Xc@`sddlmZmZmZddlZddlZddlmZddlZddl m Z ddl m Z ddlm Z m Z ddlmZddlmZdd lmZmZe Zd ejfd YZeZd ejfd YZdddZdejfdYZddZddZdejfdYZdejfdYZdejfdYZ dddZ!dde"dZ#dZ$ddZ%d ejfd!YZ&dd"Z'd#e jfd$YZ(e(Z)d%Z*d&e jfd'YZ+e+Z,d(Z-d)e jfd*YZ.e.Z/d+Z0dd,Z1d-ejfd.YZ2dS(/i(tabsolute_importtprint_functiontdivisionN(txrange(tbasic(tnlinalg(tgoftscalar(tGeneric(tgradient(tDisconnectedTypetdisconnected_typet CpuContiguouscB`sQeZdZdZidgd6ZdZdZdZdZdZ RS(sn Check to see if the input is c-contiguous, if it is, do nothing, else return a contiguous array. icC`s1tjj|}tj||g|jgS(N(ttheanottensortas_tensor_variabletApplyttype(tselftxtx_((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyt make_nodescC`sP|\}|d}|jds/|j}n|jdsBt||d`_ Notes ----- * Binary search is used to find the required insertion points. * This Op is working **only on CPU** currently. Examples -------- >>> from theano import tensor >>> x = tensor.dvector() >>> idx = x.searchsorted(3) >>> idx.eval({x: [1,2,3,4,5]}) array(2) >>> tensor.extra_ops.searchsorted([1,2,3,4,5], 3).eval() array(2) >>> tensor.extra_ops.searchsorted([1,2,3,4,5], 3, side='right').eval() array(3) >>> tensor.extra_ops.searchsorted([1,2,3,4,5], [-10, 10, 2, 3]).eval() array([0, 5, 1, 2]) .. versionadded:: 0.9 R/(R.(RR?R/R@((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyRFs7tCumOpcB`s\eZd Zd ddZdZdZdZdZdZ d Z d Z RS( taxistmodetaddcC`sD|dkr.tdt|j|fn||_||_dS(NRXtmuls%s: Unknown mode "%s"(saddsmul(R2RR)RVRW(RRVRW((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyR3s " cC`stj|}|j}|jdkrEtjjd|j}n@|j|j ksj|j|j krt dj |jntj ||g|gS(NR6saxis(={0}) out of bounds( RRRRVR:R RtvectorR6R5R2tformatR(RRRA((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyRs %cC`sL|d}|d}itjd6tjd6|j|d|j|d= 2, the main diagonal is the list of locations a[i, i, ..., i] (i.e. with indices all identical).) Support rectangular matrix and tensor with more than 2 dimensions if the later have all dimensions are equals. (tfill_diagonal_(RR((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyRstFillDiagonalOffsetcB`s2eZdZdZdZdZdZRS(cC`s |dgS(Ni((RRR((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyRCscC`sJtj|}tj|}tj|}|jdkrUtd|jjnP|jdkr}td|jjn(|jdkrtd|jjntj|dtj|j |j }|j |j krtd|jjn.|j t jj kr%td|jjnt j ||||g|jgS( Nis4%s: first parameter must have exactly two dimensionsis%%s: second parameter must be a scalars$%s: third parameter must be a scalarR6s<%s: type of second parameter must be the same as the first'ss\%s: type of third parameter must be as integer use theano.tensor.cast( input, 'int32/int64')(RRR5R=RkR)RRRR6R RRRR(RRRtoffset((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyRs('c C`s|dj}|d}|d}|j\}}|dkrd|} tt||||} n.| |jd} tt||||} |jdd} | | | } ||j| | | <||dd>> import numpy as np >>> import theano >>> x = theano.tensor.vector() >>> f = theano.function([x], Unique(True, True, False)(x)) >>> f([1, 2., 3, 4, 3, 2, 1.]) [array([ 1., 2., 3., 4.]), array([0, 1, 2, 3]), array([0, 1, 2, 3, 2, 1, 0])] >>> y = theano.tensor.matrix() >>> g = theano.function([y], Unique(True, True, False)(y)) >>> g([[1, 1, 1.0], (2, 3, 3.0)]) [array([ 1., 2., 3.]), array([0, 3, 4]), array([0, 0, 0, 1, 2, 2])] t return_indextreturn_inverset return_countscC`s||_||_||_gtjjdd D]}t|^q2}|jrt|ddgkrtdt jdndS(Nt.iii sNumpy version = s@. Option 'return_counts=True' works starting from version 1.9.0.( RRRRt __version__tsplittinttboolt RuntimeErrorRE(RRRRRvt numpy_ver((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyR3js   /! cC`stj|}tjdtgd|jg}tjdtgdd}|jrj|j|n|jr|j|n|jr|j|nt j ||g|S(NRR6R7( RRRRR6RtappendRRR R(RRRHRp((s7/tmp/pip-build-X4mzal/theano/theano/tensor/extra_ops.pyRvs$   c C`s|d}|}i}|jr,t|dsL   5 s:~    /2  n I  9  !h