clean code.

src/TensorFlowNET.Core/APIs/c_api.cs

@@ -63,8 +63,8 @@ namespace Tensorflow
 
             static unsafe DeallocatorArgs()
             {
-                Empty = new IntPtr(EmptyPtr = (DeallocatorArgs*) Marshal.AllocHGlobal(Marshal.SizeOf<DeallocatorArgs>()));
-                *EmptyPtr = new DeallocatorArgs() {gc_handle = IntPtr.Zero, deallocator_called = false};
+                Empty = new IntPtr(EmptyPtr = (DeallocatorArgs*)Marshal.AllocHGlobal(Marshal.SizeOf<DeallocatorArgs>()));
+                *EmptyPtr = new DeallocatorArgs() { gc_handle = IntPtr.Zero, deallocator_called = false };
             }
 
             public bool deallocator_called;

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

@@ -15,7 +15,6 @@
 ******************************************************************************/
 
 using NumSharp;
-using System;
 using System.Collections.Generic;
 using System.Diagnostics;
 using System.Linq;

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

@@ -15,7 +15,6 @@
 ******************************************************************************/
 
 using Tensorflow.Graphs;
-using Tensorflow.Operations;
 
 namespace Tensorflow
 {

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using NumSharp;
-
 namespace Tensorflow
 {
     public partial class tensorflow

src/TensorFlowNET.Core/APIs/tf.compat.v1.cs

@@ -14,9 +14,7 @@
    limitations under the License.
 ******************************************************************************/
 
-using System;
 using System.Collections.Generic;
-using Tensorflow.Contexts;
 using static Tensorflow.Binding;
 
 namespace Tensorflow

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

@@ -15,7 +15,6 @@
 ******************************************************************************/
 
 using System;
-using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -42,19 +41,19 @@ namespace Tensorflow
         public Operation group<T>(T[] inputs, string name = null) where T : ITensorOrOperation
             => control_flow_ops.group(inputs, name: name);
 
-        public Tensor while_loop(Func<Tensor, Tensor> cond, 
-            Func<Tensor, Tensor> body, 
+        public Tensor while_loop(Func<Tensor, Tensor> cond,
+            Func<Tensor, Tensor> body,
             Tensor loop_vars,
             int parallel_iterations = 10)
         {
-            Func<Tensor[], Tensor> cond1 = x 
+            Func<Tensor[], Tensor> cond1 = x
                 => cond(x[0]);
 
-            Func<Tensor[], Tensor[]> body1 = x 
+            Func<Tensor[], Tensor[]> body1 = x
                 => new[] { body(x[0]) };
 
-            var results = control_flow_ops.while_loop(cond1, 
-                body1, 
+            var results = control_flow_ops.while_loop(cond1,
+                body1,
                 new[] { loop_vars });
             return results[0];
         }
@@ -68,7 +67,7 @@ namespace Tensorflow
                 parallel_iterations: parallel_iterations,
                 name: name);
 
-        public _ControlDependenciesController control_dependencies(ITensorOrOperation[] control_inputs) 
+        public _ControlDependenciesController control_dependencies(ITensorOrOperation[] control_inputs)
             => ops.control_dependencies(control_inputs);
     }
 }

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using NumSharp;
-
 namespace Tensorflow
 {
     public partial class tensorflow

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using System;
-
 namespace Tensorflow
 {
     public partial class tensorflow

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

@@ -34,10 +34,10 @@ namespace Tensorflow
             object[] data = null,
             string message = null,
             string name = null)
-            => check_ops.assert_equal(t1, 
-                t2, 
-                data: data, 
-                message: message, 
+            => check_ops.assert_equal(t1,
+                t2,
+                data: data,
+                message: message,
                 name: name);
 
         public Tensor assert_greater_equal<T1, T2>(Tensor x,

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

@@ -40,11 +40,11 @@ namespace Tensorflow
             int? aggregation_method = null,
             Tensor[] stop_gradients = null)
         {
-            return gradients_util._GradientsHelper(ys, 
-                xs, 
-                grad_ys, 
-                name, 
-                colocate_gradients_with_ops, 
+            return gradients_util._GradientsHelper(ys,
+                xs,
+                grad_ys,
+                name,
+                colocate_gradients_with_ops,
                 gate_gradients,
                 stop_gradients: stop_gradients);
         }

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

@@ -24,7 +24,7 @@ namespace Tensorflow
         public GraphTransformer graph_transforms => new GraphTransformer();
         public GraphKeys GraphKeys { get; } = new GraphKeys();
 
-        public void reset_default_graph() 
+        public void reset_default_graph()
             => ops.reset_default_graph();
 
         public Graph get_default_graph()

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using System.Collections.Generic;
-using Tensorflow.IO;
 using static Tensorflow.Binding;
 
 namespace Tensorflow
@@ -34,7 +32,7 @@ namespace Tensorflow
 
             public Tensor flip_left_right(Tensor image)
                 => image_ops_impl.flip_left_right(image);
-            
+
             public Tensor flip_up_down(Tensor image)
                 => image_ops_impl.flip_up_down(image);
 
@@ -56,7 +54,7 @@ namespace Tensorflow
             public Tensor resize_image_with_crop_or_pad(Tensor image, object target_height, object target_width)
                 => image_ops_impl.resize_image_with_crop_or_pad(image, target_height, target_width);
 
-            public Tensor resize_images(Tensor images, Tensor size, string method = ResizeMethod.BILINEAR, bool preserve_aspect_ratio  = false, bool antialias = false,
+            public Tensor resize_images(Tensor images, Tensor size, string method = ResizeMethod.BILINEAR, bool preserve_aspect_ratio = false, bool antialias = false,
                 string name = null)
                 => image_ops_impl.resize_images(images, size, method, preserve_aspect_ratio, antialias, name);
 
@@ -93,7 +91,7 @@ namespace Tensorflow
 
             public Tensor random_hue(Tensor image, float max_delta, int seed = 0)
                 => image_ops_impl.random_hue(image, max_delta, seed);
-            
+
             public Tensor adjust_hue(Tensor image, Tensor delta, string name = null)
                 => image_ops_impl.adjust_hue(image, delta, name);
 
@@ -169,7 +167,7 @@ namespace Tensorflow
                         string dct_method = "",
                         string name = null)
                 => gen_image_ops.decode_jpeg(contents, channels: channels, ratio: ratio,
-                    fancy_upscaling: fancy_upscaling, try_recover_truncated: try_recover_truncated, 
+                    fancy_upscaling: fancy_upscaling, try_recover_truncated: try_recover_truncated,
                     acceptable_fraction: acceptable_fraction, dct_method: dct_method);
 
             /// <summary>
@@ -197,12 +195,12 @@ namespace Tensorflow
                 => image_ops_impl.combined_non_max_suppression(boxes, scores, max_output_size_per_class, max_total_size, iou_threshold, score_threshold,
                     pad_per_class, clip_boxes, name);
 
-            public (Tensor, Tensor) non_max_suppression_padded(Tensor boxes, Tensor scores, Tensor  max_output_size,
+            public (Tensor, Tensor) non_max_suppression_padded(Tensor boxes, Tensor scores, Tensor max_output_size,
                 float iou_threshold = 0.5f,
                 float score_threshold = -1f / 0f,
                 bool pad_to_max_output_size = false,
                 string name = null,
-                bool sorted_input =  false,
+                bool sorted_input = false,
                 bool canonicalized_coordinates = false,
                 int tile_size = 512)
                 => image_ops_impl.non_max_suppression_padded(boxes, scores, max_output_size, iou_threshold, score_threshold, pad_to_max_output_size,

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

@@ -22,7 +22,7 @@ namespace Tensorflow
     {
         public InitializersImpl initializers { get; } = new InitializersImpl();
 
-        public IInitializer constant_initializer<T>(T value, TF_DataType dtype = TF_DataType.TF_FLOAT, bool verify_shape = false) 
+        public IInitializer constant_initializer<T>(T value, TF_DataType dtype = TF_DataType.TF_FLOAT, bool verify_shape = false)
             => new Constant<T>(value, dtype: dtype, verify_shape: verify_shape);
         public IInitializer zeros_initializer => new Zeros();
         public IInitializer ones_initializer => new Ones();
@@ -97,7 +97,7 @@ namespace Tensorflow
                     dtype: dtype);
 
             public IInitializer zeros_initializer(TensorShape shape = null,
-                TF_DataType dtype = TF_DataType.TF_FLOAT) => new Zeros(shape: shape, 
+                TF_DataType dtype = TF_DataType.TF_FLOAT) => new Zeros(shape: shape,
                     dtype: dtype);
         }
     }

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using NumSharp;
-
 namespace Tensorflow
 {
     public partial class tensorflow

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

@@ -14,14 +14,11 @@
    limitations under the License.
 ******************************************************************************/
 
-using System;
 using System.Collections.Generic;
 using System.Linq;
-using NumSharp;
 using Tensorflow.Keras;
 using Tensorflow.Keras.ArgsDefinition;
 using Tensorflow.Keras.Layers;
-using Tensorflow.Operations.Activation;
 using static Tensorflow.Binding;
 
 namespace Tensorflow
@@ -37,7 +34,7 @@ namespace Tensorflow
                 int[] kernel_size,
                 int[] strides = null,
                 string padding = "valid",
-                string data_format= "channels_last",
+                string data_format = "channels_last",
                 int[] dilation_rate = null,
                 bool use_bias = true,
                 Activation activation = null,
@@ -219,7 +216,7 @@ namespace Tensorflow
                 if (inputs.shape.Length == 0)
                     throw new ValueError($"Input 0 of layer flatten is incompatible with the layer: : expected min_ndim={1}, found ndim={0}. Full shape received: ()");
 
-                var premutation = new List<int>() {0};
+                var premutation = new List<int>() { 0 };
                 if (data_format == "channels_first" && inputs.NDims > 1)
                 {
                     premutation.AddRange(Binding.range(2, inputs.NDims));
@@ -234,16 +231,17 @@ namespace Tensorflow
                 int[] compute_output_shape(int[] inputshape)
                 {
                     if (inputshape == null || inputshape.Length == 0)
-                        inputshape = new int[] {1};
+                        inputshape = new int[] { 1 };
 
                     if (inputshape.Skip(1).All(d => d > 0))
                     {
                         int[] output_shape = new int[2];
                         output_shape[0] = inputshape[0];
-                        output_shape[1] = inputshape.Skip(1).Aggregate(1, (acc, rhs) => acc*rhs); //calculate size of all the rest dimensions
+                        output_shape[1] = inputshape.Skip(1).Aggregate(1, (acc, rhs) => acc * rhs); //calculate size of all the rest dimensions
                         return output_shape;
-                    } else
-                        return new int[] {inputshape[0], -1}; //-1 == Binding.None
+                    }
+                    else
+                        return new int[] { inputshape[0], -1 }; //-1 == Binding.None
                 }
             }
         }

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

@@ -14,9 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using Tensorflow.Eager;
-using Tensorflow.Operations;
-
 namespace Tensorflow
 {
     public partial class tensorflow
@@ -52,7 +49,7 @@ namespace Tensorflow
         public Tensor add(Tensor a, Tensor b, string name = null)
             => gen_math_ops.add(a, b, name: name);
 
-        public Tensor add<Tx, Ty>(Tx a, Ty b, string name = null) 
+        public Tensor add<Tx, Ty>(Tx a, Ty b, string name = null)
             => gen_math_ops.add(a, b, name: name);
 
         /// <summary>
@@ -233,7 +230,7 @@ namespace Tensorflow
         /// <returns></returns>
         public Tensor _clip_by_value(Tensor t, Tensor clip_value_min, Tensor clip_value_max, string name = null)
             => gen_math_ops._clip_by_value(t, clip_value_min, clip_value_max);
-        
+
         /// <summary>
         ///    Clips tensor values to a specified min and max.
         /// </summary>
@@ -261,16 +258,16 @@ namespace Tensorflow
         ///    Any values less than <c>clip_value_min</c> are set to <c>clip_value_min</c>. Any values
         ///    greater than <c>clip_value_max</c> are set to <c>clip_value_max</c>.
         /// </remarks>
-        public Tensor clip_by_value<T1, T2>(Tensor t, T1 clip_value_min, T2 clip_value_max, string name = "ClipByValue") 
+        public Tensor clip_by_value<T1, T2>(Tensor t, T1 clip_value_min, T2 clip_value_max, string name = "ClipByValue")
             => clip_ops.clip_by_value(t, clip_value_min, clip_value_max, name);
-        
+
         public Tensor sub<Tx, Ty>(Tx a, Ty b, string name = null)
             => gen_math_ops.sub(a, b, name: name);
 
         public Tensor divide(Tensor a, Tensor b)
             => a / b;
 
-        public Tensor sqrt(Tensor a, string name = null) 
+        public Tensor sqrt(Tensor a, string name = null)
             => gen_math_ops.sqrt(a, name);
 
         public Tensor sign(Tensor a, string name = null)
@@ -367,7 +364,7 @@ namespace Tensorflow
         /// <param name="y"></param>
         /// <param name="name"></param>
         /// <returns></returns>
-        public Tensor multiply<Tx, Ty>(Tx x, Ty y, string name = null) 
+        public Tensor multiply<Tx, Ty>(Tx x, Ty y, string name = null)
             => gen_math_ops.mul(x, y, name: name);
 
         public Tensor negative(Tensor x, string name = null)
@@ -424,7 +421,7 @@ namespace Tensorflow
 
         public Tensor real(Tensor input, string name = null)
             => math_ops.real(input, name);
-       
+
         /// <summary>
         /// Computes the "logical or" of elements across dimensions of a tensor.
         /// </summary>
@@ -478,7 +475,7 @@ namespace Tensorflow
         /// <param name="input"></param>
         /// <param name="axis"></param>
         /// <returns></returns>
-        public Tensor reduce_sum(Tensor input, int? axis = null, int? reduction_indices = null, 
+        public Tensor reduce_sum(Tensor input, int? axis = null, int? reduction_indices = null,
             bool keepdims = false, string name = null)
         {
             if (!axis.HasValue && reduction_indices.HasValue && !keepdims)
@@ -491,7 +488,7 @@ namespace Tensorflow
                 return math_ops.reduce_sum(input, keepdims: keepdims, name: name);
         }
 
-        public Tensor reduce_sum(Tensor input, TensorShape axis, int? reduction_indices = null, 
+        public Tensor reduce_sum(Tensor input, TensorShape axis, int? reduction_indices = null,
             bool keepdims = false, string name = null)
             => math_ops.reduce_sum(input, axis, keepdims: keepdims, name: name);
 
@@ -517,7 +514,7 @@ namespace Tensorflow
 
         public Tensor reduce_variance(Tensor input_tensor, int[] axis = null, bool keepdims = false, string name = null)
             => math_ops.reduce_variance(input_tensor, axis, keepdims, name);
-       
+
         public Tensor sigmoid<T>(T x, string name = null)
             => math_ops.sigmoid(x, name: name);
 
@@ -536,7 +533,7 @@ namespace Tensorflow
         public Tensor round(Tensor x, string name = null)
             => gen_math_ops.round(x, name: name);
 
-        public Tensor cast(Tensor x, TF_DataType dtype = TF_DataType.DtInvalid, string name = null) 
+        public Tensor cast(Tensor x, TF_DataType dtype = TF_DataType.DtInvalid, string name = null)
             => math_ops.cast(x, dtype, name);
 
         public Tensor cumsum(Tensor x, int axis = 0, bool exclusive = false, bool reverse = false, string name = null)

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

@@ -14,7 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using System;
 using Tensorflow.Operations;
 using Tensorflow.Operations.Activation;
 using static Tensorflow.Binding;
@@ -27,8 +26,8 @@ namespace Tensorflow
 
         public class nn_internal
         {
-            public Tensor conv2d(Tensor input, IVariableV1 filter, int[] strides, string padding, bool use_cudnn_on_gpu = true, 
-                string data_format= "NHWC", int[] dilations= null, string name = null)
+            public Tensor conv2d(Tensor input, IVariableV1 filter, int[] strides, string padding, bool use_cudnn_on_gpu = true,
+                string data_format = "NHWC", int[] dilations = null, string name = null)
             {
                 var parameters = new Conv2dParams
                 {
@@ -92,9 +91,9 @@ namespace Tensorflow
             public (Tensor, Tensor) moments(Tensor x,
                 int[] axes,
                 string name = null,
-                bool keep_dims = false) => nn_impl.moments(x, 
-                    axes, 
-                    name: name, 
+                bool keep_dims = false) => nn_impl.moments(x,
+                    axes,
+                    name: name,
                     keep_dims: keep_dims);
 
             public Tensor embedding_lookup(IVariableV1 @params,
@@ -121,7 +120,7 @@ namespace Tensorflow
             public Tensor tanh(Tensor x, string name = null)
                 => gen_nn_ops.tanh(x, name);
 
-            public Tensor relu(Tensor features, string name = null) 
+            public Tensor relu(Tensor features, string name = null)
                 => gen_nn_ops.relu(features, name);
 
             public Tensor[] fused_batch_norm(Tensor x,
@@ -140,7 +139,7 @@ namespace Tensorflow
 
             public IPoolFunction max_pool_fn => new MaxPoolFunction();
 
-            public Tensor max_pool(Tensor value, int[] ksize, int[] strides, string padding, string data_format = "NHWC", string name = null) 
+            public Tensor max_pool(Tensor value, int[] ksize, int[] strides, string padding, string data_format = "NHWC", string name = null)
                 => nn_ops.max_pool(value, ksize, strides, padding, data_format: data_format, name: name);
 
             public Tensor in_top_k(Tensor predictions, Tensor targets, int k, string name = "InTopK")
@@ -183,7 +182,7 @@ namespace Tensorflow
 
             public Tensor softmax(Tensor logits, int axis = -1, string name = null)
                 => gen_nn_ops.softmax(logits, name);
-                
+
 
             /// <summary>
             /// Computes sparse softmax cross entropy between `logits` and `labels`.

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

@@ -27,7 +27,7 @@ namespace Tensorflow
         public void add_to_collections<T>(List<string> names, T value)
             => get_default_graph().add_to_collections(names, value);
 
-        public Tensor assign(Tensor @ref, object value, bool validate_shape = true, bool use_locking = true, string name = null) 
+        public Tensor assign(Tensor @ref, object value, bool validate_shape = true, bool use_locking = true, string name = null)
             => state_ops.assign(@ref, value, validate_shape, use_locking, name);
 
         public Tensor assign(IVariableV1 @ref, object value, bool validate_shape = true, bool use_locking = true, string name = null)
@@ -36,7 +36,7 @@ namespace Tensorflow
         public void device(string device_name)
             => get_default_graph().device(device_name);
 
-        public List<T> get_collection<T>(string key, string scope = "") 
+        public List<T> get_collection<T>(string key, string scope = "")
             => get_default_graph().get_collection<T>(key, scope: scope);
 
         /// <summary>
@@ -54,7 +54,7 @@ namespace Tensorflow
         /// <param name="default_name">The default name to use if the name argument is None.</param>
         /// <param name="values">The list of Tensor arguments that are passed to the op function.</param>
         /// <returns>The scope name.</returns>
-        public ops.NameScope name_scope(string name, string default_name = "", object values = null) 
+        public ops.NameScope name_scope(string name, string default_name = "", object values = null)
             => new ops.NameScope(name, default_name, values);
 
         /// <summary>

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using Tensorflow.Keras;
-using Tensorflow.Keras.Engine;
 using Tensorflow.Keras.Optimizers;
 
 namespace Tensorflow

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

@@ -14,7 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using System;
 using Tensorflow.Queues;
 
 namespace Tensorflow

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

@@ -97,7 +97,7 @@ namespace Tensorflow
 
         public Tensor multinomial(Tensor logits, int num_samples, int? seed = null,
             string name = null, TF_DataType output_dtype = TF_DataType.DtInvalid)
-            => random_ops.multinomial(logits, num_samples, seed: seed, 
+            => random_ops.multinomial(logits, num_samples, seed: seed,
                 name: name, output_dtype: output_dtype);
     }
 }

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

@@ -52,7 +52,7 @@ namespace Tensorflow
             bool validate_indices = true,
             string name = null)
             => gen_sparse_ops.sparse_to_dense(sparse_indices,
-                output_shape, 
+                output_shape,
                 sparse_values,
                 default_value: default_value,
                 validate_indices: validate_indices,

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

@@ -14,9 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using System.Collections.Generic;
-using Tensorflow.IO;
-
 namespace Tensorflow
 {
     public partial class tensorflow

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

@@ -20,7 +20,7 @@ namespace Tensorflow
     {
         public Summaries.Summary summary = new Summaries.Summary();
 
-        public Tensor scalar(string name, Tensor tensor) 
+        public Tensor scalar(string name, Tensor tensor)
             => summary.scalar(name, tensor);
     }
 }

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

@@ -18,7 +18,7 @@ namespace Tensorflow
 {
     public partial class tensorflow
     {
-        public Tensor convert_to_tensor(object value, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, TF_DataType preferred_dtype = TF_DataType.DtInvalid) 
+        public Tensor convert_to_tensor(object value, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, TF_DataType preferred_dtype = TF_DataType.DtInvalid)
             => ops.convert_to_tensor(value, dtype, name, preferred_dtype);
 
         public Tensor strided_slice(Tensor input, Tensor begin, Tensor end, Tensor strides = null,
@@ -66,7 +66,7 @@ namespace Tensorflow
         /// <param name="name">A name for the operation (optional)</param>
         /// <returns>if num_or_size_splits is a scalar returns num_or_size_splits Tensor objects;
         /// if num_or_size_splits is a 1-D Tensor returns num_or_size_splits.get_shape[0] Tensor objects resulting from splitting value.</returns>
-        public Tensor[] split(Tensor value, int num_split, Tensor axis, string name = null) 
+        public Tensor[] split(Tensor value, int num_split, Tensor axis, string name = null)
             => array_ops.split(
                 value: value,
                 num_split: num_split,

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

@@ -14,8 +14,6 @@
    limitations under the License.
 ******************************************************************************/
 
-using NumSharp;
-
 namespace Tensorflow
 {
     public partial class tensorflow

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

@@ -32,14 +32,14 @@ namespace Tensorflow
             public IVariableV1 get_global_step(Graph graph)
                 => TrainingUtil.get_global_step(graph);
 
-            public Optimizer GradientDescentOptimizer(float learning_rate) 
+            public Optimizer GradientDescentOptimizer(float learning_rate)
                 => new GradientDescentOptimizer(learning_rate);
 
             public Optimizer GradientDescentOptimizer(Tensor learning_rate)
                 => new GradientDescentOptimizer(learning_rate);
 
-            public Optimizer AdamOptimizer(float learning_rate, float epsilon = 1e-8f, string name = "Adam") 
-                => new AdamOptimizer(learning_rate, epsilon:epsilon, name: name);
+            public Optimizer AdamOptimizer(float learning_rate, float epsilon = 1e-8f, string name = "Adam")
+                => new AdamOptimizer(learning_rate, epsilon: epsilon, name: name);
 
             public Optimizer AdamOptimizer(float learning_rate, TF_DataType dtype, string name = "Adam")
                 => new AdamOptimizer(learning_rate, name: name, dtype: dtype);
@@ -53,10 +53,10 @@ namespace Tensorflow
             public ExponentialMovingAverage ExponentialMovingAverage(float decay)
                 => new ExponentialMovingAverage(decay);
 
-            public Saver Saver(IVariableV1[] var_list = null, int max_to_keep = 5) 
+            public Saver Saver(IVariableV1[] var_list = null, int max_to_keep = 5)
                 => new Saver(var_list: var_list, max_to_keep: max_to_keep);
 
-            public string write_graph(Graph graph, string logdir, string name, bool as_text = true) 
+            public string write_graph(Graph graph, string logdir, string name, bool as_text = true)
                 => graph_io.write_graph(graph, logdir, name, as_text);
 
             public Graph load_graph(string freeze_graph_pb)

src/TensorFlowNET.Core/Attributes/c_api.ops.cs

@@ -47,7 +47,7 @@ namespace Tensorflow
         /// <param name="status">TF_Status*</param>
         [DllImport(TensorFlowLibName)]
         public static extern void TF_OperationGetAttrString(IntPtr oper, string attr_name, IntPtr value, uint max_length, SafeStatusHandle status);
-        
+
         /// <summary>
         /// Sets `output_attr_value` to the binary-serialized AttrValue proto
         /// representation of the value of the `attr_name` attr of `oper`.

src/TensorFlowNET.Core/Binding.FuncTools.cs

@@ -1,8 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-using System.Threading.Tasks;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Binding.Util.cs

@@ -15,14 +15,13 @@
 ******************************************************************************/
 
 using NumSharp;
+using NumSharp.Utilities;
 using System;
 using System.Collections;
 using System.Collections.Generic;
 using System.ComponentModel;
 using System.Diagnostics;
 using System.Linq;
-using NumSharp.Utilities;
-using System.Runtime.CompilerServices;
 
 namespace Tensorflow
 {
@@ -32,8 +31,8 @@ namespace Tensorflow
     public static partial class Binding
     {
         public static T2 get<T1, T2>(this Dictionary<T1, T2> dict, T1 key)
-            => key == null ? 
-                default : 
+            => key == null ?
+                default :
             (dict.ContainsKey(key) ? dict[key] : default);
 
         public static void Update<T>(this IList<T> list, T element)
@@ -71,7 +70,7 @@ namespace Tensorflow
                 case NDArray nd:
                     return nd.ToString(false);
                 case Array arr:
-                    if (arr.Rank!=1 || arr.GetType().GetElementType()?.IsArray == true)
+                    if (arr.Rank != 1 || arr.GetType().GetElementType()?.IsArray == true)
                         arr = Arrays.Flatten(arr);
                     var objs = toObjectArray(arr);
                     return $"[{string.Join(", ", objs.Select(_tostring))}]";
@@ -105,7 +104,7 @@ namespace Tensorflow
                 return;
             }
 
-            foreach(var obj in objects)
+            foreach (var obj in objects)
             {
 
             }
@@ -239,13 +238,13 @@ namespace Tensorflow
                 yield return (t1[i], t2[i], t3[i]);
         }
 
-        public static IEnumerable<(T1, T2)> zip<T1, T2>(NDArray t1, NDArray t2) 
-            where T1: unmanaged
-            where T2: unmanaged
+        public static IEnumerable<(T1, T2)> zip<T1, T2>(NDArray t1, NDArray t2)
+            where T1 : unmanaged
+            where T2 : unmanaged
         {
             var a = t1.AsIterator<T1>();
             var b = t2.AsIterator<T2>();
-            while(a.HasNext() && b.HasNext())
+            while (a.HasNext() && b.HasNext())
                 yield return (a.MoveNext(), b.MoveNext());
         }
 
@@ -390,7 +389,8 @@ namespace Tensorflow
                 {
                     yield return flds[i].GetValue(tuple);
                 }
-            } else
+            }
+            else
             {
                 throw new System.Exception("Expected Tuple.");
             }
@@ -404,7 +404,7 @@ namespace Tensorflow
         public static bool isinstance(object Item1, object tuple)
         {
             foreach (var t in TupleToEnumerable(tuple))
-                if (isinstance(Item1, (Type) t))
+                if (isinstance(Item1, (Type)t))
                     return true;
             return false;
         }

src/TensorFlowNET.Core/Binding.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Diagnostics;
-using System.Dynamic;
-using System.Text;
+using System.Diagnostics;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Buffers/Buffer.cs

@@ -17,7 +17,6 @@
 using NumSharp.Backends.Unmanaged;
 using System;
 using System.Runtime.CompilerServices;
-using System.Runtime.InteropServices;
 using Tensorflow.Util;
 using static Tensorflow.c_api;
 

src/TensorFlowNET.Core/Clustering/_InitializeClustersOpFactory.cs

@@ -89,7 +89,7 @@ namespace Tensorflow.Clustering
         public Tensor op()
         {
             var x = control_flow_ops.cond(gen_math_ops.equal(_num_remaining, 0),
-                () => 
+                () =>
                 {
                     return check_ops.assert_equal(_cluster_centers_initialized, true);
                 },

src/TensorFlowNET.Core/Contexts/Context.cs

@@ -70,8 +70,8 @@ namespace Tensorflow.Contexts
             => context_switches.Current().EagerMode;
 
         public string shared_name(string name = null)
-            => !string.IsNullOrEmpty(name) || !executing_eagerly() ? 
-                name : 
+            => !string.IsNullOrEmpty(name) || !executing_eagerly() ?
+                name :
                 "cd2c89b7-88b7-44c8-ad83-06c2a9158347";
 
         public void graph_mode()

src/TensorFlowNET.Core/Contexts/ContextSwitch.cs

@@ -15,8 +15,6 @@
 ******************************************************************************/
 
 using System;
-using System.Collections.Generic;
-using System.Text;
 
 namespace Tensorflow.Contexts
 {

src/TensorFlowNET.Core/Contexts/ContextSwitchStack.cs

@@ -14,9 +14,7 @@
    limitations under the License.
 ******************************************************************************/
 
-using System;
 using System.Collections.Generic;
-using System.Text;
 
 namespace Tensorflow.Contexts
 {

src/TensorFlowNET.Core/Contrib/Learn/Estimators/tensor_signature.cs

@@ -1,5 +1,5 @@
-using System.Linq;
-using NumSharp;
+using NumSharp;
+using System.Linq;
 using Tensorflow.Framework;
 
 namespace Tensorflow.Contrib.Learn.Estimators

src/TensorFlowNET.Core/Contrib/Train/HParams.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow.Contrib.Train
+namespace Tensorflow.Contrib.Train
 {
     /// <summary>
     /// Class to hold a set of hyperparameters as name-value pairs.

src/TensorFlowNET.Core/Data/BatchDataset.cs

@@ -1,8 +1,5 @@
 using System;
-using System.Collections.Generic;
 using System.Linq;
-using System.Text;
-using Tensorflow.Framework.Models;
 using static Tensorflow.Binding;
 
 namespace Tensorflow
@@ -15,13 +12,13 @@ namespace Tensorflow
         Tensor _batch_size;
         Tensor _drop_remainder;
 
-        public BatchDataset(IDatasetV2 input_dataset, int batch_size, bool drop_remainder = false) : 
+        public BatchDataset(IDatasetV2 input_dataset, int batch_size, bool drop_remainder = false) :
             base(input_dataset)
         {
             _input_dataset = input_dataset;
             _batch_size = tf.convert_to_tensor(batch_size, dtype: TF_DataType.TF_INT64, name: "batch_size");
             _drop_remainder = tf.convert_to_tensor(drop_remainder, dtype: TF_DataType.TF_BOOL, name: "drop_remainder");
-            
+
             if (drop_remainder)
             {
                 throw new NotImplementedException("");

src/TensorFlowNET.Core/Data/CacheDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/DataSetBase.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using NumSharp;
+using NumSharp;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/DatasetManager.cs

@@ -1,7 +1,5 @@
 using NumSharp;
-using System;
 using System.Collections.Generic;
-using System.Text;
 using Tensorflow.Data;
 
 namespace Tensorflow

src/TensorFlowNET.Core/Data/DatasetOps.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     public class DatasetOps
     {

src/TensorFlowNET.Core/Data/DatasetOptions.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     public class DatasetOptions
     {

src/TensorFlowNET.Core/Data/DatasetSource.cs

@@ -1,10 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-using Tensorflow.Framework.Models;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     public class DatasetSource : DatasetV2
     {

src/TensorFlowNET.Core/Data/DatasetV2.cs

@@ -2,7 +2,6 @@
 using System.Collections;
 using System.Collections.Generic;
 using System.Linq;
-using System.Text;
 using Tensorflow.Framework.Models;
 
 namespace Tensorflow
@@ -18,9 +17,9 @@ namespace Tensorflow
         public TensorSpec[] structure { get; set; }
 
         public TensorShape[] output_shapes => structure.Select(x => x.shape).ToArray();
-        
+
         public TF_DataType[] output_types => structure.Select(x => x.dtype).ToArray();
-        
+
         public TensorSpec[] element_spec => structure;
 
         public IDatasetV2 cache(string filename = "")
@@ -54,7 +53,7 @@ namespace Tensorflow
             bool use_inter_op_parallelism = true,
             bool preserve_cardinality = true,
             bool use_legacy_function = false)
-            => new MapDataset(this, 
+            => new MapDataset(this,
                 map_func,
                 use_inter_op_parallelism: use_inter_op_parallelism,
                 preserve_cardinality: preserve_cardinality,

src/TensorFlowNET.Core/Data/Datasets.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using NumSharp;
+using NumSharp;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/FlatMapDataset.cs

@@ -1,7 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
 using Tensorflow.Functions;
 
 namespace Tensorflow

src/TensorFlowNET.Core/Data/GeneratorDataset.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow.Data
+namespace Tensorflow.Data
 {
     public class GeneratorDataset : DatasetSource
     {

src/TensorFlowNET.Core/Data/IDataSet.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using NumSharp;
+using NumSharp;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/IDatasetV2.cs

@@ -1,7 +1,5 @@
 using System;
 using System.Collections.Generic;
-using System.Linq.Expressions;
-using System.Text;
 using Tensorflow.Framework.Models;
 
 namespace Tensorflow
@@ -23,7 +21,7 @@ namespace Tensorflow
         /// </summary>
         /// <param name="filename"></param>
         /// <returns></returns>
-        IDatasetV2 cache(string filename="");
+        IDatasetV2 cache(string filename = "");
 
         /// <summary>
         /// 
@@ -57,12 +55,12 @@ namespace Tensorflow
 
         IDatasetV2 optimize(string[] optimizations, string[] optimization_configs);
 
-        IDatasetV2 map(Func<Tensor, Tensor> map_func, 
+        IDatasetV2 map(Func<Tensor, Tensor> map_func,
             bool use_inter_op_parallelism = true,
             bool preserve_cardinality = false,
             bool use_legacy_function = false);
 
-        IDatasetV2 map(Func<Tensor, (Tensor, Tensor), (Tensor, Tensor)> map_func, 
+        IDatasetV2 map(Func<Tensor, (Tensor, Tensor), (Tensor, Tensor)> map_func,
             int num_parallel_calls = -1);
 
         IDatasetV2 flat_map(Func<Tensor, IDatasetV2> map_func);

src/TensorFlowNET.Core/Data/IModelLoader.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Threading.Tasks;
-using System.Collections.Generic;
-using System.Text;
-using NumSharp;
+using System.Threading.Tasks;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/IteratorBase.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     public class IteratorBase
     {

src/TensorFlowNET.Core/Data/IteratorResourceDeleter.cs

@@ -1,7 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/MapDataset.cs

@@ -1,10 +1,5 @@
 using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
 using Tensorflow.Functions;
-using Tensorflow.Graphs;
-using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/MnistDataSet.cs

@@ -1,8 +1,6 @@
-using System;
-using System.Collections.Generic;
+using NumSharp;
+using System;
 using System.Diagnostics;
-using System.Text;
-using NumSharp;
 
 namespace Tensorflow
 {
@@ -40,7 +38,7 @@ namespace Tensorflow
 
             var start = IndexInEpoch;
             // Shuffle for the first epoch
-            if(EpochsCompleted == 0 && start == 0 && shuffle)
+            if (EpochsCompleted == 0 && start == 0 && shuffle)
             {
                 var perm0 = np.arange(NumOfExamples);
                 np.random.shuffle(perm0);

src/TensorFlowNET.Core/Data/MnistModelLoader.cs

@@ -1,9 +1,7 @@
-using System;
-using System.Threading.Tasks;
-using System.Collections.Generic;
-using System.Text;
+using NumSharp;
+using System;
 using System.IO;
-using NumSharp;
+using System.Threading.Tasks;
 
 namespace Tensorflow
 {
@@ -90,7 +88,7 @@ namespace Tensorflow
 
             var validationImages = trainImages[np.arange(validationSize)];
             var validationLabels = trainLabels[np.arange(validationSize)];
-            
+
             trainImages = trainImages[np.arange(validationSize, end)];
             trainLabels = trainLabels[np.arange(validationSize, end)];
 
@@ -114,8 +112,8 @@ namespace Tensorflow
                 var magic = Read32(bytestream);
                 if (magic != 2051)
                     throw new Exception($"Invalid magic number {magic} in MNIST image file: {file}");
-                
-                var num_images =  Read32(bytestream);
+
+                var num_images = Read32(bytestream);
                 num_images = limit == null ? num_images : Math.Min(num_images, (int)limit);
 
                 var rows = Read32(bytestream);
@@ -136,25 +134,25 @@ namespace Tensorflow
         {
             if (!Path.IsPathRooted(file))
                 file = Path.Combine(AppContext.BaseDirectory, file);
-                
+
             using (var bytestream = new FileStream(file, FileMode.Open))
             {
                 var magic = Read32(bytestream);
                 if (magic != 2049)
                     throw new Exception($"Invalid magic number {magic} in MNIST label file: {file}");
-                
+
                 var num_items = Read32(bytestream);
                 num_items = limit == null ? num_items : Math.Min(num_items, (int)limit);
-                
+
                 var buf = new byte[num_items];
 
                 bytestream.Read(buf, 0, buf.Length);
-                
+
                 var labels = np.frombuffer(buf, np.uint8);
 
                 if (one_hot)
                     return DenseToOneHot(labels, num_classes);
-                
+
                 return labels;
             }
         }

src/TensorFlowNET.Core/Data/ModelDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using Tensorflow.Framework.Models;
+using Tensorflow.Framework.Models;
 
 namespace Tensorflow
 {
@@ -10,8 +7,8 @@ namespace Tensorflow
     /// </summary>
     public class ModelDataset : UnaryUnchangedStructureDataset
     {
-        public ModelDataset(IDatasetV2 input_dataset, 
-            AutotuneAlgorithm algorithm, 
+        public ModelDataset(IDatasetV2 input_dataset,
+            AutotuneAlgorithm algorithm,
             long cpu_budget) :
             base(input_dataset)
         {

src/TensorFlowNET.Core/Data/ModelLoadSetting.cs

@@ -1,7 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
-using NumSharp;
 
 namespace Tensorflow
 {
@@ -12,7 +9,7 @@ namespace Tensorflow
         public Type DataType { get; set; } = typeof(float);
         public bool ReShape { get; set; }
         public int ValidationSize { get; set; } = 5000;
-        public int? TrainSize  { get; set; }
+        public int? TrainSize { get; set; }
         public int? TestSize { get; set; }
         public string SourceUrl { get; set; }
         public bool ShowProgressInConsole { get; set; }

src/TensorFlowNET.Core/Data/OptimizeDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -12,9 +9,9 @@ namespace Tensorflow
     {
         Tensor _optimizations;
 
-        public OptimizeDataset(IDatasetV2 dataset, 
-            string[] optimizations = null, 
-            string[] optimization_configs = null) : 
+        public OptimizeDataset(IDatasetV2 dataset,
+            string[] optimizations = null,
+            string[] optimization_configs = null) :
             base(dataset)
         {
             if (optimizations == null)
@@ -26,7 +23,7 @@ namespace Tensorflow
             variant_tensor = ops.optimize_dataset(
                 _input_dataset.variant_tensor,
                 _optimizations,
-                output_types, 
+                output_types,
                 output_shapes,
                 optimization_configs: optimization_configs);
         }

src/TensorFlowNET.Core/Data/OptionsDataset.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     /// <summary>
     /// An identity `Dataset` that stores options.
@@ -11,7 +7,7 @@ namespace Tensorflow
     {
         DatasetOptions options;
 
-        public OptionsDataset(IDatasetV2 input_dataset, DatasetOptions options) 
+        public OptionsDataset(IDatasetV2 input_dataset, DatasetOptions options)
             : base(input_dataset)
         {
             this.options = options;

src/TensorFlowNET.Core/Data/OwnedIterator.cs

@@ -1,6 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
 using Tensorflow.Framework.Models;
 
 namespace Tensorflow

src/TensorFlowNET.Core/Data/ParallelMapDataset.cs

@@ -1,7 +1,5 @@
 using System;
-using System.Collections.Generic;
 using System.Linq;
-using System.Text;
 using Tensorflow.Functions;
 using static Tensorflow.Binding;
 
@@ -10,14 +8,14 @@ namespace Tensorflow
     //A `Dataset` that maps a function over elements in its input in parallel.
     public class ParallelMapDataset : UnaryDataset
     {
-        public ParallelMapDataset(IDatasetV2 input_dataset, 
+        public ParallelMapDataset(IDatasetV2 input_dataset,
             Func<Tensor, (Tensor, Tensor), (Tensor, Tensor)> map_func,
             int num_parallel_calls = -1,
             bool use_inter_op_parallelism = true,
             bool preserve_cardinality = false,
             bool use_legacy_function = false) : base(input_dataset)
         {
-            var func = new ConcreteFunction(map_func, 
+            var func = new ConcreteFunction(map_func,
                 input_dataset.element_spec.Select(x => x.dtype).ToArray(),
                 input_dataset.element_spec.Select(x => x.shape).ToArray());
 

src/TensorFlowNET.Core/Data/PrefetchDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -13,7 +10,7 @@ namespace Tensorflow
         Tensor _buffer_size;
 
         public PrefetchDataset(IDatasetV2 input_dataset,
-            long buffer_size = -1, 
+            long buffer_size = -1,
             int? slack_period = null) :
             base(input_dataset)
         {

src/TensorFlowNET.Core/Data/RangeDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using Tensorflow.Framework.Models;
+using Tensorflow.Framework.Models;
 using static Tensorflow.Binding;
 
 namespace Tensorflow.Data
@@ -12,8 +9,8 @@ namespace Tensorflow.Data
         Tensor step;
         Tensor stop;
 
-        public RangeDataset(int stop, 
-            int start = 0, 
+        public RangeDataset(int stop,
+            int start = 0,
             int step = 1,
             TF_DataType output_type = TF_DataType.TF_INT64)
         {

src/TensorFlowNET.Core/Data/RepeatDataset.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     /// <summary>
     /// A `Dataset` that repeats its input several times.

src/TensorFlowNET.Core/Data/ShardDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/ShuffleDataset.cs

@@ -1,6 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
 using static Tensorflow.Binding;
 
 namespace Tensorflow
@@ -15,9 +13,9 @@ namespace Tensorflow
         Tensor _seed2;
         bool _reshuffle_each_iteration;
 
-        public ShuffleDataset(IDatasetV2 input_dataset, 
-            long buffer_size, 
-            int? seed = null, 
+        public ShuffleDataset(IDatasetV2 input_dataset,
+            long buffer_size,
+            int? seed = null,
             bool reshuffle_each_iteration = true) :
             base(input_dataset)
         {

src/TensorFlowNET.Core/Data/SkipDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -16,7 +13,7 @@ namespace Tensorflow
             int count) : base(input_dataset)
         {
             _count = tf.convert_to_tensor(count, dtype: dtypes.int64, name: "count");
-            variant_tensor = ops.skip_dataset(input_dataset.variant_tensor, 
+            variant_tensor = ops.skip_dataset(input_dataset.variant_tensor,
                     _count,
                     output_types, output_shapes);
         }

src/TensorFlowNET.Core/Data/TakeDataset.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using static Tensorflow.Binding;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Data/TensorDataset.cs

@@ -1,8 +1,5 @@
 using NumSharp;
-using System;
-using System.Collections.Generic;
 using System.Linq;
-using System.Text;
 using static Tensorflow.Binding;
 
 namespace Tensorflow

src/TensorFlowNET.Core/Data/TensorSliceDataset.cs

@@ -1,10 +1,5 @@
 using NumSharp;
-using NumSharp.Utilities;
-using System;
-using System.Collections.Generic;
 using System.Linq;
-using System.Text;
-using Tensorflow.Framework.Models;
 using static Tensorflow.Binding;
 
 namespace Tensorflow.Data
@@ -45,7 +40,7 @@ namespace Tensorflow.Data
             _tensors = new[] { features, labels };
             var batched_spec = _tensors.Select(x => x.ToTensorSpec()).ToArray();
             structure = batched_spec.Select(x => x._unbatch()).ToArray();
-            
+
             variant_tensor = ops.tensor_slice_dataset(_tensors, output_shapes);
         }
     }

src/TensorFlowNET.Core/Data/UnaryDataset.cs

@@ -1,9 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using Tensorflow.Framework.Models;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     /// <summary>
     /// Abstract class representing a dataset with one input.

src/TensorFlowNET.Core/Data/UnaryUnchangedStructureDataset.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     /// <summary>
     /// Represents a unary dataset with the same input and output structure.
@@ -12,7 +8,7 @@ namespace Tensorflow
         public UnaryUnchangedStructureDataset(IDatasetV2 input_dataset) :
             base(input_dataset)
         {
-            
+
         }
     }
 }

src/TensorFlowNET.Core/Data/Utils.cs

@@ -1,12 +1,9 @@
 using System;
 using System.IO;
 using System.IO.Compression;
-using System.Collections.Generic;
 using System.Net;
-using System.Text;
 using System.Threading;
 using System.Threading.Tasks;
-using Tensorflow.Framework.Models;
 
 namespace Tensorflow
 {
@@ -42,9 +39,9 @@ namespace Tensorflow
 
                 return;
             }
-            
+
             Directory.CreateDirectory(dirSaveTo);
-                
+
             using (var wc = new WebClient())
             {
                 await wc.DownloadFileTaskAsync(url, fileSaveTo).ConfigureAwait(false);
@@ -73,7 +70,7 @@ namespace Tensorflow
             {
                 if (showProgressInConsole)
                     Console.WriteLine($"The file {destFileName} already exists");
-            }            
+            }
 
             using (GZipStream unzipStream = new GZipStream(File.OpenRead(zipFile), CompressionMode.Decompress))
             {
@@ -86,7 +83,7 @@ namespace Tensorflow
 
                 unzipStream.Close();
             }
-        }        
+        }
 
         public static async Task ShowProgressInConsole(this Task task, bool enable)
         {
@@ -101,12 +98,12 @@ namespace Tensorflow
             var showProgressTask = ShowProgressInConsole(cts);
 
             try
-            {                
+            {
                 await task;
             }
             finally
             {
-                cts.Cancel();                
+                cts.Cancel();
             }
 
             await showProgressTask;

src/TensorFlowNET.Core/Data/ZipDataset.cs

@@ -1,7 +1,5 @@
-using System;
-using System.Collections.Generic;
+using System.Collections.Generic;
 using System.Linq;
-using System.Text;
 using Tensorflow.Framework.Models;
 
 namespace Tensorflow

src/TensorFlowNET.Core/DisposableObject.cs

@@ -15,10 +15,8 @@
 ******************************************************************************/
 
 using System;
-using System.Collections.Generic;
 using System.Diagnostics.CodeAnalysis;
 using System.Runtime.CompilerServices;
-using System.Text;
 
 namespace Tensorflow
 {
@@ -77,7 +75,7 @@ namespace Tensorflow
 
         public void Dispose()
         {
-            lock(this)
+            lock (this)
             {
                 internal_dispose(true);
                 GC.SuppressFinalize(this);

src/TensorFlowNET.Core/Eager/EagerOperation.cs

@@ -1,8 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-using static Tensorflow.Binding;
 
 namespace Tensorflow.Eager
 {

src/TensorFlowNET.Core/Eager/EagerRunner.ArgsToMatchingEager.cs

@@ -14,10 +14,9 @@
    limitations under the License.
 ******************************************************************************/
 
-using System.Collections.Generic;
 using System;
+using System.Collections.Generic;
 using System.Linq;
-using static Tensorflow.Binding;
 using Tensorflow.Contexts;
 
 namespace Tensorflow.Eager

src/TensorFlowNET.Core/Eager/EagerRunner.Execute.cs

@@ -14,10 +14,8 @@
    limitations under the License.
 ******************************************************************************/
 
-using System.Linq;
-using System;
-using static Tensorflow.Binding;
 using Tensorflow.Contexts;
+using static Tensorflow.Binding;
 
 namespace Tensorflow.Eager
 {

src/TensorFlowNET.Core/Eager/EagerRunner.RecordGradient.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
+using System.Linq;
 using Tensorflow.Gradients;
 using static Tensorflow.Binding;
 using static Tensorflow.tensorflow;
@@ -21,7 +18,7 @@ namespace Tensorflow.Eager
             bool should_record = false;
             foreach (var tape in tf.GetTapeSet())
             {
-                if(tape.ShouldRecord(input_ids, input_dtypes))
+                if (tape.ShouldRecord(input_ids, input_dtypes))
                 {
                     should_record = true;
                     break;
@@ -66,7 +63,7 @@ namespace Tensorflow.Eager
             bool op_inputs_tuple_created = false;
 #pragma warning restore CS0219 // Variable is assigned but its value is never used
             var unused_input_indices = gradient_exclustions.OpGradientUnusedInputIndices(op_name);
-            if(unused_input_indices != null)
+            if (unused_input_indices != null)
             {
                 if (unused_input_indices.Length == 0)
                     op_inputs = new Tensor[0];
@@ -79,7 +76,7 @@ namespace Tensorflow.Eager
             else
                 op_inputs = inputs;
 
-            TapeSetRecordOperation(op_name, inputs, results, input_ids, input_dtypes, 
+            TapeSetRecordOperation(op_name, inputs, results, input_ids, input_dtypes,
                 () => GetGradientFunction(op_name, inputs, attrs, results));
 
 

src/TensorFlowNET.Core/Eager/EagerRunner.RunCallbacks.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Tensorflow.Eager
+namespace Tensorflow.Eager
 {
     public partial class EagerRunner
     {

src/TensorFlowNET.Core/Eager/EagerRunner.TFE_Execute.cs

@@ -15,9 +15,8 @@
 ******************************************************************************/
 
 using System.Linq;
-using System;
-using static Tensorflow.Binding;
 using Tensorflow.Contexts;
+using static Tensorflow.Binding;
 
 namespace Tensorflow.Eager
 {

src/TensorFlowNET.Core/Eager/EagerRunner.TFE_FastPathExecute.cs

@@ -1,12 +1,12 @@
-using System.Collections.Generic;
+using System;
+using System.Collections.Generic;
 using System.Linq;
-using System;
-using static Tensorflow.OpDef.Types;
-using static Tensorflow.Binding;
-using Tensorflow.Util;
 using System.Runtime.InteropServices;
 using Tensorflow.Contexts;
 using Tensorflow.Functions;
+using Tensorflow.Util;
+using static Tensorflow.Binding;
+using static Tensorflow.OpDef.Types;
 
 namespace Tensorflow.Eager
 {
@@ -61,7 +61,7 @@ namespace Tensorflow.Eager
                 var attr_value = args[i + 1];
 
                 var attr = op_def.Attr.FirstOrDefault(x => x.Name == attr_name);
-                if(attr != null)
+                if (attr != null)
                 {
                     flattened_attrs.Add(attr_name);
                     flattened_attrs.Add(attr_value);
@@ -89,7 +89,7 @@ namespace Tensorflow.Eager
                         flattened_attrs.Add(len);
                     }
                     attr_list_sizes[input_arg.NumberAttr] = len;
-                    
+
                     if (len > 0)
                     {
                         var fast_input_array = (object[])args[i];
@@ -179,7 +179,7 @@ namespace Tensorflow.Eager
                 op = c_api.TFE_NewOp(ctx.Handle, op_or_function_name, status.Handle);
                 thread_local_eager_operation_map[ctx] = op;
             }
-                
+
             status.Check(true);
             return op;
         }
@@ -189,7 +189,7 @@ namespace Tensorflow.Eager
             //return !GetAccumulatorSet()->empty();
             return false;
         }
-        
+
         bool HasGradientTape()
         {
             return tf.GetTapeSet().Count > 0;
@@ -262,7 +262,7 @@ namespace Tensorflow.Eager
                 var key = attrs[i].ToString();
                 var value = attrs[i + 1];
 
-                byte is_list = 0; 
+                byte is_list = 0;
                 var type = c_api.TFE_OpGetAttrType(op, key, ref is_list, status.Handle);
                 if (!status.ok()) return;
                 if (is_list != 0)
@@ -286,8 +286,8 @@ namespace Tensorflow.Eager
         /// <param name="attr_value"></param>
         /// <param name="attr_list_sizes"></param>
         /// <param name="status"></param>
-        void SetOpAttrWithDefaults(Context ctx, SafeOpHandle op, AttrDef attr, 
-            string attr_name, object attr_value,  
+        void SetOpAttrWithDefaults(Context ctx, SafeOpHandle op, AttrDef attr,
+            string attr_name, object attr_value,
             Dictionary<string, long> attr_list_sizes,
             Status status)
         {
@@ -295,7 +295,7 @@ namespace Tensorflow.Eager
             var type = c_api.TFE_OpGetAttrType(op, attr_name, ref is_list, status.Handle);
             if (status.Code != TF_Code.TF_OK) return;
 
-            if(attr_value == null)
+            if (attr_value == null)
             {
                 if (is_list != 0)
 #pragma warning disable CS0642 // Possible mistaken empty statement
@@ -345,7 +345,7 @@ namespace Tensorflow.Eager
                 c_api.TFE_OpSetAttrShapeList(op, key, dims, num_dims, num_values, status.Handle);
                 Array.ForEach(dims, x => Marshal.FreeHGlobal(x));
             }
-            else if(type == TF_AttrType.TF_ATTR_TYPE && values is TF_DataType[] values2)
+            else if (type == TF_AttrType.TF_ATTR_TYPE && values is TF_DataType[] values2)
             {
                 c_api.TFE_OpSetAttrTypeList(op, key, values2, values2.Length);
                 attr_list_sizes[key] = values2.Length;
@@ -363,12 +363,12 @@ namespace Tensorflow.Eager
             return true;
         }
 
-        bool SetOpAttrScalar(Context ctx, SafeOpHandle op, 
+        bool SetOpAttrScalar(Context ctx, SafeOpHandle op,
             string key, object value, TF_AttrType type,
             Dictionary<string, long> attr_list_sizes,
             Status status)
         {
-            switch(type)
+            switch (type)
             {
                 case TF_AttrType.TF_ATTR_STRING:
                     c_api.TFE_OpSetAttrString(op, key, value.ToString(), (uint)value.ToString().Length);
@@ -394,7 +394,7 @@ namespace Tensorflow.Eager
                     if (value is ConcreteFunction func)
                         c_api.TFE_OpSetAttrFunctionName(op, key, func.Name, func.Name.Length);
                     else
-                        throw new NotImplementedException("TF_AttrType.TF_ATTR_FUNC"); 
+                        throw new NotImplementedException("TF_AttrType.TF_ATTR_FUNC");
                     break;
                 default:
                     throw new NotImplementedException($"SetOpAttrScalar for {type}");

src/TensorFlowNET.Core/Eager/EagerRunner.TFE_TapeGradient.cs

@@ -1,7 +1,4 @@
-using System.Collections.Generic;
-using System.Linq;
-using System;
-using static Tensorflow.OpDef.Types;
+using System;
 using Tensorflow.Gradients;
 using Tensorflow.Util;
 
@@ -31,7 +28,7 @@ namespace Tensorflow.Eager
                 source_tensors_that_are_targets.Add(target_id, TapeTensorFromTensor(tensor));
             }
 
-            if(output_gradients != null)
+            if (output_gradients != null)
             {
                 throw new NotImplementedException("");
             }

src/TensorFlowNET.Core/Eager/EagerRunner.TapeSetRecordBackprop.cs

@@ -1,6 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
 using Tensorflow.Gradients;
 using static Tensorflow.Binding;
 using static Tensorflow.tensorflow;
@@ -21,7 +19,7 @@ namespace Tensorflow.Eager
                 return;
             }
 
-            foreach(var tape in tf.GetTapeSet())
+            foreach (var tape in tf.GetTapeSet())
             {
                 tape.RecordOperation(op_type, input_tensors, output_tensors,
                     input_ids, input_dtypes,

src/TensorFlowNET.Core/Eager/EagerRunner.TapeSetRecordForwardprop.cs

@@ -1,6 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
 using Tensorflow.Gradients;
 using static Tensorflow.tensorflow;
 

src/TensorFlowNET.Core/Eager/EagerRunner.TapeSetRecordOperation.cs

@@ -1,7 +1,5 @@
 using System;
 using System.Collections.Generic;
-using System.Linq;
-using System.Text;
 using Tensorflow.Gradients;
 using static Tensorflow.tensorflow;
 

src/TensorFlowNET.Core/Eager/EagerRunner.TapeTensorFromTensor.cs

@@ -1,8 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-using Tensorflow.Gradients;
+using Tensorflow.Gradients;
 
 namespace Tensorflow.Eager
 {

src/TensorFlowNET.Core/Eager/EagerRunner.TapeTensorsFromTensorSequence.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
+using System.Collections.Generic;
 using Tensorflow.Gradients;
 
 namespace Tensorflow.Eager

src/TensorFlowNET.Core/Eager/EagerRunner.cs

@@ -1,10 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using Tensorflow.Gradients;
-using static Tensorflow.Binding;
-
-namespace Tensorflow.Eager
+namespace Tensorflow.Eager
 {
     /// <summary>
     /// Eager mode runner

src/TensorFlowNET.Core/Eager/EagerTensor.Creation.cs

@@ -1,8 +1,5 @@
 using NumSharp;
 using System;
-using System.Collections.Generic;
-using System.Text;
-using System.Threading;
 using static Tensorflow.Binding;
 
 namespace Tensorflow.Eager
@@ -11,7 +8,7 @@ namespace Tensorflow.Eager
     {
         public EagerTensor() : base(IntPtr.Zero)
         {
-            
+
         }
 
         public EagerTensor(SafeTensorHandleHandle handle) : base(IntPtr.Zero)
@@ -84,7 +81,7 @@ namespace Tensorflow.Eager
 
         void copy_handle_data(Tensor target_t)
         {
-            if(target_t.dtype == TF_DataType.TF_RESOURCE ||
+            if (target_t.dtype == TF_DataType.TF_RESOURCE ||
                 target_t.dtype == TF_DataType.TF_VARIANT)
             {
                 // need to export

src/TensorFlowNET.Core/Eager/EagerTensor.Implicit.cs

@@ -1,8 +1,4 @@
-using NumSharp;
-using System;
-using System.Collections.Generic;
-using System.Text;
-using Tensorflow.Eager;
+using System;
 
 namespace Tensorflow.Eager
 {

src/TensorFlowNET.Core/Eager/EagerTensor.ToString.cs

@@ -1,11 +1,4 @@
-using NumSharp;
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-using static Tensorflow.Binding;
-
-namespace Tensorflow.Eager
+namespace Tensorflow.Eager
 {
     public partial class EagerTensor
     {

src/TensorFlowNET.Core/Eager/EagerTensor.cs

@@ -1,6 +1,4 @@
-using NumSharp;
-using System;
-using System.Linq;
+using System;
 using Tensorflow.Util;
 using static Tensorflow.Binding;
 

src/TensorFlowNET.Core/Eager/FastPathOpExecInfo.cs

@@ -1,7 +1,4 @@
-using System;
-using System.Collections.Generic;
-using System.Text;
-using Tensorflow.Contexts;
+using Tensorflow.Contexts;
 
 namespace Tensorflow.Eager
 {

src/TensorFlowNET.Core/Eager/IEagerRunner.cs

@@ -1,6 +1,4 @@
 using System;
-using System.Collections.Generic;
-using System.Text;
 using Tensorflow.Contexts;
 using Tensorflow.Gradients;
 
@@ -13,8 +11,8 @@ namespace Tensorflow.Eager
             Tensor[] inputs, object[] attrs,
             string name = null);
 
-        (TF_DataType, Tensor[]) ArgsToMatchingEager(Context ctx, 
-            TF_DataType default_dtype = TF_DataType.DtInvalid, 
+        (TF_DataType, Tensor[]) ArgsToMatchingEager(Context ctx,
+            TF_DataType default_dtype = TF_DataType.DtInvalid,
             object[] args = null);
 
         Tensor[] TFE_FastPathExecute(Context ctx,

src/TensorFlowNET.Core/Eager/c_api.eager.cs

@@ -242,7 +242,7 @@ namespace Tensorflow
         /// <param name="length">size_t</param>
         [DllImport(TensorFlowLibName)]
         public static extern void TFE_OpSetAttrString(SafeOpHandle op, string attr_name, string value, uint length);
-    
+
         [DllImport(TensorFlowLibName)]
         public static extern void TFE_OpSetAttrTypeList(SafeOpHandle op, string attr_name, TF_DataType[] values, int num_values);
 
@@ -442,8 +442,8 @@ namespace Tensorflow
         public static extern IntPtr ResourceVariable_Handle(IntPtr variable);
 
         [DllImport(TensorFlowLibName)]
-        public static extern SafeStatusHandle TFE_TapeGradient(IntPtr tape, 
-            IntPtr[] target, int target_size, 
+        public static extern SafeStatusHandle TFE_TapeGradient(IntPtr tape,
+            IntPtr[] target, int target_size,
             IntPtr[] sources, int source_size,
             IntPtr[] outputs, int output_size);
     }

src/TensorFlowNET.Core/Exceptions/InvalidArgumentError.cs

@@ -1,6 +1,4 @@
-using System;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     public class InvalidArgumentError : TensorflowException
     {

src/TensorFlowNET.Core/Exceptions/KeyError.cs

@@ -1,6 +1,4 @@
-using System;
-
-namespace Tensorflow
+namespace Tensorflow
 {
     public class KeyError : TensorflowException
     {