| File: NasBert\Models\PredictionHead.cs | Web Access |
| Project: src\src\Microsoft.ML.TorchSharp\Microsoft.ML.TorchSharp.csproj (Microsoft.ML.TorchSharp) |
// Licensed to the .NET Foundation under one or more agreements. // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. using Microsoft.ML.TorchSharp.Utils; using TorchSharp; using TorchSharp.Modules; namespace Microsoft.ML.TorchSharp.NasBert.Models { internal sealed class PredictionHead : BaseHead, torch.nn.IModule<torch.Tensor, torch.Tensor> { [System.Diagnostics.CodeAnalysis.SuppressMessage("Naming", "MSML_PrivateFieldName:Private field name not in: _camelCase format", Justification = "Has to match TorchSharp model.")] private readonly Sequential Classifier; private bool _disposedValue; public PredictionHead(int inputDim, int numClasses, double dropoutRate) : base(nameof(PredictionHead)) { var dropoutLayer = torch.nn.Dropout(dropoutRate); var dense = torch.nn.Linear(inputDim, numClasses); ModelUtils.InitXavierUniform(dense.weight); ModelUtils.InitZeros(dense.bias); Classifier = torch.nn.Sequential( ("dropout1", dropoutLayer), ("dense", dense) ); RegisterComponents(); } [System.Diagnostics.CodeAnalysis.SuppressMessage("Naming", "MSML_GeneralName:This name should be PascalCased", Justification = "Need to match TorchSharp")] public torch.Tensor call(torch.Tensor features) { // TODO: try whitening-like techniques // take <s> token (equiv. to [CLS]) using var x = features[torch.TensorIndex.Colon, torch.TensorIndex.Single(0), torch.TensorIndex.Colon]; return Classifier.forward(x); } protected override void Dispose(bool disposing) { if (!_disposedValue) { if (disposing) { Classifier.Dispose(); _disposedValue = true; } } base.Dispose(disposing); } } }