Merge branch 'master' into hh/develop/crawler-ragdoll-updates

docs/Getting-Started.md

 ### Observing Training Progress
 
 Once you start training using `mlagents-learn` in the way described in the
-previous section, the `ml-agents` directory will contain a `summaries`
+previous section, the `ml-agents` directory will contain a `results`
-tensorboard --logdir=summaries
+tensorboard --logdir=results
 ```
 
 Then navigate to `localhost:6006` in your browser to view the TensorBoard

ml-agents/mlagents/trainers/learn.py

         base_path = "results"
         write_path = os.path.join(base_path, checkpoint_settings.run_id)
         maybe_init_path = (
-            os.path.join(base_path, checkpoint_settings.run_id)
+            os.path.join(base_path, checkpoint_settings.initialize_from)
             if checkpoint_settings.initialize_from
             else None
         )

ml-agents/mlagents/trainers/tests/test_learn.py

         {}
     """
 
+MOCK_INITIALIZE_YAML = """
+    behaviors:
+        {}
+    checkpoint_settings:
+        initialize_from: notuselessrun
+    """
+
 MOCK_PARAMETER_YAML = """
     behaviors:
         {}
         seed: 9870
     checkpoint_settings:
         run_id: uselessrun
+        initialize_from: notuselessrun
     debug: false
     """
 
     mock_env.external_brain_names = []
     mock_env.academy_name = "TestAcademyName"
     create_environment_factory.return_value = mock_env
-    load_config.return_value = yaml.safe_load(MOCK_YAML)
+    load_config.return_value = yaml.safe_load(MOCK_INITIALIZE_YAML)
 
     mock_init = MagicMock(return_value=None)
     with patch.object(TrainerController, "__init__", mock_init):
                 sampler_manager_mock.return_value,
                 None,
             )
-            handle_dir_mock.assert_called_once_with("results/ppo", False, False, None)
+            handle_dir_mock.assert_called_once_with(
+                "results/ppo", False, False, "results/notuselessrun"
+            )
             write_timing_tree_mock.assert_called_once_with("results/ppo/run_logs")
             write_run_options_mock.assert_called_once_with("results/ppo", options)
     StatsReporter.writers.clear()  # make sure there aren't any writers as added by learn.py
     assert opt.checkpoint_settings.resume is False
     assert opt.checkpoint_settings.inference is False
     assert opt.checkpoint_settings.run_id == "ppo"
+    assert opt.checkpoint_settings.initialize_from is None
     assert opt.env_settings.seed == -1
     assert opt.env_settings.base_port == 5005
     assert opt.env_settings.num_envs == 1
         "--seed=7890",
         "--train",
         "--base-port=4004",
+        "--initialize-from=testdir",
         "--num-envs=2",
         "--no-graphics",
         "--debug",
     assert opt.env_settings.env_path == "./myenvfile"
     assert opt.parameter_randomization is None
     assert opt.checkpoint_settings.run_id == "myawesomerun"
+    assert opt.checkpoint_settings.initialize_from == "testdir"
     assert opt.env_settings.seed == 7890
     assert opt.env_settings.base_port == 4004
     assert opt.env_settings.num_envs == 2
     assert opt.env_settings.env_path == "./oldenvfile"
     assert opt.parameter_randomization is None
     assert opt.checkpoint_settings.run_id == "uselessrun"
+    assert opt.checkpoint_settings.initialize_from == "notuselessrun"
     assert opt.env_settings.seed == 9870
     assert opt.env_settings.base_port == 4001
     assert opt.env_settings.num_envs == 4