# Copyright 2019 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Contains function to log if devices are compatible with mixed precision.""" import itertools import tensorflow.compat.v2 as tf # isort: off from tensorflow.python.platform import tf_logging _COMPAT_CHECK_PREFIX = "Mixed precision compatibility check (mixed_float16): " _COMPAT_CHECK_OK_PREFIX = _COMPAT_CHECK_PREFIX + "OK" _COMPAT_CHECK_WARNING_PREFIX = _COMPAT_CHECK_PREFIX + "WARNING" _COMPAT_CHECK_WARNING_SUFFIX = ( "If you will use compatible GPU(s) not attached to this host, e.g. by " "running a multi-worker model, you can ignore this warning. This message " "will only be logged once" ) def _dedup_strings(device_strs): """Groups together consecutive identical strings. For example, given: ['GPU 1', 'GPU 2', 'GPU 2', 'GPU 3', 'GPU 3', 'GPU 3'] This function returns: ['GPU 1', 'GPU 2 (x2)', 'GPU 3 (x3)'] Args: device_strs: A list of strings, each representing a device. Returns: A copy of the input, but identical consecutive strings are merged into a single string. """ new_device_strs = [] for device_str, vals in itertools.groupby(device_strs): num = len(list(vals)) if num == 1: new_device_strs.append(device_str) else: new_device_strs.append("%s (x%d)" % (device_str, num)) return new_device_strs def _log_device_compatibility_check(policy_name, gpu_details_list): """Logs a compatibility check if the devices support the policy. Currently only logs for the policy mixed_float16. Args: policy_name: The name of the dtype policy. gpu_details_list: A list of dicts, one dict per GPU. Each dict is the device details for a GPU, as returned by `tf.config.experimental.get_device_details()`. """ if policy_name != "mixed_float16": # TODO(b/145686977): Log if the policy is 'mixed_bfloat16'. This # requires checking if a TPU is available. return supported_device_strs = [] unsupported_device_strs = [] for details in gpu_details_list: name = details.get("device_name", "Unknown GPU") cc = details.get("compute_capability") if cc: device_str = f"{name}, compute capability {cc[0]}.{cc[1]}" if cc >= (7, 0): supported_device_strs.append(device_str) else: unsupported_device_strs.append(device_str) else: unsupported_device_strs.append( name + ", no compute capability (probably not an Nvidia GPU)" ) if unsupported_device_strs: warning_str = _COMPAT_CHECK_WARNING_PREFIX + "\n" if supported_device_strs: warning_str += ( "Some of your GPUs may run slowly with dtype policy " "mixed_float16 because they do not all have compute " "capability of at least 7.0. Your GPUs:\n" ) elif len(unsupported_device_strs) == 1: warning_str += ( "Your GPU may run slowly with dtype policy mixed_float16 " "because it does not have compute capability of at least " "7.0. Your GPU:\n" ) else: warning_str += ( "Your GPUs may run slowly with dtype policy " "mixed_float16 because they do not have compute " "capability of at least 7.0. Your GPUs:\n" ) for device_str in _dedup_strings( supported_device_strs + unsupported_device_strs ): warning_str += " " + device_str + "\n" warning_str += ( "See https://developer.nvidia.com/cuda-gpus for a list of " "GPUs and their compute capabilities.\n" ) warning_str += _COMPAT_CHECK_WARNING_SUFFIX tf_logging.warning(warning_str) elif not supported_device_strs: tf_logging.warning( "%s\n" "The dtype policy mixed_float16 may run slowly because " "this machine does not have a GPU. Only Nvidia GPUs with " "compute capability of at least 7.0 run quickly with " "mixed_float16.\n%s" % (_COMPAT_CHECK_WARNING_PREFIX, _COMPAT_CHECK_WARNING_SUFFIX) ) elif len(supported_device_strs) == 1: tf_logging.info( "%s\n" "Your GPU will likely run quickly with dtype policy " "mixed_float16 as it has compute capability of at least " "7.0. Your GPU: %s" % (_COMPAT_CHECK_OK_PREFIX, supported_device_strs[0]) ) else: tf_logging.info( "%s\n" "Your GPUs will likely run quickly with dtype policy " "mixed_float16 as they all have compute capability of at " "least 7.0" % _COMPAT_CHECK_OK_PREFIX ) _logged_compatibility_check = False def log_device_compatibility_check(policy_name): """Logs a compatibility check if the devices support the policy. Currently only logs for the policy mixed_float16. A log is shown only the first time this function is called. Args: policy_name: The name of the dtype policy. """ global _logged_compatibility_check if _logged_compatibility_check: return _logged_compatibility_check = True gpus = tf.config.list_physical_devices("GPU") gpu_details_list = [ tf.config.experimental.get_device_details(g) for g in gpus ] _log_device_compatibility_check(policy_name, gpu_details_list)