implementation of dpnp.fft.rfft2, dpnp.fft.irfft2, dpnp.fft.rfftn, dpnp.fft.irfftn

dpnp/backend/extensions/fft/in_place.cpp

@@ -47,7 +47,7 @@ std::pair<sycl::event, sycl::event>
                          const bool is_forward,
                          const std::vector<sycl::event> &depends)
 {
-    bool committed = descr.is_committed();
+    const bool committed = descr.is_committed();
     if (!committed) {
         throw py::value_error("Descriptor is not committed");
     }

dpnp/backend/extensions/fft/out_of_place.cpp

@@ -49,7 +49,7 @@ std::pair<sycl::event, sycl::event>
                              const bool is_forward,
                              const std::vector<sycl::event> &depends)
 {
-    bool committed = descr.is_committed();
+    const bool committed = descr.is_committed();
     if (!committed) {
         throw py::value_error("Descriptor is not committed");
     }
@@ -93,8 +93,8 @@ std::pair<sycl::event, sycl::event>
     if (in_nd > 1) {
         for (int i = 0; i < in_nd - 1; ++i) {
             if (in_shape[i] != out_shape[i]) {
-                throw py::value_error("The shape of the input and output "
-                                      "arrays must be the same.");
+                throw py::value_error("The shape of the output array is not "
+                                      "correct for the given input array.");
             }
             in_size *= in_shape[i];
         }
@@ -105,17 +105,18 @@ std::pair<sycl::event, sycl::event>
         // r2c FFT
         N = m / 2 + 1; // integer divide
         if (n != N) {
-            throw py::value_error("The shape of the output array is not "
-                                  "correct for real to complex transform.");
+            throw py::value_error(
+                "The shape of the output array is not correct for the given "
+                "input array in real to complex FFT transform.");
         }
     }
     else {
         // c2c and c2r FFT. For c2r FFT, input is zero-padded in python side to
         // have the same size as output before calling this function
         N = m;
         if (n != N) {
-            throw py::value_error("The shape of the input array must be "
-                                  "the same as the shape of the output array.");
+            throw py::value_error("The shape of the output array is not "
+                                  "correct for the given input array.");
         }
     }
 

dpnp/dpnp_utils/dpnp_algo_utils.pxd

@@ -37,24 +37,12 @@ cpdef checker_throw_value_error(function_name, param_name, param, expected)
 """
 
 
-cpdef checker_throw_axis_error(function_name, param_name, param, expected)
-""" Throw exception AxisError if 'param' is not 'expected'
-
-"""
-
-
 cpdef checker_throw_type_error(function_name, given_type)
 """ Throw exception TypeError if 'given_type' type is not supported
 
 """
 
 
-cpdef checker_throw_index_error(function_name, index, size)
-""" Throw exception IndexError if 'index' is out of bounds
-
-"""
-
-
 cpdef cpp_bool use_origin_backend(input1=*, size_t compute_size=*)
 """
 This function needs to redirect particular computation cases to original backend
@@ -71,15 +59,6 @@ Return:
 cpdef tuple _object_to_tuple(object obj)
 cdef int _normalize_order(order, cpp_bool allow_k=*) except? 0
 
-cpdef shape_type_c normalize_axis(object axis, size_t shape_size)
-"""
-Conversion of the transformation shape axis [-1, 0, 1] into [2, 0, 1] where numbers are `id`s of array shape axis
-"""
-
-cpdef long _get_linear_index(key, tuple shape, int ndim)
-"""
-Compute linear index of an element in memory from array indices
-"""
 
 cpdef tuple get_axis_offsets(shape)
 """

dpnp/dpnp_utils/dpnp_algo_utils.pyx

@@ -59,18 +59,14 @@ Python import functions
 """
 __all__ = [
     "call_origin",
-    "checker_throw_axis_error",
-    "checker_throw_index_error",
     "checker_throw_type_error",
     "checker_throw_value_error",
     "create_output_descriptor_py",
     "convert_item",
     "dpnp_descriptor",
     "get_axis_offsets",
     "get_usm_allocations",
-    "_get_linear_index",
     "map_dtype_to_device",
-    "normalize_axis",
     "_object_to_tuple",
     "unwrap_array",
     "use_origin_backend"
@@ -308,17 +304,6 @@ def map_dtype_to_device(dtype, device):
     raise RuntimeError(f"Unrecognized type of input dtype={dtype}")
 
 
-cpdef checker_throw_axis_error(function_name, param_name, param, expected):
-    err_msg = f"{ERROR_PREFIX} in function {function_name}()"
-    err_msg += f" axes '{param_name}' expected `{expected}`, but '{param}' provided"
-    raise AxisError(err_msg)
-
-
-cpdef checker_throw_index_error(function_name, index, size):
-    raise IndexError(
-        f"{ERROR_PREFIX} in function {function_name}() index {index} is out of bounds. dimension size `{size}`")
-
-
 cpdef checker_throw_type_error(function_name, given_type):
     raise TypeError(f"{ERROR_PREFIX} in function {function_name}() type '{given_type}' is not supported")
 
@@ -364,22 +349,6 @@ cpdef tuple get_axis_offsets(shape):
     return _object_to_tuple(result)
 
 
-cpdef long _get_linear_index(key, tuple shape, int ndim):
-    """
-    Compute linear index of an element in memory from array indices
-    """
-
-    if isinstance(key, tuple):
-        li = 0
-        m = 1
-        for i in range(ndim - 1, -1, -1):
-            li += key[i] * m
-            m *= shape[i]
-    else:
-        li = key
-    return li
-
-
 cdef dpnp_descriptor create_output_descriptor(shape_type_c output_shape,
                                               DPNPFuncType c_type,
                                               dpnp_descriptor requested_out,
@@ -412,28 +381,6 @@ cdef dpnp_descriptor create_output_descriptor(shape_type_c output_shape,
     return result_desc
 
 
-cpdef shape_type_c normalize_axis(object axis_obj, size_t shape_size_inp):
-    """
-    Conversion of the transformation shape axis [-1, 0, 1] into [2, 0, 1] where numbers are `id`s of array shape axis
-    """
-
-    cdef shape_type_c axis = _object_to_tuple(axis_obj)  # axis_obj might be a scalar
-    cdef ssize_t shape_size = shape_size_inp  # convert type for comparison with axis id
-
-    cdef size_t axis_size = axis.size()
-    cdef shape_type_c result = shape_type_c(axis_size, 0)
-    for i in range(axis_size):
-        if (axis[i] >= shape_size) or (axis[i] < -shape_size):
-            checker_throw_axis_error("normalize_axis", "axis", axis[i], shape_size - 1)
-
-        if (axis[i] < 0):
-            result[i] = shape_size + axis[i]
-        else:
-            result[i] = axis[i]
-
-    return result
-
-
 @cython.profile(False)
 cdef inline int _normalize_order(order, cpp_bool allow_k=True) except? 0:
     """ Converts memory order letters to some common view