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#
# Copyright (C) 2018 The Android Open Source Project
# Copyright (C) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
#
# 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.
#
'''
Testing (Reduce)Mean op when the input is dynamic.
input[1, 3, 4, 1] shape [4]
| |
+-------------+
|
Reshape (added by DynamicInputGenerator since it generates its output to be dynamic)
|
| axis = 2 keepDims = True
| | |
+-------------+-------------+
|
|
| dynamic tensor at compilation time but the shape will be [1, 3, 4, 1] at execution time
|
ReduceMean
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output (dynamic tensor, [1, 3, 1, 1] at execution time)
'''
import dynamic_tensor
model = Model()
model_input_shape = [1, 3, 4, 1]
dynamic_layer = dynamic_tensor.DynamicInputGenerator(model, model_input_shape, "TENSOR_FLOAT32")
test_node_input = dynamic_layer.getTestNodeInput()
# write REDUCE_MEAN test. input is `test_input`
# note output shape is used by expected output's shape
model_output = Output("output", "TENSOR_FLOAT32", "{1, 3, 1, 1}")
axis = Int32Scalar("axis", 2)
keepDims = Int32Scalar("keepDims", 1)
model.Operation("MEAN", test_node_input, axis, keepDims).To(model_output)
model_input_data = [1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0]
model_output_data = [2.5, 2.5, 2.5]
Example({
dynamic_layer.getModelInput() : model_input_data,
dynamic_layer.getShapeInput() : model_input_shape,
model_output: model_output_data,
})
|
