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Decouple printing logs to stdout from tensorboard #1376

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Decouple printing logs to stdout from tensorboard #1376

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26 changes: 18 additions & 8 deletions MaxText/metric_logger.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,6 +67,8 @@ def write_metrics(self, running_gcs_metrics, metrics, step, is_training=True):
steps_to_write = step

if metrics_to_write:
self.log_metrics(metrics_to_write, steps_to_write, is_training)

if self.config.enable_tensorboard:
self.write_metrics_to_tensorboard(metrics_to_write, steps_to_write, is_training)

Expand All @@ -76,6 +78,22 @@ def write_metrics(self, running_gcs_metrics, metrics, step, is_training=True):
if self.config.gcs_metrics and jax.process_index() == 0:
running_gcs_metrics = self.write_metrics_for_gcs(metrics_to_write, steps_to_write, running_gcs_metrics, is_training)

def _log_metrics(self, metrics, step):
"""Logs metrics via max_logging"""
max_logging.log(
f"completed step: {step}, seconds: {metrics['scalar']['perf/step_time_seconds']:.3f}, "
f"TFLOP/s/device: {metrics['scalar']['perf/per_device_tflops_per_sec']:.3f}, "
f"Tokens/s/device: {metrics['scalar']['perf/per_device_tokens_per_sec']:.3f}, "
f"total_weights: {metrics['scalar']['learning/total_weights']}, "
f"loss: {metrics['scalar']['learning/loss']:.3f}"
)

def log_metrics(self, metrics, step, is_training):
"""Prints metrics"""
with jax.spmd_mode("allow_all"):
if is_training:
self._log_metrics(metrics, step)
Comment on lines +93 to +95
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Is it necessary to gate the logging with with jax.spmd_mode("allow_all") and if metrics to write? I see a duplicate PR was created that isn't gating with those. Are the extra conditions needed here?


def write_metrics_locally(self, metrics, step):
"""Writes metrics locally for testing"""
with open(self.config.metrics_file, "a", encoding="utf8") as local_metrics_file:
Expand Down Expand Up @@ -115,14 +133,6 @@ def write_metrics_to_tensorboard(self, metrics, step, is_training):
if is_training:
full_log = step % self.config.log_period == 0

max_logging.log(
f"completed step: {step}, seconds: {metrics['scalar']['perf/step_time_seconds']:.3f}, "
f"TFLOP/s/device: {metrics['scalar']['perf/per_device_tflops_per_sec']:.3f}, "
f"Tokens/s/device: {metrics['scalar']['perf/per_device_tokens_per_sec']:.3f}, "
f"total_weights: {metrics['scalar']['learning/total_weights']}, "
f"loss: {metrics['scalar']['learning/loss']:.3f}"
)

if full_log and jax.process_index() == 0:
max_logging.log(f"To see full metrics 'tensorboard --logdir={self.config.tensorboard_dir}'")
self.writer.flush()
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