diff --git a/pytorch_lightning/core/saving.py b/pytorch_lightning/core/saving.py
index 429ebd298c7795..485985e57fac2a 100644
--- a/pytorch_lightning/core/saving.py
+++ b/pytorch_lightning/core/saving.py
@@ -279,8 +279,8 @@ def load_hparams_from_tags_csv(tags_csv: str) -> Dict[str, Any]:
         rank_zero_warn(f"Missing Tags: {tags_csv}.", RuntimeWarning)
         return {}
 
-    with cloud_open(tags_csv, "r") as fp:
-        csv_reader = csv.reader(fp.read(), delimiter=",")
+    with cloud_open(tags_csv, "r", newline="") as fp:
+        csv_reader = csv.reader(fp, delimiter=",")
         tags = {row[0]: convert(row[1]) for row in list(csv_reader)[1:]}
 
     return tags
diff --git a/pytorch_lightning/utilities/cloud_io.py b/pytorch_lightning/utilities/cloud_io.py
index 2d9b0dfa6491e9..d344ed39c29c8b 100644
--- a/pytorch_lightning/utilities/cloud_io.py
+++ b/pytorch_lightning/utilities/cloud_io.py
@@ -22,8 +22,6 @@
 # only support remote cloud paths if newer
 modern_gfile = version.parse(tensorboard.version.VERSION) >= version.parse('2.0')
 
-import torch
-
 
 def load(path_or_url: str, map_location=None):
     if urlparse(path_or_url).scheme == '' or Path(path_or_url).drive:  # no scheme or with a drive letter
@@ -32,7 +30,7 @@ def load(path_or_url: str, map_location=None):
 
 
 def cloud_open(path: pathlike, mode: str, newline:str = None):
-    if not modern_gfile or sys.platform == "win32":
+    if not modern_gfile:
         log.debug(
             "tenosrboard.compat gfile does not work on older versions "
             "of tensorboard normal local file open."
@@ -48,7 +46,7 @@ def cloud_open(path: pathlike, mode: str, newline:str = None):
         return gfile.GFile(path, mode)
     except NotImplementedError as e:
         # minimal dependencies are installed and only local files will work
-        return open(path, mode)
+        return open(path, mode, newline=newline)
 
 
 def makedirs(path: pathlike):
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 75bdc297e3d4e9..e594b88af1e722 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -5,8 +5,6 @@
 import pickle
 import sys
 import types
-import boto3
-import botocore
 from argparse import Namespace
 from pathlib import Path
 from unittest.mock import patch
@@ -17,7 +15,6 @@
 import torch
 from packaging import version
 from omegaconf import OmegaConf
-from moto import mock_s3
 
 import tests.base.develop_utils as tutils
 from pytorch_lightning import Callback, LightningModule, Trainer
@@ -1081,42 +1078,6 @@ def test_trainer_pickle(tmpdir):
     cloudpickle.dumps(trainer)
 
 
-@pytest.fixture(scope="function")
-def aws_credentials():
-    """Mocked AWS Credentials for moto."""
-    os.environ["AWS_ACCESS_KEY_ID"] = "testing"  # nosec
-    os.environ["AWS_SECRET_ACCESS_KEY"] = "testing"  # nosec
-    os.environ["AWS_SECURITY_TOKEN"] = "testing"  # nosec
-    os.environ["AWS_SESSION_TOKEN"] = "testing"  # nosec
-
-
-@pytest.mark.skipif(platform.system() == "Windows", reason="Saving to remote paths is not supported on Windows")
-@pytest.mark.skipif(
-    version.parse(tensorboard.version.VERSION) < version.parse("2.0"), reason="remote paths require tensorboard>=2.0"
-)
-def test_trainer_s3_path(monkeypatch,aws_credentials):
-    """Test that we can save to remote directories."""
-
-    # put everything on a remote s3 path
-    monkeypatch.setenv("TORCH_HOME", "s3://test_bucket/")
-
-    # set $TORCH_HOME, which determines torch hub's cache path, to tmpdir
-    model = EvalModelTemplate()
-    with mock_s3():
-        conn = boto3.resource("s3", region_name="us-east-1")
-        conn.create_bucket(Bucket="test_bucket")
-        tb_logger = TensorBoardLogger('s3://test_bucket/logs/')  # use an s3 path
-        trainer = Trainer(max_epochs=1, default_root_dir="s3://test_bucket/outputpath/", logger=tb_logger)
-        result = trainer.fit(model)
-
-    # Explicitly fail if not using mock s3 to indicate it tries to write to
-    # a remote location and fails if s3 is not setup
-    with pytest.raises(botocore.exceptions.ClientError):
-        tb_logger = TensorBoardLogger('s3://test_bucket/logs/')
-        trainer = Trainer(max_epochs=1, default_root_dir="s3://test_bucket/outputpath_fail/", logger=tb_logger)
-        result = trainer.fit(model)
-
-
 def test_trainer_setup_call(tmpdir):
     """Test setup call with fit and test call."""