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Implement dpnp.gradient function #1859

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merged 6 commits into from
May 31, 2024
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Implement dpnp.gradient function #1859

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bfb309f
Implement dpnp.gradient function
antonwolfy May 28, 2024
09fb98f
Merge branch 'master' into impl_gradient
antonwolfy May 28, 2024
09c4c3e
Resolve pre-commit issues
antonwolfy May 29, 2024
7813f82
Merge branch 'master' into impl_gradient
antonwolfy May 29, 2024
75f6bfb
Update dpnp/dpnp_iface_mathematical.py
antonwolfy May 30, 2024
ce82ae9
Update dpnp/dpnp_iface_mathematical.py
antonwolfy May 30, 2024
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31 changes: 0 additions & 31 deletions dpnp/dpnp_algo/dpnp_algo_mathematical.pxi
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,6 @@ __all__ += [
"dpnp_ediff1d",
"dpnp_fabs",
"dpnp_fmod",
"dpnp_gradient",
"dpnp_fmax",
"dpnp_fmin",
"dpnp_modf",
Expand Down Expand Up @@ -123,36 +122,6 @@ cpdef utils.dpnp_descriptor dpnp_fmod(utils.dpnp_descriptor x1_obj,
return call_fptr_2in_1out_strides(DPNP_FN_FMOD_EXT, x1_obj, x2_obj, dtype, out, where)


cpdef utils.dpnp_descriptor dpnp_gradient(utils.dpnp_descriptor y1, int dx=1):

cdef size_t size = y1.size

y1_obj = y1.get_array()

# create result array with type given by FPTR data
cdef shape_type_c result_shape = utils._object_to_tuple(size)
cdef utils.dpnp_descriptor result = utils_py.create_output_descriptor_py(result_shape,
dpnp.default_float_type(y1_obj.sycl_queue),
None,
device=y1_obj.sycl_device,
usm_type=y1_obj.usm_type,
sycl_queue=y1_obj.sycl_queue)

cdef double cur = (y1.get_pyobj()[1] - y1.get_pyobj()[0]) / dx

result.get_pyobj().flat[0] = cur

cur = (y1.get_pyobj()[-1] - y1.get_pyobj()[-2]) / dx

result.get_pyobj().flat[size - 1] = cur

for i in range(1, size - 1):
cur = (y1.get_pyobj()[i + 1] - y1.get_pyobj()[i - 1]) / (2 * dx)
result.get_pyobj().flat[i] = cur

return result


cpdef utils.dpnp_descriptor dpnp_fmax(utils.dpnp_descriptor x1_obj,
utils.dpnp_descriptor x2_obj,
object dtype=None,
Expand Down
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