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- import numpy as np
-
- import megengine.functional as F
- from megengine import Tensor
- from megengine.core._trace_option import use_symbolic_shape
-
-
- def test_zero_dim():
- a = Tensor(1)
- a_np = np.array(1, dtype=np.int32)
- np.testing.assert_equal(a, a_np)
- if use_symbolic_shape():
- np.testing.assert_equal(a.shape, np.array(a_np.shape))
- else:
- np.testing.assert_equal(a.shape, a_np.shape)
-
-
- def test_sum():
- a = Tensor([1, 2])
- a = a.reshape((1, 2))
- assert a.sum().ndim == 0
- assert a.sum(axis=1).ndim == 1
-
-
- def test_max():
- a = Tensor([1, 2])
- a = a.reshape((1, 2))
- assert a.max().ndim == 0
- assert a.max(axis=1).ndim == 1
-
-
- def test_reshape():
- a = Tensor(1)
- a = a.reshape((1, 1))
-
-
- def test_squeeze():
- a = Tensor(1)
- a = a.reshape((1, 1))
- assert F.squeeze(a).ndim == 0
-
-
- def test_elemementwise():
- a = Tensor(1.0)
- assert F.exp(a).ndim == 0
- assert (a + a).ndim == 0
- assert (a + 1).ndim == 0
-
-
- def test_astype():
- a = Tensor(1.0)
- assert a.astype("int32").ndim == 0
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