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solve conflict
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@Yiyan66
Yiyan66 committed Dec 11, 2019
1 parent da03340 commit 15b40b4
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204 changes: 95 additions & 109 deletions python/mxnet/symbol/numpy/_symbol.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,11 +36,11 @@
except ImportError:
from builtins import slice as py_slice

__all__ = ['zeros', 'zeros_like', 'ones', 'ones_like', 'full_like',
__all__ = ['zeros', 'zeros_like', 'ones', 'ones_like', 'full_like', 'bitwise_not', 'invert',
'add', 'subtract', 'multiply', 'divide', 'mod', 'remainder', 'power', 'arctan2',
'sin', 'cos', 'tan', 'sinh', 'cosh', 'tanh', 'log10', 'sqrt', 'cbrt', 'abs', 'absolute', 'exp',
'expm1', 'arcsin', 'arccos', 'arctan', 'sign', 'log', 'degrees', 'log2', 'log1p', 'bitwise_not',
'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor', 'invert',
'expm1', 'arcsin', 'arccos', 'arctan', 'sign', 'log', 'degrees', 'log2', 'log1p',
'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor',
'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'argsort', 'tensordot', 'histogram', 'eye',
'linspace', 'logspace', 'expand_dims', 'tile', 'arange', 'split', 'vsplit', 'concatenate', 'append',
'stack', 'vstack', 'column_stack', 'dstack', 'average', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip',
Expand Down Expand Up @@ -1040,6 +1040,98 @@ def ones(shape, dtype=_np.float32, order='C', ctx=None):
return _npi.ones(shape=shape, ctx=ctx, dtype=dtype)


@set_module('mxnet.symbol.numpy')
@wrap_np_unary_func
def invert(x, out=None, **kwargs):
r"""
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of
the integers in the input arrays. This ufunc implements the C/Python
operator ``~``.
Parameters
----------
x : array_like
Only integer and boolean types are handled.
out : ndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
Returns
-------
out : ndarray or scalar
Result.
This is a scalar if `x` is a scalar.
See Also
--------
bitwise_and, bitwise_or, bitwise_xor
logical_not
binary_repr :
Return the binary representation of the input number as a string.
Examples
--------
We've seen that 13 is represented by ``00001101``.
The invert or bit-wise NOT of 13 is then:
>>> x = np.invert(np.array(13, dtype=np.uint8))
>>> x
242
>>> np.binary_repr(x, width=8)
'11110010'
Notes
-----
`bitwise_not` is an alias for `invert`:
>>> np.bitwise_not is np.invert
True
"""
return _unary_func_helper(x, _npi.bitwise_not, _np.bitwise_not, out=out, **kwargs)


@set_module('mxnet.symbol.numpy')
@wrap_np_unary_func
def bitwise_not(x, out=None, **kwargs):
r"""
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of
the integers in the input arrays. This ufunc implements the C/Python
operator ``~``.
Parameters
----------
x : array_like
Only integer and boolean types are handled.
out : ndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
Returns
-------
out : ndarray or scalar
Result.
This is a scalar if `x` is a scalar.
See Also
--------
bitwise_and, bitwise_or, bitwise_xor
logical_not
binary_repr :
Return the binary representation of the input number as a string.
Examples
--------
We've seen that 13 is represented by ``00001101``.
The invert or bit-wise NOT of 13 is then:
>>> x = np.invert(np.array(13, dtype=np.uint8))
>>> x
242
>>> np.binary_repr(x, width=8)
'11110010'
Notes
-----
`bitwise_not` is an alias for `invert`:
>>> np.bitwise_not is np.invert
True
"""
return _unary_func_helper(x, _npi.bitwise_not, _np.bitwise_not, out=out, **kwargs)


@set_module('mxnet.symbol.numpy')
def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None): # pylint: disable=too-many-arguments
"""
Expand Down Expand Up @@ -2806,112 +2898,6 @@ def floor(x, out=None, **kwargs):
return _unary_func_helper(x, _npi.floor, _np.floor, out=out, **kwargs)


@set_module('mxnet.symbol.numpy')
@wrap_np_unary_func
def invert(x, out=None, **kwargs):
r"""
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of
the integers in the input arrays. This ufunc implements the C/Python
operator ``~``.
Parameters
----------
x : array_like
Only integer and boolean types are handled.
out : ndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
Returns
-------
out : ndarray or scalar
Result.
This is a scalar if `x` is a scalar.
See Also
--------
bitwise_and, bitwise_or, bitwise_xor
logical_not
binary_repr :
Return the binary representation of the input number as a string.
Examples
--------
We've seen that 13 is represented by ``00001101``.
The invert or bit-wise NOT of 13 is then:
>>> x = np.invert(np.array(13, dtype=np.uint8))
>>> x
242
>>> np.binary_repr(x, width=8)
'11110010'
Notes
-----
`bitwise_not` is an alias for `invert`:
>>> np.bitwise_not is np.invert
True
"""
return _unary_func_helper(x, _npi.bitwise_not, _np.bitwise_not, out=out, **kwargs)


@set_module('mxnet.symbol.numpy')
@wrap_np_unary_func
def bitwise_not(x, out=None, **kwargs):
r"""
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of
the integers in the input arrays. This ufunc implements the C/Python
operator ``~``.
Parameters
----------
x : array_like
Only integer and boolean types are handled.
out : ndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
Returns
-------
out : ndarray or scalar
Result.
This is a scalar if `x` is a scalar.
See Also
--------
bitwise_and, bitwise_or, bitwise_xor
logical_not
binary_repr :
Return the binary representation of the input number as a string.
Examples
--------
We've seen that 13 is represented by ``00001101``.
The invert or bit-wise NOT of 13 is then:
>>> x = np.invert(np.array(13, dtype=np.uint8))
>>> x
242
>>> np.binary_repr(x, width=8)
'11110010'
Notes
-----
`bitwise_not` is an alias for `invert`:
>>> np.bitwise_not is np.invert
True
"""
return _unary_func_helper(x, _npi.bitwise_not, _np.bitwise_not, out=out, **kwargs)


@set_module('mxnet.symbol.numpy')
@wrap_np_unary_func
def trunc(x, out=None, **kwargs):
Expand Down
6 changes: 1 addition & 5 deletions tests/python/unittest/test_numpy_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3737,11 +3737,7 @@ def get_grad_b(A, X):
nrhs = (-1, 0, 1, 2, 3)
dtypes = ['float32', 'float64']
for hybridize, shape, dtype, nrh in itertools.product([False, True], shapes, dtypes, nrhs):
rtol = 1e-3
atol = 1e-5
if dtype == 'float32':
rtol = 1e-2
atol = 1e-4
rtol, atol =1e-2, 1e-4
test_solve = TestSolve()
if hybridize:
test_solve.hybridize()
Expand Down

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