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(DOMString name, MLOperandDescriptor descriptor);
// Create an operand for a graph constant.
MLOperand constant(MLOperandDescriptor descriptor, ArrayBufferView bufferView);
// Create a single-value operand from the specified number of the specified type.
MLOperand constant(double value, optional MLOperandDataType type = "float32");
// Compile the graph up to the specified output operands asynchronously.
Promise<MLGraph> build(MLNamedOperands outputs);
};
partial interface MLGraphBuilder {
MLOperand argMin(MLOperand input, optional MLArgMinMaxOptions options = {});
MLOperand argMax(MLOperand input, 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);
};
partial interface MLGraphBuilder {
MLOperand clamp(MLOperand input, optional MLClampOptions options = {});
MLActivation clamp(optional MLClampOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand concat(sequence<MLOperand> inputs, [EnforceRange] unsigned long axis);
};
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);
MLOperand sub(MLOperand a, MLOperand b);
MLOperand mul(MLOperand a, MLOperand b);
MLOperand div(MLOperand a, MLOperand b);
MLOperand max(MLOperand a, MLOperand b);
MLOperand min(MLOperand a, MLOperand b);
MLOperand pow(MLOperand a, MLOperand b);
};
partial interface MLGraphBuilder {
MLOperand equal(MLOperand a, MLOperand b);
MLOperand greater(MLOperand a, MLOperand b);
MLOperand greaterOrEqual(MLOperand a, MLOperand b);
MLOperand lesser(MLOperand a, MLOperand b);
MLOperand lesserOrEqual(MLOperand a, MLOperand b);
MLOperand not(MLOperand a);
};
partial interface MLGraphBuilder {
MLOperand abs(MLOperand input);
MLOperand ceil(MLOperand input);
MLOperand cos(MLOperand input);
MLOperand erf(MLOperand input);
MLOperand exp(MLOperand input);
MLOperand floor(MLOperand input);
MLOperand identity(MLOperand input);
MLOperand log(MLOperand input);
MLOperand neg(MLOperand input);
MLOperand reciprocal(MLOperand input);
MLOperand sin(MLOperand input);
MLOperand sqrt(MLOperand input);
MLOperand tan(MLOperand input);
};
partial interface MLGraphBuilder {
MLOperand elu(MLOperand input, optional MLEluOptions options = {});
MLActivation elu(optional MLEluOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand expand(MLOperand input, sequence<[EnforceRange] unsigned long> newShape);
};
partial interface MLGraphBuilder {
MLOperand gather(MLOperand input,
MLOperand indices,
optional MLGatherOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand gelu(MLOperand input);
MLActivation gelu();
};
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 = {});
MLActivation hardSigmoid(optional MLHardSigmoidOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand hardSwish(MLOperand input);
MLActivation hardSwish();
};
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 = {});
MLActivation leakyRelu(optional MLLeakyReluOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand linear(MLOperand input, optional MLLinearOptions options = {});
MLActivation linear(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);
};
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);
};
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);
MLActivation relu();
};
partial interface MLGraphBuilder {
MLOperand resample2d(MLOperand input, optional MLResample2dOptions options = {});
};
partial interface MLGraphBuilder {
MLOperand reshape(MLOperand input, sequence<[EnforceRange] unsigned long> newShape);
};
partial interface MLGraphBuilder {
MLOperand sigmoid(MLOperand input);
MLActivation sigmoid();
};
partial interface MLGraphBuilder {
MLOperand slice(MLOperand input,
sequence<[EnforceRange] unsigned long> starts,
sequence<[EnforceRange] unsigned long> sizes);
};
partial interface MLGraphBuilder {
MLOperand softmax(MLOperand input, unsigned long axis);
MLActivation softmax(unsigned long axis);
};
partial interface MLGraphBuilder {
MLOperand softplus(MLOperand input);
MLActivation softplus();
};
partial interface MLGraphBuilder {
MLOperand softsign(MLOperand input);
MLActivation softsign();
};
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);
MLActivation tanh();
};
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 input, MLOperand other);
};
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(DOMString name, MLOperandDescriptor descriptor);
// Create an operand for a graph constant.
MLOperand constant(MLOperandDescriptor descriptor, ArrayBufferView bufferView);
// Create a single-value operand from the specified number of the specified type.
MLOperand constant(double value, optional MLOperandDataType type = "float32");
// Compile the graph up to the specified output operands asynchronously.
Promise<MLGraph> build(MLNamedOperands outputs);
MLOperand argMin(MLOperand input, optional MLArgMinMaxOptions options = {});
MLOperand argMax(MLOperand input, optional MLArgMinMaxOptions options = {});
MLOperand batchNormalization(MLOperand input, MLOperand mean, MLOperand variance,
optional MLBatchNormalizationOptions options = {});
MLOperand cast(MLOperand input, MLOperandDataType type);
MLOperand clamp(MLOperand input, optional MLClampOptions options = {});
MLActivation clamp(optional MLClampOptions options = {});
MLOperand concat(sequence<MLOperand> inputs, [EnforceRange] unsigned long axis);
MLOperand conv2d(MLOperand input,
MLOperand filter,
optional MLConv2dOptions options = {});
MLOperand convTranspose2d(MLOperand input, MLOperand filter,
optional MLConvTranspose2dOptions options = {});
MLOperand add(MLOperand a, MLOperand b);
MLOperand sub(MLOperand a, MLOperand b);
MLOperand mul(MLOperand a, MLOperand b);
MLOperand div(MLOperand a, MLOperand b);
MLOperand max(MLOperand a, MLOperand b);
MLOperand min(MLOperand a, MLOperand b);
MLOperand pow(MLOperand a, MLOperand b);
MLOperand equal(MLOperand a, MLOperand b);
MLOperand greater(MLOperand a, MLOperand b);
MLOperand greaterOrEqual(MLOperand a, MLOperand b);
MLOperand lesser(MLOperand a, MLOperand b);
MLOperand lesserOrEqual(MLOperand a, MLOperand b);
MLOperand not(MLOperand a);
MLOperand abs(MLOperand input);
MLOperand ceil(MLOperand input);
MLOperand cos(MLOperand input);
MLOperand erf(MLOperand input);
MLOperand exp(MLOperand input);
MLOperand floor(MLOperand input);
MLOperand identity(MLOperand input);
MLOperand log(MLOperand input);
MLOperand neg(MLOperand input);
MLOperand reciprocal(MLOperand input);
MLOperand sin(MLOperand input);
MLOperand sqrt(MLOperand input);
MLOperand tan(MLOperand input);
MLOperand elu(MLOperand input, optional MLEluOptions options = {});
MLActivation elu(optional MLEluOptions options = {});
MLOperand expand(MLOperand input, sequence<[EnforceRange] unsigned long> newShape);
MLOperand gather(MLOperand input,
MLOperand indices,
optional MLGatherOptions options = {});
MLOperand gelu(MLOperand input);
MLActivation gelu();
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 = {});
MLActivation hardSigmoid(optional MLHardSigmoidOptions options = {});
MLOperand hardSwish(MLOperand input);
MLActivation hardSwish();
MLOperand instanceNormalization(MLOperand input,
optional MLInstanceNormalizationOptions options = {});
MLOperand layerNormalization(MLOperand input,
optional MLLayerNormalizationOptions options = {});
MLOperand leakyRelu(MLOperand input, optional MLLeakyReluOptions options = {});
MLActivation leakyRelu(optional MLLeakyReluOptions options = {});
MLOperand linear(MLOperand input, optional MLLinearOptions options = {});
MLActivation linear(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);
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);
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);
MLActivation relu();
MLOperand resample2d(MLOperand input, optional MLResample2dOptions options = {});
MLOperand reshape(MLOperand input, sequence<[EnforceRange] unsigned long> newShape);
MLOperand sigmoid(MLOperand input);
MLActivation sigmoid();
MLOperand slice(MLOperand input,
sequence<[EnforceRange] unsigned long> starts,
sequence<[EnforceRange] unsigned long> sizes);
MLOperand softmax(MLOperand input, unsigned long axis);
MLActivation softmax(unsigned long axis);
MLOperand softplus(MLOperand input);
MLActivation softplus();
MLOperand softsign(MLOperand input);
MLActivation softsign();
sequence<MLOperand> split(
MLOperand input,
([EnforceRange] unsigned long or sequence<[EnforceRange] unsigned long>) splits,
optional MLSplitOptions options = {});
MLOperand tanh(MLOperand input);
MLActivation tanh();
MLOperand transpose(MLOperand input, optional MLTransposeOptions options = {});
MLOperand triangular(MLOperand input, optional MLTriangularOptions options = {});
MLOperand where(MLOperand condition, MLOperand input, MLOperand other);
};