Rangify constructor of HostTensorDescriptor & Tensor<> (#445)

* Rangify STL algorithms

This commit adapts rangified std::copy(), std::fill() & std::transform()

* Rangify check_err()

By rangifying check_err(), we can not only compare values between
std::vector<>s, but also compare any ranges which have same value
type.

* Allow constructing Tensor<> like a HostTensorDescriptor

* Simplify Tensor<> object construction logics

* Remove more unnecessary 'HostTensorDescriptor' objects

* Re-format example code

* Re-write more HostTensorDescriptor ctor call

example/39_permute/common.hpp

@@ -19,6 +19,7 @@
 #include "ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp"
 #include "ck/utility/type.hpp"
 
+#include "ck/library/utility/algorithm.hpp"
 #include "ck/library/utility/check_err.hpp"
 #include "ck/library/utility/device_memory.hpp"
 #include "ck/library/utility/fill.hpp"
@@ -247,19 +248,6 @@ inline auto to_array(Range& range) noexcept
     return detail::to_array_proxy<ck::remove_cvref_t<Range>>{range};
 }
 
-namespace ranges {
-template <typename InputRange, typename OutputIterator>
-inline auto copy(InputRange&& range, OutputIterator iter)
-    -> decltype(std::copy(std::begin(std::forward<InputRange>(range)),
-                          std::end(std::forward<InputRange>(range)),
-                          iter))
-{
-    return std::copy(std::begin(std::forward<InputRange>(range)),
-                     std::end(std::forward<InputRange>(range)),
-                     iter);
-}
-} // namespace ranges
-
 template <typename Axes>
 inline auto is_valid_axes(const Axes& axes)
     -> std::enable_if_t<detail::is_random_access_range_v<Axes>, bool>
@@ -350,7 +338,7 @@ auto extend_shape(const Problem::Shape& shape, std::size_t new_dim)
 
     using std::begin, std::end;
 
-    std::copy(begin(shape), end(shape), begin(extended_shape));
+    ck::ranges::copy(shape, begin(extended_shape));
     extended_shape.back() = new_dim;
 
     return extended_shape;
@@ -362,7 +350,7 @@ auto extend_axes(const Problem::Axes& axes)
 
     using std::begin, std::end;
 
-    std::copy(begin(axes), end(axes), begin(extended_axes));
+    ck::ranges::copy(axes, begin(extended_axes));
     extended_axes.back() = detail::get_array_size_v<Problem::Axes>;
 
     return extended_axes;

example/39_permute/run_permute_bundle_example.inc

@@ -57,7 +57,7 @@ bool run_permute_bundle(const Problem& problem)
     using std::begin;
 
     Tensor<DataType> input_tensor(input_shape);
-    ranges::copy(input_bundle_tensor.AsSpan<const DataType>(), begin(input_tensor));
+    ck::ranges::copy(input_bundle_tensor.AsSpan<const DataType>(), begin(input_tensor));
 
     Tensor<DataType> output_tensor(transpose(input_shape, input_axes));
     if(!host_permute(input_tensor, input_axes, PassThrough{}, output_tensor))