modify Tensor

mindspore/common/__init__.py

@@ -17,13 +17,13 @@ from . import dtype
 from .api import ms_function
 from .dtype import *
 from .parameter import Parameter, ParameterTuple
-from .tensor import MetaTensor, Tensor, RowTensor, SparseTensor
+from .tensor import Tensor, RowTensor, SparseTensor
 from .seed import set_seed, get_seed
 
 
 __all__ = dtype.__all__
 __all__.extend([
-    "MetaTensor", "Tensor", "RowTensor", "SparseTensor",  # tensor
+    "Tensor", "RowTensor", "SparseTensor",  # tensor
     'ms_function',  # api
     'Parameter', 'ParameterTuple',  # parameter
     "dtype",

mindspore/common/parameter.py

@@ -100,7 +100,6 @@ class Parameter(Tensor_):
         ...     def construct(self, x):
         ...         out = self.matmul(self.weight, x)
         ...         return out
-        >>> context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
         >>> net = Net()
         >>> x = Tensor(np.ones((2,1)))
         >>> print(net(x))
@@ -113,15 +112,14 @@ class Parameter(Tensor_):
     __base_type__ = {}
 
     def __new__(cls, default_input, *args, **kwargs):
+        init_data_flag = bool(isinstance(default_input, Tensor) and default_input.has_init)
         input_class, *class_init_args = Parameter._get_parameter_new_args(default_input)
         new_type = Parameter._get_base_class(input_class)
         obj = input_class.__new__(new_type)
         input_class.__init__(obj, *class_init_args)
         # it's better to make the Initializer a kind of tensor.
         obj.init_mode = None
-        obj.is_default_input_init = False
-        if isinstance(default_input, Tensor) and default_input.has_init:
-            obj.is_default_input_init = True
+        obj.is_default_input_init = init_data_flag
         if obj.has_init:
             obj.init_mode = default_input
         return obj

mindspore/common/tensor.py

@@ -19,11 +19,10 @@ from mindspore import log as logger
 from mindspore.communication.management import get_rank, get_group_size
 from . import dtype as mstype
 from ._register_for_tensor import tensor_operator_registry
-from .._c_expression import MetaTensor
 from .._c_expression import Tensor as Tensor_
 from .._checkparam import Validator as validator
 
-__all__ = ['Tensor', 'MetaTensor', 'RowTensor', 'SparseTensor']
+__all__ = ['Tensor', 'RowTensor', 'SparseTensor']
 np_types = (np.int8, np.int16, np.int32, np.int64,
             np.uint8, np.uint16, np.uint32, np.uint64, np.float16,
             np.float32, np.float64, np.bool_)
@@ -41,6 +40,9 @@ class Tensor(Tensor_):
         dtype (:class:`mindspore.dtype`): Input data should be None, bool or numeric type defined in `mindspore.dtype`.
             The argument is used to define the data type of the output tensor. If it is None, the data type of the
             output tensor will be as same as the `input_data`. Default: None.
+        shape (Union[tuple, list, int]): A list of integers, a tuple of integers or an integer as the shape of
+            output. Default: None.
+        init (class:'Initializer'): the information of init data.
 
     Outputs:
         Tensor, with the same shape as `input_data`.
@@ -65,6 +67,12 @@ class Tensor(Tensor_):
         if isinstance(input_data, np_types):
             input_data = np.array(input_data)
 
+        if input_data is not None and shape is not None and input_data.shape != shape:
+            raise ValueError("input_data.shape and shape should be same.")
+
+        if init is not None and (shape is None or dtype is None):
+            raise ValueError("init, dtype and shape must have values at the same time.")
+
         if ((input_data is not None and init is None) or (input_data is None and init is not None)) is False:
             raise TypeError("input_data and init can not be None at the same time.")
 
@@ -306,10 +314,12 @@ class Tensor(Tensor_):
 
     def asnumpy(self):
         """Convert tensor to numpy array."""
+        self.init_check()
         return Tensor_.asnumpy(self)
 
     def _flush_from_cache(self):
         """Flush cache data to host if tensor is cache enable."""
+        self.init_check()
         Tensor_._flush_from_cache(self)
 
     def all(self, axis=(), keep_dims=False):
@@ -327,6 +337,7 @@ class Tensor(Tensor_):
             Tensor, has the same data type as x.
         """
 
+        self.init_check()
         if axis is None:
             axis = ()
         return tensor_operator_registry.get('all')(keep_dims)(self, axis)
@@ -346,6 +357,7 @@ class Tensor(Tensor_):
             Tensor, has the same data type as x.
         """
 
+        self.init_check()
         if axis is None:
             axis = ()
         return tensor_operator_registry.get('any')(keep_dims)(self, axis)
@@ -360,6 +372,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same dimension as the input shape.
         """
+        self.init_check()
         if not shape:
             raise ValueError("The shape variable should not be empty")
         if isinstance(shape[0], tuple):
@@ -379,6 +392,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same dimension as input tensor.
         """
+        self.init_check()
         return tensor_operator_registry.get('broadcast_to')(x.shape)(self)
 
     def abs(self):
@@ -388,6 +402,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same data type as x.
         """
+        self.init_check()
         return tensor_operator_registry.get('abs')()(self)
 
     def mean(self, axis=(), keep_dims=False):
@@ -404,6 +419,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same data type as x.
         """
+        self.init_check()
         if axis is None:
             axis = ()
         return tensor_operator_registry.get('mean')(keep_dims)(self, axis)
@@ -429,6 +445,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same dimension as input tensor, with axes suitably permuted.
         """
+        self.init_check()
         perm = validator.check_transpose_axis(axes, self.ndim)
         return tensor_operator_registry.get('transpose')()(self, perm)
 
@@ -446,6 +463,7 @@ class Tensor(Tensor_):
             reshaped_tensor(Tensor): This will be a new view object if possible;
             otherwise, it will be a copy.
         """
+        self.init_check()
         new_shape = validator.check_reshape_shp(shape)
         return tensor_operator_registry.get('reshape')()(self, new_shape)
 
@@ -457,6 +475,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same data type as x.
         """
+        self.init_check()
         reshape_op = tensor_operator_registry.get('reshape')()
         return reshape_op(self, (-1,))
 
@@ -472,6 +491,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, has the same data type as x.
         """
+        self.init_check()
         reshape_op = tensor_operator_registry.get('reshape')()
         trans_op = tensor_operator_registry.get('transpose')()
 
@@ -493,6 +513,7 @@ class Tensor(Tensor_):
         Returns:
             Transposed tensor, has the same data type as the original tensor x.
         """
+        self.init_check()
         axis1, axis2 = validator.check_swapaxes_axis((axis1, axis2), self.ndim)
 
         if axis1 == axis2:
@@ -521,6 +542,7 @@ class Tensor(Tensor_):
         Returns:
             Tensor, with all or a subset of the dimensions of length 1 removed.
         """
+        self.init_check()
         if axis is None:
             return tensor_operator_registry.get('squeeze')(self)
         new_shape = validator.prepare_shape_for_squeeze(self.shape, axis)
@@ -542,12 +564,18 @@ class Tensor(Tensor_):
         Returns:
             Tensor, with the designated dtype.
         """
+        self.init_check()
         dtype = validator.check_astype_dtype(dtype)
         if not copy and dtype == self.dtype:
             return self
         return tensor_operator_registry.get('cast')(self, dtype)
 
 
+    def init_check(self):
+        if self.has_init:
+            self.init_data()
+        return self
+
     def init_data(self, slice_index=None, shape=None, opt_shard_group=None):
         """
         Get the tensor format data of this Tensor.
@@ -601,7 +629,9 @@ class Tensor(Tensor_):
             rank = get_rank(opt_shard_group)
             size = get_group_size(opt_shard_group)
             data = np.split(data, size)[rank]
-        return Tensor(data, dtype=self.dtype)
+        self.init = None
+        self.assign_value(Tensor(data, dtype=self.dtype))
+        return self
 
 
     def to_tensor(self, slice_index=None, shape=None, opt_shard_group=None):

tests/ut/python/ir/test_tensor_py.py

@@ -16,6 +16,7 @@
 import numpy as np
 
 import mindspore as ms
+import mindspore.common.initializer as init
 from mindspore.common.api import _executor
 from mindspore.nn import Cell
 from mindspore.ops import operations as P
@@ -99,6 +100,12 @@ def test_asnumpy():
     assert a.asnumpy().all() == npd.all()
 
 
+def test_initializer_asnumpy():
+    npd = np.ones((2, 3))
+    a = init.initializer('one', [2, 3], ms.int32)
+    assert a.asnumpy().all() == npd.all()
+
+
 def test_print():
     a = ms.Tensor(np.ones((2, 3)))
     a.set_dtype(ms.int32)

tests/ut/python/pipeline/parse/test_expand_as.py

@@ -13,7 +13,9 @@
 # limitations under the License.
 # ============================================================================
 """ test expand_as"""
+import mindspore as ms
 import mindspore.nn as nn
+import mindspore.common.initializer as init
 from mindspore import Tensor
 from mindspore import context
 
@@ -34,6 +36,20 @@ def test_expand_as():
     net()
 
 
+def test_initializer_expand_as():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.t1 = init.initializer('one', [1, 3], ms.float32)
+            self.t2 = init.initializer('one', [2, 3], ms.float32)
+
+        def construct(self):
+            return self.t1.expand_as(self.t2)
+
+    net = Net()
+    net()
+
+
 def test_expand_as_parameter():
     class Net(nn.Cell):
         def __init__(self):

tests/ut/python/pipeline/parse/test_view.py

@@ -15,7 +15,9 @@
 """ test view"""
 import pytest
 
+import mindspore as ms
 import mindspore.nn as nn
+import mindspore.common.initializer as init
 from mindspore import Tensor
 from mindspore import context
 
@@ -35,6 +37,19 @@ def test_view():
     net()
 
 
+def test_view_initializer():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.value = init.initializer('normal', [2, 3], ms.float32)
+
+        def construct(self):
+            return self.value.view(-1)
+
+    net = Net()
+    net()
+
+
 def test_view_1():
     class Net(nn.Cell):
         def __init__(self):