Reshape dpctl impl (#957)

* call reshape from dpctl

* reshape in non-skipped tests

* use dpctl.tensor.reshape

Author: Alexander-Makaryev

dpnp/dpnp_algo/dpnp_algo.pyx

@@ -40,6 +40,7 @@ import dpnp.dpnp_utils as utils_py
 from dpnp.dpnp_container import container_copy
 
 import numpy
+import dpctl
 
 cimport cpython
 cimport dpnp.dpnp_utils as utils

dpnp/dpnp_algo/dpnp_algo_indexing.pyx

@@ -407,7 +407,7 @@ cpdef object dpnp_take_along_axis(object arr, object indices, int axis):
                 result_array[result_offset] = arr_elem
 
         dpnp_array = dpnp.array(result_array, dtype=res_type)
-        dpnp_result_array = dpnp_array.reshape(res_shape)
+        dpnp_result_array = dpnp.reshape(dpnp_array, res_shape)
         return dpnp_result_array
 
     else:

dpnp/dpnp_algo/dpnp_algo_manipulation.pyx

@@ -40,6 +40,7 @@ __all__ += [
     "dpnp_copyto",
     "dpnp_expand_dims",
     "dpnp_repeat",
+    "dpnp_reshape",
     "dpnp_transpose",
     "dpnp_squeeze",
 ]
@@ -125,7 +126,7 @@ cpdef utils.dpnp_descriptor dpnp_expand_dims(utils.dpnp_descriptor in_array, axi
             shape_list.push_back(in_array.shape[axis_idx])
             axis_idx = axis_idx + 1
 
-    cdef utils.dpnp_descriptor result = dpnp.get_dpnp_descriptor(dpnp_copy(in_array).get_pyobj().reshape(shape_list))
+    cdef utils.dpnp_descriptor result = dpnp.get_dpnp_descriptor(dpnp.reshape(dpnp_copy(in_array).get_pyobj(), (shape_list)))
 
     return result
 
@@ -145,6 +146,11 @@ cpdef utils.dpnp_descriptor dpnp_repeat(utils.dpnp_descriptor array1, repeats, a
     return result
 
 
+cpdef utils.dpnp_descriptor dpnp_reshape(utils.dpnp_descriptor array1, newshape, order=None):
+    # return dpnp.get_dpnp_descriptor(dpctl.tensor.usm_ndarray(newshape, dtype=numpy.dtype(array1.dtype).name, buffer=array1.get_pyobj()))
+    return dpnp.get_dpnp_descriptor(dpctl.tensor.reshape(array1.get_pyobj(), newshape))
+
+
 cpdef utils.dpnp_descriptor dpnp_transpose(utils.dpnp_descriptor array1, axes=None):
     cdef shape_type_c input_shape = array1.shape
     cdef size_t input_shape_size = array1.ndim
@@ -203,6 +209,6 @@ cpdef utils.dpnp_descriptor dpnp_squeeze(utils.dpnp_descriptor in_array, axis):
             else:
                 shape_list.push_back(in_array.shape[i])
 
-    cdef utils.dpnp_descriptor result = dpnp.get_dpnp_descriptor(dpnp_copy(in_array).get_pyobj().reshape(shape_list))
+    cdef utils.dpnp_descriptor result = dpnp.get_dpnp_descriptor(dpnp.reshape(dpnp_copy(in_array).get_pyobj(), (shape_list)))
 
     return result

dpnp/dpnp_algo/dpnp_algo_mathematical.pyx

@@ -202,7 +202,7 @@ cpdef object dpnp_diff(utils.dpnp_descriptor input, int n):
                     counter = 0
 
             dpnp_array = dpnp.array(res, dtype=input.dtype)
-            arr = dpnp_array.reshape(output_shape)
+            arr = dpnp.reshape(dpnp_array, output_shape)
         return arr
     else:
         return dpnp.array([], dtype=input.dtype)

dpnp/dpnp_algo/dpnp_algo_statistics.pyx

@@ -326,7 +326,7 @@ cpdef object dpnp_mean(utils.dpnp_descriptor input, axis):
             if i not in axis_:
                 del_ = del_ / shape_input[i]
     dpnp_array = dpnp.array(result_array, dtype=input.dtype)
-    dpnp_result_array = dpnp_array.reshape(output_shape)
+    dpnp_result_array = dpnp.reshape(dpnp_array, output_shape)
     return dpnp_result_array / del_
 
 

dpnp/dpnp_iface_manipulation.py

@@ -62,6 +62,7 @@
     "moveaxis",
     "ravel",
     "repeat",
+    "reshape",
     "rollaxis",
     "squeeze",
     "stack",
@@ -465,6 +466,28 @@ def repeat(x1, repeats, axis=None):
     return call_origin(numpy.repeat, x1, repeats, axis)
 
 
+def reshape(x1, newshape, order='C'):
+    """
+    Gives a new shape to an array without changing its data.
+
+    For full documentation refer to :obj:`numpy.reshape`.
+
+    Limitations
+    -----------
+    Only 'C' order is supported.
+
+    """
+
+    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    if x1_desc:
+        if order != 'C':
+            pass
+        else:
+            return dpnp_reshape(x1_desc, newshape, order).get_pyobj()
+
+    return call_origin(numpy.reshape, x1, newshape, order)
+
+
 def rollaxis(x1, axis, start=0):
     """
     Roll the specified axis backwards, until it lies in a given position.

dpnp/linalg/dpnp_algo_linalg.pyx

@@ -250,14 +250,14 @@ cpdef object dpnp_norm(object input, ord=None, axis=None):
             for i in range(absx_size):
                 absx_elem = absx.item(i)
                 absx_power[i] = absx_elem ** ord
-            absx_ = absx_power.reshape(absx.shape)
+            absx_ = dpnp.reshape(absx_power, absx.shape)
             ret = dpnp.sum(absx_, axis=axis)
             ret_size = ret.size
             ret_power = utils_py.create_output_descriptor_py((ret_size,), None, None).get_pyobj()
             for i in range(ret_size):
                 ret_elem = ret.item(i)
                 ret_power[i] = ret_elem ** (1 / ord)
-            ret_ = ret_power.reshape(ret.shape)
+            ret_ = dpnp.reshape(ret_power, ret.shape)
             return ret_
     elif len_axis == 2:
         row_axis, col_axis = axis_

examples/example1.py

@@ -52,8 +52,8 @@
 
 
 def run_dgemm(executor, name, size, test_type, repetition):
-    x1 = executor.arange(size * size, dtype=test_type).reshape((size, size))
-    x2 = executor.arange(size * size, dtype=test_type).reshape((size, size))
+    x1 = executor.reshape(executor.arange(size * size, dtype=test_type), (size, size))
+    x2 = executor.reshape(executor.arange(size * size, dtype=test_type), (size, size))
 
     times = []
     for iteration in range(repetition):

examples/example10.py

@@ -47,7 +47,7 @@
 
 
 def run(executor, size, test_type, repetition):
-    x = executor.arange(size * size, dtype=test_type).reshape((size, size))
+    x = executor.reshape(executor.arange(size * size, dtype=test_type), (size, size))
 
     times = []
     for _ in range(repetition):

examples/example7.py

@@ -52,7 +52,7 @@
 
 
 def run_function(executor, name, size, test_type, repetition):
-    x = executor.arange(size * size, dtype=test_type).reshape((size, size))
+    x = executor.reshape(executor.arange(size * size, dtype=test_type), (size, size))
 
     times = []
     for iteration in range(repetition):