blob: 9e8b297fd56cf845aa505c574cef17b92466f2c0 [file] [log] [blame]
#
# Copyright (C) 2017 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
model = Model()
i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # depth_in = 2
f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}", [.25, 0, .25, 1, .25, 0, .25, 1]) # depth_out = 2
b1 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [100, 200]) # depth_out = 2
pad0 = Int32Scalar("pad0", 0)
act = Int32Scalar("act", 0)
stride = Int32Scalar("stride", 1)
cm = Int32Scalar("channelMultiplier", 1)
output = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 2}")
model = model.Operation("DEPTHWISE_CONV_2D",
i1, f1, b1,
pad0, pad0, pad0, pad0,
stride, stride,
cm, act).To(output)
# Example 1. Input in operand 0,
input0 = {
i1: [ # input 0
10, 21, 10, 22,
10, 23, 10, 24],
}
# (i1 (conv) f1) + b1
output0 = {output: # output 0
[110, 246]}
# Instantiate an example
Example((input0, output0))