a 8Sic| @svdZddlZddlZddlZddlmZmZmZmZm Z m Z ddl Z ddl m Z gdZe eeee edfeeefegeffedd d Zed e jZed e jZe jd e jde jdiZe je je eefdddZeddeeeeeeeeddddZddZe jD],Zee eZ eee e!e<e"eqeee j#Z#ede je jdddZ$dS) a;This module exists since the `torch.testing` exposed a lot of stuff that shouldn't have been public. Although this was never documented anywhere, some other internal FB projects as well as downstream OSS projects might use this. Thus, we don't internalize without warning, but still go through a deprecation cycle. N)AnyCallableDictOptionalTupleUnion)_legacy)randrandnassert_allcloseget_all_device_typesmake_non_contiguous.) instructionsreturncsttdfdd }|S)N)fnrcs<jddttttdfdd }|S)Nztorch.testing.z9() is deprecated since 1.12 and will be removed in 1.14. )argskwargsrcsD|i|}tr$|||n}|}t|t|S)N)callablestripwarningswarn FutureWarning)rr return_valuetailmsg)rheadrnameU/var/www/html/django/DPS/env/lib/python3.9/site-packages/torch/testing/_deprecated.py inner_wrappers   z=warn_deprecated..outer_wrapper..inner_wrapper)__name__ functoolswrapsr)rr r)rrrr outer_wrappers  z&warn_deprecated..outer_wrapper)r)rr%rr$rwarn_deprecatedsr&zUse torch.rand() instead.zUse torch.randn() instead.)MbP?r')g-C6?h㈵>)r(g:0yE>)actualexpectedrcCs8t|jd\}}t|jd\}}t||t||fS)N)r+)_DTYPE_PRECISIONSgetdtypemax)r)r*Z actual_rtolZ actual_atolZ expected_rtolZ expected_atolrrr_get_default_rtol_and_atol6sr0zUse torch.testing.assert_close() instead. For detailed upgrade instructions see https://github.com/pytorch/pytorch/issues/61844.T)r)r*rtolatol equal_nanrrc Csvt|tjst|}t|tjs2tj||jd}|durP|durPt||\}}tjj|||||ddd|pldd dS)N)r.TF)r2r3r4 check_device check_dtype check_strider) isinstancetorchTensortensorr.r0testing assert_close)r)r*r2r3r4rrrrr <s"   r cCs d|dS)NzThis call can be replaced with .r)rrrrrrr^r?a+Depending on the use case there a different replacement options: - If you are using `make_non_contiguous` in combination with a creation function to create a noncontiguous tensor with random values, use `torch.testing.make_tensor(..., noncontiguous=True)` instead. - If you are using `make_non_contiguous` with a specific tensor, you can replace this call with `torch.repeat_interleave(input, 2, dim=-1)[..., ::2]`. - If you are using `make_non_contiguous` in the PyTorch test suite, use `torch.testing._internal.common_utils.noncontiguous_like` instead.)r;rc Cs|dkr|St|}tdD]4}tdt|d}tdd}|||||<q(|t |tddg}| t|dtdd}tt|D]H}||||krtd||||}| ||||}q| ||jS)Nrr)numelclonelistsizerangerandomrandintlennewr9Sizeselectnarrowcopy_data)r;Zosize_dimaddinputiboundsrrrrjs      r)NNTr1)%__doc__r"rJrtypingrrrrrrr9r1r __all__strr&r r float16float32float64r,r:floatr0boolr Zgetter_instructionsZ__all_dtype_getters__rgetattrrglobalsappendr rrrrrsT   8