parameters: (features, grad)
return_statement: return grad * activation_grad
docstring: Gradient of Swish function defined below.
docstring_summary: Gradient of Swish function defined below.
docstring_tokens: Gradient of Swish function defined below .
function: def _swish_grad(features, grad):
    """Gradient of Swish function defined below."""
    sigmoid_features = math_ops.sigmoid(features)
    activation_grad = (
        sigmoid_features * (1.0 + features * (1.0 - sigmoid_features)))
    return grad * activation_grad
function_tokens: def _swish_grad ( features , grad ) : sigmoid_features = math_ops . sigmoid ( features ) activation_grad = ( sigmoid_features * ( 1.0 + features * ( 1.0 - sigmoid_features ) ) ) return grad * activation_grad