Source code for webdnn.graph.operators.zero_padding_1d

from typing import Optional

from webdnn.graph.axis import Axis
from webdnn.graph.operator import Operator
from webdnn.graph.operators.attributes.tensorwise import Tensorwise
from webdnn.graph.operators.util import IntOrTuple, to_tuple
from webdnn.graph.order import OrderNTC
from webdnn.graph.variable import Variable


[docs]class ZeroPadding1D(Operator): """ZeroPadding1D(name, padding) Zero padding 1D operator Add padding to time-series data (n, t, c) -> (n, left + t + right, c) Args: name (str): Operator name. padding (int or tuple of int): Padding size. [left, right] Signature .. code:: y, = op(x) - **x** - Input variable. - **y** - Output variable. Its order and shape is same as :code:`x`. """ def __init__(self, name: Optional[str], padding: IntOrTuple): super().__init__(name) self.parameters["padding"] = to_tuple(padding) self.attributes.add(Tensorwise(Axis.C)) self.attributes.add(Tensorwise(Axis.N)) def __call__(self, x: Variable): x_shape_dict = x.shape_dict N = x_shape_dict[Axis.N] T2 = x_shape_dict[Axis.T] + self.parameters["padding"][0] + self.parameters["padding"][1] C2 = x_shape_dict[Axis.C] y = Variable([N, T2, C2], OrderNTC) y.change_order(x.order) # output same order as input to preserve following reshape semantics self.append_input("x", x) self.append_output("y", y) return y,