docstr: Compute a 1-D max unpooling given the 1-D pooled input x and its
  indices.
  
  Parameters
  ----------
  self
      Pooled input image *[batch_size, w, d_in]*.
  indices
      Indices obtained from the corresponding max pooling operation.
  kernel_size
      Size of the kernel i.e., the sliding window for each
      dimension of input. *[w]*.
  strides
      The stride of the sliding window for each dimension of input.
  padding
      SAME" or "VALID" indicating the algorithm, or list
      indicating the per-dimension paddings.
  data_format
      NWC" or "NCW". Defaults to "NCW".
  
  Returns
  -------
  ret
      The result of the unpooling operation.
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code: def max_unpool1d(
      self,
      indices: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      kernel_size: Union[Tuple[int], int],
      /,
      *,
      strides: Optional[Union[int, Tuple[int]]] = None,
      padding: Union[int, Tuple[int]] = 0,
      data_format: Optional[str] = "NCW",
  ) -> ivy.Container:
      """Compute a 1-D max unpooling given the 1-D pooled input x and its
      indices.
  
      Parameters
      ----------
      self
          Pooled input image *[batch_size, w, d_in]*.
      indices
          Indices obtained from the corresponding max pooling operation.
      kernel_size
          Size of the kernel i.e., the sliding window for each
          dimension of input. *[w]*.
      strides
          The stride of the sliding window for each dimension of input.
      padding
          SAME" or "VALID" indicating the algorithm, or list
          indicating the per-dimension paddings.
      data_format
          NWC" or "NCW". Defaults to "NCW".
  
      Returns
      -------
      ret
          The result of the unpooling operation.
      """
      return self.static_max_unpool1d(
          self,
          indices,
          kernel_size,
          strides=strides,
          padding=padding,
          data_format=data_format,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Literal, Sequence, Callable
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 44 for calling the _ContainerWithLayersExperimental obj's underlying member method code with example usage: obj.max_unpool1d() and returns: self