move nn/distribution to nn/probability/distribution

mindspore/nn/__init__.py

@@ -17,14 +17,14 @@ Neural Networks Cells.
 
 Pre-defined building blocks or computing units to construct Neural Networks.
 """
-from . import layer, loss, optim, metrics, wrap, distribution
+from . import layer, loss, optim, metrics, wrap, probability
 from .cell import Cell, GraphKernel
 from .layer import *
 from .loss import *
 from .optim import *
 from .metrics import *
 from .wrap import *
-from .distribution import *
+from .probability import *
 
 
 __all__ = ["Cell", "GraphKernel"]
@@ -33,7 +33,7 @@ __all__.extend(loss.__all__)
 __all__.extend(optim.__all__)
 __all__.extend(metrics.__all__)
 __all__.extend(wrap.__all__)
-__all__.extend(distribution.__all__)
+__all__.extend(probability.__all__)
 
 
 __all__.sort()

mindspore/nn/probability/__init__.py

@@ -0,0 +1,24 @@
+# Copyright 2020 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.
+# ============================================================================
+"""
+Probability.
+
+The high-level components(Distributions) used to construct the probabilistic network.
+"""
+
+from .distribution import *
+
+__all__ = []
+__all__.extend(distribution.__all__)

mindspore/nn/probability/distribution/_utils/utils.py

@@ -16,9 +16,9 @@
 """Utitly functions to help distribution class."""
 import numpy as np
 from mindspore.ops import _utils as utils
-from ....common.tensor import Tensor
-from ....common.parameter import Parameter
-from ....common import dtype as mstype
+from mindspore.common.tensor import Tensor
+from mindspore.common.parameter import Parameter
+from mindspore.common import dtype as mstype
 
 def cast_to_tensor(t, dtype=mstype.float32):
     """

mindspore/nn/probability/distribution/bernoulli.py

@@ -13,10 +13,10 @@
 # limitations under the License.
 # ============================================================================
 """Bernoulli Distribution"""
+from mindspore.common import dtype as mstype
 from mindspore.ops import operations as P
 from .distribution import Distribution
 from ._utils.utils import cast_to_tensor, check_prob
-from ...common import dtype as mstype
 
 class Bernoulli(Distribution):
     """

mindspore/nn/probability/distribution/distribution.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 """basic"""
-from ..cell import Cell
+from mindspore.nn.cell import Cell
 from ._utils.utils import calc_broadcast_shape_from_param, check_scalar_from_param
 
 class Distribution(Cell):

mindspore/nn/probability/distribution/exponential.py

@@ -15,8 +15,8 @@
 """Exponential Distribution"""
 import numpy as np
 from mindspore.ops import operations as P
+from mindspore.common import dtype as mstype
 from .distribution import Distribution
-from ...common import dtype as mstype
 from ._utils.utils import cast_to_tensor, check_greater_zero
 
 class Exponential(Distribution):

mindspore/nn/probability/distribution/geometric.py

@@ -15,9 +15,9 @@
 """Geometric Distribution"""
 import numpy as np
 from mindspore.ops import operations as P
+from mindspore.common import dtype as mstype
 from .distribution import Distribution
 from ._utils.utils import cast_to_tensor, check_prob
-from ...common import dtype as mstype
 
 class Geometric(Distribution):
     """

mindspore/nn/probability/distribution/normal.py

@@ -16,10 +16,11 @@
 import numpy as np
 from mindspore.ops import operations as P
 from mindspore.ops import composite as C
+from mindspore.common import dtype as mstype
+from mindspore.context import get_context
 from .distribution import Distribution
 from ._utils.utils import convert_to_batch, check_greater_equal_zero
-from ...common import dtype as mstype
-from ...context import get_context
+
 
 class Normal(Distribution):
     """

mindspore/nn/probability/distribution/uniform.py

@@ -14,8 +14,8 @@
 # ============================================================================
 """Uniform Distribution"""
 from mindspore.ops import operations as P
+from mindspore.common import dtype as mstype
 from .distribution import Distribution
-from ...common import dtype as mstype
 from ._utils.utils import convert_to_batch, check_greater
 
 class Uniform(Distribution):