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tf.boolean_mask SciSharp#396 
1 parent 6c6c8c4 commit f1a3881

8 files changed

Lines changed: 84 additions & 3 deletions

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‎src/TensorFlowNET.Core/APIs/tf.array.cs‎

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@@ -39,6 +39,19 @@ public partial class tensorflow
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public Tensor batch_to_space_nd<T>(T input, int[] block_shape, int[,] crops, string name = null)
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=> gen_array_ops.batch_to_space_nd(input, block_shape, crops, name: name);
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/// <summary>
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/// Apply boolean mask to tensor.
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/// </summary>
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/// <typeparam name="T1"></typeparam>
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/// <typeparam name="T2"></typeparam>
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/// <param name="tensor">N-D tensor.</param>
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/// <param name="mask">K-D boolean tensor, K <= N and K must be known statically.</param>
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/// <param name="name"></param>
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/// <param name="axis">A 0-D int Tensor representing the axis in tensor to mask from. </param>
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/// <returns>(N-K+1)-dimensional tensor populated by entries in tensor corresponding to True values in mask.</returns>
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public Tensor boolean_mask<T1, T2>(T1 tensor, T2 mask, string name = "boolean_mask", int axis = 0)
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=> array_ops.boolean_mask(tensor, mask, name: name, axis: axis);
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public Tensor check_numerics(Tensor tensor, string message, string name = null)
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=> gen_array_ops.check_numerics(tensor, message, name: name);
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src/TensorFlowNET.Core/APIs/tf.control.cs renamed to src/TensorFlowNET.Core/APIs/tf.control_flow.cs

File renamed without changes.

‎src/TensorFlowNET.Core/APIs/tf.ops.cs‎

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@@ -21,6 +21,9 @@ public partial class tensorflow
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public Tensor assign(Tensor @ref, object value, bool validate_shape = true, bool use_locking = true, string name = null)
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=> state_ops.assign(@ref, value, validate_shape, use_locking, name);
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public void device(string device_name)
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=> get_default_graph().device(device_name);
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public object get_collection(string key, string scope = "")
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=> get_default_graph().get_collection(key, scope: scope);
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‎src/TensorFlowNET.Core/Graphs/Graph.cs‎

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@@ -288,6 +288,11 @@ public Operation create_op(string op_type, Tensor[] inputs, TF_DataType[] dtypes
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return op;
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}
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public void device(string device_name)
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{
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throw new NotImplementedException("");
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}
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private void _create_op_helper(Operation op, bool compute_device = true)
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{
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_record_op_seen_by_control_dependencies(op);

‎src/TensorFlowNET.Core/Operations/array_ops.py.cs‎

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@@ -17,6 +17,8 @@ limitations under the License.
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using NumSharp;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using Tensorflow.Framework;
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using static Tensorflow.Binding;
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namespace Tensorflow
@@ -66,6 +68,44 @@ public static Tensor zeros(TensorShape shape, TF_DataType dtype = TF_DataType.TF
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});
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}
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public static Tensor boolean_mask<T1, T2>(T1 tensor, T2 mask, string name = "boolean_mask", int axis = 0)
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{
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return tf_with(ops.name_scope(name, values: new { tensor, mask }), delegate
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{
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var tensor_tensor = ops.convert_to_tensor(tensor, name: "tensor");
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var mask_tensor = ops.convert_to_tensor(mask, name: "mask");
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var shape_mask = mask_tensor.TensorShape;
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var ndims_mask = shape_mask.ndim;
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var shape_tensor = tensor_tensor.TensorShape;
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if (ndims_mask < 1)
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throw new ValueError("mask cannot be scalar.");
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var leading_size = gen_math_ops.prod(shape(tensor_tensor)[$"{axis}:{axis + ndims_mask}"], new[] { 0 });
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var shape1 = concat(new[]
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{
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shape(tensor_tensor)[$":{axis}"],
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tf.expand_dims(leading_size, 0),
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shape(tensor_tensor)[$"{axis + ndims_mask}:"]
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}, 0);
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tensor_tensor = reshape(tensor, shape1);
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var first_dim = shape_tensor.dims.Skip(axis).Take(ndims_mask).First();
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var s1 = tensor_shape.as_shape(shape_tensor.dims.Take(axis).ToArray());
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var s2 = s1.concatenate(new[] { first_dim }).concatenate(shape_tensor.dims.Skip(axis + ndims_mask).ToArray());
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tensor_tensor.set_shape(s2);
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mask_tensor = reshape(mask_tensor, new[] { -1 });
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return _apply_mask_1d(tensor_tensor, mask_tensor, axis);
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});
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}
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private static Tensor _apply_mask_1d(Tensor reshaped_tensor, Tensor mask, int axis = 0)
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{
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var indices = squeeze(where(mask), axis: new[] { 1 });
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return gather(reshaped_tensor, indices, axis: axis);
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}
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public static Tensor zeros(Tensor shape, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = null)
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{
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dtype = dtype.as_base_dtype();
@@ -336,7 +376,12 @@ public static Tensor where(Tensor condition, object x = null, object y = null, s
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{
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if( x == null && y == null)
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{
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throw new NotImplementedException("where");
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return tf_with(ops.name_scope(name, "Where", new { condition }), scope =>
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{
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name = scope;
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condition = ops.convert_to_tensor(condition, preferred_dtype: dtypes.@bool, name: "condition");
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return gen_array_ops.where(condition: condition, name: name);
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});
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}
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else if(x != null && y != null)
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{

‎src/TensorFlowNET.Core/Operations/gen_array_ops.cs‎

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@@ -274,9 +274,10 @@ public static Tensor[] unpack(Tensor value, int num, int axis = 0, string name =
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return _op.outputs;
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}
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public static Tensor where()
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public static Tensor where(Tensor condition, string name = null)
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{
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throw new NotImplementedException("where");
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var _op = _op_def_lib._apply_op_helper("Where", name, new { input = condition });
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return _op.output;
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}
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public static Tensor one_hot(Tensor indices, int depth,

‎src/TensorFlowNET.Core/Tensors/dtypes.cs‎

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@@ -23,6 +23,7 @@ namespace Tensorflow
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{
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public static class dtypes
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{
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public static TF_DataType @bool = TF_DataType.TF_BOOL;
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public static TF_DataType int8 = TF_DataType.TF_INT8;
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public static TF_DataType int32 = TF_DataType.TF_INT32;
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public static TF_DataType int64 = TF_DataType.TF_INT64;

‎test/TensorFlowNET.UnitTest/TensorTest.cs‎

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@@ -260,5 +260,18 @@ public void batch_to_space_nd()
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Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 15, 21, 16, 22, 17, 23 }, result[0, 3].ToArray<int>()));
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}
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}
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[TestMethod]
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public void boolean_mask()
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{
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var tensor = new[] { 0, 1, 2, 3 };
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var mask = np.array(new[] { true, false, true, false });
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var masked = tf.boolean_mask(tensor, mask);
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using (var sess = tf.Session())
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{
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var result = sess.run(masked);
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Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 2 }, result.ToArray<int>()));
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}
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}
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}
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}

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