ó ùµÈ[c@@sÉdZddlmZddlZddlmZde fd„ƒYZ de fd „ƒYZ d e fd „ƒYZ d e fd „ƒYZ de fd„ƒYZde fd„ƒYZddd„ZdS(sExtra symbol documentsi(tabsolute_importNi(tbuild_param_doct NDArrayDoccB@seZdZRS(sThe basic class(t__name__t __module__t__doc__(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyRst ReshapeDoccB@seZdZRS(sJ Examples -------- Reshapes the input array into a new shape. >>> x = mx.nd.array([1, 2, 3, 4]) >>> y = mx.nd.reshape(x, shape=(2, 2)) >>> x.shape (4L,) >>> y.shape (2L, 2L) >>> y.asnumpy() array([[ 1., 2.], [ 3., 4.]], dtype=float32) You can use ``0`` to copy a particular dimension from the input to the output shape and '-1' to infer the dimensions of the output. >>> x = mx.nd.ones((2, 3, 4)) >>> x.shape (2L, 3L, 4L) >>> y = mx.nd.reshape(x, shape=(4, 0, -1)) >>> y.shape (4L, 3L, 2L) (RRR(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyRstelemwise_addDoccB@seZdZRS(sì Example ------- >>> x = mx.nd.array([1, 2, 3, 4]) >>> y = mx.nd.array([1.1, 2.1, 3.1, 4.1]) >>> mx.nd.elemwise_add(x, y).asnumpy() array([ 2.0999999 , 4.0999999 , 6.0999999 , 8.10000038], dtype=float32) (RRR(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyR9s tBroadcastToDoccB@seZdZRS(s/ Examples -------- Broadcasts the input array into a new shape. >>> a = mx.nd.array(np.arange(6).reshape(6,1)) >>> b = a.broadcast_to((6,2)) >>> a.shape (6L, 1L) >>> b.shape (6L, 2L) >>> b.asnumpy() array([[ 0., 0.], [ 1., 1.], [ 2., 2.], [ 3., 3.], [ 4., 4.], [ 5., 5.]], dtype=float32) Broadcasts along axes 1 and 2. >>> c = a.reshape((2,1,1,3)) >>> d = c.broadcast_to((2,2,2,3)) >>> d.asnumpy() array([[[[ 0., 1., 2.], [ 0., 1., 2.]], [[ 0., 1., 2.], [ 0., 1., 2.]]], [[[ 3., 4., 5.], [ 3., 4., 5.]], [[ 3., 4., 5.], [ 3., 4., 5.]]]], dtype=float32) >>> c.shape (2L, 1L, 1L, 3L) >>> d.shape (2L, 2L, 2L, 3L) (RRR(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyRDs&tStackDoccB@seZdZRS(sò Example -------- Join a sequence of arrays along a new axis. >>> x = mx.nd.array([1, 2]) >>> y = mx.nd.array([3, 4]) >>> stack(x, y) [[1, 2], [3, 4]] >>> stack(x, y, axis=1) [[1, 3], [2, 4]] (RRR(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyR ls t CustomDoccB@seZdZRS(s¯ Example ------- Applies a custom operator named `my_custom_operator` to `input`. >>> output = mx.symbol.Custom(op_type='my_custom_operator', data=input) (RRR(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyR {sc C@sÀt|||ƒ}ddddddd}|||f}d d jgtjtƒD]"} | jd |krY| j^qYƒ} |tjtj d ƒd | ƒ7}tjd d|ƒ}|S(s)Build docstring for imperative functions.s%s s%s sout : NDArray, optional s, The output NDArray to hold the result. sReturns s------- s"out : NDArray or list of NDArrays s The output of this function.s s%sDocs tsNDArray-or-SymboltNDArrays%s %s ( t_build_param_doctjointtypet__subclasses__RRRt_retsubtcompile( t func_nametdesct arg_namest arg_typestarg_desctkey_var_num_argstret_typet param_strtdoc_strtxt extra_doc((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyt _build_doc„s &"(Rt __future__Rt_abstreRtbaseRR tobjectRRRRR R tNoneR(((sQ/usr/local/lib/python2.7/site-packages/mxnet-1.3.1-py2.7.egg/mxnet/ndarray_doc.pyts  (