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messages for NN
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@rbudde
rbudde committed Nov 26, 2021
1 parent 0c5c125 commit ad93ea3
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36 changes: 18 additions & 18 deletions blockly_compressed.js
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2 changes: 1 addition & 1 deletion blocks/robActions.js
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Expand Up @@ -1571,7 +1571,7 @@ Blockly.Blocks["robActions_aifes_classify"] = {

Blockly.Blocks["robActions_NNstep"] = {
init: function () {
appendHeader(this, "NNstep");
appendHeader(this, "NN_STEP");
this.setColour(Blockly.CAT_LOGIC_RGB);
this.appendStatementInput("IONEURON");
this.getInput("IONEURON").connection.setCheck("neuron");
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11 changes: 3 additions & 8 deletions msg/js/ar.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/az.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/ba.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/bcc.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/be-tarask.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/be.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "не";
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11 changes: 3 additions & 8 deletions msg/js/bg.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/bn.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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11 changes: 3 additions & 8 deletions msg/js/br.js
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Expand Up @@ -991,20 +991,15 @@ Blockly.Msg.NN_CLASS_NUMBER = "class #"; // untranslated
Blockly.Msg.NN_CLASS_PROBABILITIES = "probabilities"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA = "initialize raw data"; // untranslated
Blockly.Msg.NN_INIT_RAW_DATA_TOOLTIP = "clear raw data memory. Then add raw data multiple times, extract the input features from it and add that to the trainings data"; // untranslated
Blockly.Msg.NN_IO_NEURON_NAMES_INVALID = "names of input/output neurons must be all different and valid (start with letter, no spaces, ...)"; // untranslated
Blockly.Msg.NN_MAX_NUMBER_OF_NEURONS = "max neurons"; // untranslated
Blockly.Msg.NN_NUMBER_INPUT_NEURONS = "# input neurons"; // untranslated
Blockly.Msg.NN_NUMBER_OF_CLASSES = "# classes"; // untranslated
Blockly.Msg.NN_RAW_DATA = "raw value"; // untranslated
Blockly.Msg.NN_SETUP = "setup the neural network"; // untranslated
Blockly.Msg.NN_SETUP_TOOLTIP = "define properties of a neural network, which can classify data"; // untranslated
Blockly.Msg.NN_STEP = "one step in the neural network"; // untranslated
Blockly.Msg.NN_STEP_INPUT0 = "input to neuron i0"; // untranslated
Blockly.Msg.NN_STEP_INPUT1 = "input to neuron i1"; // untranslated
Blockly.Msg.NN_STEP_INPUT2 = "input to neuron i2"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT0 = "output of neuron o0"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT1 = "output of neuron o1"; // untranslated
Blockly.Msg.NN_STEP_OUTPUT2 = "output of neuron o2"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in the neural network, write the outputs into the variables"; // untranslated
Blockly.Msg.NN_STEP = "one NN step"; // untranslated
Blockly.Msg.NN_STEP_TOOLTIP = "retrieve inputs, execute one step in a neural network, write the outputs into variables"; // untranslated
Blockly.Msg.NN_TRAIN = "train"; // untranslated
Blockly.Msg.NN_TRAIN_TOOLTIP = "train the neural network with the trainings data assembled"; // untranslated
Blockly.Msg.NO = "no"; // untranslated
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