codebooks, codes = submission.pq(Data_File,
P=2,
init_centroids=Centroids_File,
max_iter=20)
end = time.time()
time_cost_1 = end - start
# How to run your implementation for Part 2
with open('./toy_example/Query_File', 'rb') as f:
Query_File = pickle.load(f, encoding='bytes')
queries = Query_File
start = time.time()
candidates = submission.query(queries, codebooks, codes, T=10)
end = time.time()
time_cost_2 = end - start
# output for part 2.
print(candidates)
print(time_cost_2)
Test_Case_2 = np.load('datasets/Test_files/Test/Test_Case_2.npy')
Test_Case_2_Cent = np.load('datasets/Test_files/Test/Test_Case_2_Cent.npy')
Test_Case_2_Query = np.load('datasets/Test_files/Test/Test_Case_2_Query.npy')
Test_Case_3 = np.load('datasets/Test_files/Test/Test_Case_3.npy')
Test_Case_3_Cent = np.load('datasets/Test_files/Test/Test_Case_3_Cent.npy')
Test_Case_3_Query = np.load('datasets/Test_files/Test/Test_Case_3_Query.npy')
# How to run your implementation for Part 1
with open('datasets/Data_File', 'rb') as f:
Data_File = pickle.load(f, encoding='bytes')
with open('datasets/Centroids_File', 'rb') as f:
Centroids_File = pickle.load(f, encoding='bytes')
start = time.time()
codebooks, codes = submission.pq(Data_File,
P=4,
init_centroids=four_centroids,
max_iter=20)
end = time.time()
time_cost_1 = end - start
print(time_cost_1)
print("Codebook shape: ", codebooks.shape)
print(" Codebook type: ", codebooks.dtype)
print(" Codes shape: ", codes.shape)
print(" Codes type: ", codes.dtype)
# How to run your implementation for Part 2
with open('datasets/Query_File', 'rb') as f:
queries = pickle.load(f, encoding='bytes')
start = time.time()
candidates = submission.query(one28_que, codebooks, codes, T=10)
end = time.time()