train docstring simplification
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@ -45,7 +45,7 @@ function stop()
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end
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"""
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train!(loss, params, data, opt; cb = () -> ())
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train!(loss, params, data, opt; cb)
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For each datapoint `d` in `data` computes the gradient of `loss(d...)` through
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backpropagation and calls the optimizer `opt`.
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