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#
# Copyright (C) 2018 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, 1, 1, 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, 1, 1, 3}")
model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(output)
model = model.RelaxedExecution(True)
# Example 1. Input in operand 0,
input0 = {i1: # input 0
[99.0, 99.0, 99.0],
f1:
[1.0, 1.0, 1.0,
2.0, 2.0, 2.0,
3.0, 3.0, 3.0],
b1:
[0., 0., 0.]}
output0 = {output: # output 0
[297., 594., 891.]}
# Instantiate an example
Example((input0, output0))
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