Updated codebase such that torch>=1.3 (#1150)

Co-authored-by: vfdev <vfdev.5@gmail.com>

Author: anmolsjoshi

.github/workflows/pytorch-version-tests.yml

@@ -11,16 +11,10 @@ jobs:
       fail-fast: false
       matrix:
         python-version: [3.5, 3.6, 3.7, 3.8]
-        pytorch-version: [1.4.0, 1.3.1, 1.2.0, 1.1.0, 1.0.1]
+        pytorch-version: [1.4.0, 1.3.1]
         exclude:
           - pytorch-version: 1.3.1
             python-version: 3.8
-          - pytorch-version: 1.2.0
-            python-version: 3.8
-          - pytorch-version: 1.1.0
-            python-version: 3.8
-          - pytorch-version: 1.0.1
-            python-version: 3.8
 
     steps:
     - uses: actions/checkout@v2

ignite/distributed/comp_models/native.py

@@ -290,11 +290,9 @@ def spawn(
             "PRODUCT": dist.ReduceOp.PRODUCT,
             "MIN": dist.ReduceOp.MIN,
             "MAX": dist.ReduceOp.MAX,
+            "AND": dist.ReduceOp.BAND,
+            "OR": dist.ReduceOp.BOR,
         }
-        if LooseVersion(torch.__version__) > LooseVersion("1.2.0"):
-            _reduce_op_map.update(
-                {"AND": dist.ReduceOp.BAND, "OR": dist.ReduceOp.BOR,}
-            )
 
         def _do_all_reduce(self, tensor: torch.Tensor, op: str = "SUM") -> torch.Tensor:
             if op not in self._reduce_op_map:

setup.py

@@ -23,7 +23,7 @@ def find_version(*file_paths):
 VERSION = find_version("ignite", "__init__.py")
 
 requirements = [
-    "torch>=1.0,<2",
+    "torch>=1.3,<2",
 ]
 
 setup(

tests/ignite/engine/test_engine.py

@@ -1,6 +1,5 @@
 import os
 import time
-from distutils.version import LooseVersion
 from unittest.mock import MagicMock, Mock, call
 
 import numpy as np
@@ -514,36 +513,6 @@ def test_multinode_distrib_gpu(distributed_context_multi_node_nccl):
     _test_run_check_triggered_events()
 
 
-@pytest.mark.skipif(LooseVersion(torch.__version__) < LooseVersion("1.2.0"), reason="No IterableDataset in torch<1.2.0")
-def test_engine_with_iterable_dataloader():
-
-    from torch.utils.data import DataLoader
-
-    def _test(epoch_length=None):
-
-        le = 50
-        num_workers = 4
-        ds = get_iterable_dataset(0, le)
-        data_loader = DataLoader(ds, num_workers=num_workers)
-
-        counter = [0]
-
-        def foo(e, b):
-            print("{}-{}: {}".format(e.state.epoch, e.state.iteration, b))
-            counter[0] += 1
-
-        engine = Engine(foo)
-        engine.run(data_loader, epoch_length=epoch_length, max_epochs=5)
-
-        epoch_length = le * num_workers if epoch_length is None else epoch_length
-        assert counter[0] == 5 * epoch_length
-
-    _test(epoch_length=20)
-
-    # tests issue : https://github.com/pytorch/ignite/issues/1076
-    _test(epoch_length=None)
-
-
 def test_engine_random_state():
     def random_data_generator():
         while True: