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- # Copyright 2021 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.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.common.api import ms_function
- from mindspore.common.parameter import Parameter
- from mindspore.ops import operations as P
- import mindspore as ms
-
-
- def create_tensor(capcity, shapes, dtypes):
- buffer = []
- for i in range(len(shapes)):
- buffer.append(Tensor(np.zeros(((capcity,)+shapes[i])), dtypes[i]))
- return buffer
-
-
- class RLBuffer(nn.Cell):
- def __init__(self, batch_size, capcity, shapes, types):
- super(RLBuffer, self).__init__()
- self.buffer = create_tensor(capcity, shapes, types)
- self._capacity = capcity
- self.count = Parameter(Tensor(0, ms.int32), name="count")
- self.head = Parameter(Tensor(0, ms.int32), name="head")
- self.buffer_append = P.BufferAppend(self._capacity, shapes, types)
- self.buffer_get = P.BufferGetItem(self._capacity, shapes, types)
- self.buffer_sample = P.BufferSample(
- self._capacity, batch_size, shapes, types)
- self.randperm = P.Randperm(max_length=capcity, pad=-1)
- self.reshape = P.Reshape()
-
- @ms_function
- def append(self, exps):
- return self.buffer_append(self.buffer, exps, self.count, self.head)
-
- @ms_function
- def get(self, index):
- return self.buffer_get(self.buffer, self.count, self.head, index)
-
- @ms_function
- def sample(self):
- return self.buffer_sample(self.buffer, self.count, self.head)
-
-
- s = Tensor(np.array([2, 2, 2, 2]), ms.float32)
- a = Tensor(np.array([0, 1]), ms.int32)
- r = Tensor(np.array([1]), ms.float32)
- s_ = Tensor(np.array([3, 3, 3, 3]), ms.float32)
- exp = [s, a, r, s_]
- exp1 = [s_, a, r, s]
-
-
- @ pytest.mark.level0
- @ pytest.mark.platform_x86_gpu_training
- @ pytest.mark.env_onecard
- def test_Buffer():
- context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
- buffer = RLBuffer(batch_size=32, capcity=100, shapes=[(4,), (2,), (1,), (4,)], types=[
- ms.float32, ms.int32, ms.float32, ms.float32])
- print("init buffer:\n", buffer.buffer)
- for _ in range(0, 110):
- buffer.append(exp)
- buffer.append(exp1)
- print("buffer append:\n", buffer.buffer)
- b = buffer.get(-1)
- print("buffer get:\n", b)
- bs = buffer.sample()
- print("buffer sample:\n", bs)
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