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Diffstat (limited to 'nn/runtime/test/specs/V1_3/fully_connected_quant8_signed.mod.py')
-rw-r--r-- | nn/runtime/test/specs/V1_3/fully_connected_quant8_signed.mod.py | 187 |
1 files changed, 187 insertions, 0 deletions
diff --git a/nn/runtime/test/specs/V1_3/fully_connected_quant8_signed.mod.py b/nn/runtime/test/specs/V1_3/fully_connected_quant8_signed.mod.py new file mode 100644 index 000000000..a1e3bf201 --- /dev/null +++ b/nn/runtime/test/specs/V1_3/fully_connected_quant8_signed.mod.py @@ -0,0 +1,187 @@ +# +# 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() +in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{4, 1, 5, 1}, 0.5f, -1") +weights = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 10}, 0.5f, -1", + [1, 3, 5, 7, 9, 11, 13, 15, 17, 19, + 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, + 1, 3, 5, 7, 9, 11, 13, 15, 17, 19]) +bias = Parameter("b0", "TENSOR_INT32", "{3}, 0.25f, 0", [4, 8, 12]) +out0 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 3}, 1.f, -1") +act_relu = Int32Scalar("act_relu", 1) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [1, 3, 5, 7, 9, 11, 13, 15, -19, -21, + 1, 3, 5, 7, 9, 11, 13, -17, 17, -21]} +output0 = {out0: # output 0 + [23, 24, 25, 57, 58, 59]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128") # batch = 1, input_size = 5 +weights = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128", [-118, -108, -108, -108, -118]) # num_units = 1, input_size = 5 +bias = Parameter("b0", "TENSOR_INT32", "{1}, 0.04, 0", [10]) +out0 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1}, 1.f, -128") # batch = 1, number_units = 1 +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [-118, -118, -118, -118, -118]} +output0 = {out0: # output 0 + [-96]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128") # batch = 1, input_size = 5 +weights = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128") # num_units = 1, input_size = 5 +bias = Input("b0", "TENSOR_INT32", "{1}, 0.04, 0") +out0 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1}, 1.f, -128") # batch = 1, number_units = 1 +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [-118, -118, -118, -118, -118], + weights: + [-118, -108, -108, -108, -118], + bias: + [10]} +output0 = {out0: # output 0 + [-96]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 1}, 0.5f, -128") +weights = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1}, 0.5f, -128", [-126]) +bias = Parameter("b0", "TENSOR_INT32", "{1}, 0.25f, 0", [4]) +out0 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 1}, 1.f, -128") +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [-126, -96, -112]} +output0 = {out0: # output 0 + [-126, -111, -119]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 1}, 0.5f, -128") +weights = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1}, 0.5f, -128") +bias = Input("b0", "TENSOR_INT32", "{1}, 0.25f, 0") +out0 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 1}, 1.f, -128") +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [-126, -96, -112], + weights: [-126], + bias: [4]} +output0 = {out0: # output 0 + [-126, -111, -119]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +in0 = Input("op1", "TENSOR_FLOAT32", "{3, 1}") +weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 1}", [2]) +bias = Parameter("b0", "TENSOR_FLOAT32", "{1}", [4]) +out0 = Output("op3", "TENSOR_FLOAT32", "{3, 1}") +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +quant8_signed_mult_gt_1 = DataTypeConverter(name="quant8_mult_gt_1").Identify({ + in0: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1), + weights: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -8), + bias: ("TENSOR_INT32", 0.25, 0), + out0: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), +}) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [2, 32, 16]} +output0 = {out0: # output 0 + [8, 68, 36]} + +# Instantiate an example +Example((input0, output0)).AddVariations(quant8_signed_mult_gt_1, includeDefault=False) + +####################################################### +# zero-sized input + +# 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, 3}") +zero_sized = Internal("featureMap", "TENSOR_FLOAT32", "{0, 2, 2, 3}") +model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized) + +# FULLY_CONNECTED op with numBatches = 0. +w = Parameter("weights", "TENSOR_FLOAT32", "{1, 3}", [1, 2, 3]) # weights +b = Parameter("bias", "TENSOR_FLOAT32", "{1}", [1]) # bias +o3 = Output("out", "TENSOR_FLOAT32", "{0, 1}") # out +model = model.Operation("FULLY_CONNECTED", zero_sized, w, b, 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), + w: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0), + b: ("TENSOR_INT32", 0.01, 0), + o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0) +}) + +Example({ + i1: [1, 2, 3], + o1: [], + o2: [], + o3: [], +}).AddNchw(i1, zero_sized, layout).AddVariations(quant8_signed, includeDefault=False) |