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How to use iter method in wpt

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nasnet.py

Source:nasnet.py

1import torch2import torch.nn as nn3import torch.nn.functional as F4import torch.utils.model_zoo as model_zoo5from torch.autograd import Variable6pretrained_settings = {7    'nasnetalarge': {8        'imagenet': {9            'url': 'http://data.lip6.fr/cadene/pretrainedmodels/nasnetalarge-a1897284.pth',10            'input_space': 'RGB',11            'input_size': [3, 331, 331], # resize 35412            'input_range': [0, 1],13            'mean': [0.5, 0.5, 0.5],14            'std': [0.5, 0.5, 0.5],15            'num_classes': 100016        },17        'imagenet+background': {18            'url': 'http://data.lip6.fr/cadene/pretrainedmodels/nasnetalarge-a1897284.pth',19            'input_space': 'RGB',20            'input_size': [3, 331, 331], # resize 35421            'input_range': [0, 1],22            'mean': [0.5, 0.5, 0.5],23            'std': [0.5, 0.5, 0.5],24            'num_classes': 100125        }26    }27}28class MaxPoolPad(nn.Module):29    def __init__(self):30        super(MaxPoolPad, self).__init__()31        self.pad = nn.ZeroPad2d((1, 0, 1, 0))32        self.pool = nn.MaxPool2d(3, stride=2, padding=1)33    def forward(self, x):34        x = self.pad(x)35        x = self.pool(x)36        x = x[:, :, 1:, 1:]37        return x38class AvgPoolPad(nn.Module):39    def __init__(self, stride=2, padding=1):40        super(AvgPoolPad, self).__init__()41        self.pad = nn.ZeroPad2d((1, 0, 1, 0))42        self.pool = nn.AvgPool2d(3, stride=stride, padding=padding, count_include_pad=False)43    def forward(self, x):44        x = self.pad(x)45        x = self.pool(x)46        x = x[:, :, 1:, 1:]47        return x48class SeparableConv2d(nn.Module):49    def __init__(self, in_channels, out_channels, dw_kernel, dw_stride, dw_padding, bias=False):50        super(SeparableConv2d, self).__init__()51        self.depthwise_conv2d = nn.Conv2d(in_channels, in_channels, dw_kernel,52                                          stride=dw_stride,53                                          padding=dw_padding,54                                          bias=bias,55                                          groups=in_channels)56        self.pointwise_conv2d = nn.Conv2d(in_channels, out_channels, 1, stride=1, bias=bias)57    def forward(self, x):58        x = self.depthwise_conv2d(x)59        x = self.pointwise_conv2d(x)60        return x61class BranchSeparables(nn.Module):62    def __init__(self, in_channels, out_channels, kernel_size, stride, padding, bias=False):63        super(BranchSeparables, self).__init__()64        self.relu = nn.ReLU()65        self.separable_1 = SeparableConv2d(in_channels, in_channels, kernel_size, stride, padding, bias=bias)66        self.bn_sep_1 = nn.BatchNorm2d(in_channels, eps=0.001, momentum=0.1, affine=True)67        self.relu1 = nn.ReLU()68        self.separable_2 = SeparableConv2d(in_channels, out_channels, kernel_size, 1, padding, bias=bias)69        self.bn_sep_2 = nn.BatchNorm2d(out_channels, eps=0.001, momentum=0.1, affine=True)70    def forward(self, x):71        x = self.relu(x)72        x = self.separable_1(x)73        x = self.bn_sep_1(x)74        x = self.relu1(x)75        x = self.separable_2(x)76        x = self.bn_sep_2(x)77        return x78class BranchSeparablesStem(nn.Module):79    def __init__(self, in_channels, out_channels, kernel_size, stride, padding, bias=False):80        super(BranchSeparablesStem, self).__init__()81        self.relu = nn.ReLU()82        self.separable_1 = SeparableConv2d(in_channels, out_channels, kernel_size, stride, padding, bias=bias)83        self.bn_sep_1 = nn.BatchNorm2d(out_channels, eps=0.001, momentum=0.1, affine=True)84        self.relu1 = nn.ReLU()85        self.separable_2 = SeparableConv2d(out_channels, out_channels, kernel_size, 1, padding, bias=bias)86        self.bn_sep_2 = nn.BatchNorm2d(out_channels, eps=0.001, momentum=0.1, affine=True)87    def forward(self, x):88        x = self.relu(x)89        x = self.separable_1(x)90        x = self.bn_sep_1(x)91        x = self.relu1(x)92        x = self.separable_2(x)93        x = self.bn_sep_2(x)94        return x95class BranchSeparablesReduction(BranchSeparables):96    def __init__(self, in_channels, out_channels, kernel_size, stride, padding, z_padding=1, bias=False):97        BranchSeparables.__init__(self, in_channels, out_channels, kernel_size, stride, padding, bias)98        self.padding = nn.ZeroPad2d((z_padding, 0, z_padding, 0))99    def forward(self, x):100        x = self.relu(x)101        x = self.padding(x)102        x = self.separable_1(x)103        x = x[:, :, 1:, 1:].contiguous()104        x = self.bn_sep_1(x)105        x = self.relu1(x)106        x = self.separable_2(x)107        x = self.bn_sep_2(x)108        return x109class CellStem0(nn.Module):110    def __init__(self):111        super(CellStem0, self).__init__()112        self.conv_1x1 = nn.Sequential()113        self.conv_1x1.add_module('relu', nn.ReLU())114        self.conv_1x1.add_module('conv', nn.Conv2d(96, 42, 1, stride=1, bias=False))115        self.conv_1x1.add_module('bn', nn.BatchNorm2d(42, eps=0.001, momentum=0.1, affine=True))116        self.comb_iter_0_left = BranchSeparables(42, 42, 5, 2, 2)117        self.comb_iter_0_right = BranchSeparablesStem(96, 42, 7, 2, 3, bias=False)118        self.comb_iter_1_left = nn.MaxPool2d(3, stride=2, padding=1)119        self.comb_iter_1_right = BranchSeparablesStem(96, 42, 7, 2, 3, bias=False)120        self.comb_iter_2_left = nn.AvgPool2d(3, stride=2, padding=1, count_include_pad=False)121        self.comb_iter_2_right = BranchSeparablesStem(96, 42, 5, 2, 2, bias=False)122        self.comb_iter_3_right = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)123        self.comb_iter_4_left = BranchSeparables(42, 42, 3, 1, 1, bias=False)124        self.comb_iter_4_right = nn.MaxPool2d(3, stride=2, padding=1)125    def forward(self, x):126        x1 = self.conv_1x1(x)127        x_comb_iter_0_left = self.comb_iter_0_left(x1)128        x_comb_iter_0_right = self.comb_iter_0_right(x)129        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right130        x_comb_iter_1_left = self.comb_iter_1_left(x1)131        x_comb_iter_1_right = self.comb_iter_1_right(x)132        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right133        x_comb_iter_2_left = self.comb_iter_2_left(x1)134        x_comb_iter_2_right = self.comb_iter_2_right(x)135        x_comb_iter_2 = x_comb_iter_2_left + x_comb_iter_2_right136        x_comb_iter_3_right = self.comb_iter_3_right(x_comb_iter_0)137        x_comb_iter_3 = x_comb_iter_3_right + x_comb_iter_1138        x_comb_iter_4_left = self.comb_iter_4_left(x_comb_iter_0)139        x_comb_iter_4_right = self.comb_iter_4_right(x1)140        x_comb_iter_4 = x_comb_iter_4_left + x_comb_iter_4_right141        x_out = torch.cat([x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)142        return x_out143class CellStem1(nn.Module):144    def __init__(self):145        super(CellStem1, self).__init__()146        self.conv_1x1 = nn.Sequential()147        self.conv_1x1.add_module('relu', nn.ReLU())148        self.conv_1x1.add_module('conv', nn.Conv2d(168, 84, 1, stride=1, bias=False))149        self.conv_1x1.add_module('bn', nn.BatchNorm2d(84, eps=0.001, momentum=0.1, affine=True))150        self.relu = nn.ReLU()151        self.path_1 = nn.Sequential()152        self.path_1.add_module('avgpool', nn.AvgPool2d(1, stride=2, count_include_pad=False))153        self.path_1.add_module('conv', nn.Conv2d(96, 42, 1, stride=1, bias=False))154        self.path_2 = nn.ModuleList()155        self.path_2.add_module('pad', nn.ZeroPad2d((0, 1, 0, 1)))156        self.path_2.add_module('avgpool', nn.AvgPool2d(1, stride=2, count_include_pad=False))157        self.path_2.add_module('conv', nn.Conv2d(96, 42, 1, stride=1, bias=False))158        self.final_path_bn = nn.BatchNorm2d(84, eps=0.001, momentum=0.1, affine=True)159        self.comb_iter_0_left = BranchSeparables(84, 84, 5, 2, 2, bias=False)160        self.comb_iter_0_right = BranchSeparables(84, 84, 7, 2, 3, bias=False)161        self.comb_iter_1_left = nn.MaxPool2d(3, stride=2, padding=1)162        self.comb_iter_1_right = BranchSeparables(84, 84, 7, 2, 3, bias=False)163        self.comb_iter_2_left = nn.AvgPool2d(3, stride=2, padding=1, count_include_pad=False)164        self.comb_iter_2_right = BranchSeparables(84, 84, 5, 2, 2, bias=False)165        self.comb_iter_3_right = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)166        self.comb_iter_4_left = BranchSeparables(84, 84, 3, 1, 1, bias=False)167        self.comb_iter_4_right = nn.MaxPool2d(3, stride=2, padding=1)168    def forward(self, x_conv0, x_stem_0):169        x_left = self.conv_1x1(x_stem_0)170        x_relu = self.relu(x_conv0)171        # path 1172        x_path1 = self.path_1(x_relu)173        # path 2174        x_path2 = self.path_2.pad(x_relu)175        x_path2 = x_path2[:, :, 1:, 1:]176        x_path2 = self.path_2.avgpool(x_path2)177        x_path2 = self.path_2.conv(x_path2)178        # final path179        x_right = self.final_path_bn(torch.cat([x_path1, x_path2], 1))180        x_comb_iter_0_left = self.comb_iter_0_left(x_left)181        x_comb_iter_0_right = self.comb_iter_0_right(x_right)182        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right183        x_comb_iter_1_left = self.comb_iter_1_left(x_left)184        x_comb_iter_1_right = self.comb_iter_1_right(x_right)185        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right186        x_comb_iter_2_left = self.comb_iter_2_left(x_left)187        x_comb_iter_2_right = self.comb_iter_2_right(x_right)188        x_comb_iter_2 = x_comb_iter_2_left + x_comb_iter_2_right189        x_comb_iter_3_right = self.comb_iter_3_right(x_comb_iter_0)190        x_comb_iter_3 = x_comb_iter_3_right + x_comb_iter_1191        x_comb_iter_4_left = self.comb_iter_4_left(x_comb_iter_0)192        x_comb_iter_4_right = self.comb_iter_4_right(x_left)193        x_comb_iter_4 = x_comb_iter_4_left + x_comb_iter_4_right194        x_out = torch.cat([x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)195        return x_out196class FirstCell(nn.Module):197    def __init__(self, in_channels_left, out_channels_left, in_channels_right, out_channels_right):198        super(FirstCell, self).__init__()199        self.conv_1x1 = nn.Sequential()200        self.conv_1x1.add_module('relu', nn.ReLU())201        self.conv_1x1.add_module('conv', nn.Conv2d(in_channels_right, out_channels_right, 1, stride=1, bias=False))202        self.conv_1x1.add_module('bn', nn.BatchNorm2d(out_channels_right, eps=0.001, momentum=0.1, affine=True))203        self.relu = nn.ReLU()204        self.path_1 = nn.Sequential()205        self.path_1.add_module('avgpool', nn.AvgPool2d(1, stride=2, count_include_pad=False))206        self.path_1.add_module('conv', nn.Conv2d(in_channels_left, out_channels_left, 1, stride=1, bias=False))207        self.path_2 = nn.ModuleList()208        self.path_2.add_module('pad', nn.ZeroPad2d((0, 1, 0, 1)))209        self.path_2.add_module('avgpool', nn.AvgPool2d(1, stride=2, count_include_pad=False))210        self.path_2.add_module('conv', nn.Conv2d(in_channels_left, out_channels_left, 1, stride=1, bias=False))211        self.final_path_bn = nn.BatchNorm2d(out_channels_left * 2, eps=0.001, momentum=0.1, affine=True)212        self.comb_iter_0_left = BranchSeparables(out_channels_right, out_channels_right, 5, 1, 2, bias=False)213        self.comb_iter_0_right = BranchSeparables(out_channels_right, out_channels_right, 3, 1, 1, bias=False)214        self.comb_iter_1_left = BranchSeparables(out_channels_right, out_channels_right, 5, 1, 2, bias=False)215        self.comb_iter_1_right = BranchSeparables(out_channels_right, out_channels_right, 3, 1, 1, bias=False)216        self.comb_iter_2_left = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)217        self.comb_iter_3_left = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)218        self.comb_iter_3_right = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)219        self.comb_iter_4_left = BranchSeparables(out_channels_right, out_channels_right, 3, 1, 1, bias=False)220    def forward(self, x, x_prev):221        x_relu = self.relu(x_prev)222        # path 1223        x_path1 = self.path_1(x_relu)224        # path 2225        x_path2 = self.path_2.pad(x_relu)226        x_path2 = x_path2[:, :, 1:, 1:]227        x_path2 = self.path_2.avgpool(x_path2)228        x_path2 = self.path_2.conv(x_path2)229        # final path230        x_left = self.final_path_bn(torch.cat([x_path1, x_path2], 1))231        x_right = self.conv_1x1(x)232        x_comb_iter_0_left = self.comb_iter_0_left(x_right)233        x_comb_iter_0_right = self.comb_iter_0_right(x_left)234        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right235        x_comb_iter_1_left = self.comb_iter_1_left(x_left)236        x_comb_iter_1_right = self.comb_iter_1_right(x_left)237        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right238        x_comb_iter_2_left = self.comb_iter_2_left(x_right)239        x_comb_iter_2 = x_comb_iter_2_left + x_left240        x_comb_iter_3_left = self.comb_iter_3_left(x_left)241        x_comb_iter_3_right = self.comb_iter_3_right(x_left)242        x_comb_iter_3 = x_comb_iter_3_left + x_comb_iter_3_right243        x_comb_iter_4_left = self.comb_iter_4_left(x_right)244        x_comb_iter_4 = x_comb_iter_4_left + x_right245        x_out = torch.cat([x_left, x_comb_iter_0, x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)246        return x_out247class NormalCell(nn.Module):248    def __init__(self, in_channels_left, out_channels_left, in_channels_right, out_channels_right):249        super(NormalCell, self).__init__()250        self.conv_prev_1x1 = nn.Sequential()251        self.conv_prev_1x1.add_module('relu', nn.ReLU())252        self.conv_prev_1x1.add_module('conv', nn.Conv2d(in_channels_left, out_channels_left, 1, stride=1, bias=False))253        self.conv_prev_1x1.add_module('bn', nn.BatchNorm2d(out_channels_left, eps=0.001, momentum=0.1, affine=True))254        self.conv_1x1 = nn.Sequential()255        self.conv_1x1.add_module('relu', nn.ReLU())256        self.conv_1x1.add_module('conv', nn.Conv2d(in_channels_right, out_channels_right, 1, stride=1, bias=False))257        self.conv_1x1.add_module('bn', nn.BatchNorm2d(out_channels_right, eps=0.001, momentum=0.1, affine=True))258        self.comb_iter_0_left = BranchSeparables(out_channels_right, out_channels_right, 5, 1, 2, bias=False)259        self.comb_iter_0_right = BranchSeparables(out_channels_left, out_channels_left, 3, 1, 1, bias=False)260        self.comb_iter_1_left = BranchSeparables(out_channels_left, out_channels_left, 5, 1, 2, bias=False)261        self.comb_iter_1_right = BranchSeparables(out_channels_left, out_channels_left, 3, 1, 1, bias=False)262        self.comb_iter_2_left = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)263        self.comb_iter_3_left = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)264        self.comb_iter_3_right = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)265        self.comb_iter_4_left = BranchSeparables(out_channels_right, out_channels_right, 3, 1, 1, bias=False)266    def forward(self, x, x_prev):267        x_left = self.conv_prev_1x1(x_prev)268        x_right = self.conv_1x1(x)269        x_comb_iter_0_left = self.comb_iter_0_left(x_right)270        x_comb_iter_0_right = self.comb_iter_0_right(x_left)271        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right272        x_comb_iter_1_left = self.comb_iter_1_left(x_left)273        x_comb_iter_1_right = self.comb_iter_1_right(x_left)274        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right275        x_comb_iter_2_left = self.comb_iter_2_left(x_right)276        x_comb_iter_2 = x_comb_iter_2_left + x_left277        x_comb_iter_3_left = self.comb_iter_3_left(x_left)278        x_comb_iter_3_right = self.comb_iter_3_right(x_left)279        x_comb_iter_3 = x_comb_iter_3_left + x_comb_iter_3_right280        x_comb_iter_4_left = self.comb_iter_4_left(x_right)281        x_comb_iter_4 = x_comb_iter_4_left + x_right282        x_out = torch.cat([x_left, x_comb_iter_0, x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)283        return x_out284class ReductionCell0(nn.Module):285    def __init__(self, in_channels_left, out_channels_left, in_channels_right, out_channels_right):286        super(ReductionCell0, self).__init__() 287        self.conv_prev_1x1 = nn.Sequential()288        self.conv_prev_1x1.add_module('relu', nn.ReLU())289        self.conv_prev_1x1.add_module('conv', nn.Conv2d(in_channels_left, out_channels_left, 1, stride=1, bias=False))290        self.conv_prev_1x1.add_module('bn', nn.BatchNorm2d(out_channels_left, eps=0.001, momentum=0.1, affine=True))291        self.conv_1x1 = nn.Sequential()292        self.conv_1x1.add_module('relu', nn.ReLU())293        self.conv_1x1.add_module('conv', nn.Conv2d(in_channels_right, out_channels_right, 1, stride=1, bias=False))294        self.conv_1x1.add_module('bn', nn.BatchNorm2d(out_channels_right, eps=0.001, momentum=0.1, affine=True))295        self.comb_iter_0_left = BranchSeparablesReduction(out_channels_right, out_channels_right, 5, 2, 2, bias=False)296        self.comb_iter_0_right = BranchSeparablesReduction(out_channels_right, out_channels_right, 7, 2, 3, bias=False)297        self.comb_iter_1_left = MaxPoolPad()298        self.comb_iter_1_right = BranchSeparablesReduction(out_channels_right, out_channels_right, 7, 2, 3, bias=False)299        self.comb_iter_2_left = AvgPoolPad()300        self.comb_iter_2_right = BranchSeparablesReduction(out_channels_right, out_channels_right, 5, 2, 2, bias=False)301        self.comb_iter_3_right = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)302        self.comb_iter_4_left = BranchSeparablesReduction(out_channels_right, out_channels_right, 3, 1, 1, bias=False)303        self.comb_iter_4_right = MaxPoolPad()304    def forward(self, x, x_prev):305        x_left = self.conv_prev_1x1(x_prev)306        x_right = self.conv_1x1(x)307        x_comb_iter_0_left = self.comb_iter_0_left(x_right)308        x_comb_iter_0_right = self.comb_iter_0_right(x_left)309        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right310        x_comb_iter_1_left = self.comb_iter_1_left(x_right)311        x_comb_iter_1_right = self.comb_iter_1_right(x_left)312        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right313        x_comb_iter_2_left = self.comb_iter_2_left(x_right)314        x_comb_iter_2_right = self.comb_iter_2_right(x_left)315        x_comb_iter_2 = x_comb_iter_2_left + x_comb_iter_2_right316        x_comb_iter_3_right = self.comb_iter_3_right(x_comb_iter_0)317        x_comb_iter_3 = x_comb_iter_3_right + x_comb_iter_1318        x_comb_iter_4_left = self.comb_iter_4_left(x_comb_iter_0)319        x_comb_iter_4_right = self.comb_iter_4_right(x_right)320        x_comb_iter_4 = x_comb_iter_4_left + x_comb_iter_4_right321        x_out = torch.cat([x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)322        return x_out323class ReductionCell1(nn.Module):324    def __init__(self, in_channels_left, out_channels_left, in_channels_right, out_channels_right):325        super(ReductionCell1, self).__init__()326        self.conv_prev_1x1 = nn.Sequential()327        self.conv_prev_1x1.add_module('relu', nn.ReLU())328        self.conv_prev_1x1.add_module('conv', nn.Conv2d(in_channels_left, out_channels_left, 1, stride=1, bias=False))329        self.conv_prev_1x1.add_module('bn', nn.BatchNorm2d(out_channels_left, eps=0.001, momentum=0.1, affine=True))330        self.conv_1x1 = nn.Sequential()331        self.conv_1x1.add_module('relu', nn.ReLU())332        self.conv_1x1.add_module('conv', nn.Conv2d(in_channels_right, out_channels_right, 1, stride=1, bias=False))333        self.conv_1x1.add_module('bn', nn.BatchNorm2d(out_channels_right, eps=0.001, momentum=0.1, affine=True))334        self.comb_iter_0_left = BranchSeparables(out_channels_right, out_channels_right, 5, 2, 2, bias=False)335        self.comb_iter_0_right = BranchSeparables(out_channels_right, out_channels_right, 7, 2, 3, bias=False)336        self.comb_iter_1_left = nn.MaxPool2d(3, stride=2, padding=1)337        self.comb_iter_1_right = BranchSeparables(out_channels_right, out_channels_right, 7, 2, 3, bias=False)338        self.comb_iter_2_left = nn.AvgPool2d(3, stride=2, padding=1, count_include_pad=False)339        self.comb_iter_2_right = BranchSeparables(out_channels_right, out_channels_right, 5, 2, 2, bias=False)340        self.comb_iter_3_right = nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False)341        self.comb_iter_4_left = BranchSeparables(out_channels_right, out_channels_right, 3, 1, 1, bias=False)342        self.comb_iter_4_right = nn.MaxPool2d(3, stride=2, padding=1)343    def forward(self, x, x_prev):344        x_left = self.conv_prev_1x1(x_prev)345        x_right = self.conv_1x1(x)346        x_comb_iter_0_left = self.comb_iter_0_left(x_right)347        x_comb_iter_0_right = self.comb_iter_0_right(x_left)348        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right349        x_comb_iter_1_left = self.comb_iter_1_left(x_right)350        x_comb_iter_1_right = self.comb_iter_1_right(x_left)351        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right352        x_comb_iter_2_left = self.comb_iter_2_left(x_right)353        x_comb_iter_2_right = self.comb_iter_2_right(x_left)354        x_comb_iter_2 = x_comb_iter_2_left + x_comb_iter_2_right355        x_comb_iter_3_right = self.comb_iter_3_right(x_comb_iter_0)356        x_comb_iter_3 = x_comb_iter_3_right + x_comb_iter_1357        x_comb_iter_4_left = self.comb_iter_4_left(x_comb_iter_0)358        x_comb_iter_4_right = self.comb_iter_4_right(x_right)359        x_comb_iter_4 = x_comb_iter_4_left + x_comb_iter_4_right360        x_out = torch.cat([x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)361        return x_out362class NASNetALarge(nn.Module):363    def __init__(self, use_classifier=False, num_classes=1001):364        super(NASNetALarge, self).__init__()365        self.use_classifier,self.num_classes = use_classifier,num_classes366        self.conv0 = nn.Sequential()367        self.conv0.add_module('conv', nn.Conv2d(in_channels=3, out_channels=96, kernel_size=3, padding=0, stride=2,368                                                bias=False))369        self.conv0.add_module('bn', nn.BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True))370        self.cell_stem_0 = CellStem0()371        self.cell_stem_1 = CellStem1()372        self.cell_0 = FirstCell(in_channels_left=168, out_channels_left=84,373                                in_channels_right=336, out_channels_right=168)374        self.cell_1 = NormalCell(in_channels_left=336, out_channels_left=168,375                                 in_channels_right=1008, out_channels_right=168)376        self.cell_2 = NormalCell(in_channels_left=1008, out_channels_left=168,377                                 in_channels_right=1008, out_channels_right=168)378        self.cell_3 = NormalCell(in_channels_left=1008, out_channels_left=168,379                                 in_channels_right=1008, out_channels_right=168)380        self.cell_4 = NormalCell(in_channels_left=1008, out_channels_left=168,381                                 in_channels_right=1008, out_channels_right=168)382        self.cell_5 = NormalCell(in_channels_left=1008, out_channels_left=168,383                                 in_channels_right=1008, out_channels_right=168)384        self.reduction_cell_0 = ReductionCell0(in_channels_left=1008, out_channels_left=336,385                                               in_channels_right=1008, out_channels_right=336)386        self.cell_6 = FirstCell(in_channels_left=1008, out_channels_left=168,387                                in_channels_right=1344, out_channels_right=336)388        self.cell_7 = NormalCell(in_channels_left=1344, out_channels_left=336,389                                 in_channels_right=2016, out_channels_right=336)390        self.cell_8 = NormalCell(in_channels_left=2016, out_channels_left=336,391                                 in_channels_right=2016, out_channels_right=336)392        self.cell_9 = NormalCell(in_channels_left=2016, out_channels_left=336,393                                 in_channels_right=2016, out_channels_right=336)394        self.cell_10 = NormalCell(in_channels_left=2016, out_channels_left=336,395                                  in_channels_right=2016, out_channels_right=336)396        self.cell_11 = NormalCell(in_channels_left=2016, out_channels_left=336,397                                  in_channels_right=2016, out_channels_right=336)398        self.reduction_cell_1 = ReductionCell1(in_channels_left=2016, out_channels_left=672,399                                               in_channels_right=2016, out_channels_right=672)400        self.cell_12 = FirstCell(in_channels_left=2016, out_channels_left=336,401                                 in_channels_right=2688, out_channels_right=672)402        self.cell_13 = NormalCell(in_channels_left=2688, out_channels_left=672,403                                  in_channels_right=4032, out_channels_right=672)404        self.cell_14 = NormalCell(in_channels_left=4032, out_channels_left=672,405                                  in_channels_right=4032, out_channels_right=672)406        self.cell_15 = NormalCell(in_channels_left=4032, out_channels_left=672,407                                  in_channels_right=4032, out_channels_right=672)408        self.cell_16 = NormalCell(in_channels_left=4032, out_channels_left=672,409                                  in_channels_right=4032, out_channels_right=672)410        self.cell_17 = NormalCell(in_channels_left=4032, out_channels_left=672,411                                  in_channels_right=4032, out_channels_right=672)412        self.relu = nn.ReLU()413        self.dropout = nn.Dropout()414        self.last_linear = nn.Linear(4032, self.num_classes)415    def features(self, x):416        x_conv0 = self.conv0(x)417        x_stem_0 = self.cell_stem_0(x_conv0)418        x_stem_1 = self.cell_stem_1(x_conv0, x_stem_0)419        x_cell_0 = self.cell_0(x_stem_1, x_stem_0)420        x_cell_1 = self.cell_1(x_cell_0, x_stem_1)421        x_cell_2 = self.cell_2(x_cell_1, x_cell_0)422        x_cell_3 = self.cell_3(x_cell_2, x_cell_1)423        x_cell_4 = self.cell_4(x_cell_3, x_cell_2)424        x_cell_5 = self.cell_5(x_cell_4, x_cell_3)425        x_reduction_cell_0 = self.reduction_cell_0(x_cell_5, x_cell_4)426        x_cell_6 = self.cell_6(x_reduction_cell_0, x_cell_4)427        x_cell_7 = self.cell_7(x_cell_6, x_reduction_cell_0)428        x_cell_8 = self.cell_8(x_cell_7, x_cell_6)429        x_cell_9 = self.cell_9(x_cell_8, x_cell_7)430        x_cell_10 = self.cell_10(x_cell_9, x_cell_8)431        x_cell_11 = self.cell_11(x_cell_10, x_cell_9)432        x_reduction_cell_1 = self.reduction_cell_1(x_cell_11, x_cell_10)433        x_cell_12 = self.cell_12(x_reduction_cell_1, x_cell_10)434        x_cell_13 = self.cell_13(x_cell_12, x_reduction_cell_1)435        x_cell_14 = self.cell_14(x_cell_13, x_cell_12)436        x_cell_15 = self.cell_15(x_cell_14, x_cell_13)437        x_cell_16 = self.cell_16(x_cell_15, x_cell_14)438        x_cell_17 = self.cell_17(x_cell_16, x_cell_15)439        return self.relu(x_cell_17)440    def classifier(self, x):441        x = F.adaptive_max_pool2d(x, 1)442        x = x.view(x.size(0), -1)443        x = self.dropout(x)444        return F.log_softmax(self.linear(x))445    def forward(self, x):446        x = self.features(x)447        if self.use_classifier: x = self.classifier(x)448        return x449def nasnetalarge(num_classes=1000, pretrained='imagenet'):450    r"""NASNetALarge model architecture from the451    `"NASNet" <https://arxiv.org/abs/1707.07012>`_ paper.452    """453    if pretrained:454        settings = pretrained_settings['nasnetalarge'][pretrained]455        assert num_classes == settings['num_classes'], \456            "num_classes should be {}, but is {}".format(settings['num_classes'], num_classes)457        # both 'imagenet'&'imagenet+background' are loaded from same parameters458        model = NASNetALarge(num_classes=1001)459        model.load_state_dict(model_zoo.load_url(settings['url']))460        if pretrained == 'imagenet':461            new_last_linear = nn.Linear(model.last_linear.in_features, 1000)462            new_last_linear.weight.data = model.last_linear.weight.data[1:]463            new_last_linear.bias.data = model.last_linear.bias.data[1:]464            model.last_linear = new_last_linear465        model.input_space = settings['input_space']466        model.input_size = settings['input_size']467        model.input_range = settings['input_range']468        model.mean = settings['mean']469        model.std = settings['std']470    else:471        model = NASNetALarge(num_classes=num_classes)...

cppclass_container.py

Source:cppclass_container.py

1"""2Add container iteration powers to wrapped C++ classes3"""4from typehandlers.base import ForwardWrapperBase5from typehandlers import codesink6from pytypeobject import PyTypeObject7import utils8class IterNextWrapper(ForwardWrapperBase):9    '''10    tp_iternext wrapper11    '''12    HAVE_RETURN_VALUE = True13    def __init__(self, container):14        """15        value_type -- a ReturnValue object handling the value type;16        container -- the L{Container}17        """18        super(IterNextWrapper, self).__init__(19            None, [], "return NULL;", "return NULL;", no_c_retval=True)20        assert isinstance(container, CppClassContainerTraits)21        self.container = container22        self.c_function_name = "_wrap_%s__tp_iternext" % (self.container.iter_pystruct)23        self.iter_variable_name = None24        self.reset_code_generation_state()25    def reset_code_generation_state(self):26        super(IterNextWrapper, self).reset_code_generation_state()27        self.iter_variable_name = self.declarations.declare_variable(28            "%s::%s" % (self.container.cppclass.full_name, self.container.iterator_type), 'iter')29    def generate_call(self):30        self.before_call.write_code("%s = *self->iterator;" % (self.iter_variable_name,))31        self.before_call.write_error_check(32            "%s == self->container->obj->%s()" % (self.iter_variable_name, self.container.end_method),33            "PyErr_SetNone(PyExc_StopIteration);")34        self.before_call.write_code("++(*self->iterator);")35        if self.container.key_type is None:36            self.container.value_type.value = "(*%s)" % self.iter_variable_name37            self.container.value_type.convert_c_to_python(self)38        else:39            self.container.value_type.value = "%s->second" % self.iter_variable_name40            self.container.value_type.convert_c_to_python(self)41            self.container.key_type.value = "%s->first" % self.iter_variable_name42            self.container.key_type.convert_c_to_python(self)43    def generate(self, code_sink):44        """45        code_sink -- a CodeSink instance that will receive the generated code46        """47        48        tmp_sink = codesink.MemoryCodeSink()49        self.generate_body(tmp_sink)50        code_sink.writeln("static PyObject* %s(%s *self)" % (self.c_function_name,51                                                             self.container.iter_pystruct))52        code_sink.writeln('{')53        code_sink.indent()54        tmp_sink.flush_to(code_sink)55        code_sink.unindent()56        code_sink.writeln('}')57class CppClassContainerTraits(object):58    def __init__(self, cppclass, value_type, begin_method='begin', end_method='end', iterator_type='iterator', is_mapping=False):59        """60        :param cppclass: the L{CppClass} object that receives the container traits61        :param value_type: a ReturnValue of the element type: note,62        for mapping containers, value_type is a tuple with two63        ReturnValue's: (key, element).64        """65        self.cppclass = cppclass66        self.begin_method = begin_method67        self.end_method = end_method68        self.iterator_type = iterator_type69        self.iter_pytype = PyTypeObject()70        self._iter_pystruct = None71        if is_mapping:72            (key_type, value_type) = value_type73            self.key_type = utils.eval_retval(key_type, self)74            self.value_type = utils.eval_retval(value_type, self)75        else:76            self.key_type = None77            self.value_type = utils.eval_retval(value_type, self)78    def get_iter_pystruct(self):79        return "%s_Iter" % self.cppclass.pystruct80    iter_pystruct = property(get_iter_pystruct)81    def get_iter_pytypestruct(self):82        return "%s_IterType" % self.cppclass.pystruct83    iter_pytypestruct = property(get_iter_pytypestruct)84    def generate_forward_declarations(self, code_sink, dummy_module):85        """86        Generates forward declarations for the instance and type87        structures.88        """89        # container iterator pystruct90        code_sink.writeln('''91typedef struct {92    PyObject_HEAD93    %s *container;94    %s::%s *iterator;95} %s;96    ''' % (self.cppclass.pystruct, self.cppclass.full_name, self.iterator_type, self.iter_pystruct))97        code_sink.writeln()98        code_sink.writeln('extern PyTypeObject %s;' % (self.iter_pytypestruct,))99        code_sink.writeln()100    def get_iter_python_name(self):101        return "%sIter" % self.cppclass.get_python_name()102    def get_iter_python_full_name(self, module):103        if self.cppclass.outer_class is None:104            mod_path = module.get_module_path()105            mod_path.append(self.get_iter_python_name())106            return '.'.join(mod_path)107        else:108            return '%s.%s' % (self.cppclass.outer_class.pytype.slots['tp_name'],109                              self.get_iter_python_name())110    def generate(self, code_sink, module, docstring=None):111        """Generates the class to a code sink"""112        ## --- register the iter type in the module ---113        module.after_init.write_code("/* Register the '%s' class iterator*/" % self.cppclass.full_name)114        module.after_init.write_error_check('PyType_Ready(&%s)' % (self.iter_pytypestruct,))115        if self.cppclass.outer_class is None:116            module.after_init.write_code(117                'PyModule_AddObject(m, (char *) \"%s\", (PyObject *) &%s);' % (118                self.get_iter_python_name(), self.iter_pytypestruct))119        else:120            module.after_init.write_code(121                'PyDict_SetItemString((PyObject*) %s.tp_dict, (char *) \"%s\", (PyObject *) &%s);' % (122                self.cppclass.outer_class.pytypestruct, self.cppclass.get_iter_python_name(), self.iter_pytypestruct))123        self._generate_gc_methods(code_sink)124        self._generate_destructor(code_sink)125        self._generate_iter_methods(code_sink)126        self._generate_type_structure(code_sink, module, docstring)127        128    def _generate_type_structure(self, code_sink, module, docstring):129        """generate the type structure"""130        self.iter_pytype.slots.setdefault("tp_basicsize", "sizeof(%s)" % (self.iter_pystruct,))131        self.iter_pytype.slots.setdefault("tp_flags", ("Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_GC"))132        self.iter_pytype.slots.setdefault("typestruct", self.iter_pytypestruct)133        self.iter_pytype.slots.setdefault("tp_name", self.get_iter_python_full_name(module))134        if docstring:135            self.iter_pytype.slots.setdefault("tp_doc", '"%s"' % docstring)136        self.iter_pytype.generate(code_sink)137    def _get_iter_delete_code(self):138        delete_code = ("delete self->iterator;\n"139                       "    self->iterator = NULL;\n")140        return delete_code141    def _get_container_delete_code(self):142        delete_code = ("delete self->obj;\n"143                       "    self->obj = NULL;\n")144        return delete_code145    def _generate_gc_methods(self, code_sink):146        """Generate tp_clear and tp_traverse"""147        ## --- iterator tp_clear ---148        tp_clear_function_name = "%s__tp_clear" % (self.iter_pystruct,)149        self.iter_pytype.slots.setdefault("tp_clear", tp_clear_function_name )150        code_sink.writeln(r'''151static void152%s(%s *self)153{154    Py_CLEAR(self->container);155    %s156}157''' % (tp_clear_function_name, self.iter_pystruct, self._get_iter_delete_code()))158        ## --- iterator tp_traverse ---159        tp_traverse_function_name = "%s__tp_traverse" % (self.iter_pystruct,)160        self.iter_pytype.slots.setdefault("tp_traverse", tp_traverse_function_name )161        code_sink.writeln(r'''162static int163%s(%s *self, visitproc visit, void *arg)164{165    Py_VISIT((PyObject *) self->container);166    return 0;167}168''' % (tp_traverse_function_name, self.iter_pystruct))169    def _generate_destructor(self, code_sink):170        """Generate a tp_dealloc function and register it in the type"""171        # -- iterator --172        iter_tp_dealloc_function_name = "_wrap_%s__tp_dealloc" % (self.iter_pystruct,)173        code_sink.writeln(r'''174static void175%s(%s *self)176{177    Py_CLEAR(self->container);178    %s179    self->ob_type->tp_free((PyObject*)self);180}181''' % (iter_tp_dealloc_function_name, self.iter_pystruct, self._get_iter_delete_code()))182        self.iter_pytype.slots.setdefault("tp_dealloc", iter_tp_dealloc_function_name )183    def _generate_iter_methods(self, code_sink):184        container_tp_iter_function_name = "_wrap_%s__tp_iter" % (self.cppclass.pystruct,)185        iterator_tp_iter_function_name = "_wrap_%s__tp_iter" % (self.iter_pystruct,)186        subst_vars = {187            'CONTAINER_ITER_FUNC': container_tp_iter_function_name,188            'ITERATOR_ITER_FUNC': iterator_tp_iter_function_name,189            'PYSTRUCT': self.cppclass.pystruct,190            'ITER_PYSTRUCT': self.iter_pystruct,191            'ITER_PYTYPESTRUCT': self.iter_pytypestruct,192            'CTYPE': self.cppclass.full_name,193            'BEGIN_METHOD': self.begin_method,194            'ITERATOR_TYPE': self.iterator_type,195            }196        # -- container --197        code_sink.writeln(r'''198static PyObject*199%(CONTAINER_ITER_FUNC)s(%(PYSTRUCT)s *self)200{201    %(ITER_PYSTRUCT)s *iter = PyObject_GC_New(%(ITER_PYSTRUCT)s, &%(ITER_PYTYPESTRUCT)s);202    Py_INCREF(self);203    iter->container = self;204    iter->iterator = new %(CTYPE)s::%(ITERATOR_TYPE)s(self->obj->%(BEGIN_METHOD)s());205    return (PyObject*) iter;206}207''' % subst_vars)208        self.cppclass.pytype.slots.setdefault("tp_iter", container_tp_iter_function_name)209        210        # -- iterator --211        container_tp_iter_function_name = "_wrap_%s__tp_iter" % (self.cppclass.pystruct,)212        code_sink.writeln(r'''213static PyObject*214%(ITERATOR_ITER_FUNC)s(%(ITER_PYSTRUCT)s *self)215{216    Py_INCREF(self);217    return (PyObject*) self;218}219''' % subst_vars)220        self.iter_pytype.slots.setdefault("tp_iter", iterator_tp_iter_function_name)221        # -- iterator tp_iternext222        iternext = IterNextWrapper(self)223        iternext.generate(code_sink)224        self.iter_pytype.slots.setdefault("tp_iternext", iternext.c_function_name)...

test_parser_pddl_simple.py

Source:test_parser_pddl_simple.py

1#!/usr/bin/python32from pddl.parser import *3from pddl.lisp_parser import parse_lisp_iterator4from pddl.errors import BraceError, ParseError5from py.test import raises6## helper functions7def varListTest(varList):8    assert  [k.name for k in varList] == ['?x', '?y', '?z']9    assert  len([k for k in varList if k.typed]) == 310    assert  [k.types[0] for k in varList] == ['block', 'foo', 'block']11def keywordListTest(keyList):12    assert  [k.name for k in keyList] == ['name', 'parameters', 'foo']13## the tests14def test_parseKeywordSimple():15    test = ['(:parameters )']16    iter = parse_lisp_iterator(test)17    key = parse_keyword(next(iter))18    assert key.name == 'parameters'19def test_parseKeywordComplex():20    test = [' ( :name)']21    iter = parse_lisp_iterator(test)22    key = parse_keyword(next(iter))23    assert key.name == 'name'24def test_parseKeywordList():25    test = ['(:name :parameters :foo )']26    iter = parse_lisp_iterator(test)27    keys = parse_keyword_list(iter)28    assert iter.empty()29    keywordListTest(keys)30def test_parseRequirements():31    test = ['(:requirements :name :parameters :foo )']32    iter = parse_lisp_iterator(test)33    req = parse_requirements_stmt(iter)34    assert iter.empty()35    keywordListTest(req.keywords)36def test_parseRequirements2():37    test = ['(:predicates :name :parameters :foo )']38    iter = parse_lisp_iterator(test)39    with raises(ValueError):40        parse_requirements_stmt(iter)41def test_parseVariableNoTyping():42    test = [' ( ?x)']43    iter = parse_lisp_iterator(test)44    key = parse_variable(next(iter))45    assert key.name == '?x'46    assert key.typed == False47    assert key.types == None48def test_parseVariableTyping():49    test = [' ( ?x - block)']50    iter = parse_lisp_iterator(test)51    vlist = parse_typed_var_list(iter)52    assert len(vlist) == 153    assert vlist[0].name == '?x'54    assert vlist[0].typed == True55    assert vlist[0].types[0] == 'block'56def test_parseVariableList():57    test = [' ( ?x - block ?y - foo ?z - block  )']58    iter = parse_lisp_iterator(test)59    key = parse_typed_var_list(iter)60    varListTest(key)61def test_parseParameters():62    test = ['(:parameters ( ?x - block ?y - foo ?z - block  ))']63    iter = parse_lisp_iterator(test)64    key = parse_parameters(iter)65    varListTest(key)66def test_parseParameters2():67    test = ['(:predicates ( ?x - block ?y - foo ?z - block  ))']68    iter = parse_lisp_iterator(test)69    with raises(ValueError):70        parse_parameters(iter)71def test_parseTypes():72    test = ['(:types block plane key)']73    iter = parse_lisp_iterator(test)74    tlist = parse_types_stmt(iter)75    assert [t.name for t in tlist] == ['block', 'plane', 'key']76def test_parseTypesFail():77    test = ['(:types :block plane key)']78    iter = parse_lisp_iterator(test)79    with raises(ValueError):80        parse_types_stmt(iter)81def test_parseTypesFail2():82    test = ['(:predicates :block plane key)']83    iter = parse_lisp_iterator(test)84    with raises(ValueError):85        parse_types_stmt(iter)86def test_parseDomainStatement():87    test = ['(domain supertest-23-v0)']88    iter = parse_lisp_iterator(test)89    dom = parse_domain_stmt(iter)90    assert dom.name == 'supertest-23-v0'91def test_parseDomainStatementFail():92    test = ['(domaiin supertest-23-v0)']93    iter = parse_lisp_iterator(test)94    with raises(ValueError):95        parse_domain_stmt(iter)96def test_parsePredicate():97    test = ['(on ?x ?y)']98    iter = parse_lisp_iterator(test)99    pred = parse_predicate(iter)100    assert pred.name == 'on'101    assert [x.name for x in pred.parameters] == ['?x', '?y']102def test_parsePredicateMixed():103    test = ['(on ?x - block ?y)']104    iter = parse_lisp_iterator(test)105    pred = parse_predicate(iter)106    assert pred.name == 'on'107    assert [x.name for x in pred.parameters] == ['?x', '?y']108    assert [x.types[0] for x in pred.parameters109            if x.types != None] == ['block']110def test_parsePredicateList():111    test = ['((on ?x - block ?y) (put ?x ?z) (true))']112    iter = parse_lisp_iterator(test)113    predlist = parse_predicate_list(iter)114    assert [x.name for x in predlist] == ['on', 'put', 'true']115def test_parseFormula():116    test = ['(and (on ?x table) (true) (free ?x))']117    iter = parse_lisp_iterator(test)118    print(iter)119    formula = parse_formula(iter)120    assert formula.key == 'and'121    assert [c.key for c in formula.children] == ['on', 'true', 'free']122    assert [c.key.name for c in formula.children[0].children123            if c.type == TypeVariable] == ['?x']124    assert [c.key for c in formula.children[0].children125            if c.type == TypeConstant] == ['table']126    assert [c.key.name for c in formula.children[2].children127            if c.type == TypeVariable] == ['?x']128    assert [c for c in formula.children[1].children] == []129def test_parseFormulaFail():130    test = ['(and (on ?x table) (:true) (free ?x))']131    iter = parse_lisp_iterator(test)132    with raises(ValueError):133        parse_formula(iter)134def test_parseFormulaLispFail2():135    test = ['(and (on ?x table) (true) (free( ?x))']136    with raises(ParseError):137        iter = parse_lisp_iterator(test)138def test_parse_variable():139    test = ['(x)']140    iter = parse_lisp_iterator(test)141    with raises(ValueError):142        parse_variable(next(iter))143def test_lisp_parser_start_brace():144    test = ['test string)']145    with raises(ParseError):146        iter = parse_lisp_iterator(test)147def test_parse_keyword_raise():148    test = ['(?test)']149    iter = parse_lisp_iterator(test)150    with raises(ValueError):151        parse_keyword(next(iter))152def test_parse_objects_stmt_fail():153    test = ['(:predicates blubb blubb)']154    iter = parse_lisp_iterator(test)155    with raises(ValueError):156        parse_objects_stmt(iter)157def test_parse_constants_stmt_fail():158    test = ['(:predicates blubb blubb)']159    iter = parse_lisp_iterator(test)160    with raises(ValueError):161        parse_constants_stmt(iter)162def test_parse_problem_domain_stmt_fail():163    test = ['(:predicates blubb blubb)']164    iter = parse_lisp_iterator(test)165    with raises(ValueError):166        parse_problem_domain_stmt(iter)167def test_parse_precondition_stmt_fail():168    test = ['(:predicates blubb blubb)']169    iter = parse_lisp_iterator(test)170    with raises(ValueError):171        parse_precondition_stmt(iter)172def test_parse_effect_stmt_fail():173    test = ['(:predicates blubb blubb)']174    iter = parse_lisp_iterator(test)175    with raises(ValueError):176        parse_effect_stmt(iter)177def test_parse_action_stmt_fail():178    test = ['(:predicates blubb blubb)']179    iter = parse_lisp_iterator(test)180    with raises(ValueError):181        parse_action_stmt(iter)182def test_parse_predicates_stmt_fail():183    test = ['(:actions blubb blubb)']184    iter = parse_lisp_iterator(test)185    with raises(ValueError):186        parse_predicates_stmt(iter)187def test_parse_domain_def_fail():188    test = ['(definiere (domain BLOCKS))']189    iter = parse_lisp_iterator(test)190    with raises(ValueError):191        parse_domain_def(iter)192def test_parse_problem_def_fail():193    test = ['(definiere problem)']194    iter = parse_lisp_iterator(test)195    with raises(ValueError):196        parse_problem_def(iter)197def test_parse_problem_name_fail():198    test = ['(domain test)']199    iter = parse_lisp_iterator(test)200    with raises(ValueError):201        parse_problem_name(iter)202def test_parse_init_stmt_fail():203    test = ['(:goal ssdfsdf)']204    iter = parse_lisp_iterator(test)205    with raises(ValueError):206        parse_init_stmt(iter)207def test_parse_goal_stmt_fail():208    test = ['(:init ssdfsdf)']209    iter = parse_lisp_iterator(test)210    with raises(ValueError):...

xml-fold.js

Source:xml-fold.js

1(function(mod) {2  if (typeof exports == "object" && typeof module == "object") // CommonJS3    mod(require("../../lib/codemirror"));4  else if (typeof define == "function" && define.amd) // AMD5    define(["../../lib/codemirror"], mod);6  else // Plain browser env7    mod(CodeMirror);8})(function(CodeMirror) {9  "use strict";10  var Pos = CodeMirror.Pos;11  function cmp(a, b) { return a.line - b.line || a.ch - b.ch; }12  var nameStartChar = "A-Z_a-z\\u00C0-\\u00D6\\u00D8-\\u00F6\\u00F8-\\u02FF\\u0370-\\u037D\\u037F-\\u1FFF\\u200C-\\u200D\\u2070-\\u218F\\u2C00-\\u2FEF\\u3001-\\uD7FF\\uF900-\\uFDCF\\uFDF0-\\uFFFD";13  var nameChar = nameStartChar + "\-\:\.0-9\\u00B7\\u0300-\\u036F\\u203F-\\u2040";14  var xmlTagStart = new RegExp("<(/?)([" + nameStartChar + "][" + nameChar + "]*)", "g");15  function Iter(cm, line, ch, range) {16    this.line = line; this.ch = ch;17    this.cm = cm; this.text = cm.getLine(line);18    this.min = range ? range.from : cm.firstLine();19    this.max = range ? range.to - 1 : cm.lastLine();20  }21  function tagAt(iter, ch) {22    var type = iter.cm.getTokenTypeAt(Pos(iter.line, ch));23    return type && /\btag\b/.test(type);24  }25  function nextLine(iter) {26    if (iter.line >= iter.max) return;27    iter.ch = 0;28    iter.text = iter.cm.getLine(++iter.line);29    return true;30  }31  function prevLine(iter) {32    if (iter.line <= iter.min) return;33    iter.text = iter.cm.getLine(--iter.line);34    iter.ch = iter.text.length;35    return true;36  }37  function toTagEnd(iter) {38    for (;;) {39      var gt = iter.text.indexOf(">", iter.ch);40      if (gt == -1) { if (nextLine(iter)) continue; else return; }41      if (!tagAt(iter, gt + 1)) { iter.ch = gt + 1; continue; }42      var lastSlash = iter.text.lastIndexOf("/", gt);43      var selfClose = lastSlash > -1 && !/\S/.test(iter.text.slice(lastSlash + 1, gt));44      iter.ch = gt + 1;45      return selfClose ? "selfClose" : "regular";46    }47  }48  function toTagStart(iter) {49    for (;;) {50      var lt = iter.ch ? iter.text.lastIndexOf("<", iter.ch - 1) : -1;51      if (lt == -1) { if (prevLine(iter)) continue; else return; }52      if (!tagAt(iter, lt + 1)) { iter.ch = lt; continue; }53      xmlTagStart.lastIndex = lt;54      iter.ch = lt;55      var match = xmlTagStart.exec(iter.text);56      if (match && match.index == lt) return match;57    }58  }59  function toNextTag(iter) {60    for (;;) {61      xmlTagStart.lastIndex = iter.ch;62      var found = xmlTagStart.exec(iter.text);63      if (!found) { if (nextLine(iter)) continue; else return; }64      if (!tagAt(iter, found.index + 1)) { iter.ch = found.index + 1; continue; }65      iter.ch = found.index + found[0].length;66      return found;67    }68  }69  function toPrevTag(iter) {70    for (;;) {71      var gt = iter.ch ? iter.text.lastIndexOf(">", iter.ch - 1) : -1;72      if (gt == -1) { if (prevLine(iter)) continue; else return; }73      if (!tagAt(iter, gt + 1)) { iter.ch = gt; continue; }74      var lastSlash = iter.text.lastIndexOf("/", gt);75      var selfClose = lastSlash > -1 && !/\S/.test(iter.text.slice(lastSlash + 1, gt));76      iter.ch = gt + 1;77      return selfClose ? "selfClose" : "regular";78    }79  }80  function findMatchingClose(iter, tag) {81    var stack = [];82    for (;;) {83      var next = toNextTag(iter), end, startLine = iter.line, startCh = iter.ch - (next ? next[0].length : 0);84      if (!next || !(end = toTagEnd(iter))) return;85      if (end == "selfClose") continue;86      if (next[1]) { // closing tag87        for (var i = stack.length - 1; i >= 0; --i) if (stack[i] == next[2]) {88          stack.length = i;89          break;90        }91        if (i < 0 && (!tag || tag == next[2])) return {92          tag: next[2],93          from: Pos(startLine, startCh),94          to: Pos(iter.line, iter.ch)95        };96      } else { // opening tag97        stack.push(next[2]);98      }99    }100  }101  function findMatchingOpen(iter, tag) {102    var stack = [];103    for (;;) {104      var prev = toPrevTag(iter);105      if (!prev) return;106      if (prev == "selfClose") { toTagStart(iter); continue; }107      var endLine = iter.line, endCh = iter.ch;108      var start = toTagStart(iter);109      if (!start) return;110      if (start[1]) { // closing tag111        stack.push(start[2]);112      } else { // opening tag113        for (var i = stack.length - 1; i >= 0; --i) if (stack[i] == start[2]) {114          stack.length = i;115          break;116        }117        if (i < 0 && (!tag || tag == start[2])) return {118          tag: start[2],119          from: Pos(iter.line, iter.ch),120          to: Pos(endLine, endCh)121        };122      }123    }124  }125  CodeMirror.registerHelper("fold", "xml", function(cm, start) {126    var iter = new Iter(cm, start.line, 0);127    for (;;) {128      var openTag = toNextTag(iter), end;129      if (!openTag || iter.line != start.line || !(end = toTagEnd(iter))) return;130      if (!openTag[1] && end != "selfClose") {131        var start = Pos(iter.line, iter.ch);132        var close = findMatchingClose(iter, openTag[2]);133        return close && {from: start, to: close.from};134      }135    }136  });137  CodeMirror.findMatchingTag = function(cm, pos, range) {138    var iter = new Iter(cm, pos.line, pos.ch, range);139    if (iter.text.indexOf(">") == -1 && iter.text.indexOf("<") == -1) return;140    var end = toTagEnd(iter), to = end && Pos(iter.line, iter.ch);141    var start = end && toTagStart(iter);142    if (!end || end == "selfClose" || !start || cmp(iter, pos) > 0) return;143    var here = {from: Pos(iter.line, iter.ch), to: to, tag: start[2]};144    if (start[1]) { // closing tag145      return {open: findMatchingOpen(iter, start[2]), close: here, at: "close"};146    } else { // opening tag147      iter = new Iter(cm, to.line, to.ch, range);148      return {open: here, close: findMatchingClose(iter, start[2]), at: "open"};149    }150  };151  CodeMirror.findEnclosingTag = function(cm, pos, range) {152    var iter = new Iter(cm, pos.line, pos.ch, range);153    for (;;) {154      var open = findMatchingOpen(iter);155      if (!open) break;156      var forward = new Iter(cm, pos.line, pos.ch, range);157      var close = findMatchingClose(forward, open.tag);158      if (close) return {open: open, close: close};159    }160  };161  // Used by addon/edit/closetag.js162  CodeMirror.scanForClosingTag = function(cm, pos, name, end) {163    var iter = new Iter(cm, pos.line, pos.ch, end ? {from: 0, to: end} : null);164    return !!findMatchingClose(iter, name);165  };...

Using AI Code Generation

1var wpt = require('webpagetest');2var wpt = new WebPageTest('www.webpagetest.org');3  if (err) return console.error(err);4  console.log('Test submitted. Polling for results...');5  wpt.getTestResults(data.data.testId, function(err, data) {6    if (err) return console.error(err);7    console.log('Test completed!');8    console.log(data);9  });10});11var wpt = require('webpagetest');12var wpt = new WebPageTest('www.webpagetest.org');13var options = {14};15  if (err) return console.error(err);16  console.log('Test submitted. Polling for results...');17  wpt.getTestResults(data.data.testId, function(err, data) {18    if (err) return console.error(err);19    console.log('Test completed!');20    console.log(data);21  });22});23var wpt = require('webpagetest');24var wpt = new WebPageTest('www.webpagetest.org');25  if (err) return console.error(err);26  console.log('Test submitted. Polling for results...');27  wpt.getTestResults(data.data.testId, function(err, data) {28    if (err) return console.error(err);29    console.log('Test completed!');30    console.log(data);31  });32});33var wpt = require('webpagetest');34var wpt = new WebPageTest('www.webpagetest.org');35var options = {36};37  if (err) return console.error(err);38  console.log('Test submitted. Polling for results...');

Using AI Code Generation

1const wpt = require('webpagetest');2  if (err) {3    console.log(err);4  } else {5    console.log(data);6  }7});8const wpt = require('webpagetest');9### WPT.runTest(url, options, callback)10### WPT.getTestResults(testId, callback)11### WPT.getLocations(callback)12### WPT.getTesters(callback)13### WPT.getVersion(callback)

Using AI Code Generation

1const wptools = require('wptools');2const fs = require('fs');3const path = require('path');4const json2csv = require('json2csv').parse;5const csv = require('csvtojson');6const csvWriter = require('csv-write-stream');7const writer = csvWriter({sendHeaders: false});8const fields = ['Title', 'Description'];9const opts = { fields };10const csvFilePath = path.join(__dirname, 'output.csv');11const jsonFilePath = path.join(__dirname, 'output.json');12const getWiki = async (name) => {13    const page = wptools.page(name);14    const data = await page.get();15    return data;16}17const getWikiInfo = async (name) => {18    const page = wptools.page(name);19    const data = await page.get();20    return data;21}22const getWikiInfoIter = async (name) => {23    const page = wptools.page(name);24    const data = await page.get();25    return data;26}27const getWikiInfoIter2 = async (name) => {28    const page = wptools.page(name);29    const data = await page.get();30    return data;31}32const getWikiInfoIter3 = async (name) => {33    const page = wptools.page(name);34    const data = await page.get();35    return data;36}37const getWikiInfoIter4 = async (name) => {38    const page = wptools.page(name);39    const data = await page.get();40    return data;41}42const getWikiInfoIter5 = async (name) => {43    const page = wptools.page(name);44    const data = await page.get();45    return data;46}47const getWikiInfoIter6 = async (name) => {48    const page = wptools.page(name);49    const data = await page.get();50    return data;51}52const getWikiInfoIter7 = async (name) => {53    const page = wptools.page(name);54    const data = await page.get();55    return data;56}57const getWikiInfoIter8 = async (name) => {58    const page = wptools.page(name);59    const data = await page.get();60    return data;61}62const getWikiInfoIter9 = async (name) => {63    const page = wptools.page(name);64    const data = await page.get();

Using AI Code Generation

1const wptools = require('wptools');2const fs = require('fs');3const async = require('async');4const path = require('path');5const csv = require('fast-csv');6const _ = require('lodash');7const csvWriter = require('csv-write-stream');8const writer = csvWriter();9    .fromPath('./data/2018-05-01.csv')10    .on('data', function (data) {11        console.log(data);12    })13    .on('end', function () {14        console.log('done');15    });

Using AI Code Generation

1var wptools = require('wptools');2var fs = require('fs');3var options = {4};5var iter = wptools.page('Albert Einstein', options).iter('links');6var link;7while (link = iter()) {8    console.log(link);9}10var wptools = require('wptools');11var fs = require('fs');12var options = {13};14var iter = wptools.page('Albert Einstein', options).iter('links');15var link;16while (link = iter()) {17    console.log(link);18}19var wptools = require('wptools');20var fs = require('fs');21var options = {22};23var iter = wptools.page('Albert Einstein', options).iter('links');24var link;25while (link = iter()) {26    console.log(link);27}28var wptools = require('wptools');29var fs = require('fs');30var options = {31};32var iter = wptools.page('Albert Einstein', options).iter('links');33var link;34while (link = iter()) {35    console.log(link);36}37var wptools = require('wptools');38var fs = require('fs');39var options = {40};41var iter = wptools.page('Albert Einstein', options).iter('links');42var link;43while (link = iter()) {44    console.log(link);45}46var wptools = require('wptools');47var fs = require('fs');48var options = {

Using AI Code Generation

1var wptools = require('wptools');2var fs = require('fs');3var path = require('path');4var file = path.join(__dirname, 'test.txt');5var file2 = path.join(__dirname, 'test2.txt');6var readStream = fs.createReadStream(file);7var writeStream = fs.createWriteStream(file2);8wptools.iter(readStream, writeStream, function(err, result){9  if (err) throw err;10  console.log(result);11});

Using AI Code Generation

1var wptools = require('wptools');2var page = wptools.page('Barack Obama');3page.iter('infobox', function(err, data) {4    console.log(data);5});6var wptools = require('wptools');7var page = wptools.page('Barack Obama');8page.iter('links', function(err, data) {9    console.log(data);10});11var wptools = require('wptools');12var page = wptools.page('Barack Obama');13page.iter('categories', function(err, data) {14    console.log(data);15});16var wptools = require('wptools');17var page = wptools.page('Barack Obama');18page.iter('coordinates', function(err, data) {19    console.log(data);20});21var wptools = require('wptools');22var page = wptools.page('Barack Obama');23page.iter('images', function(err, data) {24    console.log(data);25});26var wptools = require('wptools');27var page = wptools.page('Barack Obama');28page.iter('langlinks', function(err, data) {29    console.log(data);30});31var wptools = require('wptools');32var page = wptools.page('Barack Obama');33page.iter('pageprops', function(err, data) {34    console.log(data);35});36var wptools = require('wptools');37var page = wptools.page('Barack Obama');38page.iter('revisions', function(err, data) {39    console.log(data);40});41var wptools = require('wptools');42var page = wptools.page('Barack Obama');43page.iter('templates', function

Using AI Code Generation

1const wptools = require('wptools');2const fs = require('fs');3const _ = require('lodash');4wptools.page('Barack Obama').then(page => {5  page.iter('links').then(links => {6    fs.writeFileSync('links.json', JSON.stringify(links, null, 2));7  });8});9### wptools.page()10const wptools = require('wptools');11wptools.page('Barack Obama').then(page => {12  page.data().then(data => {13    console.log(data);14  });15});16### page.data()17const wptools = require('wptools');18wptools.page('Barack Obama').then(page => {19  page.data().then(data => {20    console.log(data);21  });22});23### page.iter()24const wptools = require('wptools');25wptools.page('Barack Obama').then(page => {26  page.iter('links').then(links => {27    console.log(links);28  });29});30### page.get()31const wptools = require('wptools');32wptools.page('Barack Obama').then(page => {33  page.get('infobox').then(infobox => {34    console.log(infobox);35  });36});37### page.getImages()38const wptools = require('wptools');39wptools.page('Barack Obama').then(page => {40  page.getImages().then(images => {41    console.log(images);42  });43});44### page.getLinks()45const wptools = require('wptools');46wptools.page('Barack Obama').then(page => {47  page.getLinks().then(links => {48    console.log(links);49  });50});51### page.getReferences()52const wptools = require('wptools');53wptools.page('Barack Obama').then(page => {54  page.getReferences().then(references => {55    console.log(references);56  });57});58### page.getSections()59const wptools = require('wptools');60wptools.page('Barack Obama').then(page => {61  page.getSections().then(sections => {62    console.log(sections);63  });64});65### page.getSummary()

Using AI Code Generation

1var wpt = require('webpagetest')('www.webpagetest.org', 'A.5f6e7c1d1f1d8d2c9c9b7f86c4e6f4b6');2var fs = require('fs');3var request = require('request');4var wptJson = {};5var wptJson1 = {};6var wptJson2 = {};7var wptJson3 = {};8var wptJson4 = {};9var wptJson5 = {};

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.