Rename chunk to chunk_size for all tensor expressions (#74)

* rename chunks to chunk_size, pass expression tests

README.rst

@@ -155,7 +155,7 @@ After all mars processes are started, users can run
 .. code-block:: python
 
     sess = new_session('http://<web_ip>:<ui_port>')
-    a = mt.ones((2000, 2000), chunks=200)
+    a = mt.ones((2000, 2000), chunk_size=200)
     b = mt.inner(a, a)
     sess.run(b)
 

docs/source/distributed/prepare.rst

@@ -3,7 +3,7 @@
 Graph Preparation
 =================
 When a tensor graph is submitted into Mars scheduler, a graph comprises of
-operands and chunks will be generated given ``chunks`` parameters passed in
+operands and chunks will be generated given ``chunk_size`` parameters passed in
 data sources.
 
 Graph Compose
@@ -16,8 +16,8 @@ without branches. For example, when executing code
 .. code-block:: python
 
     import mars.tensor as mt
-    a = mt.random.rand(100, chunks=100)
-    b = mt.random.rand(100, chunks=100)
+    a = mt.random.rand(100, chunk_size=100)
+    b = mt.random.rand(100, chunk_size=100)
     c = (a + b).sum()
 
 Mars will compose operand ADD and SUM into one FUSE node. RAND operands are

docs/source/install.rst

@@ -17,7 +17,7 @@ After installation, you can simply open a Python console and run
     import mars.tensor as mt
     from mars.session import new_session
 
-    a = mt.ones((5, 5), chunks=3)
+    a = mt.ones((5, 5), chunk_size=3)
     b = a * 4
     # if there isn't a local session,
     # execute will create a default one first
@@ -98,7 +98,7 @@ After all Mars processes are started, you can open a Python console and run
     import mars.tensor as mt
     from mars.session import new_session
     sess = new_session('http://<web_ip>:<ui_port>')
-    a = mt.ones((2000, 2000), chunks=200)
+    a = mt.ones((2000, 2000), chunk_size=200)
     b = mt.inner(a, a)
     sess.run(b)
 

docs/source/tensor/datasource.rst

@@ -40,16 +40,16 @@ multi-dimensional tensor will be supported later soon.
 Chunks
 ------
 
-In mars tensor, we tile a tensor into small chunks. Argument ``chunks`` is not always required,
+In mars tensor, we tile a tensor into small chunks. Argument ``chunk_size`` is not always required,
 a chunk's bytes occupation will be 128M for the default setting.
 However, user can specify each chunk's size in a more flexible way which may be adaptive to the data scale.
 The fact is that chunk's size may effect heavily on the performance of execution.
 
 The options or arguments which will effect the chunk's size are listed below:
 
 - Change ``options.tensor.chunk_size_limit`` which is 128*1024*1024(128M) by default.
-- Specify ``chunks`` as integer, like ``5000``, means chunk's size is 5000 at most for all dimensions
-- Specify ``chunks`` as tuple, like ``(5000, 3000)``
+- Specify ``chunk_size`` as integer, like ``5000``, means chunk's size is 5000 at most for all dimensions
+- Specify ``chunk_size`` as tuple, like ``(5000, 3000)``
 - Explicitly define sizes of all chunks along all dimensions, like ``((5000, 5000, 2000), (2000, 1000))``
 
 Chunks Examples
@@ -68,9 +68,9 @@ Assume we have such a tensor with the data shown below.
     4 2 4 6 2 0
     6 8 2 6 5 4
 
-We will show how different ``chunks=`` arguments will tile the tensor.
+We will show how different ``chunk_size=`` arguments will tile the tensor.
 
-``chunks=3``:
+``chunk_size=3``:
 
 .. code-block:: python
 
@@ -85,7 +85,7 @@ We will show how different ``chunks=`` arguments will tile the tensor.
     4 2 4  6 2 0
     6 8 2  6 5 4
 
-``chunks=2``:
+``chunk_size=2``:
 
 .. code-block:: python
 
@@ -101,7 +101,7 @@ We will show how different ``chunks=`` arguments will tile the tensor.
     4 2  4 6  2 0
     6 8  2 6  5 4
 
-``chunks=(3, 2)``:
+``chunk_size=(3, 2)``:
 
 .. code-block:: python
 
@@ -116,7 +116,7 @@ We will show how different ``chunks=`` arguments will tile the tensor.
     4 2  4 6  2 0
     6 8  2 6  5 4
 
-``chunks=((3, 1, 2, 2), (3, 2, 1))``:
+``chunk_size=((3, 1, 2, 2), (3, 2, 1))``:
 
 .. code-block:: python
 

docs/source/tensor/execution.rst

@@ -30,7 +30,7 @@ More than one mars tensors can be passed to ``session.run``, and calculate the r
 
 .. code-block:: python
 
-   >>> a = mt.ones((5, 5), chunks=3)
+   >>> a = mt.ones((5, 5), chunk_size=3)
    >>> b = a + 1
    >>> c = a * 4
    >>> sess.run(b, c)

mars/config.py

@@ -290,8 +290,8 @@ def validate(x):
 })
 
 # Tensor
-default_options.register_option('tensor.chunks', None, validator=any_validator(is_null, is_integer), serialize=True)
-default_options.register_option('tensor.chunk_size_limit', 128 * 1024 ** 2, validator=(is_integer, is_float))
+default_options.register_option('tensor.chunk_size', None, validator=any_validator(is_null, is_integer), serialize=True)
+default_options.register_option('tensor.chunk_store_limit', 128 * 1024 ** 2, validator=(is_integer, is_float))
 default_options.register_option('tensor.rechunk.threshold', 4, validator=is_integer, serialize=True)
 default_options.register_option('tensor.rechunk.chunk_size_limit', int(1e8), validator=is_integer, serialize=True)
 default_options.register_option('tensor.combine_size', 4, validator=is_integer, serialize=True)

mars/deploy/local/tests/test_cluster.py

@@ -65,7 +65,7 @@ def testLocalCluster(self):
             with new_session(endpoint) as session:
                 api = session._api
 
-                t = mt.ones((3, 3), chunks=2)
+                t = mt.ones((3, 3), chunk_size=2)
                 result = session.run(t)
 
                 np.testing.assert_array_equal(result, np.ones((3, 3)))
@@ -75,13 +75,13 @@ def testLocalCluster(self):
     def testLocalClusterWithWeb(self):
         with new_cluster(scheduler_n_process=2, worker_n_process=3, web=True) as cluster:
             with cluster.session as session:
-                t = mt.ones((3, 3), chunks=2)
+                t = mt.ones((3, 3), chunk_size=2)
                 result = session.run(t)
 
                 np.testing.assert_array_equal(result, np.ones((3, 3)))
 
             with new_session('http://' + cluster._web_endpoint) as session:
-                t = mt.ones((3, 3), chunks=2)
+                t = mt.ones((3, 3), chunk_size=2)
                 result = session.run(t)
 
                 np.testing.assert_array_equal(result, np.ones((3, 3)))
@@ -128,7 +128,7 @@ def testMultipleOutputTensorExecute(self):
         with new_cluster(scheduler_n_process=2, worker_n_process=2) as cluster:
             session = cluster.session
 
-            t = mt.random.rand(20, 5, chunks=5)
+            t = mt.random.rand(20, 5, chunk_size=5)
             r = mt.linalg.svd(t)
 
             res = session.run((t,) + r)

mars/operands/base.py

@@ -304,13 +304,13 @@ class Rechunk(HasInput):
     _op_type_ = OperandDef.RECHUNK
 
     _input = KeyField('input')
-    _chunks = AnyField('chunks')
+    _chunk_size = AnyField('chunk_size')
     _threshold = Int32Field('threshold')
     _chunk_size_limit = Int64Field('chunk_size_limit')
 
     @property
-    def chunks(self):
-        return self._chunks
+    def chunk_size(self):
+        return self._chunk_size
 
     @property
     def threshold(self):

mars/scheduler/tests/test_graph.py

@@ -30,8 +30,8 @@ def testGraphActor(self):
         session_id = str(uuid.uuid4())
         graph_key = str(uuid.uuid4())
 
-        arr = mt.random.randint(10, size=(10, 8), chunks=4)
-        arr_add = mt.random.randint(10, size=(10, 8), chunks=4)
+        arr = mt.random.randint(10, size=(10, 8), chunk_size=4)
+        arr_add = mt.random.randint(10, size=(10, 8), chunk_size=4)
         arr2 = arr + arr_add
 
         graph = arr2.build_graph(compose=False)
@@ -103,7 +103,7 @@ def testGraphWithSplit(self):
         session_id = str(uuid.uuid4())
         graph_key = str(uuid.uuid4())
 
-        arr = mt.ones(12, chunks=4)
+        arr = mt.ones(12, chunk_size=4)
         arr_split = mt.split(arr, 2)
         arr_sum = arr_split[0] + arr_split[1]
 
@@ -176,7 +176,7 @@ def testSameKey(self, *_):
         session_id = str(uuid.uuid4())
         graph_key = str(uuid.uuid4())
 
-        arr = mt.ones((5, 5), chunks=3)
+        arr = mt.ones((5, 5), chunk_size=3)
         arr2 = mt.concatenate((arr, arr))
 
         graph = arr2.build_graph(compose=False)

mars/scheduler/tests/test_main.py

@@ -139,8 +139,8 @@ def testMain(self):
                                                 uid=SessionActor.gen_name(session_id),
                                                 address=scheduler_address,
                                                 session_id=session_id)
-        a = ones((100, 100), chunks=30) * 2 * 1 + 1
-        b = ones((100, 100), chunks=30) * 2 * 1 + 1
+        a = ones((100, 100), chunk_size=30) * 2 * 1 + 1
+        b = ones((100, 100), chunk_size=30) * 2 * 1 + 1
         c = (a * b * 2 + 1).sum()
         graph = c.build_graph()
         targets = [c.key]
@@ -163,8 +163,8 @@ def testMain(self):
         state = self.wait_for_termination(session_ref, graph_key)
         self.assertEqual(state, GraphState.FAILED)
 
-        a = ones((100, 50), chunks=30) * 2 + 1
-        b = ones((50, 200), chunks=30) * 2 + 1
+        a = ones((100, 50), chunk_size=30) * 2 + 1
+        b = ones((50, 200), chunk_size=30) * 2 + 1
         c = a.dot(b)
         graph = c.build_graph()
         targets = [c.key]

mars/scheduler/tests/test_operand.py

@@ -151,8 +151,8 @@ def write_mock_meta():
     @mock.patch(OperandActor.__module__ + '.OperandActor._get_raw_execution_ref')
     @mock.patch(OperandActor.__module__ + '.OperandActor._free_worker_data')
     def testOperandActor(self, *_):
-        arr = mt.random.randint(10, size=(10, 8), chunks=4)
-        arr_add = mt.random.randint(10, size=(10, 8), chunks=4)
+        arr = mt.random.randint(10, size=(10, 8), chunk_size=4)
+        arr_add = mt.random.randint(10, size=(10, 8), chunk_size=4)
         arr2 = arr + arr_add
 
         session_id = str(uuid.uuid4())
@@ -163,7 +163,7 @@ def testOperandActor(self, *_):
     @mock.patch(OperandActor.__module__ + '.OperandActor._get_raw_execution_ref')
     @mock.patch(OperandActor.__module__ + '.OperandActor._free_worker_data')
     def testOperandActorWithSameKey(self, *_):
-        arr = mt.ones((5, 5), chunks=3)
+        arr = mt.ones((5, 5), chunk_size=3)
         arr2 = mt.concatenate((arr, arr))
 
         session_id = str(uuid.uuid4())
@@ -174,8 +174,8 @@ def testOperandActorWithSameKey(self, *_):
     @mock.patch(OperandActor.__module__ + '.OperandActor._get_raw_execution_ref')
     @mock.patch(OperandActor.__module__ + '.OperandActor._free_worker_data')
     def testOperandActorWithRetry(self, *_):
-        arr = mt.random.randint(10, size=(10, 8), chunks=4)
-        arr_add = mt.random.randint(10, size=(10, 8), chunks=4)
+        arr = mt.random.randint(10, size=(10, 8), chunk_size=4)
+        arr_add = mt.random.randint(10, size=(10, 8), chunk_size=4)
         arr2 = arr + arr_add
 
         session_id = str(uuid.uuid4())
@@ -190,8 +190,8 @@ def testOperandActorWithRetry(self, *_):
     @mock.patch(OperandActor.__module__ + '.OperandActor._get_raw_execution_ref')
     @mock.patch(OperandActor.__module__ + '.OperandActor._free_worker_data')
     def testOperandActorWithRetryAndFail(self, *_):
-        arr = mt.random.randint(10, size=(10, 8), chunks=4)
-        arr_add = mt.random.randint(10, size=(10, 8), chunks=4)
+        arr = mt.random.randint(10, size=(10, 8), chunk_size=4)
+        arr_add = mt.random.randint(10, size=(10, 8), chunk_size=4)
         arr2 = arr + arr_add
 
         session_id = str(uuid.uuid4())
@@ -209,8 +209,8 @@ def testOperandActorWithCancel(self, *_):
         import logging
         logging.basicConfig(level=logging.DEBUG)
 
-        arr = mt.random.randint(10, size=(10, 8), chunks=4)
-        arr_add = mt.random.randint(10, size=(10, 8), chunks=4)
+        arr = mt.random.randint(10, size=(10, 8), chunk_size=4)
+        arr_add = mt.random.randint(10, size=(10, 8), chunk_size=4)
         arr2 = arr + arr_add
 
         session_id = str(uuid.uuid4())