@@ -15,36 +15,102 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Hub", "src\Te | |||
EndProject | |||
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Datasets", "src\TensorFlowNET.Datasets\TensorFlowNET.Datasets.csproj", "{494D6CAD-2C0D-4C0B-90E2-B097DB039383}" | |||
EndProject | |||
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "NumSharp.Core", "..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj", "{9249BCC4-3FEB-4EF5-8AB9-789FFE4040B4}" | |||
EndProject | |||
Global | |||
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Publish|x64 = Publish|x64 | |||
Release|Any CPU = Release|Any CPU | |||
Release|x64 = Release|x64 | |||
EndGlobalSection | |||
GlobalSection(ProjectConfigurationPlatforms) = postSolution | |||
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EndGlobalSection | |||
GlobalSection(SolutionProperties) = preSolution | |||
HideSolutionNode = FALSE | |||
@@ -113,6 +113,7 @@ namespace Tensorflow | |||
} | |||
} | |||
[DebuggerStepThrough] | |||
[DebuggerNonUserCode()] // with "Just My Code" enabled this lets the debugger break at the origin of the exception | |||
public static void tf_with<T>(T py, Action<T> action) where T : IObjectLife | |||
{ | |||
@@ -266,7 +266,7 @@ namespace Tensorflow | |||
name = op_type; | |||
// If a names ends with a '/' it is a "name scope" and we use it as-is, | |||
// after removing the trailing '/'. | |||
name = name.EndsWith("/") ? ops._name_from_scope_name(name) : unique_name(name); | |||
name = name.EndsWith("/") ? ops.name_from_scope_name(name) : unique_name(name); | |||
var node_def = ops._NodeDef(op_type, name, device: "", attrs: attrs); | |||
var input_ops = inputs.Select(x => x.op).ToArray(); | |||
@@ -341,7 +341,7 @@ namespace Tensorflow | |||
if (string.IsNullOrEmpty(name)) | |||
new_stack = ""; | |||
else if (name.EndsWith("/")) | |||
new_stack = ops._name_from_scope_name(name); | |||
new_stack = ops.name_from_scope_name(name); | |||
else | |||
new_stack = unique_name(name); | |||
@@ -49,7 +49,8 @@ namespace Tensorflow.Keras.Utils | |||
var v = tf.VariableV1(init_val, | |||
use_resource: use_resource, | |||
dtype: dtype, | |||
shape: shape); | |||
shape: shape, | |||
name: name); | |||
return v; | |||
} | |||
@@ -26,5 +26,12 @@ namespace Tensorflow | |||
return _op; | |||
} | |||
public static Tensor var_is_initialized_op(Tensor resource, string name = null) | |||
{ | |||
var _op = _op_def_lib._apply_op_helper("VarIsInitializedOp", name, new { resource }); | |||
return _op; | |||
} | |||
} | |||
} |
@@ -74,6 +74,29 @@ namespace Tensorflow | |||
return var is ResourceVariable; | |||
} | |||
/// <summary> | |||
/// Creates a variable handle with information to do shape inference. | |||
/// </summary> | |||
/// <param name="initial_value"></param> | |||
/// <param name="shape"></param> | |||
/// <param name="shared_name"></param> | |||
/// <param name="name"></param> | |||
/// <param name="graph_mode"></param> | |||
/// <returns></returns> | |||
public static Tensor eager_safe_variable_handle(Tensor initial_value, TensorShape shape, | |||
string shared_name, string name, bool graph_mode) | |||
{ | |||
var dtype = initial_value.dtype.as_base_dtype(); | |||
return variable_handle_from_shape_and_dtype( | |||
shape, dtype, shared_name, name, graph_mode, initial_value); | |||
} | |||
public static Tensor variable_handle_from_shape_and_dtype(TensorShape shape, TF_DataType dtype, | |||
string shared_name, string name, bool graph_mode, Tensor extra_handle_data = null) | |||
{ | |||
throw new NotImplementedException(""); | |||
} | |||
/// <summary> | |||
/// Represents a future for a read of a variable. | |||
/// Pretends to be the tensor if anyone looks. | |||
@@ -5,7 +5,7 @@ | |||
<AssemblyName>TensorFlow.NET</AssemblyName> | |||
<RootNamespace>Tensorflow</RootNamespace> | |||
<TargetTensorFlow>1.14.0</TargetTensorFlow> | |||
<Version>0.11.5</Version> | |||
<Version>0.11.6</Version> | |||
<Authors>Haiping Chen, Meinrad Recheis, Eli Belash</Authors> | |||
<Company>SciSharp STACK</Company> | |||
<GeneratePackageOnBuild>true</GeneratePackageOnBuild> | |||
@@ -17,7 +17,7 @@ | |||
<PackageTags>TensorFlow, NumSharp, SciSharp, MachineLearning, TensorFlow.NET, C#</PackageTags> | |||
<Description>Google's TensorFlow full binding in .NET Standard. | |||
Docs: https://tensorflownet.readthedocs.io</Description> | |||
<AssemblyVersion>0.11.5.0</AssemblyVersion> | |||
<AssemblyVersion>0.11.6.0</AssemblyVersion> | |||
<PackageReleaseNotes>Changes since v0.10.0: | |||
1. Upgrade NumSharp to v0.20.3. | |||
2. Add DisposableObject class to manage object lifetime. | |||
@@ -29,9 +29,11 @@ Docs: https://tensorflownet.readthedocs.io</Description> | |||
8. Add tf.random_normal, tf.constant, tf.pad, tf.shape, tf.image.resize_nearest_neighbor. | |||
9. MultiThread is safe. | |||
10. Support n-dim indexing for tensor. | |||
11. Add RegisterNoGradient</PackageReleaseNotes> | |||
11. Add RegisterNoGradients | |||
12. Add CumsumGrad, BroadcastToGrad. | |||
13. Return VariableV1 instead of RefVariable.</PackageReleaseNotes> | |||
<LangVersion>7.3</LangVersion> | |||
<FileVersion>0.11.5.0</FileVersion> | |||
<FileVersion>0.11.6.0</FileVersion> | |||
<PackageLicenseFile>LICENSE</PackageLicenseFile> | |||
<PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance> | |||
<SignAssembly>true</SignAssembly> | |||
@@ -63,7 +65,6 @@ Docs: https://tensorflownet.readthedocs.io</Description> | |||
<ItemGroup> | |||
<PackageReference Include="Google.Protobuf" Version="3.5.1" /> | |||
<PackageReference Include="NumSharp" Version="0.20.4" /> | |||
</ItemGroup> | |||
<ItemGroup> | |||
@@ -71,4 +72,8 @@ Docs: https://tensorflownet.readthedocs.io</Description> | |||
<Folder Include="Keras\Initializers\" /> | |||
<Folder Include="Models\" /> | |||
</ItemGroup> | |||
<ItemGroup> | |||
<ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" /> | |||
</ItemGroup> | |||
</Project> |
@@ -143,7 +143,7 @@ namespace Tensorflow | |||
// Use attr_scope and device(None) to simulate the behavior of | |||
// colocate_with when the variable we want to colocate with doesn't | |||
// yet exist. | |||
string true_name = ops._name_from_scope_name(name); | |||
string true_name = ops.name_from_scope_name(name); | |||
var attr = new AttrValue | |||
{ | |||
List = new AttrValue.Types.ListValue() | |||
@@ -14,6 +14,7 @@ | |||
limitations under the License. | |||
******************************************************************************/ | |||
using Google.Protobuf; | |||
using System; | |||
using System.Collections.Generic; | |||
using static Tensorflow.Binding; | |||
@@ -92,7 +93,59 @@ namespace Tensorflow | |||
var init_from_fn = initial_value.GetType().Name == "Func`1"; | |||
if(collections == null) | |||
collections = new List<string>() { tf.GraphKeys.GLOBAL_VARIABLES }; | |||
_trainable = trainable; | |||
_graph_key = ops.get_default_graph().graph_key; | |||
ops.init_scope(); | |||
_in_graph_mode = true; | |||
tf_with(ops.name_scope(name, "Variable"), scope => | |||
{ | |||
name = scope; | |||
var handle_name = ops.name_from_scope_name(name); | |||
var shared_name = handle_name; | |||
var unique_id = shared_name; | |||
var attr = new AttrValue(); | |||
attr.List = new AttrValue.Types.ListValue(); | |||
attr.List.S.Add(ByteString.CopyFromUtf8($"loc:{handle_name}")); | |||
tf_with(ops.name_scope("Initializer"), delegate | |||
{ | |||
initial_value = ops.convert_to_tensor(init_from_fn ? (initial_value as Func<Tensor>)() : initial_value, | |||
name: "initial_value", | |||
dtype: dtype); | |||
}); | |||
_shape = shape ?? (initial_value as Tensor).TensorShape; | |||
_handle = resource_variable_ops.eager_safe_variable_handle( | |||
initial_value: _initial_value, | |||
shape: _shape, | |||
shared_name: shared_name, | |||
name: name, | |||
graph_mode: _in_graph_mode); | |||
_unique_id = unique_id; | |||
_initial_value = initial_value as Tensor; | |||
_handle_name = handle_name + ":0"; | |||
_dtype = _initial_value.dtype.as_base_dtype(); | |||
// _constraint = constraint; | |||
if (_in_graph_mode) | |||
{ | |||
tf_with(ops.name_scope("IsInitialized"), delegate | |||
{ | |||
_is_initialized_op = gen_resource_variable_ops.var_is_initialized_op(_handle); | |||
}); | |||
if(initial_value != null) | |||
{ | |||
tf_with(ops.name_scope("Assign"), scope1 => | |||
{ | |||
string n = scope1; | |||
_initializer_op = gen_resource_variable_ops.assign_variable_op(_handle, | |||
variables._try_guard_against_uninitialized_dependencies(name, _initial_value), | |||
name: n); | |||
}); | |||
} | |||
} | |||
}); | |||
throw new NotImplementedException(""); | |||
} | |||
@@ -35,7 +35,11 @@ namespace Tensorflow | |||
public virtual Operation op { get; } | |||
public virtual Operation initializer { get; } | |||
public Tensor _variable; | |||
protected string _graph_key; | |||
public Graph graph => _variable.graph; | |||
public Tensor _is_initialized_op { get; set; } | |||
public VariableV1(object initial_value = null, | |||
bool trainable = true, | |||
List<string> collections = null, | |||
@@ -84,6 +84,60 @@ namespace Tensorflow | |||
return gen_control_flow_ops.no_op(name: name); | |||
} | |||
public static Tensor _try_guard_against_uninitialized_dependencies(string name, Tensor initial_value) | |||
{ | |||
return _safe_initial_value_from_tensor(name, initial_value, new Dictionary<string, Operation>()); | |||
} | |||
public static Tensor _safe_initial_value_from_tensor(string name, Tensor tensor, Dictionary<string, Operation> op_cache) | |||
{ | |||
var op = tensor.op; | |||
Operation new_op = op_cache.ContainsKey(op.name) ? op_cache[op.name] : null; | |||
if(new_op == null) | |||
{ | |||
new_op = _safe_initial_value_from_op(name, op, op_cache); | |||
op_cache[op.name] = new_op; | |||
} | |||
return new_op.outputs[tensor.value_index]; | |||
} | |||
/// <summary> | |||
/// Replace dependencies on variables with their initialized values. | |||
/// </summary> | |||
/// <param name="name"></param> | |||
/// <param name="op"></param> | |||
/// <param name="op_cache"></param> | |||
/// <returns></returns> | |||
public static Operation _safe_initial_value_from_op(string name, Operation op, Dictionary<string, Operation> op_cache) | |||
{ | |||
var op_type = op.node_def.Op; | |||
if (op_type == "IsVariableInitialized" || | |||
op_type == "VarIsInitializedOp" || | |||
op_type == "ReadVariableOp") | |||
return op; | |||
if(op_type == "Variable" || | |||
op_type == "VariableV2" || | |||
op_type == "VarHandleOp") | |||
{ | |||
throw new NotImplementedException(""); | |||
} | |||
// Recursively build initializer expressions for inputs. | |||
bool modified = false; | |||
var new_op_inputs = new List<Tensor>(); | |||
foreach(Tensor op_input in op.inputs) | |||
{ | |||
var new_op_input = _safe_initial_value_from_tensor(name, op_input, op_cache); | |||
new_op_inputs.Add(new_op_input); | |||
modified = modified || new_op_input != op_input; | |||
} | |||
// If at least one input was modified, replace the op. | |||
return op; | |||
} | |||
public static Tensor global_variables_initializer() | |||
{ | |||
throw new NotImplementedException(); | |||
@@ -274,7 +274,7 @@ namespace Tensorflow | |||
return node_def; | |||
} | |||
public static string _name_from_scope_name(string name) | |||
public static string name_from_scope_name(string name) | |||
{ | |||
if (name.EndsWith("/")) | |||
{ | |||
@@ -18,6 +18,6 @@ | |||
<AssemblyName>TensorFlow.Hub</AssemblyName> | |||
</PropertyGroup> | |||
<ItemGroup> | |||
<PackageReference Include="NumSharp" Version="0.20.3" /> | |||
<ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" /> | |||
</ItemGroup> | |||
</Project> |
@@ -8,6 +8,9 @@ using NumSharp; | |||
namespace TensorFlowNET.UnitTest.Keras | |||
{ | |||
/// <summary> | |||
/// https://www.tensorflow.org/versions/r1.14/api_docs/python/tf/keras/layers/Embedding | |||
/// </summary> | |||
[TestClass] | |||
public class EmbeddingTest | |||
{ | |||