diff --git a/Directory.Build.props b/Directory.Build.props index 48257d5d..065690ec 100644 --- a/Directory.Build.props +++ b/Directory.Build.props @@ -12,13 +12,6 @@ --> true $(NoWarn),1573,1591,1712 - - - $(NoWarn),1570 diff --git a/src/TensorFlowNET.Core/APIs/tf.array.cs b/src/TensorFlowNET.Core/APIs/tf.array.cs index 59689bc5..6a186a63 100644 --- a/src/TensorFlowNET.Core/APIs/tf.array.cs +++ b/src/TensorFlowNET.Core/APIs/tf.array.cs @@ -48,7 +48,7 @@ namespace Tensorflow /// /// /// N-D tensor. - /// K-D boolean tensor, K <= N and K must be known statically. + /// K-D boolean tensor, K <= N and K must be known statically. /// /// A 0-D int Tensor representing the axis in tensor to mask from. /// (N-K+1)-dimensional tensor populated by entries in tensor corresponding to True values in mask. diff --git a/src/TensorFlowNET.Core/APIs/tf.math.cs b/src/TensorFlowNET.Core/APIs/tf.math.cs index f960e14c..23f7753b 100644 --- a/src/TensorFlowNET.Core/APIs/tf.math.cs +++ b/src/TensorFlowNET.Core/APIs/tf.math.cs @@ -170,7 +170,7 @@ namespace Tensorflow => gen_math_ops.greater_equal(x, y, name); /// - /// Returns the truth value of (x < y) element-wise. + /// Returns the truth value of (x < y) element-wise. /// /// /// @@ -191,7 +191,7 @@ namespace Tensorflow => gen_math_ops.lgamma(x, name: name); /// - /// Returns the truth value of (x <= y) element-wise. + /// Returns the truth value of (x <= y) element-wise. /// /// /// @@ -344,7 +344,7 @@ namespace Tensorflow => gen_math_ops.maximum(x, y, name: name); /// - /// Returns the min of x and y (i.e. x < y ? x : y) element-wise. + /// Returns the min of x and y (i.e. x < y ? x : y) element-wise. /// /// /// diff --git a/src/TensorFlowNET.Core/Eager/c_api.eager.cs b/src/TensorFlowNET.Core/Eager/c_api.eager.cs index c14c4e99..af652824 100644 --- a/src/TensorFlowNET.Core/Eager/c_api.eager.cs +++ b/src/TensorFlowNET.Core/Eager/c_api.eager.cs @@ -231,7 +231,7 @@ namespace Tensorflow /// /// /// - /// const tensorflow::Tensor& + /// const tensorflow::Tensor& /// TFE_TensorHandle* [DllImport(TensorFlowLibName)] public static extern TFE_TensorHandle TFE_NewTensorHandle(IntPtr t, SafeStatusHandle status); diff --git a/src/TensorFlowNET.Core/Gradients/math_grad.cs b/src/TensorFlowNET.Core/Gradients/math_grad.cs index 12205dba..c40efc33 100644 --- a/src/TensorFlowNET.Core/Gradients/math_grad.cs +++ b/src/TensorFlowNET.Core/Gradients/math_grad.cs @@ -393,7 +393,7 @@ namespace Tensorflow.Gradients } /// - /// Returns grad*(x > y, x <= y) with type of grad. + /// Returns grad*(x > y, x <= y) with type of grad. /// /// /// @@ -405,7 +405,7 @@ namespace Tensorflow.Gradients } /// - /// Returns grad*(x < y, x >= y) with type of grad. + /// Returns grad*(x < y, x >= y) with type of grad. /// /// /// diff --git a/src/TensorFlowNET.Core/Operations/gen_logging_ops.cs b/src/TensorFlowNET.Core/Operations/gen_logging_ops.cs index dc2853cb..8d4353f8 100644 --- a/src/TensorFlowNET.Core/Operations/gen_logging_ops.cs +++ b/src/TensorFlowNET.Core/Operations/gen_logging_ops.cs @@ -45,7 +45,7 @@ namespace Tensorflow /// Tags for the summary. /// /// - /// Same shape as tags. Values for the summary. + /// Same shape as tags. Values for the summary. /// /// /// If specified, the created operation in the graph will be this one, otherwise it will be named 'ScalarSummary'. diff --git a/src/TensorFlowNET.Core/Operations/gen_ops.cs b/src/TensorFlowNET.Core/Operations/gen_ops.cs index 14b5700b..386537b7 100644 --- a/src/TensorFlowNET.Core/Operations/gen_ops.cs +++ b/src/TensorFlowNET.Core/Operations/gen_ops.cs @@ -6154,11 +6154,11 @@ namespace Tensorflow.Operations /// in normalized coordinates [y1, x1, y2, x2]. A normalized coordinate value of /// y is mapped to the image coordinate at y * (image_height - 1), so as the /// [0, 1] interval of normalized image height is mapped to - /// [0, image_height - 1] in image height coordinates. We do allow y1 &gt; y2, in + /// [0, image_height - 1] in image height coordinates. We do allow y1 &gt; y2, in /// which case the sampled crop is an up-down flipped version of the original /// image. The width dimension is treated similarly. Normalized coordinates - /// outside the [0, 1] range are allowed, in which case we use - /// extrapolation_value to extrapolate the input image values. + /// outside the [0, 1] range are allowed, in which case we use + /// extrapolation_value to extrapolate the input image values. /// /// /// A 1-D tensor of shape [num_boxes] with int32 values in [0, batch). @@ -6200,11 +6200,11 @@ namespace Tensorflow.Operations /// in normalized coordinates [y1, x1, y2, x2]. A normalized coordinate value of /// y is mapped to the image coordinate at y * (image_height - 1), so as the /// [0, 1] interval of normalized image height is mapped to - /// [0, image_height - 1] in image height coordinates. We do allow y1 &gt; y2, in + /// [0, image_height - 1] in image height coordinates. We do allow y1 &gt; y2, in /// which case the sampled crop is an up-down flipped version of the original /// image. The width dimension is treated similarly. Normalized coordinates - /// outside the [0, 1] range are allowed, in which case we use - /// extrapolation_value to extrapolate the input image values. + /// outside the [0, 1] range are allowed, in which case we use + /// extrapolation_value to extrapolate the input image values. /// /// /// A 1-D tensor of shape [num_boxes] with int32 values in [0, batch). @@ -15982,9 +15982,9 @@ namespace Tensorflow.Operations /// everything else padded with zeros. The diagonal is computed as follows: /// /// Assume diagonal has k dimensions [I, J, K, ..., N], then the output is a - /// tensor of rank k+1 with dimensions [I, J, K, ..., N, N] where: + /// tensor of rank k+1 with dimensions [I, J, K, ..., N, N] where: /// - /// output[i, j, k, ..., m, n] = 1{m=n} * diagonal[i, j, k, ..., n]. + /// output[i, j, k, ..., m, n] = 1{m=n} * diagonal[i, j, k, ..., n]. /// /// For example: /// @@ -18540,7 +18540,8 @@ namespace Tensorflow.Operations /// ][ /// [0.0, 1.0, 0.0] // one_hot(1) /// [0.0, 0.0, 0.0] // one_hot(-1) - /// ] + /// ] + /// /// public static Tensor one_hot (Tensor indices, Tensor depth, Tensor on_value, Tensor off_value, int? axis = null, string name = "OneHot") { @@ -21850,7 +21851,6 @@ namespace Tensorflow.Operations /// The Operation can be fetched from any of the Tensorreturned in the tuple values, by fetching the Operation property. /// /// - /// /// public static (Tensor output, Tensor output_min, Tensor output_max) quantized_reshape (Tensor tensor, Tensor shape, Tensor input_min, Tensor input_max, string name = "QuantizedReshape") { @@ -26970,10 +26970,10 @@ namespace Tensorflow.Operations /// /// The values of value are assigned to the positions in the variable /// ref that are selected by the slice parameters. The slice parameters - /// begin, end, strides, etc. work exactly as in StridedSlice. + /// begin, end, strides, etc. work exactly as in StridedSlice. /// - /// NOTE this op currently does not support broadcasting and so value's - /// shape must be exactly the shape produced by the slice of ref. + /// NOTE this op currently does not support broadcasting and so value's + /// shape must be exactly the shape produced by the slice of ref. /// public static Operation resource_strided_slice_assign (Tensor referecne, Tensor begin, Tensor end, Tensor strides, Tensor value, int? begin_mask = null, int? end_mask = null, int? ellipsis_mask = null, int? new_axis_mask = null, int? shrink_axis_mask = null, string name = "ResourceStridedSliceAssign") { @@ -28068,7 +28068,7 @@ namespace Tensorflow.Operations /// Tags for the summary. /// /// - /// Same shape as tags. Values for the summary. + /// Same shape as tags. Values for the summary. /// /// /// If specified, the created operation in the graph will be this one, otherwise it will be named 'ScalarSummary'. @@ -34548,10 +34548,10 @@ namespace Tensorflow.Operations /// /// The values of value are assigned to the positions in the variable /// ref that are selected by the slice parameters. The slice parameters - /// begin, end, strides, etc. work exactly as in StridedSlice. + /// begin, end, strides, etc. work exactly as in StridedSlice. /// - /// NOTE this op currently does not support broadcasting and so value's - /// shape must be exactly the shape produced by the slice of ref. + /// NOTE this op currently does not support broadcasting and so value's + /// shape must be exactly the shape produced by the slice of ref. /// public static Tensor strided_slice_assign (Tensor referecne, Tensor begin, Tensor end, Tensor strides, Tensor value, int? begin_mask = null, int? end_mask = null, int? ellipsis_mask = null, int? new_axis_mask = null, int? shrink_axis_mask = null, string name = "StridedSliceAssign") { @@ -36554,21 +36554,21 @@ namespace Tensorflow.Operations /// and that value has shape /// /// - /// (n0 + n1 + ... + n(T-1) x d0 x d1 x ...), + /// (n0 + n1 + ... + n(T-1) x d0 x d1 x ...), /// /// this splits values into a TensorArray with T tensors. /// /// TensorArray index t will be the subtensor of values with starting position /// - /// + /// /// (n0 + n1 + ... + n(t-1), 0, 0, ...) - /// + /// /// /// and having size /// - /// + /// /// nt x d0 x d1 x ... - /// + /// /// public static Tensor tensor_array_split_v3 (Tensor handle, Tensor value, Tensor lengths, Tensor flow_in, string name = "TensorArraySplitV3") { @@ -38107,9 +38107,9 @@ namespace Tensorflow.Operations /// This operation also returns a tensor idx that is the same size as /// the number of the elements in x along the axis dimension. It /// contains the index in the unique output y. - /// In other words, for an 1-D tensor x with axis = None: + /// In other words, for an 1-D tensor x with axis = None: /// - /// y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1] + /// y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1] /// /// For example: /// @@ -38120,7 +38120,7 @@ namespace Tensorflow.Operations /// idx ==&gt; [0, 0, 1, 2, 2, 2, 3, 4, 4] /// /// - /// For an 2-D tensor x with axis = 0: + /// For an 2-D tensor x with axis = 0: /// /// /// # tensor 'x' is [[1, 0, 0], @@ -38132,7 +38132,7 @@ namespace Tensorflow.Operations /// idx ==&gt; [0, 0, 1] /// /// - /// For an 2-D tensor x with axis = 1: + /// For an 2-D tensor x with axis = 1: /// /// /// # tensor 'x' is [[1, 0, 0], @@ -38241,9 +38241,9 @@ namespace Tensorflow.Operations /// that are the same size as the number of the elements in x along the /// axis dimension. The idx contains the index in the unique output y /// and the count contains the count in the unique output y. - /// In other words, for an 1-D tensor x with axis = None: + /// In other words, for an 1-D tensor x with axis = None: /// - /// y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1] + /// y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1] /// /// For example: /// @@ -38255,7 +38255,7 @@ namespace Tensorflow.Operations /// count ==&gt; [2, 1, 3, 1, 2] /// /// - /// For an 2-D tensor x with axis = 0: + /// For an 2-D tensor x with axis = 0: /// /// /// # tensor 'x' is [[1, 0, 0], @@ -38268,7 +38268,7 @@ namespace Tensorflow.Operations /// count ==&gt; [2, 1] /// /// - /// For an 2-D tensor x with axis = 1: + /// For an 2-D tensor x with axis = 1: /// /// /// # tensor 'x' is [[1, 0, 0], diff --git a/src/TensorFlowNET.Core/Operations/math_ops.cs b/src/TensorFlowNET.Core/Operations/math_ops.cs index 6631e057..0c167691 100644 --- a/src/TensorFlowNET.Core/Operations/math_ops.cs +++ b/src/TensorFlowNET.Core/Operations/math_ops.cs @@ -406,10 +406,10 @@ namespace Tensorflow /// Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each /// entry in `axis`. If `keepdims` is true, the reduced dimensions /// are retained with length 1. - + /// /// If `axis` has no entries, all dimensions are reduced, and a /// tensor with a single element is returned. - + /// /// This function is more numerically stable than log(sum(exp(input))). It avoids /// overflows caused by taking the exp of large inputs and underflows caused by /// taking the log of small inputs. diff --git a/src/TensorFlowNET.Core/Status/c_api.status.cs b/src/TensorFlowNET.Core/Status/c_api.status.cs index b5da21bf..7854481d 100644 --- a/src/TensorFlowNET.Core/Status/c_api.status.cs +++ b/src/TensorFlowNET.Core/Status/c_api.status.cs @@ -54,7 +54,7 @@ namespace Tensorflow public static extern SafeStatusHandle TF_NewStatus(); /// - /// Record in *s. Any previous information is lost. + /// Record <code, msg> in *s. Any previous information is lost. /// A common use is to clear a status: TF_SetStatus(s, TF_OK, ""); /// /// diff --git a/src/TensorFlowNET.Core/Summaries/Summary.cs b/src/TensorFlowNET.Core/Summaries/Summary.cs index 39a8c10a..a1f47bc0 100644 --- a/src/TensorFlowNET.Core/Summaries/Summary.cs +++ b/src/TensorFlowNET.Core/Summaries/Summary.cs @@ -74,7 +74,7 @@ namespace Tensorflow.Summaries /// /// Adds keys to a collection. /// - /// + /// The value to add per each key. /// A collection of keys to add. /// Used if collections is None. public void collect(ITensorOrOperation val, List collections, List default_collections) diff --git a/src/TensorFlowNET.Core/Tensors/c_api.tensor.cs b/src/TensorFlowNET.Core/Tensors/c_api.tensor.cs index dc8d795a..cf3c00c8 100644 --- a/src/TensorFlowNET.Core/Tensors/c_api.tensor.cs +++ b/src/TensorFlowNET.Core/Tensors/c_api.tensor.cs @@ -56,7 +56,7 @@ namespace Tensorflow /// /// Return the length of the tensor in the "dim_index" dimension. - /// REQUIRES: 0 <= dim_index < TF_NumDims(tensor) + /// REQUIRES: 0 <= dim_index < TF_NumDims(tensor) /// /// /// diff --git a/src/TensorFlowNET.Core/ops.cs b/src/TensorFlowNET.Core/ops.cs index d0eba736..87b0cfa1 100644 --- a/src/TensorFlowNET.Core/ops.cs +++ b/src/TensorFlowNET.Core/ops.cs @@ -124,7 +124,7 @@ namespace Tensorflow /// Wrapper for `Graph.control_dependencies()` using the default graph. /// /// See `tf.Graph.control_dependencies` for more details. - + /// /// When eager execution is enabled, any callable object in the `control_inputs` /// list will be called. ///