Function FakeQuantWithMinMaxVarsGradient

tensorflow/go/op/wrappers.go:190–207

Compute gradients for a FakeQuantWithMinMaxVars operation. Arguments: gradients: Backpropagated gradients above the FakeQuantWithMinMaxVars operation. inputs: Values passed as inputs to the FakeQuantWithMinMaxVars operation. min, max: Quantization interval, scalar floats. Returns Backpropagate

(scope *Scope, gradients tf.Output, inputs tf.Output, min tf.Output, max tf.Output, optional ...FakeQuantWithMinMaxVarsGradientAttr)

// `sum(gradients * (inputs < min))`.Backpropagated gradients w.r.t. max parameter:
// `sum(gradients * (inputs > max))`.
func FakeQuantWithMinMaxVarsGradient(scope *Scope, gradients tf.Output, inputs tf.Output, min tf.Output, max tf.Output, optional ...FakeQuantWithMinMaxVarsGradientAttr) (backprops_wrt_input tf.Output, backprop_wrt_min tf.Output, backprop_wrt_max tf.Output) {
	if scope.Err() != nil {
		return
	}
	attrs := map[string]interface{}{}
	for _, a := range optional {
		a(attrs)
	}
	opspec := tf.OpSpec{
		Type: "FakeQuantWithMinMaxVarsGradient",
		Input: []tf.Input{
			gradients, inputs, min, max,
		},
		Attrs: attrs,
	}
	op := scope.AddOperation(opspec)
	return op.Output(0), op.Output(1), op.Output(2)
}

// FakeQuantWithMinMaxVarsAttr is an optional argument to FakeQuantWithMinMaxVars.
type FakeQuantWithMinMaxVarsAttr func(optionalAttr)