# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
# 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.
try:
 from paddle.version import full_version as __version__
 from paddle.version import commit as __git_commit__

except ImportError:
 import sys
 sys.stderr.write('''Warning with import paddle: you should not
 import paddle from the source directory; please install paddlepaddle*.whl firstly.'''
 )

from .batch import batch # noqa: F401
from .fluid import monkey_patch_variable
from .fluid.dygraph import monkey_patch_math_varbase
monkey_patch_variable()
monkey_patch_math_varbase()
from .framework.dtype import dtype as dtype # noqa: F401
from paddle.framework.dtype import uint8 # noqa: F401
from paddle.framework.dtype import int8 # noqa: F401
from paddle.framework.dtype import int16 # noqa: F401
from paddle.framework.dtype import int32 # noqa: F401
from paddle.framework.dtype import int64 # noqa: F401
from paddle.framework.dtype import float16 # noqa: F401
from paddle.framework.dtype import float32 # noqa: F401
from paddle.framework.dtype import float64 # noqa: F401
from paddle.framework.dtype import bfloat16 # noqa: F401
from paddle.framework.dtype import bool # noqa: F401
from paddle.framework.dtype import complex64 # noqa: F401
from paddle.framework.dtype import complex128 # noqa: F401
from .framework import VarBase as Tensor # noqa: F401
Tensor.__qualname__ = 'Tensor' # noqa: F401
import paddle.compat # 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
import paddle.device # noqa: F401

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

from .tensor.random import bernoulli # noqa: F401

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
from .tensor.creation import to_tensor # noqa: F401
from .tensor.creation import diag # noqa: F401
from .tensor.creation import diagflat # noqa: F401
from .tensor.creation import eye # noqa: F401
from .tensor.creation import linspace # noqa: F401
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
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
from .tensor.linalg import mv # noqa: F401
from .tensor.logic import equal # noqa: F401
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
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
from .tensor.logic import not_equal # noqa: F401
from .tensor.logic import allclose # noqa: F401
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
from .tensor.manipulation import broadcast_tensors # noqa: F401
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
from .tensor.manipulation import split # noqa: F401
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
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
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
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
from .tensor.math import atan2 # noqa: F401
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
from .tensor.math import exp # noqa: F401
from .tensor.math import expm1 # noqa: F401
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
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
from .tensor.math import min # noqa: F401
from .tensor.math import minimum # noqa: F401
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
from .tensor.math import mod # noqa: F401
from .tensor.math import floor_mod # noqa: F401
from .tensor.math import multiply # noqa: F401
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
from .tensor.math import diagonal # noqa: F401
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
from .tensor.math import trunc # noqa: F401
from .tensor.math import digamma # noqa: F401
from .tensor.math import neg # noqa: F401
from .tensor.math import lgamma # noqa: F401

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
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
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

from .tensor.to_string import set_printoptions # noqa: F401

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
from .framework import ParamAttr # noqa: F401
from .framework import create_parameter # noqa: F401
from .framework import CPUPlace # noqa: F401
from .framework import CUDAPlace # noqa: F401
from .framework import NPUPlace # noqa: F401
from .framework import CUDAPinnedPlace # noqa: F401

from .framework import grad # noqa: F401
from .framework import no_grad # noqa: F401
from .framework import set_grad_enabled # noqa: F401
from .framework import save # noqa: F401
from .framework import load # noqa: F401
from .framework import DataParallel # noqa: F401

from .framework import set_default_dtype # noqa: F401
from .framework import get_default_dtype # noqa: F401

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
from .device import get_cudnn_version # noqa: F401
from .device import set_device # noqa: F401
from .device import get_device # noqa: F401
from .fluid.framework import is_compiled_with_cuda # noqa: F401
from .fluid.framework import is_compiled_with_rocm # noqa: F401
from .device import is_compiled_with_xpu # noqa: F401
from .device import is_compiled_with_npu # noqa: F401
from .device import XPUPlace # 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.layers import crop_tensor as crop # noqa: F401

# high-level api
from .hapi import Model # noqa: F401
from . import callbacks # noqa: F401
from .hapi import summary # noqa: F401
from .hapi import flops # noqa: F401
from . import hub # noqa: F401
from . import linalg # noqa: F401

import paddle.text # noqa: F401
import paddle.vision # noqa: F401

from .tensor.random import check_shape # noqa: F401
disable_static()

__all__ = [ # noqa
 'dtype',
 'uint8',
 'int8',
 'int16',
 'int32',
 'int64',
 'float16',
 'float32',
 'float64',
 'bfloat16',
 'bool',
 'complex64',
 'complex128',
 'addmm',
 'allclose',
 't',
 'add',
 'subtract',
 'diag',
 'diagflat',
 'isnan',
 'scatter_nd_add',
 'unstack',
 'get_default_dtype',
 'save',
 'multinomial',
 'get_cuda_rng_state',
 'rank',
 'empty_like',
 'eye',
 'cumsum',
 'sign',
 'is_empty',
 'equal',
 'equal_all',
 'is_tensor',
 'cross',
 'where',
 'log1p',
 'cos',
 'tan',
 'mean',
 'mv',
 'in_dynamic_mode',
 'min',
 'any',
 'slice',
 'normal',
 'logsumexp',
 'full',
 'unsqueeze',
 'unsqueeze_',
 'argmax',
 'Model',
 'summary',
 'flops',
 'sort',
 'split',
 'logical_and',
 'full_like',
 'less_than',
 'kron',
 'clip',
 'Tensor',
 'crop',
 'ParamAttr',
 'stanh',
 'randint',
 'assign',
 'gather',
 'scale',
 'zeros',
 'rsqrt',
 'squeeze',
 'squeeze_',
 'to_tensor',
 'gather_nd',
 'isinf',
 'uniform',
 'floor_divide',
 'remainder',
 'floor_mod',
 'roll',
 'batch',
 'max',
 'norm',
 'logical_or',
 'bitwise_and',
 'bitwise_or',
 'bitwise_xor',
 'bitwise_not',
 'mm',
 'flip',
 'histogram',
 'multiplex',
 'CUDAPlace',
 'NPUPlace',
 'empty',
 'shape',
 'real',
 'imag',
 'reciprocal',
 'rand',
 'less_equal',
 'triu',
 'sin',
 'dist',
 'unbind',
 'meshgrid',
 'arange',
 'load',
 'numel',
 'median',
 'inverse',
 'no_grad',
 'set_grad_enabled',
 'mod',
 'abs',
 'tril',
 'pow',
 'zeros_like',
 'maximum',
 'topk',
 'index_select',
 'CPUPlace',
 'matmul',
 'seed',
 'acos',
 'logical_xor',
 'exp',
 'expm1',
 'bernoulli',
 'sinh',
 'round',
 'DataParallel',
 'argmin',
 'prod',
 'broadcast_shape',
 'conj',
 'neg',
 'lgamma',
 'square',
 'divide',
 'ceil',
 'atan',
 'atan2',
 'expand',
 'broadcast_to',
 'ones_like',
 'index_sample',
 'cast',
 'grad',
 'all',
 'ones',
 'not_equal',
 'sum',
 'tile',
 'greater_equal',
 'isfinite',
 'create_parameter',
 'dot',
 'increment',
 'erf',
 'bmm',
 'chunk',
 'tolist',
 'greater_than',
 'shard_index',
 'argsort',
 'tanh',
 'tanh_',
 'transpose',
 'randn',
 'strided_slice',
 'unique',
 'set_cuda_rng_state',
 'set_printoptions',
 'std',
 'flatten',
 'asin',
 'multiply',
 'disable_static',
 'masked_select',
 'var',
 'trace',
 'enable_static',
 'scatter_nd',
 'set_default_dtype',
 'expand_as',
 'stack',
 'sqrt',
 'cholesky',
 'randperm',
 'linspace',
 'reshape',
 'reshape_',
 'reverse',
 'nonzero',
 'CUDAPinnedPlace',
 'logical_not',
 'add_n',
 'minimum',
 'scatter',
 'scatter_',
 'floor',
 'cosh',
 'log',
 'log2',
 'log10',
 'concat',
 'check_shape',
 'trunc',
 'digamma',
 'standard_normal',
 'diagonal',
 'broadcast_tensors',
]