8000 np.randint · SciSharp/TensorFlow.NET@9c5692b · GitHub
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np.randint
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+14
-5
lines changed

3 files changed

+14
-5
lines changed

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

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -71,7 +71,7 @@ public Tensor uniform(Shape shape,
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string name = null)
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{
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if (dtype.is_integer())
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return random_ops.random_uniform_int(shape, (int)minval, (int)maxval, dtype, seed, name);
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return random_ops.random_uniform_int(shape, (int)minval, (int)maxval, seed, name);
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else
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return random_ops.random_uniform(shape, minval, maxval, dtype, seed, name);
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}

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

Lines changed: 11 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -23,8 +23,18 @@ public void shuffle(NDArray x)
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public NDArray rand(params int[] shape)
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=> throw new NotImplementedException("");
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[AutoNumPy]
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public NDArray randint(int low, int? high = null, Shape size = null, TF_DataType dtype = TF_DataType.TF_INT32)
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=> throw new NotImplementedException("");
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{
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if(high == null)
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{
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high = low;
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low = 0;
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}
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size = size ?? Shape.Scalar;
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var tensor = random_ops.random_uniform_int(shape: size, minval: low, maxval: (int)high);
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return new NDArray(tensor);
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}
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public NDArray normal(float loc = 0.0f, float scale = 1.0f, Shape size = null)
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=> throw new NotImplementedException("");

‎src/TensorFlowNET.Core/Operations/random_ops.cs

Lines changed: 2 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -94,7 +94,6 @@ public static Tensor random_uniform(int[] shape,
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public static Tensor random_uniform_int(int[] shape,
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int minval = 0,
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int maxval = 1,
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TF_DataType dtype = TF_DataType.TF_FLOAT,
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int? seed = null,
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string name = null)
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{
@@ -103,8 +102,8 @@ public static Tensor random_uniform_int(int[] shape,
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name = scope;
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var (seed1, seed2) = random_seed.get_seed(seed);
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var tensorShape = tensor_util.shape_tensor(shape);
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var minTensor = ops.convert_to_tensor(minval, dtype: dtype, name: "min");
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var maxTensor = ops.convert_to_tensor(maxval, dtype: dtype, name: "max");
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var minTensor = ops.convert_to_tensor(minval, name: "min");
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var maxTensor = ops.convert_to_tensor(maxval, name: "max");
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return gen_random_ops.random_uniform_int(tensorShape, minTensor, maxTensor, seed: seed1, seed2: seed2);
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});
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}

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