tf.compat.v1.nn.conv1d

Computes a 1-D convolution of input with rank >=3 and a 3-D filter. (deprecated argument values) (deprecated argument values)

Given an input tensor of shape batch_shape + [in_width, in_channels] if data_format is "NWC", or batch_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 shape batch_shape + [in_width, in_channels] is reshaped to batch_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 to batch_shape + [out_width, out_channels] (where out_width is a function of the stride and padding as in conv2d) and returned to the caller.

valueA Tensor of rank at least 3. Must be of type float16, float32, or float64.
filtersA Tensor of rank at least 3. Must have the same type as value.
strideAn 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'
use_cudnn_on_gpuAn optional bool. Defaults to True.
data_formatAn optional string from "NWC", "NCW". Defaults to "NWC", the data is stored in the order of batch_shape + [in_width, in_channels]. The "NCW" format stores data as batch_shape + [in_channels, in_width].
nameA name for the operation (optional).
inputAlias for value.
dilationsAn 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.

A Tensor. Has the same type as input.

ValueErrorif data_format is invalid.