8000 Support the multiple inputs of keras model.fit. by AsakusaRinne · Pull Request #996 · SciSharp/TensorFlow.NET · GitHub
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Support the multiple inputs of keras model.fit. #996

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Merged
merged 5 commits into from
Mar 4, 2023
Merged

Support the multiple inputs of keras model.fit. #996

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c2f463f
Support the multiple inputs of keras model.fit.
AsakusaRinne Mar 4, 2023
3cd01f4
GradientTest inherts from EagerModeTestBase.
Oceania2018 Mar 4, 2023
6a295b6
Add more explicit conversion for Tensors.
AsakusaRinne Mar 4, 2023
718af97
Merge branch 'fix_939' of github.com:AsakusaRinne/TensorFlow.NET into…
AsakusaRinne Mar 4, 2023
bebf9b4
Resolve the comment.
AsakusaRinne Mar 4, 2023
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8 changes: 6 additions & 2 deletions src/TensorFlowNET.Core/Data/DatasetV2.cs
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Expand Up @@ -19,6 +19,8 @@ public class DatasetV2 : IDatasetV2

public TensorSpec[] structure { get; set; }

public int FirstInputTensorCount { get; set; } = 1;

public Shape[] output_shapes => structure.Select(x => x.shape).ToArray();

public TF_DataType[] output_types => structure.Select(x => x.dtype).ToArray();
Expand Down Expand Up @@ -131,6 +133,7 @@ public IDatasetV2 apply_options()

// (4) Apply stats aggregator options

dataset.FirstInputTensorCount = this.FirstInputTensorCount;
return dataset;
}

Expand All @@ -142,7 +145,7 @@ public override string ToString()
$"types: {string.Join(", ", structure.Select(x => "tf." + x.dtype.as_numpy_name()))}, " +
$"len: {length}";

public IEnumerator<(Tensor, Tensor)> GetEnumerator()
public IEnumerator<(Tensors, Tensors)> GetEnumerator()
{
using var ownedIterator = new OwnedIterator(this);

Expand All @@ -158,7 +161,8 @@ public override string ToString()
break;
}

yield return (results[0], results.Length == 1 ? null : results[1]);
yield return (new Tensors(results.Take(FirstInputTensorCount)), results.Length == FirstInputTensorCount ?
null : new Tensors(results.Skip(FirstInputTensorCount)));
}
}

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4 changes: 3 additions & 1 deletion src/TensorFlowNET.Core/Data/IDatasetV2.cs
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Expand Up @@ -4,7 +4,7 @@

namespace Tensorflow
{
public interface IDatasetV2 : IEnumerable<(Tensor, Tensor)>
public interface IDatasetV2 : IEnumerable<(Tensors, Tensors)>
{
string[] class_names { get; set; }

Expand All @@ -18,6 +18,8 @@ public interface IDatasetV2 : IEnumerable<(Tensor, Tensor)>

TensorSpec[] structure { get; set; }

int FirstInputTensorCount { get; set; }

/// <summary>
/// Caches the elements in this dataset.
/// </summary>
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5 changes: 3 additions & 2 deletions src/TensorFlowNET.Core/Data/OwnedIterator.cs
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Expand Up @@ -27,7 +27,8 @@ void _create_iterator(IDatasetV2 dataset)
_dataset = dataset;
_element_spec = dataset.element_spec;
// _flat_output_types =
(_iterator_resource, _deleter) = ops.anonymous_iterator_v2(_dataset.output_types, _dataset.output_shapes);
_iterator_resource = ops.anonymous_iterator_v3(_dataset.output_types, _dataset.output_shapes);
// TODO(Rinne): deal with graph mode.
ops.make_iterator(dataset.variant_tensor, _iterator_resource);
}

Expand All @@ -48,7 +49,7 @@ public Tensor[] next()

public void Dispose()
{
tf.Runner.Execute(tf.Context, "DeleteIterator", 0, new[] { _iterator_resource, _deleter }, null);
//tf.Runner.Execute(tf.Context, "DeleteIterator", 0, new[] { _iterator_resource, _deleter }, null);
}
}
}
4 changes: 2 additions & 2 deletions src/TensorFlowNET.Core/Keras/ArgsDefinition/DataAdapterArgs.cs
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Expand Up @@ -5,8 +5,8 @@ namespace Tensorflow.Keras.ArgsDefinition
{
public class DataAdapterArgs: IKerasConfig
{
public Tensor X { get; set; }
public Tensor Y { get; set; }
public Tensors X { get; set; }
public Tensors Y { get; set; }
public IDatasetV2 Dataset { get; set; }
public int BatchSize { get; set; } = 32;
public int Steps { get; set; }
Expand Down
4 changes: 2 additions & 2 deletions src/TensorFlowNET.Core/Keras/ArgsDefinition/DataHandlerArgs.cs
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Expand Up @@ -5,8 +5,8 @@ namespace Tensorflow.Keras.ArgsDefinition
{
public class DataHandlerArgs: IKerasConfig
{
public Tensor X { get; set; }
public Tensor Y { get; set; }
public Tensors X { get; set; }
public Tensors Y { get; set; }
public IDatasetV2 Dataset { get; set; }
public int BatchSize { get; set; } = 32;
public int StepsPerEpoch { get; set; } = -1;
Expand Down
11 changes: 11 additions & 0 deletions src/TensorFlowNET.Core/Keras/Engine/IModel.cs
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Expand Up @@ -24,6 +24,17 @@ ICallback fit(NDArray x, NDArray y,
int workers = 1,
bool use_multiprocessing = false);

ICallback fit(IEnumerable<NDArray> x, NDArray y,
int batch_size = -1,
int epochs = 1,
int verbose = 1,
float validation_split = 0f,
bool shuffle = true,
int initial_epoch = 0,
int max_queue_size = 10,
int workers = 1,
bool use_multiprocessing = false);

void save(string filepath,
bool overwrite = true,
bool include_optimizer = true,
Expand Down
71 changes: 70 additions & 1 deletion src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
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Expand Up @@ -14,7 +14,76 @@ public void Deconstruct(out byte blue, out byte green, out byte red)
red = data[2];
}

public static implicit operator NDArray(Array array)
public static implicit operator NDArray(int[] array)
=> new NDArray(array);

public static implicit operator NDArray(byte[] array)
=> new NDArray(array);

public static implicit operator NDArray(float[] array)
=> new NDArray(array);

public static implicit operator NDArray(double[] array)
=> new NDArray(array);

public static implicit operator NDArray(long[] array)
=> new NDArray(array);

public static implicit operator NDArray(bool[] array)
=> new NDArray(array);

public static implicit operator NDArray(uint[] array)
=> new NDArray(array);

public static implicit operator NDArray(ulong[] array)
=> new NDArray(array);

public static implicit operator NDArray(int[,] array)
=> new NDArray(array);

public static implicit operator NDArray(byte[,] array)
=> new NDArray(array);

public static implicit operator NDArray(float[,] array)
=> new NDArray(array);

public static implicit operator NDArray(double[,] array)
=> new NDArray(array);

public static implicit operator NDArray(long[,] array)
=> new NDArray(array);

public static implicit operator NDArray(bool[,] array)
=> new NDArray(array);

public static implicit operator NDArray(uint[,] array)
=> new NDArray(array);

public static implicit operator NDArray(ulong[,] array)
=> new NDArray(array);

public static implicit operator NDArray(int[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(byte[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(float[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(double[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(long[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(bool[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(uint[,,] array)
=> new NDArray(array);

public static implicit operator NDArray(ulong[,,] array)
=> new NDArray(array);

public unsafe static implicit operator bool(NDArray nd)
Expand Down
2 changes: 1 addition & 1 deletion src/TensorFlowNET.Core/NumPy/Persistence/NpzDictionaryArray.cs
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Expand Up @@ -25,7 +25,7 @@ private NDArray OpenEntry(ZipArchiveEntry entry)
return array;

using var s = entry.Open();
return LoadMatrix(s);
return (NDArray)LoadMatrix(s);
}

public Array LoadMatrix(Stream stream)
Expand Down
3 changes: 3 additions & 0 deletions src/TensorFlowNET.Core/Numpy/NDArray.cs
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Expand Up @@ -49,5 +49,8 @@ public IEnumerator<NDArray> GetEnumerator()

IEnumerator IEnumerable.GetEnumerator()
=> GetEnumerator();

public static explicit operator NDArray(Array array)
=> new NDArray(array);
}
}
34 changes: 34 additions & 0 deletions src/TensorFlowNET.Core/Operations/dataset_ops.cs
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@@ -1,6 +1,9 @@
using System;
using Tensorflow.Contexts;
using Tensorflow.Eager;
using Tensorflow.Framework.Models;
using Tensorflow.Functions;
using Tensorflow.Operations;
using static Tensorflow.Binding;

namespace Tensorflow
Expand Down Expand Up @@ -220,6 +223,37 @@ public Tensor model_dataset(Tensor input_dataset,
return (results[0], results[1]);
}

public Tensor anonymous_iterator_v3(TF_DataType[] output_types, Shape[] output_shapes, string name = null)
{
var ctx = tf.Context;
Dictionary<string, object> attrs = new();
attrs["output_types"] = output_types;
attrs["output_shapes"] = output_shapes;
if (ctx.executing_eagerly())
{
try
{
var result = tf.Runner.TFE_FastPathExecute(new FastPathOpExecInfo("AnonymousIteratorV3", name)
{
attrs = attrs
});
return result[0];
}
catch (Exception)
{
return anonymous_iterator_v3_eager_fallback(output_types, output_shapes, name, ctx);
}
}
return tf.OpDefLib._apply_op_helper("AnonymousIteratorV3", name, attrs).outputs[0];
}

public Tensor anonymous_iterator_v3_eager_fallback(TF_DataType[] output_types, Shape[] output_shapes, string name, Context ctx)
{
object[] attrs = new object[] { output_types, output_shapes };
var result = execute.quick_execute("AnonymousIteratorV3", 1, new Tensor[] { }, attrs, ctx, name);
return result[0];
}

/// <summary>
/// Makes a new iterator from the given `dataset` and stores it in `iterator`.
/// </summary>
Expand Down
18 changes: 12 additions & 6 deletions src/TensorFlowNET.Keras/Engine/DataAdapters/DataAdapter.cs
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Expand Up @@ -10,7 +10,7 @@ public abstract class DataAdapter
protected DataAdapterArgs args;
protected IDatasetV2 dataset;

public virtual bool CanHandle(Tensor x, Tensor y = null)
public virtual bool CanHandle(Tensors x, Tensors y = null)
=> throw new NotImplementedException();

public virtual IDatasetV2 GetDataset()
Expand All @@ -19,12 +19,18 @@ public virtual IDatasetV2 GetDataset()
public virtual int GetSize()
=> throw new NotImplementedException("");

public virtual (Tensor, Tensor) Expand1d(Tensor x, Tensor y)
public virtual (Tensors, Tensors) Expand1d(Tensors x, Tensors y)
{
if (x.shape.ndim == 1)
x = array_ops.expand_dims(x, axis: -1);
if (y.shape.ndim == 1)
y = array_ops.expand_dims(y, axis: -1);
for(int i = 0; i < x.Length; i++)
{
if (x[i].shape.ndim == 1)
x[i] = array_ops.expand_dims(x[i], axis: -1);
}
for (int i = 0; i < y.Length; i++)
{
if (y[i].shape.ndim == 1)
y[i] = array_ops.expand_dims(y[i], axis: -1);
}
return (x, y);
}

Expand Down
6 changes: 5 additions & 1 deletion src/TensorFlowNET.Keras/Engine/DataAdapters/DataHandler.cs
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Expand Up @@ -93,11 +93,15 @@ long _infer_steps(int steps_per_epoch, IDatasetV2 dataset)

public IEnumerable<(int, OwnedIterator)> enumerate_epochs()
{
var data_iterator = new OwnedIterator(_dataset);
foreach (var epoch in range(_initial_epoch, _epochs))
{
if (_insufficient_data)
break;
using var data_iterator = new OwnedIterator(_dataset);
if (_adapter.ShouldRecreateIterator())
{
data_iterator = new OwnedIterator(_dataset);
}
yield return (epoch, data_iterator);
}
// _adapter.on_epoch_end()
Expand Down
4 changes: 2 additions & 2 deletions src/TensorFlowNET.Keras/Engine/DataAdapters/IDataAdapter.cs
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Expand Up @@ -13,10 +13,10 @@ public interface IDataAdapter
/// <param name="x">input features</param>
/// <param name="y">target labels</param>
/// <returns></returns>
bool CanHandle(Tensor x, Tensor y = null);
bool CanHandle(Tensors x, Tensors y = null);
IDatasetV2 GetDataset();
int GetSize();
(Tensor, Tensor) Expand1d(Tensor x, Tensor y);
(Tensors, Tensors) Expand1d(Tensors x, Tensors y);
bool ShouldRecreateIterator();
}
}
13 changes: 8 additions & 5 deletions 13 src/TensorFlowNET.Keras/Engine/DataAdapters/TensorLikeDataAdapter.cs
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@@ -1,4 +1,5 @@
using System;
using System.Diagnostics;
using System.Linq;
using Tensorflow.Keras.ArgsDefinition;
using static Tensorflow.Binding;
Expand All @@ -20,7 +21,7 @@ public TensorLikeDataAdapter(DataAdapterArgs args)
{
this.args = args;
_process_tensorlike();
num_samples = (int)args.X.shape[0];
num_samples = (int)args.X[0].shape[0];
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Can we use (int)args.X.shape[0] instead of (int)args.X[0].shape[0]?

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Sure, I have changed it.

var batch_size = args.BatchSize == -1 ? 32 : args.BatchSize;
_batch_size = batch_size;
_size = Convert.ToInt32(Math.Ceiling(num_samples / (batch_size + 0.0f)));
Expand All @@ -33,10 +34,11 @@ public TensorLikeDataAdapter(DataAdapterArgs args)
indices_dataset = indices_dataset.flat_map(slice_batch_indices);
var inputs = new Tensors();
if (args.X != null)
inputs.Add(args.X);
inputs.AddRange(args.X);
if (args.Y != null)
inputs.Add(args.Y);
inputs.AddRange(args.Y);
dataset = slice_inputs(indices_dataset, inputs);
dataset.FirstInputTensorCount = args.X.Length;
}

Tensors permutation(Tensors tensor)
Expand Down Expand Up @@ -87,8 +89,9 @@ IDatasetV2 slice_inputs(IDatasetV2 indices_dataset, Tensors elements)
return dataset.with_options(new DatasetOptions { });
}

public override int GetSize()
=> _size;
public override int GetSize() => _size;

public override bool ShouldRecreateIterator() => false;

void _process_tensorlike()
{
Expand Down
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