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value_iteration_6D.py
Source:value_iteration_6D.py 
...9# ptsEachDim: the number of grid points in each dimension of the state space10# useNN: a mode flag (0: use linear interpolation, 1: use nearest neighbour)11def updateVopt(obj, i, j, k, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN):12 p = hcl.scalar(0, "p")13 with hcl.for_(0, actions.shape[0], name="a") as a:14 # set iVals equal to (i,j,k,l,m,n) and sVals equal to the corresponding state values (si,sj,sk,sl,sm,sn)15 updateStateVals(i, j, k, l, m, n, iVals, sVals, bounds, ptsEachDim)16 # call the transition function to obtain the outcome(s) of action a from state (si,sj,sk,sl,sm,sn)17 obj.transition(sVals, actions[a], bounds, trans, goal)18 # initialize the value of the action Q value with the immediate reward of taking that action19 intermeds[a] = obj.reward(sVals, actions[a], bounds, goal, trans)20 # add the value of each possible successor state to the Q value21 with hcl.for_(0, trans.shape[0], name="si") as si:22 p[0] = trans[si,0]23 sVals[0] = trans[si,1]24 sVals[1] = trans[si,2]25 sVals[2] = trans[si,3]26 sVals[3] = trans[si,4]27 sVals[4] = trans[si,5]28 sVals[5] = trans[si,6]29 # Nearest neighbour30 with hcl.if_(useNN[0] == 1):31 # convert the state values of the successor state (si,sj,sk,sl,sm,sn) into indeces (ia,ja,ka,la,ma,na)32 stateToIndex(sVals, iVals, bounds, ptsEachDim)33 # if (ia,ja,ka,la,ma,na) is within the state space, add its discounted value to the Q value34 with hcl.if_(hcl.and_(iVals[0] < Vopt.shape[0], iVals[1] < Vopt.shape[1], iVals[2] < Vopt.shape[2])):35 with hcl.if_(hcl.and_(iVals[3] < Vopt.shape[3], iVals[4] < Vopt.shape[4], iVals[5] < Vopt.shape[5])):36 with hcl.if_(hcl.and_(iVals[0] >= 0, iVals[1] >= 0, iVals[2] >= 0, iVals[3] >= 0, iVals[4] >= 0, iVals[5] >= 0)):37 intermeds[a] += (gamma[0] * (p[0] * Vopt[iVals[0], iVals[1], iVals[2], iVals[3], iVals[4], iVals[5]]))38 # maximize over each Q value to obtain the optimal value39 Vopt[i,j,k,l,m,n] = -100000040 with hcl.for_(0, intermeds.shape[0], name="r") as r:41 with hcl.if_(Vopt[i,j,k,l,m,n] < intermeds[r]):42 Vopt[i,j,k,l,m,n] = intermeds[r]43# Returns 0 if convergence has been reached44def evaluateConvergence(newV, oldV, epsilon, reSweep):45 delta = hcl.scalar(0, "delta")46 # Calculate the difference, if it's negative, make it positive47 delta[0] = newV[0] - oldV[0]48 with hcl.if_(delta[0] < 0):49 delta[0] = delta[0] * -150 with hcl.if_(delta[0] > epsilon[0]):51 reSweep[0] = 152# Converts state values into indeces using nearest neighbour rounding53def stateToIndex(sVals, iVals, bounds, ptsEachDim):54 iVals[0] = ((sVals[0] - bounds[0,0]) / (bounds[0,1] - bounds[0,0])) * (ptsEachDim[0] - 1)55 iVals[1] = ((sVals[1] - bounds[1,0]) / (bounds[1,1] - bounds[1,0])) * (ptsEachDim[1] - 1)56 iVals[2] = ((sVals[2] - bounds[2,0]) / (bounds[2,1] - bounds[2,0])) * (ptsEachDim[2] - 1)57 iVals[3] = ((sVals[3] - bounds[3,0]) / (bounds[3,1] - bounds[3,0])) * (ptsEachDim[3] - 1)58 iVals[4] = ((sVals[4] - bounds[4,0]) / (bounds[4,1] - bounds[4,0])) * (ptsEachDim[4] - 1)59 iVals[5] = ((sVals[5] - bounds[5,0]) / (bounds[5,1] - bounds[5,0])) * (ptsEachDim[5] - 1)60 # NOTE: add 0.5 to simulate rounding61 iVals[0] = hcl.cast(hcl.Int(), iVals[0] + 0.5)62 iVals[1] = hcl.cast(hcl.Int(), iVals[1] + 0.5)63 iVals[2] = hcl.cast(hcl.Int(), iVals[2] + 0.5)64 iVals[3] = hcl.cast(hcl.Int(), iVals[3] + 0.5)65 iVals[4] = hcl.cast(hcl.Int(), iVals[4] + 0.5)66 iVals[5] = hcl.cast(hcl.Int(), iVals[5] + 0.5)67# Convert indices into state values68def indexToState(iVals, sVals, bounds, ptsEachDim):69 sVals[0] = bounds[0,0] + ( (bounds[0,1] - bounds[0,0]) * (iVals[0] / (ptsEachDim[0]-1)) ) 70 sVals[1] = bounds[1,0] + ( (bounds[1,1] - bounds[1,0]) * (iVals[1] / (ptsEachDim[1]-1)) ) 71 sVals[2] = bounds[2,0] + ( (bounds[2,1] - bounds[2,0]) * (iVals[2] / (ptsEachDim[2]-1)) ) 72 sVals[3] = bounds[3,0] + ( (bounds[3,1] - bounds[3,0]) * (iVals[3] / (ptsEachDim[3]-1)) ) 73 sVals[4] = bounds[4,0] + ( (bounds[4,1] - bounds[4,0]) * (iVals[4] / (ptsEachDim[4]-1)) ) 74 sVals[5] = bounds[5,0] + ( (bounds[5,1] - bounds[5,0]) * (iVals[5] / (ptsEachDim[5]-1)) ) 75# Sets iVals equal to (i,j,k,l,m,n) and sVals equal to the corresponding state values76def updateStateVals(i, j, k, l, m, n, iVals, sVals, bounds, ptsEachDim):77 iVals[0] = i78 iVals[1] = j79 iVals[2] = k80 iVals[3] = l81 iVals[4] = m82 iVals[5] = n83 indexToState(iVals, sVals, bounds, ptsEachDim)84######################################### VALUE ITERATION ##########################################85# Main value iteration algorithm86# reSweep: a convergence flag (1: continue iterating, 0: convergence reached)87# epsilon: convergence criteria88# maxIters: maximum number of iterations that can occur without convergence being reached89# count: the number of iterations that have been performed90def value_iteration_6D(MDP_obj):91 def solve_Vopt(Vopt, actions, intermeds, trans, interpV, gamma, epsilon, iVals, sVals, bounds, goal, ptsEachDim, count, maxIters, useNN):92 reSweep = hcl.scalar(1, "reSweep")93 oldV = hcl.scalar(0, "oldV")94 newV = hcl.scalar(0, "newV")95 with hcl.while_(hcl.and_(reSweep[0] == 1, count[0] < maxIters[0])):96 reSweep[0] = 097 # Perform value iteration by sweeping in direction 198 with hcl.Stage("Sweep_1"):99 with hcl.for_(0, Vopt.shape[0], name="i") as i:100 with hcl.for_(0, Vopt.shape[1], name="j") as j:101 with hcl.for_(0, Vopt.shape[2], name="k") as k:102 with hcl.for_(0, Vopt.shape[3], name="l") as l:103 with hcl.for_(0, Vopt.shape[4], name="m") as m:104 with hcl.for_(0, Vopt.shape[5], name="n") as n:105 oldV[0] = Vopt[i,j,k,l,m,n]106 updateVopt(MDP_obj, i, j, k, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)107 newV[0] = Vopt[i,j,k,l,m,n]108 evaluateConvergence(newV, oldV, epsilon, reSweep)109 count[0] += 1110 # Perform value iteration by sweeping in direction 2111 with hcl.Stage("Sweep_2"):112 with hcl.if_(useNN[0] == 1):113 with hcl.for_(1, Vopt.shape[0] + 1, name="i") as i:114 with hcl.for_(1, Vopt.shape[1] + 1, name="j") as j:115 with hcl.for_(1, Vopt.shape[2] + 1, name="k") as k:116 with hcl.for_(0, Vopt.shape[3], name="l") as l:117 with hcl.for_(0, Vopt.shape[4], name="m") as m:118 with hcl.for_(0, Vopt.shape[5], name="n") as n:119 i2 = Vopt.shape[0] - i120 j2 = Vopt.shape[1] - j121 k2 = Vopt.shape[2] - k122 oldV[0] = Vopt[i2,j2,k2,l,m,n]123 updateVopt(MDP_obj, i2, j2, k2, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)124 newV[0] = Vopt[i2,j2,k2,l,m,n]125 evaluateConvergence(newV, oldV, epsilon, reSweep)126 count[0] += 1127 # Perform value iteration by sweeping in direction 3128 with hcl.Stage("Sweep_3"):129 with hcl.if_(useNN[0] == 1):130 with hcl.for_(1, Vopt.shape[0] + 1, name="i") as i:131 with hcl.for_(0, Vopt.shape[1], name="j") as j:132 with hcl.for_(0, Vopt.shape[2], name="k") as k:133 with hcl.for_(0, Vopt.shape[3], name="l") as l:134 with hcl.for_(0, Vopt.shape[4], name="m") as m:135 with hcl.for_(0, Vopt.shape[5], name="n") as n:136 i2 = Vopt.shape[0] - i137 oldV[0] = Vopt[i2,j,k,l,m,n]138 updateVopt(MDP_obj, i2, j, k, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)139 newV[0] = Vopt[i2,j,k,l,m,n]140 evaluateConvergence(newV, oldV, epsilon, reSweep)141 count[0] += 1142 # Perform value iteration by sweeping in direction 4143 with hcl.Stage("Sweep_4"):144 with hcl.if_(useNN[0] == 1):145 with hcl.for_(0, Vopt.shape[0], name="i") as i:146 with hcl.for_(1, Vopt.shape[1] + 1, name="j") as j:147 with hcl.for_(0, Vopt.shape[2], name="k") as k:148 with hcl.for_(0, Vopt.shape[3], name="l") as l:149 with hcl.for_(0, Vopt.shape[4], name="m") as m:150 with hcl.for_(0, Vopt.shape[5], name="n") as n:151 j2 = Vopt.shape[1] - j152 oldV[0] = Vopt[i,j2,k,l,m,n]153 updateVopt(MDP_obj, i, j2, k, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)154 newV[0] = Vopt[i,j2,k,l,m,n]155 evaluateConvergence(newV, oldV, epsilon, reSweep)156 count[0] += 1157 # Perform value iteration by sweeping in direction 5158 with hcl.Stage("Sweep_5"):159 with hcl.if_(useNN[0] == 1):160 with hcl.for_(0, Vopt.shape[0], name="i") as i:161 with hcl.for_(0, Vopt.shape[1], name="j") as j:162 with hcl.for_(1, Vopt.shape[2] + 1, name="k") as k:163 with hcl.for_(0, Vopt.shape[3], name="l") as l:164 with hcl.for_(0, Vopt.shape[4], name="m") as m:165 with hcl.for_(0, Vopt.shape[5], name="n") as n:166 k2 = Vopt.shape[2] - k167 oldV[0] = Vopt[i,j,k2,l,m,n]168 updateVopt(MDP_obj, i, j, k2, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)169 newV[0] = Vopt[i,j,k2,l,m,n]170 evaluateConvergence(newV, oldV, epsilon, reSweep)171 count[0] += 1172 # Perform value iteration by sweeping in direction 6173 with hcl.Stage("Sweep_6"):174 with hcl.if_(useNN[0] == 1):175 with hcl.for_(1, Vopt.shape[0] + 1, name="i") as i:176 with hcl.for_(1, Vopt.shape[1] + 1, name="j") as j:177 with hcl.for_(0, Vopt.shape[2], name="k") as k:178 with hcl.for_(0, Vopt.shape[3], name="l") as l:179 with hcl.for_(0, Vopt.shape[4], name="m") as m:180 with hcl.for_(0, Vopt.shape[5], name="n") as n:181 i2 = Vopt.shape[0] - i182 j2 = Vopt.shape[1] - j183 oldV[0] = Vopt[i2,j2,k,l,m,n]184 updateVopt(MDP_obj, i2, j2, k, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)185 newV[0] = Vopt[i2,j2,k,l,m,n]186 evaluateConvergence(newV, oldV, epsilon, reSweep)187 count[0] += 1188 # Perform value iteration by sweeping in direction 7189 with hcl.Stage("Sweep_7"):190 with hcl.if_(useNN[0] == 1):191 with hcl.for_(1, Vopt.shape[0] + 1, name="i") as i:192 with hcl.for_(0, Vopt.shape[1], name="j") as j:193 with hcl.for_(1, Vopt.shape[2] + 1, name="k") as k:194 with hcl.for_(0, Vopt.shape[3], name="l") as l:195 with hcl.for_(0, Vopt.shape[4], name="m") as m:196 with hcl.for_(0, Vopt.shape[5], name="n") as n:197 i2 = Vopt.shape[0] - i198 k2 = Vopt.shape[2] - k199 oldV[0] = Vopt[i2,j,k2,l,m,n]200 updateVopt(MDP_obj, i2, j, k2, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)201 newV[0] = Vopt[i2,j,k2,l,m,n]202 evaluateConvergence(newV, oldV, epsilon, reSweep)203 count[0] += 1204 # Perform value iteration by sweeping in direction 8205 with hcl.Stage("Sweep_8"):206 with hcl.if_(useNN[0] == 1):207 with hcl.for_(0, Vopt.shape[0], name="i") as i:208 with hcl.for_(1, Vopt.shape[1] + 1, name="j") as j:209 with hcl.for_(1, Vopt.shape[2] + 1, name="k") as k:210 with hcl.for_(0, Vopt.shape[3], name="l") as l:211 with hcl.for_(0, Vopt.shape[4], name="m") as m:212 with hcl.for_(0, Vopt.shape[5], name="n") as n:213 j2 = Vopt.shape[1] - j214 k2 = Vopt.shape[2] - k215 oldV[0] = Vopt[i,j2,k2,l,m,n]216 updateVopt(MDP_obj, i, j2, k2, l, m, n, iVals, sVals, actions, Vopt, intermeds, trans, interpV, gamma, bounds, goal, ptsEachDim, useNN)217 newV[0] = Vopt[i,j2,k2,l,m,n]218 evaluateConvergence(newV, oldV, epsilon, reSweep)219 count[0] += 1220 ###################################### SETUP PLACEHOLDERS ######################################221 222 # Initialize the HCL environment223 hcl.init()224 hcl.config.init_dtype = hcl.Float()225 # NOTE: trans is a tensor with size = maximum number of transitions226 # NOTE: intermeds must have size [# possible actions]...
TimeToReach_5D.py
Source:TimeToReach_5D.py
...72 #debugger[i, j, k, l] = phiNew[0]73 phi[i, j, k, l, m] = my_min(phi[i, j, k, l, m], phiNew[0])74def EvalBoundary(phi, g):75 if 0 not in g.pDim:76 with hcl.for_(0, phi.shape[1], name="j") as j:77 with hcl.for_(0, phi.shape[2], name="k") as k:78 with hcl.for_(0, phi.shape[3], name="l") as l:79 with hcl.for_(0, phi.shape[4], name="m") as m:80 #debug2[0] = j81 tmp1 = hcl.scalar(0, "tmp1")82 tmp1[0] = 2 * phi[1, j, k, l, m] - phi[2, j, k, l, m]83 tmp1[0] = my_max(tmp1[0], phi[2, j, k, l, m])84 phi[0, j, k, l, m] = my_min(tmp1[0], phi[0, j, k, l, m])85 tmp2 = hcl.scalar(0, "tmp2")86 tmp2[0] = 2 * phi[phi.shape[0] - 2, j, k, l, m] - phi[phi.shape[0] - 3, j, k, l, m]87 tmp2[0] = my_max(tmp2[0], phi[phi.shape[0] - 3, j, k, l, m])88 phi[phi.shape[0] - 1, j, k, l, m] = my_min(tmp2[0], phi[phi.shape[0] - 1, j, k, l, m])89 if 1 not in g.pDim:90 with hcl.for_(0, phi.shape[0], name="i") as i:91 with hcl.for_(0, phi.shape[2], name="k") as k:92 with hcl.for_(0, phi.shape[3], name="l") as l:93 with hcl.for_(0, phi.shape[4], name="m") as m:94 tmp1 = hcl.scalar(0, "tmp1")95 tmp1[0] = 2 * phi[i, 1, k, l] - phi[i, 2, k, l, m]96 tmp1[0] = my_max(tmp1[0], phi[i, 2, k, l, m])97 phi[i, 0, k, l, m] = my_min(tmp1[0], phi[i, 0, k, l, m])98 tmp2 = hcl.scalar(0, "tmp2")99 tmp2[0] = 2 * phi[i, phi.shape[1] - 2, k, l, m] - phi[i, phi.shape[1] - 3, k, l, m]100 tmp2[0] = my_max(tmp2[0], phi[i, phi.shape[1] - 3, k, l, m])101 phi[i, phi.shape[1] - 1, k, l, m] = my_min(tmp2[0], phi[i, phi.shape[1] - 1, k, l, m])102 if 2 not in g.pDim:103 with hcl.for_(0, phi.shape[0], name="i") as i:104 with hcl.for_(0, phi.shape[1], name="j") as j:105 with hcl.for_(0, phi.shape[3], name="l") as l:106 with hcl.for_(0, phi.shape[4], name="m") as m:107 tmp1 = hcl.scalar(0, "tmp1")108 tmp1[0] = 2 * phi[i, j, 1, l, m] - phi[i, j, 2, l, m]109 tmp1[0] = my_max(tmp1[0], phi[i, j, 2, l, m])110 phi[i, j, 0, l, m] = my_min(tmp1[0], phi[i, j, 0, l, m])111 tmp2 = hcl.scalar(0, "tmp2")112 tmp2[0] = 2 * phi[i, j, phi.shape[2] - 2, l, m] - phi[i, j, phi.shape[2] - 3, l, m]113 tmp2[0] = my_max(tmp2[0], phi[i, j, phi.shape[2] - 3, l, m])114 phi[i, j, phi.shape[2] - 1, l, m] = my_min(tmp2[0], phi[i, j, phi.shape[2] - 1, l, m])115 if 3 not in g.pDim:116 with hcl.for_(0, phi.shape[0], name="i") as i:117 with hcl.for_(0, phi.shape[1], name="j") as j:118 with hcl.for_(0, phi.shape[2], name="k") as k:119 with hcl.for_(0, phi.shape[4], name="m") as m:120 tmp1 = hcl.scalar(0, "tmp1")121 tmp1[0] = 2 * phi[i, j, k, 1, m] - phi[i, j, k, 2, m]122 tmp1[0] = my_max(tmp1[0], phi[i, j, k, 2, m])123 phi[i, j, k, 0, m] = my_min(tmp1[0], phi[i, j, k, 0, m])124 tmp2 = hcl.scalar(0, "tmp2")125 tmp2[0] = 2 * phi[i, j, k, phi.shape[2] - 2, m] - phi[i, j, k, phi.shape[2] - 3, m]126 tmp2[0] = my_max(tmp2[0], phi[i, j, k, phi.shape[2] - 3, m])127 phi[i, j, k, phi.shape[2] - 1, m] = my_min(tmp2[0], phi[i, j, k, phi.shape[2] - 1, m])128 if 4 not in g.pDim:129 with hcl.for_(0, phi.shape[0], name="i") as i:130 with hcl.for_(0, phi.shape[1], name="j") as j:131 with hcl.for_(0, phi.shape[2], name="k") as k:132 with hcl.for_(0, phi.shape[3], name="l") as l:133 tmp1 = hcl.scalar(0, "tmp1")134 tmp1[0] = 2 * phi[i, j, k, l, 1] - phi[i, j, k, l, 2]135 tmp1[0] = my_max(tmp1[0], phi[i, j, k, l, 2])136 phi[i, j, k, l, 0] = my_min(tmp1[0], phi[i, j, k, l, 0])137 tmp2 = hcl.scalar(0, "tmp2")138 tmp2[0] = 2 * phi[i, j, k, l, phi.shape[2] - 2] - phi[i, j, k, l, phi.shape[2] - 3]139 tmp2[0] = my_max(tmp2[0], phi[i, j, k, l, phi.shape[2] - 3])140 phi[i, j, k, l, phi.shape[2] - 1] = my_min(tmp2[0], phi[i, j, k, l, phi.shape[2] - 1])141######################################### VALUE ITERATION ##########################################142def TTR_5D(my_object, g):143 def solve_phiNew(phi, x1, x2, x3, x4, x5):144 l_i = 0 if 0 in g.pDim else 1145 h_i = phi.shape[0] if 0 in g.pDim else phi.shape[0] - 1146 l_j = 0 if 1 in g.pDim else 1147 h_j = phi.shape[1] if 1 in g.pDim else phi.shape[1] - 1148 l_k = 0 if 2 in g.pDim else 1149 h_k = phi.shape[2] if 2 in g.pDim else phi.shape[2] - 1150 l_l = 0 if 3 in g.pDim else 1151 h_l = phi.shape[3] if 3 in g.pDim else phi.shape[3] - 1152 l_m = 0 if 4 in g.pDim else 1153 h_m = phi.shape[4] if 4 in g.pDim else phi.shape[4] - 1154 # Perform value iteration by sweeping in direction 1155 with hcl.Stage("Sweep_1"):156 with hcl.for_(l_i, h_i, name="i") as i:157 with hcl.for_(l_j, h_j, name="j") as j:158 with hcl.for_(l_k, h_k, name="k") as k:159 with hcl.for_(l_l, h_l, name="l") as l:160 with hcl.for_(l_m, h_m, name="m") as m:161 updatePhi(i, j, k, l, m, my_object, phi, g, x1, x2, x3, x4, x5)162 EvalBoundary(phi, g)163 # Perform value iteration by sweeping in direction 2164 with hcl.Stage("Sweep_2"):165 with hcl.for_(l_i, h_i, name="i") as i:166 with hcl.for_(l_j, h_j, name="j") as j:167 with hcl.for_(l_k, h_k, name="k") as k:168 with hcl.for_(l_l, h_l, name="l") as l:169 with hcl.for_(l_m, h_m, name="m") as m:170 i2 = phi.shape[0] - i - 1171 j2 = phi.shape[1] - j - 1172 k2 = phi.shape[2] - k - 1173 l2 = phi.shape[3] - l - 1174 m2 = phi.shape[4] - m - 1175 updatePhi(i2, j2, k2, l2, m2, my_object, phi, g, x1, x2, x3, x4, x5)176 EvalBoundary(phi, g)177 # Perform value iteration by sweeping in direction 3178 with hcl.Stage("Sweep_3"):179 with hcl.for_(l_i, h_i, name="i") as i:180 with hcl.for_(l_j, h_j, name="j") as j:181 with hcl.for_(l_k, h_k, name="k") as k:182 with hcl.for_(l_l, h_l, name="l") as l:183 with hcl.for_(l_m, h_m, name="m") as m:184 i2 = phi.shape[0] - i - 1185 j2 = phi.shape[1] - j - 1186 k2 = phi.shape[2] - k - 1187 l2 = phi.shape[3] - l - 1188 updatePhi(i2, j2, k2, l2, m, my_object, phi, g, x1, x2, x3, x4, x5)189 EvalBoundary(phi, g)190 # Perform value iteration by sweeping in direction 4191 with hcl.Stage("Sweep_4"):192 with hcl.for_(l_i, h_i, name="i") as i:193 with hcl.for_(l_j, h_j, name="j") as j:194 with hcl.for_(l_k, h_k, name="k") as k:195 with hcl.for_(l_l, h_l, name="l") as l:196 with hcl.for_(l_m, h_m, name="m") as m:197 i2 = phi.shape[0] - i - 1198 j2 = phi.shape[1] - j - 1199 k2 = phi.shape[2] - k - 1200 updatePhi(i2, j2, k2, l, m, my_object, phi, g, x1, x2, x3, x4, x5)201 EvalBoundary(phi, g)202 # Perform value iteration by sweeping in direction 5203 with hcl.Stage("Sweep_5"):204 with hcl.for_(l_i, h_i, name="i") as i:205 with hcl.for_(l_j, h_j, name="j") as j:206 with hcl.for_(l_k, h_k, name="k") as k:207 with hcl.for_(l_l, h_l, name="l") as l:208 with hcl.for_(l_m, h_m, name="m") as m:209 i2 = phi.shape[0] - i - 1210 j2 = phi.shape[1] - j - 1211 updatePhi(i2, j2, k, l, m, my_object, phi, g, x1, x2, x3, x4, x5)212 EvalBoundary(phi, g)213 # Perform value iteration by sweeping in direction 6214 with hcl.Stage("Sweep_6"):215 with hcl.for_(l_i, h_i, name="i") as i:216 with hcl.for_(l_j, h_j, name="j") as j:217 with hcl.for_(l_k, h_k, name="k") as k:218 with hcl.for_(l_l, h_l, name="l") as l:219 with hcl.for_(l_m, h_m, name="m") as m:220 i2 = phi.shape[0] - i - 1221 updatePhi(i2, j, k, l, m, my_object, phi, g, x1, x2, x3, x4, x5)222 EvalBoundary(phi, g)223 # Perform value iteration by sweeping in direction 7224 with hcl.Stage("Sweep_7"):225 with hcl.for_(l_i, h_i, name="i") as i:226 with hcl.for_(l_j, h_j, name="j") as j:227 with hcl.for_(l_k, h_k, name="k") as k:228 with hcl.for_(l_l, h_l, name="l") as l:229 with hcl.for_(l_m, h_m, name="m") as m:230 j2 = phi.shape[1] - j - 1231 updatePhi(i, j2, k, l, m, my_object, phi, g, x1, x2, x3, x4, x5)232 EvalBoundary(phi, g)233 # Perform value iteration by sweeping in direction 8234 with hcl.Stage("Sweep_8"):235 with hcl.for_(l_i, h_i, name="i") as i:236 with hcl.for_(l_j, h_j, name="j") as j:237 with hcl.for_(l_k, h_k, name="k") as k:238 with hcl.for_(l_l, h_l, name="l") as l:239 with hcl.for_(l_m, h_m, name="m") as m:240 j2 = phi.shape[1] - j - 1241 k2 = phi.shape[2] - k - 1242 updatePhi(i, j2, k2, l, m, my_object, phi, g, x1, x2, x3, x4, x5)243 EvalBoundary(phi, g)244 ###################################### SETUP PLACEHOLDERS ######################################245 # Positions vector246 x1 = hcl.placeholder((g.pts_each_dim[0],), name="x1", dtype=hcl.Float())247 x2 = hcl.placeholder((g.pts_each_dim[1],), name="x2", dtype=hcl.Float())248 x3 = hcl.placeholder((g.pts_each_dim[2],), name="x3", dtype=hcl.Float())249 x4 = hcl.placeholder((g.pts_each_dim[3],), name="x4", dtype=hcl.Float())250 x5 = hcl.placeholder((g.pts_each_dim[4],), name="x5", dtype=hcl.Float())251 phi = hcl.placeholder(tuple(g.pts_each_dim), name="phi", dtype=hcl.Float())252 debugger = hcl.placeholder(tuple(g.pts_each_dim), name="debugger", dtype=hcl.Float())253 debug2 = hcl.placeholder((0,), "debug2")...
main.py
Source:main.py
1import asyncio2from discord.ext import commands3client = commands.Bot(command_prefix='kh!')4@client.event5async def on_ready():6 print('bot is ready')7@client.command()8@commands.has_permissions(manage_channels=True, administrator=True)9async def delete_channels(ctx, channel_name, *, exceptions='None'):10 deleted_channels = 011 if exceptions == 'None':12 guild = client.get_guild(ctx.guild.id)13 for channel in ctx.guild.text_channels:14 is_exception = False15 if channel.name == channel_name:16 await channel.delete()17 deleted_channels += 118 if deleted_channels == 0:19 await ctx.send("Couldn't find any channels with that name")20 else:21 try:22 await ctx.send(f'Found and deleted {deleted_channels} channels')23 except Exception: 24 pass25 else:26 exceptions_cont = exceptions.split(', ')27 guild = client.get_guild(ctx.guild.id)28 for channel in ctx.guild.text_channels:29 is_exception = False30 if channel.name == channel_name:31 for exception in exceptions_cont:32 if int(channel.id) == int(exception):33 is_exception = True34 if is_exception:35 pass36 else:37 await channel.delete()38 deleted_channels += 139 if deleted_channels == 0:40 await ctx.send("Couldn't find any channels with that name")41 else:42 try:43 await ctx.send(f'Found and deleted {deleted_channels} channels')44 except Exception: 45 pass46@client.command()47@commands.has_guild_permissions(manage_roles=True, administrator=True)48async def delete_roles(ctx, role_name, *, exceptions=None):49 deleted_roles = 050 if exceptions == None:51 guild = client.get_guild(ctx.guild.id)52 for role in ctx.guild.roles:53 is_exception = False54 if role.name == role_name:55 await role.delete()56 deleted_roles += 157 if deleted_roles == 0:58 await ctx.send("Couldn't find any roles with that name")59 else:60 await ctx.send(f'Found and deleted {deleted_roles} roles')61 else:62 try:63 exceptions_cont = exceptions.split(' --exc ')64 65 if len(exceptions_cont) > 1:66 role_name = role_name + ' ' + exceptions_cont[0]67 if not exceptions_cont[1] == '':68 exceptions = exceptions_cont[1].split(', ')69 else:70 exceptions = exceptions.split(', ')71 72 except Exception as e:73 exceptions = exceptions.split(', ')74 75 guild = client.get_guild(ctx.guild.id)76 for role in ctx.guild.roles:77 is_exception = False78 if role.name == '@everyone':79 continue80 if role.name == role_name:81 for exception in exceptions:82 if int(role.id) == int(exception):83 is_exception = True84 if is_exception:85 pass86 else:87 await role.delete()88 deleted_roles += 189 if deleted_roles == 0:90 await ctx.send("Couldn't find any roles with that name")91 else:92 await ctx.send(f'Found and deleted {deleted_roles} roles')93@client.command()94@commands.has_guild_permissions(manage_guild=True)95async def delete_messages(ctx, for_, *, message_):96 guild = int(ctx.guild.id)97 if str(for_).endswith('m'):98 for_ = for_[:-1]99 for_ = int(for_) * 60100 elif str(for_).endswith('s'):101 for_ = for_[:-1]102 for_ = int(for_)103 elif str(for_).endswith('h'):104 for_ = for_[:-1]105 for_ = int(for_)106 else:107 for_ = for_[:-1]108 for_ = int(for_)109 @client.listen()110 async def on_message(message):111 if message.guild.id == ctx.guild.id:112 if message.content == message_:113 await message.delete()114 await asyncio.sleep(for_)115 client.remove_listener(func=on_message)...
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