alea sync

runs/rl_r2.log

@@ -0,0 +1,17 @@
+`torch_dtype` is deprecated! Use `dtype` instead!
+`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`.
+Traceback (most recent call last):
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "/root/alea/alea/rl_env.py", line 277, in <module>
+    main()
+  File "/root/alea/alea/rl_env.py", line 250, in main
+    loss.backward()
+  File "/root/venv/lib/python3.11/site-packages/torch/_tensor.py", line 626, in backward
+    torch.autograd.backward(
+  File "/root/venv/lib/python3.11/site-packages/torch/autograd/__init__.py", line 347, in backward
+    _engine_run_backward(
+  File "/root/venv/lib/python3.11/site-packages/torch/autograd/graph.py", line 823, in _engine_run_backward
+    return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed). Saved intermediate values of the graph are freed when you call .backward() or autograd.grad(). Specify retain_graph=True if you need to backward through the graph a second time or if you need to access saved tensors after calling backward.