Reshape dpctl impl (#957)

Alexander-Makaryev · web-flow · commit 03c11855e665 · 2021-09-23T17:54:44.000+03:00
* call reshape from dpctl

* reshape in non-skipped tests

* use dpctl.tensor.reshape
diff --git a/dpnp/dpnp_algo/dpnp_algo.pyx b/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
diff --git a/dpnp/dpnp_algo/dpnp_algo_indexing.pyx b/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:
diff --git a/dpnp/dpnp_algo/dpnp_algo_manipulation.pyx b/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
diff --git a/dpnp/dpnp_algo/dpnp_algo_mathematical.pyx b/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)
diff --git a/dpnp/dpnp_algo/dpnp_algo_statistics.pyx b/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_
 
 
diff --git a/dpnp/dpnp_iface_manipulation.py b/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.
diff --git a/dpnp/linalg/dpnp_algo_linalg.pyx b/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_
diff --git a/examples/example1.py b/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):
diff --git a/examples/example10.py b/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):
diff --git a/examples/example7.py b/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):
diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
@@ -73,15 +73,15 @@ def test_concatenate(self):
         # Arrays much match shape
         numpy.testing.assert_raises(ValueError, dpnp.concatenate, (a23.T, a13.T), 0)
         # 3D
-        res = dpnp.arange(2 * 3 * 7).reshape((2, 3, 7))
+        res = dpnp.reshape(dpnp.arange(2 * 3 * 7), (2, 3, 7))
         a0 = res[..., :4]
         a1 = res[..., 4:6]
         a2 = res[..., 6:]
         numpy.testing.assert_array_equal(dpnp.concatenate((a0, a1, a2), 2), res)
         numpy.testing.assert_array_equal(dpnp.concatenate((a0, a1, a2), -1), res)
         numpy.testing.assert_array_equal(dpnp.concatenate((a0.T, a1.T, a2.T), 0), res.T)
 
-        out = res.copy()
+        out = dpnp.copy(res)
         rout = dpnp.concatenate((a0, a1, a2), 2, out=out)
         numpy.testing.assert_(out is rout)
         numpy.testing.assert_equal(res, rout)
diff --git a/tests/test_dot.py b/tests/test_dot.py
@@ -41,10 +41,10 @@ def test_dot_arange(type):
                          ids=['float64', 'float32', 'int64', 'int32'])
 def test_multi_dot(type):
     n = 16
-    a = inp.arange(n, dtype=type).reshape((4, 4))
-    b = inp.arange(n, dtype=type).reshape((4, 4))
-    c = inp.arange(n, dtype=type).reshape((4, 4))
-    d = inp.arange(n, dtype=type).reshape((4, 4))
+    a = inp.reshape(inp.arange(n, dtype=type), (4, 4))
+    b = inp.reshape(inp.arange(n, dtype=type), (4, 4))
+    c = inp.reshape(inp.arange(n, dtype=type), (4, 4))
+    d = inp.reshape(inp.arange(n, dtype=type), (4, 4))
 
     a1 = numpy.arange(n, dtype=type).reshape((4, 4))
     b1 = numpy.arange(n, dtype=type).reshape((4, 4))
diff --git a/tests/test_mixins.py b/tests/test_mixins.py
@@ -12,8 +12,8 @@ def test_matmul(self):
         size = 2
 
         # DPNP
-        array1 = inp.array(array_data, dtype=inp.float64).reshape((size, size))
-        array2 = inp.array(array_data, dtype=inp.float64).reshape((size, size))
+        array1 = inp.reshape(inp.array(array_data, dtype=inp.float64), (size, size))
+        array2 = inp.reshape(inp.array(array_data, dtype=inp.float64), (size, size))
         result = inp.matmul(array1, array2)
         # print(result)
 
@@ -33,8 +33,8 @@ def test_matmul2(self):
         array_data2 = [1., 2., 3., 4., 5., 6., 7., 8.]
 
         # DPNP
-        array1 = inp.array(array_data1, dtype=inp.float64).reshape((3, 2))
-        array2 = inp.array(array_data2, dtype=inp.float64).reshape((2, 4))
+        array1 = inp.reshape(inp.array(array_data1, dtype=inp.float64), (3, 2))
+        array2 = inp.reshape(inp.array(array_data2, dtype=inp.float64), (2, 4))
         result = inp.matmul(array1, array2)
         # print(result)
 
diff --git a/tests/test_umath.py b/tests/test_umath.py
@@ -34,7 +34,7 @@ def shaped_arange(shape, xp=numpy, dtype=numpy.float32):
     for i in shape:
         size = size * i
     array_data = numpy.arange(1, size + 1, 1).tolist()
-    return xp.array(array_data, dtype=dtype).reshape(shape)
+    return xp.reshape(xp.array(array_data, dtype=dtype), shape)
 
 
 def get_args(args_str, xp=numpy):
