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Model.Compile.cs
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108 lines (86 loc) · 3.34 KB
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using Tensorflow.Keras.ArgsDefinition;
using Tensorflow.Keras.Losses;
using Tensorflow.Keras.Metrics;
using Tensorflow.Keras.Optimizers;
namespace Tensorflow.Keras.Engine
{
public partial class Model
{
LossesContainer compiled_loss;
MetricsContainer compiled_metrics;
public void compile(IOptimizer optimizer,
ILossFunc loss)
{
this.optimizer = optimizer ?? new RMSprop(new RMSpropArgs
{
});
this.loss = loss ?? new MeanSquaredError();
compiled_loss = new LossesContainer(this.loss, output_names: output_names);
compiled_metrics = new MetricsContainer(new string[0], output_names: output_names);
int experimental_steps_per_execution = 1;
_configure_steps_per_execution(experimental_steps_per_execution);
// Initialize cache attrs.
_reset_compile_cache();
_is_compiled = true;
}
public void compile(IOptimizer optimizer,
ILossFunc loss,
string[] metrics)
{
this.optimizer = optimizer ?? new RMSprop(new RMSpropArgs
{
});
this.loss = loss ?? new MeanSquaredError();
compiled_loss = new LossesContainer(this.loss, output_names: output_names);
compiled_metrics = new MetricsContainer(metrics, output_names: output_names);
int experimental_steps_per_execution = 1;
_configure_steps_per_execution(experimental_steps_per_execution);
// Initialize cache attrs.
_reset_compile_cache();
_is_compiled = true;
}
public void compile(string optimizer,
string loss,
string[] metrics)
{
this.optimizer = optimizer switch
{
"rmsprop" => new RMSprop(new RMSpropArgs
{
}),
_ => new RMSprop(new RMSpropArgs
{
})
};
this.loss = loss switch
{
"mse" => new MeanSquaredError(),
"mae" => new MeanAbsoluteError(),
_ => new MeanSquaredError()
};
compiled_loss = new LossesContainer(this.loss, output_names: output_names);
compiled_metrics = new MetricsContainer(metrics, output_names: output_names);
int experimental_steps_per_execution = 1;
_configure_steps_per_execution(experimental_steps_per_execution);
// Initialize cache attrs.
_reset_compile_cache();
_is_compiled = true;
}
public void compile(IOptimizer optimizer,
ILossFunc loss,
IMetricFunc[] metrics)
{
this.optimizer = optimizer ?? new RMSprop(new RMSpropArgs
{
});
this.loss = loss ?? new MeanSquaredError();
compiled_loss = new LossesContainer(this.loss, output_names: output_names);
compiled_metrics = new MetricsContainer(metrics, output_names: output_names);
int experimental_steps_per_execution = 1;
_configure_steps_per_execution(experimental_steps_per_execution);
// Initialize cache attrs.
_reset_compile_cache();
_is_compiled = true;
}
}
}