Environment Variables


Intel® Extension for TensorFlow* provides environment variables for users to quickly adjust the configuration without any model code changes. Not all configuration options can be set via environment variable. For the rest, you’ll need to use the Python APIs. The priority for setting values is Python APIs > Environment Variables > Default value.

Configuration via Environment Variables

Environment Variables Names Default Value Definition
ITEX_TILE_AS_DEVICE 1 The default is 1, which will configure every tile as TensorFlow individual device in the scenario of one GPU card with multiple tiles. If set to 0, the whole GPU card will be treated as single TensorFlow device for execution.
ITEX_OMP_THREADPOOL 1 By default, ITEX CPU uses OMP threadpool and sets the number of inter parallelism threads to be 1. If the graph has large inter-op concurrency, it is recommended to set to 0, which uses eigen threadpool.
ITEX_FP32_MATH_MODE FP32 Sets oneDNN primitive floating-point math mode. The value can be FP32 or TF32 in GPU device and FP32 or BF32 in CPU device. Default will be FP32.
ITEX_AUTO_MIXED_PRECISION_LOG_PATH auto_mixed_precision_log_path Sets log path
ITEX_VERBOSE 1 Same semantics as TF_CPP_MAX_VLOG_LEVEL, but only works with Intel® Extension for TensorFlow*
ITEX_CPP_MIN_LOG_LEVEL 0 Same semantics as TF_CPP_MIN_LOG_LEVEL, but only works with Intel® Extension for TensorFlow*

ITEX_VERBOSE level definition

  • Level 1 is basic verbose information including device, graph, kernel and other infrastructure initialization logs, displayed only once.

  • Level 2 is help information including performance, functionality, debug and error logs, displayed only once.

  • Level 3 is normal tips or kernel execution logs. It is reported multiple times across different iterations. Note that Intel® Extension for TensorFlow* will generate large size logs using this level.

  • Level 4 is for graph information. This level can dump node or large-size whole graph information. Example:

node {
  name: "bert/encoder/layer_0/attention/output/dense/BiasAdd"
  op: "BiasAdd"
  input: "bert/encoder/layer_0/attention/output/dense/MatMul"
  input: "bert/encoder/layer_0/attention/output/dense/bias/read"
  device: "/job:localhost/replica:0/task:0/device:CPU:0"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
  attr {
    key: "data_format"
    value {
      s: "NHWC"
  • Levels 5 or higher are used for any remaining situations.

Environment Variables with Python APIs

Backend and Config Protocol

Refer to Python APIs and preserved environment variable Names.

Auto Mixed Precision Options

Refer to Advanced Auto Mixed Precision.