tf.nn.conv1d | TensorFlow v2.16.1 (original) (raw)

Computes a 1-D convolution given 3-D input and filter tensors.

tf.nn.conv1d(
    input,
    filters,
    stride,
    padding,
    data_format='NWC',
    dilations=None,
    name=None
)

Given an input tensor of shapebatch_shape + [in_width, in_channels]if data_format is "NWC", orbatch_shape + [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 shapebatch_shape + [in_width, in_channels]is reshaped tobatch_shape + [1, in_width, in_channels], and the filter is reshaped to[1, filter_width, in_channels, out_channels]. The result is then reshaped back tobatch_shape + [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 Tensor of rank at least 3. Must be of type float16, float32, orfloat64.
filters	A Tensor of rank at least 3. 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'. Seeherefor more information.
data_format	An optional string from "NWC", "NCW". Defaults to "NWC", the data is stored in the order ofbatch_shape + [in_width, in_channels]. The "NCW" format stores data as batch_shape + [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.