[Numpy] Numpy operator diff

python/mxnet/ndarray/numpy/_op.py

@@ -38,7 +38,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', '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', 'shares_memory', 'may_share_memory']
+           'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero', 'shares_memory', 'may_share_memory', 'diff']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -4983,3 +4983,51 @@ def may_share_memory(a, b, max_work=None):
     - Actually it is same as `shares_memory` in MXNet DeepNumPy
     """
     return _npi.share_memory(a, b).item()
+
+
+def diff(a, n=1, axis=-1, prepend=None, append=None):
+    r"""
+    numpy.diff(a, n=1, axis=-1, prepend=<no value>, append=<no value>)
+
+    Calculate the n-th discrete difference along the given axis.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input array
+    n : int, optional
+        The number of times values are differenced. If zero, the input is returned as-is.
+    axis : int, optional
+        The axis along which the difference is taken, default is the last axis.
+    prepend, append : ndarray, optional
+        Not supported yet
+
+    Returns
+    -------
+    diff : ndarray
+        The n-th differences.
+        The shape of the output is the same as a except along axis where the dimension is smaller by n.
+        The type of the output is the same as the type of the difference between any two elements of a.
+
+    Examples
+    --------
+    >>> x = np.array([1, 2, 4, 7, 0])
+    >>> np.diff(x)
+    array([ 1,  2,  3, -7])
+    >>> np.diff(x, n=2)
+    array([  1,   1, -10])
+
+    >>> x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]])
+    >>> np.diff(x)
+    array([[2, 3, 4],
+        [5, 1, 2]])
+    >>> np.diff(x, axis=0)
+    array([[-1,  2,  0, -2]])
+
+    Notes
+    -----
+    Optional inputs `prepend` and `append` are not supported yet
+    """
+    if (prepend or append):
+        raise NotImplementedError('prepend and append options are not supported yet')
+    return _npi.diff(a, n=n, axis=axis)

python/mxnet/numpy/multiarray.py

@@ -56,7 +56,7 @@
            'blackman', 'flip', 'around', 'arctan2', 'hypot', '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', 'shares_memory',
-           'may_share_memory']
+           'may_share_memory', 'diff']
 
 # Return code for dispatching indexing function call
 _NDARRAY_UNSUPPORTED_INDEXING = -1
@@ -6975,3 +6975,52 @@ def may_share_memory(a, b, max_work=None):
     - Actually it is same as `shares_memory` in MXNet DeepNumPy
     """
     return _mx_nd_np.may_share_memory(a, b, max_work)
+
+
+def diff(a, n=1, axis=-1, prepend=None, append=None):
+    r"""
+    numpy.diff(a, n=1, axis=-1, prepend=<no value>, append=<no value>)
+
+    Calculate the n-th discrete difference along the given axis.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input array
+    n : int, optional
+        The number of times values are differenced. If zero, the input is returned as-is.
+    axis : int, optional
+        The axis along which the difference is taken, default is the last axis.
+    prepend, append : ndarray, optional
+        Not supported yet
+
+    Returns
+    -------
+    diff : ndarray
+        The n-th differences.
+        The shape of the output is the same as a except along axis where the dimension is smaller by n.
+        The type of the output is the same as the type of the difference between any two elements of a.
+        This is the same as the type of a in most cases.
+
+    Examples
+    --------
+    >>> x = np.array([1, 2, 4, 7, 0])
+    >>> np.diff(x)
+    array([ 1,  2,  3, -7])
+    >>> np.diff(x, n=2)
+    array([  1,   1, -10])
+
+    >>> x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]])
+    >>> np.diff(x)
+    array([[2, 3, 4],
+        [5, 1, 2]])
+    >>> np.diff(x, axis=0)
+    array([[-1,  2,  0, -2]])
+
+    Notes
+    -----
+    Optional inputs `prepend` and `append` are not supported yet
+    """
+    if (prepend or append):
+        raise NotImplementedError('prepend and append options are not supported yet')
+    return _mx_nd_np.diff(a, n=n, axis=axis)

python/mxnet/numpy_dispatch_protocol.py

@@ -130,6 +130,7 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
     'einsum',
     'shares_memory',
     'may_share_memory',
+    'diff',
 ]
 
 

python/mxnet/symbol/numpy/_symbol.py

@@ -40,7 +40,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', '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', 'shares_memory', 'may_share_memory']
+           'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'shares_memory', 'may_share_memory', 'diff']
 
 
 def _num_outputs(sym):
@@ -4629,4 +4629,53 @@ def may_share_memory(a, b, max_work=None):
     return _npi.share_memory(a, b)
 
 
+def diff(a, n=1, axis=-1, prepend=None, append=None):
+    r"""
+    numpy.diff(a, n=1, axis=-1, prepend=<no value>, append=<no value>)
+
+    Calculate the n-th discrete difference along the given axis.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input array
+    n : int, optional
+        The number of times values are differenced. If zero, the input is returned as-is.
+    axis : int, optional
+        The axis along which the difference is taken, default is the last axis.
+    prepend, append : ndarray, optional
+        Not supported yet
+
+    Returns
+    -------
+    diff : ndarray
+        The n-th differences.
+        The shape of the output is the same as a except along axis where the dimension is smaller by n.
+        The type of the output is the same as the type of the difference between any two elements of a.
+        This is the same as the type of a in most cases.
+
+    Examples
+    --------
+    >>> x = np.array([1, 2, 4, 7, 0])
+    >>> np.diff(x)
+    array([ 1,  2,  3, -7])
+    >>> np.diff(x, n=2)
+    array([  1,   1, -10])
+
+    >>> x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]])
+    >>> np.diff(x)
+    array([[2, 3, 4],
+        [5, 1, 2]])
+    >>> np.diff(x, axis=0)
+    array([[-1,  2,  0, -2]])
+
+    Notes
+    -----
+    Optional inputs `prepend` and `append` are not supported yet
+    """
+    if (prepend or append):
+        raise NotImplementedError('prepend and append options are not supported yet')
+    return _npi.diff(a, n=n, axis=axis)
+
+
 _set_np_symbol_class(_Symbol)