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fix Multi Threaded unit test. · MSavameri/TensorFlow.NET@3f0b1f9 · GitHub

  1. MSavameri
  2. TensorFlow.NET

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Commit 3f0b1f9

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Oceania2018
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fix Multi Threaded unit test.
1 parent 8dd1eec commit 3f0b1f9

17 files changed

Lines changed: 208 additions & 36 deletions

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‎README.md‎

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Original file line numberDiff line numberDiff line change
@@ -63,7 +63,7 @@ Import TF.NET and Keras API in your project.
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using static Tensorflow.Binding;
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using static Tensorflow.KerasApi;
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using Tensorflow;
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using NumSharp;
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using Tensorflow.NumPy;
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```
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Linear Regression in `Eager` mode:
@@ -162,10 +162,9 @@ Linear Regression in `Eager` mode:
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#r "nuget: TensorFlow.Net"
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#r "nuget: TensorFlow.Keras"
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#r "nuget: SciSharp.TensorFlow.Redist"
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#r "nuget: NumSharp"
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167-
open NumSharp
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open Tensorflow
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open Tensorflow.NumPy
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open type Tensorflow.Binding
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open type Tensorflow.KerasApi
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‎src/TensorFlowNET.Core/Binding.Util.cs‎

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@@ -203,13 +203,6 @@ public static IEnumerable<T> reversed<T>(IList<T> values)
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yield return values[i];
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}
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206-
public static T New<T>() where T : ITensorFlowObject, new()
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{
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var instance = new T();
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instance.__init__();
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return instance;
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}
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[DebuggerStepThrough]
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public static void tf_with(ITensorFlowObject py, Action<ITensorFlowObject> action)
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{

‎src/TensorFlowNET.Core/Eager/EagerRunner.RecordGradient.cs‎

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@@ -81,7 +81,7 @@ BackwardFunction GetGradientFunction(string op_name,
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if (ops.gradientFunctions[op_name] == null)
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return new Tensor[op_inputs.Length];
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84-
var gradients = ops.gradientFunctions[op_name](new EagerOperation
84+
var op = new EagerOperation
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{
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Name = op_name,
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NumInputs = op_inputs.Length,
@@ -90,9 +90,9 @@ BackwardFunction GetGradientFunction(string op_name,
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Outputs = op_outputs,
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SkipInputIndices = unneeded_gradients,
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Attrs = attrs
93-
}, output_grads);
93+
};
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95-
return gradients;
95+
return ops.gradientFunctions[op_name](op, output_grads);
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};
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9898
bool CouldForwardprop()

‎src/TensorFlowNET.Core/Interfaces/ITensorFlowObject.cs‎

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Original file line numberDiff line numberDiff line change
@@ -20,15 +20,8 @@ namespace Tensorflow
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{
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public interface ITensorFlowObject : IDisposable
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{
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/// <summary>
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/// Called when the instance is created.
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/// </summary>
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void __init__();
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void __enter__();
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3025
void __exit__();
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void __del__();
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}
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}

‎src/TensorFlowNET.Core/Keras/ArgsDefinition/Normalization/LayerNormalizationArgs.cs‎

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@@ -0,0 +1,16 @@
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using static Tensorflow.Binding;
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namespace Tensorflow.Keras.ArgsDefinition
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{
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public class LayerNormalizationArgs : LayerArgs
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{
7+
public Axis Axis { get; set; } = -1;
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public float Epsilon { get; set; } = 1e-3f;
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public bool Center { get; set; } = true;
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public bool Scale { get; set; } = true;
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public IInitializer BetaInitializer { get; set; } = tf.zeros_initializer;
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public IInitializer GammaInitializer { get; set; } = tf.ones_initializer;
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public IRegularizer BetaRegularizer { get; set; }
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public IRegularizer GammaRegularizer { get; set; }
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}
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}

‎src/TensorFlowNET.Core/Tensorflow.Binding.csproj‎

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Original file line numberDiff line numberDiff line change
@@ -89,8 +89,8 @@ tf.net 0.6x.x aligns with TensorFlow v2.6.x native library.</PackageReleaseNotes
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</ItemGroup>
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<ItemGroup>
92-
<PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.139" />
93-
<PackageReference Include="Microsoft.Extensions.DependencyInjection" Version="5.0.2" />
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<PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.144" />
93+
<PackageReference Include="Microsoft.Extensions.DependencyInjection" Version="6.0.0" />
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<PackageReference Include="Protobuf.Text" Version="0.5.0" />
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<PackageReference Include="Serilog.Sinks.Console" Version="4.0.0" />
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</ItemGroup>

‎src/TensorFlowNET.Keras/Engine/Functional.cs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -316,7 +316,7 @@ protected override Tensors Call(Tensors inputs, Tensor state = null, bool? train
316316
var outputs = node.Layer.Apply(layer_inputs, is_training: training ?? false);
317317
foreach (var output in outputs.Where(x => x != null))
318318
tf.Logger.Information($"Depth {depth}: {node.Layer}: {node.Layer.Name} {output.shape}");
319-
// Update tensor_dict for next input
319+
// Update tensor_dict for next or later input
320320
foreach (var (x_id, y) in zip(node.Outputs.Select(x => x.Id), outputs))
321321
tensor_dict[x_id] = new Queue<Tensor>(Enumerable.Range(0, tensor_usage_count[x_id]).Select(x => y));
322322
}

‎src/TensorFlowNET.Keras/Layers/LayersApi.cs‎

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Original file line numberDiff line numberDiff line change
@@ -635,6 +635,21 @@ public Tensor max_pooling2d(Tensor inputs,
635635
return layer.Apply(inputs);
636636
}
637637

638+
public Layer LayerNormalization(Axis? axis,
639+
float epsilon = 1e-3f,
640+
bool center = true,
641+
bool scale = true,
642+
IInitializer beta_initializer = null,
643+
IInitializer gamma_initializer = null)
644+
=> new LayerNormalization(new LayerNormalizationArgs
645+
{
646+
Axis = axis ?? -1,
647+
Epsilon = epsilon,
648+
Center = center,
649+
Scale = scale,
650+
BetaInitializer = beta_initializer ?? tf.zeros_initializer
651+
});
652+
638653
/// <summary>
639654
/// Leaky version of a Rectified Linear Unit.
640655
/// </summary>

‎src/TensorFlowNET.Keras/Layers/Normalization/BatchNormalization.cs‎

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Original file line numberDiff line numberDiff line change
@@ -218,7 +218,8 @@ private Tensor _fused_batch_norm(Tensor inputs, Tensor training)
218218
beta,
219219
mean: moving_mean,
220220
variance: moving_variance,
221-
epsilon: epsilon, is_training: true,
221+
epsilon: epsilon,
222+
is_training: true,
222223
data_format: _data_format,
223224
exponential_avg_factor: exponential_avg_factor);
224225
};

‎src/TensorFlowNET.Keras/Layers/Normalization/LayerNormalization.cs‎

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@@ -0,0 +1,145 @@
1+
/*****************************************************************************
2+
Copyright 2021 Haiping Chen. All Rights Reserved.
3+
4+
Licensed under the Apache License, Version 2.0 (the "License");
5+
you may not use this file except in compliance with the License.
6+
You may obtain a copy of the License at
7+
8+
http://www.apache.org/licenses/LICENSE-2.0
9+
10+
Unless required by applicable law or agreed to in writing, software
11+
distributed under the License is distributed on an "AS IS" BASIS,
12+
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13+
See the License for the specific language governing permissions and
14+
limitations under the License.
15+
******************************************************************************/
16+
17+
using System;
18+
using System.Collections.Generic;
19+
using System.Linq;
20+
using Tensorflow.Keras.ArgsDefinition;
21+
using Tensorflow.Keras.Engine;
22+
using Tensorflow.Keras.Utils;
23+
using static Tensorflow.Binding;
24+
25+
namespace Tensorflow.Keras.Layers
26+
{
27+
public class LayerNormalization : Layer
28+
{
29+
LayerNormalizationArgs args;
30+
31+
float epsilon => args.Epsilon;
32+
bool center => args.Center;
33+
bool scale => args.Scale;
34+
bool _fused;
35+
int[] axis;
36+
string _data_format;
37+
Shape kernel_size;
38+
IInitializer beta_initializer => args.BetaInitializer;
39+
IInitializer gamma_initializer => args.GammaInitializer;
40+
IRegularizer gamma_regularizer => args.GammaRegularizer;
41+
IVariableV1 gamma;
42+
IVariableV1 beta;
43+
IVariableV1 moving_mean;
44+
IVariableV1 moving_variance;
45+
46+
public LayerNormalization(LayerNormalizationArgs args) : base(args)
47+
{
48+
this.args = args;
49+
axis = args.Axis.axis;
50+
}
51+
52+
protected override void build(Tensors inputs)
53+
{
54+
Shape input_shape = inputs.shape;
55+
var ndims = input_shape.ndim;
56+
foreach (var (idx, x) in enumerate(axis))
57+
if (x < 0)
58+
axis[idx] = ndims + x;
59+
60+
var axis_to_dim = new Dictionary<int, int>();
61+
foreach (var x in axis)
62+
axis_to_dim[x] = (int)input_shape[x];
63+
64+
inputSpec = new InputSpec(ndim: ndims, axes: axis_to_dim);
65+
var param_dtype = DType == TF_DataType.DtInvalid ? TF_DataType.TF_FLOAT : DType;
66+
var param_shape = inputSpec.AllAxisDim;
67+
68+
if (scale)
69+
gamma = add_weight("gamma",
70+
param_shape,
71+
dtype: param_dtype,
72+
initializer: gamma_initializer,
73+
trainable: true);
74+
75+
if (center)
76+
beta = add_weight("beta",
77+
param_shape,
78+
dtype: param_dtype,
79+
initializer: beta_initializer,
80+
trainable: true);
81+
82+
_fused = _fused_can_be_used(ndims);
83+
84+
built = true;
85+
}
86+
87+
bool _fused_can_be_used(int ndims)
88+
{
89+
var can_use_fused = false;
90+
if (axis.Last() == ndims - 1 && axis.Last() - axis[0] == len(axis) - 1)
91+
can_use_fused = true;
92+
if (epsilon < 1.001e-5 || DType != tf.float32)
93+
can_use_fused = false;
94+
return can_use_fused;
95+
}
96+
97+
public override Shape ComputeOutputShape(Shape input_shape)
98+
{
99+
return input_shape;
100+
}
101+
102+
protected override Tensors Call(Tensors inputs, Tensor state = null, bool? training = null)
103+
{
104+
Tensors outputs = null;
105+
var inputs_dtype = inputs.dtype.as_base_dtype();
106+
var input_shape = inputs.shape;
107+
var ndims = len(input_shape);
108+
var broadcast_shape = range(ndims).Select(x => 1).ToArray();
109+
foreach (var dim in axis)
110+
broadcast_shape[dim] = input_shape.as_int_list()[dim];
111+
112+
if (_fused)
113+
{
114+
var tensor_shape = tf.shape(inputs);
115+
var pre_dim = tf.constant(1);
116+
var in_dim = tf.constant(1);
117+
foreach (var dim in range(ndims))
118+
{
119+
var dim_tensor = tensor_shape[dim];
120+
if (dim < axis[0])
121+
pre_dim = pre_dim * dim_tensor;
122+
else
123+
in_dim = in_dim * dim_tensor;
124+
}
125+
inputs = tf.reshape(inputs, new object[] { 1, pre_dim, in_dim, 1 });
126+
127+
var scale = tf.ones(new Shape((int)pre_dim), dtype: DType);
128+
var offset = tf.zeros(new Shape((int)pre_dim), dtype: DType);
129+
130+
/*outputs = tf.nn.fused_batch_norm(
131+
inputs,
132+
scale: scale,
133+
offset: offset,
134+
epsilon: epsilon,
135+
data_format: "NCHW");*/
136+
}
137+
else
138+
{
139+
140+
}
141+
142+
return outputs;
143+
}
144+
}
145+
}

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