dmlc--dgl
Quan (Andy) Gan
e19cd62ecd
* test basics * batched graph & filter, mxnet filter fix * frame and function; bugfix * test graph adj and inc matrices * fixing start = 0 for mxnet * test index * inplace update & line graph * multi send recv * more tests * oops * more tests * removing old test files; readonly graphs for mxnet still kept * modifying test scripts * adding a placeholder for pytorch to reserve directory * torch 0.4.1 compat fixes * moving backend out of compute to avoid nose detection * tests guide * mx sparse-to-dense/sparse-to-numpy is buggy * oops * contribution guide for unit tests * printing incmat * printing dlpack * small push * typo * fixing duplicate entries that causes undefined behavior * move equal comparison to backend
94 行
2.5 KiB
Python
94 行
2.5 KiB
Python
import dgl
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import dgl.ndarray as nd
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from dgl.utils import toindex
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import numpy as np
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import backend as F
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def test_dlpack():
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# test dlpack conversion.
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def nd2th():
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ans = np.array([[1., 1., 1., 1.],
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[0., 0., 0., 0.],
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[0., 0., 0., 0.]])
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x = nd.array(np.zeros((3, 4), dtype=np.float32))
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dl = x.to_dlpack()
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y = F.zerocopy_from_dlpack(dl)
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y[0] = 1
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print(x)
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print(y)
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assert np.allclose(x.asnumpy(), ans)
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def th2nd():
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ans = np.array([[1., 1., 1., 1.],
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[0., 0., 0., 0.],
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[0., 0., 0., 0.]])
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x = F.zeros((3, 4))
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dl = F.zerocopy_to_dlpack(x)
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y = nd.from_dlpack(dl)
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x[0] = 1
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print(x)
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print(y)
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assert np.allclose(y.asnumpy(), ans)
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def th2nd_incontiguous():
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x = F.astype(F.tensor([[0, 1], [2, 3]]), F.int64)
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ans = np.array([0, 2])
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y = x[:2, 0]
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# Uncomment this line and comment the one below to observe error
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#dl = dlpack.to_dlpack(y)
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dl = F.zerocopy_to_dlpack(y)
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z = nd.from_dlpack(dl)
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print(x)
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print(z)
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assert np.allclose(z.asnumpy(), ans)
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nd2th()
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th2nd()
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th2nd_incontiguous()
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def test_index():
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ans = np.ones((10,), dtype=np.int64) * 10
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# from np data
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data = np.ones((10,), dtype=np.int64) * 10
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idx = toindex(data)
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y1 = idx.tonumpy()
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y2 = F.asnumpy(idx.tousertensor())
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y3 = idx.todgltensor().asnumpy()
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assert np.allclose(ans, y1)
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assert np.allclose(ans, y2)
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assert np.allclose(ans, y3)
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# from list
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data = [10] * 10
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idx = toindex(data)
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y1 = idx.tonumpy()
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y2 = F.asnumpy(idx.tousertensor())
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y3 = idx.todgltensor().asnumpy()
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assert np.allclose(ans, y1)
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assert np.allclose(ans, y2)
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assert np.allclose(ans, y3)
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# from torch
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data = F.ones((10,), dtype=F.int64) * 10
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idx = toindex(data)
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y1 = idx.tonumpy()
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y2 = F.asnumpy(idx.tousertensor())
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y3 = idx.todgltensor().asnumpy()
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assert np.allclose(ans, y1)
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assert np.allclose(ans, y2)
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assert np.allclose(ans, y3)
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# from dgl.NDArray
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data = dgl.ndarray.array(np.ones((10,), dtype=np.int64) * 10)
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idx = toindex(data)
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y1 = idx.tonumpy()
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y2 = F.asnumpy(idx.tousertensor())
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y3 = idx.todgltensor().asnumpy()
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assert np.allclose(ans, y1)
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assert np.allclose(ans, y2)
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assert np.allclose(ans, y3)
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if __name__ == '__main__':
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test_dlpack()
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test_index()
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