parameters: (shape, fill_value, dtype=None, order='C', ctx=None, out=None)
return_statement: return _npi.full(shape=shape, value=fill_value, ctx=ctx, dtype=dtype, out=out)
docstring: 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 or _Symbol
          Fill value.
      dtype : data-type, optional
          When npx.is_np_default_dtype() returns False, default dtype is float32;
          When npx.is_np_default_dtype() returns True, default dtype is float64.
          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)
docstring_summary: 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 or _Symbol
          Fill value.
      dtype : data-type, optional
          When npx.is_np_default_dtype() returns False, default dtype is float32;
          When npx.is_np_default_dtype() returns True, default dtype is float64.
          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)
docstring_tokens: 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 or _Symbol Fill value . dtype : data - type optional When npx . is_np_default_dtype () returns False default dtype is float32 ; When npx . is_np_default_dtype () returns True default dtype is float64 . 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 )
function: 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 or _Symbol
          Fill value.
      dtype : data-type, optional
          When npx.is_np_default_dtype() returns False, default dtype is float32;
          When npx.is_np_default_dtype() returns True, default dtype is float64.
          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()
      if isinstance(fill_value, Symbol):
          if dtype is None:
              ret = broadcast_to(fill_value, shape)
          else:
              ret = broadcast_to(fill_value, shape).astype(dtype)
          return ret
      if isinstance(fill_value, bool):
          fill_value = int(fill_value)
          dtype = _np.bool if dtype is None else dtype
      return _npi.full(shape=shape, value=fill_value, ctx=ctx, dtype=dtype, out=out)
function_tokens: def full ( shape , fill_value , dtype = None , order = 'C' , ctx = None , out = None ) : # pylint: disable=too-many-arguments if order != 'C' : raise NotImplementedError if ctx is None : ctx = current_context ( ) if isinstance ( fill_value , Symbol ) : if dtype is None : ret = broadcast_to ( fill_value , shape ) else : ret = broadcast_to ( fill_value , shape ) . astype ( dtype ) return ret if isinstance ( fill_value , bool ) : fill_value = int ( fill_value ) dtype = _np . bool if dtype is None else dtype return _npi . full ( shape = shape , value = fill_value , ctx = ctx , dtype = dtype , out = out )