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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,69 @@ | ||
| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
|
|
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| import {TensorView} from '../../tensor-view'; | ||
| import {ShapeUtil} from '../../util'; | ||
| import {ComputeContext, GpuDataType, ProgramInfo, ProgramMetadata} from '../types'; | ||
|
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| import {inputVariable, outputVariable, ShaderHelper} from './common'; | ||
|
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| const validateInputs = (inputs: readonly TensorView[]): void => { | ||
| if (inputs[0].dims.length !== 3) { | ||
| throw new Error('input should have 3 dimensions'); | ||
| } | ||
|
|
||
| if (![320, 640, 1280].includes(inputs[0].dims[2])) { | ||
| throw new Error('number of channels should be 320, 640 or 1280'); | ||
| } | ||
|
|
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| if (inputs[1].dims.length !== 1) { | ||
| throw new Error('bias is expected to have 1 dimensions'); | ||
| } | ||
|
|
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| if (inputs[0].dims[2] !== inputs[1].dims[0]) { | ||
| throw new Error('last dimension of input and bias are not the same'); | ||
| } | ||
| }; | ||
|
|
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| const createBiasAddProgramInfo = (metadata: ProgramMetadata, inputs: readonly TensorView[]): ProgramInfo => { | ||
| const outputShape = inputs[0].dims; | ||
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| const channels = inputs[0].dims[2]; | ||
| // since channel number can be only 320/640/1280, it's always divisable by 4 | ||
| const outputSize = ShapeUtil.size(outputShape) / 4; | ||
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| const dataType = inputs[0].dataType; | ||
| const input = inputVariable('input', dataType, outputShape, 4); | ||
| const bias = inputVariable('bias', dataType, [channels], 4); | ||
| const residual = inputVariable('residual', dataType, outputShape, 4); | ||
| const output = outputVariable('output', dataType, outputShape, 4); | ||
|
|
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| const getShaderSource = (shaderHelper: ShaderHelper) => ` | ||
| const channels = ${channels}u / 4; | ||
| ${shaderHelper.declareVariables(input, bias, residual, output)} | ||
| ${shaderHelper.mainStart()} | ||
| ${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(outputSize)} | ||
| let value = ${input.getByOffset('global_idx')} | ||
| + ${bias.getByOffset('global_idx % channels')} + ${residual.getByOffset('global_idx')}; | ||
| ${output.setByOffset('global_idx', 'value')} | ||
| }`; | ||
|
|
||
| return { | ||
| ...metadata, | ||
| outputs: [{dims: outputShape, dataType: inputs[0].dataType, gpuDataType: GpuDataType.default}], | ||
| getShaderSource, | ||
| dispatchGroup: () => ({x: Math.ceil(outputSize / 64 /* workgroup size */)}) | ||
| }; | ||
| }; | ||
|
|
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| export const biasAdd = (context: ComputeContext): void => { | ||
| validateInputs(context.inputs); | ||
| const inputTypes = Array(context.inputs.length).fill(GpuDataType.default); | ||
| const metadata = { | ||
| name: 'BiasAdd', | ||
| inputTypes, | ||
| }; | ||
|
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| context.compute(createBiasAddProgramInfo(metadata, context.inputs)); | ||
| }; |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,76 @@ | ||
| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
|
|
||
| import {TensorView} from '../../tensor-view'; | ||
| import {ShapeUtil} from '../../util'; | ||
| import {ComputeContext, GpuDataType, ProgramInfo, ProgramMetadata} from '../types'; | ||
|
|
||
| import {inputVariable, outputVariable, ShaderHelper} from './common'; | ||
| import {erfImpl} from './unary-op'; | ||
|
|
||
| const validateInputs = (inputs: readonly TensorView[]): void => { | ||
| if (inputs[0].dims.length !== 3) { | ||
| throw new Error('input should have 3 dimensions'); | ||
| } | ||
|
|
||
| if (![2560, 5120, 10240].includes(inputs[0].dims[2])) { | ||
| throw new Error('hidden state should be 2560, 5120 or 10240'); | ||
| } | ||
|
|
||
| if (inputs[1].dims.length !== 1) { | ||
| throw new Error('bias is expected to have 1 dimensions'); | ||
| } | ||
|
|
||
| if (inputs[0].dims[2] !== inputs[1].dims[0]) { | ||
| throw new Error('last dimension of input and bias are not the same'); | ||
| } | ||
| }; | ||
|
|
||
| const createBiasSplitGeluProgramInfo = (metadata: ProgramMetadata, inputs: readonly TensorView[]): ProgramInfo => { | ||
| const outputShape = inputs[0].dims.slice(); | ||
| outputShape[2] = outputShape[2] / 2; | ||
|
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| const input = inputVariable('input', inputs[0].dataType, inputs[0].dims, 4); | ||
| const bias = inputVariable('bias', inputs[0].dataType, [inputs[0].dims[2]], 4); | ||
| const output = outputVariable('output', inputs[0].dataType, outputShape, 4); | ||
|
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| const outputSize = ShapeUtil.size(outputShape) / 4; | ||
|
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| const getShaderSource = (shaderHelper: ShaderHelper) => ` | ||
| const M_SQRT2 = sqrt(2.0); | ||
| const halfChannels = ${inputs[0].dims[2] / 4 / 2}u; | ||
| ${shaderHelper.declareVariables(input, bias, output)} | ||
| ${erfImpl('vec4f')} | ||
| ${shaderHelper.mainStart()} | ||
| ${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(outputSize)} | ||
| let biasIdx = global_idx % halfChannels; | ||
| let batchIndex = global_idx / halfChannels; | ||
| let inputOffset = biasIdx + batchIndex * halfChannels * 2; | ||
| let valueLeft = input[inputOffset] + bias[biasIdx]; | ||
| let valueRight = input[inputOffset + halfChannels] + bias[biasIdx + halfChannels]; | ||
| let geluRight = valueRight * 0.5 * (erf_vf32(valueRight / M_SQRT2) + 1); | ||
| ${output.setByOffset('global_idx', 'valueLeft * geluRight')} | ||
| }`; | ||
|
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| return { | ||
| ...metadata, | ||
| outputs: [{dims: outputShape, dataType: inputs[0].dataType, gpuDataType: GpuDataType.default}], | ||
| getShaderSource, | ||
| dispatchGroup: () => ({x: Math.ceil(outputSize / 64 /* workgroup size */)}) | ||
| }; | ||
| }; | ||
|
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| export const biasSplitGelu = (context: ComputeContext): void => { | ||
| validateInputs(context.inputs); | ||
|
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| const metadata = { | ||
| name: 'BiasSplitGelu', | ||
| inputTypes: [GpuDataType.default, GpuDataType.default], | ||
| }; | ||
|
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| context.compute(createBiasSplitGeluProgramInfo(metadata, context.inputs)); | ||
| }; |
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