class_docstr: Compute the magnitude of the input (tflite compatible).
  
  The input is a real tensor, the last dimension has a size of `2`
  representing real and imaginary parts respectively.
  
  Example:
      ::
  
          input_shape = (2048, 1)  # mono signal
          model = Sequential()
          model.add(kapre.STFTTflite(n_fft=1024, hop_length=512, input_shape=input_shape))
          mode.add(MagnitudeTflite())
          # now the shape is (batch, n_frame=3, n_freq=513, ch=1) and dtype is float
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docstr: Args:
      x (real or complex `Tensor`): input is real tensor whose last
          dimension has a size of `2` and represents real and imaginary
          parts
  
  Returns:
      (float `Tensor`): magnitude of `x`
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code: def call(self, x):
      """
      Args:
          x (real or complex `Tensor`): input is real tensor whose last
              dimension has a size of `2` and represents real and imaginary
              parts
  
      Returns:
          (float `Tensor`): magnitude of `x`
      """
      return tf.norm(x, ord="euclidean", axis=-1)
  
file_path: kapre/kapre/time_frequency_tflite.py
imports: import tensorflow
  from .backend import _CH_FIRST_STR, _CH_LAST_STR, _CH_DEFAULT_STR
  from .tflite_compatible_stft import stft_tflite, atan2_tflite
  from .time_frequency import STFT, InverseSTFT, Magnitude, Phase
label_desc: Use image node_id 1 for calling the MagnitudeTflite obj's underlying member method code with example usage: obj.call(x) and returns: tf