Question: I've been using tensorflow without issue, until I added the following lines of code: log_dir = os.path.join("logs", "fit", datetime.datetime.now().strftime("%Y%m%d-%H%M%S")) tensorboard_callback = TensorBoard(log_dir)  After running this I get an large amount of information printed to the console. I've tried looking at the tf.keras.callbacks.TensorBoard documentation to see if I can reduce verbosity but I don't see an option. From various stackoverflow answers I've also tried setting the verbosity of tf down but to no avail: tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR) tf.get_logger().setLevel('ERROR') tf.autograph.set_verbosity(3) os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'  I have the following specifications: Python = 3.8 Tensorflow = 2.3.1 Cuda Toolkit = 10.1 cuDNN = 7.6.4 GPU=Nvidia RTX2060  The information being printed to the console are all I messages, I've pasted these below if they add any important detail. 2020-10-19 20:59:45.205887: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll 2020-10-19 20:59:47.463539: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll 2020-10-19 20:59:48.540417: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: pciBusID: 0000:01:00.0 name: GeForce RTX 2060 computeCapability: 7.5 coreClock: 1.2GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s 2020-10-19 20:59:48.542360: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll 2020-10-19 20:59:48.562444: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll 2020-10-19 20:59:48.569770: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll 2020-10-19 20:59:48.572530: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll 2020-10-19 20:59:48.581126: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll 2020-10-19 20:59:48.586315: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll 2020-10-19 20:59:48.604682: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll 2020-10-19 20:59:48.605112: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0 2020-10-19 21:00:02.120333: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2020-10-19 21:00:02.128143: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x255e4b0b0a0 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2020-10-19 21:00:02.128792: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2020-10-19 21:00:03.014080: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: pciBusID: 0000:01:00.0 name: GeForce RTX 2060 computeCapability: 7.5 coreClock: 1.2GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s 2020-10-19 21:00:03.014776: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll 2020-10-19 21:00:03.015127: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll 2020-10-19 21:00:03.015477: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll 2020-10-19 21:00:03.015822: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll 2020-10-19 21:00:03.016172: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll 2020-10-19 21:00:03.016565: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll 2020-10-19 21:00:03.016911: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll 2020-10-19 21:00:03.017288: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0 2020-10-19 21:00:03.722569: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix: 2020-10-19 21:00:03.722942: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0 2020-10-19 21:00:03.723166: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N 2020-10-19 21:00:03.723522: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4594 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5) 2020-10-19 21:00:03.726833: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x255883632b0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2020-10-19 21:00:03.727297: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce RTX 2060, Compute Capability 7.5 2020-10-19 21:00:08.908192: I tensorflow/core/profiler/lib/profiler_session.cc:164] Profiler session started. 2020-10-19 21:00:08.908485: I tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1391] Profiler found 1 GPUs 2020-10-19 21:00:08.910553: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cupti64_101.dll 2020-10-19 21:00:09.007043: I tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1513] CUPTI activity buffer flushed 2020-10-19 21:06:09.402869: I tensorflow/core/profiler/lib/profiler_session.cc:164] Profiler session started. 2020-10-19 21:06:09.403307: I tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1513] CUPTI activity buffer flushed  Can anyone please help me to stop these messages printing to the console its making analysing other info on the console very difficult! Thanks!

Answer: You can disable debugging logs with os.environ. import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import tensorflow as tf  Possible values are as follows: 0 = all messages are logged (default behavior) 1 = INFO messages are not printed 2 = INFO and WARNING messages are not printed 3 = INFO, WARNING, and ERROR messages are not printed