Just import torch AdamW instead (#36177)

* Just import torch AdamW instead

* Update docs too

* Make AdamW undocumented

* make fixup

* Add a basic wrapper class

* Add it back to the docs

* Just remove AdamW entirely

* Remove some AdamW references

* Drop AdamW from the public init

* make fix-copies

* Cleanup some references

* make fixup

* Delete lots of transformers.AdamW references

* Remove extra references to adamw_hf

tests/optimization/test_optimization.py

@@ -28,7 +28,6 @@ if is_torch_available():
 
     from transformers import (
         Adafactor,
-        AdamW,
         get_constant_schedule,
         get_constant_schedule_with_warmup,
         get_cosine_schedule_with_warmup,
@@ -76,7 +75,7 @@ class OptimizationTest(unittest.TestCase):
         target = torch.tensor([0.4, 0.2, -0.5])
         criterion = nn.MSELoss()
         # No warmup, constant schedule, no gradient clipping
-        optimizer = AdamW(params=[w], lr=2e-1, weight_decay=0.0)
+        optimizer = torch.optim.AdamW(params=[w], lr=2e-1, weight_decay=0.0)
         for _ in range(100):
             loss = criterion(w, target)
             loss.backward()
@@ -114,7 +113,7 @@ class OptimizationTest(unittest.TestCase):
 @require_torch
 class ScheduleInitTest(unittest.TestCase):
     m = nn.Linear(50, 50) if is_torch_available() else None
-    optimizer = AdamW(m.parameters(), lr=10.0) if is_torch_available() else None
+    optimizer = torch.optim.AdamW(m.parameters(), lr=10.0) if is_torch_available() else None
     num_steps = 10
 
     def assertListAlmostEqual(self, list1, list2, tol, msg=None):