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deepakkumar1984deepakkumar1984
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Sequential, Metric base and Metric Util class skeleton methods added
1 parent 4977716 commit 4deb320

7 files changed

Lines changed: 145 additions & 18 deletions

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‎src/TensorFlowNET.Keras/Args.cs‎

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using System;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Args
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{
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private List<object> args = new List<object>();
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public object this[int index]
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{
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get
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{
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return args.Count < index ? args[index] : null;
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}
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}
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public T Get<T>(int index)
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{
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return args.Count < index ? (T)args[index] : default(T);
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}
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public void Add<T>(T arg)
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{
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args.Add(arg);
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}
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}
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}

‎src/TensorFlowNET.Keras/Engine/Node.cs‎

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namespace Tensorflow.Keras.Engine
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{
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class Node
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public class Node
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{
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}
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}

‎src/TensorFlowNET.Keras/Engine/Sequential.cs‎

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namespace Tensorflow.Keras.Engine
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{
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class Sequential
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public class Sequential
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{
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}
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}

‎src/TensorFlowNET.Keras/Metrics/Metric.cs‎

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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras.Metrics
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{
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public abstract class Metric
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public abstract class Metric : Layers.Layer
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{
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public string dtype
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{
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get
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{
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throw new NotImplementedException();
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}
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}
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public Metric(string name, string dtype)
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{
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throw new NotImplementedException();
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}
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public void __new__ (Metric cls, Args args, KwArgs kwargs) => throw new NotImplementedException();
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public Tensor __call__(Metric cls, Args args, KwArgs kwargs) => throw new NotImplementedException();
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public virtual Hashtable get_config() => throw new NotImplementedException();
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public virtual void reset_states() => throw new NotImplementedException();
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public abstract void update_state(Args args, KwArgs kwargs);
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public abstract Tensor result();
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public void add_weight(string name, TensorShape shape= null, VariableAggregation aggregation= VariableAggregation.Sum,
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VariableSynchronization synchronization = VariableSynchronization.OnRead, Initializers.Initializer initializer= null,
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string dtype= null) => throw new NotImplementedException();
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}
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}

‎src/TensorFlowNET.Keras/Models.cs‎

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using System;
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using Keras.Layers;
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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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using Tensorflow.Keras.Engine;
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namespace Tensorflow.Keras
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{
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class Models
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{
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public class Model : Keras.Engine.Training.Model
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{
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public class Model : Keras.Engine.Training.Model{}
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}
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public static Layer share_weights(Layer layer) => throw new NotImplementedException();
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private static Layer _clone_layer(Layer layer) => throw new NotImplementedException();
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private static Layer _insert_ancillary_layers(Model model, Layer ancillary_layers, string[] metrics_names, Node[] new_nodes) => throw new NotImplementedException();
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private static Node[] _make_new_nodes(Node[] nodes_by_depth, Func<Layer, Layer> layer_fn, Hashtable layer_map, Hashtable tensor_map) => throw new NotImplementedException();
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private static Model _clone_functional_model(Model model, Tensor[] input_tensors = null, Func<Layer, Layer> layer_fn = null) => throw new NotImplementedException();
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private static (Hashtable, Layer[]) _clone_layers_and_model_config(Model model, Layer[] input_layers, Func<Layer, Layer> layer_fn) => throw new NotImplementedException();
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private static (Layer[], Layer[]) _remove_ancillary_layers(Model model, Hashtable layer_map, Layer[] layers) => throw new NotImplementedException();
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private static Sequential _clone_sequential_model(Model model, Tensor[] input_tensors = null, Func<Layer, Layer> layer_fn = null) => throw new NotImplementedException();
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public static Model clone_model(Model model, Tensor[] input_tensors = null, Func<Layer, Layer> layer_fn = null) => throw new NotImplementedException();
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private static void _in_place_subclassed_model_reset(Model model) => throw new NotImplementedException();
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private static void _reset_build_compile_trackers(Model model) => throw new NotImplementedException();
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public static void in_place_subclassed_model_state_restoration(Model model) => throw new NotImplementedException();
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public static void clone_and_build_model(Model model, Tensor[] input_tensors= null, Tensor[] target_tensors= null, object custom_objects= null,
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bool compile_clone= true, bool in_place_reset= false, VariableV1 optimizer_iterations= null, Hashtable optimizer_config= null)
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=> throw new NotImplementedException();
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}
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}

‎src/TensorFlowNET.Keras/Ops.cs‎

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This file was deleted.

‎src/TensorFlowNET.Keras/Utils/MetricsUtils.cs‎

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using System;
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using System.Collections.Generic;
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using System.Reflection;
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using System.Text;
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namespace Tensorflow.Keras.Utils
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{
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class MetricsUtils
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public class MetricsUtils
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{
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public static class Reduction
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{
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public const string SUM = "sum";
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public const string SUM_OVER_BATCH_SIZE = "sum_over_batch_size";
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public const string WEIGHTED_MEAN = "weighted_mean";
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}
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public static class ConfusionMatrix
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{
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public const string TRUE_POSITIVES = "tp";
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public const string FALSE_POSITIVES = "fp";
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public const string TRUE_NEGATIVES = "tn";
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public const string FALSE_NEGATIVES = "fn";
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}
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public static class AUCCurve
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{
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public const string ROC = "ROC";
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public const string PR = "PR";
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public static string from_str(string key) => throw new NotImplementedException();
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}
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public static class AUCSummationMethod
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{
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public const string INTERPOLATION = "interpolation";
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public const string MAJORING = "majoring";
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public const string MINORING = "minoring";
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public static string from_str(string key) => throw new NotImplementedException();
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}
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public static dynamic update_state_wrapper(Func<Args, KwArgs, Func<bool>> update_state_fn) => throw new NotImplementedException();
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public static dynamic result_wrapper(Func<Args, Tensor> result_fn) => throw new NotImplementedException();
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public static WeakReference weakmethod(MethodInfo method) => throw new NotImplementedException();
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public static void assert_thresholds_range(float[] thresholds) => throw new NotImplementedException();
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public static void parse_init_thresholds(float[] thresholds, float default_threshold = 0.5f) => throw new NotImplementedException();
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public static Operation update_confusion_matrix_variables(variables variables_to_update, Tensor y_true, Tensor y_pred, float[] thresholds,
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int? top_k= null,int? class_id= null, Tensor sample_weight= null, bool multi_label= false,
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Tensor label_weights= null) => throw new NotImplementedException();
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private static Tensor _filter_top_k(Tensor x, int k) => throw new NotImplementedException();
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private static (Tensor[], Tensor) ragged_assert_compatible_and_get_flat_values(Tensor[] values, Tensor mask = null) => throw new NotImplementedException();
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}
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}

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