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Implemented support for loading Concatenate layers · MSavameri/TensorFlow.NET@93a242c · GitHub

/ TensorFlow.NET Public
forked from SciSharp/TensorFlow.NET

Commit 93a242c

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Jucko13
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Implemented support for loading Concatenate layers
model.load_model now supports loading of concatenate layers. python tensorflow exports concatenate layers in an extra nested array in the manifest so added a check for that in generic_utils.cs. Concatenate was missing the build=true, this fix prevents the layer being build multiple times. Concatenate has 2 or more input nodes so List<NodeConfig> was required instead of just NodeConfig in Functional.FromConfig.cs. Added missing axis JsonProperty attribute for MergeArgs (used by Concatenate)
1 parent 090dc1e commit 93a242c

4 files changed

Lines changed: 35 additions & 15 deletions

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‎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;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras.ArgsDefinition
67
{
78
// TODO: complete the implementation
8-
public class MergeArgs : LayerArgs
9+
public class MergeArgs : AutoSerializeLayerArgs
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{
1011
public Tensors Inputs { get; set; }
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[JsonProperty("axis")]
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public int Axis { get; set; }
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}
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}

‎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>();
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var node_index_map = new Dictionary<(string, int), int>();
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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>>();
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// First, we create all layers and enqueue nodes to be processed
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foreach (var layer_data in config.Layers)
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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
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static void process_layer(Dictionary<string, ILayer> created_layers,
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LayerConfig layer_data,
82-
Dictionary<ILayer, NodeConfig> unprocessed_nodes,
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Dictionary<ILayer, List<NodeConfig>> unprocessed_nodes,
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Dictionary<ILayer, int> node_count_by_layer)
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{
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ILayer layer = null;
@@ -92,32 +92,38 @@ static void process_layer(Dictionary<string, ILayer> created_layers,
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9393
created_layers[layer_name] = layer;
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}
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);
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var inbound_nodes_data = layer_data.InboundNodes;
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foreach (var node_data in inbound_nodes_data)
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{
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if (!unprocessed_nodes.ContainsKey(layer))
101-
unprocessed_nodes[layer] = node_data;
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unprocessed_nodes[layer] = new List<NodeConfig>() { node_data };
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else
103-
unprocessed_nodes.Add(layer, node_data);
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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,
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Dictionary<string, ILayer> created_layers,
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Dictionary<ILayer, int> node_count_by_layer,
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Dictionary<(string, int), int> node_index_map)
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{
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var input_tensors = new List<Tensor>();
114-
var inbound_layer_name = node_data.Name;
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var inbound_node_index = node_data.NodeIndex;
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var inbound_tensor_index = node_data.TensorIndex;
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118-
var inbound_layer = created_layers[inbound_layer_name];
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var inbound_node = inbound_layer.InboundNodes[inbound_node_index];
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input_tensors.Add(inbound_node.Outputs[inbound_node_index]);
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for (int i = 0; i < nodes_data.Count; i++)
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{
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var node_data = nodes_data[i];
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var inbound_layer_name = node_data.Name;
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var inbound_node_index = node_data.NodeIndex;
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var inbound_tensor_index = node_data.TensorIndex;
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var inbound_layer = created_layers[inbound_layer_name];
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var inbound_node = inbound_layer.InboundNodes[inbound_node_index];
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input_tensors.Add(inbound_node.Outputs[inbound_node_index]);
126+
}
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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)
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shape_set.Add(shape);
4040
}*/
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_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>>();

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