Add TRAINS experiment manager support (#1122)

* Add allegro.ai TRAINS experiment manager support

* improve docstring and type hinting, fix the bug in log_metrics, add support torch.Tensor to input into log_image

* complete missing docstring of constructor's arguments

* fix docs

* pep8

* pep8

* remove redundant typing
use logging
fix typing and pep8

* remove deprecated interface

* add TrainsLogger test

* add TrainsLogger PR in CHANGELOG

* add id/name property documentation

* change logging as log

Co-authored-by: bmartinn <>
Co-authored-by: Sou Uchida <s.aiueo32@gmail.com>

docs/source/conf.py

@@ -297,7 +297,8 @@ with open(os.path.join(PATH_ROOT, 'requirements.txt'), 'r') as fp:
             MOCK_REQUIRE_PACKAGES.append(pkg.rstrip())
 
 # TODO: better parse from package since the import name and package name may differ
-MOCK_MANUAL_PACKAGES = ['torch', 'torchvision', 'test_tube', 'mlflow', 'comet_ml', 'wandb', 'neptune']
+MOCK_MANUAL_PACKAGES = ['torch', 'torchvision', 'test_tube',
+                        'mlflow', 'comet_ml', 'wandb', 'neptune', 'trains']
 autodoc_mock_imports = MOCK_REQUIRE_PACKAGES + MOCK_MANUAL_PACKAGES
 # for mod_name in MOCK_REQUIRE_PACKAGES:
 #     sys.modules[mod_name] = mock.Mock()

docs/source/experiment_logging.rst

@@ -62,6 +62,34 @@ The Neptune.ai is available anywhere except ``__init__`` in your LightningModule
          some_img = fake_image()
          self.logger.experiment.add_image('generated_images', some_img, 0)
 
+allegro.ai TRAINS
+^^^^^^^^^^^^^^^^^
+
+`allegro.ai <https://github.com/allegroai/trains/>`_ is a third-party logger.
+To use TRAINS as your logger do the following.
+
+.. note:: See: :ref:`trains` docs.
+
+.. code-block:: python
+
+   from pytorch_lightning.loggers import TrainsLogger
+
+    trains_logger = TrainsLogger(
+        project_name="examples",
+        task_name="pytorch lightning test"
+    )
+   trainer = Trainer(logger=trains_logger)
+
+The TrainsLogger is available anywhere in your LightningModule
+
+.. code-block:: python
+
+   class MyModule(pl.LightningModule):
+
+      def __init__(self, ...):
+         some_img = fake_image()
+         self.logger.log_image('debug', 'generated_image_0', some_img, 0)
+
 Tensorboard
 ^^^^^^^^^^^
 

docs/source/experiment_reporting.rst

@@ -32,7 +32,7 @@ want to log using this trainer flag.
 Log metrics
 ^^^^^^^^^^^
 
-To plot metrics into whatever logger you passed in (tensorboard, comet, neptune, etc...)
+To plot metrics into whatever logger you passed in (tensorboard, comet, neptune, TRAINS, etc...)
 
 1. training_epoch_end, validation_epoch_end, test_epoch_end will all log anything in the "log" key of the return dict.