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Merge pull request #1343 from IntelPython/fix-gh-1279
Fix gh-1279, implement tensor.allclose
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# Data Parallel Control (dpctl) | ||
# | ||
# Copyright 2020-2023 Intel Corporation | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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import numpy as np | ||
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import dpctl.tensor as dpt | ||
import dpctl.utils as du | ||
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from ._manipulation_functions import _broadcast_shape_impl | ||
from ._type_utils import _to_device_supported_dtype | ||
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def _allclose_complex_fp(z1, z2, atol, rtol, equal_nan): | ||
z1r = dpt.real(z1) | ||
z1i = dpt.imag(z1) | ||
z2r = dpt.real(z2) | ||
z2i = dpt.imag(z2) | ||
if equal_nan: | ||
check1 = dpt.all(dpt.isnan(z1r) == dpt.isnan(z2r)) and dpt.all( | ||
dpt.isnan(z1i) == dpt.isnan(z2i) | ||
) | ||
else: | ||
check1 = ( | ||
dpt.logical_not(dpt.any(dpt.isnan(z1r))) | ||
and dpt.logical_not(dpt.any(dpt.isnan(z1i))) | ||
) and ( | ||
dpt.logical_not(dpt.any(dpt.isnan(z2r))) | ||
and dpt.logical_not(dpt.any(dpt.isnan(z2i))) | ||
) | ||
if not check1: | ||
return check1 | ||
mr = dpt.isinf(z1r) | ||
mi = dpt.isinf(z1i) | ||
check2 = dpt.all(mr == dpt.isinf(z2r)) and dpt.all(mi == dpt.isinf(z2i)) | ||
if not check2: | ||
return check2 | ||
check3 = dpt.all(z1r[mr] == z2r[mr]) and dpt.all(z1i[mi] == z2i[mi]) | ||
if not check3: | ||
return check3 | ||
mr = dpt.isfinite(z1r) | ||
mi = dpt.isfinite(z1i) | ||
mv1 = z1r[mr] | ||
mv2 = z2r[mr] | ||
check4 = dpt.all( | ||
dpt.abs(mv1 - mv2) | ||
< dpt.maximum(atol, rtol * dpt.maximum(dpt.abs(mv1), dpt.abs(mv2))) | ||
) | ||
if not check4: | ||
return check4 | ||
mv1 = z1i[mi] | ||
mv2 = z2i[mi] | ||
check5 = dpt.all( | ||
dpt.abs(mv1 - mv2) | ||
<= dpt.maximum(atol, rtol * dpt.maximum(dpt.abs(mv1), dpt.abs(mv2))) | ||
) | ||
return check5 | ||
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def _allclose_real_fp(r1, r2, atol, rtol, equal_nan): | ||
if equal_nan: | ||
check1 = dpt.all(dpt.isnan(r1) == dpt.isnan(r2)) | ||
else: | ||
check1 = dpt.logical_not(dpt.any(dpt.isnan(r1))) and dpt.logical_not( | ||
dpt.any(dpt.isnan(r2)) | ||
) | ||
if not check1: | ||
return check1 | ||
mr = dpt.isinf(r1) | ||
check2 = dpt.all(mr == dpt.isinf(r2)) | ||
if not check2: | ||
return check2 | ||
check3 = dpt.all(r1[mr] == r2[mr]) | ||
if not check3: | ||
return check3 | ||
m = dpt.isfinite(r1) | ||
mv1 = r1[m] | ||
mv2 = r2[m] | ||
check4 = dpt.all( | ||
dpt.abs(mv1 - mv2) | ||
<= dpt.maximum(atol, rtol * dpt.maximum(dpt.abs(mv1), dpt.abs(mv2))) | ||
) | ||
return check4 | ||
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def _allclose_others(r1, r2): | ||
return dpt.all(r1 == r2) | ||
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def allclose(a1, a2, atol=1e-8, rtol=1e-5, equal_nan=False): | ||
"""allclose(a1, a2, atol=1e-8, rtol=1e-5, equal_nan=False) | ||
Returns True if two arrays are element-wise equal within tolerances. | ||
The testing is based on the following elementwise comparison: | ||
abs(a - b) <= max(atol, rtol * max(abs(a), abs(b))) | ||
""" | ||
if not isinstance(a1, dpt.usm_ndarray): | ||
raise TypeError( | ||
f"Expected dpctl.tensor.usm_ndarray type, got {type(a1)}." | ||
) | ||
if not isinstance(a2, dpt.usm_ndarray): | ||
raise TypeError( | ||
f"Expected dpctl.tensor.usm_ndarray type, got {type(a2)}." | ||
) | ||
atol = float(atol) | ||
rtol = float(rtol) | ||
if atol < 0.0 or rtol < 0.0: | ||
raise ValueError( | ||
"Absolute and relative tolerances must be non-negative" | ||
) | ||
equal_nan = bool(equal_nan) | ||
exec_q = du.get_execution_queue(tuple(a.sycl_queue for a in (a1, a2))) | ||
if exec_q is None: | ||
raise du.ExecutionPlacementError( | ||
"Execution placement can not be unambiguously inferred " | ||
"from input arguments." | ||
) | ||
res_sh = _broadcast_shape_impl([a1.shape, a2.shape]) | ||
b1 = a1 | ||
b2 = a2 | ||
if b1.dtype == b2.dtype: | ||
res_dt = b1.dtype | ||
else: | ||
res_dt = np.promote_types(b1.dtype, b2.dtype) | ||
res_dt = _to_device_supported_dtype(res_dt, exec_q.sycl_device) | ||
b1 = dpt.astype(b1, res_dt) | ||
b2 = dpt.astype(b2, res_dt) | ||
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b1 = dpt.broadcast_to(b1, res_sh) | ||
b2 = dpt.broadcast_to(b2, res_sh) | ||
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k = b1.dtype.kind | ||
if k == "c": | ||
return _allclose_complex_fp(b1, b2, atol, rtol, equal_nan) | ||
elif k == "f": | ||
return _allclose_real_fp(b1, b2, atol, rtol, equal_nan) | ||
else: | ||
return _allclose_others(b1, b2) |
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