// Factory method for SignatureDataTransform.
private static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(args, nameof(args));
env.CheckValue(input, nameof(input));
env.CheckValue(args.InputColumns, nameof(args.InputColumns));
env.CheckValue(args.OutputColumns, nameof(args.OutputColumns));
return(new TensorFlowTransform(env, TensorFlowUtils.GetSession(env, args.Model), args.InputColumns, args.OutputColumns, TensorFlowUtils.IsSavedModel(env, args.Model) ? args.Model : null, false).MakeDataTransform(input));
}
// Factory method for SignatureLoadModel.
private static TensorFlowTransform Create(IHostEnvironment env, ModelLoadContext ctx)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(ctx, nameof(ctx));
ctx.CheckAtModel(GetVersionInfo());
// *** Binary format ***
// byte: indicator for frozen models
// stream: tensorFlow model.
// int: number of input columns
// for each input column
// int: id of int column name
// int: number of output columns
// for each output column
// int: id of output column name
GetModelInfo(env, ctx, out string[] inputs, out string[] outputs, out bool isFrozen);
if (isFrozen)
{
byte[] modelBytes = null;
if (!ctx.TryLoadBinaryStream("TFModel", r => modelBytes = r.ReadByteArray()))
{
throw env.ExceptDecode();
}
return(new TensorFlowTransform(env, TensorFlowUtils.LoadTFSession(env, modelBytes), inputs, outputs, null, false));
}
var tempDirPath = Path.GetFullPath(Path.Combine(Path.GetTempPath(), RegistrationName + "_" + Guid.NewGuid()));
TensorFlowUtils.CreateFolderWithAclIfNotExists(env, tempDirPath);
try
{
var load = ctx.TryLoadBinaryStream("TFSavedModel", br =>
{
int count = br.ReadInt32();
for (int n = 0; n < count; n++)
{
string relativeFile = br.ReadString();
long fileLength = br.ReadInt64();
string fullFilePath = Path.Combine(tempDirPath, relativeFile);
string fullFileDir = Path.GetDirectoryName(fullFilePath);
if (fullFileDir != tempDirPath)
{
TensorFlowUtils.CreateFolderWithAclIfNotExists(env, fullFileDir);
}
using (var fs = new FileStream(fullFilePath, FileMode.Create, FileAccess.Write))
{
long actualRead = br.BaseStream.CopyRange(fs, fileLength);
env.Assert(actualRead == fileLength);
}
}
});
return(new TensorFlowTransform(env, TensorFlowUtils.GetSession(env, tempDirPath), inputs, outputs, tempDirPath, true));
}
catch (Exception)
{
TensorFlowUtils.DeleteFolderWithRetries(env, tempDirPath);
throw;
}
}
/// <summary>
/// Convenience constructor for public facing API.
/// </summary>
/// <param name="env">Host Environment.</param>
/// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
/// <param name="model">Path to the TensorFlow model. </param>
/// <param name="names">Name of the output column(s). Keep it same as in the Tensorflow model.</param>
/// <param name="source">Name of the input column(s). Keep it same as in the Tensorflow model.</param>
public static IDataTransform Create(IHostEnvironment env, IDataView input, string model, string[] names, string[] source)
{
return(new TensorFlowTransform(env, TensorFlowUtils.GetSession(env, model), source, names, TensorFlowUtils.IsSavedModel(env, model) ? model : null, false).MakeDataTransform(input));
}
public TensorFlowEstimator(IHostEnvironment env, string model, string[] inputs, string[] outputs)
: this(env, new TensorFlowTransform(env, TensorFlowUtils.GetSession(env, model), inputs, outputs, TensorFlowUtils.IsSavedModel(env, model) ? model : null, false))
{
}
