Completed NDArray indexing fix and numpy ndarray indexing.

3rdparty/mshadow/mshadow/extension/slice.h

@@ -33,8 +33,8 @@ struct SliceExp : public TRValue<SliceExp<SrcExp,
       : src_(src), ch_begin_(begin) {
     shape_ = ShapeCheck<srcdim, SrcExp>::Check(src_);
     ch_old_ = shape_[dimslice];
-    CHECK(begin < shape_[dimslice] && end <= shape_[dimslice])
-        << "The slice went out of range";
+    CHECK(begin <= shape_[dimslice] && end <= shape_[dimslice])
+        << "The slice went out of range. ";
     shape_[dimslice] = end - begin;
   }
   template<typename E, int etype>

python/mxnet/ndarray/numpy/_op.py

@@ -27,7 +27,7 @@
 from . import _internal as _npi
 from ..ndarray import NDArray
 
-__all__ = ['zeros', 'ones', 'add', 'subtract', 'multiply', 'divide', 'mod', 'power', 'sin',
+__all__ = ['zeros', 'ones', 'full', 'add', 'subtract', 'multiply', 'divide', 'mod', 'power', 'sin',
            'cos', 'tan', 'sinh', 'cosh', 'tanh', 'log10', 'sqrt', 'cbrt', 'abs', 'absolute',
            'exp', 'expm1', 'arcsin', 'arccos', 'arctan', 'sign', 'log', 'degrees', 'log2', 'log1p',
            'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor',
@@ -103,6 +103,61 @@ def ones(shape, dtype=_np.float32, order='C', ctx=None):
     return _npi.ones(shape=shape, ctx=ctx, dtype=dtype)
 
 
+@set_module('mxnet.ndarray.numpy')
+def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None):  # pylint: disable=too-many-arguments
+    """
+    Return a new array of given shape and type, filled with `fill_value`.
+    Parameters
+    ----------
+    shape : int or sequence of ints
+        Shape of the new array, e.g., ``(2, 3)`` or ``2``.
+    fill_value : scalar
+        Fill value.
+    dtype : data-type, optional
+        The desired data-type for the array. The default, `None`, means
+        `np.array(fill_value).dtype`.
+    order : {'C'}, optional
+        Whether to store multidimensional data in C- or Fortran-contiguous
+        (row- or column-wise) order in memory. Currently only supports C order.
+    ctx: to specify the device, e.g. the i-th GPU.
+    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
+    -------
+    out : ndarray
+        Array of `fill_value` with the given shape, dtype, and order.
+    Notes
+    -----
+    This function differs from the original `numpy.full
+    https://docs.scipy.org/doc/numpy/reference/generated/numpy.full.html`_ in
+    the following way(s):
+    - Have an additional `ctx` argument to specify the device
+    - Have an additional `out` argument
+    - Currently does not support `order` selection
+    See Also
+    --------
+    empty : Return a new uninitialized array.
+    ones : Return a new array setting values to one.
+    zeros : Return a new array setting values to zero.
+    Examples
+    --------
+    >>> np.full((2, 2), 10)
+    array([[10., 10.],
+           [10., 10.]])
+    >>> np.full((2, 2), 2, dtype=np.int32, ctx=mx.cpu(0))
+    array([[2, 2],
+           [2, 2]], dtype=int32)
+    """
+    if order != 'C':
+        raise NotImplementedError
+    if ctx is None:
+        ctx = current_context()
+    dtype = _np.float32 if dtype is None else dtype
+    return _npi.full(shape=shape, value=fill_value, ctx=ctx, dtype=dtype, out=out)
+
+
 @set_module('mxnet.ndarray.numpy')
 def arange(start, stop=None, step=1, dtype=None, ctx=None):
     """Return evenly spaced values within a given interval.