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Paddle
未验证 提交 42eb56e2 编写于 作者: Z zhiboniu 提交者： GitHub
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unset fluid in tensor (#35082)

上级 a08ee62a
隐藏空白更改
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Showing with 223 addition and 218 deletion
python/paddle/framework/__init__.py
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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
浏览文件 @ 42eb56e2
......@@ -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__ = []
......
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