forked from mindspore-Ecosystem/mindspore
fix
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@ -2141,13 +2141,12 @@ def lcm(x1, x2, dtype=None):
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def _lcm(x1, x2):
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"""Calculates lcm without applying keyword arguments"""
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common_divisor = _gcd(x1, x2)
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dtype = _promote(F.dtype(x1), F.dtype(x2))
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x1 = x1.astype(mstype.float32)
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x2 = x2.astype(mstype.float32)
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q1 = F.tensor_div(x1, common_divisor)
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q2 = F.tensor_div(x2, common_divisor)
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res = F.tensor_mul(F.tensor_mul(q1, q2), common_divisor)
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dtype = F.dtype(res)
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if not _check_is_float(dtype):
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# F.absolute only supports float
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res = F.cast(res, mstype.float32)
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return F.absolute(res).astype(dtype)
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return _apply_tensor_op(_lcm, x1, x2, dtype=dtype)
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@ -4602,7 +4601,7 @@ def histogram(a, bins=10, range=None, weights=None, density=False): # pylint: di
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Deprecated numpy argument `normed` is not supported.
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Args:
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x (Union[int, float, bool, list, tuple, Tensor]): Input data. The histogram
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a (Union[int, float, bool, list, tuple, Tensor]): Input data. The histogram
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is computed over the flattened array.
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bins (Union[int, tuple, list, Tensor], optional): If `bins` is an int, it
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defines the number of equal-width bins in the given range (10, by
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@ -5278,6 +5277,8 @@ def unwrap(p, discont=3.141592653589793, axis=-1):
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>>> print(np.unwrap(phase))
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[ 0.0000000e+00 7.8539819e-01 1.5707964e+00 -7.8539848e-01 -4.7683716e-07]
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"""
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if not isinstance(discont, (int, float)):
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_raise_type_error('discont should be a float')
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p = _to_tensor(p)
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ndim = F.rank(p)
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axis = _check_axis_in_range(axis, ndim)
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@ -2172,7 +2172,7 @@ def test_bincount():
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onp.bincount(x, weights, minlength=25), error=3)
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@pytest.mark.level2
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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@ -2195,7 +2195,7 @@ def test_histogram():
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match_all_arrays(mnp_res, onp_res, error=1)
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@pytest.mark.level2
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@pytest.mark.level1
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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@ -2238,7 +2238,7 @@ def test_histogramdd():
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match_all_arrays(mnp_res[1], onp_res[1], error=3)
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@pytest.mark.level2
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@pytest.mark.level1
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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