[英]Progress bar when using Numba (tqdm is not working) -Python
我一直在尝试使用 numba 运行代码,我还添加了打印以查看我的代码的进度:
from numba import jit,njit,prange
import numpy as np
# for minimum reproducible example
a=1e5
ar = np.random.rand(a)
at = np.random.rand(a)
an = np.random.rand(a)
###############################3
tau = 1 # time lag
window = 6000
@njit(parallel=True)
def func_DB(ar,at,an):
DBtotal= np.zeros((len(an)-tau))
k = 0
for i in prange(0,len(an)-tau,1):
DBtotal[i] = np.sqrt((ar[i + tau]- ar[i])**2 +(at[i + tau]- at[i])**2 +(an[i + tau]- an[i])**2)
## To print the progress
if i%1e5==0:
k+=1
print(k*1e5/len(DBtotal))
return DBtotal
@njit(parallel=True)
def func_PVI(tau, window):
PVI = np.zeros((len(DBtotal)))
k = 0
for i in prange(int(window/2),len(DBtotal)-int(window/2)):
PVI[i] = DBtotal[i]/np.sqrt((np.mean(DBtotal[i-int(window/2):i+int(window/2)]**2)))
# To print the progress
if i%1e5==0:
k+=1
print(k*1e5/len(DBtotal))
return PVI
DBtotal = func_DB(ar,at,an)
PVI = func_PVI(DBtotal,tau, window)
但是,在代码运行时,我没有得到我预期的结果(即随着代码的进行,go 的值从 0 到 1)相反,我得到了这个:
Out[:] 0.009479390005044932
0.009479390005044932
0.009479390005044932
0.009479390005044932
0.009479390005044932
0.018958780010089864
有人可以建议一种查看代码进度的方法吗?
此外,我们将不胜感激任何使代码更高效的建议!
我将 function 拆成碎片,并在其周围包裹了一个 tqdm。
代替
@jit(nopython=True)
def dothings(A, rows, cols):
for r in range(rows):
for c in range(cols):
stuff...
dothings(data, data.shape[0], data.shape[1])
我用了
rows=data.shape[0]
@jit(nopython=True)
def dothings(A, cols, r):
# for r in range(rows):
for c in range(cols):
stuff...
for r in tqdm.tqdm(range(rows), total=rows):
dothings(data, data.shape[1], r)
尝试这个:
from numba import njit,prange,objmode
@njit(parallel=True)
def harmonic_load_flow_func_time_inside():
with objmode(time1='f8'):
time1 = time.perf_counter()
calc = 0
for x in prange(1000000):
calc += x
with objmode():
print('time: {}'.format(time.perf_counter() - time1),end='\r')
我在 github 上找到了一个小项目,它可以自动完成所有这些工作。 它被称为numba-progress
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