public static TensorFlowMapper Create(IHostEnvironment env, ModelLoadContext ctx, ISchema schema)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(ctx, nameof(ctx));
ctx.CheckAtModel(GetVersionInfo());
var numInputs = ctx.Reader.ReadInt32();
Contracts.CheckDecode(numInputs > 0);
string[] source = new string[numInputs];
for (int j = 0; j < source.Length; j++)
{
source[j] = ctx.LoadNonEmptyString();
}
byte[] data = null;
if (!ctx.TryLoadBinaryStream("TFModel", r => data = r.ReadByteArray()))
{
throw env.ExceptDecode();
}
var outputColName = ctx.LoadNonEmptyString();
return(new TensorFlowMapper(env, schema, data, source, outputColName));
}
// Factory method for SignatureLoadModel.
private static OnnxTransform Create(IHostEnvironment env, ModelLoadContext ctx)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(ctx, nameof(ctx));
ctx.CheckAtModel(GetVersionInfo());
byte[] modelBytes = null;
if (!ctx.TryLoadBinaryStream("OnnxModel", r => modelBytes = r.ReadByteArray()))
throw env.ExceptDecode();
bool supportsMultiInputOutput = ctx.Header.ModelVerWritten > 0x00010001;
var numInputs = (supportsMultiInputOutput) ? ctx.Reader.ReadInt32() : 1;
env.CheckDecode(numInputs > 0);
var inputs = new string[numInputs];
for (int j = 0; j < inputs.Length; j++)
inputs[j] = ctx.LoadNonEmptyString();
var numOutputs = (supportsMultiInputOutput) ? ctx.Reader.ReadInt32() : 1;
env.CheckDecode(numOutputs > 0);
var outputs = new string[numOutputs];
for (int j = 0; j < outputs.Length; j++)
outputs[j] = ctx.LoadNonEmptyString();
var args = new Arguments() { InputColumns = inputs, OutputColumns = outputs };
return new OnnxTransform(env, args, modelBytes);
}
// Factory method for SignatureLoadModel.
private static OnnxTransformer Create(IHostEnvironment env, ModelLoadContext ctx)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(ctx, nameof(ctx));
ctx.CheckAtModel(GetVersionInfo());
byte[] modelBytes = null;
if (!ctx.TryLoadBinaryStream("OnnxModel", r => modelBytes = r.ReadByteArray()))
{
throw env.ExceptDecode();
}
bool supportsMultiInputOutput = ctx.Header.ModelVerWritten > 0x00010001;
var numInputs = (supportsMultiInputOutput) ? ctx.Reader.ReadInt32() : 1;
env.CheckDecode(numInputs > 0);
var inputs = new string[numInputs];
for (int j = 0; j < inputs.Length; j++)
{
inputs[j] = ctx.LoadNonEmptyString();
}
var numOutputs = (supportsMultiInputOutput) ? ctx.Reader.ReadInt32() : 1;
env.CheckDecode(numOutputs > 0);
var outputs = new string[numOutputs];
for (int j = 0; j < outputs.Length; j++)
{
outputs[j] = ctx.LoadNonEmptyString();
}
// Save custom-provided shapes. Those shapes overwrite shapes loaded from the ONNX model file.
int customShapeInfosLength = ctx.Reader.ReadInt32(); // 0 means no custom shape. Non-zero means count of custom shapes.
CustomShapeInfo[] loadedCustomShapeInfos = null;
if (customShapeInfosLength > 0)
{
loadedCustomShapeInfos = new CustomShapeInfo[customShapeInfosLength];
for (int i = 0; i < customShapeInfosLength; ++i)
{
var name = ctx.LoadNonEmptyString();
var shape = ctx.Reader.ReadIntArray();
loadedCustomShapeInfos[i] = new CustomShapeInfo()
{
Name = name, Shape = shape
};
}
}
var options = new Options()
{
InputColumns = inputs, OutputColumns = outputs, CustomShapeInfos = loadedCustomShapeInfos
};
return(new OnnxTransformer(env, options, modelBytes));
}
private static void CheckBinaryLabel(bool user, IHostEnvironment env, IPredictorModel[] predictors)
{
int classCount = CheckLabelColumn(env, predictors, true);
if (classCount != 2)
{
var error = string.Format("Expected label to have exactly 2 classes, instead has {0}", classCount);
throw user?env.ExceptParam(nameof(predictors), error) : env.ExceptDecode(error);
}
}
/// <summary>
/// Load from the given repository entry using the default loader(s) specified in the header.
/// </summary>
public static void LoadModel <TRes, TSig>(IHostEnvironment env, out TRes result, RepositoryReader rep, Repository.Entry ent, string dir, params object[] extra)
where TRes : class
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(rep, nameof(rep));
if (!TryLoadModel <TRes, TSig>(env, out result, rep, ent, dir, extra))
{
throw env.ExceptDecode("Couldn't load model: '{0}'", dir);
}
}
/// <summary>
/// Load an object from the repository directory.
/// </summary>
public static void LoadModel <TRes, TSig>(IHostEnvironment env, out TRes result, RepositoryReader rep, string dir, params object[] extra)
where TRes : class
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(rep, nameof(rep));
if (!LoadModelOrNull <TRes, TSig>(env, out result, rep, dir, extra))
{
throw env.ExceptDecode("Corrupt model file");
}
env.AssertValue(result);
}
public static Bindings Create(IHostEnvironment env, ModelLoadContext ctx, Schema input, OptionalColumnTransform parent)
{
Contracts.AssertValue(ctx);
Contracts.AssertValue(input);
// *** Binary format ***
// Schema of the data view containing the optional columns
// int: number of added columns
// for each added column
// int: id of output column name
// ColumnType: the type of the column
byte[] buffer = null;
if (!ctx.TryLoadBinaryStream("Schema.idv", r => buffer = r.ReadByteArray()))
{
throw env.ExceptDecode();
}
BinaryLoader loader = null;
var strm = new MemoryStream(buffer, writable: false);
loader = new BinaryLoader(env, new BinaryLoader.Arguments(), strm);
int size = ctx.Reader.ReadInt32();
Contracts.CheckDecode(size > 0);
var saver = new BinarySaver(env, new BinarySaver.Arguments());
var names = new string[size];
var columnTypes = new ColumnType[size];
var srcCols = new int[size];
var srcColsWithOptionalColumn = new int[size];
for (int i = 0; i < size; i++)
{
names[i] = ctx.LoadNonEmptyString();
columnTypes[i] = saver.LoadTypeDescriptionOrNull(ctx.Reader.BaseStream);
int col;
bool success = input.TryGetColumnIndex(names[i], out col);
srcCols[i] = success ? col : -1;
success = loader.Schema.TryGetColumnIndex(names[i], out var colWithOptionalColumn);
env.CheckDecode(success);
srcColsWithOptionalColumn[i] = colWithOptionalColumn;
}
return(new Bindings(parent, columnTypes, srcCols, srcColsWithOptionalColumn, input, loader.Schema, false, names));
}
// 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 ***
// 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
byte[] modelBytes = null;
if (!ctx.TryLoadBinaryStream("TFModel", r => modelBytes = r.ReadByteArray()))
{
throw env.ExceptDecode();
}
var session = TensorFlowUtils.LoadTFSession(env, modelBytes);
var numInputs = ctx.Reader.ReadInt32();
env.CheckDecode(numInputs > 0);
string[] inputs = new string[numInputs];
for (int j = 0; j < inputs.Length; j++)
{
inputs[j] = ctx.LoadNonEmptyString();
}
bool isMultiOutput = ctx.Header.ModelVerReadable >= 0x00010002;
var numOutputs = 1;
if (isMultiOutput)
{
numOutputs = ctx.Reader.ReadInt32();
}
env.CheckDecode(numOutputs > 0);
var outputs = new string[numOutputs];
for (int j = 0; j < outputs.Length; j++)
{
outputs[j] = ctx.LoadNonEmptyString();
}
return(new TensorFlowTransform(env, session, inputs, outputs));
}
// Factory method for SignatureLoadModel.
private static OnnxTransform Create(IHostEnvironment env, ModelLoadContext ctx)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(ctx, nameof(ctx));
ctx.CheckAtModel(GetVersionInfo());
byte[] modelBytes = null;
if (!ctx.TryLoadBinaryStream("OnnxModel", r => modelBytes = r.ReadByteArray()))
{
throw env.ExceptDecode();
}
var inputColumn = ctx.LoadNonEmptyString();
var outputColumn = ctx.LoadNonEmptyString();
var args = new Arguments()
{
InputColumn = inputColumn, OutputColumn = outputColumn
};
return(new OnnxTransform(env, args, modelBytes));
}
// 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;
}
}
