tf.nn.conv1d

tf.nn.conv1d

tf.nn.conv1d

conv1d(
    value,
    filters,
    stride,
    padding,
    use_cudnn_on_gpu=None,
    data_format=None,
    name=None
)

Defined in tensorflow/python/ops/nn_ops.py.

See the guide: Neural Network > Convolution

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 "NHWC", or [batch, in_channels, in_width] if data_format is "NCHW", 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:

• value: A 3D Tensor. Must be of type float32 or float64.
• filters: A 3D Tensor. Must have the same type as input.
• stride: An integer. The number of entries by which the filter is moved right at each step.
• padding: 'SAME' or 'VALID'
• use_cudnn_on_gpu: An optional bool. Defaults to True.
• data_format: An optional string from "NHWC", "NCHW". Defaults to "NHWC", the data is stored in the order of [batch, in_width, in_channels]. The "NCHW" format stores data as [batch, in_channels, in_width].
• name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input.

Raises:

• ValueError: if data_format is invalid.