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How to use g_target method in autotest
Best Python code snippet using autotest_python
TransformCxCascade.py
Source:TransformCxCascade.py 
1import logging2from qiskit.dagcircuit import DAGCircuit3from qiskit.extensions import CXGate, U2Gate4from qiskit.transpiler import TransformationPass, TranspilerError5from qiskit.transpiler.passes import Unroller, Optimize1qGates, CXCancellation6from qiskit.qasm import pi7logger = logging.getLogger(__name__)8class TransformCxCascade(TransformationPass):9 """10 Finds CNOT cascades int the dag and transform them into nearest-neighbor CNOT sequences,11 which are more easily mapped over a real device coupling map::12 ---x--x--x--x--- --------x--------13 | | | | |14 ---o--|--|--|--- ------x-o-x------15 | | | | |16 ------o--|--|--- ---> ----x-o---o-x----17 | | | |18 ---------o--|--- --x-o-------o-x--19 | | |20 ------------o--- --o-----------o--21 ---o--o--o--o--- -H-------x-------H-22 | | | | |23 ---x--|--|--|--- -H-----x-o-x-----H-24 | | | | |25 ------x--|--|--- ---> -H---x-o---o-x---H-26 | | | |27 ---------x--|--- -H-x-o-------o-x-H-28 | | |29 ------------x--- -H-o-----------o-H-30 """31 def __init__(self):32 """TransformCxCascade initializer.33 Raises:34 TranspilerError: if run after the layout has been set.35 """36 super().__init__()37 if self.property_set['layout']:38 raise TranspilerError('TransformCxCascade pass must be run before any layout has been set.')39 self.requires.append(Unroller(['u1', 'u2', 'u3', 'cx', 'id']))40 self._num_qubits = None41 self._wires_to_id = {}42 self._id_to_wires = {}43 self._layers = None44 self._extra_layers = None45 self._skip = []46 def run(self, dag):47 """48 Run the CNOTCascadesTransform pass over a dag circuit.49 After the transformation, proceeds to check for possible one-qubit gates optimizations and50 CNOT cancellations, as subsequent CNOT nearest-neighbor sequences could create51 the opportunity for useful circuit simplifications.52 Args:53 dag (DAGCircuit): the dag circuit to be searched for CNOT cascades.54 Returns:55 new_dag (DAGCircuit): a new dag where all CNOT cascades have been transformed.56 """57 # prepare new dag58 new_dag = DAGCircuit()59 new_dag.name = dag.name60 self._num_qubits = dag.num_qubits()61 for q_reg in dag.qregs.values():62 new_dag.add_qreg(q_reg)63 for c_reg in dag.cregs.values():64 new_dag.add_creg(c_reg)65 i = 066 for q_reg in dag.qregs.values():67 for q in q_reg:68 self._wires_to_id[q] = i69 self._id_to_wires[i] = q70 i += 171 depth = new_dag.depth()72 while True:73 new_dag = Optimize1qGates().run(new_dag)74 new_dag = CXCancellation().run(new_dag)75 new_depth = new_dag.depth()76 if new_depth < depth:77 depth = new_depth78 else:79 break80 # get dag layers81 self._layers = [layer['graph'] for layer in dag.layers()]82 # this is the list of new layers for the nearest-neighbor CNOT sequences83 self._extra_layers = {l: [] for l in range(len(self._layers))}84 # loop through all layers85 for i, layer in enumerate(self._layers):86 if i != 0:87 # add nearest-neighbor CNOT sequences in the right layer88 for gate in self._extra_layers[i - 1]:89 new_dag.apply_operation_back(*gate)90 # check all gates in the layer91 for gate in layer.op_nodes():92 temp = None93 # do not add gates that have been used in the transformation process94 if gate in self._skip:95 continue96 # every cnot could be the starting point for a CNOT cascade97 elif gate.name == 'cx':98 logger.debug('Check Cascade %s with qargs: %s\n' % (gate.name, gate.qargs))99 # check for a CNOT cascade100 temp = self.check_cascade(gate, i)101 if temp is not None:102 logger.info('Cascade Starts at %s with qargs: %s\n' % (gate.name, gate.qargs))103 self._skip.extend(temp)104 else:105 logger.debug(106 'Check Inverse Cascade at %s with qargs: %s\n' % (gate.name, gate.qargs))107 # check for an inverted CNOT cascade108 temp = self.check_inverse_cascade(gate, i)109 if temp is not None:110 logger.info(111 'Inverse Cascade Starts at %s with qargs: %s\n' % (gate.name, gate.qargs))112 self._skip.extend(temp)113 else:114 # apply the CNOT if no cascade was found115 self._skip.append(gate)116 logger.debug(117 'Found Nothing at %s with qargs: %s\n' % (gate.name, gate.qargs))118 new_dag.apply_operation_back(gate.op, gate.qargs, gate.cargs, gate.condition)119 else:120 self._skip.append(gate)121 new_dag.apply_operation_back(gate.op, gate.qargs, gate.cargs, gate.condition)122 logger.debug('Cascades found: %s' % str(self._extra_layers))123 # optimize dag after transformation124 depth = new_dag.depth()125 while True:126 new_dag = Optimize1qGates().run(new_dag)127 new_dag = CXCancellation().run(new_dag)128 new_depth = new_dag.depth()129 if new_depth < depth:130 depth = new_depth131 else:132 break133 return new_dag134 def check_cascade(self, gate, layer_id):135 """Searches for a CNOT cascade, a sequence of CNOT gates where the target qubit136 is the same for every CNOT while the control changes, and transforms it137 into a nearest-neighbor CNOT sequence ::138 ---x--x--x--x--- --------x--------139 | | | | |140 ---o--|--|--|--- ------x-o-x------141 | | | | |142 ------o--|--|--- ---> ----x-o---o-x----143 | | | |144 ---------o--|--- --x-o-------o-x--145 | | |146 ------------o--- --o-----------o--147 Args:148 gate (DAGNode): first CNOT of a possible CNOT cascade.149 layer_id (int): layer index of the CNOT.150 Returns:151 skip (list): list of gates to be skipped as part of the CNOT cascade,152 may include one-qubit gates that appears before or after the cascade.153 """154 target = self._wires_to_id[gate.qargs[1]]155 control = self._wires_to_id[gate.qargs[0]]156 controls = [control]157 skip = [gate]158 # qubits already added to the CNOT sequence159 used = set()160 used.add(target)161 used.add(control)162 # qubits that cannot be used anymore163 off_limits = set()164 before = {}165 after = []166 # flag to identify the direction of the cascade167 descending = False168 if control > target:169 descending = True170 count = 0171 last_layer = layer_id172 double_break = False173 # loop through layers until a max limit is reached174 while count < min([2 * (self._num_qubits - 1), len(self._layers) - layer_id]):175 for gate in self._layers[layer_id + count].op_nodes():176 logger.debug('Last layer: %d' % last_layer)177 logger.debug('Layer: %d' % (layer_id + count))178 logger.debug('Off limits: %s' % off_limits)179 logger.debug('Gate Name: %s\tType: %s\tQargs: %s\tCargs: %s\tCond: %s' % (180 gate.name, gate.type, gate.qargs, gate.cargs, gate.condition))181 if gate in self._skip:182 for qarg in gate.qargs:183 if self._wires_to_id[qarg] == target:184 double_break = True185 break186 elif gate not in skip:187 if gate.name == 'cx' and gate not in self._skip:188 g_control = self._wires_to_id[gate.qargs[0]]189 g_target = self._wires_to_id[gate.qargs[1]]190 logger.debug('Check CNOT Name: %s\tType: %s\tQargs: %s\tCargs: %s\tCond: %s' % (191 gate.name, gate.type, [g_control, g_target], gate.cargs, gate.condition))192 if g_control == target:193 double_break = True194 break195 if g_control in off_limits or g_target in off_limits:196 off_limits.add(g_control)197 off_limits.add(g_target)198 if g_control not in used:199 used.add(g_control)200 if g_target not in used:201 used.add(g_target)202 logger.debug('CNOT Off limits')203 continue204 logger.debug('Used: %s' % str(used))205 logger.debug('Controls: %s' % str(controls))206 logger.debug('Control-G_control: %d-%d' % (control, g_control))207 logger.debug('Target-G_target: %d-%d' % (target, g_target))208 # chek that the CNOT is part of the cascade209 a = (g_target == target and g_control not in controls and g_control not in used)210 b = (descending is True and g_control > target) or (descending is False and g_control < target)211 logger.debug('A: %s B: %s Descending: %s\n' % (a, b, descending))212 if a and b:213 controls.append(g_control)214 used.add(g_control)215 skip.append(gate)216 # check if the CNOT interrupts the cascade217 elif g_target != target and g_control != target:218 # remember to put the CNOT after the transformation219 if g_target not in used and g_control not in used:220 if last_layer < layer_id + count:221 last_layer = layer_id + count222 # updates used and off limits qubits when necessary223 else:224 off_limits.add(g_control)225 off_limits.add(g_target)226 if last_layer > layer_id + count - 1:227 last_layer = layer_id + count - 1228 if g_control not in used:229 used.add(g_control)230 if g_target not in used:231 used.add(g_target)232 else:233 # break the loop if the CNOT interrupts the cascade234 double_break = True235 break236 else:237 # ignore gates acting on off limits qubits238 double_continue = False239 for qarg in gate.qargs:240 if self._wires_to_id[qarg] in off_limits:241 double_continue = True242 continue243 if double_continue is True:244 continue245 # for special multi-qubits gates, update used and off limits qubits properly,246 # break the loop if necessary247 if gate.name in ["barrier", "snapshot", "save", "load", "noise"]:248 qargs = [self._wires_to_id[qarg] for qarg in gate.qargs]249 if target in qargs:250 if last_layer > layer_id + count - 1:251 last_layer = layer_id + count - 1252 double_break = True253 break254 u = []255 not_u = []256 for qarg in qargs:257 if qarg in used:258 off_limits.add(qarg)259 u.append(qarg)260 else:261 not_u.append(qarg)262 if len(u) == len(qargs):263 # the transformation must be applied before this gate264 if last_layer > layer_id + count - 1:265 last_layer = layer_id + count - 1266 elif len(u) == 0:267 # the transformation must be applied after this gate268 if last_layer < layer_id + count:269 last_layer = layer_id + count270 else:271 # the transformation must be applied before this gate272 if last_layer > layer_id + count - 1:273 last_layer = layer_id + count - 1274 for qarg in not_u + u:275 used.add(qarg)276 off_limits.add(qarg)277 else:278 # check if one-qubits gates either interrupt the cascade, can be applied after or before279 qarg = self._wires_to_id[gate.qargs[0]]280 logger.debug(gate.op.__class__)281 logger.debug('Gate Name: %s\tType: %s\tQarg: %s\tCarg: %s\tCond: %s' % (282 gate.name, gate.type, qarg, gate.cargs, gate.condition))283 if qarg == target:284 logger.debug('After')285 after.append(gate)286 skip.append(gate)287 double_break = True288 break289 if qarg not in used:290 logger.debug('Before')291 if qarg not in before:292 before[qarg] = []293 before[qarg].append(gate)294 skip.append(gate)295 else:296 logger.debug('After')297 after.append(gate)298 skip.append(gate)299 count += 1300 if double_break is True:301 break302 # if a cascade was found303 if len(controls) > 1:304 logger.debug('Found Cascade from layer %d to %d\n' % (layer_id, last_layer))305 if descending is True:306 controls = sorted(controls)307 else:308 controls = sorted(controls, reverse=True)309 # apply all gates that were encountered before the cascade310 for u in before:311 for gate in before[u]:312 self._extra_layers[last_layer].append(313 (gate.op.__class__(*gate.op.params), gate.qargs, gate.cargs, gate.condition))314 # apply the transformation315 for i in range(len(controls) - 1, 0, -1):316 self._extra_layers[last_layer].append((CXGate(),317 [self._id_to_wires[controls[i]],318 self._id_to_wires[controls[i - 1]]], []))319 self._extra_layers[last_layer].append(320 (CXGate(), [self._id_to_wires[controls[0]], self._id_to_wires[target]], []))321 for i in range(len(controls) - 1):322 self._extra_layers[last_layer].append((CXGate(),323 [self._id_to_wires[controls[i + 1]],324 self._id_to_wires[controls[i]]], []))325 # apply all gates that were encountered after the cascade326 for gate in after:327 self._extra_layers[last_layer].append(328 (gate.op.__class__(*gate.op.params), gate.qargs, gate.cargs, gate.condition))329 else:330 skip = None331 return skip332 def check_inverse_cascade(self, gate, layer_id):333 """Searches for an inverted CNOT cascade, a sequence of CNOT gates where the control qubit is the same for every CNOT334 while the target changes, and transforms it into a nearest-neighbor CNOT sequence.335 It is very similar to a CNOT cascade by using H gates to invert every CNOT.336 For every H gate it adds another H gate to maintain the circuit identity::337 ---o--o--o--o--- -H-------x-------H-338 | | | | |339 ---x--|--|--|--- -H-----x-o-x-----H-340 | | | | |341 ------x--|--|--- ---> -H---x-o---o-x---H-342 | | | |343 ---------x--|--- -H-x-o-------o-x-H-344 | | |345 ------------x--- -H-o-----------o-H-346 Args:347 gate (DAGNode): first CNOT of a possible inverted CNOT cascade.348 layer_id (int): layer index of the CNOT.349 Returns:350 skip (list): list of gates to be skipped as part of the inverted CNOT cascade,351 may include one-qubit gates that appears before or after the cascade.352 """353 target = self._wires_to_id[gate.qargs[1]]354 control = self._wires_to_id[gate.qargs[0]]355 targets = [target]356 skip = [gate]357 # qubits already added to the CNOT sequence358 used = set()359 used.add(target)360 used.add(control)361 # qubits that cannot be used anymore362 off_limits = set()363 before = {}364 after = []365 # flag to identify the direction of the cascade366 descending = False367 if target > control:368 descending = True369 count = 0370 last_layer = layer_id371 double_break = False372 # loop through layers until a max limit is reached373 while count < min([2 * (self._num_qubits - 1), len(self._layers) - layer_id]):374 for gate in self._layers[layer_id + count].op_nodes():375 logger.debug('Last layer: %d' % last_layer)376 logger.debug('Layer: %d' % (layer_id + count))377 logger.debug('Off limits: %s' % off_limits)378 logger.debug('Gate Name: %s\tType: %s\tQargs: %s\tCargs: %s\tCond: %s' % (379 gate.name, gate.type, gate.qargs, gate.cargs, gate.condition))380 if gate in self._skip:381 for qarg in gate.qargs:382 if self._wires_to_id[qarg] == control:383 double_break = True384 break385 elif gate not in skip:386 if gate.name == 'cx' and gate not in self._skip:387 g_control = self._wires_to_id[gate.qargs[0]]388 g_target = self._wires_to_id[gate.qargs[1]]389 logger.debug('Check CNOT Name: %s\tType: %s\tQargs: %s\tCargs: %s\tCond: %s' % (390 gate.name, gate.type, [g_control, g_target], gate.cargs, gate.condition))391 if g_target == control:392 double_break = True393 break394 if g_control in off_limits or g_target in off_limits:395 if last_layer > layer_id + count - 1:396 last_layer = layer_id + count - 1397 off_limits.add(g_control)398 off_limits.add(g_target)399 if g_control not in used:400 used.add(g_control)401 if g_target not in used:402 used.add(g_target)403 logger.debug('CNOT off limits')404 continue405 logger.debug('Used: %s' % str(used))406 logger.debug('Targets: %s' % str(targets))407 logger.debug('Control-G_control: %d-%d' % (control, g_control))408 logger.debug('Target-G_target: %d-%d' % (target, g_target))409 # chek that the CNOT is part of the cascade410 a = (g_control == control and g_target not in targets and g_target not in used)411 b = (descending is True and g_target > control) or (descending is False and g_target < control)412 logger.debug('A: %s B: %s Descending: %s\n' % (a, b, descending))413 if a and b:414 targets.append(g_target)415 used.add(g_target)416 skip.append(gate)417 # check if the CNOT interrupts the cascade418 elif g_control != control and g_target != control:419 # remember to put the CNOT after the transformation420 if g_control not in used and g_target not in used:421 if last_layer < layer_id + count:422 last_layer = layer_id + count423 # updates used and off limits qubits when necessary424 else:425 off_limits.add(g_control)426 off_limits.add(g_target)427 if last_layer > layer_id + count - 1:428 last_layer = layer_id + count - 1429 if g_control not in used:430 used.add(g_control)431 if g_target not in used:432 used.add(g_target)433 else:434 # break the loop if the CNOT interrupts the cascade435 double_break = True436 break437 else:438 # ignore gates acting on off limits qubits439 double_continue = False440 for qarg in gate.qargs:441 if self._wires_to_id[qarg] in off_limits:442 double_continue = True443 continue444 if double_continue is True:445 continue446 # for special multi-qubits gates, update used and off limits qubits properly,447 # break the loop if necessary448 if gate.name in ["barrier", "snapshot", "save", "load", "noise"]:449 qargs = [self._wires_to_id[qarg] for qarg in gate.qargs]450 if control in qargs:451 if last_layer > layer_id + count - 1:452 last_layer = layer_id + count - 1453 double_break = True454 break455 u = []456 not_u = []457 for qarg in qargs:458 if qarg in used:459 off_limits.add(qarg)460 u.append(qarg)461 else:462 not_u.append(qarg)463 if len(u) == len(qargs):464 # the transformation must be applied before this gate465 if last_layer > layer_id + count - 1:466 last_layer = layer_id + count - 1467 elif len(u) == 0:468 # the transformation must be applied after this gate469 if last_layer < layer_id + count:470 last_layer = layer_id + count471 else:472 # the transformation must be applied before this gate473 if last_layer > layer_id + count - 1:474 last_layer = layer_id + count - 1475 for qarg in not_u + u:476 used.add(qarg)477 off_limits.add(qarg)478 else:479 # check if one-qubits gates either interrupt the cascade, can be applied after or before480 qarg = self._wires_to_id[gate.qargs[0]]481 logger.debug(gate.op.__class__)482 logger.debug('Gate Name: %s\tType: %s\tQarg: %s\tCarg: %s\tCond: %s' % (483 gate.name, gate.type, qarg, gate.cargs, gate.condition))484 if qarg == control:485 logger.debug('After')486 after.append(gate)487 skip.append(gate)488 double_break = True489 break490 if qarg not in used:491 logger.debug('Before')492 if qarg not in before:493 before[qarg] = []494 before[qarg].append(gate)495 skip.append(gate)496 else:497 logger.debug('After')498 after.append(gate)499 skip.append(gate)500 count += 1501 if double_break is True:502 break503 # if an inverse cascade was found504 if len(targets) > 1:505 logger.debug('Found Inverse Cascade from layer %d to %d\n' % (layer_id, last_layer))506 if descending is True:507 targets = sorted(targets)508 else:509 targets = sorted(targets, reverse=True)510 # apply all gates that were encountered before the cascade511 for u in before:512 for gate in before[u]:513 self._extra_layers[last_layer].append(514 (gate.op.__class__(*gate.op.params), gate.qargs, gate.cargs, gate.condition))515 # apply the transformation516 self._extra_layers[last_layer].append((U2Gate(0, pi), [self._id_to_wires[control]], []))517 for t in targets:518 self._extra_layers[last_layer].append((U2Gate(0, pi), [self._id_to_wires[t]], []))519 for i in range(len(targets) - 1, 0, -1):520 self._extra_layers[last_layer].append((CXGate(),521 [self._id_to_wires[targets[i]],522 self._id_to_wires[targets[i - 1]]], []))523 self._extra_layers[last_layer].append(524 (CXGate(), [self._id_to_wires[targets[0]], self._id_to_wires[control]], []))525 for i in range(len(targets) - 1):526 self._extra_layers[last_layer].append((CXGate(),527 [self._id_to_wires[targets[i + 1]],528 self._id_to_wires[targets[i]]], []))529 self._extra_layers[last_layer].append((U2Gate(0, pi), [self._id_to_wires[control]], []))530 for t in targets:531 self._extra_layers[last_layer].append((U2Gate(0, pi), [self._id_to_wires[t]], []))532 # apply all gates that were encountered after the cascade533 for gate in after:534 self._extra_layers[last_layer].append(535 (gate.op.__class__(*gate.op.params), gate.qargs, gate.cargs, gate.condition))536 else:537 skip = None...
finetune.py
Source:finetune.py
...32 gen_i, gen_j = args.gen_sample.get(args.image_size, (10, 5))33 images = []34 with torch.no_grad():35 for i in range(gen_i):36 images.append(G_running_target(fixed_noise[i].cuda(), step=step, alpha=alpha).cpu())37 sample_path = f'sample/{args.name}/{str(iteration).zfill(6)}.png'38 utils.save_image(torch.cat(images, dim=0), sample_path, nrow=gen_i, normalize=True, range=(-1, 1))39 # compute evaluation metrics40 sample_num = args.sample_num41 fake_images, fake_acts = get_fake_images_and_acts(inception, G_running_target, code_size, step, alpha, sample_num, batch_size)42 fid = compute_fid(real_acts, fake_acts)43 metrics = {'fid': fid}44 return metrics45def l2_reg(net_src, net_tgt):46 params_src = list(net_src.parameters())47 params_tgt = list(net_tgt.parameters())48 loss = 049 for p_src, p_tgt in zip(params_src, params_tgt):50 loss += F.mse_loss(p_tgt, p_src)...
generate.py
Source:generate.py
...31 z = z2*alpha + (1-alpha)*z132 sample_s, _ = g_source([z], randomize_noise=False)33 w = [g_target.module.style(z)]34 w = [Proj_module.modulate(item) for item in w]35 sample_t, _= g_target(w, input_is_latent=True, randomize_noise=False)36 utils.save_image(37 sample_s,38 f'%s/sample%d.png' % (args.save_source, (t*n_steps) + i) ,39 normalize=True,40 range=(-1, 1),41 )42 utils.save_image(43 sample_t,44 f'%s/sample%d.png' % (args.save_target, (t*n_steps) + i),45 normalize=True,46 range=(-1, 1),47 )48def generate_imgs(args, g_source, g_target, Proj_module):49 with torch.no_grad():50 51 if args.load_noise:52 sample_z = torch.load(args.load_noise)53 else:54 sample_z = torch.randn(args.n_sample, args.latent).cuda()55 sample_s, _ = g_source([sample_z], input_is_latent=False, randomize_noise=False)56 w = [g_target.module.style(sample_z)]57 w = [Proj_module.modulate(item) for item in w]58 sample_t, _= g_target(w, input_is_latent=True, randomize_noise=False)59 utils.save_image(60 sample_s,61 f'%s/sample_s.png' % args.save_source,62 nrow=5,63 normalize=True,64 range=(-1, 1),65 )66 utils.save_image(67 sample_t,68 f'%s/sample_t.png' % args.save_target,69 nrow=5,70 normalize=True,71 range=(-1, 1),72 )73def generate_img_pairs(args, g_source, g_target, Proj_module):74 75 with torch.no_grad():76 sample_z = torch.randn(args.SCS_samples, args.latent).cuda()77 for i in range(10):78 print(i)79 w = [g_target.module.style(sample_z[i* int(args.SCS_samples / 10): (i+1)*int(args.SCS_samples / 10)])]80 w = [Proj_module.modulate(item) for item in w]81 sample_t, _= g_target(w, input_is_latent=True, randomize_noise=False)82 sample_s, _ = g_source([sample_z[i* int(args.SCS_samples / 10): (i+1)*int(args.SCS_samples / 10)]], input_is_latent=False, randomize_noise=False)83 84 for (num, (img_s, img_t)) in enumerate(zip(sample_s, sample_t)):85 utils.save_image(86 img_s,87 f'%s/img%d.png' % (args.save_source, (i* int(args.SCS_samples / 10)) + num) ,88 normalize=True,89 range=(-1, 1),90 )91 utils.save_image(92 img_t,93 f'%s/img%d.png' % (args.save_target, (i * int(args.SCS_samples / 10)) + num) ,94 normalize=True,95 range=(-1, 1),96 )97def generate_imgs_4IS(args, g_target, Proj_module):98 99 with torch.no_grad():100 101 sample_z = torch.randn(args.IS_sample, args.latent).cuda()102 step = int(args.IS_sample / 50)103 batch = 50104 for i in range(int(args.IS_sample / 50)):105 print(i)106 w = [g_target.module.style(sample_z[i*batch: (i+1)*batch])]107 w = [Proj_module.modulate(item) for item in w]108 sample_t, _= g_target(w, input_is_latent=True, randomize_noise=False)109 for (num, img) in enumerate(sample_t):110 utils.save_image(111 img,112 f'%s/img%d.png' % (args.save_target, (i * batch) + num) ,113 normalize=True,114 range=(-1, 1),115 )116if __name__ == '__main__':117 device = 'cuda'118 parser = argparse.ArgumentParser()119 parser.add_argument('--size', type=int, default=256)120 parser.add_argument('--SCS_samples', type=int, default=500, help='number of image pairs to eval SCS')121 parser.add_argument('--n_sample', type=int, default=25, help='number of fake images to be sampled')122 parser.add_argument('--IS_sample', type=int, default=10000, help='number of fake images to be sampled for IS')...
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