From 02cb239c5ffb5a109297aaec047ffed35fc05269 Mon Sep 17 00:00:00 2001 From: Luc BOLOGNA Date: Sun, 4 Jun 2023 21:58:40 +0200 Subject: [PATCH 1/7] Refactor: Change Model evaluate IModel.Dictionary evaluate(NDArray, NDArray, ...) is now IModel.Dictionary evaluate(Tensor, Tensor, ...) Merge Model.Evaluate.test_step_multi_inputs_function(...) and Model.Evaluate.test_function(...) Note: An internal function need to add an explicit cast in Tensor --- src/TensorFlowNET.Core/Keras/Engine/IModel.cs | 2 +- src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs | 16 +++++----------- src/TensorFlowNET.Keras/Engine/Model.Fit.cs | 2 +- 3 files changed, 7 insertions(+), 13 deletions(-) diff --git a/src/TensorFlowNET.Core/Keras/Engine/IModel.cs b/src/TensorFlowNET.Core/Keras/Engine/IModel.cs index 19f3df9b..ddc72aee 100644 --- a/src/TensorFlowNET.Core/Keras/Engine/IModel.cs +++ b/src/TensorFlowNET.Core/Keras/Engine/IModel.cs @@ -60,7 +60,7 @@ public interface IModel : ILayer bool skip_mismatch = false, object options = null); - Dictionary evaluate(NDArray x, NDArray y, + Dictionary evaluate(Tensor x, Tensor y, int batch_size = -1, int verbose = 1, int steps = -1, diff --git a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs index 185de4f4..a71f7f39 100644 --- a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs +++ b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs @@ -27,7 +27,7 @@ namespace Tensorflow.Keras.Engine /// /// /// - public Dictionary evaluate(NDArray x, NDArray y, + public Dictionary evaluate(Tensor x, Tensor y, int batch_size = -1, int verbose = 1, int steps = -1, @@ -91,7 +91,7 @@ namespace Tensorflow.Keras.Engine return results; } - public Dictionary evaluate(IEnumerable x, NDArray y, int verbose = 1, bool is_val = false) + public Dictionary evaluate(IEnumerable x, Tensor y, int verbose = 1, bool is_val = false) { var data_handler = new DataHandler(new DataHandlerArgs { @@ -119,7 +119,7 @@ namespace Tensorflow.Keras.Engine foreach (var step in data_handler.steps()) { callbacks.on_test_batch_begin(step); - logs = test_step_multi_inputs_function(data_handler, iterator); + logs = test_function(data_handler, iterator); var end_step = step + data_handler.StepIncrement; if (is_val == false) callbacks.on_test_batch_end(end_step, logs); @@ -178,20 +178,14 @@ namespace Tensorflow.Keras.Engine } Dictionary test_function(DataHandler data_handler, OwnedIterator iterator) - { - var data = iterator.next(); - var outputs = test_step(data_handler, data[0], data[1]); - tf_with(ops.control_dependencies(new object[0]), ctl => _test_counter.assign_add(1)); - return outputs; - } - Dictionary test_step_multi_inputs_function(DataHandler data_handler, OwnedIterator iterator) { var data = iterator.next(); var x_size = data_handler.DataAdapter.GetDataset().FirstInputTensorCount; var outputs = train_step(data_handler, new Tensors(data.Take(x_size)), new Tensors(data.Skip(x_size))); - tf_with(ops.control_dependencies(new object[0]), ctl => _train_counter.assign_add(1)); + tf_with(ops.control_dependencies(new object[0]), ctl => _test_counter.assign_add(1)); return outputs; } + Dictionary test_step(DataHandler data_handler, Tensor x, Tensor y) { (x, y) = data_handler.DataAdapter.Expand1d(x, y); diff --git a/src/TensorFlowNET.Keras/Engine/Model.Fit.cs b/src/TensorFlowNET.Keras/Engine/Model.Fit.cs index bb8e18cc..17ecde98 100644 --- a/src/TensorFlowNET.Keras/Engine/Model.Fit.cs +++ b/src/TensorFlowNET.Keras/Engine/Model.Fit.cs @@ -266,7 +266,7 @@ namespace Tensorflow.Keras.Engine { // Because evaluate calls call_test_batch_end, this interferes with our output on the screen // so we need to pass a is_val parameter to stop on_test_batch_end - var val_logs = evaluate(validation_data.Value.Item1, validation_data.Value.Item2, is_val:true); + var val_logs = evaluate((Tensor)validation_data.Value.Item1, validation_data.Value.Item2, is_val:true); foreach (var log in val_logs) { logs["val_" + log.Key] = log.Value; From f7208c9494f31d203ed5e17def29ea6dd4e361bf Mon Sep 17 00:00:00 2001 From: Luc BOLOGNA Date: Mon, 5 Jun 2023 00:01:53 +0200 Subject: [PATCH 2/7] Refactor: Model.Evaluate.cs --- .../Engine/Model.Evaluate.cs | 129 +++++------------- 1 file changed, 36 insertions(+), 93 deletions(-) diff --git a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs index a71f7f39..85c262a9 100644 --- a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs +++ b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs @@ -14,6 +14,38 @@ namespace Tensorflow.Keras.Engine { public partial class Model { + protected Dictionary evaluate(CallbackList callbacks, DataHandler data_handler, bool is_val) + { + callbacks.on_test_begin(); + + //Dictionary? logs = null; + var logs = new Dictionary(); + int x_size = data_handler.DataAdapter.GetDataset().FirstInputTensorCount; + foreach (var (epoch, iterator) in data_handler.enumerate_epochs()) + { + reset_metrics(); + callbacks.on_epoch_begin(epoch); + // data_handler.catch_stop_iteration(); + + foreach (var step in data_handler.steps()) + { + callbacks.on_test_batch_begin(step); + + var data = iterator.next(); + + logs = train_step(data_handler, new Tensors(data.Take(x_size)), new Tensors(data.Skip(x_size))); + tf_with(ops.control_dependencies(Array.Empty()), ctl => _test_counter.assign_add(1)); + + var end_step = step + data_handler.StepIncrement; + + if (!is_val) + callbacks.on_test_batch_end(end_step, logs); + } + } + + return logs; + } + /// /// Returns the loss value & metrics values for the model in test mode. /// @@ -64,31 +96,8 @@ namespace Tensorflow.Keras.Engine Verbose = verbose, Steps = data_handler.Inferredsteps }); - callbacks.on_test_begin(); - - //Dictionary? logs = null; - var logs = new Dictionary(); - foreach (var (epoch, iterator) in data_handler.enumerate_epochs()) - { - reset_metrics(); - // data_handler.catch_stop_iteration(); - foreach (var step in data_handler.steps()) - { - callbacks.on_test_batch_begin(step); - logs = test_function(data_handler, iterator); - var end_step = step + data_handler.StepIncrement; - if (is_val == false) - callbacks.on_test_batch_end(end_step, logs); - } - } - - var results = new Dictionary(); - foreach (var log in logs) - { - results[log.Key] = log.Value; - } - return results; + return evaluate(callbacks, data_handler, is_val); } public Dictionary evaluate(IEnumerable x, Tensor y, int verbose = 1, bool is_val = false) @@ -107,31 +116,8 @@ namespace Tensorflow.Keras.Engine Verbose = verbose, Steps = data_handler.Inferredsteps }); - callbacks.on_test_begin(); - Dictionary logs = null; - foreach (var (epoch, iterator) in data_handler.enumerate_epochs()) - { - reset_metrics(); - callbacks.on_epoch_begin(epoch); - // data_handler.catch_stop_iteration(); - - foreach (var step in data_handler.steps()) - { - callbacks.on_test_batch_begin(step); - logs = test_function(data_handler, iterator); - var end_step = step + data_handler.StepIncrement; - if (is_val == false) - callbacks.on_test_batch_end(end_step, logs); - } - } - - var results = new Dictionary(); - foreach (var log in logs) - { - results[log.Key] = log.Value; - } - return results; + return evaluate(callbacks, data_handler, is_val); } @@ -150,51 +136,8 @@ namespace Tensorflow.Keras.Engine Verbose = verbose, Steps = data_handler.Inferredsteps }); - callbacks.on_test_begin(); - - Dictionary logs = null; - foreach (var (epoch, iterator) in data_handler.enumerate_epochs()) - { - reset_metrics(); - callbacks.on_epoch_begin(epoch); - // data_handler.catch_stop_iteration(); - - foreach (var step in data_handler.steps()) - { - callbacks.on_test_batch_begin(step); - logs = test_function(data_handler, iterator); - var end_step = step + data_handler.StepIncrement; - if (is_val == false) - callbacks.on_test_batch_end(end_step, logs); - } - } - - var results = new Dictionary(); - foreach (var log in logs) - { - results[log.Key] = log.Value; - } - return results; - } - - Dictionary test_function(DataHandler data_handler, OwnedIterator iterator) - { - var data = iterator.next(); - var x_size = data_handler.DataAdapter.GetDataset().FirstInputTensorCount; - var outputs = train_step(data_handler, new Tensors(data.Take(x_size)), new Tensors(data.Skip(x_size))); - tf_with(ops.control_dependencies(new object[0]), ctl => _test_counter.assign_add(1)); - return outputs; - } - - Dictionary test_step(DataHandler data_handler, Tensor x, Tensor y) - { - (x, y) = data_handler.DataAdapter.Expand1d(x, y); - var y_pred = Apply(x, training: false); - var loss = compiled_loss.Call(y, y_pred); - - compiled_metrics.update_state(y, y_pred); - return metrics.Select(x => (x.Name, x.result())).ToDictionary(x=>x.Item1, x=>(float)x.Item2); + return evaluate(callbacks, data_handler, is_val); } } -} +} \ No newline at end of file From 0effee430c905f7ee84a064a4b1474ef931368a0 Mon Sep 17 00:00:00 2001 From: Luc Bologna Date: Mon, 5 Jun 2023 20:14:57 +0200 Subject: [PATCH 3/7] Update Model.Evaluate.cs Fix my bad: Bad handling between test_function and test_step_multi_inputs_function. --- .../Engine/Model.Evaluate.cs | 116 +++++++++++------- 1 file changed, 75 insertions(+), 41 deletions(-) diff --git a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs index 85c262a9..99a891c0 100644 --- a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs +++ b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs @@ -1,51 +1,19 @@ -using Tensorflow.NumPy; using System; using System.Collections.Generic; using System.Linq; +using Tensorflow; using Tensorflow.Keras.ArgsDefinition; +using Tensorflow.Keras.Callbacks; using Tensorflow.Keras.Engine.DataAdapters; -using static Tensorflow.Binding; using Tensorflow.Keras.Layers; using Tensorflow.Keras.Utils; -using Tensorflow; -using Tensorflow.Keras.Callbacks; +using Tensorflow.NumPy; +using static Tensorflow.Binding; namespace Tensorflow.Keras.Engine { public partial class Model { - protected Dictionary evaluate(CallbackList callbacks, DataHandler data_handler, bool is_val) - { - callbacks.on_test_begin(); - - //Dictionary? logs = null; - var logs = new Dictionary(); - int x_size = data_handler.DataAdapter.GetDataset().FirstInputTensorCount; - foreach (var (epoch, iterator) in data_handler.enumerate_epochs()) - { - reset_metrics(); - callbacks.on_epoch_begin(epoch); - // data_handler.catch_stop_iteration(); - - foreach (var step in data_handler.steps()) - { - callbacks.on_test_batch_begin(step); - - var data = iterator.next(); - - logs = train_step(data_handler, new Tensors(data.Take(x_size)), new Tensors(data.Skip(x_size))); - tf_with(ops.control_dependencies(Array.Empty()), ctl => _test_counter.assign_add(1)); - - var end_step = step + data_handler.StepIncrement; - - if (!is_val) - callbacks.on_test_batch_end(end_step, logs); - } - } - - return logs; - } - /// /// Returns the loss value & metrics values for the model in test mode. /// @@ -97,7 +65,7 @@ namespace Tensorflow.Keras.Engine Steps = data_handler.Inferredsteps }); - return evaluate(callbacks, data_handler, is_val); + return evaluate(data_handler, callbacks, is_val, test_function); } public Dictionary evaluate(IEnumerable x, Tensor y, int verbose = 1, bool is_val = false) @@ -117,10 +85,9 @@ namespace Tensorflow.Keras.Engine Steps = data_handler.Inferredsteps }); - return evaluate(callbacks, data_handler, is_val); + return evaluate(data_handler, callbacks, is_val, test_step_multi_inputs_function); } - public Dictionary evaluate(IDatasetV2 x, int verbose = 1, bool is_val = false) { var data_handler = new DataHandler(new DataHandlerArgs @@ -137,7 +104,74 @@ namespace Tensorflow.Keras.Engine Steps = data_handler.Inferredsteps }); - return evaluate(callbacks, data_handler, is_val); + return evaluate(data_handler, callbacks, is_val, test_function); + } + + /// + /// Internal bare implementation of evaluate function. + /// + /// Interations handling objects + /// + /// The function to be called on each batch of data. + /// Whether it is validation or test. + /// + Dictionary evaluate(DataHandler data_handler, CallbackList callbacks, bool is_val, Func> test_func) + { + callbacks.on_test_begin(); + + var results = new Dictionary(); + var logs = results; + foreach (var (epoch, iterator) in data_handler.enumerate_epochs()) + { + reset_metrics(); + callbacks.on_epoch_begin(epoch); + // data_handler.catch_stop_iteration(); + + foreach (var step in data_handler.steps()) + { + callbacks.on_test_batch_begin(step); + + var data = iterator.next(); + + logs = test_func(data_handler, iterator.next()); + + tf_with(ops.control_dependencies(Array.Empty()), ctl => _train_counter.assign_add(1)); + + var end_step = step + data_handler.StepIncrement; + if (!is_val) + callbacks.on_test_batch_end(end_step, logs); + } + + if (!is_val) + callbacks.on_epoch_end(epoch, logs); + } + + foreach (var log in logs) + { + results[log.Key] = log.Value; + } + + return results; + } + + Dictionary test_function(DataHandler data_handler, Tensor[] data) + { + var (x, y) = data_handler.DataAdapter.Expand1d(data[0], data[1]); + + var y_pred = Apply(x, training: false); + var loss = compiled_loss.Call(y, y_pred); + + compiled_metrics.update_state(y, y_pred); + + var outputs = metrics.Select(x => (x.Name, x.result())).ToDictionary(x => x.Name, x => (float)x.Item2); + return outputs; + } + + Dictionary test_step_multi_inputs_function(DataHandler data_handler, Tensor[] data) + { + var x_size = data_handler.DataAdapter.GetDataset().FirstInputTensorCount; + var outputs = train_step(data_handler, new Tensors(data.Take(x_size)), new Tensors(data.Skip(x_size))); + return outputs; } } -} \ No newline at end of file +} From a8288af655d966e09484e04fc5c0cd6cf00ef0f7 Mon Sep 17 00:00:00 2001 From: Luc Bologna Date: Mon, 5 Jun 2023 21:15:57 +0200 Subject: [PATCH 4/7] Update Model.Evaluate.cs --- src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs index 99a891c0..912f5e06 100644 --- a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs +++ b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs @@ -131,8 +131,6 @@ namespace Tensorflow.Keras.Engine { callbacks.on_test_batch_begin(step); - var data = iterator.next(); - logs = test_func(data_handler, iterator.next()); tf_with(ops.control_dependencies(Array.Empty()), ctl => _train_counter.assign_add(1)); From e1ece662643ac4daa98c3390f4a1d790dcff5270 Mon Sep 17 00:00:00 2001 From: Luc BOLOGNA Date: Sat, 17 Jun 2023 22:24:48 +0200 Subject: [PATCH 5/7] Refactor: remove useless unsafe on tensor implicit cast --- src/TensorFlowNET.Core/Tensors/Tensors.cs | 24 +++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/src/TensorFlowNET.Core/Tensors/Tensors.cs b/src/TensorFlowNET.Core/Tensors/Tensors.cs index d063ee39..8d382d61 100644 --- a/src/TensorFlowNET.Core/Tensors/Tensors.cs +++ b/src/TensorFlowNET.Core/Tensors/Tensors.cs @@ -90,73 +90,73 @@ namespace Tensorflow } #region Explicit Conversions - public unsafe static explicit operator bool(Tensors tensor) + public static explicit operator bool(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to bool"); return (bool)tensor[0]; } - public unsafe static explicit operator sbyte(Tensors tensor) + public static explicit operator sbyte(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to sbyte"); return (sbyte)tensor[0]; } - public unsafe static explicit operator byte(Tensors tensor) + public static explicit operator byte(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to byte"); return (byte)tensor[0]; } - public unsafe static explicit operator ushort(Tensors tensor) + public static explicit operator ushort(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to ushort"); return (ushort)tensor[0]; } - public unsafe static explicit operator short(Tensors tensor) + public static explicit operator short(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to short"); return (short)tensor[0]; } - public unsafe static explicit operator int(Tensors tensor) + public static explicit operator int(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to int"); return (int)tensor[0]; } - public unsafe static explicit operator uint(Tensors tensor) + public static explicit operator uint(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to uint"); return (uint)tensor[0]; } - public unsafe static explicit operator long(Tensors tensor) + public static explicit operator long(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to long"); return (long)tensor[0]; } - public unsafe static explicit operator ulong(Tensors tensor) + public static explicit operator ulong(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to ulong"); return (ulong)tensor[0]; } - public unsafe static explicit operator float(Tensors tensor) + public static explicit operator float(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to byte"); return (byte)tensor[0]; } - public unsafe static explicit operator double(Tensors tensor) + public static explicit operator double(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to double"); return (double)tensor[0]; } - public unsafe static explicit operator string(Tensors tensor) + public static explicit operator string(Tensors tensor) { EnsureSingleTensor(tensor, "explicit conversion to string"); return (string)tensor[0]; From 35d2e107f325dc0070cde780a9f8d491cfe2c4f8 Mon Sep 17 00:00:00 2001 From: Wanglongzhi2001 <583087864@qq.com> Date: Sun, 18 Jun 2023 12:15:56 +0800 Subject: [PATCH 6/7] refactor model.evaluate to deal with confilict --- src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs index 912f5e06..eaa9eb23 100644 --- a/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs +++ b/src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs @@ -72,7 +72,7 @@ namespace Tensorflow.Keras.Engine { var data_handler = new DataHandler(new DataHandlerArgs { - X = new Tensors(x), + X = new Tensors(x.ToArray()), Y = y, Model = this, StepsPerExecution = _steps_per_execution @@ -168,7 +168,8 @@ namespace Tensorflow.Keras.Engine Dictionary test_step_multi_inputs_function(DataHandler data_handler, Tensor[] data) { var x_size = data_handler.DataAdapter.GetDataset().FirstInputTensorCount; - var outputs = train_step(data_handler, new Tensors(data.Take(x_size)), new Tensors(data.Skip(x_size))); + var outputs = train_step(data_handler, new Tensors(data.Take(x_size).ToArray()), new Tensors(data.Skip(x_size).ToArray())); + tf_with(ops.control_dependencies(new object[0]), ctl => _train_counter.assign_add(1)); return outputs; } } From 1b1a50371b0829363d1f9c469aedbe727a6ec41f Mon Sep 17 00:00:00 2001 From: Visagan Guruparan <103048@smsassist.com> Date: Sun, 18 Jun 2023 22:46:36 -0500 Subject: [PATCH 7/7] np update square and dot product --- src/TensorFlowNET.Core/APIs/tf.math.cs | 15 ++++++++-- src/TensorFlowNET.Core/Binding.Util.cs | 23 ++++++++++++++- src/TensorFlowNET.Core/NumPy/Numpy.Math.cs | 21 ++++++++++++++ .../TensorFlowNET.UnitTest/Numpy/Math.Test.cs | 29 ++++++++++++++++++- 4 files changed, 84 insertions(+), 4 deletions(-) diff --git a/src/TensorFlowNET.Core/APIs/tf.math.cs b/src/TensorFlowNET.Core/APIs/tf.math.cs index 75253700..0e53d938 100644 --- a/src/TensorFlowNET.Core/APIs/tf.math.cs +++ b/src/TensorFlowNET.Core/APIs/tf.math.cs @@ -14,6 +14,7 @@ limitations under the License. ******************************************************************************/ +using Tensorflow.NumPy; using Tensorflow.Operations; namespace Tensorflow @@ -42,7 +43,6 @@ namespace Tensorflow public Tensor multiply(Tensor x, Tensor y, string name = null) => math_ops.multiply(x, y, name: name); - public Tensor divide_no_nan(Tensor a, Tensor b, string name = null) => math_ops.div_no_nan(a, b); @@ -452,7 +452,18 @@ namespace Tensorflow /// public Tensor multiply(Tx x, Ty y, string name = null) => gen_math_ops.mul(ops.convert_to_tensor(x), ops.convert_to_tensor(y), name: name); - + /// + /// return scalar product + /// + /// + /// + /// + /// + /// + /// + /// + public Tensor dot_prod(Tx x, Ty y, NDArray axes, string name = null) + => math_ops.tensordot(convert_to_tensor(x), convert_to_tensor(y), axes, name: name); public Tensor negative(Tensor x, string name = null) => gen_math_ops.neg(x, name); diff --git a/src/TensorFlowNET.Core/Binding.Util.cs b/src/TensorFlowNET.Core/Binding.Util.cs index 8df39334..e414ef6e 100644 --- a/src/TensorFlowNET.Core/Binding.Util.cs +++ b/src/TensorFlowNET.Core/Binding.Util.cs @@ -486,7 +486,28 @@ namespace Tensorflow throw new NotImplementedException(""); } } - + public static NDArray GetFlattenArray(NDArray x) + { + switch (x.GetDataType()) + { + case TF_DataType.TF_FLOAT: + x = x.ToArray(); + break; + case TF_DataType.TF_DOUBLE: + x = x.ToArray(); + break; + case TF_DataType.TF_INT16: + case TF_DataType.TF_INT32: + x = x.ToArray(); + break; + case TF_DataType.TF_INT64: + x = x.ToArray(); + break; + default: + break; + } + return x; + } public static TF_DataType GetDataType(this object data) { var type = data.GetType(); diff --git a/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs b/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs index ea85048f..5bc97952 100644 --- a/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs +++ b/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs @@ -49,9 +49,30 @@ namespace Tensorflow.NumPy [AutoNumPy] public static NDArray prod(params T[] array) where T : unmanaged => new NDArray(tf.reduce_prod(new NDArray(array))); + [AutoNumPy] + public static NDArray dot(NDArray x1, NDArray x2, NDArray? axes = null, string? name = null) + { + //if axes mentioned + if (axes != null) + { + return new NDArray(tf.dot_prod(x1, x2, axes, name)); + } + if (x1.shape.ndim > 1) + { + x1 = GetFlattenArray(x1); + } + if (x2.shape.ndim > 1) + { + x2 = GetFlattenArray(x2); + } + //if axes not mentioned, default 0,0 + return new NDArray(tf.dot_prod(x1, x2, axes: new int[] { 0, 0 }, name)); + } [AutoNumPy] public static NDArray power(NDArray x, NDArray y) => new NDArray(tf.pow(x, y)); + [AutoNumPy] + public static NDArray square(NDArray x) => new NDArray(tf.square(x)); [AutoNumPy] public static NDArray sin(NDArray x) => new NDArray(math_ops.sin(x)); diff --git a/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs b/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs index 32b517e4..65cdaedd 100644 --- a/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs +++ b/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs @@ -65,7 +65,34 @@ namespace TensorFlowNET.UnitTest.NumPy var y = np.power(x, 3); Assert.AreEqual(y, new[] { 0, 1, 8, 27, 64, 125 }); } - [TestMethod] + [TestMethod] + public void square() + { + var x = np.arange(6); + var y = np.square(x); + Assert.AreEqual(y, new[] { 0, 1, 4, 9, 16, 25 }); + } + [TestMethod] + public void dotproduct() + { + var x1 = new NDArray(new[] { 1, 2, 3 }); + var x2 = new NDArray(new[] { 4, 5, 6 }); + double result1 = np.dot(x1, x2); + NDArray y1 = new float[,] { + { 1.0f, 2.0f, 3.0f }, + { 4.0f, 5.1f,6.0f }, + { 4.0f, 5.1f,6.0f } + }; + NDArray y2 = new float[,] { + { 3.0f, 2.0f, 1.0f }, + { 6.0f, 5.1f, 4.0f }, + { 6.0f, 5.1f, 4.0f } + }; + double result2 = np.dot(y1, y2); + Assert.AreEqual(result1, 32); + Assert.AreEqual(Math.Round(result2, 2), 158.02); + } + [TestMethod] public void maximum() { var x1 = new NDArray(new[,] { { 1, 2, 3 }, { 4, 5.1, 6 } });