// META: title=test WebNN API convTranspose2d operation
// META: global=window,dedicatedworker
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils.js
// META: timeout=long
'use strict';
// https://www.w3.org/TR/webnn/#api-mlgraphbuilder-convtranspose2d
// Compute a 2-D transposed convolution given 4-D input and filter tensors.
//
// enum MLConvTranspose2dFilterOperandLayout {
// "iohw",
// "hwoi",
// "ohwi"
// };
//
// dictionary MLConvTranspose2dOptions {
// sequence<[EnforceRange] unsigned long> padding;
// sequence<[EnforceRange] unsigned long> strides;
// sequence<[EnforceRange] unsigned long> dilations;
// sequence<[EnforceRange] unsigned long> outputPadding;
// sequence<[EnforceRange] unsigned long> outputSizes;
// [EnforceRange] unsigned long groups = 1;
// MLInputOperandLayout inputLayout = "nchw";
// MLConvTranspose2dFilterOperandLayout filterLayout = "iohw";
// MLOperand bias;
// };
//
// MLOperand convTranspose2d(
// MLOperand input, MLOperand filter,
// optional MLConvTranspose2dOptions options = {});
const convTranspose2dTests = [
{
'name':
'convTranspose2d float32 4D both input and filter non-constant tensors default options',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.5872158408164978, 0.6077792048454285, 0.017289165407419205,
0.2614607512950897
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.3292713165283203, 0.5866857171058655, 0.29701370000839233,
0.0033378428779542446
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'}
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'}, {'filter': 'convTranspose2dFilter'}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.1933533400297165, 0.5446354150772095, 0.3565753698348999,
0.18010397255420685, 0.2787136137485504, 0.15542395412921906,
0.0051351189613342285, 0.07771513611078262, 0.0008727149106562138
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D both input and filter constant tensors default options',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.5872158408164978, 0.6077792048454285, 0.017289165407419205,
0.2614607512950897
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'},
'constant': true
},
'convTranspose2dFilter': {
'data': [
0.3292713165283203, 0.5866857171058655, 0.29701370000839233,
0.0033378428779542446
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'}, {'filter': 'convTranspose2dFilter'}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.1933533400297165, 0.5446354150772095, 0.3565753698348999,
0.18010397255420685, 0.2787136137485504, 0.15542395412921906,
0.0051351189613342285, 0.07771513611078262, 0.0008727149106562138
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors default options',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.5872158408164978, 0.6077792048454285, 0.017289165407419205,
0.2614607512950897
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.3292713165283203, 0.5866857171058655, 0.29701370000839233,
0.0033378428779542446
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'}, {'filter': 'convTranspose2dFilter'}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.1933533400297165, 0.5446354150772095, 0.3565753698348999,
0.18010397255420685, 0.2787136137485504, 0.15542395412921906,
0.0051351189613342285, 0.07771513611078262, 0.0008727149106562138
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.groups',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.8161798119544983, 0.5442776083946228, 0.7910669445991516,
0.36564111709594727, 0.25429198145866394, 0.20815767347812653,
0.7023073434829712, 0.5734469890594482
],
'descriptor': {'dimensions': [1, 2, 2, 2], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.09232201427221298, 0.31896016001701355, 0.5445202589035034,
0.6582807898521423, 0.9634373188018799, 0.012118860147893429,
0.9230011701583862, 0.4781944155693054
],
'descriptor': {'dimensions': [2, 1, 2, 2], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'}, {'options': {'groups': 2}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.07535136491060257, 0.3105776607990265, 0.1736028790473938,
0.5174593329429626, 1.1197212934494019, 0.4749124348163605,
0.4307519793510437, 0.7198431491851807, 0.24069452285766602,
0.2449943870306015, 0.20362859964370728, 0.002522633643820882,
0.9113409519195557, 0.8747221827507019, 0.10648936033248901,
0.6482304930686951, 0.865131676197052, 0.2742191553115845
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.groups=2 options.strides=[2, 2]',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.8161798119544983, 0.5442776083946228, 0.7910669445991516,
0.36564111709594727, 0.25429198145866394, 0.20815767347812653,
0.7023073434829712, 0.5734469890594482
],
'descriptor': {'dimensions': [1, 2, 2, 2], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.09232201427221298, 0.31896016001701355, 0.5445202589035034,
0.6582807898521423, 0.9634373188018799, 0.012118860147893429,
0.9230011701583862, 0.4781944155693054
],
'descriptor': {'dimensions': [2, 1, 2, 2], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'strides': [2, 2], 'groups': 2}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.07535136491060257, 0.26032882928848267, 0.050248805433511734,
0.1736028790473938, 0.44442644715309143, 0.537275493144989,
0.29637017846107483, 0.3582874834537506, 0.07303289324045181,
0.2523188292980194, 0.03375672549009323, 0.11662495136260986,
0.4307519793510437, 0.5207441449165344, 0.19909898936748505,
0.24069452285766602, 0.2449943870306015, 0.0030817289371043444,
0.20054687559604645, 0.002522633643820882, 0.23471179604530334,
0.12160100787878036, 0.19212977588176727, 0.09953983873128891,
0.6766291260719299, 0.008511164225637913, 0.5524802207946777,
0.00694952392950654, 0.6482304930686951, 0.3358394503593445,
0.5292922258377075, 0.2742191553115845
],
'descriptor': {'dimensions': [1, 2, 4, 4], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.padding',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.5872158408164978, 0.6077792048454285, 0.017289165407419205,
0.2614607512950897
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.3292713165283203, 0.5866857171058655, 0.29701370000839233,
0.0033378428779542446
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'padding': [1, 1, 1, 1]}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [0.2787136137485504],
'descriptor': {'dimensions': [1, 1, 1, 1], 'dataType': 'float32'}
}
}
}
},
{
'name': 'convTranspose2d options.padding is the same upper padding',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
'descriptor': {'dimensions': [1, 3, 3, 1], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
'descriptor': {'dimensions': [2, 3, 3, 1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'}, {
'options': {
'outputSizes': [6, 6],
'groups': 1,
'strides': [2, 2],
'dilations': [1, 1],
'padding': [0, 1, 0, 1],
'filterLayout': 'ohwi',
'inputLayout': 'nhwc'
}
}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.5, 0.5, 0.5, 0.5, 1, 1, 0.5, 0.5, 1, 1, 0.5, 0.5,
0.5, 0.5, 0.5, 0.5, 1, 1, 0.5, 0.5, 1, 1, 0.5, 0.5,
1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1,
0.5, 0.5, 0.5, 0.5, 1, 1, 0.5, 0.5, 1, 1, 0.5, 0.5,
1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1,
0.5, 0.5, 0.5, 0.5, 1, 1, 0.5, 0.5, 1, 1, 0.5, 0.5
],
'descriptor': {'dimensions': [1, 6, 6, 2], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.strides',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'}, {'options': {'strides': [3, 2]}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.03513447195291519, 0.6485382318496704,
0.4458966553211212, 1.015426516532898, 0.4092629551887512,
0.4157154858112335, 0.0469902828335762, 0.0066622416488826275,
0.6519761085510254, 0.08455146849155426, 1.2531912326812744,
0.07760494202375412, 0.6478374600410461, 0.018416915088891983,
0.04900681599974632, 0.27412328124046326, 0.6219525337219238,
0.7271442413330078, 0.5708546042442322, 0.4705001711845398,
0.3327140808105469, 0.24207575619220734, 0.5793426632881165,
0.24261142313480377, 1.0615012645721436, 0.593023955821991,
0.6023737192153931, 0.32376202940940857, 0.04590269923210144,
0.7076690793037415, 0.0460042729973793, 1.177173137664795,
0.11244992911815643, 0.9387195110321045, 0.12689214944839478,
0.3376559019088745, 0.40547001361846924, 0.3384030759334564,
0.5897663235664368, 0.8271709680557251, 0.6817569732666016,
0.08246752619743347, 0.06000163406133652, 0.8564596176147461,
0.5787978172302246, 1.1360399723052979, 0.39879822731018066,
0.4050857424736023, 0.0802486464381218, 0.011377583257853985,
0.8690866827964783, 0.1097523421049118, 1.4495694637298584,
0.0756206065416336, 0.6312723755836487, 0.03145187348127365,
0.08369242399930954, 0.37237587571144104, 0.8073278069496155,
0.8744456768035889, 0.556257963180542, 0.45846959948539734,
0.05494653806090355, 0.0034586030524224043, 0.7153855562210083,
0.04389362782239914, 0.869132936000824, 0.04028744250535965,
0.21026825904846191, 0.04203145205974579, 0.02203426882624626,
0.5411697030067444, 0.2796400785446167, 0.5878635048866272,
0.25666558742523193, 0.0901883915066719, 0.015911730006337166,
0.023744819685816765, 0.21005792915821075, 0.30134889483451843,
0.2883978486061096, 0.27659088373184204, 0.09458412230014801,
0.3785804808139801, 0.02382970042526722, 0.5037901997566223,
0.0238824300467968, 1.0520728826522827, 0.05837669596076012,
0.3046796917915344, 0.2895958125591278, 0.15181563794612885,
0.3435823321342468, 0.15215156972408295, 0.7628997564315796,
0.37190964818000793, 0.13068340718746185, 0.1096314787864685,
0.16360129415988922, 0.16581982374191284, 0.16396330296993256,
0.3246387541294098, 0.400781512260437, 0.13705284893512726,
0.09383610635995865, 0.00590650225058198, 0.9360047578811646,
0.05697628855705261, 0.9210482239723206, 0.03925730288028717,
0.20489174127578735, 0.07178010046482086, 0.03762948885560036,
0.7056396007537842, 0.36298784613609314, 0.6046316623687744,
0.2501027286052704, 0.08788229525089264, 0.027173593640327454,
0.04055071249604225, 0.27599334716796875, 0.3911670744419098,
0.3143731355667114, 0.26951852440834045, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 2, 9, 7], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.dilations',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.3194596767425537, 0.9762163758277893, 0.4131408631801605,
0.47982943058013916, 0.76741623878479, 0.9083173871040344,
0.6205142140388489, 0.6580719947814941, 0.6553052067756653
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.6835425496101379, 0.9641214609146118, 0.8272836804389954,
0.5771222710609436
],
'descriptor': {'dimensions': [1, 1, 2, 2], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'dilations': [2, 2]}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.21836428344249725, 0.6672854423522949, 0.590397298336029,
0.9411911368370056, 0.39831796288490295, 0.3279838263988495,
0.5245616436004639, 1.0834873914718628, 0.7398824691772461,
0.8757283091545105, 0.6884316205978394, 1.2574280500411987,
1.5723320245742798, 1.1978574991226196, 0.8702266216278076,
0.39695504307746887, 0.6348709464073181, 1.0283564329147339,
0.44289299845695496, 0.5242102146148682, 0.5133413076400757,
0.5444121956825256, 0.9002358913421631, 0.37978801131248474,
0.3781912326812744
],
'descriptor': {'dimensions': [1, 1, 5, 5], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.outputPadding',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'strides': [3, 2], 'outputPadding': [1, 1]}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196,
0.03513447195291519,
0.6485382318496704,
0.4458966553211212,
1.015426516532898,
0.4092629551887512,
0.4157154858112335,
0,
0.0469902828335762,
0.0066622416488826275,
0.6519761085510254,
0.08455146849155426,
1.2531912326812744,
0.07760494202375412,
0.6478374600410461,
0,
0.018416915088891983,
0.04900681599974632,
0.27412328124046326,
0.6219525337219238,
0.7271442413330078,
0.5708546042442322,
0.4705001711845398,
0,
0.3327140808105469,
0.24207575619220734,
0.5793426632881165,
0.24261142313480377,
1.0615012645721436,
0.593023955821991,
0.6023737192153931,
0,
0.32376202940940857,
0.04590269923210144,
0.7076690793037415,
0.0460042729973793,
1.177173137664795,
0.11244992911815643,
0.9387195110321045,
0,
0.12689214944839478,
0.3376559019088745,
0.40547001361846924,
0.3384030759334564,
0.5897663235664368,
0.8271709680557251,
0.6817569732666016,
0,
0.08246752619743347,
0.06000163406133652,
0.8564596176147461,
0.5787978172302246,
1.1360399723052979,
0.39879822731018066,
0.4050857424736023,
0,
0.0802486464381218,
0.011377583257853985,
0.8690866827964783,
0.1097523421049118,
1.4495694637298584,
0.0756206065416336,
0.6312723755836487,
0,
0.03145187348127365,
0.08369242399930954,
0.37237587571144104,
0.8073278069496155,
0.8744456768035889,
0.556257963180542,
0.45846959948539734,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0.05494653806090355,
0.0034586030524224043,
0.7153855562210083,
0.04389362782239914,
0.869132936000824,
0.04028744250535965,
0.21026825904846191,
0,
0.04203145205974579,
0.02203426882624626,
0.5411697030067444,
0.2796400785446167,
0.5878635048866272,
0.25666558742523193,
0.0901883915066719,
0,
0.015911730006337166,
0.023744819685816765,
0.21005792915821075,
0.30134889483451843,
0.2883978486061096,
0.27659088373184204,
0.09458412230014801,
0,
0.3785804808139801,
0.02382970042526722,
0.5037901997566223,
0.0238824300467968,
1.0520728826522827,
0.05837669596076012,
0.3046796917915344,
0,
0.2895958125591278,
0.15181563794612885,
0.3435823321342468,
0.15215156972408295,
0.7628997564315796,
0.37190964818000793,
0.13068340718746185,
0,
0.1096314787864685,
0.16360129415988922,
0.16581982374191284,
0.16396330296993256,
0.3246387541294098,
0.400781512260437,
0.13705284893512726,
0,
0.09383610635995865,
0.00590650225058198,
0.9360047578811646,
0.05697628855705261,
0.9210482239723206,
0.03925730288028717,
0.20489174127578735,
0,
0.07178010046482086,
0.03762948885560036,
0.7056396007537842,
0.36298784613609314,
0.6046316623687744,
0.2501027286052704,
0.08788229525089264,
0,
0.027173593640327454,
0.04055071249604225,
0.27599334716796875,
0.3911670744419098,
0.3143731355667114,
0.26951852440834045,
0.09216563403606415,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
'descriptor': {'dimensions': [1, 2, 10, 8], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.outputSizes',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'strides': [3, 2], 'outputSizes': [10, 8]}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196,
0.03513447195291519,
0.6485382318496704,
0.4458966553211212,
1.015426516532898,
0.4092629551887512,
0.4157154858112335,
0,
0.0469902828335762,
0.0066622416488826275,
0.6519761085510254,
0.08455146849155426,
1.2531912326812744,
0.07760494202375412,
0.6478374600410461,
0,
0.018416915088891983,
0.04900681599974632,
0.27412328124046326,
0.6219525337219238,
0.7271442413330078,
0.5708546042442322,
0.4705001711845398,
0,
0.3327140808105469,
0.24207575619220734,
0.5793426632881165,
0.24261142313480377,
1.0615012645721436,
0.593023955821991,
0.6023737192153931,
0,
0.32376202940940857,
0.04590269923210144,
0.7076690793037415,
0.0460042729973793,
1.177173137664795,
0.11244992911815643,
0.9387195110321045,
0,
0.12689214944839478,
0.3376559019088745,
0.40547001361846924,
0.3384030759334564,
0.5897663235664368,
0.8271709680557251,
0.6817569732666016,
0,
0.08246752619743347,
0.06000163406133652,
0.8564596176147461,
0.5787978172302246,
1.1360399723052979,
0.39879822731018066,
0.4050857424736023,
0,
0.0802486464381218,
0.011377583257853985,
0.8690866827964783,
0.1097523421049118,
1.4495694637298584,
0.0756206065416336,
0.6312723755836487,
0,
0.03145187348127365,
0.08369242399930954,
0.37237587571144104,
0.8073278069496155,
0.8744456768035889,
0.556257963180542,
0.45846959948539734,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0.05494653806090355,
0.0034586030524224043,
0.7153855562210083,
0.04389362782239914,
0.869132936000824,
0.04028744250535965,
0.21026825904846191,
0,
0.04203145205974579,
0.02203426882624626,
0.5411697030067444,
0.2796400785446167,
0.5878635048866272,
0.25666558742523193,
0.0901883915066719,
0,
0.015911730006337166,
0.023744819685816765,
0.21005792915821075,
0.30134889483451843,
0.2883978486061096,
0.27659088373184204,
0.09458412230014801,
0,
0.3785804808139801,
0.02382970042526722,
0.5037901997566223,
0.0238824300467968,
1.0520728826522827,
0.05837669596076012,
0.3046796917915344,
0,
0.2895958125591278,
0.15181563794612885,
0.3435823321342468,
0.15215156972408295,
0.7628997564315796,
0.37190964818000793,
0.13068340718746185,
0,
0.1096314787864685,
0.16360129415988922,
0.16581982374191284,
0.16396330296993256,
0.3246387541294098,
0.400781512260437,
0.13705284893512726,
0,
0.09383610635995865,
0.00590650225058198,
0.9360047578811646,
0.05697628855705261,
0.9210482239723206,
0.03925730288028717,
0.20489174127578735,
0,
0.07178010046482086,
0.03762948885560036,
0.7056396007537842,
0.36298784613609314,
0.6046316623687744,
0.2501027286052704,
0.08788229525089264,
0,
0.027173593640327454,
0.04055071249604225,
0.27599334716796875,
0.3911670744419098,
0.3143731355667114,
0.26951852440834045,
0.09216563403606415,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
'descriptor': {'dimensions': [1, 2, 10, 8], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.inputLayout=nchw',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'inputLayout': 'nchw'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.6479843258857727, 1.0440847873687744,
0.8621897101402283, 0.4157154858112335, 0.3797043561935425,
1.1785486936569214, 1.9911006689071655, 1.6228916645050049,
1.2502111196517944, 0.4246464669704437, 1.5086332559585571,
3.287064790725708, 2.5666797161102295, 1.8143054246902466,
0.20714078843593597, 1.2503143548965454, 1.6656538248062134,
2.097904920578003, 1.313029408454895, 0.03145187348127365,
0.38708874583244324, 1.0853508710861206, 1.2216601371765137,
0.45846959948539734, 0.05494653806090355, 0.7007930278778076,
0.7019880414009094, 0.26937708258628845, 0.21026825904846191,
0.4206119179725647, 0.9587093591690063, 1.8526650667190552,
0.5379507541656494, 0.39486807584762573, 0.3993436396121979,
1.5788191556930542, 2.121230363845825, 1.141642689704895,
0.4301592707633972, 0.18141157925128937, 1.0035220384597778,
1.3417718410491943, 0.8345021605491638, 0.2249351441860199,
0.027173593640327454, 0.3026771545410156, 0.5856420397758484,
0.40328359603881836, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 2, 5, 5], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.inputLayout=nhwc',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 3, 3, 1], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'inputLayout': 'nhwc'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.05494653806090355, 0.6479843258857727,
0.7007930278778076, 1.0440847873687744, 0.7019880414009094,
0.8621897101402283, 0.26937708258628845, 0.4157154858112335,
0.21026825904846191, 0.3797043561935425, 0.4206119179725647,
1.1785486936569214, 0.9587093591690063, 1.9911006689071655,
1.8526650667190552, 1.6228916645050049, 0.5379507541656494,
1.2502111196517944, 0.39486807584762573, 0.4246464669704437,
0.3993436396121979, 1.5086332559585571, 1.5788191556930542,
3.287064790725708, 2.121230363845825, 2.5666797161102295,
1.141642689704895, 1.8143054246902466, 0.4301592707633972,
0.20714078843593597, 0.18141157925128937, 1.2503143548965454,
1.0035220384597778, 1.6656538248062134, 1.3417718410491943,
2.097904920578003, 0.8345021605491638, 1.313029408454895,
0.2249351441860199, 0.03145187348127365, 0.027173593640327454,
0.38708874583244324, 0.3026771545410156, 1.0853508710861206,
0.5856420397758484, 1.2216601371765137, 0.40328359603881836,
0.45846959948539734, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 5, 5, 2], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.filterLayout=iohw',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'filterLayout': 'iohw'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.6479843258857727, 1.0440847873687744,
0.8621897101402283, 0.4157154858112335, 0.3797043561935425,
1.1785486936569214, 1.9911006689071655, 1.6228916645050049,
1.2502111196517944, 0.4246464669704437, 1.5086332559585571,
3.287064790725708, 2.5666797161102295, 1.8143054246902466,
0.20714078843593597, 1.2503143548965454, 1.6656538248062134,
2.097904920578003, 1.313029408454895, 0.03145187348127365,
0.38708874583244324, 1.0853508710861206, 1.2216601371765137,
0.45846959948539734, 0.05494653806090355, 0.7007930278778076,
0.7019880414009094, 0.26937708258628845, 0.21026825904846191,
0.4206119179725647, 0.9587093591690063, 1.8526650667190552,
0.5379507541656494, 0.39486807584762573, 0.3993436396121979,
1.5788191556930542, 2.121230363845825, 1.141642689704895,
0.4301592707633972, 0.18141157925128937, 1.0035220384597778,
1.3417718410491943, 0.8345021605491638, 0.2249351441860199,
0.027173593640327454, 0.3026771545410156, 0.5856420397758484,
0.40328359603881836, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 2, 5, 5], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.filterLayout=hwoi',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.9801966547966003, 0.6267672777175903,
0.06169835478067398, 0.6366490125656128, 0.3220160901546478,
0.8382642269134521, 0.7498031854629517, 0.11884837597608566,
0.3930714726448059, 0.9921330213546753, 0.13811933994293213,
0.3285411298274994, 0.28385090827941895, 0.8742373585700989,
0.4235861301422119, 0.7205492258071899, 0.1448512077331543
],
'descriptor': {'dimensions': [3, 3, 2, 1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'filterLayout': 'hwoi'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.6479843258857727, 1.0440847873687744,
0.8621897101402283, 0.4157154858112335, 0.3797043561935425,
1.1785486936569214, 1.9911006689071655, 1.6228916645050049,
1.2502111196517944, 0.4246464669704437, 1.5086332559585571,
3.287064790725708, 2.5666797161102295, 1.8143054246902466,
0.20714078843593597, 1.2503143548965454, 1.6656538248062134,
2.097904920578003, 1.313029408454895, 0.03145187348127365,
0.38708874583244324, 1.0853508710861206, 1.2216601371765137,
0.45846959948539734, 0.05494653806090355, 0.7007930278778076,
0.7019880414009094, 0.26937708258628845, 0.21026825904846191,
0.4206119179725647, 0.9587093591690063, 1.8526650667190552,
0.5379507541656494, 0.39486807584762573, 0.3993436396121979,
1.5788191556930542, 2.121230363845825, 1.141642689704895,
0.4301592707633972, 0.18141157925128937, 1.0035220384597778,
1.3417718410491943, 0.8345021605491638, 0.2249351441860199,
0.027173593640327454, 0.3026771545410156, 0.5856420397758484,
0.40328359603881836, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 2, 5, 5], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.filterLayout=ohwi',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [2, 3, 3, 1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'filterLayout': 'ohwi'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.6479843258857727, 1.0440847873687744,
0.8621897101402283, 0.4157154858112335, 0.3797043561935425,
1.1785486936569214, 1.9911006689071655, 1.6228916645050049,
1.2502111196517944, 0.4246464669704437, 1.5086332559585571,
3.287064790725708, 2.5666797161102295, 1.8143054246902466,
0.20714078843593597, 1.2503143548965454, 1.6656538248062134,
2.097904920578003, 1.313029408454895, 0.03145187348127365,
0.38708874583244324, 1.0853508710861206, 1.2216601371765137,
0.45846959948539734, 0.05494653806090355, 0.7007930278778076,
0.7019880414009094, 0.26937708258628845, 0.21026825904846191,
0.4206119179725647, 0.9587093591690063, 1.8526650667190552,
0.5379507541656494, 0.39486807584762573, 0.3993436396121979,
1.5788191556930542, 2.121230363845825, 1.141642689704895,
0.4301592707633972, 0.18141157925128937, 1.0035220384597778,
1.3417718410491943, 0.8345021605491638, 0.2249351441860199,
0.027173593640327454, 0.3026771545410156, 0.5856420397758484,
0.40328359603881836, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 2, 5, 5], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.inputLayout=nhwc options.filterLayout=iohw',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 3, 3, 1], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [1, 2, 3, 3], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'inputLayout': 'nhwc', 'filterLayout': 'iohw'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.05494653806090355, 0.6479843258857727,
0.7007930278778076, 1.0440847873687744, 0.7019880414009094,
0.8621897101402283, 0.26937708258628845, 0.4157154858112335,
0.21026825904846191, 0.3797043561935425, 0.4206119179725647,
1.1785486936569214, 0.9587093591690063, 1.9911006689071655,
1.8526650667190552, 1.6228916645050049, 0.5379507541656494,
1.2502111196517944, 0.39486807584762573, 0.4246464669704437,
0.3993436396121979, 1.5086332559585571, 1.5788191556930542,
3.287064790725708, 2.121230363845825, 2.5666797161102295,
1.141642689704895, 1.8143054246902466, 0.4301592707633972,
0.20714078843593597, 0.18141157925128937, 1.2503143548965454,
1.0035220384597778, 1.6656538248062134, 1.3417718410491943,
2.097904920578003, 0.8345021605491638, 1.313029408454895,
0.2249351441860199, 0.03145187348127365, 0.027173593640327454,
0.38708874583244324, 0.3026771545410156, 1.0853508710861206,
0.5856420397758484, 1.2216601371765137, 0.40328359603881836,
0.45846959948539734, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 5, 5, 2], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.inputLayout=nhwc options.filterLayout=hwoi',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 3, 3, 1], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.9801966547966003, 0.6267672777175903,
0.06169835478067398, 0.6366490125656128, 0.3220160901546478,
0.8382642269134521, 0.7498031854629517, 0.11884837597608566,
0.3930714726448059, 0.9921330213546753, 0.13811933994293213,
0.3285411298274994, 0.28385090827941895, 0.8742373585700989,
0.4235861301422119, 0.7205492258071899, 0.1448512077331543
],
'descriptor': {'dimensions': [3, 3, 2, 1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'inputLayout': 'nhwc', 'filterLayout': 'hwoi'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.05494653806090355, 0.6479843258857727,
0.7007930278778076, 1.0440847873687744, 0.7019880414009094,
0.8621897101402283, 0.26937708258628845, 0.4157154858112335,
0.21026825904846191, 0.3797043561935425, 0.4206119179725647,
1.1785486936569214, 0.9587093591690063, 1.9911006689071655,
1.8526650667190552, 1.6228916645050049, 0.5379507541656494,
1.2502111196517944, 0.39486807584762573, 0.4246464669704437,
0.3993436396121979, 1.5086332559585571, 1.5788191556930542,
3.287064790725708, 2.121230363845825, 2.5666797161102295,
1.141642689704895, 1.8143054246902466, 0.4301592707633972,
0.20714078843593597, 0.18141157925128937, 1.2503143548965454,
1.0035220384597778, 1.6656538248062134, 1.3417718410491943,
2.097904920578003, 0.8345021605491638, 1.313029408454895,
0.2249351441860199, 0.03145187348127365, 0.027173593640327454,
0.38708874583244324, 0.3026771545410156, 1.0853508710861206,
0.5856420397758484, 1.2216601371765137, 0.40328359603881836,
0.45846959948539734, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 5, 5, 2], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors options.inputLayout=nhwc options.filterLayout=ohwi',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.05605664849281311, 0.7114229798316956, 0.6529743671417236,
0.38622909784317017, 0.3870837390422821, 0.9461629390716553,
0.09573192149400711, 0.9234652519226074, 0.636277973651886
],
'descriptor': {'dimensions': [1, 3, 3, 1], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.8614422678947449, 0.6267672777175903, 0.6366490125656128,
0.8382642269134521, 0.11884837597608566, 0.9921330213546753,
0.3285411298274994, 0.8742373585700989, 0.7205492258071899,
0.9801966547966003, 0.06169835478067398, 0.3220160901546478,
0.7498031854629517, 0.3930714726448059, 0.13811933994293213,
0.28385090827941895, 0.4235861301422119, 0.1448512077331543
],
'descriptor': {'dimensions': [2, 3, 3, 1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'inputLayout': 'nhwc', 'filterLayout': 'ohwi'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.04828956723213196, 0.05494653806090355, 0.6479843258857727,
0.7007930278778076, 1.0440847873687744, 0.7019880414009094,
0.8621897101402283, 0.26937708258628845, 0.4157154858112335,
0.21026825904846191, 0.3797043561935425, 0.4206119179725647,
1.1785486936569214, 0.9587093591690063, 1.9911006689071655,
1.8526650667190552, 1.6228916645050049, 0.5379507541656494,
1.2502111196517944, 0.39486807584762573, 0.4246464669704437,
0.3993436396121979, 1.5086332559585571, 1.5788191556930542,
3.287064790725708, 2.121230363845825, 2.5666797161102295,
1.141642689704895, 1.8143054246902466, 0.4301592707633972,
0.20714078843593597, 0.18141157925128937, 1.2503143548965454,
1.0035220384597778, 1.6656538248062134, 1.3417718410491943,
2.097904920578003, 0.8345021605491638, 1.313029408454895,
0.2249351441860199, 0.03145187348127365, 0.027173593640327454,
0.38708874583244324, 0.3026771545410156, 1.0853508710861206,
0.5856420397758484, 1.2216601371765137, 0.40328359603881836,
0.45846959948539734, 0.09216563403606415
],
'descriptor': {'dimensions': [1, 5, 5, 2], 'dataType': 'float32'}
}
}
}
},
{
'name': 'convTranspose2d float32 4D input and filter tensors options.bias',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
0.1109575480222702, 0.8681362271308899, 0.7342095971107483,
0.43077003955841064, 0.5981627106666565, 0.12321650236845016,
0.1610974818468094, 0.0884026437997818, 0.29100972414016724
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.6161394715309143, 0.26224616169929504, 0.7951397895812988,
0.8730561137199402, 0.8309102058410645, 0.854960560798645,
0.5552039742469788, 0.840092122554779, 0.85308438539505
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'},
'constant': true
},
'convTranspose2dBias': {
'data': [0.451673686504364],
'descriptor': {'dimensions': [1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'bias': 'convTranspose2dBias'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
0.5200390219688416, 1.01566481590271, 1.2199413776397705,
1.3345069885253906, 1.0354729890823364, 0.8139602541923523,
1.7833205461502075, 2.484194278717041, 2.311894178390503,
1.1773682832717896, 0.9886226654052734, 2.0037572383880615,
2.9867470264434814, 2.5694668292999268, 1.41475510597229,
0.8314860463142395, 1.3567005395889282, 1.8553334474563599,
1.3828538656234741, 0.8055896162986755, 0.5411156415939331,
0.6360918879508972, 0.8249395489692688, 0.7715635895729065,
0.6999295353889465
],
'descriptor': {'dimensions': [1, 1, 5, 5], 'dataType': 'float32'}
}
}
}
},
{
'name':
'convTranspose2d float32 4D input and filter tensors, both negative input tensor and options.bias',
'graph': {
'inputs': {
'convTranspose2dInput': {
'data': [
-0.10889056324958801, -0.29801905155181885, -0.3907785713672638,
-0.5624061226844788, -0.7322093844413757, -0.8421320915222168,
-0.30598655343055725, -0.976659893989563, -0.014158561825752258
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'}
},
'convTranspose2dFilter': {
'data': [
0.6161394715309143, 0.26224616169929504, 0.7951397895812988,
0.8730561137199402, 0.8309102058410645, 0.854960560798645,
0.5552039742469788, 0.840092122554779, 0.85308438539505
],
'descriptor': {'dimensions': [1, 1, 3, 3], 'dataType': 'float32'},
'constant': true
},
'convTranspose2dBias': {
'data': [-0.8457866311073303],
'descriptor': {'dimensions': [1], 'dataType': 'float32'},
'constant': true
}
},
'operators': [{
'name': 'convTranspose2d',
'arguments': [
{'input': 'convTranspose2dInput'},
{'filter': 'convTranspose2dFilter'},
{'options': {'bias': 'convTranspose2dBias'}}
],
'outputs': 'convTranspose2dOutput'
}],
'expectedOutputs': {
'convTranspose2dOutput': {
'data': [
-0.9128783941268921, -1.0579640865325928, -1.2512983083724976,
-1.1852335929870605, -1.1565102338790894, -1.2873748540878296,
-1.7950842380523682, -2.6857638359069824, -2.2283377647399902,
-1.8494995832443237, -1.5857856273651123, -2.8912975788116455,
-3.738619565963745, -3.5343525409698486, -1.910401463508606,
-1.425180196762085, -2.8317112922668457, -3.49372935295105,
-3.0246617794036865, -1.5763013362884521, -1.0156716108322144,
-1.645089030265808, -1.935164213180542, -1.6908544301986694,
-0.8578650951385498
],
'descriptor': {'dimensions': [1, 1, 5, 5], 'dataType': 'float32'}
}
}
}
}
];
if (navigator.ml) {
convTranspose2dTests.forEach((test) => {
// reuse getConv2dPrecisionTolerance method for convTranspose2d tests
webnn_conformance_test(
buildGraphAndCompute, getConv2dPrecisionTolerance, test);
});
} else {
test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
}
Codebase Browser
chromium