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Merged
Honry merged 1 commit into from
Jan 6, 2023
Merged

Add webnn relu tests #37071

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10 changes: 10 additions & 0 deletions webnn/relu.https.any.js
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,10 @@
// META: title=test WebNN API relu operation
// META: global=window,dedicatedworker
// META: script=./resources/utils.js
// META: timeout=long

'use strict';

// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-relu

testWebNNOperation('relu', '/webnn/resources/test_data/relu.json', buildOperationWithSingleInput);
334 changes: 334 additions & 0 deletions webnn/resources/test_data/relu.json
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Original file line number Diff line number Diff line change
@@ -0,0 +1,334 @@
{
"tests": [ // relu input tensor of 1D to 5D with same data values
{
"name": "relu float32 1D tensor",
"inputs": {
"x": {
"shape": [24],
"data": [
79.04725231657116,
2.2503608756501166,
80.73939090529203,
63.90392076789547,
77.67340745512104,
-71.09157819044825,
-82.74703468427575,
-26.814426600801028,
-99.16788836397058,
-35.71083406288831,
18.36165830990626,
-37.36091648205435,
-52.8386119809162,
-10.408374773008958,
60.60291560236189,
-13.644198913810342,
-76.54250291031946,
-8.132338049258351,
51.51447452437017,
-51.63370281825297,
-64.567999424324,
-5.093302411117136,
15.354103550744384,
90.03858807393516
],
"type": "float32"
}
},
"expected": {
"name": "output",
"shape": [24],
"data": [
79.04724884033203,
2.2503609657287598,
80.73938751220703,
63.9039192199707,
77.67340850830078,
0,
0,
0,
0,
0,
18.361658096313477,
0,
0,
0,
60.6029167175293,
0,
0,
0,
51.51447296142578,
0,
0,
0,
15.354103088378906,
90.03858947753906
],
"type": "float32"
}
},
{
"name": "relu float32 2D tensor",
"inputs": {
"x": {
"shape": [4, 6],
"data": [
79.04725231657116,
2.2503608756501166,
80.73939090529203,
63.90392076789547,
77.67340745512104,
-71.09157819044825,
-82.74703468427575,
-26.814426600801028,
-99.16788836397058,
-35.71083406288831,
18.36165830990626,
-37.36091648205435,
-52.8386119809162,
-10.408374773008958,
60.60291560236189,
-13.644198913810342,
-76.54250291031946,
-8.132338049258351,
51.51447452437017,
-51.63370281825297,
-64.567999424324,
-5.093302411117136,
15.354103550744384,
90.03858807393516
],
"type": "float32"
}
},
"expected": {
"name": "output",
"shape": [4, 6],
"data": [
79.04724884033203,
2.2503609657287598,
80.73938751220703,
63.9039192199707,
77.67340850830078,
0,
0,
0,
0,
0,
18.361658096313477,
0,
0,
0,
60.6029167175293,
0,
0,
0,
51.51447296142578,
0,
0,
0,
15.354103088378906,
90.03858947753906
],
"type": "float32"
}
},
{
"name": "relu float32 3D tensor",
"inputs": {
"x": {
"shape": [2, 3, 4],
"data": [
79.04725231657116,
2.2503608756501166,
80.73939090529203,
63.90392076789547,
77.67340745512104,
-71.09157819044825,
-82.74703468427575,
-26.814426600801028,
-99.16788836397058,
-35.71083406288831,
18.36165830990626,
-37.36091648205435,
-52.8386119809162,
-10.408374773008958,
60.60291560236189,
-13.644198913810342,
-76.54250291031946,
-8.132338049258351,
51.51447452437017,
-51.63370281825297,
-64.567999424324,
-5.093302411117136,
15.354103550744384,
90.03858807393516
],
"type": "float32"
}
},
"expected": {
"name": "output",
"shape": [2, 3, 4],
"data": [
79.04724884033203,
2.2503609657287598,
80.73938751220703,
63.9039192199707,
77.67340850830078,
0,
0,
0,
0,
0,
18.361658096313477,
0,
0,
0,
60.6029167175293,
0,
0,
0,
51.51447296142578,
0,
0,
0,
15.354103088378906,
90.03858947753906
],
"type": "float32"
}
},
{
"name": "relu float32 4D tensor",
"inputs": {
"x": {
"shape": [2, 2, 2, 3],
"data": [
79.04725231657116,
2.2503608756501166,
80.73939090529203,
63.90392076789547,
77.67340745512104,
-71.09157819044825,
-82.74703468427575,
-26.814426600801028,
-99.16788836397058,
-35.71083406288831,
18.36165830990626,
-37.36091648205435,
-52.8386119809162,
-10.408374773008958,
60.60291560236189,
-13.644198913810342,
-76.54250291031946,
-8.132338049258351,
51.51447452437017,
-51.63370281825297,
-64.567999424324,
-5.093302411117136,
15.354103550744384,
90.03858807393516
],
"type": "float32"
}
},
"expected": {
"name": "output",
"shape": [2, 2, 2, 3],
"data": [
79.04724884033203,
2.2503609657287598,
80.73938751220703,
63.9039192199707,
77.67340850830078,
0,
0,
0,
0,
0,
18.361658096313477,
0,
0,
0,
60.6029167175293,
0,
0,
0,
51.51447296142578,
0,
0,
0,
15.354103088378906,
90.03858947753906
],
"type": "float32"
}
},
{
"name": "relu float32 5D tensor",
"inputs": {
"x": {
"shape": [2, 1, 4, 1, 3],
"data": [
79.04725231657116,
2.2503608756501166,
80.73939090529203,
63.90392076789547,
77.67340745512104,
-71.09157819044825,
-82.74703468427575,
-26.814426600801028,
-99.16788836397058,
-35.71083406288831,
18.36165830990626,
-37.36091648205435,
-52.8386119809162,
-10.408374773008958,
60.60291560236189,
-13.644198913810342,
-76.54250291031946,
-8.132338049258351,
51.51447452437017,
-51.63370281825297,
-64.567999424324,
-5.093302411117136,
15.354103550744384,
90.03858807393516
],
"type": "float32"
}
},
"expected": {
"name": "output",
"shape": [2, 1, 4, 1, 3],
"data": [
79.04724884033203,
2.2503609657287598,
80.73938751220703,
63.9039192199707,
77.67340850830078,
0,
0,
0,
0,
0,
18.361658096313477,
0,
0,
0,
60.6029167175293,
0,
0,
0,
51.51447296142578,
0,
0,
0,
15.354103088378906,
90.03858947753906
],
"type": "float32"
}
}
]
}
1 change: 1 addition & 0 deletions webnn/resources/utils.js
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,7 @@ const getExpectedData = (resources, outputName) => {
const PrecisionMetrics = {
clamp: {ULP: {float32: 0, float16: 0}},
concat: {ULP: {float32: 0, float16: 0}},
relu: {ULP: {float32: 0, float16: 0}},
reshape: {ULP: {float32: 0, float16: 0}},
};

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