为什么全局变量无效？

综合讨论区
#1 
import taichi as ti
import numpy as np

ti.init(arch=ti.cpu)

all_model = np.random.random((100000,50)).astype(np.float32)
all_t = ti.Matrix.field(n=10,m=5,dtype =ti.f32, shape=())
all_t.from_numpy(all_model)

id = np.random.random(50).astype(np.float32)
id_t = ti.Vector.field(5,ti.f32,shape=())
id_t.from_numpy(id)

mesh2 = ti.field(dtype =ti.f32, shape=())

@ti.kernel
def compute(): 
    mesh2= all_t[None] @ id_t[None]

compute()

print('mesh2:',mesh2)
#output: mesh2: 0.0

按理来说mesh2不应该为0把？请问为什么呢？

#3

mesh2是一个scalar field，所以赋值的时候可以用 mesh2[None] = all_t[Nonoe] @ id_t[None]。然后输出的话：print(mesh2[None])试一下？

#4

环境：[Taichi] version 1.4.1, llvm 15.0.1, commit e67c674e, win, python 3.8.12

尝试更改赋值代码：

@ti.kernel
def compute(): 
    mesh2[None] = all_t[None] @ id_t[None]  #更改

报错:Field with dim 2 accessed with indices of dim 0

如果将mesh2换种方式定义：

mesh2 = ti.Matrix.field(n=10,m=5,dtype =ti.f32, shape=())#方式1
mesh2 = ti.Vector.field(5,dtype =ti.f32, shape=())#方式2
# mesh2 = ti.field(dtype =ti.f32, shape=(1000,50))

@ti.kernel
def compute(): #a:ti.types.ndarray(),b:ti.types.ndarray()
    mesh2[None] = all_t[None] @ id_t[None]

都会红色报错：
[E 03/17/23 10:30:43.104 118484] [scalarize.cpp:taichi::lang::Scalarize::scalarize_store_stmt@51] Assertion failure: dest_tensor_type->get_shape() == val_tensor_type->get_shape()

[E 03/17/23 10:30:43.104 118484] [ir.cpp:taichi::lang::DelayedIRModifier::~DelayedIRModifier@408] Assertion failure: to_insert_before_.empty()

如果单独输出mesh2

mesh2 = ti.field(dtype =ti.f32, shape=(1000,50))
print('mesh2:',mesh2[None])

报错:AssertionError: Slicing is not supported on ti.field

1 个赞
#5

Hi @MrBor , 我看了下你的代码。发现你kernel内计算的 field之间的dimension是不匹配的。

import taichi as ti
import numpy as np

ti.init(arch=ti.cpu)

all_model = np.random.random((10, 5)).astype(np.float32)
all_t = ti.Matrix.field(n=10,m=5,dtype =ti.f32, shape=())
all_t.from_numpy(all_model)

id = np.random.random((5, 10)).astype(np.float32)
id_t = ti.Vector.field(5,ti.f32,shape=(10))
id_t.from_numpy(id)

mesh2 = ti.Vector.field(10, dtype =ti.f32, shape=())

@ti.kernel
def compute(): 
    # all_t[None] is a 10x5 matrix, id_t[0] is a 5 x 1 vector , mesh2 should be a 10x1 vector
    mesh2[None]= all_t[None] @ id_t[0]

compute()

print('mesh2:',mesh2[None])

第三个问题中如果你定义 mesh2 = ti.field(dtype =ti.f32, shape=(1000,50))， 那么mesh2就不是一个scalar field， 就不能用 mesh2[None]， 而是应该用 mesh2[i, j]。

#6

感谢回复，

我复制了你的代码，但是无法正确运行

Traceback (most recent call last):
  File "test/test_mul.py", line 30, in <module>
    id_t.from_numpy(id)
  File "F:\anaconda\envs\opencvandpytorch\lib\site-packages\taichi\lang\util.py", line 310, in wrapped
    return func(*args, **kwargs)
  File "F:\anaconda\envs\opencvandpytorch\lib\site-packages\taichi\lang\matrix.py", line 1376, in from_numpy
    self._from_external_arr(arr)
  File "F:\anaconda\envs\opencvandpytorch\lib\site-packages\taichi\lang\util.py", line 310, in wrapped
    return func(*args, **kwargs)
  File "F:\anaconda\envs\opencvandpytorch\lib\site-packages\taichi\lang\matrix.py", line 1356, in _from_external_arr
    assert len(arr.shape) == len(self.shape) + 2
AssertionError

当我尝试将id_t = ti.Vector.field(5,ti.f32,shape=(10))的10去掉后
代码将会运行到mesh2[None]= all_t[None] @ id_t[0]
并报错：

Traceback (most recent call last):
  File "test/test_mul.py", line 39, in <module>
    compute()
  File "F:\anaconda\envs\opencvandpytorch\lib\site-packages\taichi\lang\kernel_impl.py", line 976, in wrapped
    raise type(e)('\n' + str(e)) from None
taichi.lang.exception.TaichiIndexError:
File "test/test_mul.py", line 37, in compute:
    mesh2[None]= all_t[None] @ id_t[0]
                               ^^^^^^^
Field with dim 0 accessed with indices of dim 1
#7

我修改了一下代码，你再尝试一下？

#8

感谢指点 :grinning:
我再次修改了代码，将其与numpy对齐：

import taichi as ti
import numpy as np

ti.init(arch=ti.cpu)

all_model = np.random.random((10, 5)).astype(np.float32)
all_t = ti.Matrix.field(n=10,m=5,dtype =ti.f32, shape=())
all_t.from_numpy(all_model)

id = np.random.random((5, 1)).astype(np.float32)
id_t = ti.Vector.field(5,ti.f32,shape=())#这里的shape为空才能运行
id_t.from_numpy(id)


mesh2 = ti.Vector.field(10, dtype =ti.f32, shape=())

@ti.kernel
def compute(): 
    # all_t[None] is a 10x5 matrix, id_t[0] is a 5 x 1 vector , mesh2 should be a 10x1 vector
    mesh2[None]= all_t[None] @ id_t[None]


compute()

print('mesh1:',all_model.dot(id))
print('mesh2:',mesh2)

再次感谢，我还需要多研究一下