| @@ -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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| Debug|x64 = Debug|x64 | |||
| Publish|Any CPU = Publish|Any CPU | |||
| Publish|x64 = Publish|x64 | |||
| Release|Any CPU = Release|Any CPU | |||
| Release|x64 = Release|x64 | |||
| EndGlobalSection | |||
| GlobalSection(ProjectConfigurationPlatforms) = postSolution | |||
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| {9249BCC4-3FEB-4EF5-8AB9-789FFE4040B4}.Release|Any CPU.ActiveCfg = Release|Any CPU | |||
| {9249BCC4-3FEB-4EF5-8AB9-789FFE4040B4}.Release|Any CPU.Build.0 = Release|Any CPU | |||
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| {9249BCC4-3FEB-4EF5-8AB9-789FFE4040B4}.Release|x64.Build.0 = Release|x64 | |||
| 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 | |||
| { | |||