mirror of
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Fix all doxygen warnings.
This commit is contained in:
@@ -16,7 +16,7 @@
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#include "src/util/CXX11Meta.h"
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/** \defgroup CXX11_TensorSymmetry_Module Tensor Symmetry Module
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/** \defgroup TensorSymmetry_Module Tensor Symmetry Module
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*
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* This module provides a classes that allow for the definition of
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* symmetries w.r.t. tensor indices.
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@@ -91,7 +91,7 @@ See Assigning to a TensorRef below.
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## Accessing Tensor Elements
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#### <data_type> tensor(index0, index1...)
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#### data_type tensor(index0, index1...)
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Return the element at position `(index0, index1...)` in tensor
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`tensor`. You must pass as many parameters as the rank of `tensor`.
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@@ -470,7 +470,7 @@ Represents the datatype of individual tensor elements. For example, for a
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`Tensor<float>`, `Scalar` is the type `float`. See
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`setConstant()`.
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#### <Operation>
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#### (Operation)
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We use this pseudo type to indicate that a tensor Operation is returned by a
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method. We indicate in the text the type and dimensions of the tensor that the
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@@ -776,7 +776,7 @@ The chain of Operation is evaluated lazily, typically when it is assigned to a
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tensor. See "Controlling when Expression are Evaluated" for more details about
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their evaluation.
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### <Operation> constant(const Scalar& val)
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### (Operation) constant(const Scalar& val)
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Returns a tensor of the same type and dimensions as the original tensor but
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where all elements have the value `val`.
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@@ -804,7 +804,7 @@ tensor, or multiply every element of a tensor by a scalar.
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0.6 0.6 0.6
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0.6 0.6 0.6
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### <Operation> random()
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### (Operation) random()
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Returns a tensor of the same type and dimensions as the current tensor
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but where all elements have random values.
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@@ -834,7 +834,7 @@ All these operations take a single input tensor as argument and return a tensor
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of the same type and dimensions as the tensor to which they are applied. The
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requested operations are applied to each element independently.
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### <Operation> operator-()
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### (Operation) operator-()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the opposite values of the original tensor.
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@@ -853,42 +853,42 @@ containing the opposite values of the original tensor.
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-1 -1 -1
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-1 -1 -1
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### <Operation> sqrt()
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### (Operation) sqrt()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the square roots of the original tensor.
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### <Operation> rsqrt()
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### (Operation) rsqrt()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the inverse square roots of the original tensor.
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### <Operation> square()
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### (Operation) square()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the squares of the original tensor values.
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### <Operation> inverse()
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### (Operation) inverse()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the inverse of the original tensor values.
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### <Operation> exp()
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### (Operation) exp()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the exponential of the original tensor.
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### <Operation> log()
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### (Operation) log()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the natural logarithms of the original tensor.
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### <Operation> abs()
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### (Operation) abs()
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Returns a tensor of the same type and dimensions as the original tensor
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containing the absolute values of the original tensor.
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### <Operation> pow(Scalar exponent)
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### (Operation) pow(Scalar exponent)
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Returns a tensor of the same type and dimensions as the original tensor
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containing the coefficients of the original tensor to the power of the
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@@ -915,17 +915,17 @@ cubic roots of an int Tensor:
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0 1 2
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3 4 5
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### <Operation> operator * (Scalar scale)
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### (Operation) operator * (Scalar scale)
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Multiplies all the coefficients of the input tensor by the provided scale.
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### <Operation> cwiseMax(Scalar threshold)
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### (Operation) cwiseMax(Scalar threshold)
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TODO
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### <Operation> cwiseMin(Scalar threshold)
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### (Operation) cwiseMin(Scalar threshold)
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TODO
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### <Operation> unaryExpr(const CustomUnaryOp& func)
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### (Operation) unaryExpr(const CustomUnaryOp& func)
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TODO
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@@ -937,39 +937,39 @@ dimensions as the tensors to which they are applied, and unless otherwise
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specified it is also of the same type. The requested operations are applied to
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each pair of elements independently.
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### <Operation> operator+(const OtherDerived& other)
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### (Operation) operator+(const OtherDerived& other)
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Returns a tensor of the same type and dimensions as the input tensors
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containing the coefficient wise sums of the inputs.
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### <Operation> operator-(const OtherDerived& other)
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### (Operation) operator-(const OtherDerived& other)
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Returns a tensor of the same type and dimensions as the input tensors
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containing the coefficient wise differences of the inputs.
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### <Operation> operator*(const OtherDerived& other)
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### (Operation) operator*(const OtherDerived& other)
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Returns a tensor of the same type and dimensions as the input tensors
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containing the coefficient wise products of the inputs.
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### <Operation> operator/(const OtherDerived& other)
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### (Operation) operator/(const OtherDerived& other)
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Returns a tensor of the same type and dimensions as the input tensors
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containing the coefficient wise quotients of the inputs.
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This operator is not supported for integer types.
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### <Operation> cwiseMax(const OtherDerived& other)
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### (Operation) cwiseMax(const OtherDerived& other)
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Returns a tensor of the same type and dimensions as the input tensors
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containing the coefficient wise maximums of the inputs.
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### <Operation> cwiseMin(const OtherDerived& other)
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### (Operation) cwiseMin(const OtherDerived& other)
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Returns a tensor of the same type and dimensions as the input tensors
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containing the coefficient wise mimimums of the inputs.
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### <Operation> Logical operators
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### (Operation) Logical operators
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The following logical operators are supported as well:
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@@ -1127,50 +1127,50 @@ scalar, represented as a zero-dimension tensor.
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276
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### <Operation> sum(const Dimensions& new_dims)
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### <Operation> sum()
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### (Operation) sum(const Dimensions& new_dims)
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### (Operation) sum()
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Reduce a tensor using the sum() operator. The resulting values
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are the sum of the reduced values.
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### <Operation> mean(const Dimensions& new_dims)
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### <Operation> mean()
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### (Operation) mean(const Dimensions& new_dims)
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### (Operation) mean()
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Reduce a tensor using the mean() operator. The resulting values
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are the mean of the reduced values.
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### <Operation> maximum(const Dimensions& new_dims)
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### <Operation> maximum()
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### (Operation) maximum(const Dimensions& new_dims)
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### (Operation) maximum()
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Reduce a tensor using the maximum() operator. The resulting values are the
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largest of the reduced values.
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### <Operation> minimum(const Dimensions& new_dims)
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### <Operation> minimum()
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### (Operation) minimum(const Dimensions& new_dims)
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### (Operation) minimum()
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Reduce a tensor using the minimum() operator. The resulting values
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are the smallest of the reduced values.
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### <Operation> prod(const Dimensions& new_dims)
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### <Operation> prod()
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### (Operation) prod(const Dimensions& new_dims)
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### (Operation) prod()
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Reduce a tensor using the prod() operator. The resulting values
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are the product of the reduced values.
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### <Operation> all(const Dimensions& new_dims)
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### <Operation> all()
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### (Operation) all(const Dimensions& new_dims)
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### (Operation) all()
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Reduce a tensor using the all() operator. Casts tensor to bool and then checks
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whether all elements are true. Runs through all elements rather than
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short-circuiting, so may be significantly inefficient.
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### <Operation> any(const Dimensions& new_dims)
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### <Operation> any()
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### (Operation) any(const Dimensions& new_dims)
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### (Operation) any()
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Reduce a tensor using the any() operator. Casts tensor to bool and then checks
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whether any element is true. Runs through all elements rather than
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short-circuiting, so may be significantly inefficient.
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### <Operation> reduce(const Dimensions& new_dims, const Reducer& reducer)
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### (Operation) reduce(const Dimensions& new_dims, const Reducer& reducer)
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Reduce a tensor using a user-defined reduction operator. See `SumReducer`
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in TensorFunctors.h for information on how to implement a reduction operator.
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@@ -1206,8 +1206,8 @@ Example: Trace along 2 dimensions.
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15
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### <Operation> trace(const Dimensions& new_dims)
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### <Operation> trace()
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### (Operation) trace(const Dimensions& new_dims)
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### (Operation) trace()
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As a special case, if no parameter is passed to the operation, trace is computed
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along *all* dimensions of the input tensor.
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@@ -1257,18 +1257,18 @@ dd a comment to this line
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1 3 6
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4 9 15
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### <Operation> cumsum(const Index& axis)
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### (Operation) cumsum(const Index& axis)
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Perform a scan by summing consecutive entries.
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### <Operation> cumprod(const Index& axis)
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### (Operation) cumprod(const Index& axis)
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Perform a scan by multiplying consecutive entries.
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## Convolutions
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### <Operation> convolve(const Kernel& kernel, const Dimensions& dims)
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### (Operation) convolve(const Kernel& kernel, const Dimensions& dims)
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Returns a tensor that is the output of the convolution of the input tensor with the kernel,
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along the specified dimensions of the input tensor. The dimension size for dimensions of the output tensor
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@@ -1311,7 +1311,7 @@ These operations return a Tensor with different dimensions than the original
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Tensor. They can be used to access slices of tensors, see them with different
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dimensions, or pad tensors with additional data.
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### <Operation> reshape(const Dimensions& new_dims)
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### (Operation) reshape(const Dimensions& new_dims)
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Returns a view of the input tensor that has been reshaped to the specified
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new dimensions. The argument new_dims is an array of Index values. The
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@@ -1390,7 +1390,7 @@ Note that "b" itself was not reshaped but that instead the assignment is done to
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the reshape view of b.
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### <Operation> shuffle(const Shuffle& shuffle)
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### (Operation) shuffle(const Shuffle& shuffle)
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Returns a copy of the input tensor whose dimensions have been
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reordered according to the specified permutation. The argument shuffle
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@@ -1431,7 +1431,7 @@ Let's rewrite the previous example to take advantage of this feature:
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output.shuffle({2, 0, 1}) = input;
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### <Operation> stride(const Strides& strides)
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### (Operation) stride(const Strides& strides)
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Returns a view of the input tensor that strides (skips stride-1
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elements) along each of the dimensions. The argument strides is an
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@@ -1457,7 +1457,7 @@ It is possible to assign a tensor to a stride:
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output.stride({2, 3, 4}) = input;
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### <Operation> slice(const StartIndices& offsets, const Sizes& extents)
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### (Operation) slice(const StartIndices& offsets, const Sizes& extents)
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Returns a sub-tensor of the given tensor. For each dimension i, the slice is
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made of the coefficients stored between offset[i] and offset[i] + extents[i] in
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@@ -1483,7 +1483,7 @@ the input tensor.
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600 700
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### <Operation> chip(const Index offset, const Index dim)
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### (Operation) chip(const Index offset, const Index dim)
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A chip is a special kind of slice. It is the subtensor at the given offset in
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the dimension dim. The returned tensor has one fewer dimension than the input
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@@ -1534,7 +1534,7 @@ lvalue. For example:
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0 0 0
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### <Operation> reverse(const ReverseDimensions& reverse)
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### (Operation) reverse(const ReverseDimensions& reverse)
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Returns a view of the input tensor that reverses the order of the coefficients
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along a subset of the dimensions. The argument reverse is an array of boolean
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@@ -1564,7 +1564,7 @@ of a 2D tensor:
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0 100 200
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### <Operation> broadcast(const Broadcast& broadcast)
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### (Operation) broadcast(const Broadcast& broadcast)
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Returns a view of the input tensor in which the input is replicated one to many
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times.
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@@ -1588,11 +1588,11 @@ made in each of the dimensions.
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0 100 200 0 100 200
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300 400 500 300 400 500
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### <Operation> concatenate(const OtherDerived& other, Axis axis)
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### (Operation) concatenate(const OtherDerived& other, Axis axis)
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TODO
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### <Operation> pad(const PaddingDimensions& padding)
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### (Operation) pad(const PaddingDimensions& padding)
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Returns a view of the input tensor in which the input is padded with zeros.
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@@ -1617,7 +1617,7 @@ Returns a view of the input tensor in which the input is padded with zeros.
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0 0 0 0
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### <Operation> extract_patches(const PatchDims& patch_dims)
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### (Operation) extract_patches(const PatchDims& patch_dims)
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Returns a tensor of coefficient patches extracted from the input tensor, where
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each patch is of dimension specified by 'patch_dims'. The returned tensor has
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@@ -1704,7 +1704,7 @@ This code results in the following output when the data layout is RowMajor:
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6 7
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10 11
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### <Operation> extract_image_patches(const Index patch_rows, const Index patch_cols, const Index row_stride, const Index col_stride, const PaddingType padding_type)
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### (Operation) extract_image_patches(const Index patch_rows, const Index patch_cols, const Index row_stride, const Index col_stride, const PaddingType padding_type)
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Returns a tensor of coefficient image patches extracted from the input tensor,
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which is expected to have dimensions ordered as follows (depending on the data
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@@ -1761,7 +1761,7 @@ sizes:
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## Special Operations
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### <Operation> cast<T>()
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### (Operation) cast<T>()
|
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Returns a tensor of type T with the same dimensions as the original tensor.
|
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The returned tensor contains the values of the original tensor converted to
|
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@@ -1790,7 +1790,7 @@ but you can easily cast the tensors to floats to do the division:
|
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1 2 2
|
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|
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|
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### <Operation> eval()
|
||||
### (Operation) eval()
|
||||
|
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TODO
|
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|
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@@ -424,7 +424,7 @@ struct ThreadProperties {
|
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* \tparam input_mapper_properties : determine if the input tensors are matrix. If they are matrix, special memory
|
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access is used to guarantee that always the memory access are coalesced.
|
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*
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* \tptaram IsFinal : determine if this is the final kernel. If so, the result will be written in a final output.
|
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* \tparam IsFinal : determine if this is the final kernel. If so, the result will be written in a final output.
|
||||
Otherwise, the result of contraction will be written iin a temporary buffer. This is the case when Tall/Skinny
|
||||
contraction is used. So in this case, a final reduction step is required to compute final output.
|
||||
|
||||
|
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@@ -106,7 +106,7 @@ namespace group_theory {
|
||||
/** \internal
|
||||
*
|
||||
* \class strip_identities
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Cleanse a list of group elements of the identity element
|
||||
*
|
||||
@@ -148,7 +148,7 @@ struct strip_identities<Equality, id, type_list<EIGEN_TPL_PP_SPEC_HACK_USE(ts)>>
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_first_step_elements_helper
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Recursive template that adds powers of the first generator to the list of group elements
|
||||
*
|
||||
@@ -198,7 +198,7 @@ struct dimino_first_step_elements_helper<Multiply, Equality, id, g, current_elem
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_first_step_elements
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Add all powers of the first generator to the list of group elements
|
||||
*
|
||||
@@ -236,7 +236,7 @@ struct dimino_first_step_elements
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_get_coset_elements
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Generate all elements of a specific coset
|
||||
*
|
||||
@@ -277,7 +277,7 @@ struct dimino_get_coset_elements<Multiply, sub_group_elements, new_coset_rep, fa
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_add_cosets_for_rep
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Recursive template for adding coset spaces
|
||||
*
|
||||
@@ -365,7 +365,7 @@ struct dimino_add_cosets_for_rep<Multiply, Equality, id, sub_group_elements, ele
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_add_all_coset_spaces
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Recursive template for adding all coset spaces for a new generator
|
||||
*
|
||||
@@ -440,7 +440,7 @@ struct dimino_add_all_coset_spaces<Multiply, Equality, id, sub_group_elements, e
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_add_generator
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Enlarge the group by adding a new generator.
|
||||
*
|
||||
@@ -502,7 +502,7 @@ struct dimino_add_generator<Multiply, Equality, id, elements, generators_done, c
|
||||
/** \internal
|
||||
*
|
||||
* \class dimino_add_remaining_generators
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Recursive template that adds all remaining generators to a group
|
||||
*
|
||||
@@ -570,7 +570,7 @@ struct dimino_add_remaining_generators<Multiply, Equality, id, generators_done,
|
||||
/** \internal
|
||||
*
|
||||
* \class enumerate_group_elements_noid
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Helper template that implements group element enumeration
|
||||
*
|
||||
@@ -625,7 +625,7 @@ struct enumerate_group_elements_noid<Multiply, Equality, id, type_list<>, initia
|
||||
/** \internal
|
||||
*
|
||||
* \class enumerate_group_elements
|
||||
* \ingroup CXX11_TensorSymmetry_Module
|
||||
* \ingroup TensorSymmetry_Module
|
||||
*
|
||||
* \brief Enumerate all elements in a finite group
|
||||
*
|
||||
|
||||
@@ -13,7 +13,7 @@
|
||||
namespace Eigen {
|
||||
|
||||
/** \class MaxSizeVector
|
||||
* \ingroup Core
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \brief The MaxSizeVector class.
|
||||
*
|
||||
|
||||
@@ -16,7 +16,7 @@
|
||||
|
||||
|
||||
/**
|
||||
* \defgroup IterativeLinearSolvers_Module Iterative solvers module
|
||||
* \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
|
||||
* This module aims to provide various iterative linear and non linear solver algorithms.
|
||||
* It currently provides:
|
||||
* - a constrained conjugate gradient
|
||||
|
||||
@@ -299,6 +299,7 @@ namespace Eigen
|
||||
|
||||
#define EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(AXES, SCALAR_TYPE, SCALAR_POSTFIX) \
|
||||
/** \ingroup EulerAngles_Module */ \
|
||||
/** \brief \noop */ \
|
||||
typedef EulerAngles<SCALAR_TYPE, EulerSystem##AXES> EulerAngles##AXES##SCALAR_POSTFIX;
|
||||
|
||||
#define EIGEN_EULER_ANGLES_TYPEDEFS(SCALAR_TYPE, SCALAR_POSTFIX) \
|
||||
|
||||
@@ -284,6 +284,7 @@ namespace Eigen
|
||||
|
||||
#define EIGEN_EULER_SYSTEM_TYPEDEF(A, B, C) \
|
||||
/** \ingroup EulerAngles_Module */ \
|
||||
/** \brief \noop */ \
|
||||
typedef EulerSystem<EULER_##A, EULER_##B, EULER_##C> EulerSystem##A##B##C;
|
||||
|
||||
EIGEN_EULER_SYSTEM_TYPEDEF(X,Y,Z)
|
||||
|
||||
@@ -13,7 +13,7 @@
|
||||
namespace Eigen {
|
||||
|
||||
/**
|
||||
* \ingroup IterativeSolvers_Module
|
||||
* \ingroup IterativeLinearSolvers_Module
|
||||
* \brief iterative scaling algorithm to equilibrate rows and column norms in matrices
|
||||
*
|
||||
* This class can be used as a preprocessing tool to accelerate the convergence of iterative methods
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
/// \brief Namespace containing all symbols from the %Eigen library.
|
||||
namespace Eigen {
|
||||
|
||||
/** \mainpage %Eigen's unsupported modules
|
||||
/** \mainpage notitle
|
||||
|
||||
This is the API documentation for %Eigen's unsupported modules.
|
||||
|
||||
|
||||
@@ -1,66 +1,103 @@
|
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add_custom_target(unsupported_examples)
|
||||
|
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include_directories(../../../unsupported ../../../unsupported/test)
|
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|
||||
foreach(example_src ${examples_SRCS})
|
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get_filename_component(example ${example_src} NAME_WE)
|
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add_executable(example_${example} ${example_src})
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if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO)
|
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target_link_libraries(example_${example} ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO})
|
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endif()
|
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target_link_libraries(example_${example} Eigen3::Eigen)
|
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add_custom_command(
|
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TARGET example_${example}
|
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POST_BUILD
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@@ -2,16 +2,11 @@ FILE(GLOB examples_SRCS "*.cpp")
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set(EIGEN_SYCL ON)
|
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list(APPEND CMAKE_EXE_LINKER_FLAGS -pthread)
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if(EIGEN_SYCL_TRISYCL)
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else(EIGEN_SYCL_TRISYCL)
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set(CMAKE_CXX_STANDARD 17)
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if(EIGEN_SYCL_ComputeCpp)
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||||
if(MSVC)
|
||||
# Set the host and device compilers C++ standard to C++14. On Windows setting this to C++11
|
||||
# can cause issues with the ComputeCpp device compiler parsing Visual Studio Headers.
|
||||
set(CMAKE_CXX_STANDARD 14)
|
||||
list(APPEND COMPUTECPP_USER_FLAGS -DWIN32)
|
||||
else()
|
||||
set(CMAKE_CXX_STANDARD 11)
|
||||
list(APPEND COMPUTECPP_USER_FLAGS -Wall)
|
||||
endif()
|
||||
# The following flags are not supported by Clang and can cause warnings
|
||||
@@ -20,14 +15,13 @@ else(EIGEN_SYCL_TRISYCL)
|
||||
set(CMAKE_CXX_COMPILER ${ComputeCpp_DEVICE_COMPILER_EXECUTABLE})
|
||||
string(REPLACE "-Wlogical-op" "" CMAKE_CXX_FLAGS ${CMAKE_CXX_FLAGS})
|
||||
string(REPLACE "-Wno-psabi" "" CMAKE_CXX_FLAGS ${CMAKE_CXX_FLAGS})
|
||||
string(REPLACE "-ansi" "" CMAKE_CXX_FLAGS ${CMAKE_CXX_FLAGS})
|
||||
endif()
|
||||
list(APPEND COMPUTECPP_USER_FLAGS
|
||||
-DEIGEN_NO_ASSERTION_CHECKING=1
|
||||
-no-serial-memop
|
||||
-Xclang
|
||||
-cl-mad-enable)
|
||||
endif(EIGEN_SYCL_TRISYCL)
|
||||
endif(EIGEN_SYCL_ComputeCpp)
|
||||
|
||||
FOREACH(example_src ${examples_SRCS})
|
||||
GET_FILENAME_COMPONENT(example ${example_src} NAME_WE)
|
||||
|
||||
Reference in New Issue
Block a user