blob: cc0eaa9e4ce5faeb5dbeb5592079b10c86b855f1 [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, 3, 3}")
f1 = Input("op2", "TENSOR_FLOAT32", "{3, 1, 1, 3}")
b1 = Input("op3", "TENSOR_FLOAT32", "{3}")
pad0 = Int32Scalar("pad0", 0)
act = Int32Scalar("act", 0)
stride = Int32Scalar("stride", 1)
# output dimension:
# (i1.height - f1.height + 1) x (i1.width - f1.width + 1)
output = Output("op4", "TENSOR_FLOAT32", "{1, 2, 3, 3}")
model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(output)
# Example 1. Input in operand 0,
input0 = {i1: # input 0
[ 1., 2., 3., 4., 5., 6., 7., 8., 9.,
10., 11., 12., 13., 14., 15., 16., 17., 18.],
f1:
[ 1., 4., 7.,
2., 5., 8.,
3., 6., 9.],
b1:
[0., 0., 0.]}
output0 = {output: # output 0
[ 30., 36., 42.,
66., 81., 96.,
102., 126., 150.,
138., 171., 204.,
174., 216., 258.,
210., 261., 312.]
}
# Instantiate an example
Example((input0, output0))