Row 6040

Row ID: 6040 | Dataset Entry | Axioma AXP Content Repository

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Does your model convert to tflite? Have you tried running inference and checking the results. You will input the series up until a point and it will predict the following values.

If you want to continually predict the next value, the naive solution is to run the entire series as input on each inference. The LSTM stores “memory” as it processes through the input series. It does not store memory between inferences. You as a developer, do not need to manage these.

The page on the tflite docs for rnn: https://www.tensorflow.org/lite/models/convert/rnn

FieldValue
text Does your model convert to tflite? Have you tried running inference and checking the results. You will input the series up until a point and it will predict the following values. If you want to continually predict the next value, the naive solution is to run the entire series as input on each inference. The LSTM stores “memory” as it processes through the input series. It does not store memory between inferences. You as a developer, do not need to manage these. The page on the tflite docs fo…
label r/tensorflow
dataType comment
communityName r/tensorflow
datetime 2024-05-06
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  "text": "Does your model convert to tflite? Have you tried running inference and checking the results. You will input the series up until a point and it will predict the following values. \n\nIf you want to continually predict the next value, the naive solution is to run the entire series as input on each inference. The LSTM stores “memory” as it processes through the input series. It does not store memory between inferences. You as a developer, do not need to manage these. \n\nThe page on the tflite docs for rnn: https://www.tensorflow.org/lite/models/convert/rnn",
  "label": "r/tensorflow",
  "dataType": "comment",
  "communityName": "r/tensorflow",
  "datetime": "2024-05-06",
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}
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