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#
# 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, 4}") # depth_in = 4
f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_out = 4
b1 = Input("op3", "TENSOR_FLOAT32", "{4}") # depth_out = 4
pad0 = Int32Scalar("pad0", 0)
act = Int32Scalar("act", 0)
stride = Int32Scalar("stride", 1)
cm = Int32Scalar("channelMultiplier", 1)
output = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 4}")
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, 100, 0,
10, 22, 200, 0,
10, 23, 300, 0,
10, 24, 400, 0],
f1: [
.25, 0, 10, 100,
.25, 1, 20, 100,
.25, 0, 30, 100,
.25, 1, 40, 100],
b1:
[600000, 700000, 800000, 900000]
}
# (i1 (conv) f1) + b1
output0 = {output: # output 0
[600010, 700046, 830000, 900000]}
# Instantiate an example
Example((input0, output0))
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