fixup! Added basic file logger Lightning-AI#1803

pytorch_lightning/loggers/__init__.py

@@ -2,13 +2,14 @@
 
 from pytorch_lightning.loggers.base import LightningLoggerBase, LoggerCollection
 from pytorch_lightning.loggers.tensorboard import TensorBoardLogger
-from pytorch_lightning.loggers.file_logger import FileLogger
+from pytorch_lightning.loggers.csv import CSVLogger
 
 
 __all__ = [
     'LightningLoggerBase',
     'LoggerCollection',
     'TensorBoardLogger',
+    'CSVLogger',
 ]
 
 try:

pytorch_lightning/loggers/file_logger.py → pytorch_lightning/loggers/csv.py

@@ -1,6 +1,9 @@
 """
-File logger
------------
+CSV logger
+----------
+
+CSV logger for basic experiment logging that does not require opening ports
+
 """
 import io
 import os
@@ -14,10 +17,25 @@
 from pytorch_lightning import _logger as log
 from pytorch_lightning.core.saving import save_hparams_to_yaml
 from pytorch_lightning.loggers.base import LightningLoggerBase
-from pytorch_lightning.utilities.distributed import rank_zero_only
+from pytorch_lightning.utilities.distributed import rank_zero_warn, rank_zero_only
 
 
 class ExperimentWriter(object):
+    r"""
+    Experiment writer for CSVLogger.
+
+    Currently supports to log hyperparameters and metrics in YAML and CSV
+    format. Creates the directory structure:
+    ```
+        log_dir/
+            hparams.yaml
+            metrics.csv
+    ```
+
+    Args:
+        log_dir: Directory for the experiment logs
+    """
+
     NAME_HPARAMS_FILE = 'hparams.yaml'
     NAME_METRICS_FILE = 'metrics.csv'
 
@@ -27,15 +45,21 @@ def __init__(self, log_dir):
         self.metrics_keys = ["step"]
 
         self.log_dir = log_dir
-        if not os.path.exists(log_dir):
-            os.makedirs(log_dir)
+        if os.path.exists(self.log_dir):
+            rank_zero_warn(
+                f"Experiment logs directory {self.log_dir} exists and is not empty. "
+                "Previous log files in this directory will be deleted when the new ones are saved!"
+            )
+        os.makedirs(self.log_dir, exist_ok=True)
 
         self.metrics_file_path = os.path.join(self.log_dir, self.NAME_METRICS_FILE)
 
     def log_hparams(self, params):
+        """Record hparams"""
         self.hparams.update(params)
 
     def log_metrics(self, metrics_dict, step=None):
+        """Record metrics"""
         def _handle_value(value):
             if isinstance(value, torch.Tensor):
                 return value.item()
@@ -53,6 +77,7 @@ def _handle_value(value):
         self.metrics.append(new_row)
 
     def save(self):
+        """Save recorded hparams and metrics into files"""
         hparams_file = os.path.join(self.log_dir, self.NAME_HPARAMS_FILE)
         save_hparams_to_yaml(hparams_file, self.hparams)
 
@@ -63,15 +88,15 @@ def save(self):
                 self.writer.writerows(self.metrics)
 
 
-class FileLogger(LightningLoggerBase):
+class CSVLogger(LightningLoggerBase):
     r"""
     Log to local file system in yaml and CSV format. Logs are saved to
     ``os.path.join(save_dir, name, version)``.
 
     Example:
         >>> from pytorch_lightning import Trainer
-        >>> from pytorch_lightning.loggers import FileLogger
-        >>> logger = FileLogger("logs", name="my_exp_name")
+        >>> from pytorch_lightning.loggers import CSVLogger
+        >>> logger = CSVLogger("logs", name="my_exp_name")
         >>> trainer = Trainer(logger=logger)
 
     Args:

tests/loggers/test_file_logger.py → tests/loggers/test_csv.py

@@ -4,7 +4,7 @@
 import torch
 import os
 
-from pytorch_lightning.loggers import FileLogger
+from pytorch_lightning.loggers import CSVLogger
 
 
 def test_file_logger_automatic_versioning(tmpdir):
@@ -14,7 +14,7 @@ def test_file_logger_automatic_versioning(tmpdir):
     root_dir.mkdir("version_0")
     root_dir.mkdir("version_1")
 
-    logger = FileLogger(save_dir=tmpdir, name="exp")
+    logger = CSVLogger(save_dir=tmpdir, name="exp")
 
     assert logger.version == 2
 
@@ -27,7 +27,7 @@ def test_file_logger_manual_versioning(tmpdir):
     root_dir.mkdir("version_1")
     root_dir.mkdir("version_2")
 
-    logger = FileLogger(save_dir=tmpdir, name="exp", version=1)
+    logger = CSVLogger(save_dir=tmpdir, name="exp", version=1)
 
     assert logger.version == 1
 
@@ -39,7 +39,7 @@ def test_file_logger_named_version(tmpdir):
     tmpdir.mkdir(exp_name)
     expected_version = "2020-02-05-162402"
 
-    logger = FileLogger(save_dir=tmpdir, name=exp_name, version=expected_version)
+    logger = CSVLogger(save_dir=tmpdir, name=exp_name, version=expected_version)
     logger.log_hyperparams({"a": 1, "b": 2})
     logger.save()
     assert logger.version == expected_version
@@ -50,15 +50,15 @@ def test_file_logger_named_version(tmpdir):
 @pytest.mark.parametrize("name", ['', None])
 def test_file_logger_no_name(tmpdir, name):
     """Verify that None or empty name works"""
-    logger = FileLogger(save_dir=tmpdir, name=name)
+    logger = CSVLogger(save_dir=tmpdir, name=name)
     logger.save()
     assert logger.root_dir == tmpdir
     assert os.listdir(tmpdir / 'version_0')
 
 
 @pytest.mark.parametrize("step_idx", [10, None])
 def test_file_logger_log_metrics(tmpdir, step_idx):
-    logger = FileLogger(tmpdir)
+    logger = CSVLogger(tmpdir)
     metrics = {
         "float": 0.3,
         "int": 1,
@@ -70,7 +70,7 @@ def test_file_logger_log_metrics(tmpdir, step_idx):
 
 
 def test_file_logger_log_hyperparams(tmpdir):
-    logger = FileLogger(tmpdir)
+    logger = CSVLogger(tmpdir)
     hparams = {
         "float": 0.3,
         "int": 1,