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Diffstat (limited to 'runtimes/tests/neural_networks_test/specs/V1_0/max_pool_quant8_3.mod.py')
-rw-r--r-- | runtimes/tests/neural_networks_test/specs/V1_0/max_pool_quant8_3.mod.py | 53 |
1 files changed, 53 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/specs/V1_0/max_pool_quant8_3.mod.py b/runtimes/tests/neural_networks_test/specs/V1_0/max_pool_quant8_3.mod.py new file mode 100644 index 000000000..e2270aaa6 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_0/max_pool_quant8_3.mod.py @@ -0,0 +1,53 @@ +# +# 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 = Model() + +bat = 5 +row = 50 +col = 70 +chn = 3 + +i0 = Input("i0", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 0.5f, 0" % (bat, row, col, chn)) + +std = 20 +flt = 20 +pad = 0 + +stride = Int32Scalar("stride", std) +filt = Int32Scalar("filter", flt) +padding = Int32Scalar("padding", pad) +act2 = Int32Scalar("relu1_activation", 2) +output_row = (row + 2 * pad - flt + std) // std +output_col = (col + 2 * pad - flt + std) // std + +output = Output("output", "TENSOR_QUANT8_ASYMM", + "{%d, %d, %d, %d}, 0.5f, 0" % (bat, output_row, output_col, chn)) + +model = model.Operation( + "MAX_POOL_2D", i0, padding, padding, padding, padding, stride, stride, filt, filt, act2).To(output) + +# Example 1. Input in operand 0 +input_range = bat * row * col * chn +input_values = (lambda s = std, r = input_range: [x % s + 1 for x in range(r)])() +input0 = {i0: input_values} +output_range = bat * output_row * output_col * chn +output_values = (lambda r = output_range: [ 2 for _ in range(r)])() +output0 = {output: output_values} + +# Instantiate an example +Example((input0, output0)) |