update

packages/app/RM-Code-Lattices-master/README.md

@@ -1,3 +0,0 @@
-# Reed-Muller Code Lattices
-
-Lattice Code is elegant mathematical structure code.

packages/app/RM-Code-Lattices-master/src/NeuralBeliefPropagation.py

@@ -1,85 +0,0 @@
-import sys
-import os
-
-from learned_BP import *  # noqa
-from itertools import product  # noqa
-
-def multi_loss_CE(x, outputs, discount):
-    return multi_loss(cross_entropy, x, outputs, discount)
-
-def multi_loss_sBER(x, outputs, discount):
-    return multi_loss(soft_BER, x, outputs, discount)
-
-# Give name and directory of a set of trainings
-exp_name = '/Users/ryojishimizu/research/ConstructionD_NBP/bch_lattice/001116'
-exp_dir = os.path.join('.', exp_name)
-
-if not os.path.exists(exp_dir):
-    os.system(f'mkdir {exp_dir}')
-if not os.path.exists(f'{exp_dir}/ckpts'):
-    os.system(f'mkdir {exp_dir}/ckpts')
-if not os.path.exists(f'{exp_dir}/logs'):
-    os.system(f'mkdir {exp_dir}/logs')
-if not os.path.exists(f'{exp_dir}/test_results'):
-    os.system(f'mkdir {exp_dir}/test_results')
-
-CUDA = False
-handler_kwargs = {
-    'checkpoint_dir': f'{exp_dir}/ckpts',           # directory to store training checkpoints
-    'tensorboard_dir': f'{exp_dir}/logs',           # directory to store tensorboard logs
-    'test_result_dir': f'{exp_dir}/test_results',   # directory to store simulation results
-    'report_every': 50,                             # write one tensorboard point every such many mini-batches
-    'use_cuda': CUDA,                               # whether to use CUDA
-    'lr_init': 1e-3,                                # initial learning rate
-    'loss': multi_loss_CE,
-    'weight_decay': 0.0,                            # L2 regularization term
-    'grad_clip': 0.1,                               # gradient clipping
-    'optimizer': 'RMSprop',                         # optimizer
-    #'lr_lambda': 'lambda ep: 0.8 ** (ep // 5)',     # learning rate decay along epoch number
-    # multiloss discount as a function of initial discount factor and epoch number
-    #'discount_lambda': 'lambda d_init, ep: d_init * 0.5 ** (min(ep, 40) // 5)',
-    # additional information to append at the end of the model name
-    #'name_suffix': 'lr_decay_factor=0.8,discount_decay_factor=0.9',
-}
-
-# model arguments of BP with 5 iterations.
-model_kwargs = {
-    'T': 5,
-    'tie': True,
-    'use_cuda': CUDA,
-    'damping_init': 1,
-    'damping_train': False,
-}
-
-# create the linear code, mode determines parity-check matrix
-code = BCH_Code(63, 57, mode='e', use_cuda=CUDA)
-# create the channel
-channel = AWGN_Channel([1, 9])
-# create data loader for generating mini-batches
-loader = DataLoader(code, channel, 120, use_cuda=CUDA)
-
-# # train and simulate a set of Neural BP decoders over a grid
-for args in product(['full'],[0.8],[0.5]): #(['plain','simple','full'], [0.8],[0.5]):# [0.5, 0]):
-    mode, lr_decay, discount_decay = args
-    #mode, lr_decay, discount_decay = 'simple', 0.8, 0.5
-    extra_model = {
-        'mode': mode,
-    }
-    extra = {
-        # learning rate decay along epoch number
-        'lr_lambda': f'lambda ep: {lr_decay} ** (ep // 5)',
-        # multiloss discount as a function of initial discount factor and epoch number
-        'discount_lambda': f'lambda d_init, ep: d_init * {discount_decay} ** (min(ep, 40) // 5)',
-        # additional information to append at the end of the model name
-        'name_suffix': f'lr_decay_factor={lr_decay},discount_decay_factor={discount_decay}'
-    }
-
-    # construct BP decoder
-    model = BP_Decoder(code, **model_kwargs, **extra_model)
-    # create train handler
-    handler = TrainHandler(loader, model, **handler_kwargs, **extra)
-    print(handler.name())
-    # train for 50 epochs, in this case 50k mini-batches
-    handler.train(5)
-    # simulate the decoder after training
-    handler.test(np.arange(1, 9.5, 0.5), min_word_error=1000, min_mb_num=20000)

packages/app/RM-Code-Lattices-master/src/main.py

@@ -1,40 +0,0 @@
-
-
-def encode(_G_mat, info_bits):
-    _N = _G_mat.size()[1]
-    _K = _G_mat.size()[0]
-    codeword = np.zeros(_N)
-    for i in range(_N):
-        for j in range(_K):
-            codeword[i] += info_bits[j] * _G_mat[j][i]
-    return codeword
-
-def generate_lattice(mod_input):
-    symbols = np.zeros(n)
-    for i in range(n):
-        tmp = 0
-        for j in range(num_level + 1):
-            tmp += (1 << j) * mod_input[j][i]
-        symbols[i] = tmp
-    return symbols
-
-def AWGN_channel(x, sigma2):
-    y = np.zeros(n):
-    for i in range(n):
-        y[i] = x[i] + np.sqrt(sigma2) * np.random.normal(0, 1.0)
-    return y
-
-def mod_triangle(value):
-    return np.fabs( np.fmod(value + 1.0, 2.0) - 1.0 )
-
-def subtract(x, dec):
-    y = np.zeros(n)
-    for i in range(n):
-        y[i] = x[i] - dec[i]
-        y[i] /= 2.0
-    return y
-
-def hard_decision(logit):
-    # Make hard decision on LLR = log(p0/p1)
-    if logit < 0: return 1
-    return 0

packages/app/public/static/locales/ja_JP/admin.json

@@ -847,10 +847,6 @@
       "force_update_parents_description": "このオプションを有効化すると、親グループ変更後に祖先グループに足りないユーザーが存在した場合にそれらのユーザーを強制的に追加することができます"
     }
   },
-  "plugins-extention": {
-    "title": "プラグイン拡張",
-    "plugin_url": "プラグイン URL",
-  },
   "audit_log_management": {
     "audit_log": "監査ログ",
     "audit_log_settings": "監査ログ設定",

packages/app/src/components/Admin/AdminHome/InstalledPluginTable.jsx

@@ -27,7 +27,7 @@ const InstalledPluginTable = (props) => {
         </tr>
       </thead>
       <tbody>
-        {/* {adminHomeContainer.state.installedPlugins.map((plugin) => {
+        {adminHomeContainer.state.installedPlugins.map((plugin) => {
           return (
             <tr key={plugin.name}>
               <td>{plugin.name}</td>
@@ -35,7 +35,7 @@ const InstalledPluginTable = (props) => {
               <td data-hide-in-vrt className="text-center">{plugin.installedVersion}</td>
             </tr>
           );
-        })} */}
+        })}
       </tbody>
     </table>
   );

packages/app/src/pages/admin/[[...path]].page.tsx

@@ -109,7 +109,7 @@ const AdminMarkdownSettingsPage: NextPage<Props> = (props: Props) => {
         nodeVersion={props.nodeVersion}
         npmVersion={props.npmVersion}
         yarnVersion={props.yarnVersion}
-        // installedPlugins={props.installedPlugins}
+        installedPlugins={props.installedPlugins}
       />,
     },
     app: {
@@ -290,7 +290,7 @@ async function injectServerConfigurations(context: GetServerSidePropsContext, pr
   props.nodeVersion = crowi.runtimeVersions.versions.node ? crowi.runtimeVersions.versions.node.version.version : null;
   props.npmVersion = crowi.runtimeVersions.versions.npm ? crowi.runtimeVersions.versions.npm.version.version : null;
   props.yarnVersion = crowi.runtimeVersions.versions.yarn ? crowi.runtimeVersions.versions.yarn.version.version : null;
-  // props.installedPlugins= crowi.pluginService.listPlugins(crowi.rootDir);
+  props.installedPlugins = crowi.pluginService.listPlugins(crowi.rootDir);
   props.envVars = await ConfigLoader.getEnvVarsForDisplay(true);
   props.isAclEnabled = aclService.isAclEnabled();