fix name issue in internal_convert_to_tensor._autopacking_helper

Oceania2018 · Oceania2018 · commit e3c5bb7755c4 · 2019-04-10T06:50:14.000-05:00
diff --git a/src/TensorFlowNET.Core/Clustering/KMeans.cs b/src/TensorFlowNET.Core/Clustering/KMeans.cs
@@ -79,9 +79,8 @@ private RefVariable[] _create_variables(Tensor num_clusters)
             else
             {
                 var cluster_centers_updated = cluster_centers;
-                var cluster_counts = _use_mini_batch ?
-                    tf.Variable(array_ops.ones(new Tensor[] { num_clusters }, dtype: TF_DataType.TF_INT64)) : 
-                    null;
+                var ones = array_ops.ones(new Tensor[] { num_clusters }, dtype: TF_DataType.TF_INT64);
+                var cluster_counts = _use_mini_batch ? tf.Variable(ones) : null;
                 return new RefVariable[]
                 {
                     cluster_centers,
diff --git a/src/TensorFlowNET.Core/Operations/array_ops.py.cs b/src/TensorFlowNET.Core/Operations/array_ops.py.cs
@@ -32,6 +32,11 @@ public static Tensor zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_FLOAT
             });
         }
 
+        private static Tensor _constant_if_small(int value, Tensor shape)
+        {
+            return shape < 1000;
+        }
+
         private static Tensor _constant_if_small<T>(T value, Shape shape, TF_DataType dtype, string name)
         {
             Tensor tShape = null;
@@ -167,8 +172,9 @@ public static Tensor ones(Tensor[] shape, TF_DataType dtype = TF_DataType.TF_FLO
             return with(ops.name_scope(name, "ones", new { shape }), scope =>
             {
                 name = scope;
+                var output = _constant_if_small(1, shape[0]);
                 var shape1 = ops.convert_to_tensor(shape, dtype: TF_DataType.TF_INT32);
-                var output = gen_array_ops.fill(shape1, constant_op.constant(1, dtype: dtype), name: name);
+                output = gen_array_ops.fill(shape1, constant_op.constant(1, dtype: dtype), name: name);
                 return output;
             });
         }
diff --git a/src/TensorFlowNET.Core/ops.py.cs b/src/TensorFlowNET.Core/ops.py.cs
@@ -425,7 +425,7 @@ public static Tensor internal_convert_to_tensor(object value, TF_DataType dtype
                 case Tensor tensor:
                     return tensor;
                 case Tensor[] tensors:
-                    return array_ops._autopacking_helper(tensors, dtype, name);
+                    return array_ops._autopacking_helper(tensors, dtype, name == null ? "packed" : name);
                 case RefVariable varVal:
                     return varVal._TensorConversionFunction(as_ref: as_ref);
                 case object[] objects:

Original file line number	Diff line number	Diff line change
`@@ -79,9 +79,8 @@ private RefVariable[] _create_variables(Tensor num_clusters)`
`79`	`79`	`else`
`80`	`80`	`{`
`81`	`81`	`var cluster_centers_updated = cluster_centers;`
`82`		`- var cluster_counts = _use_mini_batch ?`
`83`		`- tf.Variable(array_ops.ones(new Tensor[] { num_clusters }, dtype: TF_DataType.TF_INT64)) :`
`84`		`- null;`
	`82`	`+ var ones = array_ops.ones(new Tensor[] { num_clusters }, dtype: TF_DataType.TF_INT64);`
	`83`	`+ var cluster_counts = _use_mini_batch ? tf.Variable(ones) : null;`
`85`	`84`	`return new RefVariable[]`
`86`	`85`	`{`
`87`	`86`	`cluster_centers,`
Original file line number	Diff line number	Diff line change
`@@ -32,6 +32,11 @@ public static Tensor zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_FLOAT`
`32`	`32`	`});`
`33`	`33`	`}`
`34`	`34`
	`35`	`+ private static Tensor _constant_if_small(int value, Tensor shape)`
	`36`	`+ {`
	`37`	`+ return shape < 1000;`
	`38`	`+ }`
	`39`	`+`
`35`	`40`	`private static Tensor _constant_if_small<T>(T value, Shape shape, TF_DataType dtype, string name)`
`36`	`41`	`{`
`37`	`42`	`Tensor tShape = null;`
`@@ -167,8 +172,9 @@ public static Tensor ones(Tensor[] shape, TF_DataType dtype = TF_DataType.TF_FLO`
`167`	`172`	`return with(ops.name_scope(name, "ones", new { shape }), scope =>`
`168`	`173`	`{`
`169`	`174`	`name = scope;`
	`175`	`+ var output = _constant_if_small(1, shape[0]);`
`170`	`176`	`var shape1 = ops.convert_to_tensor(shape, dtype: TF_DataType.TF_INT32);`
`171`		`- var output = gen_array_ops.fill(shape1, constant_op.constant(1, dtype: dtype), name: name);`
	`177`	`+ output = gen_array_ops.fill(shape1, constant_op.constant(1, dtype: dtype), name: name);`
`172`	`178`	`return output;`
`173`	`179`	`});`
`174`	`180`	`}`