Update dpnp.geomspace and dpnp.logspace functions

dpnp/dpnp_algo/dpnp_algo_arraycreation.pxi

@@ -38,9 +38,6 @@ and the rest of the library
 __all__ += [
     "dpnp_copy",
     "dpnp_diag",
-    "dpnp_geomspace",
-    "dpnp_linspace",
-    "dpnp_logspace",
     "dpnp_ptp",
     "dpnp_trace",
     "dpnp_vander",
@@ -138,116 +135,6 @@ cpdef utils.dpnp_descriptor dpnp_diag(utils.dpnp_descriptor v, int k):
     return result
 
 
-cpdef utils.dpnp_descriptor dpnp_geomspace(start, stop, num, endpoint, dtype, axis):
-    cdef shape_type_c obj_shape = utils._object_to_tuple(num)
-    cdef utils.dpnp_descriptor result = utils_py.create_output_descriptor_py(obj_shape, dtype, None)
-
-    if endpoint:
-        steps_count = num - 1
-    else:
-        steps_count = num
-
-    # if there are steps, then fill values
-    if steps_count > 0:
-        step = dpnp.power(dpnp.float64(stop) / start, 1.0 / steps_count)
-        mult = step
-        for i in range(1, result.size):
-            result.get_pyobj()[i] = start * mult
-            mult = mult * step
-    else:
-        step = dpnp.nan
-
-    # if result is not empty, then fiil first and last elements
-    if num > 0:
-        result.get_pyobj()[0] = start
-        if endpoint and result.size > 1:
-            result.get_pyobj()[result.size - 1] = stop
-
-    return result
-
-
-def dpnp_linspace(start, stop, num, dtype=None, device=None, usm_type=None, sycl_queue=None, endpoint=True, retstep=False, axis=0):
-    usm_type_alloc, sycl_queue_alloc = utils_py.get_usm_allocations([start, stop])
-
-    # Get sycl_queue.
-    if sycl_queue is None and device is None:
-        sycl_queue = sycl_queue_alloc
-    sycl_queue_normalized = dpnp.get_normalized_queue_device(sycl_queue=sycl_queue, device=device)
-
-    # Get temporary usm_type for getting dtype.
-    if usm_type is None:
-        _usm_type = "device" if usm_type_alloc is None else usm_type_alloc
-    else:
-        _usm_type = usm_type
-
-    # Get dtype.
-    if not hasattr(start, "dtype") and not dpnp.isscalar(start):
-        start = dpnp.asarray(start, usm_type=_usm_type, sycl_queue=sycl_queue_normalized)
-    if not hasattr(stop, "dtype") and not dpnp.isscalar(stop):
-        stop = dpnp.asarray(stop, usm_type=_usm_type, sycl_queue=sycl_queue_normalized)
-    dt = numpy.result_type(start, stop, float(num))
-    dt = utils_py.map_dtype_to_device(dt, sycl_queue_normalized.sycl_device)
-    if dtype is None:
-        dtype = dt
-
-    if dpnp.isscalar(start) and dpnp.isscalar(stop):
-        # Call linspace() function for scalars.
-        res = dpnp_container.linspace(start,
-                                      stop,
-                                      num,
-                                      dtype=dt,
-                                      usm_type=_usm_type,
-                                      sycl_queue=sycl_queue_normalized,
-                                      endpoint=endpoint)
-    else:
-        num = operator.index(num)
-        if num < 0:
-            raise ValueError("Number of points must be non-negative")
-
-        # Get final usm_type and copy arrays if needed with current dtype, usm_type and sycl_queue.
-        # Do not need to copy usm_ndarray by usm_type if it is not explicitly stated.
-        if usm_type is None:
-            usm_type = _usm_type
-            if not hasattr(start, "usm_type"):
-                _start = dpnp.asarray(start, dtype=dt, usm_type=usm_type, sycl_queue=sycl_queue_normalized)
-            else:
-                _start = dpnp.asarray(start, dtype=dt, sycl_queue=sycl_queue_normalized)
-            if not hasattr(stop, "usm_type"):
-                _stop = dpnp.asarray(stop, dtype=dt, usm_type=usm_type, sycl_queue=sycl_queue_normalized)
-            else:
-                _stop = dpnp.asarray(stop, dtype=dt, sycl_queue=sycl_queue_normalized)
-        else:
-            _start = dpnp.asarray(start, dtype=dt, usm_type=usm_type, sycl_queue=sycl_queue_normalized)
-            _stop = dpnp.asarray(stop, dtype=dt, usm_type=usm_type, sycl_queue=sycl_queue_normalized)
-
-        # FIXME: issue #1304. Mathematical operations with scalar don't follow data type.
-        _num = dpnp.asarray((num - 1) if endpoint else num, dtype=dt, usm_type=usm_type, sycl_queue=sycl_queue_normalized)
-
-        step = (_stop - _start) / _num
-
-        res = dpnp_container.arange(0,
-                                    stop=num,
-                                    step=1,
-                                    dtype=dt,
-                                    usm_type=usm_type,
-                                    sycl_queue=sycl_queue_normalized)
-
-        res = res.reshape((-1,) + (1,) * step.ndim)
-        res = res * step + _start
-
-        if endpoint and num > 1:
-            res[-1] = dpnp_container.full(step.shape, _stop)
-
-    if numpy.issubdtype(dtype, dpnp.integer):
-        dpnp.floor(res, out=res)
-    return res.astype(dtype)
-
-
-cpdef utils.dpnp_descriptor dpnp_logspace(start, stop, num, endpoint, base, dtype, axis):
-    temp = dpnp.linspace(start, stop, num=num, endpoint=endpoint)
-    return dpnp.get_dpnp_descriptor(dpnp.astype(dpnp.power(base, temp), dtype))
-
-
 cpdef dpnp_ptp(utils.dpnp_descriptor arr, axis=None):
     cdef shape_type_c shape_arr = arr.shape
     cdef shape_type_c output_shape