Fix docs - missing Trainer (#1159)

* drop pandas

* formatting

docs/source/early_stopping.rst

@@ -11,7 +11,7 @@ Enable Early Stopping
 ---------------------
 There are two ways to enable early stopping.
 
-.. note:: See: :ref:`trainer`
+.. seealso:: :ref:`trainer`
 
 .. code-block:: python
 
@@ -35,4 +35,4 @@ To disable early stopping pass ``False`` to the `early_stop_callback`.
 Note that ``None`` will not disable early stopping but will lead to the
 default behaviour.
 
-.. note:: See: :ref:`trainer`
+.. seealso:: :ref:`trainer`

docs/source/experiment_logging.rst

@@ -7,7 +7,7 @@ Comet.ml
 `Comet.ml <https://www.comet.ml/site/>`_ is a third-party logger.
 To use CometLogger as your logger do the following.
 
-.. note:: See: :ref:`comet` docs.
+.. seealso:: :ref:`comet` docs.
 
 .. code-block:: python
 
@@ -38,7 +38,7 @@ Neptune.ai
 `Neptune.ai <https://neptune.ai/>`_ is a third-party logger.
 To use Neptune.ai as your logger do the following.
 
-.. note:: See: :ref:`neptune` docs.
+.. seealso:: :ref:`neptune` docs.
 
 .. code-block:: python
 
@@ -68,7 +68,7 @@ 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.
+.. seealso:: :ref:`trains` docs.
 
 .. code-block:: python
 
@@ -95,7 +95,7 @@ Tensorboard
 
 To use `Tensorboard <https://pytorch.org/docs/stable/tensorboard.html>`_ as your logger do the following.
 
-.. note:: See: TensorBoardLogger :ref:`tf-logger`
+.. seealso:: TensorBoardLogger :ref:`tf-logger`
 
 .. code-block:: python
 
@@ -121,7 +121,7 @@ Test Tube
 `Test Tube <https://github.com/williamFalcon/test-tube>`_ is a tensorboard logger but with nicer file structure.
 To use TestTube as your logger do the following.
 
-.. note:: See: TestTube :ref:`testTube`
+.. seealso:: TestTube :ref:`testTube`
 
 .. code-block:: python
 
@@ -146,7 +146,7 @@ Wandb
 `Wandb <https://www.wandb.com/>`_ is a third-party logger.
 To use Wandb as your logger do the following.
 
-.. note:: See: :ref:`wandb` docs
+.. seealso:: :ref:`wandb` docs
 
 .. code-block:: python
 

docs/source/experiment_reporting.rst

@@ -22,7 +22,7 @@ Control log writing frequency
 Writing to a logger  can be expensive. In Lightning you can set the interval at which you
 want to log using this trainer flag.
 
-.. note:: See: :ref:`trainer`
+.. seealso:: :ref:`trainer`
 
 .. code-block:: python
 

docs/source/fast_training.rst

@@ -16,7 +16,7 @@ Force training for min or max epochs
 -------------------------------------
 It can be useful to force training for a minimum number of epochs or limit to a max number.
 
-.. note:: See: :ref:`trainer`
+.. seealso:: :ref:`trainer`
 
 .. code-block:: python
 

docs/source/introduction_guide.rst

@@ -472,7 +472,7 @@ First, change the runtime to TPU (and reinstall lightning).
 
 Next, install the required xla library (adds support for PyTorch on TPUs)
 
-.. code-block:: python
+.. code-block::
 
     import collections
     from datetime import datetime, timedelta

docs/source/training_tricks.rst

@@ -7,7 +7,7 @@ Accumulate gradients
 Accumulated gradients runs K small batches of size N before doing a backwards pass.
 The effect is a large effective batch size of size KxN.
 
-.. note:: See: :ref:`trainer`
+.. seealso:: :ref:`trainer`
 
 .. code-block:: python
 
@@ -20,7 +20,7 @@ Gradient Clipping
 Gradient clipping may be enabled to avoid exploding gradients. Specifically, this will `clip the gradient
 norm <https://pytorch.org/docs/stable/nn.html#torch.nn.utils.clip_grad_norm_>`_ computed over all model parameters together.
 
-.. note:: See: :ref:`trainer`
+.. seealso:: :ref:`trainer`
 
 .. code-block:: python
 

pytorch_lightning/core/lightning.py

@@ -8,8 +8,8 @@ from argparse import Namespace
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 import torch
-import torch.distributed as dist
 from torch import Tensor
+from torch.distributed import init_process_group
 from torch.nn.parallel import DistributedDataParallel
 from torch.optim import Adam
 from torch.optim.optimizer import Optimizer
@@ -859,7 +859,7 @@ class LightningModule(ABC, GradInformation, ModelIO, ModelHooks):
 
         root_node = self.trainer.resolve_root_node_address(root_node)
         os.environ['MASTER_ADDR'] = root_node
-        dist.init_process_group('nccl', rank=proc_rank, world_size=world_size)
+        init_process_group('nccl', rank=proc_rank, world_size=world_size)
 
     def configure_apex(
             self,

pytorch_lightning/loggers/trains.py

@@ -29,9 +29,7 @@ from argparse import Namespace
 from pathlib import Path
 from typing import Any, Dict, Optional, Union
 
-import PIL
 import numpy as np
-import pandas as pd
 import torch
 
 try:
@@ -79,6 +77,7 @@ class TrainsLogger(LightningLoggerBase):
 
         Example:
             .. code-block:: python
+
                 self.logger.experiment.some_trains_function()
 
         """
@@ -180,7 +179,7 @@ class TrainsLogger(LightningLoggerBase):
     @rank_zero_only
     def log_image(
             self, title: str, series: str,
-            image: Union[str, np.ndarray, PIL.Image.Image, torch.Tensor],
+            image: Union[str, np.ndarray, 'PIL.Image', torch.Tensor],
             step: Optional[int] = None) -> None:
         """Log Debug image in TRAINS experiment
 
@@ -217,7 +216,7 @@ class TrainsLogger(LightningLoggerBase):
     @rank_zero_only
     def log_artifact(
             self, name: str,
-            artifact: Union[str, Path, Dict[str, Any], pd.DataFrame, np.ndarray, PIL.Image.Image],
+            artifact: Union[str, Path, Dict[str, Any], 'pandas.DataFrame', 'numpy.ndarray', 'PIL.Image.Image'],
             metadata: Optional[Dict[str, Any]] = None, delete_after_upload: bool = False) -> None:
         """Save an artifact (file/object) in TRAINS experiment storage.