python
PyTorch backward on non-scalar tensor
torch\.autograd\..*grad can be implicitly created only for scalar outputs
Fixes
- 1.Call .sum() or .mean() on the loss before .backward()
- 2.Pass gradient argument to .backward() for non-scalar tensors
- 3.Ensure loss function returns a scalar value
pytorchautograd
Related Errors
python3 fixes
Asyncio event loop already running
RuntimeError: This event loop is already running
- •Use nest_asyncio.apply() to allow nested event loops
- •Use asyncio.run_coroutine_threadsafe() instead of asyncio.run()
python3 fixes
Coroutine never awaited
RuntimeWarning: coroutine '.*' was never awaited
- •Add 'await' before the coroutine call
- •Use asyncio.create_task() to schedule the coroutine
python3 fixes
Asyncio task was cancelled
asyncio\.CancelledError
- •Handle CancelledError in try/except within the task
- •Use asyncio.shield() to protect critical sections from cancellation