np.randint

Author: Oceania2018

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

@@ -71,7 +71,7 @@ public Tensor uniform(Shape shape,
                 string name = null)
             {
                 if (dtype.is_integer())
-                    return random_ops.random_uniform_int(shape, (int)minval, (int)maxval, dtype, seed, name);
+                    return random_ops.random_uniform_int(shape, (int)minval, (int)maxval, seed, name);
                 else
                     return random_ops.random_uniform(shape, minval, maxval, dtype, seed, name);
             }

src/TensorFlowNET.Core/NumPy/Implementation/RandomizedImpl.cs

@@ -23,8 +23,18 @@ public void shuffle(NDArray x)
         public NDArray rand(params int[] shape)
             => throw new NotImplementedException("");
 
+        [AutoNumPy]
         public NDArray randint(int low, int? high = null, Shape size = null, TF_DataType dtype = TF_DataType.TF_INT32)
-            => throw new NotImplementedException("");
+        {
+            if(high == null)
+            {
+                high = low;
+                low = 0;
+            }
+            size = size ?? Shape.Scalar;
+            var tensor = random_ops.random_uniform_int(shape: size, minval: low, maxval: (int)high);
+            return new NDArray(tensor);
+        }
 
         public NDArray normal(float loc = 0.0f, float scale = 1.0f, Shape size = null)
             => throw new NotImplementedException("");

src/TensorFlowNET.Core/Operations/random_ops.cs

@@ -94,7 +94,6 @@ public static Tensor random_uniform(int[] shape,
         public static Tensor random_uniform_int(int[] shape,
             int minval = 0,
             int maxval = 1,
-            TF_DataType dtype = TF_DataType.TF_FLOAT,
             int? seed = null,
             string name = null)
         {
@@ -103,8 +102,8 @@ public static Tensor random_uniform_int(int[] shape,
                 name = scope;
                 var (seed1, seed2) = random_seed.get_seed(seed);
                 var tensorShape = tensor_util.shape_tensor(shape);
-                var minTensor = ops.convert_to_tensor(minval, dtype: dtype, name: "min");
-                var maxTensor = ops.convert_to_tensor(maxval, dtype: dtype, name: "max");
+                var minTensor = ops.convert_to_tensor(minval, name: "min");
+                var maxTensor = ops.convert_to_tensor(maxval, name: "max");
                 return gen_random_ops.random_uniform_int(tensorShape, minTensor, maxTensor, seed: seed1, seed2: seed2);
             });
         }