Add test case for CellList getattr.

tests/st/rl/test_cell_list_getattr.py

@@ -1,4 +1,4 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
+# Copyright 2021-2022 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -13,8 +13,9 @@
 # limitations under the License.
 # ============================================================================
 """ test a list of cell, and getattr by its item """
+import pytest
 import numpy as np
-from mindspore import context, nn, dtype, Tensor
+from mindspore import context, nn, dtype, Tensor, ms_function
 from mindspore.ops import operations as P
 
 
@@ -49,6 +50,26 @@ def test_list_item_getattr():
     assert np.array_equal(res.asnumpy(), expect_res.asnumpy())
 
 
+@pytest.mark.skip(reason='Not support in graph mode yet')
+def test_cell_list_getattr():
+    """
+    Feature: getattr by the item from nn.CellList.
+    Description: Support RL use method in graph mode.
+    Expectation: No exception.
+    """
+    context.set_context(mode=context.GRAPH_MODE)
+    actor_list = nn.CellList()
+    for _ in range(3):
+        actor_list.append(Actor())
+    trainer = Trainer(actor_list)
+    x = Tensor([3], dtype=dtype.float32)
+    y = Tensor([6], dtype=dtype.float32)
+    res = trainer(x, y)
+    print(f'res: {res}')
+    expect_res = Tensor([9], dtype=dtype.float32)
+    assert np.array_equal(res.asnumpy(), expect_res.asnumpy())
+
+
 class Trainer2(nn.Cell):
     def __init__(self, net_list):
         super(Trainer2, self).__init__()
@@ -80,3 +101,98 @@ def test_list_item_getattr2():
     print(f'res: {res}')
     expect_res = Tensor([27], dtype=dtype.float32)
     assert np.array_equal(res.asnumpy(), expect_res.asnumpy())
+
+
+@pytest.mark.skip(reason='Not support in graph mode yet')
+def test_cell_list_getattr2():
+    """
+    Feature: getattr by the item from nn.CellList.
+    Description: Support RL use method in graph mode.
+    Expectation: No exception.
+    """
+    context.set_context(mode=context.GRAPH_MODE)
+    actor_list = nn.CellList()
+    for _ in range(3):
+        actor_list.append(Actor())
+    trainer = Trainer2(actor_list)
+    x = Tensor([3], dtype=dtype.float32)
+    y = Tensor([6], dtype=dtype.float32)
+    res = trainer(x, y)
+    print(f'res: {res}')
+    expect_res = Tensor([27], dtype=dtype.float32)
+    assert np.array_equal(res.asnumpy(), expect_res.asnumpy())
+
+
+class MSRL(nn.Cell):
+    def __init__(self, agent):
+        super(MSRL, self).__init__()
+        self.agent = agent
+
+
+class Agent(nn.Cell):
+    def __init__(self, actor):
+        super(Agent, self).__init__()
+        self.actor = actor
+
+    def act(self, x, y):
+        out = self.actor.act(x, y)
+        return out
+
+
+class Trainer3(nn.Cell):
+    def __init__(self, msrl):
+        super(Trainer3, self).__init__()
+        self.msrl = msrl
+
+    @ms_function
+    def test(self, x, y):
+        num_actor = 0
+        output = 0
+        while num_actor < 3:
+            output += self.msrl.agent[num_actor].act(x, y)
+            num_actor += 1
+        return output
+
+
+@pytest.mark.skip(reason='Not support in graph mode yet')
+def test_list_item_getattr3():
+    """
+    Feature: getattr by the item from list of cell.
+    Description: Support RL use method in graph mode.
+    Expectation: No exception.
+    """
+    context.set_context(mode=context.GRAPH_MODE)
+    agent_list = []
+    for _ in range(3):
+        actor = Actor()
+        agent_list.append(Agent(actor))
+    msrl = MSRL(agent_list)
+    trainer = Trainer3(msrl)
+    x = Tensor([2], dtype=dtype.int32)
+    y = Tensor([3], dtype=dtype.int32)
+    res = trainer.test(x, y)
+    print(f'res: {res}')
+    expect_res = Tensor([15], dtype=dtype.int32)
+    assert np.array_equal(res.asnumpy(), expect_res.asnumpy())
+
+
+@pytest.mark.skip(reason='Not support in graph mode yet')
+def test_cell_list_getattr3():
+    """
+    Feature: getattr by the item from list of cell.
+    Description: Support RL use method in graph mode.
+    Expectation: No exception.
+    """
+    context.set_context(mode=context.GRAPH_MODE)
+    agent_list = nn.CellList()
+    for _ in range(3):
+        actor = Actor()
+        agent_list.append(Agent(actor))
+    msrl = MSRL(agent_list)
+    trainer = Trainer3(msrl)
+    x = Tensor([2], dtype=dtype.float32)
+    y = Tensor([3], dtype=dtype.float32)
+    res = trainer.test(x, y)
+    print(f'res: {res}')
+    expect_res = Tensor([15], dtype=dtype.float32)
+    assert np.array_equal(res.asnumpy(), expect_res.asnumpy())