Python raise runtimeerror
In this article, we will discuss how to manage unexpected errors in Python using the ‘raise RuntimeError’ statement. Also, we will learn how to identify and fix errors in your …
Python RuntimeError Reference: 49+ PyTorch, CUDA, asyncio, Flask Fixes (2026)
itsourcecode.com hosts 49+ documented fixes for Python RuntimeError messages: the catch-all error class Python raises when something goes wrong at runtime that doesn’t fit a more specific category. In modern Python, most RuntimeErrors come from PyTorch/CUDA (GPU memory, scalar type, cudnn), asyncio (event loop already running), Flask/Django (working outside request context), or iteration mutation (set/dict changed size during iteration). Browse the fixes below.
What is a Python RuntimeError?
A RuntimeError is the base class for errors that don’t fit a more specific built-in exception. Libraries raise RuntimeError when something happens that the standard exception hierarchy doesn’t anticipate, PyTorch raises it for GPU/tensor problems, asyncio for event loop state issues, Flask for missing application context. Because it’s a catch-all, the fix depends heavily on which library raised it and what the message says.
How to debug any RuntimeError in 4 steps
Read the full message. RuntimeError messages are library-specific and usually descriptive. “CUDA out of memory” means GPU memory; “event loop is already running” means asyncio context; “working outside of request context” means Flask scope.
Identify the library. The traceback above the error tells you which library raised it. PyTorch → tensor/dtype/GPU. asyncio → event loop. Flask/Django → request context. PySpark → Java gateway. Each has a different fix pattern.
Check resource state. For CUDA: nvidia-smi to see GPU memory. For asyncio: check if you’re inside an existing event loop. For dict/set iteration: never mutate while iterating, copy first or use a comprehension.
Search this hub by library category below. Most RuntimeErrors have well-documented patterns. Find your exact message.
Featured RuntimeError fixes by library
🔥 PyTorch: scalar type / dtype mismatches
PyTorch tensor operations require specific dtypes; mixing float16, float32, bfloat16, and double raises RuntimeError.
Found dtype Long but expected Float
Expected scalar type Half but found Float
Expected scalar type BFloat16 but found Float
Expected scalar type Float but found Double
mat1 and mat2 shapes cannot be multiplied
🎮 PyTorch / CUDA: GPU errors
The most painful RuntimeErrors in ML, usually GPU memory, driver, or device assertion issues.
CUDA out of memory
No CUDA GPUs are available
CUDA error: invalid device ordinal
CUDA error: device-side assert triggered
All CUDA-capable devices are busy or unavailable
cuDNN error: CUDNN_STATUS_MAPPING_ERROR
cuDNN error: CUDNN_STATUS_NOT_INITIALIZED
cuDNN error: CUDNN_STATUS_EXECUTION_FAILED
Couldn’t install torch
⏱️ asyncio: event loop state
This event loop is already running
No running event loop
🌐 Flask / Django: request context
Working outside of request context (Flask)
SQLALCHEMY_DATABASE_URI or SQLALCHEMY_BINDS must be set
Cannot add middleware after an application has started
🔁 Mutation-during-iteration
Dictionary changed size during iteration
Set changed size during iteration
☕ PySpark: Java gateway
Java gateway process exited before sending its port number
📦 Build / Install / Config
Poetry configuration is invalid
Ninja is required to load C++ extensions
Product license has not been initialized
Python raise RuntimeError (manual raise)
Related error categories
RuntimeError is one of 10 hubs in our Python & JavaScript error reference cluster, 980+ documented fixes total:
TypeError Reference, 220+ Python & JS TypeError fixes
ModuleNotFoundError Reference, 198+ Python import errors
AttributeError Reference, 173+ “object has no attribute X” fixes
ValueError Reference, 100+ pandas/NumPy/sklearn fixes
ImportError Reference, 67+ “cannot import name X from Y” fixes
NameError Reference, 49+ “name X is not defined” fixes
SyntaxError Reference, 48+ Python & JavaScript syntax errors
ReferenceError Reference, 34+ JavaScript “is not defined” fixes
HTTP Error Reference, 35+ HTTP status code fixes (4xx, 5xx)
Python Tutorial, beginner-to-intermediate Python lessons
About this RuntimeError reference
Built since 2015 by PIES Information Technology Solutions, Binalbagan, Negros Occidental, Philippines. Every post comes from a real error encountered in production. Used by 12,000+ Python developers monthly.
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Runtimeerror: mat1 and mat2 must have the same dtype
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Runtimeerror working outside of request context
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[Fixed 2026] RuntimeError: Trying to resize storage that is not resizable
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Runtimeerror: grad can be implicitly created only for scalar outputs
If you are running a project in PyTorch, you may often encountered the error message which is: Runtimeerror: grad can be implicitly created only for scalar outputs This error frequently …
[Fixed 2026] RuntimeError: Event Loop Is Closed
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runtimeerror: working outside of application context.
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Runtimeerror: ninja is required to load c++ extensions
As a Python developer, encountering errors while coding is a common circumstance. One of the most perplexing errors is the runtimeerror: ninja is required to load c++ extensions. This error …
Runtimeerror: expected scalar type long but found float
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Runtimeerror: can’t start new thread
If you are a developer or system administrator, you may have encountered the RuntimeError: Can’t Start New Thread error at some point. This error occurs when your application or system …
Runtimeerror: no cuda gpus are available
The RuntimeError: no CUDA GPUs are available error typically occurs if a program attempts to use the CUDA library for GPU acceleration, yet no compatible GPUs are available on the …
Frequently Asked Questions
What is the difference between RuntimeError and other exceptions?
RuntimeError is the catch-all base class for errors that do not fit a more specific exception (TypeError, ValueError, KeyError, etc.). Libraries reach for RuntimeError when no built-in exception matches their failure mode, common for GPU, async, framework-context issues.
How do I fix "CUDA out of memory" in PyTorch?
Five things to try in order: (1) Reduce batch size by half. (2) Add torch.cuda.empty_cache() between training epochs. (3) Use mixed-precision training (torch.cuda.amp). (4) Gradient checkpointing to trade compute for memory. (5) If using a Jupyter notebook, restart the kernel, old tensors may still be alive in GPU memory.
How do I fix "dictionary changed size during iteration"?
You are modifying a dict while iterating it. Fix by iterating over a copy: for key in list(d.keys()): or for key in dict(d):. Or build a new dict with a comprehension: d = {k: v for k, v in d.items() if condition}. Same applies to sets.
How do I fix "This event loop is already running"?
You are calling asyncio.run(...) from inside an already-running event loop (Jupyter, FastAPI, etc.). Use await directly if you are already in an async context. For Jupyter, use nest_asyncio.apply() at the top of the notebook, but only as a last resort.
How do I fix "Working outside of request context" in Flask?
You are trying to access request, session, or g from code that runs outside an HTTP request, typically background jobs, CLI commands, or unit tests. For backgrounded code, push an application context manually: with app.app_context():. For request-specific objects, you may need to pass the data explicitly instead.
How often is this RuntimeError reference updated?
New posts are added weekly. Existing posts are revised when major versions of PyTorch, CUDA, Flask, or asyncio ship breaking changes. Last refreshed: May 2026.