frozenleaves/pytorch
1
0
Fork 0
mirror of https://github.com/pytorch/pytorch.git synced 2025-10-20 21:14:14 +08:00
Code Issues Packages Projects Releases Wiki Activity

Rename DefaultBackend to CompositeExplicitAutograd (#54470)

Browse Source 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54470

```
git grep -l 'DefaultBackend' | xargs sed -i 's/DefaultBackend/CompositeExplicitAutograd/g'
```

Plus a quick fixup in native/README.md

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Test Plan: Imported from OSS

Reviewed By: bdhirsh

Differential Revision: D27253240

Pulled By: ezyang

fbshipit-source-id: 964df951ea8b52fa72937f3cc66aeaf49a702e6f
This commit is contained in:
Edward Yang
2021-03-26 10:50:06 -07:00
committed by Facebook GitHub Bot
parent 70dd2a2bdd
commit 13b1ca9466
18 changed files with 328 additions and 325 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
test/test_dispatch.py
View File

@ -562,8 +562,8 @@ QuantizedCPU: fn_quantizedcpu [kernel]
lambda m: m.def_("foo(Tensor x) -> Tensor"),
# m.impl("foo", torch::kCPU, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "CPU", debug="fn_cpu"),
# m.impl("foo", torch::kDefaultBackend, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "DefaultBackend", debug="fn_defaultbackend"),
# m.impl("foo", torch::kCompositeExplicitAutograd, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "CompositeExplicitAutograd", debug="fn_defaultbackend"),
])
state, table = result.state, result.table
self.assertExpectedInline(state, '''\
@ -572,7 +572,7 @@ schema: test::foo(Tensor x) -> (Tensor)
debug: registered at /dev/null:0
alias analysis kind: FROM_SCHEMA
CPU: fn_cpu :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
DefaultBackend[alias]: fn_defaultbackend :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
CompositeExplicitAutograd[alias]: fn_defaultbackend :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
''')
# computed dispatch table is too big, so we only check on a few entries we're interested in.
@ -597,8 +597,8 @@ AutogradXLA: fallthrough registered in pytorch framework [backend fallback]
lambda m: m.impl_t_t("foo", "CPU", debug="fn_cpu"),
# m.impl("foo", torch::kAutograd, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "Autograd", debug="fn_autograd"),
# m.impl("foo", torch::kDefaultBackend, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "DefaultBackend", debug="fn_defaultbackend"),
# m.impl("foo", torch::kCompositeExplicitAutograd, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "CompositeExplicitAutograd", debug="fn_defaultbackend"),
])
state, table = result.state, result.table
self.assertExpectedInline(state, '''\
@ -608,7 +608,7 @@ debug: registered at /dev/null:0
alias analysis kind: FROM_SCHEMA
CPU: fn_cpu :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
Autograd[alias]: fn_autograd :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
DefaultBackend[alias]: fn_defaultbackend :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
CompositeExplicitAutograd[alias]: fn_defaultbackend :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
''')
# computed dispatch table is too big, so we only check on a few entries we're interested in.
@ -636,8 +636,8 @@ QuantizedCPU: fn_defaultbackend [default backend kernel]
lambda m: m.impl_t_t("foo", "Autograd", debug="fn_autograd"),
# m.impl("foo", torch::kCompositeImplicitAutograd, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "CompositeImplicitAutograd", debug="fn_math"),
# m.impl("foo", torch::kDefaultBackend, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "DefaultBackend", debug="fn_defaultbackend"),
# m.impl("foo", torch::kCompositeExplicitAutograd, [](const Tensor & x) { return x })
lambda m: m.impl_t_t("foo", "CompositeExplicitAutograd", debug="fn_defaultbackend"),
])
state, table = result.state, result.table
self.assertExpectedInline(state, '''\
@ -648,7 +648,7 @@ alias analysis kind: FROM_SCHEMA
CPU: fn_cpu :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
Autograd[alias]: fn_autograd :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
CompositeImplicitAutograd[alias]: fn_math :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
DefaultBackend[alias]: fn_defaultbackend :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
CompositeExplicitAutograd[alias]: fn_defaultbackend :: (Tensor _0) -> (Tensor _0) [ boxed unboxed ]
''')
# computed dispatch table is too big, so we only check on a few entries we're interested in.
@ -809,7 +809,7 @@ CompositeImplicitAutograd[alias] fn_CompositeImplicitAutograd
def test_defaultbackend_autogradcpu(self):
dispatcher = PythonDispatcher()
dispatcher.register(["CPU", "XLA", "DefaultBackend", "AutogradCPU"])
dispatcher.register(["CPU", "XLA", "CompositeExplicitAutograd", "AutogradCPU"])
self.assertExpectedInline(
dispatcher.dispatchTable(),
'''\
@ -819,7 +819,7 @@ key kernel
---------------------------
CPU fn_CPU [kernel]
XLA fn_XLA [kernel]
QuantizedCPU fn_DefaultBackend [default backend kernel]
QuantizedCPU fn_CompositeExplicitAutograd [default backend kernel]
AutogradOther fallthrough [backend fallback]
AutogradCPU fn_AutogradCPU [kernel]
AutogradXLA fallthrough [backend fallback]
@ -836,7 +836,7 @@ key kernel
CPU fn_CPU
XLA fn_XLA
AutogradCPU fn_AutogradCPU
DefaultBackend[alias] fn_DefaultBackend
CompositeExplicitAutograd[alias] fn_CompositeExplicitAutograd
'''
)
@ -883,8 +883,8 @@ CompositeImplicitAutograd[alias] fn_CompositeImplicitAutograd
with self.assertRaisesRegex(
RuntimeError,
r"Registration to both CompositeImplicitAutograd and DefaultBackend is not allowed"):
dispatcher.register(["DefaultBackend", "CompositeImplicitAutograd"])
r"Registration to both CompositeImplicitAutograd and CompositeExplicitAutograd is not allowed"):
dispatcher.register(["CompositeExplicitAutograd", "CompositeImplicitAutograd"])
if __name__ == '__main__':