readme upd

README.md

@@ -204,11 +204,15 @@ _Notice: data shaping approach is under development, expect some changes. [7.01.
  - [ ] risk-sensitive agents implementation;
  - [x] sequential and sliding time-window sampling;
  - [x] multiply instruments trading;
- - [x] docker image; - CPU version
+ - [x] docker image; - CPU version, `Signalprime` contribution, 
  - [ ] TF serving model serialisation functionality;
 
 
 ### <a name="news"></a>[News and updates:](#title)
+- 10.01.2019:
+    - **docker CPU version** is now available, contributed by `Signalprime`, 
+    (https://github.com/signalprime), see `btgym/docker/README.md` for details;
+
 - 9.02.2019:
     - **Introduction to analytic data model** notebook added to [model_based_stat_arb](./examples/model_based_stat_arb/) examples folder.
 

btgym/algorithms/worker.py

@@ -214,8 +214,8 @@ def run(self):
                     job_name='worker',
                     task_index=self.task,
                     config=tf.ConfigProto(
-                        intra_op_parallelism_threads=1,  # original was: 1
-                        inter_op_parallelism_threads=2  # original was: 2
+                        intra_op_parallelism_threads=4,  # original was: 1
+                        inter_op_parallelism_threads=4,  # original was: 2
                     )
                 )
                 self.log.debug('tf.server started.')

btgym/research/model_based/model/rec.py

@@ -177,7 +177,7 @@ def _update_embed(self, x, disjoint=False):
                         if set to True - discards embedded trajectory already being kept.
 
         Returns:
-            embedded update
+            embedded update/home/muzikin/Repos/ml_serving
 
         """
         assert len(x.shape) == 1, 'Expected 1d trajectory but got input shaped: {}'.format(x.shape)