// Do not modify this file by hand!
    // Re-generate this file by running lit-localize

    
    

    /* eslint-disable no-irregular-whitespace */
    /* eslint-disable @typescript-eslint/no-explicit-any */

    export const templates = {
      's9d167ef77aed79b6': `Layer`,
'se157debe22915185': `was deleted because no data could be assigned to it!`,
's8192fafe6f0cc0bb': `An input layer is a layer that just takes data provided from outside the network and passes it on to the next layer(s)`,
's0e36885f01f95cc8': `A dense layer, also called fully-connected layer, is a layer whose inside neurons connect to every neuron in the preceding layer.`,
's3310986378624a28': `The selected layer can not be duplicated! Only a single output layer is currently supported!`,
'sdc95be9d922008e7': `An output layer in this simulation is just a normal dense layer, additionally equipped with the ability to output the incoming data out of the network.`,
'sa5982fd2e05ee92d': `Since the purpose if this layer is to output a classifiction, we should combine it with a softmax activation function in order to provide a probability distribution.`,
's835dc746e771a9d6': `Boston House Pricing`,
's4c5805b438fae5b7': `The Boston House Price data set involves the prediction of a house price in thousands of dollars given details of the house and its neighborhood.`,
's92dd08d474f4ba4b': `Per capita crime rate by town`,
'sa2cb02c992247501': `Proportion of residential land zoned for lots over 25,000 sq.ft.`,
's0ba84c8c8dd5dfe5': `Proportion of nonretail business acres per town`,
'sb85fa3ee37f69a87': `Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)`,
's902fe1322b1d2c62': `Nitric oxides concentration (parts per 10 million)`,
'sf928898f4043c6ff': `Average number of rooms per dwelling`,
's95f88e83db13ec5c': `Proportion of owner-occupied units built prior to 1940`,
'sb0be465979ef3758': `Weighted distances to five Boston employment centers`,
'sb60c67627b3119cc': `Index of accessibility to radial highways`,
'sc3ba6f6e119cd273': `Full-value property-tax rate per \$10,000`,
's49d8fc3f40b093ac': `Pupil-teacher ratio by town`,
's577b270038a8c007': `1000(Bk – 0.63)^2 where Bk is the proportion of blacks by town`,
's2f41bf569b07a4cc': `% lower status of the population`,
's473a26666565450c': `Median value of owner-occupied homes in \$1000s`,
'sb96294312677cad5': `Pima Indians Diabetes`,
'sc20c7530f6afbb7c': `The Pima Indians Diabetes data set involves predicting the onset of diabetes within 5 years in Pima Indians given medical details. It is a binary (2-class) classification problem. The number of observations for each class is not balanced. There are 768 observations with 8 input variables and 1 output variable. Missing values are believed to be encoded with zero values.`,
's4e77426bf7986294': `Number of times pregnant`,
's5923001bb6219bb3': `Plasma glucose concentration a 2 hours in an oral glucose tolerance test.`,
'sf7cdf4e3adc1b2fa': `Diastolic blood pressure (mm Hg)`,
's5659cbd3943227de': `Triceps skinfold thickness (mm)`,
'sa17f891acb35efd2': `2-Hour serum insulin (mu U/ml)`,
's4a39fd2eb0e136da': `Body mass index (weight in kg/(height in m)^2)`,
's66ebf0bd757d5159': `Diabetes pedigree function`,
's5ef9308d320834d1': `Age (years)`,
's4e64552852c163c0': `Diabetes`,
's93d85c9969bc1e8e': `Get started`,
's37f8f9ad6c3ca6e8': `Import JSON configuration`,
'sb39c29728a3aab64': `Intermediate`,
's4aba9979380614e1': `Classification`,
's7e7ce210415ee02c': `Feed Forward`,
's382a2aa3984474dd': `Create`,
's85f01e331f787810': `Regression`,
's13bf923e48a38e88': `You can create a custom configuration by using the options in the corresponding right panels.`,
'sf27f87a94b05a690': `Toggle Menu`,
's236ae937cbcd6a39': `Zoom in`,
's5b1749c67945a111': `Zoom to network`,
'sc65ea2cf2f21a13a': `Zoom out`,
'sd03c537f123f42a6': `Exit Fullscreen`,
's4b10acae683d2978': `Fullscreen`,
's9d8b8aa2b404c2c8': `Settings`,
's769b92432aa0e57f': `Configure which options the users of this widget are allowed to view and edit`,
's255857544a9d5ec0': `Reset`,
's295e7ec3fae5aa15': `Set to default`,
's7f76d461768c268c': `Allow importing configurations`,
'sa219044786efe4f4': `Show recommendations`,
'sa133a50ad676b757': `Allow exporting configurations`,
's9feb1a1345ccc3e5': `Network`,
's3de2e4f3353ff071': `Restrict layer types`,
'scfa788c4d56c9859': `Allow dense layers`,
's05c44a5db696fcaf': `Editing`,
'secd2b30927c9ada1': `Allow adding and removing layers`,
's1d6d96fee1f77a74': `Allow editing layers`,
'sc728fae3603c8b93': `Allow selecting the data flowing into input layers`,
's91346ada0f5220bf': `Allow editing the number of neurons`,
'sff69314112eb4786': `Allow changing the activation function`,
'sb4aaa150117048eb': `Allow reconnecting the layers with each other`,
's4488dd99533e7f65': `Data set`,
's505d96c3ca2f3c78': `Allow selecting a different data set`,
'sa3900af79012fda0': `Allow managing (creating new and deleting) data sets`,
's0605944041e20ba8': `Show plots`,
'se65e4e6f3696e997': `Training`,
's7188f983604e2188': `Allow editing hyperparameters`,
's77d657d2989d8bf6': `Allow editing the batch size`,
's14a65ec1c3dc6761': `Allow editing the learning rate`,
's399ed88a7aa67028': `Allow editing the dropout rate`,
's991dbe8a07858b6b': `Important info`,
's4c3e975942fc568d': `You decided to train a model with the current configuration. As an effect, all options to edit the configuration have been temporarily removed or disabled to make sure the configuration you see is the same configuration the model uses. If you want to make changes to your configuration, you need to discard the current model first. If you discard your model, you can again perform any changes and train a new model based on the new configuration.`,
'sb4810a60b4ad921e': `Discards the model, which gains you back your editing capabilities`,
'sc00a88b90cd60661': `Discard`,
's2ed914b45e6f8fb0': `Discard model`,
's293aa6a6446fb153': `Export`,
'sc7aaabd93fb4c486': `Export the current configuration to your local file system as a JSON file. Storing trained models is not supported.`,
'se3b4c857f91f80d7': `Keyboard shortcuts`,
'sc25745d3142338ca': `Deletes the currently selected layer`,
'sa5ed0165e089255e': `Duplicates the currently selected layer`,
's8ff8cee7c5d100bc': `Moves the currently selected layer`,
'sa7f495fff0f250d9': `Q & A`,
's14b03351d9f0f4e8': `There are currently no help entries. If you publish the widget like this, the help section will be hidden.`,
'se1f4d0fd4b9438d0': `Update entry`,
's3983b0213bfac281': `Remove entry`,
's99f110d27e30b289': `Title`,
's6cee92a3b310e650': `Add entry`,
'sc20cf39aef9b3355': `About this app`,
's984fb2f8f14ee101': `This app was developed by Christian Koch, a student at RWTH Aachen University, with support of Frederic Salmen and the chair i9 at RWTH Aachen University.`,
'sc62667aa0380bc6b': `About the developer`,
's17597a8bb4810524': `License`,
's8e7cfd29f14ffad6': `All third-party data sets have been published under public domain`,
'sb546e48af5e5c359': `Add layer`,
'saea857a2b4e1f6a7': `Drag a layer anywhere to place it on the canvas`,
'sfd77270c3f54f664': `Output`,
'sb4f1dffbb6be6302': `Clear`,
'se6e9902ddea314c4': `Clear network`,
's14ad6d4ee3b48ca2': `This will remove every layer from the network.`,
'sae901180c48ddefb': `Your network currently contains`,
's4554e34a747022df': `layers`,
's4d1b055aa7613557': `Your network is currently empty.`,
'sd2e79aff2aea724a': `You currently do not have an input layer. Drag one onto the canvas!`,
's37abcf4d745436f7': `You currently do not have an output layer. Drag one onto the canvas!`,
's6a4607c5c4e55a03': `Always make sure to connect your layers such that there is a path from your input layer(s) to your output layer! Therefore select a layer in the canvas and select its incoming or outgoing connections`,
's6a0bc0ce56a9ae4a': `Features`,
's5590dbf7e425789d': `Label`,
's07e767f1fe8ad66a': `View raw data`,
's41ee884e3b2d7413': `Click on an feature pill above to see the relation between this feature and the label in a plot`,
'scc33c632d6e60d84': `plotted against`,
's01c091af962d4963': `Plots`,
's573de432d7ee9439': `The progress you made in creating your own data set was successfully restored!`,
's8e77b85b1ae353e5': `A data set with the same name already exists!`,
's669ebaf3b9787562': `The provided data does not match the required format! Please check again`,
'see988347633ae840': `A new data set was successfully created and automatically selected!`,
's18de3f0678131658': `Create a new data set`,
'scdb1bac161852c73': `Welcome`,
's59163864a74213df': `This tour will guide you through creating your own data set in a few simple steps. Everything is stored automatically, so you can close this modal at any time and resume.`,
's420e8fef6d553399': `General info about the data set`,
'sf82bd0ca92fc7478': `Choose a short but meaningful name for your data set and write a description.`,
'sef49aec68fd1dc66': `Name`,
's63d894b1ddb06289': `Description`,
'sea29890d344759e2': `Choose 'regression' if you want to predict continous values like house or gas prices`,
'sa51b42a0f8bc1196': `Choose 'classification' if you want information about the affiliation of the feature(s) to a class (e.g. what animal can be seen in this image? A dog, cat or horse?)`,
's381b5d0debf831a1': `Choose a type`,
's641101718c90c0aa': `Which data will be put into the neural network? Create arbitrary many features!`,
's506b6a19d12f414c': `Key`,
's0c9543b42518e43e': `1-6 capital letters`,
's9ccab5f6530bd7fb': `Remove feature`,
'sb1cdfd5a8a60f3ca': `Add feature`,
'sa7f1260d99ed4dcb': `What shall be the output of the network?`,
's2ba861fd720acdec': `an integer`,
's2511ced2063529c4': `Animal was detected as a horse`,
's81fe4b139dbcd729': `Remove class`,
's3187969905158d04': `Add class`,
's93aa17486b781f3d': `You are nearly done`,
's4770b2377cfb5113': `Now add your data in the following format`,
's514bbfe7a6a1385a': `Each row needs to represent one set containing the features and the label. Seperate items with a comma (spaces before and after the comma are okay). The single last item always represents the label while the items before it represent the features. Make sure to use only dots and no commas for floating point values. If you have data in CSV format, you can just paste it here but make sure to remove any comments.`,
'sf3ff78cc329d3528': `Previous`,
's0fbf6dc6a1966408': `Next`,
's886925e360029fea': `Validate and create`,
's688d523f38404f47': `Manage data sets`,
's114321122eed37a2': `Currently selected`,
's05560220ff65f5eb': `Permanently delete data set`,
's7ad8f95cd252ff9b': `Select data set`,
's8e0e95cf2d9f0fe0': `"Select a data set"`,
's9ea77d0d371dc469': `Train`,
's69bf683344258f79': `Training completed!`,
'sedc9092c834a7a37': `Feel free to continue training your model for some additional epochs which might get you even better results!`,
's900c980bdb200fcf': `Epochs`,
's7f291599fb79b2a9': `Number of iterations over the whole training data set`,
's9fbbc819fe7e66aa': `Run`,
's7ae39eeb994f4040': `Train for 1 epoch`,
's415ece5a1e4e50ce': `Train for`,
'sa24fcd4e36a13aef': `epochs`,
's12db7f32a3851306': `Epoch`,
'safda35e3d523b59b': `Batch`,
's97aa76056a81bd36': `Metrics`,
's61e8f3fac73d5e85': `Loss: Categorical Crossentropy`,
's9f262d3debac7e63': `Accuracy: In what percentage of the tests was the right class predicted?`,
's04cf457a74a1ca3e': `Loss: Mean Squared Error`,
's5f343a43e7ea9f91': `Error`,
's7fd689e3ee842226': `What is the difference between the two lines in a graph?`,
's9cc47ae161b22379': `For val_..., the metric is calculated on the validation data set while for the data without val as a prefix the metric is calculated on the training data set. The metrics for the validation data set can be seen as more meaningful since this is the data the network does not 'know'.`,
's5ebe428b72f9d9fd': `Hyperparameters`,
'sd674ba4ce23f2290': `Batch size`,
'sa4aa72be4b18da23': `Learning rate`,
's29028574383c26b2': `Dropout rate`,
's0d783bd504d48897': `Adjust the probability of neurons being deactivated during training`,
'sd8305d1efc816b0a': `Predict`,
'sf7aa4a7f6a7a6ae9': `Predicted label`,
's5a27bd37c0a0ad1a': `with a probability of`,
'sd0ee89e8e7353561': `Make another prediction`,
's8af61807443f32a4': `Actions`,
'sfac15b89e0668996': `Duplicate`,
'sdc673e73b5c13aea': `Delete`,
's22b10e3713c037c7': `Activation function`,
'sa90802aba569f823': `The selected activation applies to all neurons in this layer.`,
's256782b6fa6c81e3': `After calculating a neuron's value by adding up its weighted input values and its bias:`,
's514d47a63e3b11c3': `Range of possible output values:`,
's801ac62b23cc5f5f': `Neurons`,
'sea4f08110bb8f15d': `Remove`,
'sf9aee319a006c9b4': `Add`,
's5a95fb6f50ddd6ff': `neurons`,
's8b0432eecbd8b034': `Update`,
's69a4b7731c4ab258': `Incoming connections`,
'sfcb8881b108f62ed': `Select the layers that connect to this layer`,
'sf35b120256b540b4': `Assign feature to this layer. Hover over the feature keys in the opened dropdown menu for a description.`,
's47333467f911302a': `Outgoing connections`,
's684e13d4e599ccdd': `Select the layers this layer connects to`,
'saf83c9eefbdeee91': `Outgoing data`,
's690d876ebcfe1dd6': `Neuron`,
's8efe9b047510b849': `Corresponding layer:`,
'sd6b4fb36bd73f830': `Assigned feature (input)`,
's888d98a196a240d8': `Inputs`,
's7aaa83f30a557ce9': `- All neurons from`,
's4a3a9e0c684b763f': `Label (output)`,
's066d70cf9d5e2915': `Outputs`,
's6503256c2de2745c': `Edge`,
's517acbf1f96324f9': `Weight`,
'sae1c7f13b7c0c47f': `Start`,
's0b29ddb08394f57b': `Failed to enter fullscreen mode.`,
'sb59d68ed12d46377': `Loading`,
    };