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gradients_impl. not finish yet. · attackgithub/TensorFlow.NET@c6f9ec6 · GitHub

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  2. TensorFlow.NET

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Commit c6f9ec6

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Oceania2018
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gradients_impl. not finish yet.
1 parent bcb803d commit c6f9ec6

7 files changed

Lines changed: 109 additions & 5 deletions

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‎src/TensorFlowNET.Core/Gradients/AggregationMethod.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
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{
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public class AggregationMethod
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{
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public static int ADD_N = 0;
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public static int DEFAULT = ADD_N;
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// The following are experimental and may not be supported in future releases.
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public static int EXPERIMENTAL_TREE = 1;
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public static int EXPERIMENTAL_ACCUMULATE_N = 2;
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}
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}

‎src/TensorFlowNET.Core/Gradients/gradients_impl.py.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
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{
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public class gradients_impl
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{
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public static void gradients(object ys,
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object xs,
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List<Tensor> grad_ys = null,
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string name = "gradients",
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bool colocate_gradients_with_ops = false,
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bool gate_gradients = false,
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int? aggregation_method = null)
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{
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_GradientsHelper(ys, xs, grad_ys, name, colocate_gradients_with_ops, gate_gradients);
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}
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public static void _GradientsHelper(object ys,
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object xs,
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List<Tensor> grad_ys = null,
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string name = "gradients",
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bool colocate_gradients_with_ops = false,
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bool gate_gradients = false,
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Graph src_graph = null)
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{
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if (src_graph == null)
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src_graph = ops.get_default_graph();
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}
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}
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}

‎src/TensorFlowNET.Core/Tensors/Tensor.cs‎

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@@ -222,7 +222,7 @@ public override string ToString()
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}
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}
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return "";
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return $"{name} {dtype} {rank} {string.Join(",", shape)}";
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}
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public void Dispose()

‎src/TensorFlowNET.Core/Train/Optimizer.cs‎

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@@ -1,5 +1,6 @@
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using distribute_lib = Tensorflow.Distribute;
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@@ -48,8 +49,10 @@ public Optimizer minimize(Tensor loss,
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/// <param name="gate_gradients"></param>
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public List<KeyValuePair<object, object>> compute_gradients(Tensor loss,
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List<RefVariable> var_list = null,
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int? aggregation_method = null,
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GateGradientType gate_gradients = GateGradientType.GATE_OP,
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bool colocate_gradients_with_ops = false)
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bool colocate_gradients_with_ops = false,
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List<Tensor> grad_loss = null)
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{
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int num_towers = 1;
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if(distribute_lib.get_loss_reduction() == VariableAggregationType.MEAN)
@@ -65,10 +68,13 @@ public List<KeyValuePair<object, object>> compute_gradients(Tensor loss,
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break;
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}
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foreach(var v in var_list)
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{
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var processors = var_list.Select(v => optimizer._get_processor(v));
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var var_refs = processors.Select(x => x.target()).ToList();
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}
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gradients_impl.gradients(loss, var_refs, grad_ys: grad_loss,
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gate_gradients: (gate_gradients == GateGradientType.GATE_OP),
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aggregation_method: aggregation_method,
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colocate_gradients_with_ops: colocate_gradients_with_ops);
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return null;
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}

‎src/TensorFlowNET.Core/Train/_OptimizableVariable.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
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{
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public interface _OptimizableVariable
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{
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Tensor target();
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void update_op(Graph g);
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}
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}

‎src/TensorFlowNET.Core/Train/optimizer.py.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
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{
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public class optimizer
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{
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public static _OptimizableVariable _get_processor(RefVariable v)
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{
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return new _RefVariableProcessor(v);
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}
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}
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public class _RefVariableProcessor : _OptimizableVariable
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{
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private RefVariable _v;
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public _RefVariableProcessor(RefVariable v)
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{
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_v = v;
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}
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public Tensor target()
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{
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return _v._ref();
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}
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public void update_op(Graph g)
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{
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}
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}
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}

‎src/TensorFlowNET.Core/Variables/RefVariable.cs‎

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@@ -78,6 +78,11 @@ private void _init_from_args(object initial_value,
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ops.add_to_collections(collections, this);
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}
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81+
public Tensor _ref()
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{
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return _variable;
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}
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public static implicit operator _VariableScopeStore(RefVariable variable)
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{
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return null;

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