remove output for assign_add_variable_op.

Oceania2018 · Oceania2018 · commit 784b1ebee9bb · 2020-05-31T06:55:52.000-05:00
diff --git a/src/TensorFlowNET.Core/Eager/EagerTensor.Creation.cs b/src/TensorFlowNET.Core/Eager/EagerTensor.Creation.cs
@@ -62,7 +62,8 @@ protected override void DisposeUnmanagedResources(IntPtr handle)
             GarbageCollector.Decrease(tfe_tensor_handle);
             GarbageCollector.Decrease(EagerTensorHandle);
 
-            /*c_api.TF_DeleteTensor(_handle);
+            /*print($"deleting DeleteTensorHandle {Id} {_handle.ToString("x16")}");
+            c_api.TF_DeleteTensor(_handle);
             print($"deleting DeleteTensorHandle {Id} {tfe_tensor_handle.ToString("x16")}");
             c_api.TFE_DeleteTensorHandle(tfe_tensor_handle);
             print($"deleting DeleteEagerTensor {Id} {EagerTensorHandle.ToString("x16")}");
diff --git a/src/TensorFlowNET.Core/Operations/gen_resource_variable_ops.cs b/src/TensorFlowNET.Core/Operations/gen_resource_variable_ops.cs
@@ -56,17 +56,16 @@ public static Operation assign_add_variable_op(Tensor resource, Tensor value, st
         {
             if (tf.context.executing_eagerly())
             {
-                var results = new[] { new EagerTensor() };
                 Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
                     "AssignAddVariableOp", name,
                     new IntPtr[]
                     {
                         resource as EagerTensor,
                         value as EagerTensor
                     }, 2, null,
-                    results.Select(x => x.EagerTensorHandle).ToArray(), results.Length);
+                    null, 0);
                 status.Check(true);
-                return results[0].Resolve();
+                return null;
             }
 
             return null;
@@ -76,15 +75,14 @@ public static Operation assign_variable_op(Tensor resource, Tensor value, string
         {
             if (tf.context.executing_eagerly())
             {
-                var results = new EagerTensor[0];
                 Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
                     "AssignVariableOp", name,
                     new IntPtr[]
                     {
                         resource as EagerTensor,
                         value as EagerTensor
                     }, 2, null,
-                    results.Select(x => x.EagerTensorHandle).ToArray(), results.Length);
+                    null, 0);
                 status.Check(true);
                 return null;
             }
diff --git a/src/TensorFlowNET.Core/System/GarbageCollector.cs b/src/TensorFlowNET.Core/System/GarbageCollector.cs
@@ -29,6 +29,9 @@ public static void Init()
 
         public static void Increase(IntPtr handle, GCItemType type)
         {
+            if (handle == IntPtr.Zero)
+                return;
+
             if (container.ContainsKey(handle))
             {
                 container[handle].RefCounter++;
@@ -51,11 +54,8 @@ public static void Increase(IntPtr handle, GCItemType type)
 
         public static void Decrease(IntPtr handle)
         {
-            lock (locker)
-            {
-                if (container.ContainsKey(handle))
-                    container[handle].RefCounter--;
-            }
+            if (handle != IntPtr.Zero && container.ContainsKey(handle))
+                container[handle].RefCounter--;
         }
 
         private static void Recycle()
diff --git a/src/TensorFlowNET.Core/Training/gen_training_ops.cs b/src/TensorFlowNET.Core/Training/gen_training_ops.cs
@@ -65,7 +65,6 @@ public static Operation resource_apply_gradient_descent(EagerTensor var, EagerTe
         {
             if (tf.context.executing_eagerly())
             {
-                var results = new[] { new EagerTensor() };
                 Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
                     "ResourceApplyGradientDescent", name, new IntPtr[]
                     {
@@ -74,9 +73,9 @@ public static Operation resource_apply_gradient_descent(EagerTensor var, EagerTe
                         delta
                     }, 3, 
                     op => wrap_tfe_src.SetOpAttrs(op, "use_locking", use_locking),
-                    results.Select(x => x.EagerTensorHandle).ToArray(), results.Length);
+                    null, 0);
                 status.Check(true);
-                return results[0].Resolve();
+                return null;
             }
 
             var _op = _op_def_lib._apply_op_helper("ResourceApplyGradientDescent", name, new

Original file line number	Diff line number	Diff line change
`@@ -56,17 +56,16 @@ public static Operation assign_add_variable_op(Tensor resource, Tensor value, st`
`56`	`56`	`{`
`57`	`57`	`if (tf.context.executing_eagerly())`
`58`	`58`	`{`
`59`		`- var results = new[] { new EagerTensor() };`
`60`	`59`	`Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,`
`61`	`60`	`"AssignAddVariableOp", name,`
`62`	`61`	`new IntPtr[]`
`63`	`62`	`{`
`64`	`63`	`resource as EagerTensor,`
`65`	`64`	`value as EagerTensor`
`66`	`65`	`}, 2, null,`
`67`		`- results.Select(x => x.EagerTensorHandle).ToArray(), results.Length);`
	`66`	`+ null, 0);`
`68`	`67`	`status.Check(true);`
`69`		`- return results[0].Resolve();`
	`68`	`+ return null;`
`70`	`69`	`}`
`71`	`70`
`72`	`71`	`return null;`
`@@ -76,15 +75,14 @@ public static Operation assign_variable_op(Tensor resource, Tensor value, string`
`76`	`75`	`{`
`77`	`76`	`if (tf.context.executing_eagerly())`
`78`	`77`	`{`
`79`		`- var results = new EagerTensor[0];`
`80`	`78`	`Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,`
`81`	`79`	`"AssignVariableOp", name,`
`82`	`80`	`new IntPtr[]`
`83`	`81`	`{`
`84`	`82`	`resource as EagerTensor,`
`85`	`83`	`value as EagerTensor`
`86`	`84`	`}, 2, null,`
`87`		`- results.Select(x => x.EagerTensorHandle).ToArray(), results.Length);`
	`85`	`+ null, 0);`
`88`	`86`	`status.Check(true);`
`89`	`87`	`return null;`
`90`	`88`	`}`
Original file line number	Diff line number	Diff line change
`@@ -29,6 +29,9 @@ public static void Init()`
`29`	`29`
`30`	`30`	`public static void Increase(IntPtr handle, GCItemType type)`
`31`	`31`	`{`
	`32`	`+ if (handle == IntPtr.Zero)`
	`33`	`+ return;`
	`34`	`+`
`32`	`35`	`if (container.ContainsKey(handle))`
`33`	`36`	`{`
`34`	`37`	`container[handle].RefCounter++;`
`@@ -51,11 +54,8 @@ public static void Increase(IntPtr handle, GCItemType type)`
`51`	`54`
`52`	`55`	`public static void Decrease(IntPtr handle)`
`53`	`56`	`{`
`54`		`- lock (locker)`
`55`		`- {`
`56`		`- if (container.ContainsKey(handle))`
`57`		`- container[handle].RefCounter--;`
`58`		`- }`
	`57`	`+ if (handle != IntPtr.Zero && container.ContainsKey(handle))`
	`58`	`+ container[handle].RefCounter--;`
`59`	`59`	`}`
`60`	`60`
`61`	`61`	`private static void Recycle()`
Original file line number	Diff line number	Diff line change
`@@ -65,7 +65,6 @@ public static Operation resource_apply_gradient_descent(EagerTensor var, EagerTe`
`65`	`65`	`{`
`66`	`66`	`if (tf.context.executing_eagerly())`
`67`	`67`	`{`
`68`		`- var results = new[] { new EagerTensor() };`
`69`	`68`	`Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,`
`70`	`69`	`"ResourceApplyGradientDescent", name, new IntPtr[]`
`71`	`70`	`{`
`@@ -74,9 +73,9 @@ public static Operation resource_apply_gradient_descent(EagerTensor var, EagerTe`
`74`	`73`	`delta`
`75`	`74`	`}, 3,`
`76`	`75`	`op => wrap_tfe_src.SetOpAttrs(op, "use_locking", use_locking),`
`77`		`- results.Select(x => x.EagerTensorHandle).ToArray(), results.Length);`
	`76`	`+ null, 0);`
`78`	`77`	`status.Check(true);`
`79`		`- return results[0].Resolve();`
	`78`	`+ return null;`
`80`	`79`	`}`
`81`	`80`
`82`	`81`	`var _op = _op_def_lib._apply_op_helper("ResourceApplyGradientDescent", name, new`