Merge branch 'master' of https://github.com/SciSharp/TensorFlow.NET

src/TensorFlowNET.Core/APIs/tf.train.cs

@@ -41,6 +41,9 @@ namespace Tensorflow
             public Optimizer AdamOptimizer(float learning_rate, string name = "Adam") 
                 => new AdamOptimizer(learning_rate, name: name);
 
+            public Optimizer AdamOptimizer(float learning_rate, TF_DataType dtype, string name = "Adam")
+                => new AdamOptimizer(learning_rate, name: name, dtype: dtype);
+
             public Optimizer AdamOptimizer(Tensor learning_rate, string name = "Adam")
                 => new AdamOptimizer(learning_rate, name: name);
 

src/TensorFlowNET.Core/Tensors/TF_DataType.cs

@@ -35,6 +35,25 @@
         DtFloatRef = 101, // DT_FLOAT_REF
         DtDoubleRef = 102, // DT_DOUBLE_REF
         DtInt32Ref = 103, // DT_INT32_REF
-        DtInt64Ref = 109 // DT_INT64_REF
+        DtUint8Ref = 104,
+        DtInt16Ref = 105,
+        DtInt8Ref = 106,
+        DtStringRef = 107,
+        DtComplex64Ref = 108,
+        DtInt64Ref = 109, // DT_INT64_REF
+        DtBoolRef = 110,
+        DtQint8Ref = 111,
+        DtQuint8Ref = 112,
+        DtQint32Ref = 113,
+        DtBfloat16Ref = 114,
+        DtQint16Ref = 115,
+        DtQuint16Ref = 116,
+        DtUint16Ref = 117,
+        DtComplex128Ref = 118,
+        DtHalfRef = 119,
+        DtResourceRef = 120,
+        DtVariantRef = 121,
+        DtUint32Ref = 122,
+        DtUint64Ref = 123,
     }
 }

src/TensorFlowNET.Core/Tensors/dtypes.cs

@@ -46,7 +46,7 @@ namespace Tensorflow
         /// <returns><see cref="System.Type"/> equivalent to <paramref name="type"/>, if none exists, returns null.</returns>
         public static Type as_numpy_dtype(this TF_DataType type)
         {
-            switch (type)
+            switch (type.as_base_dtype())
             {
                 case TF_DataType.TF_BOOL:
                     return typeof(bool);
@@ -182,14 +182,12 @@ namespace Tensorflow
 
         public static DataType as_datatype_enum(this TF_DataType type)
         {
-            return Enum.TryParse(((int) type).ToString(), out DataType dtype) ? dtype : DataType.DtInvalid;
+            return (DataType)type;
         }
 
         public static TF_DataType as_base_dtype(this TF_DataType type)
         {
-            return (int)type > 100 ?
-                (TF_DataType)Enum.Parse(typeof(TF_DataType), ((int)type - 100).ToString()) :
-                type;
+            return (int)type > 100 ? (TF_DataType)((int)type - 100) : type;
         }
 
         public static int name(this TF_DataType type)
@@ -213,21 +211,17 @@ namespace Tensorflow
 
         public static DataType as_base_dtype(this DataType type)
         {
-            return (int)type > 100 ?
-                (DataType)Enum.Parse(typeof(DataType), ((int)type - 100).ToString()) :
-                type;
+            return (int)type > 100 ? (DataType)((int)type - 100) : type;
         }
 
         public static TF_DataType as_tf_dtype(this DataType type)
         {
-            return Enum.TryParse(((int) type).ToString(), out TF_DataType dtype) ? dtype : TF_DataType.DtInvalid;
+            return (TF_DataType)type;
         }
 
         public static TF_DataType as_ref(this TF_DataType type)
         {
-            return (int)type < 100 ?
-                (TF_DataType)Enum.Parse(typeof(TF_DataType), ((int)type + 100).ToString()) :
-                type;
+            return (int)type < 100 ? (TF_DataType)((int)type + 100) : type;
         }
 
         public static long max(this TF_DataType type)

src/TensorFlowNET.Core/Training/AdamOptimizer.cs

@@ -32,21 +32,24 @@ namespace Tensorflow.Train
         float _beta2;
         float _epsilon;
         Tensor _beta1_t, _beta2_t, _epsilon_t;
+        TF_DataType _dtype;
 
-        public AdamOptimizer(float learning_rate, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1e-8f, bool use_locking = false, string name = "Adam")
+        public AdamOptimizer(float learning_rate, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1e-8f, bool use_locking = false, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = "Adam")
             : base(learning_rate, use_locking, name)
         {
             _beta1 = beta1;
             _beta2 = beta2;
             _epsilon = epsilon;
+            _dtype = dtype;
         }
 
-        public AdamOptimizer(Tensor learning_rate, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1e-8f, bool use_locking = false, string name = "Adam")
+        public AdamOptimizer(Tensor learning_rate, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1e-8f, bool use_locking = false, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = "Adam")
             : base(learning_rate, use_locking, name)
         {
             _beta1 = beta1;
             _beta2 = beta2;
             _epsilon = epsilon;
+            _dtype = dtype;
         }
 
         public override Operation _apply_sparse(IndexedSlices grad, RefVariable var)
@@ -154,10 +157,10 @@ namespace Tensorflow.Train
             var beta2 = _call_if_callable(_beta2);
             var epsilon = _call_if_callable(_epsilon);
 
-            _lr_t = _lr_t ?? ops.convert_to_tensor(lr, name: "learning_rate");
-            _beta1_t = _beta1_t ?? ops.convert_to_tensor(beta1, name: "beta1");
-            _beta2_t = _beta2_t ?? ops.convert_to_tensor(beta2, name: "beta2");
-            _epsilon_t = _epsilon_t ?? ops.convert_to_tensor(epsilon, name: "epsilon");
+            _lr_t = _lr_t ?? ops.convert_to_tensor(lr, name: "learning_rate", dtype: _dtype);
+            _beta1_t = _beta1_t ?? ops.convert_to_tensor(beta1, name: "beta1", dtype: _dtype);
+            _beta2_t = _beta2_t ?? ops.convert_to_tensor(beta2, name: "beta2", dtype: _dtype);
+            _epsilon_t = _epsilon_t ?? ops.convert_to_tensor(epsilon, name: "epsilon", dtype: _dtype);
         }
     }
 }

src/TensorFlowNET.Core/Training/Optimizer.cs

@@ -253,6 +253,7 @@ namespace Tensorflow
                 v = variable_scope.default_variable_creator(
                     initial_value, 
                     name: name, 
+                    dtype: colocate_with.dtype.as_base_dtype(),
                     trainable: false,
                     use_resource: resource_variable_ops.is_resource_variable(
                         colocate_with));