409 lines
15 KiB
JavaScript
409 lines
15 KiB
JavaScript
// META: title=validation tests for WebNN API gruCell operation
|
|
// META: global=window
|
|
// META: variant=?cpu
|
|
// META: variant=?gpu
|
|
// META: variant=?npu
|
|
// META: script=../resources/utils_validation.js
|
|
|
|
'use strict';
|
|
|
|
const batchSize = 3, inputSize = 4, hiddenSize = 5;
|
|
|
|
// Dimensions required of required inputs.
|
|
const kValidInputShape = [batchSize, inputSize];
|
|
const kValidWeightShape = [3 * hiddenSize, inputSize];
|
|
const kValidRecurrentWeightShape = [3 * hiddenSize, hiddenSize];
|
|
const kValidHiddenStateShape = [batchSize, hiddenSize];
|
|
// Dimensions required of optional inputs.
|
|
const kValidBiasShape = [3 * hiddenSize];
|
|
const kValidRecurrentBiasShape = [3 * hiddenSize];
|
|
// Dimensions required of required output.
|
|
const kValidOutputShape = [batchSize, hiddenSize];
|
|
|
|
// Example descriptors which are valid according to the above dimensions.
|
|
const kExampleInputDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidInputShape
|
|
};
|
|
const kExampleWeightDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidWeightShape
|
|
};
|
|
const kExampleRecurrentWeightDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidRecurrentWeightShape
|
|
};
|
|
const kExampleHiddenStateDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidHiddenStateShape
|
|
};
|
|
const kExampleBiasDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidBiasShape
|
|
};
|
|
const kExampleRecurrentBiasDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidRecurrentBiasShape
|
|
};
|
|
const kExampleOutputDescriptor = {
|
|
dataType: 'float32',
|
|
shape: kValidOutputShape
|
|
};
|
|
|
|
const tests = [
|
|
{
|
|
name: '[gruCell] Test with default options',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
output: kExampleOutputDescriptor
|
|
},
|
|
{
|
|
name: '[gruCell] Test with given options',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {
|
|
bias: kExampleBiasDescriptor,
|
|
recurrentBias: kExampleRecurrentBiasDescriptor,
|
|
restAfter: true,
|
|
layout: 'rzn',
|
|
activations: ['sigmoid', 'relu']
|
|
},
|
|
output: kExampleOutputDescriptor
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if hiddenSize equals to zero',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: 0
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if hiddenSize is too large',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: 4294967295,
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if the data type of the inputs is not one of the floating point types',
|
|
input: {dataType: 'uint32', shape: kValidInputShape},
|
|
weight: {dataType: 'uint32', shape: kValidWeightShape},
|
|
recurrentWeight: {dataType: 'uint32', shape: kValidRecurrentWeightShape},
|
|
hiddenState: {dataType: 'uint32', shape: kValidHiddenStateShape},
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the rank of input is not 2',
|
|
input: {dataType: 'float32', shape: [batchSize]},
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the input.shape[1] is incorrect',
|
|
input: {dataType: 'float32', shape: [inputSize, inputSize]},
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if data type of weight is not one of the floating point types',
|
|
input: kExampleInputDescriptor,
|
|
weight: {dataType: 'int8', shape: [3 * hiddenSize, inputSize]},
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if rank of weight is not 2',
|
|
input: kExampleInputDescriptor,
|
|
weight: {dataType: 'float32', shape: [3 * hiddenSize]},
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if weight.shape[0] is not 3 * hiddenSize',
|
|
input: kExampleInputDescriptor,
|
|
weight: {dataType: 'float32', shape: [4 * hiddenSize, inputSize]},
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if data type of recurrentWeight is not one of the floating point types',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: {dataType: 'int32', shape: [3 * hiddenSize, hiddenSize]},
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the rank of recurrentWeight is not 2',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: {dataType: 'float32', shape: [3 * hiddenSize]},
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the recurrentWeight.shape is invalid',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: {dataType: 'float32', shape: [4 * hiddenSize, inputSize]},
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if data type of hiddenState is not one of the floating point types',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: {dataType: 'uint32', shape: [batchSize, hiddenSize]},
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the rank of hiddenState is not 2',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: {dataType: 'float32', shape: [hiddenSize]},
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the hiddenState.shape is invalid',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: {dataType: 'float32', shape: [batchSize, 3 * hiddenSize]},
|
|
hiddenSize: hiddenSize
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the size of options.activations is not 2',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {activations: ['sigmoid', 'tanh', 'relu']}
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if data type of options.bias is not one of the floating point types',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {bias: {dataType: 'uint8', shape: [3 * hiddenSize]}}
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the rank of options.bias is not 1',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {bias: {dataType: 'float32', shape: [batchSize, 3 * hiddenSize]}}
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if options.bias.shape[0] is not 3 * hiddenSize',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {bias: {dataType: 'float32', shape: [2 * hiddenSize]}}
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if data type of options.recurrentBias is not one of the floating point types',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {recurrentBias: {dataType: 'int8', shape: [3 * hiddenSize]}}
|
|
},
|
|
{
|
|
name: '[gruCell] Throw if the rank of options.recurrentBias is not 1',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {
|
|
recurrentBias: {dataType: 'float32', shape: [batchSize, 3 * hiddenSize]}
|
|
}
|
|
},
|
|
{
|
|
name:
|
|
'[gruCell] Throw if options.recurrentBias.shape[0] is not 3 * hiddenSize',
|
|
input: kExampleInputDescriptor,
|
|
weight: kExampleWeightDescriptor,
|
|
recurrentWeight: kExampleRecurrentWeightDescriptor,
|
|
hiddenState: kExampleHiddenStateDescriptor,
|
|
hiddenSize: hiddenSize,
|
|
options: {recurrentBias: {dataType: 'float16', shape: [4 * hiddenSize]}}
|
|
}
|
|
];
|
|
|
|
tests.forEach(
|
|
test =>
|
|
promise_test(async t => {
|
|
const builder = new MLGraphBuilder(context);
|
|
const input = builder.input('input', test.input);
|
|
const weight = builder.input('weight', test.weight);
|
|
const recurrentWeight =
|
|
builder.input('recurrentWeight', test.recurrentWeight);
|
|
const hiddenState = builder.input('hiddenState', test.hiddenState);
|
|
|
|
const options = {};
|
|
if (test.options) {
|
|
if (test.options.bias) {
|
|
options.bias = builder.input('bias', test.options.bias);
|
|
}
|
|
if (test.options.recurrentBias) {
|
|
options.recurrentBias =
|
|
builder.input('recurrentBias', test.options.recurrentBias);
|
|
}
|
|
if (test.options.resetAfter) {
|
|
options.resetAfter = test.options.resetAfter;
|
|
}
|
|
if (test.options.layout) {
|
|
options.layout = test.options.layout;
|
|
}
|
|
if (test.options.activations) {
|
|
options.activations = test.options.activations;
|
|
}
|
|
}
|
|
|
|
if (test.output &&
|
|
context.opSupportLimits().gruCell.input.dataTypes.includes(
|
|
test.input.dataType)) {
|
|
const output = builder.gruCell(
|
|
input, weight, recurrentWeight, hiddenState, test.hiddenSize,
|
|
options);
|
|
assert_equals(output.dataType, test.output.dataType);
|
|
assert_array_equals(output.shape, test.output.shape);
|
|
} else {
|
|
const label = 'gru_cell_xxx';
|
|
options.label = label;
|
|
const regrexp = new RegExp('\\[' + label + '\\]');
|
|
assert_throws_with_label(
|
|
() => builder.gruCell(
|
|
input, weight, recurrentWeight, hiddenState,
|
|
test.hiddenSize, options),
|
|
regrexp);
|
|
}
|
|
}, test.name));
|
|
|
|
multi_builder_test(async (t, builder, otherBuilder) => {
|
|
const inputFromOtherBuilder =
|
|
otherBuilder.input('input', kExampleInputDescriptor);
|
|
|
|
const weight = builder.input('weight', kExampleWeightDescriptor);
|
|
const recurrentWeight =
|
|
builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
|
|
const hiddenState =
|
|
builder.input('hiddenState', kExampleHiddenStateDescriptor);
|
|
assert_throws_js(
|
|
TypeError,
|
|
() => builder.gruCell(
|
|
inputFromOtherBuilder, weight, recurrentWeight, hiddenState,
|
|
hiddenSize));
|
|
}, '[gruCell] throw if input is from another builder');
|
|
|
|
multi_builder_test(async (t, builder, otherBuilder) => {
|
|
const weightFromOtherBuilder =
|
|
otherBuilder.input('weight', kExampleWeightDescriptor);
|
|
|
|
const input = builder.input('input', kExampleInputDescriptor);
|
|
const recurrentWeight =
|
|
builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
|
|
const hiddenState =
|
|
builder.input('hiddenState', kExampleHiddenStateDescriptor);
|
|
assert_throws_js(
|
|
TypeError,
|
|
() => builder.gruCell(
|
|
input, weightFromOtherBuilder, recurrentWeight, hiddenState,
|
|
hiddenSize));
|
|
}, '[gruCell] throw if weight is from another builder');
|
|
|
|
multi_builder_test(async (t, builder, otherBuilder) => {
|
|
const recurrentWeightFromOtherBuilder =
|
|
otherBuilder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
|
|
|
|
const input = builder.input('input', kExampleInputDescriptor);
|
|
const weight = builder.input('weight', kExampleWeightDescriptor);
|
|
const hiddenState =
|
|
builder.input('hiddenState', kExampleHiddenStateDescriptor);
|
|
assert_throws_js(
|
|
TypeError,
|
|
() => builder.gruCell(
|
|
input, weight, recurrentWeightFromOtherBuilder, hiddenState,
|
|
hiddenSize));
|
|
}, '[gruCell] throw if recurrentWeight is from another builder');
|
|
|
|
multi_builder_test(async (t, builder, otherBuilder) => {
|
|
const hiddenStateFromOtherBuilder =
|
|
otherBuilder.input('hiddenState', kExampleHiddenStateDescriptor);
|
|
|
|
const input = builder.input('input', kExampleInputDescriptor);
|
|
const weight = builder.input('weight', kExampleWeightDescriptor);
|
|
const recurrentWeight =
|
|
builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
|
|
assert_throws_js(
|
|
TypeError,
|
|
() => builder.gruCell(
|
|
input, weight, recurrentWeight, hiddenStateFromOtherBuilder,
|
|
hiddenSize));
|
|
}, '[gruCell] throw if hiddenState is from another builder');
|
|
|
|
multi_builder_test(async (t, builder, otherBuilder) => {
|
|
const biasFromOtherBuilder =
|
|
otherBuilder.input('bias', kExampleBiasDescriptor);
|
|
const options = {bias: biasFromOtherBuilder};
|
|
|
|
const input = builder.input('input', kExampleInputDescriptor);
|
|
const weight = builder.input('weight', kExampleWeightDescriptor);
|
|
const recurrentWeight =
|
|
builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
|
|
const hiddenState =
|
|
builder.input('hiddenState', kExampleHiddenStateDescriptor);
|
|
assert_throws_js(
|
|
TypeError,
|
|
() => builder.gruCell(
|
|
input, weight, recurrentWeight, hiddenState, hiddenSize, options));
|
|
}, '[gruCell] throw if bias option is from another builder');
|
|
|
|
multi_builder_test(async (t, builder, otherBuilder) => {
|
|
const recurrentBiasFromOtherBuilder =
|
|
otherBuilder.input('recurrentBias', kExampleRecurrentBiasDescriptor);
|
|
const options = {recurrentBias: recurrentBiasFromOtherBuilder};
|
|
|
|
const input = builder.input('input', kExampleInputDescriptor);
|
|
const weight = builder.input('weight', kExampleWeightDescriptor);
|
|
const recurrentWeight =
|
|
builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
|
|
const hiddenState =
|
|
builder.input('hiddenState', kExampleHiddenStateDescriptor);
|
|
assert_throws_js(
|
|
TypeError,
|
|
() => builder.gruCell(
|
|
input, weight, recurrentWeight, hiddenState, hiddenSize, options));
|
|
}, '[gruCell] throw if recurrentBias option is from another builder');
|