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Merge pull request #1192 from Jucko13/master
fix: Implemented support for loading models with Concatenate layers
2 parents 090dc1e + 9f0ffa4 commit 9e3654b

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+97
-20
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7 files changed

+97
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lines changed

‎src/TensorFlowNET.Core/Keras/ArgsDefinition/Merging/MergeArgs.cs‎

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,13 +1,15 @@
1-
using System;
1+
using Newtonsoft.Json;
2+
using System;
23
using System.Collections.Generic;
34
using System.Text;
45

56
namespace Tensorflow.Keras.ArgsDefinition
67
{
78
// TODO: complete the implementation
8-
public class MergeArgs : LayerArgs
9+
public class MergeArgs : AutoSerializeLayerArgs
910
{
1011
public Tensors Inputs { get; set; }
12+
[JsonProperty("axis")]
1113
public int Axis { get; set; }
1214
}
1315
}

‎src/TensorFlowNET.Core/NumPy/Numpy.Manipulation.cs‎

Lines changed: 9 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -30,6 +30,15 @@ public static NDArray concatenate((NDArray, NDArray) tuple, int axis = 0)
3030
[AutoNumPy]
3131
public static NDArray stack(params NDArray[] arrays) => new NDArray(array_ops.stack(arrays));
3232

33+
[AutoNumPy]
34+
public static NDArray stack(NDArray[] arrays, int axis = 0) => new NDArray(array_ops.stack(arrays, axis));
35+
36+
[AutoNumPy]
37+
public static NDArray stack((NDArray, NDArray) tuple, int axis = 0) => new NDArray(array_ops.stack(new[] { tuple.Item1, tuple.Item2 }, axis));
38+
39+
[AutoNumPy]
40+
public static NDArray stack((NDArray, NDArray, NDArray) tuple, int axis = 0) => new NDArray(array_ops.stack(new[] { tuple.Item1, tuple.Item2, tuple.Item3 }, axis));
41+
3342
[AutoNumPy]
3443
public static NDArray moveaxis(NDArray array, Axis source, Axis destination) => new NDArray(array_ops.moveaxis(array, source, destination));
3544
}

‎src/TensorFlowNET.Keras/Engine/Functional.FromConfig.cs‎

Lines changed: 18 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -30,7 +30,7 @@ public static (Tensors, Tensors, Dictionary<string, ILayer>) reconstruct_from_co
3030
created_layers = created_layers ?? new Dictionary<string, ILayer>();
3131
var node_index_map = new Dictionary<(string, int), int>();
3232
var node_count_by_layer = new Dictionary<ILayer, int>();
33-
var unprocessed_nodes = new Dictionary<ILayer, NodeConfig>();
33+
var unprocessed_nodes = new Dictionary<ILayer, List<NodeConfig>>();
3434
// First, we create all layers and enqueue nodes to be processed
3535
foreach (var layer_data in config.Layers)
3636
process_layer(created_layers, layer_data, unprocessed_nodes, node_count_by_layer);
@@ -79,7 +79,7 @@ public static (Tensors, Tensors, Dictionary<string, ILayer>) reconstruct_from_co
7979

8080
static void process_layer(Dictionary<string, ILayer> created_layers,
8181
LayerConfig layer_data,
82-
Dictionary<ILayer, NodeConfig> unprocessed_nodes,
82+
Dictionary<ILayer, List<NodeConfig>> unprocessed_nodes,
8383
Dictionary<ILayer, int> node_count_by_layer)
8484
{
8585
ILayer layer = null;
@@ -92,32 +92,38 @@ static void process_layer(Dictionary<string, ILayer> created_layers,
9292

9393
created_layers[layer_name] = layer;
9494
}
95-
node_count_by_layer[layer] = _should_skip_first_node(layer) ? 1 : 0;
95+
node_count_by_layer[layer] = layer_data.InboundNodes.Count - (_should_skip_first_node(layer) ? 1 : 0);
9696

9797
var inbound_nodes_data = layer_data.InboundNodes;
9898
foreach (var node_data in inbound_nodes_data)
9999
{
100100
if (!unprocessed_nodes.ContainsKey(layer))
101-
unprocessed_nodes[layer] = node_data;
101+
unprocessed_nodes[layer] = new List<NodeConfig>() { node_data };
102102
else
103-
unprocessed_nodes.Add(layer, node_data);
103+
unprocessed_nodes[layer].Add(node_data);
104104
}
105105
}
106106

107107
static void process_node(ILayer layer,
108-
NodeConfig node_data,
108+
List<NodeConfig> nodes_data,
109109
Dictionary<string, ILayer> created_layers,
110110
Dictionary<ILayer, int> node_count_by_layer,
111111
Dictionary<(string, int), int> node_index_map)
112112
{
113+
113114
var input_tensors = new List<Tensor>();
114-
var inbound_layer_name = node_data.Name;
115-
var inbound_node_index = node_data.NodeIndex;
116-
var inbound_tensor_index = node_data.TensorIndex;
117115

118-
var inbound_layer = created_layers[inbound_layer_name];
119-
var inbound_node = inbound_layer.InboundNodes[inbound_node_index];
120-
input_tensors.Add(inbound_node.Outputs[inbound_node_index]);
116+
for (int i = 0; i < nodes_data.Count; i++)
117+
{
118+
var node_data = nodes_data[i];
119+
var inbound_layer_name = node_data.Name;
120+
var inbound_node_index = node_data.NodeIndex;
121+
var inbound_tensor_index = node_data.TensorIndex;
122+
123+
var inbound_layer = created_layers[inbound_layer_name];
124+
var inbound_node = inbound_layer.InboundNodes[inbound_node_index];
125+
input_tensors.Add(inbound_node.Outputs[inbound_node_index]);
126+
}
121127

122128
var output_tensors = layer.Apply(input_tensors);
123129

‎src/TensorFlowNET.Keras/Layers/Merging/Concatenate.cs‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -39,6 +39,7 @@ public override void build(KerasShapesWrapper input_shape)
3939
shape_set.Add(shape);
4040
}*/
4141
_buildInputShape = input_shape;
42+
built = true;
4243
}
4344

4445
protected override Tensors _merge_function(Tensors inputs)

‎src/TensorFlowNET.Keras/Utils/generic_utils.cs‎

Lines changed: 12 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -112,12 +112,23 @@ public static FunctionalConfig deserialize_model_config(JToken json)
112112
foreach (var token in layersToken)
113113
{
114114
var args = deserialize_layer_args(token["class_name"].ToObject<string>(), token["config"]);
115+
116+
List<NodeConfig> nodeConfig = null; //python tensorflow sometimes exports inbound nodes in an extra nested array
117+
if (token["inbound_nodes"].Count() > 0 && token["inbound_nodes"][0].Count() > 0 && token["inbound_nodes"][0][0].Count() > 0)
118+
{
119+
nodeConfig = token["inbound_nodes"].ToObject<List<List<NodeConfig>>>().FirstOrDefault() ?? new List<NodeConfig>();
120+
}
121+
else
122+
{
123+
nodeConfig = token["inbound_nodes"].ToObject<List<NodeConfig>>();
124+
}
125+
115126
config.Layers.Add(new LayerConfig()
116127
{
117128
Config = args,
118129
Name = token["name"].ToObject<string>(),
119130
ClassName = token["class_name"].ToObject<string>(),
120-
InboundNodes = token["inbound_nodes"].ToObject<List<NodeConfig>>()
131+
InboundNodes = nodeConfig,
121132
});
122133
}
123134
config.InputLayers = json["input_layers"].ToObject<List<NodeConfig>>();

‎test/TensorFlowNET.Keras.UnitTest/Layers/Layers.Merging.Test.cs‎

Lines changed: 10 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,5 @@
11
using Microsoft.VisualStudio.TestTools.UnitTesting;
2+
using System.Collections.Generic;
23
using Tensorflow.NumPy;
34
using static Tensorflow.KerasApi;
45

@@ -8,12 +9,16 @@ namespace Tensorflow.Keras.UnitTest.Layers
89
public class LayersMergingTest : EagerModeTestBase
910
{
1011
[TestMethod]
11-
public void Concatenate()
12+
[DataRow(1, 4, 1, 5)]
13+
[DataRow(2, 2, 2, 5)]
14+
[DataRow(3, 2, 1, 10)]
15+
public void Concatenate(int axis, int shapeA, int shapeB, int shapeC)
1216
{
13-
var x = np.arange(20).reshape((2, 2, 5));
14-
var y = np.arange(20, 30).reshape((2, 1, 5));
15-
var z = keras.layers.Concatenate(axis: 1).Apply(new Tensors(x, y));
16-
Assert.AreEqual((2, 3, 5), z.shape);
17+
var x = np.arange(10).reshape((1, 2, 1, 5));
18+
var y = np.arange(10, 20).reshape((1, 2, 1, 5));
19+
var z = keras.layers.Concatenate(axis: axis).Apply(new Tensors(x, y));
20+
Assert.AreEqual((1, shapeA, shapeB, shapeC), z.shape);
1721
}
22+
1823
}
1924
}

‎test/TensorFlowNET.Keras.UnitTest/Model/ModelLoadTest.cs‎

Lines changed: 43 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,10 +1,13 @@
11
using Microsoft.VisualStudio.TestPlatform.Utilities;
22
using Microsoft.VisualStudio.TestTools.UnitTesting;
3+
using Newtonsoft.Json.Linq;
34
using System.Linq;
5+
using System.Xml.Linq;
46
using Tensorflow.Keras.Engine;
57
using Tensorflow.Keras.Optimizers;
68
using Tensorflow.Keras.UnitTest.Helpers;
79
using Tensorflow.NumPy;
10+
using static HDF.PInvoke.H5Z;
811
using static Tensorflow.Binding;
912
using static Tensorflow.KerasApi;
1013

@@ -124,4 +127,44 @@ public void TestModelBeforeTF2_5()
124127
var model = tf.saved_model.load(@"D:\development\temp\saved_model") as Tensorflow.Keras.Engine.Model;
125128
model.summary();
126129
}
130+
131+
132+
133+
[TestMethod]
134+
public void CreateConcatenateModelSaveAndLoad()
135+
{
136+
// a small demo model that is just here to see if the axis value for the concatenate method is saved and loaded.
137+
var input_layer = tf.keras.layers.Input((8, 8, 5));
138+
139+
var conv1 = tf.keras.layers.Conv2D(2, kernel_size: 3, activation: "relu", padding: "same"/*, data_format: "_conv_1"*/).Apply(input_layer);
140+
conv1.Name = "conv1";
141+
142+
var conv2 = tf.keras.layers.Conv2D(2, kernel_size: 3, activation: "relu", padding: "same"/*, data_format: "_conv_2"*/).Apply(input_layer);
143+
conv2.Name = "conv2";
144+
145+
var concat1 = tf.keras.layers.Concatenate(axis: 3).Apply((conv1, conv2));
146+
concat1.Name = "concat1";
147+
148+
var model = tf.keras.Model(input_layer, concat1);
149+
model.compile(tf.keras.optimizers.Adam(), tf.keras.losses.CategoricalCrossentropy());
150+
151+
model.save(@"Assets/concat_axis3_model");
152+
153+
154+
var tensorInput = np.arange(320).reshape((1, 8, 8, 5)).astype(TF_DataType.TF_FLOAT);
155+
156+
var tensors1 = model.predict(tensorInput);
157+
158+
Assert.AreEqual((1, 8, 8, 4), tensors1.shape);
159+
160+
model = null;
161+
keras.backend.clear_session();
162+
163+
var model2 = tf.keras.models.load_model(@"Assets/concat_axis3_model");
164+
165+
var tensors2 = model2.predict(tensorInput);
166+
167+
Assert.AreEqual(tensors1.shape, tensors2.shape);
168+
}
169+
127170
}

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