Remove data synchronize where possible

dpnp/dpnp_algo/dpnp_elementwise_common.py

@@ -179,7 +179,6 @@ def __call__(
         out_usm = None if out is None else dpnp.get_usm_ndarray(out)
         res_usm = super().__call__(x_usm, out=out_usm, order=order)
 
-        dpnp.synchronize_array_data(res_usm)
         if out is not None and isinstance(out, dpnp_array):
             return out
         return dpnp_array._create_from_usm_ndarray(res_usm)
@@ -352,7 +351,6 @@ def __call__(
         out_usm = None if out is None else dpnp.get_usm_ndarray(out)
         res_usm = super().__call__(x1_usm, x2_usm, out=out_usm, order=order)
 
-        dpnp.synchronize_array_data(res_usm)
         if out is not None and isinstance(out, dpnp_array):
             return out
         return dpnp_array._create_from_usm_ndarray(res_usm)
@@ -540,7 +538,6 @@ def __call__(self, x, decimals=0, out=None, dtype=None):
             if dtype is not None:
                 res_usm = dpt.astype(res_usm, dtype, copy=False)
 
-            dpnp.synchronize_array_data(res_usm)
             if out is not None and isinstance(out, dpnp_array):
                 return out
             return dpnp_array._create_from_usm_ndarray(res_usm)

dpnp/dpnp_array.py

@@ -257,9 +257,6 @@ def __getitem__(self, key):
 
         res = self.__new__(dpnp_array)
         res._array_obj = item
-
-        if self._array_obj.usm_data is not res._array_obj.usm_data:
-            dpnp.synchronize_array_data(self)
         return res
 
     def __gt__(self, other):
@@ -456,7 +453,6 @@ def __setitem__(self, key, val):
             val = val.get_array()
 
         self._array_obj.__setitem__(key, val)
-        dpnp.synchronize_array_data(self)
 
     # '__setstate__',
     # '__sizeof__',

dpnp/dpnp_container.py

@@ -80,7 +80,6 @@ def arange(
         sycl_queue=sycl_queue_normalized,
     )
 
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj)
 
 
@@ -133,7 +132,6 @@ def asarray(
         if array_obj is x1_obj and isinstance(x1, dpnp_array):
             return x1
 
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order=order)
 
 
@@ -143,7 +141,6 @@ def copy(x1, /, *, order="K"):
         order = "K"
 
     array_obj = dpt.copy(dpnp.get_usm_ndarray(x1), order=order)
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order="K")
 
 
@@ -205,7 +202,6 @@ def eye(
         usm_type=usm_type,
         sycl_queue=sycl_queue_normalized,
     )
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order=order)
 
 
@@ -240,7 +236,6 @@ def full(
         usm_type=usm_type,
         sycl_queue=sycl_queue_normalized,
     )
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order=order)
 
 
@@ -269,21 +264,18 @@ def ones(
         usm_type=usm_type,
         sycl_queue=sycl_queue_normalized,
     )
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order=order)
 
 
 def tril(x1, /, *, k=0):
     """Creates `dpnp_array` as lower triangular part of an input array."""
     array_obj = dpt.tril(dpnp.get_usm_ndarray(x1), k=k)
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order="K")
 
 
 def triu(x1, /, *, k=0):
     """Creates `dpnp_array` as upper triangular part of an input array."""
     array_obj = dpt.triu(dpnp.get_usm_ndarray(x1), k=k)
-    dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order="K")
 
 
@@ -312,6 +304,4 @@ def zeros(
         usm_type=usm_type,
         sycl_queue=sycl_queue_normalized,
     )
-    # TODO: uncomment once dpctl implements asynchronous call
-    # dpnp.synchronize_array_data(array_obj)
     return dpnp_array(array_obj.shape, buffer=array_obj, order=order)

dpnp/dpnp_iface.py

@@ -284,7 +284,6 @@ def astype(x1, dtype, order="K", casting="unsafe", copy=True, device=None):
         x1_obj, dtype, order=order, casting=casting, copy=copy, device=device
     )
 
-    dpnp.synchronize_array_data(x1)
     if array_obj is x1_obj and isinstance(x1, dpnp_array):
         # return x1 if dpctl returns a zero copy of x1_obj
         return x1
@@ -797,6 +796,5 @@ def synchronize_array_data(a):
 
     """
 
-    if hasattr(dpu, "SequentialOrderManager"):
-        check_supported_arrays_type(a)
-        dpu.SequentialOrderManager[a.sycl_queue].wait()
+    check_supported_arrays_type(a)
+    dpu.SequentialOrderManager[a.sycl_queue].wait()

dpnp/dpnp_iface_arraycreation.py

@@ -2188,7 +2188,7 @@ def geomspace(
 
     """
 
-    res = dpnp_geomspace(
+    return dpnp_geomspace(
         start,
         stop,
         num,
@@ -2200,9 +2200,6 @@ def geomspace(
         axis=axis,
     )
 
-    dpnp.synchronize_array_data(res)
-    return res
-
 
 def identity(
     n,
@@ -2410,7 +2407,7 @@ def linspace(
 
     """
 
-    res = dpnp_linspace(
+    return dpnp_linspace(
         start,
         stop,
         num,
@@ -2423,12 +2420,6 @@ def linspace(
         axis=axis,
     )
 
-    if isinstance(res, tuple):  # (result, step) is returning
-        dpnp.synchronize_array_data(res[0])
-    else:
-        dpnp.synchronize_array_data(res)
-    return res
-
 
 def loadtxt(
     fname,
@@ -2643,7 +2634,7 @@ def logspace(
 
     """
 
-    res = dpnp_logspace(
+    return dpnp_logspace(
         start,
         stop,
         num=num,
@@ -2656,9 +2647,6 @@ def logspace(
         axis=axis,
     )
 
-    dpnp.synchronize_array_data(res)
-    return res
-
 
 # pylint: disable=redefined-outer-name
 def meshgrid(*xi, copy=True, sparse=False, indexing="xy"):
@@ -2759,9 +2747,7 @@ def meshgrid(*xi, copy=True, sparse=False, indexing="xy"):
     if copy:
         output = [dpt.copy(x) for x in output]
 
-    dpnp.synchronize_array_data(output[0])
-    output = [dpnp_array._create_from_usm_ndarray(x) for x in output]
-    return output
+    return [dpnp_array._create_from_usm_ndarray(x) for x in output]
 
 
 class MGridClass:

dpnp/dpnp_iface_histograms.py

@@ -40,17 +40,11 @@
 import operator
 import warnings
 
-import dpctl.tensor as dpt
 import dpctl.utils as dpu
 import numpy
 
 import dpnp
 
-from .dpnp_algo.dpnp_arraycreation import (
-    dpnp_linspace,
-)
-from .dpnp_array import dpnp_array
-
 __all__ = [
     "digitize",
     "histogram",
@@ -63,10 +57,14 @@
 
 
 def _ravel_check_a_and_weights(a, weights):
-    """Check input `a` and `weights` arrays, and ravel both."""
+    """
+    Check input `a` and `weights` arrays, and ravel both.
+    The returned array have :class:`dpnp.ndarray` type always.
+
+    """
 
     # ensure that `a` array has supported type
-    a = dpnp.get_usm_ndarray(a)
+    dpnp.check_supported_arrays_type(a)
     usm_type = a.usm_type
 
     # ensure that the array is a "subtractable" dtype
@@ -77,11 +75,11 @@ def _ravel_check_a_and_weights(a, weights):
             RuntimeWarning,
             stacklevel=3,
         )
-        a = dpt.astype(a, numpy.uint8)
+        a = dpnp.astype(a, numpy.uint8)
 
     if weights is not None:
         # check that `weights` array has supported type
-        weights = dpnp.get_usm_ndarray(weights)
+        dpnp.check_supported_arrays_type(weights)
         usm_type = dpu.get_coerced_usm_type([usm_type, weights.usm_type])
 
         # check that arrays have the same allocation queue
@@ -92,9 +90,9 @@ def _ravel_check_a_and_weights(a, weights):
 
         if weights.shape != a.shape:
             raise ValueError("weights should have the same shape as a.")
-        weights = dpt.reshape(weights, -1)
+        weights = dpnp.ravel(weights)
 
-    a = dpt.reshape(a, -1)
+    a = dpnp.ravel(a)
     return a, weights, usm_type
 
 
@@ -120,7 +118,7 @@ def _get_outer_edges(a, range):
         first_edge, last_edge = 0, 1
 
     else:
-        first_edge, last_edge = dpt.min(a), dpt.max(a)
+        first_edge, last_edge = a.min(), a.max()
         if not (dpnp.isfinite(first_edge) and dpnp.isfinite(last_edge)):
             raise ValueError(
                 f"autodetected range of [{first_edge}, {last_edge}] "
@@ -164,9 +162,11 @@ def _get_bin_edges(a, bins, range, usm_type):
                     "a and bins must be allocated on the same SYCL queue"
                 )
 
-        bin_edges = dpnp.as_usm_ndarray(
-            bins, usm_type=usm_type, sycl_queue=sycl_queue
-        )
+            bin_edges = bins
+        else:
+            bin_edges = dpnp.asarray(
+                bins, sycl_queue=sycl_queue, usm_type=usm_type
+            )
 
         if dpnp.any(bin_edges[:-1] > bin_edges[1:]):
             raise ValueError(
@@ -188,15 +188,15 @@ def _get_bin_edges(a, bins, range, usm_type):
             )
 
         # bin edges must be computed
-        bin_edges = dpnp_linspace(
+        bin_edges = dpnp.linspace(
             first_edge,
             last_edge,
             n_equal_bins + 1,
             endpoint=True,
             dtype=bin_type,
             sycl_queue=sycl_queue,
             usm_type=usm_type,
-        ).get_array()
+        )
         return bin_edges, (first_edge, last_edge, n_equal_bins)
     return bin_edges, None
 
@@ -209,11 +209,8 @@ def _search_sorted_inclusive(a, v):
 
     """
 
-    return dpt.concat(
-        (
-            dpt.searchsorted(a, v[:-1], side="left"),
-            dpt.searchsorted(a, v[-1:], side="right"),
-        )
+    return dpnp.concatenate(
+        (a.searchsorted(v[:-1], "left"), a.searchsorted(v[-1:], "right"))
     )
 
 
@@ -305,14 +302,8 @@ def digitize(x, bins, right=False):
         # Use dpnp.searchsorted directly if bins are increasing
         return dpnp.searchsorted(bins, x, side=side)
 
-    usm_x = dpnp.get_usm_ndarray(x)
-    usm_bins = dpnp.get_usm_ndarray(bins)
-
     # Reverse bins and adjust indices if bins are decreasing
-    usm_res = usm_bins.size - dpt.searchsorted(usm_bins[::-1], usm_x, side=side)
-
-    dpnp.synchronize_array_data(usm_res)
-    return dpnp_array._create_from_usm_ndarray(usm_res)
+    return bins.size - dpnp.searchsorted(bins[::-1], x, side=side)
 
 
 def histogram(a, bins=10, range=None, density=None, weights=None):
@@ -426,36 +417,26 @@ def histogram(a, bins=10, range=None, density=None, weights=None):
     else:
         # Compute via cumulative histogram
         if weights is None:
-            sa = dpt.sort(a)
+            sa = dpnp.sort(a)
             cum_n = _search_sorted_inclusive(sa, bin_edges)
         else:
-            zero = dpt.zeros(
+            zero = dpnp.zeros(
                 1, dtype=ntype, sycl_queue=a.sycl_queue, usm_type=usm_type
             )
-            sorting_index = dpt.argsort(a)
+            sorting_index = dpnp.argsort(a)
             sa = a[sorting_index]
             sw = weights[sorting_index]
-            cw = dpt.concat((zero, dpt.cumulative_sum(sw, dtype=ntype)))
+            cw = dpnp.concatenate((zero, sw.cumsum(dtype=ntype)))
             bin_index = _search_sorted_inclusive(sa, bin_edges)
             cum_n = cw[bin_index]
 
         n = dpnp.diff(cum_n)
 
-    # convert bin_edges to dpnp.ndarray
-    bin_edges = dpnp_array._create_from_usm_ndarray(bin_edges)
-
     if density:
         # pylint: disable=possibly-used-before-assignment
-        db = dpnp.diff(bin_edges)
-        db = dpt.astype(db.get_array(), dpnp.default_float_type())
+        db = dpnp.diff(bin_edges).astype(dpnp.default_float_type())
+        return n / db / n.sum(), bin_edges
 
-        usm_n = n.get_array()
-        hist = usm_n / db / dpt.sum(usm_n)
-
-        dpnp.synchronize_array_data(hist)
-        return dpnp_array._create_from_usm_ndarray(hist), bin_edges
-
-    dpnp.synchronize_array_data(n)
     return n, bin_edges
 
 
@@ -541,6 +522,4 @@ def histogram_bin_edges(a, bins=10, range=None, weights=None):
 
     a, weights, usm_type = _ravel_check_a_and_weights(a, weights)
     bin_edges, _ = _get_bin_edges(a, bins, range, usm_type)
-
-    dpnp.synchronize_array_data(bin_edges)
-    return dpnp_array._create_from_usm_ndarray(bin_edges)
+    return bin_edges