Function conv1d_v2

tensorflow/python/ops/nn_ops.py:1728–1789

r"""Computes a 1-D convolution given 3-D input and filter tensors. Given an input tensor of shape [batch, in_width, in_channels] if data_format is "NWC", or [batch, in_channels, in_width] if data_format is "NCW", and a filter / kernel tensor of shape [filter_width, in_channels, ou

(
    input,  # pylint: disable=redefined-builtin
    filters,
    stride,
    padding,
    data_format="NWC",
    dilations=None,
    name=None)

@tf_export("nn.conv1d", v1=[])
def conv1d_v2(
    input,  # pylint: disable=redefined-builtin
    filters,
    stride,
    padding,
    data_format="NWC",
    dilations=None,
    name=None):
  r"""Computes a 1-D convolution given 3-D input and filter tensors.

  Given an input tensor of shape
    [batch, in_width, in_channels]
  if data_format is "NWC", or
    [batch, in_channels, in_width]
  if data_format is "NCW",
  and a filter / kernel tensor of shape
  [filter_width, in_channels, out_channels], this op reshapes
  the arguments to pass them to conv2d to perform the equivalent
  convolution operation.

  Internally, this op reshapes the input tensors and invokes `tf.nn.conv2d`.
  For example, if `data_format` does not start with "NC", a tensor of shape
    [batch, in_width, in_channels]
  is reshaped to
    [batch, 1, in_width, in_channels],
  and the filter is reshaped to
    [1, filter_width, in_channels, out_channels].
  The result is then reshaped back to
    [batch, out_width, out_channels]
  \(where out_width is a function of the stride and padding as in conv2d\) and
  returned to the caller.

  Args:
    input: A 3D `Tensor`.  Must be of type `float16`, `float32`, or `float64`.
    filters: A 3D `Tensor`.  Must have the same type as `input`.
    stride: An int or list of `ints` that has length `1` or `3`.  The number of
      entries by which the filter is moved right at each step.
    padding: 'SAME' or 'VALID'
    data_format: An optional `string` from `"NWC", "NCW"`.  Defaults to `"NWC"`,
      the data is stored in the order of [batch, in_width, in_channels].  The
      `"NCW"` format stores data as [batch, in_channels, in_width].
    dilations: An int or list of `ints` that has length `1` or `3` which
      defaults to 1. The dilation factor for each dimension of input. If set to
      k > 1, there will be k-1 skipped cells between each filter element on that
      dimension. Dilations in the batch and depth dimensions must be 1.
    name: A name for the operation (optional).

  Returns:
    A `Tensor`.  Has the same type as input.

  Raises:
    ValueError: if `data_format` is invalid.
  """
  return conv1d(
      input,  # pylint: disable=redefined-builtin
      filters,
      stride,
      padding,