diff --git a/src/TensorFlowNET.Core/APIs/tf.math.cs b/src/TensorFlowNET.Core/APIs/tf.math.cs index 66e1ba00..4ad70420 100644 --- a/src/TensorFlowNET.Core/APIs/tf.math.cs +++ b/src/TensorFlowNET.Core/APIs/tf.math.cs @@ -528,5 +528,7 @@ namespace Tensorflow public Tensor square(Tensor x, string name = null) => gen_math_ops.square(x, name: name); + public Tensor squared_difference(Tensor x, Tensor y, string name = null) + => gen_math_ops.squared_difference(x: x, y: y, name: name); } } diff --git a/src/TensorFlowNET.Core/APIs/tf.nn.cs b/src/TensorFlowNET.Core/APIs/tf.nn.cs index c8ce62f9..19afce1d 100644 --- a/src/TensorFlowNET.Core/APIs/tf.nn.cs +++ b/src/TensorFlowNET.Core/APIs/tf.nn.cs @@ -116,6 +116,8 @@ namespace Tensorflow public IActivation relu() => new relu(); public IActivation swish() => new swish(); public IActivation tanh() => new tanh(); + + public IActivation softmax() => new softmax(); public Tensor tanh(Tensor x, string name = null) => gen_nn_ops.tanh(x, name); diff --git a/src/TensorFlowNET.Core/APIs/tf.random.cs b/src/TensorFlowNET.Core/APIs/tf.random.cs index d6c7d93a..54fd57be 100644 --- a/src/TensorFlowNET.Core/APIs/tf.random.cs +++ b/src/TensorFlowNET.Core/APIs/tf.random.cs @@ -38,6 +38,12 @@ namespace Tensorflow TF_DataType dtype = TF_DataType.TF_FLOAT, int? seed = null, string name = null) => random_ops.random_normal(shape, mean, stddev, dtype, seed, name); + public Tensor categorical( + 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, name: name, output_dtype: output_dtype); } public Tensor random_uniform(TensorShape shape, diff --git a/src/TensorFlowNET.Core/APIs/tf.train.cs b/src/TensorFlowNET.Core/APIs/tf.train.cs index ca0ecc32..b3819b7b 100644 --- a/src/TensorFlowNET.Core/APIs/tf.train.cs +++ b/src/TensorFlowNET.Core/APIs/tf.train.cs @@ -38,8 +38,8 @@ namespace Tensorflow public Optimizer GradientDescentOptimizer(Tensor learning_rate) => new GradientDescentOptimizer(learning_rate); - public Optimizer AdamOptimizer(float learning_rate, string name = "Adam") - => new AdamOptimizer(learning_rate, 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);