__init__.py 21.9 KB
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# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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try:
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    from paddle.version import full_version as __version__
    from paddle.version import commit as __git_commit__
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    from paddle.cuda_env import *  # noqa: F403
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except ImportError:
    import sys
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    sys.stderr.write(
        '''Warning with import paddle: you should not
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     import paddle from the source directory; please install paddlepaddle*.whl firstly.'''
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    )
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from .batch import batch  # noqa: F401
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from .framework import monkey_patch_variable
from .framework import monkey_patch_math_varbase
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monkey_patch_variable()
monkey_patch_math_varbase()
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from .framework import disable_signal_handler  # noqa: F401
from .framework import get_flags  # noqa: F401
from .framework import set_flags  # noqa: F401

from .framework import disable_static  # noqa: F401
from .framework import enable_static  # noqa: F401
from .framework import in_dynamic_mode  # noqa: F401
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from .fluid.dataset import *  # noqa: F401, F403
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from .fluid.lazy_init import LazyGuard  # noqa: F401
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from .framework.dtype import iinfo  # noqa: F401
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from .framework.dtype import finfo  # noqa: F401
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from .framework.dtype import dtype as dtype  # noqa: F401
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from .framework.dtype import uint8  # noqa: F401
from .framework.dtype import int8  # noqa: F401
from .framework.dtype import int16  # noqa: F401
from .framework.dtype import int32  # noqa: F401
from .framework.dtype import int64  # noqa: F401
from .framework.dtype import float16  # noqa: F401
from .framework.dtype import float32  # noqa: F401
from .framework.dtype import float64  # noqa: F401
from .framework.dtype import bfloat16  # noqa: F401
from .framework.dtype import bool  # noqa: F401
from .framework.dtype import complex64  # noqa: F401
from .framework.dtype import complex128  # noqa: F401
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if fluid.framework.global_var._in_eager_mode_:
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    Tensor = framework.core.eager.Tensor
else:
    from .framework import VarBase as Tensor  # noqa: F401
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Tensor.__qualname__ = 'Tensor'  # noqa: F401
import paddle.distributed  # noqa: F401
import paddle.sysconfig  # noqa: F401
import paddle.distribution  # noqa: F401
import paddle.nn  # noqa: F401
import paddle.distributed.fleet  # noqa: F401
import paddle.optimizer  # noqa: F401
import paddle.metric  # noqa: F401
import paddle.regularizer  # noqa: F401
import paddle.incubate  # noqa: F401
import paddle.autograd  # noqa: F401
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import paddle.device  # noqa: F401
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import paddle.jit  # noqa: F401
import paddle.amp  # noqa: F401
import paddle.dataset  # noqa: F401
import paddle.inference  # noqa: F401
import paddle.io  # noqa: F401
import paddle.onnx  # noqa: F401
import paddle.reader  # noqa: F401
import paddle.static  # noqa: F401
import paddle.vision  # noqa: F401
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import paddle.audio  # noqa: F401
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import paddle.geometric  # noqa: F401
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import paddle.sparse  # noqa: F401
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import paddle.quantization  # noqa: F401
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from .tensor.attribute import is_complex  # noqa: F401
from .tensor.attribute import is_integer  # noqa: F401
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from .tensor.attribute import rank  # noqa: F401
from .tensor.attribute import shape  # noqa: F401
from .tensor.attribute import real  # noqa: F401
from .tensor.attribute import imag  # noqa: F401
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from .tensor.attribute import is_floating_point  # noqa: F401
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from .tensor.creation import create_parameter  # noqa: F401
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from .tensor.creation import to_tensor  # noqa: F401
from .tensor.creation import diag  # noqa: F401
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from .tensor.creation import diagflat  # noqa: F401
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from .tensor.creation import eye  # noqa: F401
from .tensor.creation import linspace  # noqa: F401
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from .tensor.creation import logspace  # noqa: F401
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from .tensor.creation import ones  # noqa: F401
from .tensor.creation import ones_like  # noqa: F401
from .tensor.creation import zeros  # noqa: F401
from .tensor.creation import zeros_like  # noqa: F401
from .tensor.creation import arange  # noqa: F401
from .tensor.creation import full  # noqa: F401
from .tensor.creation import full_like  # noqa: F401
from .tensor.creation import triu  # noqa: F401
from .tensor.creation import tril  # noqa: F401
from .tensor.creation import meshgrid  # noqa: F401
from .tensor.creation import empty  # noqa: F401
from .tensor.creation import empty_like  # noqa: F401
from .tensor.creation import assign  # noqa: F401
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from .tensor.creation import complex  # noqa: F401
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from .tensor.creation import clone  # noqa: F401
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from .tensor.creation import tril_indices  # noqa: F401
from .tensor.creation import triu_indices  # noqa: F401
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from .tensor.linalg import matmul  # noqa: F401
from .tensor.linalg import dot  # noqa: F401
from .tensor.linalg import norm  # noqa: F401
from .tensor.linalg import transpose  # noqa: F401
from .tensor.linalg import dist  # noqa: F401
from .tensor.linalg import t  # noqa: F401
from .tensor.linalg import cross  # noqa: F401
from .tensor.linalg import cholesky  # noqa: F401
from .tensor.linalg import bmm  # noqa: F401
from .tensor.linalg import histogram  # noqa: F401
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from .tensor.linalg import bincount  # noqa: F401
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from .tensor.linalg import mv  # noqa: F401
from .tensor.logic import equal  # noqa: F401
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from .tensor.linalg import eigvalsh  # noqa: F401
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from .tensor.logic import greater_equal  # noqa: F401
from .tensor.logic import greater_than  # noqa: F401
from .tensor.logic import is_empty  # noqa: F401
from .tensor.logic import less_equal  # noqa: F401
from .tensor.logic import less_than  # noqa: F401
from .tensor.logic import logical_and  # noqa: F401
from .tensor.logic import logical_not  # noqa: F401
from .tensor.logic import logical_or  # noqa: F401
from .tensor.logic import logical_xor  # noqa: F401
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from .tensor.logic import bitwise_and  # noqa: F401
from .tensor.logic import bitwise_not  # noqa: F401
from .tensor.logic import bitwise_or  # noqa: F401
from .tensor.logic import bitwise_xor  # noqa: F401
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from .tensor.logic import not_equal  # noqa: F401
from .tensor.logic import allclose  # noqa: F401
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from .tensor.logic import isclose  # noqa: F401
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from .tensor.logic import equal_all  # noqa: F401
from .tensor.logic import is_tensor  # noqa: F401
from .tensor.manipulation import cast  # noqa: F401
from .tensor.manipulation import concat  # noqa: F401
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from .tensor.manipulation import broadcast_tensors  # noqa: F401
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from .tensor.manipulation import expand  # noqa: F401
from .tensor.manipulation import broadcast_to  # noqa: F401
from .tensor.manipulation import expand_as  # noqa: F401
from .tensor.manipulation import tile  # noqa: F401
from .tensor.manipulation import flatten  # noqa: F401
from .tensor.manipulation import gather  # noqa: F401
from .tensor.manipulation import gather_nd  # noqa: F401
from .tensor.manipulation import reshape  # noqa: F401
from .tensor.manipulation import reshape_  # noqa: F401
from .tensor.manipulation import flip as reverse  # noqa: F401
from .tensor.manipulation import scatter  # noqa: F401
from .tensor.manipulation import scatter_  # noqa: F401
from .tensor.manipulation import scatter_nd_add  # noqa: F401
from .tensor.manipulation import scatter_nd  # noqa: F401
from .tensor.manipulation import shard_index  # noqa: F401
from .tensor.manipulation import slice  # noqa: F401
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from .tensor.manipulation import crop  # noqa: F401
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from .tensor.manipulation import split  # noqa: F401
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from .tensor.manipulation import vsplit  # noqa: F401
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from .tensor.manipulation import squeeze  # noqa: F401
from .tensor.manipulation import squeeze_  # noqa: F401
from .tensor.manipulation import stack  # noqa: F401
from .tensor.manipulation import strided_slice  # noqa: F401
from .tensor.manipulation import unique  # noqa: F401
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from .tensor.manipulation import unique_consecutive  # noqa: F401
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from .tensor.manipulation import unsqueeze  # noqa: F401
from .tensor.manipulation import unsqueeze_  # noqa: F401
from .tensor.manipulation import unstack  # noqa: F401
from .tensor.manipulation import flip  # noqa: F401
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from .tensor.manipulation import rot90  # noqa: F401
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from .tensor.manipulation import unbind  # noqa: F401
from .tensor.manipulation import roll  # noqa: F401
from .tensor.manipulation import chunk  # noqa: F401
from .tensor.manipulation import tolist  # noqa: F401
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from .tensor.manipulation import take_along_axis  # noqa: F401
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from .tensor.manipulation import put_along_axis  # noqa: F401
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from .tensor.manipulation import tensordot  # noqa: F401
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from .tensor.manipulation import as_complex  # noqa: F401
from .tensor.manipulation import as_real  # noqa: F401
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from .tensor.manipulation import moveaxis  # noqa: F401
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from .tensor.manipulation import repeat_interleave  # noqa: F401
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from .tensor.manipulation import index_add  # noqa: F401
from .tensor.manipulation import index_add_  # noqa: F401
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from .tensor.math import abs  # noqa: F401
from .tensor.math import acos  # noqa: F401
from .tensor.math import asin  # noqa: F401
from .tensor.math import atan  # noqa: F401
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from .tensor.math import atan2  # noqa: F401
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from .tensor.math import ceil  # noqa: F401
from .tensor.math import cos  # noqa: F401
from .tensor.math import tan  # noqa: F401
from .tensor.math import cosh  # noqa: F401
from .tensor.math import cumsum  # noqa: F401
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from .tensor.math import cumprod  # noqa: F401
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from .tensor.math import logcumsumexp  # noqa: F401
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from .tensor.math import logit  # noqa: F401
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from .tensor.math import exp  # noqa: F401
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from .tensor.math import expm1  # noqa: F401
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from .tensor.math import floor  # noqa: F401
from .tensor.math import increment  # noqa: F401
from .tensor.math import log  # noqa: F401
from .tensor.math import log2  # noqa: F401
from .tensor.math import log10  # noqa: F401
from .tensor.math import multiplex  # noqa: F401
from .tensor.math import pow  # noqa: F401
from .tensor.math import reciprocal  # noqa: F401
from .tensor.math import all  # noqa: F401
from .tensor.math import any  # noqa: F401
from .tensor.math import round  # noqa: F401
from .tensor.math import rsqrt  # noqa: F401
from .tensor.math import scale  # noqa: F401
from .tensor.math import sign  # noqa: F401
from .tensor.math import sin  # noqa: F401
from .tensor.math import sinh  # noqa: F401
from .tensor.math import sqrt  # noqa: F401
from .tensor.math import square  # noqa: F401
from .tensor.math import stanh  # noqa: F401
from .tensor.math import sum  # noqa: F401
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from .tensor.math import nan_to_num  # noqa: F401
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from .tensor.math import nansum  # noqa: F401
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from .tensor.math import nanmean  # noqa: F401
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from .tensor.math import count_nonzero  # noqa: F401
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from .tensor.math import tanh  # noqa: F401
from .tensor.math import tanh_  # noqa: F401
from .tensor.math import add_n  # noqa: F401
from .tensor.math import max  # noqa: F401
from .tensor.math import maximum  # noqa: F401
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from .tensor.math import amax  # noqa: F401
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from .tensor.math import min  # noqa: F401
from .tensor.math import minimum  # noqa: F401
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from .tensor.math import amin  # noqa: F401
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from .tensor.math import mm  # noqa: F401
from .tensor.math import divide  # noqa: F401
from .tensor.math import floor_divide  # noqa: F401
from .tensor.math import remainder  # noqa: F401
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from .tensor.math import remainder_  # noqa: F401
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from .tensor.math import mod  # noqa: F401
from .tensor.math import floor_mod  # noqa: F401
from .tensor.math import multiply  # noqa: F401
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from .tensor.math import renorm  # noqa: F401
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from .tensor.math import add  # noqa: F401
from .tensor.math import subtract  # noqa: F401
from .tensor.math import logsumexp  # noqa: F401
from .tensor.math import inverse  # noqa: F401
from .tensor.math import log1p  # noqa: F401
from .tensor.math import erf  # noqa: F401
from .tensor.math import addmm  # noqa: F401
from .tensor.math import clip  # noqa: F401
from .tensor.math import trace  # noqa: F401
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from .tensor.math import diagonal  # noqa: F401
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from .tensor.math import kron  # noqa: F401
from .tensor.math import isfinite  # noqa: F401
from .tensor.math import isinf  # noqa: F401
from .tensor.math import isnan  # noqa: F401
from .tensor.math import prod  # noqa: F401
from .tensor.math import broadcast_shape  # noqa: F401
from .tensor.math import conj  # noqa: F401
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from .tensor.math import trunc  # noqa: F401
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from .tensor.math import digamma  # noqa: F401
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from .tensor.math import neg  # noqa: F401
from .tensor.math import lgamma  # noqa: F401
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from .tensor.math import acosh  # noqa: F401
from .tensor.math import asinh  # noqa: F401
from .tensor.math import atanh  # noqa: F401
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from .tensor.math import lerp  # noqa: F401
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from .tensor.math import erfinv  # noqa: F401
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from .tensor.math import rad2deg  # noqa: F401
from .tensor.math import deg2rad  # noqa: F401
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from .tensor.math import gcd  # noqa: F401
from .tensor.math import lcm  # noqa: F401
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from .tensor.math import diff  # noqa: F401
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from .tensor.math import angle  # noqa: F401
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from .tensor.math import fmax  # noqa: F401
from .tensor.math import fmin  # noqa: F401
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from .tensor.math import inner  # noqa: F401
from .tensor.math import outer  # noqa: F401
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from .tensor.math import heaviside  # noqa: F401
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from .tensor.math import frac  # noqa: F401
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from .tensor.math import sgn  # noqa: F401
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from .tensor.math import take  # noqa: F401
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from .tensor.math import frexp  # noqa: F401
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from .tensor.random import bernoulli  # noqa: F401
from .tensor.random import poisson  # noqa: F401
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from .tensor.random import multinomial  # noqa: F401
from .tensor.random import standard_normal  # noqa: F401
from .tensor.random import normal  # noqa: F401
from .tensor.random import uniform  # noqa: F401
from .tensor.random import randn  # noqa: F401
from .tensor.random import rand  # noqa: F401
from .tensor.random import randint  # noqa: F401
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from .tensor.random import randint_like  # noqa: F401
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from .tensor.random import randperm  # noqa: F401
from .tensor.search import argmax  # noqa: F401
from .tensor.search import argmin  # noqa: F401
from .tensor.search import argsort  # noqa: F401
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from .tensor.search import searchsorted  # noqa: F401
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from .tensor.search import bucketize  # noqa: F401
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from .tensor.search import masked_select  # noqa: F401
from .tensor.search import topk  # noqa: F401
from .tensor.search import where  # noqa: F401
from .tensor.search import index_select  # noqa: F401
from .tensor.search import nonzero  # noqa: F401
from .tensor.search import sort  # noqa: F401
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from .tensor.search import kthvalue  # noqa: F401
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from .tensor.search import mode  # noqa: F401
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from .tensor.to_string import set_printoptions  # noqa: F401
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from .tensor.einsum import einsum  # noqa: F401

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from .framework.random import seed  # noqa: F401
from .framework.random import get_cuda_rng_state  # noqa: F401
from .framework.random import set_cuda_rng_state  # noqa: F401
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from .framework.random import get_rng_state  # noqa: F401
from .framework.random import set_rng_state  # noqa: F401
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from .framework import ParamAttr  # noqa: F401
from .framework import CPUPlace  # noqa: F401
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from .framework import IPUPlace  # noqa: F401
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from .framework import CUDAPlace  # noqa: F401
from .framework import NPUPlace  # noqa: F401
from .framework import CUDAPinnedPlace  # noqa: F401
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from .framework import MLUPlace  # noqa: F401
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from .framework import CustomPlace  # noqa: F401
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from .autograd import grad  # noqa: F401
from .autograd import no_grad  # noqa: F401
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from .autograd import enable_grad  # noqa:F401
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from .autograd import set_grad_enabled  # noqa: F401
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from .autograd import is_grad_enabled  # noqa: F401
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from .framework import save  # noqa: F401
from .framework import load  # noqa: F401
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from .distributed import DataParallel  # noqa: F401
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from .framework import set_default_dtype  # noqa: F401
from .framework import get_default_dtype  # noqa: F401
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from .tensor.search import index_sample  # noqa: F401
from .tensor.stat import mean  # noqa: F401
from .tensor.stat import std  # noqa: F401
from .tensor.stat import var  # noqa: F401
from .tensor.stat import numel  # noqa: F401
from .tensor.stat import median  # noqa: F401
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from .tensor.stat import nanmedian  # noqa: F401
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from .tensor.stat import quantile  # noqa: F401
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from .tensor.stat import nanquantile  # noqa: F401
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from .device import get_cudnn_version  # noqa: F401
from .device import set_device  # noqa: F401
from .device import get_device  # noqa: F401
from .device import is_compiled_with_xpu  # noqa: F401
from .device import is_compiled_with_npu  # noqa: F401
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from .device import is_compiled_with_ipu  # noqa: F401
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from .device import is_compiled_with_mlu  # noqa: F401
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from .device import is_compiled_with_cinn  # noqa: F401
from .device import is_compiled_with_cuda  # noqa: F401
from .device import is_compiled_with_rocm  # noqa: F401
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from .device import is_compiled_with_custom_device  # noqa: F401
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from .device import XPUPlace  # noqa: F401
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# high-level api
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from .hapi import Model  # noqa: F401
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from . import callbacks  # noqa: F401
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from .hapi import summary  # noqa: F401
from .hapi import flops  # noqa: F401
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from . import hub  # noqa: F401
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from . import linalg  # noqa: F401
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from . import fft  # noqa: F401
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from . import signal  # noqa: F401
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import paddle.text  # noqa: F401
import paddle.vision  # noqa: F401
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from .tensor.random import check_shape  # noqa: F401
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# CINN has to set a flag to include a lib
if is_compiled_with_cinn():
    import os
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    package_dir = os.path.dirname(os.path.abspath(__file__))
    runtime_include_dir = os.path.join(package_dir, "libs")
    cuh_file = os.path.join(runtime_include_dir, "cinn_cuda_runtime_source.cuh")
    if os.path.exists(cuh_file):
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        os.environ.setdefault('runtime_include_dir', runtime_include_dir)
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disable_static()
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__all__ = [  # noqa
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    'iinfo',
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    'finfo',
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    'dtype',
    'uint8',
    'int8',
    'int16',
    'int32',
    'int64',
    'float16',
    'float32',
    'float64',
    'bfloat16',
    'bool',
    'complex64',
    'complex128',
    'addmm',
    'allclose',
    'isclose',
    't',
    'add',
    'subtract',
    'diag',
    'diagflat',
    'isnan',
    'scatter_nd_add',
    'unstack',
    'get_default_dtype',
    'save',
    'multinomial',
    'get_cuda_rng_state',
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    'get_rng_state',
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    'rank',
    'empty_like',
    'eye',
    'cumsum',
    'cumprod',
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    'logcumsumexp',
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    'logit',
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    'LazyGuard',
442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472
    'sign',
    'is_empty',
    'equal',
    'equal_all',
    'is_tensor',
    'is_complex',
    'is_integer',
    'cross',
    'where',
    'log1p',
    'cos',
    'tan',
    'mean',
    'mode',
    'mv',
    'in_dynamic_mode',
    'min',
    'amin',
    'any',
    'slice',
    'normal',
    'logsumexp',
    'full',
    'unsqueeze',
    'unsqueeze_',
    'argmax',
    'Model',
    'summary',
    'flops',
    'sort',
    'searchsorted',
473
    'bucketize',
474
    'split',
475
    'vsplit',
476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539
    'logical_and',
    'full_like',
    'less_than',
    'kron',
    'clip',
    'Tensor',
    'crop',
    'ParamAttr',
    'stanh',
    'randint',
    'randint_like',
    'assign',
    'gather',
    'scale',
    'zeros',
    'rsqrt',
    'squeeze',
    'squeeze_',
    'to_tensor',
    'gather_nd',
    'isinf',
    'uniform',
    'floor_divide',
    'remainder',
    'floor_mod',
    'roll',
    'batch',
    'max',
    'amax',
    'logical_or',
    'bitwise_and',
    'bitwise_or',
    'bitwise_xor',
    'bitwise_not',
    'mm',
    'flip',
    'rot90',
    'bincount',
    'histogram',
    'multiplex',
    'CUDAPlace',
    'NPUPlace',
    'empty',
    'shape',
    'real',
    'imag',
    'is_floating_point',
    'complex',
    'reciprocal',
    'rand',
    'less_equal',
    'triu',
    'sin',
    'dist',
    'unbind',
    'meshgrid',
    'arange',
    'load',
    'numel',
    'median',
    'nanmedian',
    'quantile',
    'nanquantile',
    'no_grad',
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Hui Zhang 已提交
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    'enable_grad',
541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593
    'set_grad_enabled',
    'is_grad_enabled',
    'mod',
    'abs',
    'tril',
    'pow',
    'zeros_like',
    'maximum',
    'topk',
    'index_select',
    'CPUPlace',
    'matmul',
    'seed',
    'acos',
    'logical_xor',
    'exp',
    'expm1',
    'bernoulli',
    'poisson',
    'sinh',
    'round',
    'DataParallel',
    'argmin',
    'prod',
    'broadcast_shape',
    'conj',
    'neg',
    'lgamma',
    'lerp',
    'erfinv',
    'inner',
    'outer',
    'square',
    'divide',
    'ceil',
    'atan',
    'atan2',
    'rad2deg',
    'deg2rad',
    'gcd',
    'lcm',
    'expand',
    'broadcast_to',
    'ones_like',
    'index_sample',
    'cast',
    'grad',
    'all',
    'ones',
    'not_equal',
    'sum',
    'nansum',
    'nanmean',
594
    'count_nonzero',
595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616
    'tile',
    'greater_equal',
    'isfinite',
    'create_parameter',
    'dot',
    'increment',
    'erf',
    'bmm',
    'chunk',
    'tolist',
    'tensordot',
    'greater_than',
    'shard_index',
    'argsort',
    'tanh',
    'tanh_',
    'transpose',
    'randn',
    'strided_slice',
    'unique',
    'unique_consecutive',
    'set_cuda_rng_state',
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QingshuChen 已提交
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    'set_rng_state',
618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678
    'set_printoptions',
    'std',
    'flatten',
    'asin',
    'multiply',
    'disable_static',
    'masked_select',
    'var',
    'trace',
    'enable_static',
    'scatter_nd',
    'set_default_dtype',
    'disable_signal_handler',
    'expand_as',
    'stack',
    'sqrt',
    'randperm',
    'linspace',
    'logspace',
    'reshape',
    'reshape_',
    'reverse',
    'nonzero',
    'CUDAPinnedPlace',
    'logical_not',
    'add_n',
    'minimum',
    'scatter',
    'scatter_',
    'floor',
    'cosh',
    'log',
    'log2',
    'log10',
    'concat',
    'check_shape',
    'trunc',
    'frac',
    'digamma',
    'standard_normal',
    'diagonal',
    'broadcast_tensors',
    'einsum',
    'set_flags',
    'get_flags',
    'asinh',
    'acosh',
    'atanh',
    'as_complex',
    'as_real',
    'diff',
    'angle',
    'fmax',
    'fmin',
    'moveaxis',
    'repeat_interleave',
    'clone',
    'kthvalue',
    'renorm',
    'take_along_axis',
    'put_along_axis',
679
    'nan_to_num',
680 681
    'heaviside',
    'tril_indices',
L
Li Min 已提交
682 683
    'index_add',
    "index_add_",
684
    'sgn',
685
    'triu_indices',
686
    'take',
687
    'frexp',
688
]