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Diffstat (limited to 'nn/runtime/test/specs/V1_3/add_quant8_signed.mod.py')
-rw-r--r-- | nn/runtime/test/specs/V1_3/add_quant8_signed.mod.py | 96 |
1 files changed, 96 insertions, 0 deletions
diff --git a/nn/runtime/test/specs/V1_3/add_quant8_signed.mod.py b/nn/runtime/test/specs/V1_3/add_quant8_signed.mod.py new file mode 100644 index 000000000..9fb33eabd --- /dev/null +++ b/nn/runtime/test/specs/V1_3/add_quant8_signed.mod.py @@ -0,0 +1,96 @@ +# +# Copyright (C) 2019 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_QUANT8_ASYMM_SIGNED", "{2}, 2.0, 0") +i2 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, 0") +act = Int32Scalar("act", 0) +i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, 0") +model = model.Operation("ADD", i1, i2, act).To(i3) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2], + i2: # input 1 + [3, 4]} + +output0 = {i3: # output 0 + [5, 8]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2}, 2.0, 0") +i2 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 1.0, 0") +act = Int32Scalar("act", 0) +i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 1.0, 0") +model = model.Operation("ADD", i1, i2, act).To(i3) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2], + i2: # input 1 + [1, 2, 3, 4]} + +output0 = {i3: # output 0 + [3, 6, 5, 8]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +# Zero-sized input test +# Use BOX_WITH_NMS_LIMIT op to generate a zero-sized internal tensor for box cooridnates. +p1 = Parameter("scores", "TENSOR_FLOAT32", "{1, 2}", [0.90, 0.10]) # scores +p2 = Parameter("roi", "TENSOR_FLOAT32", "{1, 8}", [1, 1, 10, 10, 0, 0, 10, 10]) # roi +o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out +o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out +tmp1 = Internal("roiOut", "TENSOR_FLOAT32", "{0, 4}") # roi out +tmp2 = Internal("batchSplitOut", "TENSOR_INT32", "{0}") # batch split out +model = Model("zero_sized").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) + +# Use ROI_ALIGN op to convert into zero-sized feature map. +layout = BoolScalar("layout", False) # NHWC +i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") +zero_sized = Internal("featureMap", "TENSOR_FLOAT32", "{0, 2, 2, 2}") +model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized) + +# ADD op with numBatches = 0. +i2 = Parameter("op", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) # weights +o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 2}") # out +model = model.Operation("ADD", zero_sized, i2, 0).To(o3) + +quant8_signed = DataTypeConverter().Identify({ + p1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), + p2: ("TENSOR_QUANT16_ASYMM", 0.125, 0), + o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), + tmp1: ("TENSOR_QUANT16_ASYMM", 0.125, 0), + i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), + zero_sized: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), + i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), + o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0) +}) + +Example({ + i1: [1, 2], + o1: [], + o2: [], + o3: [], +}).AddVariations(quant8_signed, includeDefault=False) |