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fix: remove the reflection in the implemention of Bidirectional #1162

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Jul 29, 2023
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fix: remove the reflection in the implemention of Bidirectional #1162

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31 changes: 20 additions & 11 deletions src/TensorFlowNET.Keras/Layers/Rnn/Bidirectional.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -13,17 +13,17 @@ namespace Tensorflow.Keras.Layers
/// </summary>
public class Bidirectional: Wrapper
{
BidirectionalArgs _args;
RNN _forward_layer;
RNN _backward_layer;
RNN _layer;
bool _support_masking = true;
int _num_constants = 0;
bool _support_masking = true;
bool _return_state;
bool _stateful;
bool _return_sequences;
InputSpec _input_spec;
BidirectionalArgs _args;
RNNArgs _layer_args_copy;
RNN _forward_layer;
RNN _backward_layer;
RNN _layer;
InputSpec _input_spec;
public Bidirectional(BidirectionalArgs args):base(args)
{
_args = args;
Expand Down Expand Up @@ -66,12 +66,16 @@ public Bidirectional(BidirectionalArgs args):base(args)

// Recreate the forward layer from the original layer config, so that it
// will not carry over any state from the layer.
var actualType = _layer.GetType();
if (actualType == typeof(LSTM))
if (_layer is LSTM)
{
var arg = _layer_args_copy as LSTMArgs;
_forward_layer = new LSTM(arg);
}
else if(_layer is SimpleRNN)
{
var arg = _layer_args_copy as SimpleRNNArgs;
_forward_layer = new SimpleRNN(arg);
}
// TODO(Wanglongzhi2001), add GRU if case.
else
{
Expand Down Expand Up @@ -154,12 +158,18 @@ private RNN _recreate_layer_from_config(RNN layer, bool go_backwards = false)
{
config.GoBackwards = !config.GoBackwards;
}
var actualType = layer.GetType();
if (actualType == typeof(LSTM))

if (layer is LSTM)
{
var arg = config as LSTMArgs;
return new LSTM(arg);
}
else if(layer is SimpleRNN)
{
var arg = config as SimpleRNNArgs;
return new SimpleRNN(arg);
}
// TODO(Wanglongzhi2001), add GRU if case.
else
{
return new RNN(cell, config);
Expand All @@ -183,7 +193,6 @@ public override void build(KerasShapesWrapper input_shape)
protected override Tensors Call(Tensors inputs, Tensors state = null, bool? training = null, IOptionalArgs? optional_args = null)
{
// `Bidirectional.call` implements the same API as the wrapped `RNN`.

Tensors forward_inputs;
Tensors backward_inputs;
Tensors forward_state;
Expand Down