Definition
Web Neural Network API defines MLGraphBuilder
[SecureContext, Exposed=(Window, DedicatedWorker)]
interface MLGraphBuilder {
// Construct the graph builder from the context.
constructor(MLContext context);
// Create an operand for a graph input.
MLOperand input(USVString name, MLOperandDescriptor descriptor);
// Create an operand for a graph constant.
MLOperand constant(MLOperandDescriptor descriptor, ArrayBufferView bufferView);
// Create a scalar operand from the specified number of the specified type.
MLOperand constant(MLOperandDataType type, MLNumber value);
// Compile the graph up to the specified output operands asynchronously.
Promise<MLGraph> build(MLNamedOperands outputs);
};
partial interface MLGraphBuilder {
MLOperand argMin(MLOperand input, [EnforceRange] unsigned long axis,
optional MLArgMinMaxOptions options = {});
MLOperand argMax(MLOperand input, [EnforceRange] unsigned long axis,
optional MLArgMinMaxOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand batchNormalization(MLOperand input, MLOperand mean, MLOperand variance,
optional MLBatchNormalizationOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand cast(MLOperand input,
MLOperandDataType type,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand clamp(MLOperand input, optional MLClampOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand concat(sequence<MLOperand> inputs,
[EnforceRange] unsigned long axis,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand conv2d(MLOperand input,
MLOperand filter,
optional MLConv2dOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand convTranspose2d(MLOperand input, MLOperand filter,
optional MLConvTranspose2dOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand add(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand sub(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand mul(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand div(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand max(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand min(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand pow(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand equal(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand greater(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand greaterOrEqual(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand lesser(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand lesserOrEqual(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand logicalNot(MLOperand a, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand abs(MLOperand input, optional MLOperatorOptions options = {});
MLOperand ceil(MLOperand input, optional MLOperatorOptions options = {});
MLOperand cos(MLOperand input, optional MLOperatorOptions options = {});
MLOperand erf(MLOperand input, optional MLOperatorOptions options = {});
MLOperand exp(MLOperand input, optional MLOperatorOptions options = {});
MLOperand floor(MLOperand input, optional MLOperatorOptions options = {});
MLOperand identity(MLOperand input, optional MLOperatorOptions options = {});
MLOperand log(MLOperand input, optional MLOperatorOptions options = {});
MLOperand neg(MLOperand input, optional MLOperatorOptions options = {});
MLOperand reciprocal(MLOperand input, optional MLOperatorOptions options = {});
MLOperand sin(MLOperand input, optional MLOperatorOptions options = {});
MLOperand sqrt(MLOperand input, optional MLOperatorOptions options = {});
MLOperand tan(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand elu(MLOperand input, optional MLEluOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand expand(MLOperand input,
sequence<[EnforceRange] unsigned long> newShape,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand gather(MLOperand input,
MLOperand indices,
optional MLGatherOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand gelu(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand gemm(MLOperand a, MLOperand b, optional MLGemmOptions options = {});
};
partial interface MLGraphBuilder {
sequence<MLOperand> gru(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
[EnforceRange] unsigned long steps,
[EnforceRange] unsigned long hiddenSize,
optional MLGruOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand gruCell(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
MLOperand hiddenState,
[EnforceRange] unsigned long hiddenSize,
optional MLGruCellOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand hardSigmoid(MLOperand input, optional MLHardSigmoidOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand hardSwish(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand instanceNormalization(MLOperand input,
optional MLInstanceNormalizationOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand layerNormalization(MLOperand input,
optional MLLayerNormalizationOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand leakyRelu(MLOperand input, optional MLLeakyReluOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand linear(MLOperand input, optional MLLinearOptions options = {});
};
partial interface MLGraphBuilder {
sequence<MLOperand> lstm(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
[EnforceRange] unsigned long steps,
[EnforceRange] unsigned long hiddenSize,
optional MLLstmOptions options = {});
};
partial interface MLGraphBuilder {
sequence<MLOperand> lstmCell(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
MLOperand hiddenState,
MLOperand cellState,
[EnforceRange] unsigned long hiddenSize,
optional MLLstmCellOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand matmul(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand pad(MLOperand input,
sequence<[EnforceRange] unsigned long> beginningPadding,
sequence<[EnforceRange] unsigned long> endingPadding,
optional MLPadOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand averagePool2d(MLOperand input, optional MLPool2dOptions options = {});
MLOperand l2Pool2d(MLOperand input, optional MLPool2dOptions options = {});
MLOperand maxPool2d(MLOperand input, optional MLPool2dOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand prelu(MLOperand input,
MLOperand slope,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand reduceL1(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceL2(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceLogSum(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceLogSumExp(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceMax(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceMean(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceMin(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceProduct(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceSum(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceSumSquare(MLOperand input, optional MLReduceOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand relu(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand resample2d(MLOperand input, optional MLResample2dOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand reshape(MLOperand input,
sequence<[EnforceRange] unsigned long> newShape,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand sigmoid(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand slice(MLOperand input,
sequence<[EnforceRange] unsigned long> starts,
sequence<[EnforceRange] unsigned long> sizes,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand softmax(MLOperand input,
[EnforceRange] unsigned long axis,
optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand softplus(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand softsign(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
sequence<MLOperand> split(
MLOperand input,
([EnforceRange] unsigned long or sequence<[EnforceRange] unsigned long>) splits,
optional MLSplitOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand tanh(MLOperand input, optional MLOperatorOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand transpose(MLOperand input, optional MLTransposeOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand triangular(MLOperand input, optional MLTriangularOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand where(MLOperand condition,
MLOperand trueValue,
MLOperand falseValue,
optional MLOperatorOptions options = {});
};Consolidated IDL (across mixin and partials)
[SecureContext, Exposed=(Window, DedicatedWorker)]
interface MLGraphBuilder {
// Construct the graph builder from the context.
constructor(MLContext context);
// Create an operand for a graph input.
MLOperand input(USVString name, MLOperandDescriptor descriptor);
// Create an operand for a graph constant.
MLOperand constant(MLOperandDescriptor descriptor, ArrayBufferView bufferView);
// Create a scalar operand from the specified number of the specified type.
MLOperand constant(MLOperandDataType type, MLNumber value);
// Compile the graph up to the specified output operands asynchronously.
Promise<MLGraph> build(MLNamedOperands outputs);
MLOperand argMin(MLOperand input, [EnforceRange] unsigned long axis,
optional MLArgMinMaxOptions options = {});
MLOperand argMax(MLOperand input, [EnforceRange] unsigned long axis,
optional MLArgMinMaxOptions options = {});
MLOperand batchNormalization(MLOperand input, MLOperand mean, MLOperand variance,
optional MLBatchNormalizationOptions options = {});
MLOperand cast(MLOperand input,
MLOperandDataType type,
optional MLOperatorOptions options = {});
MLOperand clamp(MLOperand input, optional MLClampOptions options = {});
MLOperand concat(sequence<MLOperand> inputs,
[EnforceRange] unsigned long axis,
optional MLOperatorOptions options = {});
MLOperand conv2d(MLOperand input,
MLOperand filter,
optional MLConv2dOptions options = {});
MLOperand convTranspose2d(MLOperand input, MLOperand filter,
optional MLConvTranspose2dOptions options = {});
MLOperand add(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand sub(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand mul(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand div(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand max(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand min(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand pow(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand equal(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand greater(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand greaterOrEqual(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand lesser(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand lesserOrEqual(MLOperand a,
MLOperand b,
optional MLOperatorOptions options = {});
MLOperand logicalNot(MLOperand a, optional MLOperatorOptions options = {});
MLOperand abs(MLOperand input, optional MLOperatorOptions options = {});
MLOperand ceil(MLOperand input, optional MLOperatorOptions options = {});
MLOperand cos(MLOperand input, optional MLOperatorOptions options = {});
MLOperand erf(MLOperand input, optional MLOperatorOptions options = {});
MLOperand exp(MLOperand input, optional MLOperatorOptions options = {});
MLOperand floor(MLOperand input, optional MLOperatorOptions options = {});
MLOperand identity(MLOperand input, optional MLOperatorOptions options = {});
MLOperand log(MLOperand input, optional MLOperatorOptions options = {});
MLOperand neg(MLOperand input, optional MLOperatorOptions options = {});
MLOperand reciprocal(MLOperand input, optional MLOperatorOptions options = {});
MLOperand sin(MLOperand input, optional MLOperatorOptions options = {});
MLOperand sqrt(MLOperand input, optional MLOperatorOptions options = {});
MLOperand tan(MLOperand input, optional MLOperatorOptions options = {});
MLOperand elu(MLOperand input, optional MLEluOptions options = {});
MLOperand expand(MLOperand input,
sequence<[EnforceRange] unsigned long> newShape,
optional MLOperatorOptions options = {});
MLOperand gather(MLOperand input,
MLOperand indices,
optional MLGatherOptions options = {});
MLOperand gelu(MLOperand input, optional MLOperatorOptions options = {});
MLOperand gemm(MLOperand a, MLOperand b, optional MLGemmOptions options = {});
sequence<MLOperand> gru(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
[EnforceRange] unsigned long steps,
[EnforceRange] unsigned long hiddenSize,
optional MLGruOptions options = {});
MLOperand gruCell(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
MLOperand hiddenState,
[EnforceRange] unsigned long hiddenSize,
optional MLGruCellOptions options = {});
MLOperand hardSigmoid(MLOperand input, optional MLHardSigmoidOptions options = {});
MLOperand hardSwish(MLOperand input, optional MLOperatorOptions options = {});
MLOperand instanceNormalization(MLOperand input,
optional MLInstanceNormalizationOptions options = {});
MLOperand layerNormalization(MLOperand input,
optional MLLayerNormalizationOptions options = {});
MLOperand leakyRelu(MLOperand input, optional MLLeakyReluOptions options = {});
MLOperand linear(MLOperand input, optional MLLinearOptions options = {});
sequence<MLOperand> lstm(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
[EnforceRange] unsigned long steps,
[EnforceRange] unsigned long hiddenSize,
optional MLLstmOptions options = {});
sequence<MLOperand> lstmCell(MLOperand input,
MLOperand weight,
MLOperand recurrentWeight,
MLOperand hiddenState,
MLOperand cellState,
[EnforceRange] unsigned long hiddenSize,
optional MLLstmCellOptions options = {});
MLOperand matmul(MLOperand a, MLOperand b, optional MLOperatorOptions options = {});
MLOperand pad(MLOperand input,
sequence<[EnforceRange] unsigned long> beginningPadding,
sequence<[EnforceRange] unsigned long> endingPadding,
optional MLPadOptions options = {});
MLOperand averagePool2d(MLOperand input, optional MLPool2dOptions options = {});
MLOperand l2Pool2d(MLOperand input, optional MLPool2dOptions options = {});
MLOperand maxPool2d(MLOperand input, optional MLPool2dOptions options = {});
MLOperand prelu(MLOperand input,
MLOperand slope,
optional MLOperatorOptions options = {});
MLOperand reduceL1(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceL2(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceLogSum(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceLogSumExp(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceMax(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceMean(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceMin(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceProduct(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceSum(MLOperand input, optional MLReduceOptions options = {});
MLOperand reduceSumSquare(MLOperand input, optional MLReduceOptions options = {});
MLOperand relu(MLOperand input, optional MLOperatorOptions options = {});
MLOperand resample2d(MLOperand input, optional MLResample2dOptions options = {});
MLOperand reshape(MLOperand input,
sequence<[EnforceRange] unsigned long> newShape,
optional MLOperatorOptions options = {});
MLOperand sigmoid(MLOperand input, optional MLOperatorOptions options = {});
MLOperand slice(MLOperand input,
sequence<[EnforceRange] unsigned long> starts,
sequence<[EnforceRange] unsigned long> sizes,
optional MLOperatorOptions options = {});
MLOperand softmax(MLOperand input,
[EnforceRange] unsigned long axis,
optional MLOperatorOptions options = {});
MLOperand softplus(MLOperand input, optional MLOperatorOptions options = {});
MLOperand softsign(MLOperand input, optional MLOperatorOptions options = {});
sequence<MLOperand> split(
MLOperand input,
([EnforceRange] unsigned long or sequence<[EnforceRange] unsigned long>) splits,
optional MLSplitOptions options = {});
MLOperand tanh(MLOperand input, optional MLOperatorOptions options = {});
MLOperand transpose(MLOperand input, optional MLTransposeOptions options = {});
MLOperand triangular(MLOperand input, optional MLTriangularOptions options = {});
MLOperand where(MLOperand condition,
MLOperand trueValue,
MLOperand falseValue,
optional MLOperatorOptions options = {});
};