mean_absolute_percentage_error

Oceania2018 · Oceania2018 · commit cb7e0170eb49 · 2021-10-17T21:43:45.000-05:00
diff --git a/src/TensorFlowNET.Core/Variables/ResourceVariable.Index.cs b/src/TensorFlowNET.Core/Variables/ResourceVariable.Index.cs
@@ -19,6 +19,7 @@ limitations under the License.
 using System.Collections.Generic;
 using System.Text;
 using static Tensorflow.Binding;
+using System.Linq;
 
 namespace Tensorflow
 {
@@ -62,5 +63,8 @@ public Tensor this[params Slice[] slices]
                 });
             }
         }
+
+        public Tensor this[params string[] slices]
+            => this[slices.Select(x => new Slice(x)).ToArray()];
     }
 }
diff --git a/src/TensorFlowNET.Keras/Engine/MetricsContainer.cs b/src/TensorFlowNET.Keras/Engine/MetricsContainer.cs
@@ -77,9 +77,9 @@ Metric _get_metric_object(string metric, Tensor y_t, Tensor y_p)
                     metric_obj = keras.metrics.categorical_accuracy;
             }
             else if(metric == "mean_absolute_error" || metric == "mae")
-            {
                 metric_obj = keras.metrics.mean_absolute_error;
-            }
+            else if (metric == "mean_absolute_percentage_error" || metric == "mape")
+                metric_obj = keras.metrics.mean_absolute_percentage_error;
             else
                 throw new NotImplementedException("");
 
diff --git a/src/TensorFlowNET.Keras/Engine/Model.Compile.cs b/src/TensorFlowNET.Keras/Engine/Model.Compile.cs
@@ -42,9 +42,10 @@ public void compile(string optimizer, string loss, string[] metrics)
                 _ => throw new NotImplementedException("")
             };
 
-            var _loss = loss switch
+            ILossFunc _loss = loss switch
             {
                 "mse" => new MeanSquaredError(),
+                "mae" => new MeanAbsoluteError(),
                 _ => throw new NotImplementedException("")
             };
 
diff --git a/src/TensorFlowNET.Keras/Metrics/MetricsApi.cs b/src/TensorFlowNET.Keras/Metrics/MetricsApi.cs
@@ -46,5 +46,12 @@ public Tensor mean_absolute_error(Tensor y_true, Tensor y_pred)
             y_true = math_ops.cast(y_true, y_pred.dtype);
             return keras.backend.mean(math_ops.abs(y_pred - y_true), axis: -1);
         }
+
+        public Tensor mean_absolute_percentage_error(Tensor y_true, Tensor y_pred)
+        {
+            y_true = math_ops.cast(y_true, y_pred.dtype);
+            var diff = (y_true - y_pred) / math_ops.maximum(math_ops.abs(y_true), keras.backend.epsilon());
+            return 100f * keras.backend.mean(math_ops.abs(diff), axis: -1);
+        }
     }
 }

Original file line number	Diff line number	Diff line change
`@@ -19,6 +19,7 @@ limitations under the License.`
`19`	`19`	`using System.Collections.Generic;`
`20`	`20`	`using System.Text;`
`21`	`21`	`using static Tensorflow.Binding;`
	`22`	`+using System.Linq;`
`22`	`23`
`23`	`24`	`namespace Tensorflow`
`24`	`25`	`{`
`@@ -62,5 +63,8 @@ public Tensor this[params Slice[] slices]`
`62`	`63`	`});`
`63`	`64`	`}`
`64`	`65`	`}`
	`66`	`+`
	`67`	`+ public Tensor this[params string[] slices]`
	`68`	`+ => this[slices.Select(x => new Slice(x)).ToArray()];`
`65`	`69`	`}`
`66`	`70`	`}`
Original file line number	Diff line number	Diff line change
`@@ -46,5 +46,12 @@ public Tensor mean_absolute_error(Tensor y_true, Tensor y_pred)`
`46`	`46`	`y_true = math_ops.cast(y_true, y_pred.dtype);`
`47`	`47`	`return keras.backend.mean(math_ops.abs(y_pred - y_true), axis: -1);`
`48`	`48`	`}`
	`49`	`+`
	`50`	`+ public Tensor mean_absolute_percentage_error(Tensor y_true, Tensor y_pred)`
	`51`	`+ {`
	`52`	`+ y_true = math_ops.cast(y_true, y_pred.dtype);`
	`53`	`+ var diff = (y_true - y_pred) / math_ops.maximum(math_ops.abs(y_true), keras.backend.epsilon());`
	`54`	`+ return 100f * keras.backend.mean(math_ops.abs(diff), axis: -1);`
	`55`	`+ }`
`49`	`56`	`}`
`50`	`57`	`}`