@@ -2,7 +2,7 @@ | |||
<PropertyGroup> | |||
<RootNamespace>Tensorflow.Hub</RootNamespace> | |||
<TargetFramework>netstandard2.0</TargetFramework> | |||
<Version>0.0.1</Version> | |||
<Version>0.0.2</Version> | |||
<Authors>Kerry Jiang</Authors> | |||
<Company>SciSharp STACK</Company> | |||
<Copyright>Apache 2.0</Copyright> | |||
@@ -13,7 +13,7 @@ | |||
<Description>TensorFlow Hub is a library to foster the publication, discovery, and consumption of reusable parts of machine learning models.</Description> | |||
<PackageId>SciSharp.TensorFlowHub</PackageId> | |||
<GeneratePackageOnBuild>true</GeneratePackageOnBuild> | |||
<PackageReleaseNotes>1. Add MNIST loader.</PackageReleaseNotes> | |||
<PackageReleaseNotes></PackageReleaseNotes> | |||
<PackageIconUrl>https://avatars3.githubusercontent.com/u/44989469?s=200&v=4</PackageIconUrl> | |||
</PropertyGroup> | |||
<ItemGroup> | |||
@@ -28,20 +28,13 @@ namespace Tensorflow.Hub | |||
var fileSaveTo = Path.Combine(dirSaveTo, fileName); | |||
if (File.Exists(fileSaveTo)) | |||
return; | |||
Directory.CreateDirectory(dirSaveTo); | |||
using (var wc = new WebClient()) | |||
{ | |||
//TODO:maybe you can check file's hashcode and "donglowad.info" to complete file ... | |||
Console.WriteLine($"{fileSaveTo} already exists."); | |||
} | |||
else | |||
{ | |||
if (!Directory.Exists(dirSaveTo)) | |||
Directory.CreateDirectory(dirSaveTo); | |||
using (var wc = new WebClient()) | |||
{ | |||
await wc.DownloadFileTaskAsync(url, fileSaveTo); | |||
} | |||
await wc.DownloadFileTaskAsync(url, fileSaveTo); | |||
} | |||
} | |||
@@ -52,8 +45,7 @@ namespace Tensorflow.Hub | |||
if (!Path.IsPathRooted(saveTo)) | |||
saveTo = Path.Combine(AppContext.BaseDirectory, saveTo); | |||
if (!Directory.Exists(saveTo)) | |||
Directory.CreateDirectory(saveTo); | |||
Directory.CreateDirectory(saveTo); | |||
if (!Path.IsPathRooted(zipFile)) | |||
zipFile = Path.Combine(AppContext.BaseDirectory, zipFile); | |||
@@ -192,6 +192,9 @@ namespace Tensorflow | |||
public static Tensor logical_and(Tensor x, Tensor y, string name = null) | |||
=> gen_math_ops.logical_and(x, y, name); | |||
public static Tensor logical_not(Tensor x, string name = null) | |||
=> gen_math_ops.logical_not(x, name); | |||
/// <summary> | |||
/// Clips tensor values to a specified min and max. | |||
/// </summary> | |||
@@ -34,10 +34,17 @@ namespace Tensorflow | |||
public Graph get_controller() | |||
{ | |||
if (stack.Count == 0) | |||
if (stack.Count(x => x.IsDefault) == 0) | |||
stack.Add(new StackModel { Graph = tf.Graph(), IsDefault = true }); | |||
return stack.First(x => x.IsDefault).Graph; | |||
return stack.Last(x => x.IsDefault).Graph; | |||
} | |||
public bool remove(Graph g) | |||
{ | |||
var sm = stack.FirstOrDefault(x => x.Graph == g); | |||
if (sm == null) return false; | |||
return stack.Remove(sm); | |||
} | |||
public void reset() | |||
@@ -73,9 +73,8 @@ namespace Tensorflow | |||
all variables that are created during the construction of a graph. The caller | |||
may define additional collections by specifying a new name. | |||
*/ | |||
public partial class Graph : IPython, IDisposable, IEnumerable<Operation> | |||
public partial class Graph : DisposableObject, IEnumerable<Operation> | |||
{ | |||
private IntPtr _handle; | |||
private Dictionary<int, ITensorOrOperation> _nodes_by_id; | |||
public Dictionary<string, ITensorOrOperation> _nodes_by_name; | |||
private Dictionary<string, int> _names_in_use; | |||
@@ -121,10 +120,6 @@ namespace Tensorflow | |||
_graph_key = $"grap-key-{ops.uid()}/"; | |||
} | |||
public void __enter__() | |||
{ | |||
} | |||
public ITensorOrOperation as_graph_element(object obj, bool allow_tensor = true, bool allow_operation = true) | |||
{ | |||
return _as_graph_element_locked(obj, allow_tensor, allow_operation); | |||
@@ -443,14 +438,15 @@ namespace Tensorflow | |||
_unfetchable_ops.Add(op); | |||
} | |||
public void Dispose() | |||
{ | |||
/*if (_handle != IntPtr.Zero) | |||
c_api.TF_DeleteGraph(_handle); | |||
_handle = IntPtr.Zero; | |||
GC.SuppressFinalize(this);*/ | |||
protected override void DisposeManagedState() | |||
{ | |||
ops.default_graph_stack.remove(this); | |||
} | |||
protected override void DisposeUnManagedState(IntPtr handle) | |||
{ | |||
Console.WriteLine($"Destroy graph {handle}"); | |||
c_api.TF_DeleteGraph(handle); | |||
} | |||
/// <summary> | |||
@@ -481,17 +477,19 @@ namespace Tensorflow | |||
return new TensorShape(dims.Select(x => (int)x).ToArray()); | |||
} | |||
string debugString = string.Empty; | |||
public override string ToString() | |||
{ | |||
int len = 0; | |||
return c_api.TF_GraphDebugString(_handle, out len); | |||
return $"{graph_key}, ({_handle})"; | |||
/*if (string.IsNullOrEmpty(debugString)) | |||
{ | |||
int len = 0; | |||
debugString = c_api.TF_GraphDebugString(_handle, out len); | |||
} | |||
return debugString;*/ | |||
} | |||
public void __exit__() | |||
{ | |||
} | |||
private IEnumerable<Operation> GetEnumerable() | |||
=> c_api_util.tf_operations(this); | |||
@@ -84,7 +84,7 @@ namespace Tensorflow | |||
// Dict mapping op name to file and line information for op colocation | |||
// context managers. | |||
_control_flow_context = graph._get_control_flow_context(); | |||
_control_flow_context = _graph._get_control_flow_context(); | |||
// Note: _control_flow_post_processing() must not be called here, the caller is responsible for calling it when using this constructor. | |||
} | |||
@@ -357,6 +357,13 @@ namespace Tensorflow | |||
return _op.outputs[0]; | |||
} | |||
public static Tensor logical_not(Tensor x, string name = null) | |||
{ | |||
var _op = _op_def_lib._apply_op_helper("LogicalNot", name, args: new { x }); | |||
return _op.outputs[0]; | |||
} | |||
public static Tensor squared_difference(Tensor x, Tensor y, string name = null) | |||
{ | |||
var _op = _op_def_lib._apply_op_helper("SquaredDifference", name, args: new { x, y, name }); | |||
@@ -31,7 +31,6 @@ namespace Tensorflow | |||
protected bool _closed; | |||
protected int _current_version; | |||
protected byte[] _target; | |||
protected IntPtr _session; | |||
public Graph graph => _graph; | |||
public BaseSession(string target = "", Graph g = null, SessionOptions opts = null) | |||
@@ -46,7 +45,7 @@ namespace Tensorflow | |||
var status = new Status(); | |||
_session = c_api.TF_NewSession(_graph, opts ?? newOpts, status); | |||
_handle = c_api.TF_NewSession(_graph, opts ?? newOpts, status); | |||
// dispose newOpts | |||
if (opts == null) | |||
@@ -216,7 +215,7 @@ namespace Tensorflow | |||
var output_values = fetch_list.Select(x => IntPtr.Zero).ToArray(); | |||
c_api.TF_SessionRun(_session, | |||
c_api.TF_SessionRun(_handle, | |||
run_options: null, | |||
inputs: feed_dict.Select(f => f.Key).ToArray(), | |||
input_values: feed_dict.Select(f => (IntPtr)f.Value).ToArray(), | |||
@@ -30,7 +30,7 @@ namespace Tensorflow | |||
public Session(IntPtr handle, Graph g = null) | |||
: base("", g, null) | |||
{ | |||
_session = handle; | |||
_handle = handle; | |||
} | |||
public Session(Graph g, SessionOptions opts = null, Status s = null) | |||
@@ -73,7 +73,7 @@ namespace Tensorflow | |||
return new Session(sess, g: new Graph(graph).as_default()); | |||
} | |||
public static implicit operator IntPtr(Session session) => session._session; | |||
public static implicit operator IntPtr(Session session) => session._handle; | |||
public static implicit operator Session(IntPtr handle) => new Session(handle); | |||
public void __enter__() | |||
@@ -37,7 +37,7 @@ Docs: https://tensorflownet.readthedocs.io</Description> | |||
15. Fix Tensor memory leak. | |||
16. Rename with to tf_with that is only used to build graph purpose.</PackageReleaseNotes> | |||
<LangVersion>7.3</LangVersion> | |||
<FileVersion>0.10.9.0</FileVersion> | |||
<FileVersion>0.10.10.0</FileVersion> | |||
<PackageLicenseFile>LICENSE</PackageLicenseFile> | |||
<PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance> | |||
<SignAssembly>true</SignAssembly> | |||
@@ -52,7 +52,8 @@ namespace TensorFlowNET.Examples | |||
// The location where variable checkpoints will be stored. | |||
string CHECKPOINT_NAME = Path.Join(data_dir, "_retrain_checkpoint"); | |||
string tfhub_module = "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/3"; | |||
string final_tensor_name = "final_result"; | |||
string input_tensor_name = "Placeholder"; | |||
string final_tensor_name = "Score"; | |||
float testing_percentage = 0.1f; | |||
float validation_percentage = 0.1f; | |||
float learning_rate = 0.01f; | |||
@@ -81,13 +82,13 @@ namespace TensorFlowNET.Examples | |||
PrepareData(); | |||
#region For debug purpose | |||
// predict images | |||
// Predict(null); | |||
// load saved pb and test new images. | |||
// Test(null); | |||
#endregion | |||
var graph = IsImportingGraph ? ImportGraph() : BuildGraph(); | |||
@@ -276,16 +277,13 @@ namespace TensorFlowNET.Examples | |||
private (Graph, Tensor, Tensor, bool) create_module_graph() | |||
{ | |||
var (height, width) = (299, 299); | |||
return tf_with(tf.Graph().as_default(), graph => | |||
{ | |||
tf.train.import_meta_graph("graph/InceptionV3.meta"); | |||
Tensor resized_input_tensor = graph.OperationByName("Placeholder"); //tf.placeholder(tf.float32, new TensorShape(-1, height, width, 3)); | |||
// var m = hub.Module(module_spec); | |||
Tensor bottleneck_tensor = graph.OperationByName("module_apply_default/hub_output/feature_vector/SpatialSqueeze");// m(resized_input_tensor); | |||
var wants_quantization = false; | |||
return (graph, bottleneck_tensor, resized_input_tensor, wants_quantization); | |||
}); | |||
var graph = tf.Graph().as_default(); | |||
tf.train.import_meta_graph("graph/InceptionV3.meta"); | |||
Tensor resized_input_tensor = graph.OperationByName(input_tensor_name); //tf.placeholder(tf.float32, new TensorShape(-1, height, width, 3)); | |||
// var m = hub.Module(module_spec); | |||
Tensor bottleneck_tensor = graph.OperationByName("module_apply_default/hub_output/feature_vector/SpatialSqueeze");// m(resized_input_tensor); | |||
var wants_quantization = false; | |||
return (graph, bottleneck_tensor, resized_input_tensor, wants_quantization); | |||
} | |||
private (NDArray, long[], string[]) get_random_cached_bottlenecks(Session sess, Dictionary<string, Dictionary<string, string[]>> image_lists, | |||
@@ -594,13 +592,10 @@ namespace TensorFlowNET.Examples | |||
create_module_graph(); | |||
// Add the new layer that we'll be training. | |||
tf_with(graph.as_default(), delegate | |||
{ | |||
(train_step, cross_entropy, bottleneck_input, | |||
ground_truth_input, final_tensor) = add_final_retrain_ops( | |||
class_count, final_tensor_name, bottleneck_tensor, | |||
wants_quantization, is_training: true); | |||
}); | |||
(train_step, cross_entropy, bottleneck_input, | |||
ground_truth_input, final_tensor) = add_final_retrain_ops( | |||
class_count, final_tensor_name, bottleneck_tensor, | |||
wants_quantization, is_training: true); | |||
return graph; | |||
} | |||
@@ -734,15 +729,15 @@ namespace TensorFlowNET.Examples | |||
var labels = File.ReadAllLines(output_labels); | |||
// predict image | |||
var img_path = Path.Join(image_dir, "roses", "12240303_80d87f77a3_n.jpg"); | |||
var img_path = Path.Join(image_dir, "daisy", "5547758_eea9edfd54_n.jpg"); | |||
var fileBytes = ReadTensorFromImageFile(img_path); | |||
// import graph and variables | |||
var graph = new Graph(); | |||
graph.Import(output_graph, ""); | |||
Tensor input = graph.OperationByName("Placeholder"); | |||
Tensor output = graph.OperationByName("final_result"); | |||
Tensor input = graph.OperationByName(input_tensor_name); | |||
Tensor output = graph.OperationByName(final_tensor_name); | |||
using (var sess = tf.Session(graph)) | |||
{ | |||
@@ -7,12 +7,13 @@ namespace TensorFlowNET.UnitTest | |||
[TestClass] | |||
public class NameScopeTest | |||
{ | |||
Graph g = ops.get_default_graph(); | |||
string name = ""; | |||
[TestMethod] | |||
public void NestedNameScope() | |||
{ | |||
Graph g = tf.Graph().as_default(); | |||
tf_with(new ops.NameScope("scope1"), scope1 => | |||
{ | |||
name = scope1; | |||
@@ -37,6 +38,8 @@ namespace TensorFlowNET.UnitTest | |||
Assert.AreEqual("scope1/Const_1:0", const3.name); | |||
}); | |||
g.Dispose(); | |||
Assert.AreEqual("", g._name_stack); | |||
} | |||
} | |||
@@ -131,7 +131,7 @@ namespace TensorFlowNET.UnitTest | |||
} | |||
[TestMethod] | |||
public void logicalAndTest() | |||
public void logicalOpsTest() | |||
{ | |||
var a = tf.constant(new[] {1f, 2f, 3f, 4f, -4f, -3f, -2f, -1f}); | |||
var b = tf.less(a, 0f); | |||
@@ -144,6 +144,15 @@ namespace TensorFlowNET.UnitTest | |||
var o = sess.run(d); | |||
Assert.IsTrue(o.array_equal(check)); | |||
} | |||
d = tf.cast(tf.logical_not(b), tf.int32); | |||
check = np.array(new[] { 1, 1, 1, 1, 0, 0, 0, 0 }); | |||
using (var sess = tf.Session()) | |||
{ | |||
var o = sess.run(d); | |||
Assert.IsTrue(o.array_equal(check)); | |||
} | |||
} | |||
[TestMethod] | |||