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Oceania2018Oceania2018
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change tensorflow to non-static class in order to execute some initialization.
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106 files changed

Lines changed: 338 additions & 250 deletions

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‎src/KerasNET.Core/Core.cs‎

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@@ -1,4 +1,5 @@
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using Tensorflow;
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using static Tensorflow.Binding;
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namespace Keras
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{

‎src/KerasNET.Core/Layers/Dense.cs‎

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@@ -19,6 +19,7 @@ limitations under the License.
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using static Keras.Keras;
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using NumSharp;
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using Tensorflow.Operations.Activation;
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using static Tensorflow.Binding;
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namespace Keras.Layers
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{

‎src/KerasNET.Core/Model.cs‎

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@@ -19,7 +19,7 @@ limitations under the License.
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using System;
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using System.Collections.Generic;
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using Tensorflow;
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using static Tensorflow.Python;
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using static Tensorflow.Binding;
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namespace Keras
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{

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

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@@ -20,7 +20,7 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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/// <summary>
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/// Concatenates tensors along one dimension.
@@ -29,7 +29,7 @@ public static partial class tf
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/// <param name="axis"></param>
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/// <param name="name"></param>
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/// <returns>A `Tensor` resulting from concatenation of the input tensors.</returns>
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public static Tensor concat(IList<Tensor> values, int axis, string name = "concat")
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public Tensor concat(IList<Tensor> values, int axis, string name = "concat")
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{
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if (values.Count == 1)
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throw new NotImplementedException("tf.concat length is 1");
@@ -48,7 +48,7 @@ public static Tensor concat(IList<Tensor> values, int axis, string name = "conca
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/// A `Tensor` with the same data as `input`, but its shape has an additional
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/// dimension of size 1 added.
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/// </returns>
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public static Tensor expand_dims(Tensor input, int axis = -1, string name = null, int dim = -1)
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public Tensor expand_dims(Tensor input, int axis = -1, string name = null, int dim = -1)
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=> array_ops.expand_dims(input, axis, name, dim);
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/// <summary>
@@ -58,14 +58,14 @@ public static Tensor expand_dims(Tensor input, int axis = -1, string name = null
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/// <param name="value"></param>
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/// <param name="name"></param>
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/// <returns></returns>
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public static Tensor fill<T>(Tensor dims, T value, string name = null)
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public Tensor fill<T>(Tensor dims, T value, string name = null)
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=> gen_array_ops.fill(dims, value, name: name);
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/// <summary>
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/// Return the elements, either from `x` or `y`, depending on the `condition`.
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/// </summary>
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/// <returns></returns>
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public static Tensor where<Tx, Ty>(Tensor condition, Tx x, Ty y, string name = null)
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public Tensor where<Tx, Ty>(Tensor condition, Tx x, Ty y, string name = null)
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=> array_ops.where(condition, x, y, name);
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/// <summary>
@@ -76,10 +76,10 @@ public static Tensor where<Tx, Ty>(Tensor condition, Tx x, Ty y, string name = n
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/// <param name="name"></param>
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/// <param name="conjugate"></param>
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/// <returns></returns>
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public static Tensor transpose<T1>(T1 a, int[] perm = null, string name = "transpose", bool conjugate = false)
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public Tensor transpose<T1>(T1 a, int[] perm = null, string name = "transpose", bool conjugate = false)
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=> array_ops.transpose(a, perm, name, conjugate);
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82-
public static Tensor squeeze(Tensor input, int[] axis = null, string name = null, int squeeze_dims = -1)
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public Tensor squeeze(Tensor input, int[] axis = null, string name = null, int squeeze_dims = -1)
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=> gen_array_ops.squeeze(input, axis, name);
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/// <summary>
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/// <param name="axis"></param>
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/// <param name="name"></param>
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/// <returns></returns>
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public static Tensor stack(object values, int axis = 0, string name = "stack")
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public Tensor stack(object values, int axis = 0, string name = "stack")
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=> array_ops.stack(values, axis, name: name);
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public static Tensor one_hot(Tensor indices, int depth,
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public Tensor one_hot(Tensor indices, int depth,
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Tensor on_value = null,
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Tensor off_value = null,
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TF_DataType dtype = TF_DataType.DtInvalid,
@@ -110,7 +110,7 @@ public static Tensor one_hot(Tensor indices, int depth,
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/// </param>
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/// <param name="name">A name for the operation (optional).</param>
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/// <returns>A `Tensor`. Has the same type as `input`.</returns>
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public static Tensor placeholder_with_default<T>(T input, int[] shape, string name = null)
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public Tensor placeholder_with_default<T>(T input, int[] shape, string name = null)
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=> gen_array_ops.placeholder_with_default(input, shape, name: name);
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}
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}

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

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@@ -18,9 +18,9 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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public static Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor> body, Tensor[] loop_vars,
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public Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor> body, Tensor[] loop_vars,
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TensorShape shape_invariants = null,
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int parallel_iterations = 10,
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bool back_prop = true,
@@ -37,7 +37,7 @@ public static Tensor while_loop(Func<Tensor, Tensor> cond, Func<Tensor, Tensor>
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maximum_iterations: maximum_iterations,
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return_same_structure: return_same_structure);
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public static _ControlDependenciesController control_dependencies(Operation[] control_inputs)
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public _ControlDependenciesController control_dependencies(Operation[] control_inputs)
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=> ops.control_dependencies(control_inputs);
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}
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}

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

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@@ -16,11 +16,13 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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public static class distributions
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public distributions_internal distributions { get; } = new distributions_internal();
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public class distributions_internal
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{
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public static Normal Normal(Tensor loc,
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public Normal Normal(Tensor loc,
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Tensor scale,
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bool validate_args = false,
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bool allow_nan_stats = true,

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

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@@ -16,9 +16,9 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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public static Tensor exp(Tensor x,
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public Tensor exp(Tensor x,
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string name = null) => gen_math_ops.exp(x, name);
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}

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

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@@ -16,9 +16,9 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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public static Tensor[] gradients(Tensor[] ys,
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public Tensor[] gradients(Tensor[] ys,
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Tensor[] xs,
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Tensor[] grad_ys = null,
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string name = "gradients",
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stop_gradients: stop_gradients);
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}
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39-
public static Tensor[] gradients(Tensor ys,
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public Tensor[] gradients(Tensor ys,
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Tensor[] xs,
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Tensor[] grad_ys = null,
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string name = "gradients",
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stop_gradients: stop_gradients);
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}
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57-
public static Tensor[] gradients(Tensor ys,
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public Tensor[] gradients(Tensor ys,
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Tensor xs,
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Tensor[] grad_ys = null,
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string name = "gradients",

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

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@@ -16,15 +16,15 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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public static graph_util_impl graph_util => new graph_util_impl();
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public static Graph get_default_graph()
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public graph_util_impl graph_util => new graph_util_impl();
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public Graph get_default_graph()
2323
{
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return ops.get_default_graph();
2525
}
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27-
public static Graph Graph()
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public Graph Graph()
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=> new Graph();
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}
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}

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

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@@ -18,14 +18,14 @@ limitations under the License.
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namespace Tensorflow
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{
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public static partial class tf
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public partial class tensorflow
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{
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public static IInitializer zeros_initializer => new Zeros();
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public static IInitializer ones_initializer => new Ones();
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public static IInitializer glorot_uniform_initializer => new GlorotUniform();
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public static IInitializer uniform_initializer => new RandomUniform();
23+
public IInitializer zeros_initializer => new Zeros();
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public IInitializer ones_initializer => new Ones();
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public IInitializer glorot_uniform_initializer => new GlorotUniform();
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public IInitializer uniform_initializer => new RandomUniform();
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28-
public static variable_scope variable_scope(string name,
28+
public variable_scope variable_scope(string name,
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string default_name = null,
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Tensor[] values = null,
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bool? reuse = null,
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reuse: reuse,
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auxiliary_name_scope: auxiliary_name_scope);
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38-
public static variable_scope variable_scope(VariableScope scope,
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public variable_scope variable_scope(VariableScope scope,
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string default_name = null,
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Tensor[] values = null,
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bool? reuse = null,
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reuse: reuse,
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auxiliary_name_scope: auxiliary_name_scope);
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48-
public static IInitializer truncated_normal_initializer(float mean = 0.0f,
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public IInitializer truncated_normal_initializer(float mean = 0.0f,
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float stddev = 1.0f,
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int? seed = null,
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TF_DataType dtype = TF_DataType.DtInvalid) => new TruncatedNormal(mean: mean,

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