def conv1DWavelet(wav, waveletWidth, waveletEquation):
kernelSamples = waveletWidth * 10
kernel = waveletEquation(waveletWidth, kernelSamples)
kernel = tf.reverse(kernel, [0])
kernel = tf.reshape(kernel, tf.stack([kernelSamples,1,1,1]))
conv = tf.nn.conv2d(wav, kernel, [1,1,1,1], padding='SAME')
conv = tf.squeeze(tf.squeeze(conv))
return conv
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