Is there a difference between tf.nn.conv1d and tf.nn.convolution in Tensorflow?
In TensorFlow 2, they accept different arguments:


  tf.nn.convolution(input,...)
  
  Computes sums of N-D convolutions (actually cross-correlation). 
  
  input: An (N+2)-D Tensor of type T, of shape [batch_size] + input_spatial_shape + [in_channels]


While the second one is more specific:


  tf.nn.conv1d(input,...)
  
  Computes a 1-D convolution given 3-D input and filter tensors.
  
  input: A 3D Tensor.input: A 3D Tensor.