code: def test_conv1d(
      self,
      filters,
      kernel_size,
      strides,
      padding,
      data_format,
      dilation_rate,
      groups,
  ):
      layer = layers.Conv1D(
          filters=filters,
          kernel_size=kernel_size,
          strides=strides,
          padding=padding,
          data_format=data_format,
          dilation_rate=dilation_rate,
          groups=groups,
      )
  
      inputs = np.random.normal(size=[2, 8, 4])
      layer.build(input_shape=inputs.shape)
  
      kernel_shape = layer.kernel.shape
      kernel_weights = np.random.normal(size=kernel_shape)
      bias_weights = np.random.normal(size=(filters,))
      layer.kernel.assign(kernel_weights)
      layer.bias.assign(bias_weights)
  
      outputs = layer(inputs)
      expected = np_conv1d(
          inputs,
          kernel_weights,
          bias_weights,
          strides=strides,
          padding=padding,
          data_format=data_format,
          dilation_rate=dilation_rate,
          groups=groups,
      )
      self.assertAllClose(outputs, expected)
  
imports: import numpy
  import pytest
  from absl.testing import parameterized
  from numpy.lib.stride_tricks import as_strided
  from keras import constraints
  from keras import layers
  from keras import testing
label_desc: Use image node_id 1 for calling the ConvCorrectnessTest obj's underlying member method code with example usage: obj.test_conv1d(filters, kernel_size, strides, padding, data_format, dilation_rate, groups) without return types