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Update tests to run on Iris Xe #1498

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merged 5 commits into from
Jul 27, 2023
Merged

Update tests to run on Iris Xe #1498

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c88cfe4
Update tests to run on Iris Xe
npolina4 Jul 25, 2023
cf91bc4
Added more dtypes for minins tests and manipulation tests.
npolina4 Jul 27, 2023
bbeb3ce
Merge branch 'master' into iris_xe_test1
npolina4 Jul 27, 2023
815436c
Update test_mixins.py
npolina4 Jul 27, 2023
f510e16
Update test_mixins.py
npolina4 Jul 27, 2023
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12 changes: 12 additions & 0 deletions dpnp/backend/kernels/dpnp_krnl_random.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2988,9 +2988,13 @@ void func_map_init_random(func_map_t &fmap)

fmap[DPNPFuncName::DPNP_FN_RNG_CHISQUARE][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_chisquare_default_c<double>};
fmap[DPNPFuncName::DPNP_FN_RNG_CHISQUARE][eft_FLT][eft_FLT] = {
eft_FLT, (void *)dpnp_rng_chisquare_default_c<float>};

fmap[DPNPFuncName::DPNP_FN_RNG_CHISQUARE_EXT][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_chisquare_ext_c<double>};
fmap[DPNPFuncName::DPNP_FN_RNG_CHISQUARE_EXT][eft_FLT][eft_FLT] = {
eft_FLT, (void *)dpnp_rng_chisquare_ext_c<float>};

fmap[DPNPFuncName::DPNP_FN_RNG_EXPONENTIAL][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_exponential_default_c<double>};
Expand Down Expand Up @@ -3136,15 +3140,23 @@ void func_map_init_random(func_map_t &fmap)

fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_CAUCHY][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_standard_cauchy_default_c<double>};
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_CAUCHY][eft_FLT][eft_FLT] = {
eft_FLT, (void *)dpnp_rng_standard_cauchy_default_c<float>};

fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_CAUCHY_EXT][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_standard_cauchy_ext_c<double>};
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_CAUCHY_EXT][eft_FLT][eft_FLT] = {
eft_FLT, (void *)dpnp_rng_standard_cauchy_ext_c<float>};

fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_EXPONENTIAL][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_standard_exponential_default_c<double>};
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_EXPONENTIAL][eft_FLT][eft_FLT] = {
eft_FLT, (void *)dpnp_rng_standard_exponential_default_c<float>};

fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_EXPONENTIAL_EXT][eft_DBL][eft_DBL] =
{eft_DBL, (void *)dpnp_rng_standard_exponential_ext_c<double>};
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_EXPONENTIAL_EXT][eft_FLT][eft_FLT] =
{eft_FLT, (void *)dpnp_rng_standard_exponential_ext_c<float>};

fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_GAMMA][eft_DBL][eft_DBL] = {
eft_DBL, (void *)dpnp_rng_standard_gamma_default_c<double>};
Expand Down
9 changes: 5 additions & 4 deletions dpnp/random/dpnp_algo_random.pyx
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Expand Up @@ -96,7 +96,8 @@ ctypedef c_dpctl.DPCTLSyclEventRef(*fptr_dpnp_rng_beta_c_1out_t)(c_dpctl.DPCTLSy
const c_dpctl.DPCTLEventVectorRef) except +
ctypedef c_dpctl.DPCTLSyclEventRef(*fptr_dpnp_rng_binomial_c_1out_t)(c_dpctl.DPCTLSyclQueueRef,
void * ,
const int, const double,
const int,
const double,
const size_t,
const c_dpctl.DPCTLEventVectorRef) except +
ctypedef c_dpctl.DPCTLSyclEventRef(*fptr_dpnp_rng_chisquare_c_1out_t)(c_dpctl.DPCTLSyclQueueRef,
Expand Down Expand Up @@ -585,7 +586,7 @@ cpdef utils.dpnp_descriptor dpnp_rng_chisquare(int df, size):
"""

# convert string type names (array.dtype) to C enum DPNPFuncType
cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(dpnp.float64)
cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(dpnp.default_float_type())

# get the FPTR data structure
cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_RNG_CHISQUARE_EXT, param1_type, param1_type)
Expand Down Expand Up @@ -1329,7 +1330,7 @@ cpdef utils.dpnp_descriptor dpnp_rng_standard_cauchy(size):
"""

# convert string type names (array.dtype) to C enum DPNPFuncType
cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(dpnp.float64)
cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(dpnp.default_float_type())

# get the FPTR data structure
cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_RNG_STANDARD_CAUCHY_EXT, param1_type, param1_type)
Expand Down Expand Up @@ -1364,7 +1365,7 @@ cpdef utils.dpnp_descriptor dpnp_rng_standard_exponential(size):
cdef fptr_dpnp_rng_standard_exponential_c_1out_t func

# convert string type names (array.dtype) to C enum DPNPFuncType
cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(dpnp.float64)
cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(dpnp.default_float_type())

# get the FPTR data structure
cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_RNG_STANDARD_EXPONENTIAL_EXT, param1_type, param1_type)
Expand Down
6 changes: 3 additions & 3 deletions dpnp/random/dpnp_iface_random.py
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Expand Up @@ -230,7 +230,7 @@ def chisquare(df, size=None):
-----------
Parameter ``df`` is supported as a scalar.
Otherwise, :obj:`numpy.random.chisquare(df, size)` samples are drawn.
Output array data type is :obj:`dpnp.float64`.
Output array data type is default float type.

Examples
--------
Expand Down Expand Up @@ -1533,7 +1533,7 @@ def standard_cauchy(size=None):

Limitations
-----------
Output array data type is :obj:`dpnp.float64`.
Output array data type is default float type.

Examples
--------
Expand Down Expand Up @@ -1562,7 +1562,7 @@ def standard_exponential(size=None):

Limitations
-----------
Output array data type is :obj:`dpnp.float64`.
Output array data type is default float type.

Examples
--------
Expand Down
5 changes: 4 additions & 1 deletion tests/test_logic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@

import dpnp

from .helper import get_all_dtypes
from .helper import get_all_dtypes, has_support_aspect64


@pytest.mark.parametrize("type", get_all_dtypes())
Expand Down Expand Up @@ -40,6 +40,9 @@ def test_all(type, shape):
assert_allclose(dpnp_res, np_res)


@pytest.mark.skipif(
not has_support_aspect64(), reason="Aborted on Iris Xe: SAT-5988"
)
@pytest.mark.parametrize("type", get_all_dtypes(no_bool=True, no_complex=True))
def test_allclose(type):
a = numpy.random.rand(10)
Expand Down
18 changes: 11 additions & 7 deletions tests/test_manipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,19 +4,23 @@

import dpnp

from .helper import has_support_aspect64

testdata = []
testdata += [
([True, False, True], dtype)
for dtype in ["float32", "float64", "int32", "int64", "bool"]
]
testdata += [
([1, -1, 0], dtype) for dtype in ["float32", "float64", "int32", "int64"]
for dtype in ["float32", "int32", "int64", "bool"]
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]
testdata += [([0.1, 0.0, -0.1], dtype) for dtype in ["float32", "float64"]]
testdata += [([1j, -1j, 1 - 2j], dtype) for dtype in ["complex128"]]
testdata += [([1, -1, 0], dtype) for dtype in ["float32", "int32", "int64"]]
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testdata += [([0.1, 0.0, -0.1], dtype) for dtype in ["float32"]]
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if has_support_aspect64():
testdata += [([True, False, True], dtype) for dtype in ["float64"]]
testdata += [([1, -1, 0], dtype) for dtype in ["float64"]]
testdata += [([0.1, 0.0, -0.1], dtype) for dtype in ["float64"]]
testdata += [([1j, -1j, 1 - 2j], dtype) for dtype in ["complex128"]]
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@pytest.mark.parametrize("in_obj,out_dtype", testdata)
@pytest.mark.parametrize("in_obj, out_dtype", testdata)
def test_copyto_dtype(in_obj, out_dtype):
ndarr = numpy.array(in_obj)
expected = numpy.empty(ndarr.size, dtype=out_dtype)
Expand Down
28 changes: 14 additions & 14 deletions tests/test_mixins.py
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Expand Up @@ -12,19 +12,19 @@ def test_matmul(self):

# DPNP
array1 = inp.reshape(
inp.array(array_data, dtype=inp.float64), (size, size)
inp.array(array_data, dtype=inp.float32), (size, size)
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)
array2 = inp.reshape(
inp.array(array_data, dtype=inp.float64), (size, size)
inp.array(array_data, dtype=inp.float32), (size, size)
)
result = inp.matmul(array1, array2)
# print(result)
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# original
array_1 = numpy.array(array_data, dtype=numpy.float64).reshape(
array_1 = numpy.array(array_data, dtype=numpy.float32).reshape(
(size, size)
)
array_2 = numpy.array(array_data, dtype=numpy.float64).reshape(
array_2 = numpy.array(array_data, dtype=numpy.float32).reshape(
(size, size)
)
expected = numpy.matmul(array_1, array_2)
Expand All @@ -40,14 +40,14 @@ def test_matmul2(self):
array_data2 = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]

# DPNP
array1 = inp.reshape(inp.array(array_data1, dtype=inp.float64), (3, 2))
array2 = inp.reshape(inp.array(array_data2, dtype=inp.float64), (2, 4))
array1 = inp.reshape(inp.array(array_data1, dtype=inp.float32), (3, 2))
array2 = inp.reshape(inp.array(array_data2, dtype=inp.float32), (2, 4))
result = inp.matmul(array1, array2)
# print(result)

# original
array_1 = numpy.array(array_data1, dtype=numpy.float64).reshape((3, 2))
array_2 = numpy.array(array_data2, dtype=numpy.float64).reshape((2, 4))
array_1 = numpy.array(array_data1, dtype=numpy.float32).reshape((3, 2))
array_2 = numpy.array(array_data2, dtype=numpy.float32).reshape((2, 4))
expected = numpy.matmul(array_1, array_2)
# print(expected)

Expand All @@ -56,17 +56,17 @@ def test_matmul2(self):
def test_matmul3(self):
array_data1 = numpy.full((513, 513), 5)
array_data2 = numpy.full((513, 513), 2)
out = numpy.empty((513, 513), dtype=numpy.float64)
out = numpy.empty((513, 513), dtype=numpy.float32)

# DPNP
array1 = inp.array(array_data1, dtype=inp.float64)
array2 = inp.array(array_data2, dtype=inp.float64)
out1 = inp.array(out, dtype=inp.float64)
array1 = inp.array(array_data1, dtype=inp.float32)
array2 = inp.array(array_data2, dtype=inp.float32)
out1 = inp.array(out, dtype=inp.float32)
result = inp.matmul(array1, array2, out=out1)

# original
array_1 = numpy.array(array_data1, dtype=numpy.float64)
array_2 = numpy.array(array_data2, dtype=numpy.float64)
array_1 = numpy.array(array_data1, dtype=numpy.float32)
array_2 = numpy.array(array_data2, dtype=numpy.float32)
expected = numpy.matmul(array_1, array_2, out=out)

numpy.testing.assert_array_equal(expected, result)
Expand Down
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