def testDumpLoad(self): local_size = 2 mat_sources = [np.random.rand(local_size), np.random.rand(local_size, 2), np.random.rand(local_size, 2, 3)] for mat in mat_sources: mpi.dump_matrix(mat, _MPI_DUMP_TEST_FILE) if mpi.is_root(): mat_dumped = np.load(_MPI_DUMP_TEST_FILE) self.assertEqual(mat_dumped.shape, (local_size * mpi.SIZE,) + mat.shape[1:]) mat_read = mpi.load_matrix(_MPI_DUMP_TEST_FILE) self.assertEqual(mat.shape, mat_read.shape)
def testDumpLoad(self): local_size = 2 mat_sources = [ np.random.rand(local_size), np.random.rand(local_size, 2), np.random.rand(local_size, 2, 3) ] for mat in mat_sources: mpi.dump_matrix(mat, _MPI_DUMP_TEST_FILE) if mpi.is_root(): mat_dumped = np.load(_MPI_DUMP_TEST_FILE) self.assertEqual(mat_dumped.shape, (local_size * mpi.SIZE, ) + mat.shape[1:]) mat_read = mpi.load_matrix(_MPI_DUMP_TEST_FILE) self.assertEqual(mat.shape, mat_read.shape)
mpi.root_pickle(conv, 'cvpr_exemplar_centroids_conv.pickle') mpi.root_pickle((conv[-2].dictionary, ap_result), 'cvpr_exemplar_centroids.pickle') """ mpi.root_pickle((eigval, eigval_recon, eigval_random), 'cvpr_exemplar_centroids_covmat_eigvals.pickle') # perform sampling # sample post-pooling guys Xtrain *= std Xtrain += m sampler = mathutil.ReservoirSampler(2000) for i in range(covmat.shape[0]): label = ap_result[1][i] centroid_id = ap_result[0][label] if centroid_id != i: sampler.consider(Xtrain[:, [i, centroid_id]]) mpi.dump_matrix(sampler.get(), 'cvpr_exemplar_centroids_distribution_within_cluster_postpooling.npy') sampler = mathutil.ReservoirSampler(2000) for i in range(len(ap_result[0])): for j in range(i+1, len(ap_result[0])): sampler.consider(Xtrain[:,[ap_result[0][i],ap_result[0][j]]]) mpi.dump_matrix(sampler.get(), 'cvpr_exemplar_centroids_distribution_between_cluster_postpooling.npy') # clean up something for the large sampler del Xtrain del Cpred del Csel del Crecon del sampler sampler = mathutil.ReservoirSampler(2000) temp = pipeline.ConvLayer(conv[:-1]).sample(cifar, 200000, True)