add op isnan isinf (apache#17535)

python/mxnet/ndarray/numpy/_op.py

@@ -43,7 +43,7 @@
            'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
            'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum',
            'true_divide', 'nonzero', 'quantile', 'percentile', 'shares_memory', 'may_share_memory',
-           'diff', 'resize', 'nan_to_num', 'where', 'bincount']
+           'diff', 'resize', 'nan_to_num', 'isnan', 'isinf', 'where', 'bincount']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -6543,6 +6543,106 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None, **kwargs):
         raise TypeError('type {} not supported'.format(str(type(x))))
 
 
+@set_module('mxnet.ndarray.numpy')
+@wrap_np_unary_func
+def isnan(x, out=None, **kwargs):
+    """
+    Test element-wise for NaN and return result as a boolean array.
+
+    Parameters
+    ----------
+    x : ndarray
+        Input array.
+    out : ndarray or None, optional
+        A location into which the result is stored.
+        If provided, it must have the same shape and dtype as input ndarray.
+        If not provided or `None`, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    y : ndarray or bool
+        True where x is NaN, false otherwise.
+        This is a scalar if x is a scalar.
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
+    This means that Not a Number is not equivalent to infinity.
+
+    This function differs from the original `numpy.isnan
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html>`_ in
+    the following aspects:
+    - Does not support complex number for now
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be the same as the expected output.
+    - ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the same as the expected output.
+    - ``out`` param does not support scalar input case.
+
+    Examples
+    --------
+    >>> np.isnan(np.nan)
+    True
+    >>> np.isnan(np.inf)
+    False
+    >>> np.isnan(np.array([np.log(-1.),1.,np.log(0)]))
+    array([ True, False, False])
+    """
+    return _unary_func_helper(x, _npi.isnan, _np.isnan, out=out, **kwargs)
+
+
+@set_module('mxnet.ndarray.numpy')
+@wrap_np_unary_func
+def isinf(x, out=None, **kwargs):
+    """
+    Test element-wise for positive or negative infinity.
+
+    Parameters
+    ----------
+    x : ndarray
+        Input array.
+    out : ndarray or None, optional
+        A location into which the result is stored.
+        If provided, it must have the same shape and dtype as input ndarray.
+        If not provided or `None`, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    y : ndarray or bool
+        True where x is positive or negative infinity, false otherwise.
+        This is a scalar if x is a scalar.
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
+    This means that Not a Number is not equivalent to infinity.
+
+    This function differs from the original `numpy.isnan
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html>`_ in
+    the following aspects:
+    - Does not support complex number for now
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be the same as the expected output.
+    - ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the same as the expected output.
+    - ``out`` param does not support scalar input case.
+
+    Examples
+    --------
+    >>> np.isinf(np.inf)
+    True
+    >>> np.isinf(np.nan)
+    False
+    >>> np.isinf(np.array([np.inf, -np.inf, 1.0, np.nan]))
+    array([ True,  True, False, False])
+    >>> x = np.array([-np.inf, 0., np.inf])
+    >>> y = np.array([True, True, True], dtype=np.bool_)
+    >>> np.isinf(x, y)
+    array([ True, False,  True])
+    >>> y
+    array([ True, False,  True])
+    """
+    return _unary_func_helper(x, _npi.isinf, _np.isinf, out=out, **kwargs)
+
+
 @set_module('mxnet.ndarray.numpy')
 def where(condition, x=None, y=None):
     """where(condition, [x, y])

python/mxnet/numpy/multiarray.py

@@ -64,8 +64,8 @@
            'bitwise_and', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad',
            'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal',
            'greater', 'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero',
-           'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'resize', 'nan_to_num', 'where',
-           'bincount']
+           'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'resize',
+           'nan_to_num', 'isnan', 'isinf', 'where', 'bincount']
 
 __all__ += fallback.__all__
 
@@ -8625,6 +8625,106 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None, **kwargs):
     return _mx_nd_np.nan_to_num(x, copy=copy, nan=nan, posinf=posinf, neginf=neginf)
 
 
+@set_module('mxnet.numpy')
+@wrap_np_unary_func
+def isnan(x, out=None, **kwargs):
+    """
+    Test element-wise for NaN and return result as a boolean array.
+
+    Parameters
+    ----------
+    x : ndarray
+        Input array.
+    out : ndarray or None, optional
+        A location into which the result is stored.
+        If provided, it must have the same shape and dtype as input ndarray.
+        If not provided or `None`, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    y : ndarray or bool
+        True where x is NaN, false otherwise.
+        This is a scalar if x is a scalar.
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
+    This means that Not a Number is not equivalent to infinity.
+
+    This function differs from the original `numpy.isnan
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html>`_ in
+    the following aspects:
+    - Does not support complex number for now
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be the same as the expected output.
+    - ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the same as the expected output.
+    - ``out`` param does not support scalar input case.
+
+    Examples
+    --------
+    >>> np.isnan(np.nan)
+    True
+    >>> np.isnan(np.inf)
+    False
+    >>> np.isnan(np.array([np.log(-1.),1.,np.log(0)]))
+    array([ True, False, False])
+    """
+    return _mx_nd_np.isnan(x, out=out, **kwargs)
+
+
+@set_module('mxnet.numpy')
+@wrap_np_unary_func
+def isinf(x, out=None, **kwargs):
+    """
+    Test element-wise for positive or negative infinity.
+
+    Parameters
+    ----------
+    x : ndarray
+        Input array.
+    out : ndarray or None, optional
+        A location into which the result is stored.
+        If provided, it must have the same shape and dtype as input ndarray.
+        If not provided or `None`, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    y : ndarray or bool
+        True where x is positive or negative infinity, false otherwise.
+        This is a scalar if x is a scalar.
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
+    This means that Not a Number is not equivalent to infinity.
+
+    This function differs from the original `numpy.isnan
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html>`_ in
+    the following aspects:
+    - Does not support complex number for now
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be the same as the expected output.
+    - ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the same as the expected output.
+    - ``out`` param does not support scalar input case.
+
+    Examples
+    --------
+    >>> np.isinf(np.inf)
+    True
+    >>> np.isinf(np.nan)
+    False
+    >>> np.isinf(np.array([np.inf, -np.inf, 1.0, np.nan]))
+    array([ True,  True, False, False])
+    >>> x = np.array([-np.inf, 0., np.inf])
+    >>> y = np.array([True, True, True], dtype=np.bool_)
+    >>> np.isinf(x, y)
+    array([ True, False,  True])
+    >>> y
+    array([ True, False,  True])
+    """
+    return _mx_nd_np.isinf(x, out=out, **kwargs)
+
+
 @set_module('mxnet.numpy')
 def where(condition, x=None, y=None):
     """where(condition, [x, y])

python/mxnet/numpy_dispatch_protocol.py

@@ -171,6 +171,8 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
     'bincount',
     'empty_like',
     'nan_to_num',
+    'isnan',
+    'isinf',
 ]
 
 

python/mxnet/symbol/numpy/_symbol.py

@@ -51,7 +51,7 @@
            'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
            'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum',
            'true_divide', 'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff',
-           'resize', 'nan_to_num', 'where', 'bincount']
+           'resize', 'nan_to_num', 'isnan', 'isinf', 'where', 'bincount']
 
 
 @set_module('mxnet.symbol.numpy')
@@ -5883,6 +5883,82 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None, **kwargs):
         raise TypeError('type {} not supported'.format(str(type(x))))
 
 
+@set_module('mxnet.symbol.numpy')
+@wrap_np_unary_func
+def isnan(x, out=None, **kwargs):
+    """
+    Test element-wise for NaN and return result as a boolean array.
+
+    Parameters
+    ----------
+    x : _Symbol
+        Input array.
+    out : _Symbol or None, optional
+        A location into which the result is stored.
+        If provided, it must have the same shape and dtype as input ndarray.
+        If not provided or `None`, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    y : _Symbol or bool
+        True where x is NaN, false otherwise.
+        This is a scalar if x is a scalar.
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
+    This means that Not a Number is not equivalent to infinity.
+
+    This function differs from the original `numpy.isnan
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html>`_ in
+    the following aspects:
+    - Does not support complex number for now
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be the same as the expected output.
+    - ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the same as the expected output.
+    - ``out`` param does not support scalar input case.
+    """
+    return _unary_func_helper(x, _npi.isnan, _np.isnan, out=out, **kwargs)
+
+
+@set_module('mxnet.symbol.numpy')
+@wrap_np_unary_func
+def isinf(x, out=None, **kwargs):
+    """
+    Test element-wise for positive or negative infinity.
+
+    Parameters
+    ----------
+    x : _Symbol
+        Input array.
+    out : ndarray or None, optional
+        A location into which the result is stored.
+        If provided, it must have the same shape and dtype as input ndarray.
+        If not provided or `None`, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    y : _Symbol or bool
+        True where x is positive or negative infinity, false otherwise.
+        This is a scalar if x is a scalar.
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
+    This means that Not a Number is not equivalent to infinity.
+
+    This function differs from the original `numpy.isnan
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.isnan.html>`_ in
+    the following aspects:
+    - Does not support complex number for now
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be the same as the expected output.
+    - ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the same as the expected output.
+    - ``out`` param does not support scalar input case.
+    """
+    return _unary_func_helper(x, _npi.isinf, _np.isinf, out=out, **kwargs)
+
+
 @set_module('mxnet.symbol.numpy')
 def where(condition, x, y):
     """

src/operator/mshadow_op.h

@@ -683,6 +683,22 @@ struct fix : public mxnet_op::tunable {
   }
 };
 
+/*! \brief used to determine whether a number is Not A Number*/
+struct isnan : public mxnet_op::tunable {
+  template<typename DType>
+  MSHADOW_XINLINE static bool Map(DType a) {
+    return IsNan(a);
+  }
+};
+
+/*! \brief used to determine whether a number is infinite*/
+struct isinf : public mxnet_op::tunable {
+  template<typename DType>
+  MSHADOW_XINLINE static bool Map(DType a) {
+    return IsInf(a);
+  }
+};
+
 /*! \brief used for generate gradient of MAE loss*/
 MXNET_BINARY_MATH_OP_NC(minus_sign, a - b > DType(0) ? DType(1) : -DType(1));
 

src/operator/numpy/np_elemwise_unary_op_basic.cc

@@ -287,6 +287,14 @@ MXNET_OPERATOR_REGISTER_NUMPY_UNARY(_npi_expm1, "x", mshadow_op::expm1)
 MXNET_OPERATOR_REGISTER_NUMPY_UNARY_LOGIC(_npi_logical_not, "x", mshadow_op::np_logical_not)
 .set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes);
 
+// isnan
+MXNET_OPERATOR_REGISTER_NUMPY_UNARY_LOGIC(_npi_isnan, "x", mshadow_op::isnan)
+.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes);
+
+// isinf
+MXNET_OPERATOR_REGISTER_NUMPY_UNARY_LOGIC(_npi_isinf, "x", mshadow_op::isinf)
+.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes);
+
 // sin
 MXNET_OPERATOR_REGISTER_NUMPY_UNARY(_npi_sin, "x", mshadow_op::sin)
 .describe(R"code(Trigonometric sine, element-wise.

src/operator/numpy/np_elemwise_unary_op_basic.cu

@@ -82,6 +82,12 @@ MXNET_OPERATOR_REGISTER_NUMPY_UNARY_GPU(_npi_expm1, mshadow_op::expm1);
 NNVM_REGISTER_OP(_npi_logical_not)
 .set_attr<FCompute>("FCompute<gpu>", UnaryOp::ComputeLogic<gpu, mshadow_op::np_logical_not>);
 
+NNVM_REGISTER_OP(_npi_isnan)
+.set_attr<FCompute>("FCompute<gpu>", UnaryOp::ComputeLogic<gpu, mshadow_op::isnan>);
+
+NNVM_REGISTER_OP(_npi_isinf)
+.set_attr<FCompute>("FCompute<gpu>", UnaryOp::ComputeLogic<gpu, mshadow_op::isinf>);
+
 MXNET_OPERATOR_REGISTER_NUMPY_UNARY_GPU(_npi_sin, mshadow_op::sin);
 
 MXNET_OPERATOR_REGISTER_NUMPY_UNARY_GPU(_npi_cos, mshadow_op::cos);

src/operator/operator_tune.cc

@@ -312,6 +312,8 @@ IMPLEMENT_UNARY_WORKLOAD_BWD(mxnet::op::mshadow_op::radians_grad);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::nt);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD_WITH_BOOL(mxnet::op::mshadow_op::np_logical_not);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD_WITH_BOOL(mxnet::op::mshadow_op::bitwise_not);  // NOLINT()
+IMPLEMENT_UNARY_WORKLOAD_FWD_WITH_BOOL(mxnet::op::mshadow_op::isnan);  // NOLINT()
+IMPLEMENT_UNARY_WORKLOAD_FWD_WITH_BOOL(mxnet::op::mshadow_op::isinf);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_BWD(mxnet::op::mshadow_op::nt);  // NOLINT()
 IMPLEMENT_BINARY_WORKLOAD_FWD(mxnet::op::mshadow_op::clip);  // NOLINT()
 IMPLEMENT_BINARY_WORKLOAD_BWD(mxnet::op::mshadow_op::clip);  // NOLINT()