carrot/tinygrad_repo/docs/env_vars.md

List of environment variables that control tinygrad behavior.

This is a list of environment variable that control the runtime behavior of tinygrad and its examples. Most of these are self-explanatory, and are usually used to set an option at runtime.

Example: GPU=1 DEBUG=4 python3 -m pytest

However you can also decorate a function to set a value only inside that function.

# in tensor.py (probably only useful if you are a tinygrad developer)
@Context(DEBUG=4)
def numpy(self) -> ...

Or use contextmanager to temporarily set a value inside some scope:

with Context(DEBUG=0):
  a = Tensor.ones(10, 10)
  a *= 2

Global Variables

The columns of this list are are: Variable, Possible Value(s) and Description.

• A # means that the variable can take any integer value.

These control the behavior of core tinygrad even when used as a library.

Variable	Possible Value(s)	Description
DEBUG	[1-7]	enable debugging output (operations, timings, speed, generated code and more)
GPU	[1]	enable the GPU (OpenCL) backend
CUDA	[1]	enable CUDA backend
AMD	[1]	enable AMD backend
NV	[1]	enable NV backend
METAL	[1]	enable Metal backend (for Mac M1 and after)
CPU	[1]	enable CPU (Clang) backend
LLVM	[1]	enable LLVM backend
BEAM	[#]	number of beams in kernel beam search
DEFAULT_FLOAT	[HALF, ...]	specify the default float dtype (FLOAT32, HALF, BFLOAT16, FLOAT64, ...), default to FLOAT32
IMAGE	[1-2]	enable 2d specific optimizations
FLOAT16	[1]	use float16 for images instead of float32
PTX	[1]	enable the specialized PTX assembler for Nvidia GPUs. If not set, defaults to generic CUDA codegen backend.
PROFILE	[1]	enable profiling. This feature is supported in NV, AMD, QCOM and METAL backends.
VISIBLE_DEVICES	[list[int]]	restricts the NV/AMD devices that are available. The format is a comma-separated list of identifiers (indexing starts with 0).
JIT	[0-2]	0=disabled, 1=jit enabled (default), 2=jit enabled, but graphs are disabled
VIZ	[1]	0=disabled, 1=viz enabled
ALLOW_TF32	[1]	enable TensorFloat-32 tensor cores on Ampere or newer GPUs.
WEBGPU_BACKEND	[WGPUBackendType_Metal, ...]	Force select a backend for WebGPU (Metal, DirectX, OpenGL, Vulkan...)
CUDA_PATH	str	Use CUDA_PATH/include for CUDA headers for CUDA and NV backends. If not set, TinyGrad will use /usr/local/cuda/include, /usr/include and /opt/cuda/include.

Debug breakdown

Variable	Value	Description
DEBUG	>= 1	Enables debugging and lists devices being used
DEBUG	>= 2	Provides performance metrics for operations, including timing, memory usage, bandwidth for each kernel execution
DEBUG	>= 3	Outputs buffers used for each kernel (shape, dtype and strides) and the applied optimizations at a kernel level
DEBUG	>= 4	Outputs the generated kernel code
DEBUG	>= 5	Displays the intermediate representation of the computation UOps (AST)
DEBUG	>= 6	Displays the intermediate representation of the computation UOps in a linearized manner, detailing the operation sequence
DEBUG	>= 7	Outputs the assembly code generated for the target hardware