飞桨paddle技术点整理

前面的步骤跟乌班图安装Pytorch、Tensorflow Cuda环境 是一样。

安装GPU版本的paddle

python -m pip install paddlepaddle-gpu==2.3.1.post116 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html

张量

import paddle

if __name__ == '__main__':

    a = paddle.to_tensor([[1, 2], [3, 4]])
    print(a)
    print(a.shape)
    print(a.type)

    b = paddle.ones([2, 2])
    print(b)
    print(b.type)

    c = paddle.zeros([2, 2])
    print(c)
    print(c.type)

    d = paddle.eye(2, 2)
    print(d)
    print(d.type)

    e = paddle.zeros_like(a)
    print(e)
    print(e.type)

    f = paddle.ones_like(a)
    print(f)
    print(f.type)

    g = paddle.arange(0, 11, 1)
    print(g)
    print(g.type)

    h = paddle.linspace(2, 10, 4)
    print(h)

    i = paddle.rand([2, 2])
    print(i)

    j = paddle.normal(mean=0.0, std=paddle.rand([5]))
    print(j)

    k = paddle.uniform(shape=[2, 2])
    print(k)

    l = paddle.randperm(10)
    print(l)

运行结果

Tensor(shape=[2, 2], dtype=int64, place=Place(gpu:0), stop_gradient=True,
       [[1, 2],
        [3, 4]])
[2, 2]
VarType.LOD_TENSOR
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[1., 1.],
        [1., 1.]])
VarType.LOD_TENSOR
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0., 0.],
        [0., 0.]])
VarType.LOD_TENSOR
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[1., 0.],
        [0., 1.]])
VarType.LOD_TENSOR
Tensor(shape=[2, 2], dtype=int64, place=Place(gpu:0), stop_gradient=True,
       [[0, 0],
        [0, 0]])
VarType.LOD_TENSOR
Tensor(shape=[2, 2], dtype=int64, place=Place(gpu:0), stop_gradient=True,
       [[1, 1],
        [1, 1]])
VarType.LOD_TENSOR
Tensor(shape=[11], dtype=int64, place=Place(gpu:0), stop_gradient=True,
       [0 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10])
VarType.LOD_TENSOR
Tensor(shape=[4], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [2.        , 4.66666651, 7.33333349, 10.       ])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0.17855753, 0.15026711],
        [0.54343289, 0.04870688]])
Tensor(shape=[5], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [-0.07493367, -0.10425358, -1.67506480,  0.02299307,  0.38065284])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[ 0.01213348, -0.30467188],
        [-0.81535292,  0.09958601]])
Tensor(shape=[10], dtype=int64, place=Place(gpu:0), stop_gradient=True,
       [2, 9, 4, 5, 8, 7, 0, 1, 6, 3])

• 算数运算、矩阵乘法

import paddle

if __name__ == '__main__':

    a = paddle.to_tensor([[1., 2.], [3., 4.]])
    print(a)

    b = paddle.ones([2, 2])
    print(b)

    c = a + b
    print(c)

    c = paddle.add(a, b)
    print(c)

    d = paddle.subtract(a, b)
    print(d)

    e = paddle.to_tensor([2., 3.])
    f = a * e
    print(f)

    f = paddle.multiply(a, e)
    print(f)

    g = a / e
    print(g)

    g = paddle.divide(a, e)
    print(g)

    h = paddle.to_tensor([[1, 2, 3], [4, 5, 6]], dtype='float32')
    i = paddle.to_tensor([[2, 4], [11, 13], [7, 9]], dtype='float32')
    j = paddle.mm(h, i)
    print(j)

    k = paddle.matmul(h, i)
    print(k)

运行结果

Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[1., 2.],
        [3., 4.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[1., 1.],
        [1., 1.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[2., 3.],
        [4., 5.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[2., 3.],
        [4., 5.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0., 1.],
        [2., 3.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[2. , 6. ],
        [6. , 12.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[2. , 6. ],
        [6. , 12.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0.50000000, 0.66666669],
        [1.50000000, 1.33333337]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[0.50000000, 0.66666669],
        [1.50000000, 1.33333337]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[45. , 57. ],
        [105., 135.]])
Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
       [[45. , 57. ],
        [105., 135.]])

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