Documentation
Fie Specific Variables

File Specific Variables

These are variables that control the behavior of a specific file, these usually don't affect the library itself. Most of the time these will never be used, but they are here for completeness.

accel/ane/2_compile/hwx_parse.py

VariablePossible Value(s)Description
PRINTALL[1]print all ANE registers

# extra/onnx.py

VariablePossible Value(s)Description
ONNXLIMIT[#]set a limit for ONNX
DEBUGONNX[1]enable ONNX debugging

extra/thneed.py

VariablePossible Value(s)Description
DEBUGCL[1-4]enable Debugging for OpenCL
PRINT_KERNEL[1]Print OpenCL Kernels

extra/kernel_search.py

VariablePossible Value(s)Description
OP[1-3]different operations
NOTEST[1]enable not testing AST
DUMP[1]enable dumping of intervention cache
REDUCE[1]enable reduce operations
SIMPLE_REDUCE[1]enable simpler reduce operations
BC[1]enable big conv operations
CONVW[1]enable convw operations
FASTCONV[1]enable faster conv operations
GEMM[1]enable general matrix multiply operations
BROKEN[1]enable a kind of operation
BROKEN3[1]enable a kind of operation

examples/vit.py

VariablePossible Value(s)Description
LARGE[1]enable larger dimension model

examples/llama.py

VariablePossible Value(s)Description
WEIGHTS[1]enable loading weights

examples/mlperf

VariablePossible Value(s)Description
MODEL[resnet,retinanet,unet3d,rnnt,bert,maskrcnn]what models to use

examples/benchmark_train_efficientnet.py

VariablePossible Value(s)Description
CNT[10]the amount of times to loop the benchmark
BACKWARD[1]enable backward pass
TRAINING[1]set Tensor.training
CLCACHE[1]enable cache for OpenCL

examples/hlb_cifar10.py

VariablePossible Value(s)Description
TORCHWEIGHTS[1]use torch to initialize weights
DISABLE_BACKWARD[1]don't do backward pass
DIST[1]enable distributed training
STEPS[#]number of steps

examples/benchmark_train_efficientnet.py & examples/hlb_cifar10.py

VariablePossible Value(s)Description
ADAM[1]use the Adam optimizer

examples/train_efficientnet.py

VariablePossible Value(s)Description
STEPS[# % 1024]number of steps
TINY[1]use a tiny convolution network
IMAGENET[1]use imagenet for training

examples/train_efficientnet.py & examples/train_resnet.py

VariablePossible Value(s)Description
TRANSFER[1]enable to use pretrained data

examples & test/external/external_test_opt.py

VariablePossible Value(s)Description
NUM[18, 2]what ResNet[18] / EfficientNet[2] to train

test/test_ops.py

VariablePossible Value(s)Description
PRINT_TENSORS[1]print tensors
FORWARD_ONLY[1]use forward operations only

test/test_speed_v_torch.py

VariablePossible Value(s)Description
TORCHCUDA[1]enable the torch cuda backend

test/external/external_test_gpu_ast.py

VariablePossible Value(s)Description
KCACHE[1]enable kernel cache

test/external/external_test_opt.py

VariablePossible Value(s)Description
ENET_NUM[-2,-1]what EfficientNet to use

test/test_dtype.py & test/extra/test_utils.py & extra/training.py

VariablePossible Value(s)Description
CI[1]disables some tests for CI

examples & extra & test

VariablePossible Value(s)Description
BS[8, 16, 32, 64, 128]batch size to use

extra/datasets/imagenet_download.py

VariablePossible Value(s)Description
IMGNET_TRAIN[1]download also training data with imagenet