remove File Specific Variables from env_vars.md (#4684)

docs/env_vars.md

@@ -46,133 +46,3 @@ DEFAULT_FLOAT       | [HALF, ...]| specify the default float dtype (FLOAT32, HAL
 IMAGE               | [1-2]      | enable 2d specific optimizations
 FLOAT16             | [1]        | use float16 for images instead of float32
 PTX                 | [1]        | enable the specialized [PTX](https://docs.nvidia.com/cuda/parallel-thread-execution/) assembler for Nvidia GPUs. If not set, defaults to generic CUDA codegen backend.
-
-## 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
-
-Variable | Possible Value(s) | Description
----|---|---
-PRINTALL | [1] | print all ANE registers
-
-### extra/onnx.py
-
-Variable | Possible Value(s) | Description
----|---|---
-ONNXLIMIT | [#] | set a limit for ONNX
-DEBUGONNX | [1] | enable ONNX debugging
-
-### extra/thneed.py
-
-Variable | Possible Value(s) | Description
----|---|---
-DEBUGCL      | [1-4] | enable Debugging for OpenCL
-PRINT_KERNEL | [1]   | Print OpenCL Kernels
-
-### examples/vit.py
-
-Variable | Possible Value(s) | Description
----|---|---
-LARGE | [1] | enable larger dimension model
-
-### examples/llama.py
-
-Variable | Possible Value(s) | Description
----|---|---
-WEIGHTS | [1] | enable loading weights
-
-### examples/mlperf
-
-Variable | Possible Value(s) | Description
----|---|---
-MODEL | [resnet,retinanet,unet3d,rnnt,bert,maskrcnn] | what models to use
-
-### examples/benchmark_train_efficientnet.py
-
-Variable | Possible 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
-
-Variable | Possible 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
-
-Variable | Possible Value(s) | Description
----|---|---
-ADAM | [1] | use the Adam optimizer
-
-### examples/train_efficientnet.py
-
-Variable | Possible 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
-
-Variable | Possible Value(s) | Description
----|---|---
-TRANSFER | [1] | enable to use pretrained data
-
-### examples & test/external/external_test_opt.py
-
-Variable | Possible Value(s) | Description
----|---|---
-NUM | [18, 2] | what ResNet[18] / EfficientNet[2] to train
-
-### test/test_ops.py
-
-Variable | Possible Value(s) | Description
----|---|---
-PRINT_TENSORS | [1] | print tensors
-FORWARD_ONLY  | [1] | use forward operations only
-
-### test/test_speed_v_torch.py
-
-Variable | Possible Value(s) | Description
----|---|---
-TORCHCUDA | [1] | enable the torch cuda backend
-
-### test/external/external_test_gpu_ast.py
-
-Variable | Possible Value(s) | Description
----|---|---
-KCACHE | [1] | enable kernel cache
-
-### test/external/external_test_opt.py
-
-Variable | Possible Value(s) | Description
----|---|---
-ENET_NUM | [-2,-1] | what EfficientNet to use
-
-### test/test_dtype.py & test/extra/test_utils.py & extra/training.py
-
-Variable | Possible Value(s) | Description
----|---|---
-CI | [1] | disables some tests for CI
-
-### examples & extra & test
-
-Variable | Possible Value(s) | Description
----|---|---
-BS | [8, 16, 32, 64, 128] | batch size to use
-
-### extra/datasets/imagenet_download.py
-
-Variable | Possible Value(s) | Description
----|---|---
-IMGNET_TRAIN | [1] | download also training data with imagenet