Data-Oriented Class
To define a Taichi kernel as a Python class member function:
- Decorate the class with a
@ti.data_oriented
decorator. - Define
ti.kernel
s andti.func
s in your Data-Oriented Python class.
note
The first argument of the function should be the class instance ("self
"), unless you are defining a @staticmethod
.
A brief example. Notice the use of @ti.data_oriented
and @ti.kernel
in lines 1 and 6, respectively:
@ti.data_oriented
class TiArray:
def __init__(self, n):
self.x = ti.field(dtype=ti.i32, shape=n)
@ti.kernel
def inc(self):
for i in self.x:
self.x[i] += 1
a = TiArray(32)
a.inc()
Definitions of Taichi fields can be made not only in init functions, but also at any place of a Python-scope function in a Data-Oriented class.
import taichi as ti
ti.init()
@ti.data_oriented
class MyClass:
@ti.kernel
def inc(self, temp: ti.template()):
#increment all elements in array by 1
for I in ti.grouped(temp):
temp[I] += 1
def call_inc(self):
self.inc(self.temp)
def allocate_temp(self, n):
self.temp = ti.field(dtype = ti.i32, shape=n)
a = MyClass() # creating an instance of Data-Oriented Class
# a.call_inc() cannot be called, because a.temp has not been allocated at this point
a.allocate_temp(4) # [0 0 0 0]
a.call_inc() # [1 1 1 1]
a.call_inc() # [2 2 2 2]
print(a.temp) # will print [2 2 2 2]
a.allocate_temp(8) # [0 0 0 0 0 0 0 0 0]
a.call_inc() # [1 1 1 1 1 1 1 1]
print(a.temp) # will print [1 1 1 1 1 1 1 1]
Another memory recycling example:
import taichi as ti
ti.init()
@ti.data_oriented
class Calc:
def __init__(self):
self.x = ti.field(dtype=ti.f32, shape=16)
self.y = ti.field(dtype=ti.f32, shape=4)
@ti.kernel
def func(self, temp: ti.template()):
for i in range(8):
temp[i] = self.x[i * 2] + self.x[i * 2 + 1]
for i in range(4):
self.y[i] = ti.max(temp[i * 2], temp[i * 2 + 1])
def call_func(self):
fb = ti.FieldsBuilder()
temp = ti.field(dtype=ti.f32)
fb.dense(ti.i, 8).place(temp)
tree = fb.finalize()
self.func(temp)
tree.destroy()
a = Calc()
for i in range(16):
a.x[i] = i
a.call_func()
print(a.y) # [ 5. 13. 21. 29.]
To know more about FieldsBuilder
, please refer to FieldsBuilder.
Inheritance of Data-Oriented classes
The Data-Oriented property is automatically carried along with the Python class inheritance. This implies that you can call a Taichi Kernel if any of its ancestor classes is decorated with @ti.data_oriented
, which is shown in the example below:
An example:
import taichi as ti
ti.init(arch=ti.cuda)
class BaseClass:
def __init__(self):
self.n = 10
self.num = ti.field(dtype=ti.i32, shape=(self.n, ))
@ti.kernel
def sum(self) -> ti.i32:
ret = 0
for i in range(self.n):
ret += self.num[i]
return ret
@ti.kernel
def add(self, d: ti.i32):
for i in range(self.n):
self.num[i] += d
@ti.data_oriented
class DataOrientedClass(BaseClass):
pass
class DeviatedClass(DataOrientedClass):
@ti.kernel
def sub(self, d: ti.i32):
for i in range(self.n):
self.num[i] -= d
a = DeviatedClass()
a.add(1)
a.sub(1)
print(a.sum()) # 0
b = DataOrientedClass()
b.add(2)
print(b.sum()) # 20
c = BaseClass()
# c.add(3)
# print(c.sum())
# The two lines above trigger a kernel define error, because class c is not decorated with @ti.data_oriented
Python built-in decorators
Common decorators that are pre-built in Python, @staticmethod
1 and @classmethod
2, can decorate a Taichi kernel in Data-Oriented classes.
staticmethod
example:
import taichi as ti
ti.init()
@ti.data_oriented
class Array2D:
def __init__(self, n):
self.arr = ti.Vector([0.] * n)
@staticmethod
@ti.func
def clamp(x): # Clamp to [0, 1)
return max(0, min(1, x))
classmethod
example:
import taichi as ti
ti.init(arch=ti.cuda)
@ti.data_oriented
class Counter:
num_ = ti.field(dtype=ti.i32, shape=(32, ))
def __init__(self, data_range):
self.range = data_range
self.add(data_range[0], data_range[1], 1)
@classmethod
@ti.kernel
def add(cls, l: ti.i32, r: ti.i32, d: ti.i32):
for i in range(l, r):
cls.num_[i] += d
@ti.kernel
def num(self) -> ti.i32:
ret = 0
for i in range(self.range[0], self.range[1]):
ret += self.num_[i]
return ret
a = Counter((0, 5))
print(a.num()) # 5
b = Counter((4, 10))
print(a.num()) # 6
print(b.num()) # 7