unset fluid in tensor (#35082)

python/paddle/framework/__init__.py

@@ -32,7 +32,7 @@ from ..fluid.core import MLUPlace  # noqa: F401
 from ..fluid.core import CustomPlace  # noqa: F401
 from ..fluid.core import VarBase  # noqa: F401
 
-from paddle.fluid import core  # noqa: F401
+from ..fluid import core  # noqa: F401
 from ..fluid.dygraph.base import no_grad_ as no_grad  # noqa: F401
 from ..fluid.dygraph.base import grad  # noqa: F401
 from .io import save  # noqa: F401
@@ -47,5 +47,10 @@ from ..fluid.framework import set_flags  # noqa: F401
 from ..fluid.dygraph.base import enable_dygraph as disable_static  # noqa: F401
 from ..fluid.dygraph.base import disable_dygraph as enable_static  # noqa: F401
 from ..fluid.framework import in_dygraph_mode as in_dynamic_mode  # noqa: F401
+from ..fluid.framework import _current_expected_place, _get_paddle_place  # noqa: F401
+from ..fluid.framework import dygraph_only  # noqa: F401
+from ..fluid.framework import convert_np_dtype_to_dtype_, _varbase_creator, OpProtoHolder  # noqa: F401
+from ..fluid.framework import _in_eager_mode  # noqa: F401
+from ..fluid.framework import _dygraph_tracer  # noqa: F401
 
 __all__ = []

python/paddle/tensor/attribute.py

@@ -14,7 +14,7 @@
 
 from __future__ import print_function
 
-from ..fluid.framework import core, in_dygraph_mode, Variable
+from ..framework import core
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_variable_and_dtype
 
@@ -23,6 +23,7 @@ from ..fluid.layers import rank  # noqa: F401
 from ..fluid.layers import shape  # noqa: F401
 import paddle
 from paddle import _C_ops
+from paddle.static import Variable
 
 __all__ = []
 
@@ -184,7 +185,7 @@ def real(x, name=None):
             #        [[1., 2., 3.],
             #         [4., 5., 6.]])
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.real(x)
 
     check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'real')
@@ -228,7 +229,7 @@ def imag(x, name=None):
             #        [[6., 5., 4.],
             #         [3., 2., 1.]])
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.imag(x)
 
     check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'imag')

python/paddle/tensor/creation.py

@@ -18,21 +18,19 @@ from paddle.common_ops_import import fill_constant
 from ..fluid.layers import utils
 
 from ..fluid.layers import tensor
-from ..fluid.framework import Variable
-from ..fluid.framework import unique_name
-from ..fluid.framework import _current_expected_place, _get_paddle_place
-from ..fluid.framework import dygraph_only
-from ..fluid.initializer import Constant
-from ..fluid.layers import core
+from ..static import Variable, device_guard
+from ..framework import _current_expected_place, _get_paddle_place
+from ..framework import dygraph_only
+from ..framework import core
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, convert_dtype
-from ..fluid.framework import convert_np_dtype_to_dtype_, in_dygraph_mode, _varbase_creator, device_guard, OpProtoHolder
+from ..framework import convert_np_dtype_to_dtype_, _varbase_creator, OpProtoHolder
 from paddle.tensor.attribute import _complex_to_real_dtype, _real_to_complex_dtype
 # TODO: define functions to get create a tensor  
 from ..fluid.layers import linspace  # noqa: F401
 import paddle
 from paddle import _C_ops
-from ..fluid.framework import _in_eager_mode
+from ..framework import _in_eager_mode
 
 __all__ = []
 
@@ -214,7 +212,7 @@ def full_like(x, fill_value, dtype=None, name=None):
         if not isinstance(dtype, core.VarDesc.VarType):
             dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.fill_any_like(x, 'value', fill_value, 'dtype', dtype)
 
     helper = LayerHelper("full_like", **locals())
@@ -648,7 +646,7 @@ def tril(x, diagonal=0, name=None):
             #        [ 9, 10,  0,  0]])
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         op = getattr(_C_ops, 'tril_triu')
         return op(x, 'diagonal', diagonal, "lower", True)
 
@@ -715,7 +713,7 @@ def triu(x, diagonal=0, name=None):
             #        [ 0, 10, 11, 12]])
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         op = getattr(_C_ops, 'tril_triu')
         return op(x, 'diagonal', diagonal, "lower", False)
 
@@ -757,7 +755,7 @@ def meshgrid(*args, **kwargs):
 
     if len(args) == 1 and isinstance(args[0], (list, tuple)):
         args = args[0]
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         num = len(args)
         out = _C_ops.meshgrid(list(args), num)
         return out
@@ -862,7 +860,7 @@ def diagflat(x, offset=0, name=None):
           #  [0 0 0 4 0]]
     """
     padding_value = 0
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if len(x.shape) == 1:
             return _C_ops.diag_v2(x, "offset", offset, "padding_value",
                                   padding_value)
@@ -976,7 +974,7 @@ def diag(x, offset=0, padding_value=0, name=None):
           print(y.numpy())
           # [4]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.diag_v2(x, "offset", offset, "padding_value",
                               padding_value)
 
@@ -1057,7 +1055,7 @@ def empty(shape, dtype=None, name=None):
 
     dtype = convert_dtype(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         shape = utils.convert_shape_to_list(shape)
         out = _C_ops.empty('shape', shape, 'dtype',
                            convert_np_dtype_to_dtype_(dtype))
@@ -1125,7 +1123,7 @@ def empty_like(x, dtype=None, name=None):
         dtype = x.dtype
     dtype = convert_dtype(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out = _C_ops.empty('shape', x.shape, 'dtype',
                            convert_np_dtype_to_dtype_(dtype))
         out.stop_gradient = True
@@ -1309,7 +1307,7 @@ def complex(real, imag, name=None):
             # [[0.+0.j 0.+1.j 0.+2.j]
             #  [1.+0.j 1.+1.j 1.+2.j]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return paddle._C_ops.complex(real, imag)
 
     check_variable_and_dtype(real, 'real', ['float32', 'float64'], 'complex')

python/paddle/tensor/einsum.py

@@ -15,9 +15,8 @@
 import itertools
 import re
 
-from ..fluid.layers import reshape, transpose
-from .linalg import matmul
-from .manipulation import squeeze, unsqueeze
+from .linalg import matmul, transpose
+from .manipulation import squeeze, unsqueeze, reshape
 from .math import multiply
 from .math import sum as paddle_sum
 
@@ -792,10 +791,10 @@ def einsum(equation, *operands):
                 - For any free label which is not present for the output, it's lowered to
                 a dummy label.
         - Examples
-            - '...ij, ...jk'，where i and k are free labels, j is dummy. The output label
+            - '...ij, ...jk', where i and k are free labels, j is dummy. The output label
             string is '...ik'
             - 'ij -> i', where i is a free label and j is a dummy label. 
-            - '...ij, ...jk -> ...ijk'，where i, j and k are all free labels.
+            - '...ij, ...jk -> ...ijk', where i, j and k are all free labels.
             - '...ij, ...jk -> ij', an invalid equation since `...` is not present for
             the output.
 

python/paddle/tensor/linalg.py

@@ -14,8 +14,9 @@
 
 import numpy as np
 from ..fluid.layer_helper import LayerHelper
-from ..fluid.framework import in_dygraph_mode, _varbase_creator, Variable, _dygraph_tracer
+from ..framework import _varbase_creator, _dygraph_tracer
 from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype
+from ..static import Variable
 
 from ..fluid.layers import transpose, cast  # noqa: F401
 from ..fluid import layers
@@ -133,7 +134,7 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None):
 
     """
     op_type = 'matmul_v2'
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         op = getattr(_C_ops, op_type)
         return op(x, y, 'trans_x', transpose_x, 'trans_y', transpose_y)
 
@@ -245,7 +246,7 @@ def norm(x, p='fro', axis=None, keepdim=False, name=None):
             raise ValueError(
                 "The dim of frobenius norm op should be None or two elements list!"
             )
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             if dim is None:
                 return _C_ops.frobenius_norm(input, 'keep_dim', keepdim,
                                              'reduce_all', True)
@@ -282,7 +283,7 @@ def norm(x, p='fro', axis=None, keepdim=False, name=None):
           axis (int, optional): None for last dimension.
           keepdim (bool, optional): Whether keep the dimensions as the `input`, Default False.
         """
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             if axis is None: axis = -1
             return _C_ops.p_norm(input, 'porder', porder, 'axis', axis,
                                  'keepdim', keepdim, 'asvector', asvector)
@@ -642,7 +643,7 @@ def cond(x, p=None, name=None):
         axis = axis if axis != None and axis != [] else [0]
         keepdim = False
 
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             abs_out = _C_ops.abs(input)
             sum_out = _C_ops.reduce_sum(abs_out, 'dim', axis, 'keepdim',
                                         keepdim, 'reduce_all', reduce_all)
@@ -699,7 +700,7 @@ def cond(x, p=None, name=None):
         reduce_all = True if axis is None or axis == [] else False
         keepdim = False
 
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             pow_out = _C_ops.pow(input, 'factor', porder)
             sum_out_1 = _C_ops.reduce_sum(pow_out, 'dim', axis, 'keepdim',
                                           keepdim, 'reduce_all', reduce_all)
@@ -753,7 +754,7 @@ def cond(x, p=None, name=None):
 
         u, s, vh = svd(input, full_matrices=False)
 
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             if porder == "nuc":
                 return _C_ops.reduce_sum(s, 'dim', axis, 'keepdim', keepdim,
                                          'reduce_all', reduce_all)
@@ -820,7 +821,7 @@ def cond(x, p=None, name=None):
             return out
 
     def empty_tensor(input, shape):
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             return input.reshape(shape)
         raise ValueError("only support x is nonempty tensor in static mode")
 
@@ -895,7 +896,7 @@ def dot(x, y, name=None):
     """
     op_type = 'dot'
     # skip var type check in dygraph mode to improve efficiency
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         op = getattr(_C_ops, op_type)
         return op(x, y)
 
@@ -1079,7 +1080,7 @@ def t(input, name=None):
             "Input(input) only support N-D (N<=2) tensor, but received "
             "length of Input(input) is %s. Perhaps you can use paddle."
             "tensor.transpose() instead." % len(input.shape))
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if len(input.shape) == 1:
             return input
         # 2-D tensor
@@ -1144,7 +1145,7 @@ def cross(x, y, axis=None, name=None):
             #  [0. 0. 0.]
             #  [0. 0. 0.]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if axis is not None:
             return _C_ops.cross(x, y, 'dim', axis)
         else:
@@ -1203,7 +1204,7 @@ def cholesky(x, upper=False, name=None):
             #  [1.25450498 0.05600871 0.06400121]]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.cholesky(x, "upper", upper)
     check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'cholesky')
     check_type(upper, 'upper', bool, 'cholesky')
@@ -1257,7 +1258,7 @@ def matrix_rank(x, tol=None, hermitian=False, name=None):
 
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if tol is None:
             tol_tensor = None
             tol_attr = 0.0
@@ -1355,7 +1356,7 @@ def bmm(x, y, name=None):
             "x's batch (shape[0]) must be equal with y's batch (shape[0]). But received x's shape: {}, y's shape: {}".
             format(x_shape, y_shape))
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.bmm(x, y)
 
     helper = LayerHelper('bmm', **locals())
@@ -1388,7 +1389,7 @@ def histogram(input, bins=100, min=0, max=0, name=None):
             result = paddle.histogram(inputs, bins=4, min=0, max=3)
             print(result) # [0, 2, 1, 0]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.histogram(input, "bins", bins, "min", min, "max", max)
 
     helper = LayerHelper('histogram', **locals())
@@ -1435,7 +1436,7 @@ def bincount(x, weights=None, minlength=0, name=None):
     if x.dtype not in [paddle.int32, paddle.int64]:
         raise TypeError("Elements in Input(x) should all be integers")
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.bincount(x, weights, "minlength", minlength)
 
     helper = LayerHelper('bincount', **locals())
@@ -1488,7 +1489,7 @@ def mv(x, vec, name=None):
             vec = paddle.to_tensor(vec_data).astype("float64")
             out = paddle.mv(x, vec)
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out = _C_ops.mv(x, vec)
         return out
 
@@ -1541,7 +1542,7 @@ def det(x, name=None):
 
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.determinant(x)
 
     check_dtype(x.dtype, 'Input', ['float32', 'float64'], 'det')
@@ -1596,7 +1597,7 @@ def slogdet(x, name=None):
         # [-0.98610914, -0.43010661, -0.10872950]])
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.slogdeterminant(x)
 
     check_dtype(x.dtype, 'Input', ['float32', 'float64'], 'slogdet')
@@ -1669,7 +1670,7 @@ def svd(x, full_matrices=False, name=None):
             #                  V * VH == I
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.svd(x, 'full_matrices', full_matrices)
     check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'svd')
     check_type(full_matrices, 'full_matrices', bool, 'svd')
@@ -1744,7 +1745,7 @@ def matrix_power(x, n, name=None):
             #  [-7.66666667 ,  8.         , -1.83333333 ],
             #  [ 1.80555556 , -1.91666667 ,  0.44444444 ]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.matrix_power(x, "n", n)
 
     check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'matrix_power')
@@ -1801,7 +1802,7 @@ def qr(x, mode="reduced", name=None):
             
             # one can verify : X = Q * R ;     
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         q, r = _C_ops.qr(x, 'mode', mode)
         if mode == "r":
             return r
@@ -1900,7 +1901,7 @@ def lu(x, pivot=True, get_infos=False, name=None):
 
             # one can verify : X = P @ L @ U ;     
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         LU, Piv, Info = _C_ops.lu(x, 'pivots', pivot)
         if get_infos:
             return LU, Piv, Info
@@ -1997,7 +1998,7 @@ def lu_unpack(x, y, unpack_ludata=True, unpack_pivots=True, name=None):
             # one can verify : X = P @ L @ U ;   
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         P, L, U = _C_ops.lu_unpack(x, y, 'unpack_ludata', unpack_ludata,
                                    'unpack_pivots', unpack_pivots)
         return P, L, U
@@ -2070,7 +2071,7 @@ def eig(x, name=None):
             #       [ (16.50471283351188+0j)  , (-5.5034820550763515+0j) ,
             #         (-0.21026087843552282+0j)])
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         w, v = _C_ops.eig(x)
         return w, v
 
@@ -2139,7 +2140,7 @@ def eigvals(x, name=None):
             "The last two dimensions of Input(x) should be equal, but received x's shape = {}".
             format(x_shape))
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.eigvals(x)
 
     helper = LayerHelper('eigvals', **locals())
@@ -2210,7 +2211,7 @@ def multi_dot(x, name=None):
         # [10, 7]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.multi_dot(x)
 
     check_type(x, 'x', (list, tuple), 'multi_dot')
@@ -2262,7 +2263,7 @@ def eigh(x, UPLO='L', name=None):
             #[ 0.3826834323650898j    , -0.9238795325112867j    ]]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.eigh(x, 'UPLO', UPLO)
 
     def __check_input(x, UPLO):
@@ -2361,7 +2362,7 @@ def pinv(x, rcond=1e-15, hermitian=False, name=None):
             # or              out * x * out = x ;
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if not hermitian:
             # combine svd and matmul op
             u, s, vt = _C_ops.svd(x, 'full_matrices', False)
@@ -2611,7 +2612,7 @@ def solve(x, y, name=None):
         print(out)
         # [2., 3.])
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.solve(x, y)
 
     inputs = {"X": [x], "Y": [y]}
@@ -2675,7 +2676,7 @@ def triangular_solve(x,
         print(out)
         # [7, -2, -5]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.triangular_solve(x, y, 'upper', upper, 'transpose',
                                        transpose, 'unitriangular',
                                        unitriangular)
@@ -2732,7 +2733,7 @@ def cholesky_solve(x, y, upper=False, name=None):
         print(out)
         # [-2.5, -7, 9.5]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.cholesky_solve(x, y, 'upper', upper)
 
     helper = LayerHelper("cholesky_solve", **locals())
@@ -2776,7 +2777,7 @@ def eigvalsh(x, UPLO='L', name=None):
             print(out_value)
             #[0.17157288, 5.82842712]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         is_test = x.stop_gradient
         values, _ = _C_ops.eigvalsh(x, 'UPLO', UPLO, 'is_test', is_test)
         return values
@@ -2904,7 +2905,7 @@ def lstsq(x, y, rcond=None, driver=None, name=None):
         elif x.dtype == paddle.float64:
             rcond = 1e-15 * max(x.shape[-2], x.shape[-1])
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         solution, rank, singular_values = _C_ops.lstsq(x, y, "rcond", rcond,
                                                        "driver", driver)
         if x.shape[-2] > x.shape[-1]:

python/paddle/tensor/logic.py

@@ -15,8 +15,7 @@
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_type, check_variable_and_dtype
 from ..fluid.layers.layer_function_generator import templatedoc
-from .. import fluid
-from ..fluid.framework import in_dygraph_mode, Variable
+from ..static import Variable
 from ..framework import VarBase as Tensor
 
 # TODO: define logic functions of a tensor  
@@ -25,8 +24,7 @@ from ..fluid.layers import logical_and  # noqa: F401
 from ..fluid.layers import logical_not  # noqa: F401
 from ..fluid.layers import logical_or  # noqa: F401
 from ..fluid.layers import logical_xor  # noqa: F401
-
-from paddle.common_ops_import import core
+import paddle
 from paddle import _C_ops
 from paddle.tensor.creation import full
 
@@ -61,7 +59,7 @@ def equal_all(x, y, name=None):
           result2 = paddle.equal_all(x, z)
           print(result2) # result2 = [False ]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.equal_all(x, y)
 
     helper = LayerHelper("equal_all", **locals())
@@ -124,7 +122,7 @@ def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
           # [True]
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.allclose(x, y, 'rtol',
                                str(rtol), 'atol',
                                str(atol), 'equal_nan', equal_nan)
@@ -182,7 +180,7 @@ def equal(x, y, name=None):
     if not isinstance(y, Variable):
         y = full(shape=[1], dtype=x.dtype, fill_value=y)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.equal(x, y)
 
     check_variable_and_dtype(
@@ -224,7 +222,7 @@ def greater_equal(x, y, name=None):
             result1 = paddle.greater_equal(x, y)
             print(result1)  # result1 = [True False True]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.greater_equal(x, y)
 
     check_variable_and_dtype(x, "x",
@@ -270,7 +268,7 @@ def greater_than(x, y, name=None):
             result1 = paddle.greater_than(x, y)
             print(result1)  # result1 = [False False True]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.greater_than(x, y)
 
     check_variable_and_dtype(x, "x",
@@ -317,7 +315,7 @@ def less_equal(x, y, name=None):
             result1 = paddle.less_equal(x, y)
             print(result1)  # result1 = [True True False]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.less_equal(x, y)
 
     check_variable_and_dtype(
@@ -360,7 +358,7 @@ def less_than(x, y, name=None):
             result1 = paddle.less_than(x, y)
             print(result1)  # result1 = [False True False]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.less_than(x, y)
 
     check_variable_and_dtype(
@@ -403,7 +401,7 @@ def not_equal(x, y, name=None):
             result1 = paddle.not_equal(x, y)
             print(result1)  # result1 = [False True True]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.not_equal(x, y)
 
     check_variable_and_dtype(
@@ -449,7 +447,7 @@ def is_tensor(x):
 
 
 def _bitwise_op(op_name, x, y, out=None, name=None, binary_op=True):
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         op = getattr(_C_ops, op_name)
         if binary_op:
             return op(x, y)
@@ -637,7 +635,7 @@ def isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
           # [True, True]
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.isclose(x, y, 'rtol',
                               str(rtol), 'atol',
                               str(atol), 'equal_nan', equal_nan)

python/paddle/tensor/manipulation.py

@@ -15,11 +15,11 @@
 from __future__ import print_function
 from collections import Counter
 
-from ..fluid.layers import core
+from ..static import Variable, device_guard
+from ..framework import core
 from ..fluid.layer_helper import LayerHelper
-from ..fluid.framework import Variable, OpProtoHolder, in_dygraph_mode, convert_np_dtype_to_dtype_, device_guard, dygraph_only
+from ..framework import OpProtoHolder, convert_np_dtype_to_dtype_, dygraph_only
 from ..fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype
-from ..fluid.layers.tensor import fill_constant
 from ..fluid.layers import utils
 import numpy as np
 # TODO: define functions to manipulate a tensor  
@@ -378,7 +378,7 @@ def broadcast_tensors(input, name=None):
     """
 
     num_inputs = len(input)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.broadcast_tensors(input, num_inputs)
 
     check_type(input, 'input', (list, tuple), 'broadcast_tensors')
@@ -475,7 +475,7 @@ def flip(x, axis, name=None):
     """
     if isinstance(axis, int):
         axis = [axis]
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.flip(x, "axis", axis)
 
     helper = LayerHelper("flip", **locals())
@@ -671,7 +671,7 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
     if not (isinstance(x, Variable)):
         raise ValueError("The input x should be a Tensor")
 
-    if not in_dygraph_mode():
+    if not paddle.in_dynamic_mode():
         check_variable_and_dtype(
             x, 'x',
             ['float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8'],
@@ -693,7 +693,7 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
     if start_axis > stop_axis:
         raise ValueError("The stop_axis should be larger than stat_axis")
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         dy_out, _ = _C_ops.flatten_contiguous_range(x, 'start_axis', start_axis,
                                                     'stop_axis', stop_axis)
         return dy_out
@@ -792,7 +792,7 @@ def roll(x, shifts, axis=None, name=None):
     else:
         axis = []
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.roll(x, 'axis', axis, 'shifts', shifts)
 
     helper = LayerHelper("roll", **locals())
@@ -1108,7 +1108,7 @@ def unique_consecutive(x,
     else:
         axis = [axis]
     attr_dtype = convert_np_dtype_to_dtype_(dtype)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out, inverse, counts = _C_ops.unique_consecutive(
             x, 'dtype', attr_dtype, 'return_inverse', return_inverse,
             'return_counts', return_counts, 'axis', axis)
@@ -1213,7 +1213,7 @@ def unique(x,
     else:
         axis = [axis]
     attr_dtype = convert_np_dtype_to_dtype_(dtype)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out, inverse, indices, counts = _C_ops.unique(
             x, 'dtype', attr_dtype, 'return_index', return_index,
             'return_inverse', return_inverse, 'return_counts', return_counts,
@@ -1397,7 +1397,7 @@ def gather(x, index, axis=None, name=None):
     if axis is None:
         axis = 0
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         axis = axis.item() if isinstance(axis, paddle.Tensor) else axis
         return _C_ops.gather(x, index, None, "axis", axis, "overwrite", False)
 
@@ -1471,7 +1471,7 @@ def unbind(input, axis=0):
     input_shape = input.shape
     axis_ = axis if axis >= 0 else len(input_shape) + axis
     num = input_shape[axis_]
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.unbind(input, num, 'axis', axis)
 
     helper = LayerHelper("unbind", **locals())
@@ -1565,7 +1565,7 @@ def scatter(x, index, updates, overwrite=True, name=None):
             #  [2., 2.],
             #  [1., 1.]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.scatter(x, index, updates, 'overwrite', overwrite)
 
     check_variable_and_dtype(
@@ -1744,7 +1744,7 @@ def tile(x, repeat_times, name=None):
             np_out = out.numpy()
             # [[1, 2, 3], [1, 2, 3]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.tile(x, 'repeat_times', repeat_times)
     check_type(repeat_times, 'repeat_times', (list, tuple, Variable), 'tile')
     if isinstance(repeat_times, Variable):
@@ -1827,7 +1827,7 @@ def expand_as(x, y, name=None):
             np_out = out.numpy()
             # [[1, 2, 3], [1, 2, 3]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.expand_as_v2(x, 'target_shape', y.shape)
 
     check_variable_and_dtype(
@@ -1881,7 +1881,7 @@ def broadcast_to(x, shape, name=None):
             print(out)
             # [[1, 2, 3], [1, 2, 3]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.expand_v2(x, 'shape', shape)
 
     if isinstance(shape, Variable):
@@ -1968,7 +1968,7 @@ def expand(x, shape, name=None):
             print(out)
             # [[1, 2, 3], [1, 2, 3]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.expand_v2(x, 'shape', shape)
 
     if isinstance(shape, Variable):
@@ -2407,7 +2407,7 @@ def tensordot(x, y, axes=2, name=None):
     check_type(axes, 'axes', (int, tuple, list, Variable), op_type)
 
     def _var_to_list(var):
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             return tolist(var)
         raise TypeError(
             "The 'axes' with type 'Tensor' in " + op_type +
@@ -2523,7 +2523,7 @@ def as_complex(x, name=None):
             # [[ 0. +1.j  2. +3.j  4. +5.j]
             #  [ 6. +7.j  8. +9.j 10.+11.j]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return paddle._C_ops.as_complex(x)
 
     check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'as_complex')
@@ -2572,7 +2572,7 @@ def as_real(x, name=None):
             #   [ 8.  9.]
             #   [10. 11.]]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return paddle._C_ops.as_real(x)
 
     check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'as_real')
@@ -2626,7 +2626,7 @@ def repeat_interleave(x, repeats, axis=None, name=None):
         x = paddle.flatten(x)
         axis = 0
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if isinstance(repeats, int):
             return _C_ops.repeat_interleave(x, None, 'Repeats', repeats, 'dim',
                                             axis)
@@ -2733,7 +2733,7 @@ def moveaxis(x, source, destination, name=None):
     for i in range(len(src_dims)):
         perm[dst_dims[i]] = src_dims[i]
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out, _ = _C_ops.transpose2(x, 'axis', perm)
         return out
 
@@ -2814,7 +2814,7 @@ def take_along_axis(arr, indices, axis):
     if not broadcast_shape:
         # if indices matrix have larger size than arr, arr should broadcast into indices shape.
         broadcast_shape = indices.shape
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         indices = paddle.broadcast_to(indices, broadcast_shape)
         broadcast_shape_list = list(broadcast_shape)
         broadcast_shape_list[axis] = list(arr.shape)[axis]
@@ -2879,7 +2879,7 @@ def put_along_axis(arr, indices, values, axis, reduce='assign'):
             "`indices` and `arr` must have the same number of dimensions!")
     axis = non_negative_axis(arr, axis)
     broadcast_shape = infer_broadcast_shape(arr, indices, axis)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         values = paddle.to_tensor(values) if not isinstance(
             values, paddle.Tensor) else values
         if broadcast_shape:

python/paddle/tensor/math.py

@@ -26,8 +26,9 @@ from paddle.common_ops_import import dygraph_utils
 from paddle.tensor import cast
 from paddle.tensor.attribute import _complex_to_real_dtype
 import paddle
-from ..fluid import layers
-from ..fluid.framework import core, _varbase_creator, in_dygraph_mode, Variable, convert_np_dtype_to_dtype_
+from paddle.static import Variable
+from ..framework import core
+from ..framework import _varbase_creator, convert_np_dtype_to_dtype_
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, convert_dtype
 from ..fluid.layers.layer_function_generator import _generate_doc_string_, generate_activation_fn, generate_layer_fn
@@ -70,7 +71,8 @@ from ..fluid.layers import acosh    # noqa: F401
 from ..fluid.layers import atanh    # noqa: F401
 
 from ..fluid.layers import multiplex    # noqa: F401
-from ..fluid import layers
+from ..fluid.layers import reduce_prod
+from ..fluid.layers import elementwise_sub
 from paddle import _C_ops
 
 __all__ = []
@@ -147,7 +149,7 @@ def pow(x, y, name=None):
 
     """
     # in dynamic graph mode
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if isinstance(y, (int, float)):
             return _C_ops.pow(x, 'factor', y)
         elif isinstance(y, (paddle.Tensor, Variable)):
@@ -240,7 +242,7 @@ def add(x, y, name=None):
 
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.elementwise_add(x, y)
 
     return _elementwise_op(LayerHelper('elementwise_add', **locals()))
@@ -319,7 +321,7 @@ def subtract(x, y, name=None):
     op_type = 'elementwise_sub'
     axis = -1
     act = None
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
@@ -376,7 +378,7 @@ def divide(x, y, name=None):
     op_type = 'elementwise_div'
     axis = -1
     act = None
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
 
@@ -415,7 +417,7 @@ def floor_divide(x, y, name=None):
     """
     op_type = 'elementwise_floordiv'
     axis = -1
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, op_name=op_type)
 
@@ -455,7 +457,7 @@ def remainder(x, y, name=None):
     """
     op_type = 'elementwise_mod'
     axis = -1
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, op_name=op_type)
 
@@ -505,7 +507,7 @@ def multiply(x, y, name=None):
     act = None
     axis = -1
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
 
@@ -570,7 +572,7 @@ def maximum(x, y, name=None):
     op_type = 'elementwise_max'
     axis = -1
     act = None
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
@@ -629,7 +631,7 @@ def minimum(x, y, name=None):
     op_type = 'elementwise_min'
     axis = -1
     act = None
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
@@ -690,7 +692,7 @@ def fmax(x, y, name=None):
     op_type = 'elementwise_fmax'
     axis = -1
     act = None
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
@@ -751,7 +753,7 @@ def fmin(x, y, name=None):
     op_type = 'elementwise_fmin'
     axis = -1
     act = None
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
@@ -860,7 +862,7 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None):
         return (False, src_type)
 
     dtype_flag, dtype = get_dtype(x, dtype)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         axis = axis if axis != None and axis != [] else [0]
         if dtype_flag:
             return _C_ops.reduce_sum(x, 'dim', axis, 'keep_dim', keepdim,
@@ -1024,7 +1026,7 @@ def add_n(inputs, name=None):
             # [[8., 10., 12.], 
             #  [14., 16., 18.]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if isinstance(inputs, Variable):
             inputs = [inputs]
         return _C_ops.sum(inputs, 'use_mkldnn', False)
@@ -1080,7 +1082,7 @@ def trunc(input, name=None):
             #         [[0., 0.],
             #         [0., 0.]]))
     '''
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.trunc(input)
     else:
         inputs = {"X": input}
@@ -1164,7 +1166,7 @@ def mm(input, mat2, name=None):
 
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.matmul_v2(input, mat2)
 
     def __check_input(x, y):
@@ -1269,7 +1271,7 @@ def addmm(input, x, y, beta=1.0, alpha=1.0, name=None):
 
 
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out = _C_ops.addmm(input, x, y, "Alpha", alpha, "Beta", beta)
         return out
 
@@ -1328,7 +1330,7 @@ def renorm(x, p, axis, max_norm):
         if not axis >= -1 * len(input_shape):
             raise ValueError("the axis:{} should not be less than -1 * length of input_shape:{}".format(axis,-1 * len(input_shape)))
         axis = axis + len(input_shape)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out = core.ops.renorm(x, 'p',p, 'axis',axis, 'max_norm', max_norm)
         return out
 
@@ -1384,7 +1386,7 @@ def inner(x, y, name=None):
         nx = x.reshape((-1, xshape[-1]))
         ny = y.reshape((-1, yshape[-1]))
 
-        if in_dygraph_mode():
+        if paddle.in_dynamic_mode():
             return _C_ops.matmul_v2(nx, ny.T).reshape(dstshape)
 
         def __check_input(x, y):
@@ -1447,7 +1449,7 @@ def outer(x, y, name=None):
     nx = x.reshape((-1, 1))
     ny = y.reshape((1, -1))
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.matmul_v2(nx, ny)
 
     def __check_input(x, y):
@@ -1516,7 +1518,7 @@ def logsumexp(x, axis=None, keepdim=False, name=None):
     if axis is None or len(axis) == 0:
         axis = [0]
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.logsumexp(x, 'axis', axis, 'keepdim', keepdim, 'reduce_all', reduce_all)
 
     check_variable_and_dtype(x, 'x',
@@ -1560,7 +1562,7 @@ def inverse(x, name=None):
             print(inv) # [[0.5, 0], [0, 0.5]]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.inverse(x)
 
     def _check_input(x):
@@ -1676,7 +1678,7 @@ def max(x, axis=None, keepdim=False, name=None):
     """
 
     reduce_all, axis = _get_reduce_all_value(axis)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.reduce_max(x, 'dim', axis, 'keep_dim', keepdim,
                                    'reduce_all', reduce_all)
 
@@ -1776,7 +1778,7 @@ def min(x, axis=None, keepdim=False, name=None):
     """
 
     reduce_all, axis = _get_reduce_all_value(axis)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.reduce_min(x, 'dim', axis, 'keep_dim', keepdim,
                                    'reduce_all', reduce_all)
 
@@ -1889,7 +1891,7 @@ def amax(x, axis=None, keepdim=False, name=None):
     """
 
     reduce_all, axis = _get_reduce_all_value(axis)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.reduce_amax(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all)
 
     helper = LayerHelper('amax', **locals())
@@ -2002,7 +2004,7 @@ def amin(x, axis=None, keepdim=False, name=None):
     """
 
     reduce_all, axis = _get_reduce_all_value(axis)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.reduce_amin(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all)
 
     helper = LayerHelper('amin', **locals())
@@ -2046,7 +2048,7 @@ def log1p(x, name=None):
             # [[0.], [0.6931472]]
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.log1p(x)
 
     check_variable_and_dtype(x, 'x', ['float32', 'float64'], "log1p")
@@ -2095,7 +2097,7 @@ def log2(x, name=None):
             res = paddle.log2(x_i)
             print(res) # [1.0]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.log2(x)
 
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], "log2")
@@ -2145,7 +2147,7 @@ def log10(x, name=None):
             res = paddle.log10(x_i)
             print(res) # [1.0]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.log10(x)
 
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], "log10")
@@ -2206,7 +2208,7 @@ def clip(x, min=None, max=None, name=None):
         min_ = float(np.finfo(np.float32).min)
         max_ = float(np.finfo(np.float32).max)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if isinstance(min, Variable):
             min = min.numpy().item(0)
         if isinstance(max, Variable):
@@ -2339,7 +2341,7 @@ def trace(x, offset=0, axis1=0, axis2=1, name=None):
                 "But received axis1 = %d, axis2 = %d\n"%(axis1, axis2)
 
     __check_input(input, offset, axis1, axis2)
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.trace(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2)
 
     inputs = {'Input': [x]}
@@ -2422,7 +2424,7 @@ def diagonal(x, offset=0, axis1=0, axis2=1, name=None):
             #        [0.17020577, 0.27325270]])
             
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.diagonal(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2)
 
     def __check_input(input, offset, dim1, dim2):
@@ -2499,7 +2501,7 @@ ${comment}
             #         [12, 15, 18, 16, 20, 24],
             #         [21, 24, 27, 28, 32, 36]])
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.kron(x, y)
 
     helper = LayerHelper('kron', **locals())
@@ -2557,9 +2559,9 @@ def cumsum(x, axis=None, dtype=None, name=None):
     else:
         flatten = False
     if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
-        x = layers.cast(x, dtype)
+        x = cast(x, dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if axis is None:
             return _C_ops.cumsum(x, 'flatten', flatten)
         else:
@@ -2622,9 +2624,9 @@ def cumprod(x, dim=None, dtype=None, name=None):
     """
 
     if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
-        x = layers.cast(x, dtype)
+        x = cast(x, dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.cumprod(x, 'dim', dim)
 
     check_variable_and_dtype(x, "x", ['complex64', 'complex128', 'float32', 'float64', 'int32', 'int64'], 'cumprod')
@@ -2656,7 +2658,7 @@ def isfinite(x, name=None):
             out = paddle.tensor.isfinite(x)
             print(out)  # [False  True  True False  True False False]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.isfinite_v2(x)
     helper = LayerHelper("isfinite_v2", **locals())
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isfinite')
@@ -2684,7 +2686,7 @@ def isinf(x, name=None):
             out = paddle.tensor.isinf(x)
             print(out)  # [ True False False  True False False False]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.isinf_v2(x)
     helper = LayerHelper("isinf_v2", **locals())
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isinf')
@@ -2712,7 +2714,7 @@ def isnan(x, name=None):
             out = paddle.tensor.isnan(x)
             print(out)  # [False False False False False  True  True]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.isnan_v2(x)
     helper = LayerHelper("isnan_v2", **locals())
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isnan')
@@ -2783,9 +2785,9 @@ def prod(x, axis=None, keepdim=False, dtype=None, name=None):
     if dtype is not None:
         check_dtype(dtype, 'dtype', ['float32', 'float64', 'int32', 'int64'], 'prod')
         if x.dtype != convert_np_dtype_to_dtype_(dtype):
-            x = layers.cast(x, dtype)
+            x = cast(x, dtype)
 
-    return layers.reduce_prod(input=x, dim=axis, keep_dim=keepdim, name=name)
+    return reduce_prod(input=x, dim=axis, keep_dim=keepdim, name=name)
 
 
 def sign(x, name=None):
@@ -2809,7 +2811,7 @@ def sign(x, name=None):
           out = paddle.sign(x=x)
           print(out)  # [1.0, 0.0, -1.0, 1.0]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.sign(x)
 
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'sign')
@@ -2846,7 +2848,7 @@ def tanh(x, name=None):
             print(out)
             # [-0.37994896 -0.19737532  0.09966799  0.29131261]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.tanh(x)
 
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'tanh')
@@ -2888,7 +2890,7 @@ def increment(x, value=1.0, name=None):
             # [1.]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.increment(x, 'step', value)
 
     check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
@@ -2969,7 +2971,7 @@ def all(x, axis=None, keepdim=False, name=None):
         else:
             reduce_all_flag = False
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         axis = axis if axis != None and axis != [] else [0]
         return _C_ops.reduce_all(x, 'dim', axis, 'keep_dim', keepdim,
                                        'reduce_all', reduce_all_flag)
@@ -3061,7 +3063,7 @@ def any(x, axis=None, keepdim=False, name=None):
         else:
             reduce_all_flag = False
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         axis = axis if axis != None and axis != [] else [0]
         return _C_ops.reduce_any(x, 'dim', axis, 'keep_dim', keepdim,
                                        'reduce_all', reduce_all_flag)
@@ -3142,7 +3144,7 @@ def conj(x, name=None):
           #        [(4-4j), (5-5j), (6-6j)]])
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.conj(x)
 
     check_variable_and_dtype(x, "x", ['complex64', 'complex128', 'float32', 'float64', 'int32', 'int64'], 'conj')
@@ -3181,7 +3183,7 @@ def digamma(x, name=None):
             #        [ nan       ,  5.32286835]])
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.digamma(x)
 
     check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'digamma')
@@ -3212,7 +3214,7 @@ def neg(x, name=None):
             # [0.4 0.2 -0.1 -0.3]
     """
 
-    return layers.scale(x, scale=-1.0, bias=0.0, bias_after_scale=True, act=None, name=name)
+    return scale(x, scale=-1.0, bias=0.0, bias_after_scale=True, act=None, name=name)
 
 def atan2(x, y, name=None):
     r"""
@@ -3257,7 +3259,7 @@ def atan2(x, y, name=None):
 
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.atan2(x, y)
     else:
         check_variable_and_dtype(x, 'x', ['int32', 'int64', 'float16', 'float32', 'float64'], 'atan2')
@@ -3313,7 +3315,7 @@ def logit(x, eps=None, name=None):
 
     if eps == None:
         eps = 0.0
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.logit(x, 'eps', eps)
 
     check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'logit')
@@ -3356,7 +3358,7 @@ def lerp(x, y, weight, name=None):
             # out: [5.5., 6., 6.5, 7.]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         check_type(weight, 'weight', (float, paddle.Tensor, Variable), 'lerp')
         if isinstance(weight, float):
             weight = paddle.to_tensor(weight, dtype=x.dtype)
@@ -3419,7 +3421,7 @@ def erfinv(x, name=None):
     """
     check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'erfinv')
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.erfinv(x)
 
     helper = LayerHelper('erfinv', **locals())
@@ -3478,7 +3480,7 @@ def rad2deg(x, name=None):
             #         [57.29578018])
     """
     rad2deg_scale = 180 / np.pi
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if convert_dtype(x.dtype) in ['int32', 'int64']:
             x = cast(x, dtype="float32")
         return _C_ops.scale(x, 'scale', rad2deg_scale)
@@ -3531,7 +3533,7 @@ def deg2rad(x, name=None):
             #         [3.14159274])
     """
     deg2rad_scale = np.pi / 180.0
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if convert_dtype(x.dtype) in ['int32', 'int64']:
             x = cast(x, dtype="float32")
         return _C_ops.scale(x, 'scale', deg2rad_scale)
@@ -3615,7 +3617,7 @@ def gcd(x, y, name=None):
                   paddle.where(y_not_equal_0, paddle.mod(x, y_safe),paddle.zeros(y.shape, y.dtype)))
         return (paddle.where(x < y, y, x), paddle.where(x < y, x, y))
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         while _gcd_cond_fn(x, y):
             x, y = _gcd_body_fn(x, y)
 
@@ -3749,7 +3751,7 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None):
     dtype = x.dtype
     axes = [axis]
     infer_flags = list(1 for i in range(len(axes)))
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         has_pend = False
         input_list = []
         if prepend is not None and append is not None:
@@ -3788,7 +3790,7 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None):
             op = getattr(_C_ops, "logical_xor")
             out = op(input_back, input_front)
         else:
-            out = layers.elementwise_sub(input_back, input_front, axis=axis)
+            out = elementwise_sub(input_back, input_front, axis=axis)
         return out
     else:
         check_variable_and_dtype(x, 'x', ['float32', 'float64', 'bool', 'int32', 'int64'], 'diff')
@@ -3840,7 +3842,7 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None):
                 type='logical_xor', inputs={"X": input_back, "Y": input_front}, outputs={"Out": out}
             )
         else:
-            out = layers.elementwise_sub(input_back, input_front, axis=axis)
+            out = elementwise_sub(input_back, input_front, axis=axis)
 
         return out
 
@@ -3883,7 +3885,7 @@ def angle(x, name=None):
             #  [-1.1071488 -0.7853982  0.         0.7853982]]
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.angle(x)
 
     check_variable_and_dtype(x, 'x',

python/paddle/tensor/random.py

@@ -14,13 +14,14 @@
 
 # TODO: define random functions  
 
-from ..fluid import core
-from ..fluid.framework import in_dygraph_mode, Variable, convert_np_dtype_to_dtype_, dygraph_only
+from ..framework import core
+from ..framework import convert_np_dtype_to_dtype_, dygraph_only
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, check_shape
 from ..fluid.layers import utils
 import paddle
 from paddle import _C_ops
+from paddle.static import Variable
 
 __all__ = []
 
@@ -65,7 +66,7 @@ def bernoulli(x, name=None):
 
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.bernoulli(x)
 
     check_variable_and_dtype(x, "x", ["float32", "float64"], "bernoulli")
@@ -110,7 +111,7 @@ def poisson(x, name=None):
 
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.poisson(x)
 
     check_variable_and_dtype(x, "x", ["float32", "float64"], "poisson")
@@ -173,7 +174,7 @@ def multinomial(x, num_samples=1, replacement=False, name=None):
     assert core.is_compiled_with_rocm() == False, (
         "multinomial op is not supported on ROCM yet.")
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.multinomial(x, 'num_samples', num_samples, 'replacement',
                                   replacement)
 
@@ -231,7 +232,7 @@ def gaussian(shape, mean=0.0, std=1.0, dtype=None, name=None):
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         shape = utils.convert_shape_to_list(shape)
         return _C_ops.gaussian_random('shape', shape, 'mean',
                                       float(mean), 'std',
@@ -422,7 +423,7 @@ def normal(mean=0.0, std=1.0, shape=None, name=None):
             # [1.00780561 3.78457445 5.81058198]  # random
 
     """
-    if not in_dygraph_mode():
+    if not paddle.in_dynamic_mode():
         check_type(mean, 'mean', (int, float, Variable), 'normal')
         check_type(std, 'std', (int, float, Variable), 'normal')
         if isinstance(mean, Variable):
@@ -454,7 +455,7 @@ def normal(mean=0.0, std=1.0, shape=None, name=None):
         return gaussian(shape=shape, mean=mean, std=std, name=name)
 
     out = out * std + mean
-    if not in_dygraph_mode():
+    if not paddle.in_dynamic_mode():
         out.stop_grediant = True
     return out
 
@@ -540,7 +541,7 @@ def uniform(shape, dtype=None, min=-1.0, max=1.0, seed=0, name=None):
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         shape = utils.convert_shape_to_list(shape)
         return _C_ops.uniform_random('shape', shape, 'min',
                                      float(min), 'max',
@@ -679,7 +680,7 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         shape = utils.convert_shape_to_list(shape)
         return _C_ops.randint('shape', shape, 'low', low, 'high', high, 'seed',
                               0, 'dtype', dtype)
@@ -846,7 +847,7 @@ def randint_like(x, low=0, high=None, dtype=None, name=None):
             "randint_like's low must less then high, but received low = {0}, "
             "high = {1}".format(low, high))
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         shape = utils.convert_shape_to_list(shape)
         out = _C_ops.randint('shape', shape, 'low', low, 'high', high, 'seed',
                              0, 'dtype', core.VarDesc.VarType.INT64)
@@ -911,7 +912,7 @@ def randperm(n, dtype="int64", name=None):
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.randperm('n', n, 'seed', 0, 'dtype', dtype)
 
     if n < 1:
@@ -1014,7 +1015,7 @@ def exponential_(x, lam=1.0, name=None):
             #  [0.72520673, 0.45208144, 0.30234432]]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.exponential_(x, "lambda", lam)
 
     check_variable_and_dtype(x, "x", ["float32", "float64"], "exponential")

python/paddle/tensor/search.py

@@ -13,14 +13,16 @@
 # limitations under the License.
 from __future__ import print_function
 import numpy as np
+import paddle
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype
-from ..fluid import core, layers
-from paddle.common_ops_import import in_dygraph_mode
+from ..fluid import layers
+from ..framework import core
 from paddle.common_ops_import import convert_np_dtype_to_dtype_
 from paddle.common_ops_import import Variable
 from paddle.common_ops_import import VarDesc
 from paddle import _C_ops
+from .logic import logical_not
 
 # TODO: define searching & indexing functions of a tensor  
 # from ..fluid.layers import has_inf  #DEFINE_ALIAS
@@ -88,7 +90,7 @@ def argsort(x, axis=-1, descending=False, name=None):
             #  [1 1 0 2]
             #  [0 2 1 1]]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         _, ids = _C_ops.argsort(x, 'axis', axis, 'descending', descending)
         return ids
     check_variable_and_dtype(
@@ -165,7 +167,7 @@ def argmax(x, axis=None, keepdim=False, dtype="int64", name=None):
         flatten = True
         axis = 0
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out = _C_ops.arg_max(x, 'axis', axis, 'dtype', var_dtype, 'keepdims',
                              keepdim, 'flatten', flatten)
         return out
@@ -242,7 +244,7 @@ def argmin(x, axis=None, keepdim=False, dtype="int64", name=None):
         flatten = True
         axis = 0
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out = _C_ops.arg_min(x, 'axis', axis, 'dtype', var_dtype, 'keepdims',
                              keepdim, 'flatten', flatten)
         return out
@@ -302,7 +304,7 @@ def index_select(x, index, axis=0, name=None):
             # [ 9. 10. 10.]]
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.index_select(x, index, 'dim', axis)
 
     helper = LayerHelper("index_select", **locals())
@@ -378,7 +380,7 @@ def nonzero(x, as_tuple=False):
     shape = x.shape
     rank = len(shape)
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         outs = _C_ops.where_index(x)
     else:
         outs = layers.where(x)
@@ -390,7 +392,7 @@ def nonzero(x, as_tuple=False):
     else:
         for i in range(rank):
             list_out.append(
-                layers.slice(
+                paddle.slice(
                     outs, axes=[1], starts=[i], ends=[i + 1]))
         return tuple(list_out)
 
@@ -452,7 +454,7 @@ def sort(x, axis=-1, descending=False, name=None):
             #  [4. 7. 4. 6.]
             #  [5. 7. 7. 9.]]]
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         out, _ = _C_ops.argsort(x, 'axis', axis, 'descending', descending)
         return out
     helper = LayerHelper("sort", **locals())
@@ -501,7 +503,7 @@ def mode(x, axis=-1, keepdim=False, name=None):
            #    [1, 0]]))
            
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.mode(x, "axis", axis, "keepdim", keepdim)
 
     helper = LayerHelper("mode", **locals())
@@ -575,7 +577,7 @@ def where(condition, x=None, y=None, name=None):
     if x is None or y is None:
         raise ValueError("either both or neither of x and y should be given")
 
-    if not in_dygraph_mode():
+    if not paddle.in_dynamic_mode():
         check_variable_and_dtype(condition, 'condition', ['bool'], 'where')
         check_variable_and_dtype(
             x, 'x', ['float32', 'float64', 'int32', 'int64'], 'where')
@@ -592,28 +594,27 @@ def where(condition, x=None, y=None, name=None):
         broadcast_y = y
     else:
         if core.is_compiled_with_xpu():
-            cond_int = layers.cast(condition, x.dtype)
-            cond_not_int = layers.cast(layers.logical_not(condition), x.dtype)
-            out1 = layers.elementwise_mul(x, cond_int)
-            out2 = layers.elementwise_mul(y, cond_not_int)
-            out = layers.elementwise_add(out1, out2)
+            cond_int = paddle.cast(condition, x.dtype)
+            cond_not_int = paddle.cast(logical_not(condition), x.dtype)
+            out1 = paddle.multiply(x, cond_int)
+            out2 = paddle.multiply(y, cond_not_int)
+            out = paddle.add(out1, out2)
             return out
 
-        zeros_like_x = layers.zeros_like(x)
-        zeros_like_y = layers.zeros_like(y)
-        zeros_like_condition = layers.zeros_like(condition)
-        zeros_like_condition = layers.cast(zeros_like_condition, x.dtype)
-        cast_cond = layers.cast(condition, x.dtype)
-
-        broadcast_zeros = layers.elementwise_add(zeros_like_x, zeros_like_y)
-        broadcast_zeros = layers.elementwise_add(broadcast_zeros,
-                                                 zeros_like_condition)
-        broadcast_x = layers.elementwise_add(x, broadcast_zeros)
-        broadcast_y = layers.elementwise_add(y, broadcast_zeros)
-        broadcast_condition = layers.elementwise_add(cast_cond, broadcast_zeros)
-        broadcast_condition = layers.cast(broadcast_condition, 'bool')
-
-    if in_dygraph_mode():
+        zeros_like_x = paddle.zeros_like(x)
+        zeros_like_y = paddle.zeros_like(y)
+        zeros_like_condition = paddle.zeros_like(condition)
+        zeros_like_condition = paddle.cast(zeros_like_condition, x.dtype)
+        cast_cond = paddle.cast(condition, x.dtype)
+
+        broadcast_zeros = paddle.add(zeros_like_x, zeros_like_y)
+        broadcast_zeros = paddle.add(broadcast_zeros, zeros_like_condition)
+        broadcast_x = paddle.add(x, broadcast_zeros)
+        broadcast_y = paddle.add(y, broadcast_zeros)
+        broadcast_condition = paddle.add(cast_cond, broadcast_zeros)
+        broadcast_condition = paddle.cast(broadcast_condition, 'bool')
+
+    if paddle.in_dynamic_mode():
         return _C_ops.where(broadcast_condition, broadcast_x, broadcast_y)
     else:
         helper = LayerHelper("where", **locals())
@@ -704,7 +705,7 @@ def index_sample(x, index):
             # [1200 1100]]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.index_sample(x, index)
 
     helper = LayerHelper("index_sample", **locals())
@@ -752,7 +753,7 @@ def masked_select(x, mask, name=None):
             #[1.0 5.0 6.0 9.0]
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.masked_select(x, mask)
 
     helper = LayerHelper("masked_select", **locals())
@@ -822,7 +823,7 @@ def topk(x, k, axis=None, largest=True, sorted=True, name=None):
            # [[1 1 0 0]]
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         k = k.numpy().item(0) if isinstance(k, Variable) else k
         if axis is None:
             out, indices = _C_ops.top_k_v2(x, 'k',
@@ -906,7 +907,7 @@ def searchsorted(sorted_sequence,
             
     """
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.searchsorted(sorted_sequence, values, "out_int32",
                                    out_int32, "right", right)
 
@@ -969,7 +970,7 @@ def kthvalue(x, k, axis=None, keepdim=False, name=None):
             #  [[0, 2],
             #  [1, 2]]))
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         if axis is not None:
             return _C_ops.kthvalue(x, 'k', k, "axis", axis, "keepdim", keepdim)
         else:

python/paddle/tensor/stat.py

@@ -15,10 +15,9 @@
 # TODO: define statistical functions of a tensor  
 
 import numpy as np
-from ..fluid.framework import Variable
+from ..static import Variable
 from ..fluid.layer_helper import LayerHelper
-from ..fluid.framework import core, in_dygraph_mode
-from ..fluid import layers
+from ..framework import core
 from .search import where
 from ..fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype
 import paddle
@@ -88,7 +87,7 @@ def mean(x, axis=None, keepdim=False, name=None):
     if axis is None or len(axis) == 0:
         axis = [0]
 
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.reduce_mean(x, 'dim', axis, 'keep_dim', keepdim,
                                   'reduce_all', reduce_all)
 
@@ -150,7 +149,7 @@ def var(x, axis=None, unbiased=True, keepdim=False, name=None):
             out2 = paddle.var(x, axis=1)
             # [1.         4.33333333]
     """
-    if not in_dygraph_mode():
+    if not paddle.in_dynamic_mode():
         check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'var')
 
     u = mean(x, axis, True, name)
@@ -209,7 +208,7 @@ def std(x, axis=None, unbiased=True, keepdim=False, name=None):
             out2 = paddle.std(x, axis=1)
             # [1.       2.081666]
     """
-    if not in_dygraph_mode():
+    if not paddle.in_dynamic_mode():
         check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'std')
 
     out = var(**locals())
@@ -237,7 +236,7 @@ def numel(x, name=None):
 
 
     """
-    if in_dygraph_mode():
+    if paddle.in_dynamic_mode():
         return _C_ops.size(x)
 
     if not isinstance(x, Variable):

python/paddle/tensor/to_string.py

@@ -14,7 +14,7 @@
 
 import paddle
 import numpy as np
-from paddle.fluid.layers import core
+from ..framework import core
 from paddle.fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype
 
 __all__ = []