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author | Lev Proleev <levp@google.com> | 2019-12-19 15:18:50 +0000 |
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committer | Lev Proleev <levp@google.com> | 2020-01-03 16:01:32 +0000 |
commit | f40dc3a495a069d70d95187c7e2eb68e22a514bd (patch) | |
tree | 5ce61595f8fad9ead7741652c2b26f1f8ed63e5d /nn/runtime/test/specs/V1_3/depthwise_conv2d_quant8_signed.mod.py | |
parent | 21d5907e55f6ed8a3e08c240efb9cf5d4a644fd8 (diff) | |
download | ml-f40dc3a495a069d70d95187c7e2eb68e22a514bd.tar.gz |
Add quant8 signed generated tests
The tests are written semi-automatically by joining all of the 1.0-1.2
tests with TENSOR_QUANT8_ASYMM operands and converting them to
TENSOR_QUANT8_ASYMM_SIGNED.
Also:
* Fix implementation of CONCATENATION op for zero-sized tensors
* Add support for TENSOR_QUANT8_ASYMM_SIGNED in test generator
Bug: 136735770
Test: NNTest_static and VtsHalNeuralnetworksV1_3TargetTest
Change-Id: I250dbe85684aa594892494eb53e6312c1cacb6f3
Diffstat (limited to 'nn/runtime/test/specs/V1_3/depthwise_conv2d_quant8_signed.mod.py')
-rw-r--r-- | nn/runtime/test/specs/V1_3/depthwise_conv2d_quant8_signed.mod.py | 526 |
1 files changed, 526 insertions, 0 deletions
diff --git a/nn/runtime/test/specs/V1_3/depthwise_conv2d_quant8_signed.mod.py b/nn/runtime/test/specs/V1_3/depthwise_conv2d_quant8_signed.mod.py new file mode 100644 index 000000000..ed7cb0e5f --- /dev/null +++ b/nn/runtime/test/specs/V1_3/depthwise_conv2d_quant8_signed.mod.py @@ -0,0 +1,526 @@ +# +# 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. +# + +layout = BoolScalar("layout", False) # NHWC + +# dilation set to 1 (default) +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") +f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0., 0., 0., .25, .1, 0., 0.]) +b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) +o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") +Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout, 1, 1).To(o1) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128), + b1: ("TENSOR_INT32", 0.005, 0), + o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128) +}) + +# Instantiate an example +example = Example({ + i1: [10, 21, 10, 22, 10, 23, + 10, 24, 10, 25, 10, 26, + 10, 27, 10, 28, 10, 29], + o1: [11, 3, 7.2, 10.6, + 11, 3, 7.4, 10.9, + 11, 3, 7.8, 11.5, + 11, 3, 8.0, 11.8] +}).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# dilation set to 2 +i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") +f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]) +b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [0,0,0,0]) +o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") +Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 2, 0, layout, 2, 2).To(o2) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128), + b2: ("TENSOR_INT32", 0.0625, 0), + o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128) +}) + +# Instantiate an example +example = Example({ + i2: [0, 0, 0, 0, 0, 0, 0, 0, + 0, 0, 0, 1, 1, 0, 0, 0, + 0, 0, 0, 1, 1, 0, 0, 0, + 0, 0, 0, 0, 0, 0, 0, 0,], + o2: [13, 14, 0, 0, + 0, 0, 11, 12, + 5, 6, 0, 0, + 0, 0, 3, 4] +}).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# same as test 1 but with implicit padding +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") +f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0., 0., 0., .25, .1, 0., 0.]) +b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) +o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") +Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 2, 1, 1, 2, 0, layout, 1, 1).To(o1) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128), + b1: ("TENSOR_INT32", 0.005, 0), + o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128) +}) + +# Instantiate an example +example = Example({ + i1: [10, 21, 10, 22, 10, 23, + 10, 24, 10, 25, 10, 26, + 10, 27, 10, 28, 10, 29], + o1: [11, 3, 7.2, 10.6, + 11, 3, 7.4, 10.9, + 11, 3, 7.8, 11.5, + 11, 3, 8.0, 11.8] +}, name="valid_padding").AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# same as test 2 but with implicit padding +i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") +f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]) +b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [0,0,0,0]) +o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") +Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 2, 1, 1, 2, 0, layout, 2, 2).To(o2) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128), + b2: ("TENSOR_INT32", 0.05, 0), + o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128) +}) + +# Instantiate an example +example = Example({ + i2: [0, 0, 0, 0, 0, 0, 0, 0, + 0, 0, 0, 1, 1, 0, 0, 0, + 0, 0, 0, 1, 1, 0, 0, 0, + 0, 0, 0, 0, 0, 0, 0, 0,], + o2: [13, 14, 0, 0, + 0, 0, 11, 12, + 5, 6, 0, 0, + 0, 0, 3, 4] +}, name="valid_padding").AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# dilation set to 3, padding SAME, stride 2 +i2 = Input("op1", "TENSOR_FLOAT32", "{1, 6, 6, 1}") +f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) +b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) +o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") +Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 1, 2, 2, 1, 0, layout, 3, 3).To(o2) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128), + b2: ("TENSOR_INT32", 0.0625, 0), + o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128) +}) + +# Instantiate an example +example = Example({ + i2: [0, 0, 0, 0, 0, 0, + 0, 0, 0, 0, 0, 0, + 0, 0, 1, 1, 0, 0, + 0, 0, 1, 1, 0, 0, + 0, 0, 0, 0, 0, 0, + 0, 0, 0, 0, 0, 0], + o2: [4, 0, 3, + 0, 0, 0, + 2, 0, 1] +}, name="same_padding_stride_2").AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# Same scales, zeroPoint = 0 +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +f1 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 2}", + [2, 4, 2, 0, 2, 2, 2, 0], + extraParams = SymmPerChannelQuantParams(channelDim=3, scales=[0.5, 0.5])) +b1 = Parameter("op3", "TENSOR_INT32", "{2}", [0, 0]) +o1 = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1, 1, 2}, 1.f, -128") +Model("same").Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 1, 0).To(o1) + +# Instantiate an example +Example({ + i1: [-124, -112, -124, -96, -124, -64, -124, 0], + o1: [-120, -80], +}) + +####################################################### + +# Different scales, zeroPoint=128 +i2 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 3, 3, 2}, 0.5f, 0") +f2 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 4}", + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], + extraParams = SymmPerChannelQuantParams(channelDim=3, scales=[1.0, 0.5, 1.0, 0.5])) +b2 = Parameter("op3", "TENSOR_INT32", "{4}", [4, 4, 4, 4]) +o2 = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 4}, 1.f, 0") +Model("different").Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 2, 0).To(o2) + +# Instantiate an example +Example({ + i2: [1, 2] * 9, + o2: [4, 2, 6, 3, 4, 2, 6, 3, + 4, 2, 6, 3, 4, 2, 6, 3], +}) + +####################################################### + +layout = BoolScalar("layout", False) # NHWC + +# With layout param +i3 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 3, 3, 2}, 0.5f, 0") +f3 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 4}", + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], + extraParams = SymmPerChannelQuantParams(channelDim=3, scales=[1.0, 0.5, 1.0, 0.5])) +b3 = Parameter("op3", "TENSOR_INT32", "{4}", [4, 4, 4, 4]) +o3 = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 4}, 1.f, 0") +Model("layout").Operation("DEPTHWISE_CONV_2D", i3, f3, b3, 0, 0, 0, 0, 1, 1, 2, 0, layout).To(o3) + +# Instantiate an example +Example({ + i3: [1, 2] * 9, + o3: [4, 2, 6, 3, 4, 2, 6, 3, + 4, 2, 6, 3, 4, 2, 6, 3], +}).AddNchw(i3, o3, layout) + +####################################################### + +model = Model() +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 3, 2, 2}, 0.5f, -1") +f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 4}, 0.5f, -1", [1, 3, 5, 7, -19, 19, -23, 23, 9, 11, 13, 15, 25, -29, 29, -33]) +b1 = Parameter("op3", "TENSOR_INT32", "{4}, 0.25f, 0", [4, 8, 12, 16]) +pad_valid = Int32Scalar("pad_valid", 2) +act_none = Int32Scalar("act_none", 0) +stride = Int32Scalar("stride", 1) +cm = Int32Scalar("channelMultiplier", 2) +output = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 1, 4}, 1.f, -1") + +model = model.Operation("DEPTHWISE_CONV_2D", + i1, f1, b1, + pad_valid, + stride, stride, + cm, act_none).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 3, 13, 15, + 5, 7, 17, 19, + 9, 11, 21, 23]} +# (i1 (depthconv) f1) +output0 = {output: # output 0 + [70, -35, 98, -21, + 90, -27, 126, -5]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128", + [-126, -124, -126, -128, -126, -126, -126, -128]) +b1 = Parameter("op3", "TENSOR_INT32", "{2}, 0.25f, 0", [0, 0]) +pad0 = Int32Scalar("pad0", 0) +act = Int32Scalar("act", 0) +stride = Int32Scalar("stride", 1) +cm = Int32Scalar("channelMultiplier", 1) +output = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1, 1, 2}, 1.f, -128") + +model = model.Operation("DEPTHWISE_CONV_2D", + i1, f1, b1, + pad0, pad0, pad0, pad0, + stride, stride, + cm, act).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [-124, -112, -124, -96, -124, -64, -124, 0]} +# (i1 (depthconv) f1) +output0 = {output: # output 0 + [-120, -80]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +f1 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +b1 = Input("op3", "TENSOR_INT32", "{2}, 0.25f, 0") +pad0 = Int32Scalar("pad0", 0) +act = Int32Scalar("act", 0) +stride = Int32Scalar("stride", 1) +cm = Int32Scalar("channelMultiplier", 1) +output = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 1, 1, 2}, 1.f, -128") + +model = model.Operation("DEPTHWISE_CONV_2D", + i1, f1, b1, + pad0, pad0, pad0, pad0, + stride, stride, + cm, act).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [-124, -112, -124, -96, -124, -64, -124, 0], + f1: + [-126, -124, -126, -128, -126, -126, -126, -128], + b1: + [0, 0]} +# (i1 (depthconv) f1) +output0 = {output: # output 0 + [-120, -80]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128", + [-126, -124, -126, -128, -126, -126, -126, -128]) +b1 = Parameter("op3", "TENSOR_INT32", "{2}, 0.25f, 0", [0, 0]) +pad0 = Int32Scalar("pad0", 0) +act = Int32Scalar("act", 0) +stride = Int32Scalar("stride", 1) +cm = Int32Scalar("channelMultiplier", 1) +output = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1,1,1,2}, 1.f, -128") + +model = model.Operation("DEPTHWISE_CONV_2D", + i1, f1, b1, + pad0, pad0, pad0, pad0, + stride, stride, + cm, act).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [-124, -112, -124, -96, -124, -64, -124, 0]} +# (i1 (depthconv) f1) +output0 = {output: # output 0 + [-120, -80]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +model = Model() +i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +f1 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 2}, 0.5f, -128") +b1 = Input("op3", "TENSOR_INT32", "{2}, 0.25f, 0") +pad0 = Int32Scalar("pad0", 0) +act = Int32Scalar("act", 0) +stride = Int32Scalar("stride", 1) +cm = Int32Scalar("channelMultiplier", 1) +output = Output("op4", "TENSOR_QUANT8_ASYMM_SIGNED", "{1,1,1,2}, 1.f, -128") + +model = model.Operation("DEPTHWISE_CONV_2D", + i1, f1, b1, + pad0, pad0, pad0, pad0, + stride, stride, + cm, act).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [-124, -112, -124, -96, -124, -64, -124, 0], + f1: + [-126, -124, -126, -128, -126, -126, -126, -128], + b1: + [0, 0]} +# (i1 (depthconv) f1) +output0 = {output: # output 0 + [-120, -80]} + +# Instantiate an example +Example((input0, output0)) + +####################################################### + +layout = BoolScalar("layout", False) # NHWC + +# DEPTHWISE_CONV2D_NCHW, pad = 0, stride = 1, cm = 2, act = none +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") +f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0., 0., 0., .25, .1, 0., 0.]) +b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) +o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") +Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout).To(o1) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128), + b1: ("TENSOR_INT32", 0.005, 0), + o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128) +}) +channelquant8_signed = DataTypeConverter().Identify({ + i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f1: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[0.01, 0.005, 0.01, 0.005])), + b1: ("TENSOR_INT32", 0.0, 0, SymmPerChannelQuantParams(channelDim=0, scales=[0.005, 0.0025, 0.005, 0.0025], hide=True)), + o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128) +}) +channelQuant8_mult_gt_1 = DataTypeConverter().Identify({ + i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128), + f1: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[0.01, 0.005, 0.01, 0.005])), + b1: ("TENSOR_INT32", 0.0, 0, SymmPerChannelQuantParams(channelDim=0, scales=[0.005, 0.0025, 0.005, 0.0025], hide=True)), + o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.0001, -128) +}) + +# Instantiate an example +example = Example({ + i1: [10, 21, 10, 22, 10, 23, + 10, 24, 10, 25, 10, 26, + 10, 27, 10, 28, 10, 29], + o1: [11, 3, 7.2, 10.6, + 11, 3, 7.4, 10.9, + 11, 3, 7.8, 11.5, + 11, 3, 8.0, 11.8] +}).AddNchw(i1, o1, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# DEPTHWISE_CONV2D_NCHW_2, pad = valid, stride = 1, cm = 2, act = none +i2 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 2, 2}") +f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1, 2, 3, 4, -9, 10, -11, 12, 5, 6, 7, 8, 13, -14, 15, -16]) +b2 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4]) +o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 1, 4}") +Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 2, 1, 1, 2, 0, layout).To(o2) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0), + f2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0), + b2: ("TENSOR_INT32", 0.25, 0), + o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0, -28) +}) +channelquant8_signed = DataTypeConverter().Identify({ + i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0), + f2: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[0.5, 0.25, 0.5, 0.25])), + b2: ("TENSOR_INT32", 0.0, 0, SymmPerChannelQuantParams(channelDim=0, scales=[0.25, 0.125, 0.25, 0.125], hide=True)), + o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0, -28) +}) + +# Instantiate an example +example = Example({ + i2: [1, 2, 7, 8, 3, 4, 9, 10, 5, 6, 11, 12], + o2: [71, -34, 99, -20, 91, -26, 127, -4] +}).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# DEPTHWISE_CONV2D_NCHW_LARGE, pad = 0, stride = 1, cm = 1, act = none +i3 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 2}") +f3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}", [.25, 0, .25, 1, .25, 0, .25, 1]) +b3 = Parameter("op3", "TENSOR_FLOAT32", "{2}", [100, 200]) +o3 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 2}") +Model("large").Operation("DEPTHWISE_CONV_2D", i3, f3, b3, 0, 0, 0, 0, 1, 1, 1, 0, layout).To(o3) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -28), + f3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, 0), + b3: ("TENSOR_INT32", 0.0625, 0), + o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.0, 0) +}) +channelquant8_signed = DataTypeConverter().Identify({ + i3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0), + f3: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[0.125, 0.25])), + b3: ("TENSOR_INT32", 0.0, 0, SymmPerChannelQuantParams(channelDim=0, scales=[0.0625, 0.125], hide=True)), + o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.0, 0) +}) + +# Instantiate an example +example = Example({ + i3: [10, 21, 10, 22, 10, 23, 10, 24], + o3: [110, 246] +}).AddNchw(i3, o3, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# DEPTHWISE_CONV2D_NCHW_LARGE, pad = 0, stride = 1, cm = 1, act = none +i4 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") +f4 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, 10, 50, .25, 1, 20, 50, .25, 0, 30, 50, .25, 1, 40, 50]) +b4 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [6000, 7000, 8000, 9000]) +o4 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 4}") +Model("large").Operation("DEPTHWISE_CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 1, 0, layout).To(o4) + +# Additional data type +quant8_signed = DataTypeConverter().Identify({ + i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0), + f4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -128), + b4: ("TENSOR_INT32", 0.125, 0), + o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 50.0, -128) +}) +channelquant8_signed = DataTypeConverter().Identify({ + i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0), + f4: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[1.0, 2.0, 1.0, 1.0])), + b4: ("TENSOR_INT32", 0.0, 0, SymmPerChannelQuantParams(channelDim=0, scales=[0.5, 1.0, 0.5, 0.5], hide=True)), + o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 50.0, -128) +}) + +# Instantiate an example +example = Example({ + i4: [10, 21, 10, 0, + 10, 22, 20, 0, + 10, 23, 30, 0, + 10, 24, 40, 0], + o4: [6010, 7046, 11000, 9000] +}).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False) + +####################################################### + +# quantized with scale product greater than output scale +input_scale = 256.5 / 255 +input_zero_point = -1 +filter_scale = 256.5 / 255 +filter_zero_point = 0 +i9 = Input("op1", + ("TENSOR_QUANT8_ASYMM_SIGNED", [1, 3, 2, 2], input_scale, input_zero_point)) +f9 = Parameter( + "op2", + ("TENSOR_QUANT8_ASYMM_SIGNED", [1, 2, 2, 4], filter_scale, filter_zero_point), [ + 1, 2, 3, 4, -9, 10, -11, 12, 5, 6, 7, 8, 13, -14, + 15, -16 + ]) +b9 = Parameter("op3", ("TENSOR_INT32", [4], input_scale * filter_scale, 0), + [2, 4, 6, 8]) +o9 = Output("op4", ("TENSOR_QUANT8_ASYMM_SIGNED", [1, 2, 1, 4], 1.0, -1)) +model9 = Model("quant_output_multiplier_gt_1").Operation("DEPTHWISE_CONV_2D", i9, f9, b9, 2, 1, 1, 2, + 0).To(o9) + +# Instantiate an example +example = Example({ + i9: [1, 3, 13, 15, 5, 7, 17, 19, 9, 11, 21, 23], + o9: [127, -70, 127, -41, 127, -54, 127, -9] +}, model=model9) |