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105 lines
3.1 KiB
105 lines
3.1 KiB
import numpy as np
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
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class Net(nn.Cell):
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def __init__(self, transpose_x1, transpose_x2):
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super(Net, self).__init__()
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self.matmul = nn.MatMul(transpose_x1, transpose_x2)
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def construct(self, x1, x2):
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return self.matmul(x1, x2)
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def test_x1_2D_x2_3D():
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x1 = np.random.randn(16, 64).astype(np.float32)
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x2 = np.random.randn(32, 64, 20).astype(np.float32)
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transpose_x1 = False
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transpose_x2 = False
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (32, 16, 20)
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def test_x1_4D_x2_3D_transpose_x2_True():
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x1 = np.random.randn(3, 2, 3, 4).astype(np.float32)
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x2 = np.random.randn(1, 5, 4).astype(np.float32)
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transpose_x1 = False
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transpose_x2 = True
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (3, 2, 3, 5)
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def test_x1_3D_transpose_x1_True_x2_2D():
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x1 = np.random.randn(2, 3, 4).astype(np.float32)
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x2 = np.random.randn(3, 4).astype(np.float32)
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transpose_x1 = True
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transpose_x2 = False
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (2, 4, 4)
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def test_x1_3D_transpose_x1_True_x2_3D_transpose_x2_True():
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x1 = np.random.randn(2, 5, 6).astype(np.float32)
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x2 = np.random.randn(2, 4, 5).astype(np.float32)
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transpose_x1 = True
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transpose_x2 = True
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (2, 6, 4)
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def test_x1_1D_x2_1D():
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x1 = np.random.randn(4).astype(np.float32)
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x2 = np.random.randn(4).astype(np.float32)
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transpose_x1 = False
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transpose_x2 = False
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == ()
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def test_x1_1D_x2_3D():
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x1 = np.random.randn(4).astype(np.float32)
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x2 = np.random.randn(2, 4, 5).astype(np.float32)
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transpose_x1 = False
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transpose_x2 = False
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (2, 5)
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def test_x1_3D_x2_1D():
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x1 = np.random.randn(2, 4, 5).astype(np.float32)
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x2 = np.random.randn(5).astype(np.float32)
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transpose_x1 = False
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transpose_x2 = False
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (2, 4)
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def test_x1_1D_transpose_x1_True_x2_3D():
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x1 = np.random.randn(4).astype(np.float32)
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x2 = np.random.randn(2, 4, 5).astype(np.float32)
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transpose_x1 = True
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transpose_x2 = False
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (2, 5)
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def test_x1_3D_x2_1D_transpose_x2_True():
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x1 = np.random.randn(2, 4, 5).astype(np.float32)
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x2 = np.random.randn(5).astype(np.float32)
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transpose_x1 = False
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transpose_x2 = True
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net = Net(transpose_x1, transpose_x2)
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output = net(Tensor(x1), Tensor(x2))
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assert output.shape == (2, 4)
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