def getNNIndicesForBigFeatureMats(test_org,mats):
test=ca.array(test_org);
distances=[]
for idx_mat,mat_curr in enumerate(mats):
print idx_mat
distances.append(nearest_neighbor.getSimpleDot(test,ca.array(mats[idx_mat]),gpuFlag=True));
# print '';
distances=np.hstack(tuple(distances));
indices=np.argsort(distances,axis=1)[:,::-1].astype(np.uint32)
return indices
def getNNIndicesForBigFeatureMats(test_org, mats):
test = ca.array(test_org)
distances = []
for idx_mat, mat_curr in enumerate(mats):
print idx_mat
distances.append(
nearest_neighbor.getSimpleDot(test,
ca.array(mats[idx_mat]),
gpuFlag=True))
# print '';
distances = np.hstack(tuple(distances))
indices = np.argsort(distances, axis=1)[:, ::-1].astype(np.uint32)
return indices
def saveDotProduct((first_shot_path, second_shot_path, out_file, idx)):
test = getGPUArray(first_shot_path)
train = getGPUArray(second_shot_path)
results = nearest_neighbor.getSimpleDot(test, train, gpuFlag=True)
np.savez(out_file, results)
return True
def saveDotProduct((first_shot_path,second_shot_path,out_file,idx)):
test = getGPUArray(first_shot_path);
train = getGPUArray(second_shot_path);
results = nearest_neighbor.getSimpleDot(test,train,gpuFlag=True)
np.savez(out_file,results);
return True