From 42eb56e248543830a08a115d775f135aae8be954 Mon Sep 17 00:00:00 2001 From: zhiboniu <31800336+zhiboniu@users.noreply.github.com> Date: Tue, 22 Feb 2022 20:38:30 +0800 Subject: [PATCH] unset fluid in tensor (#35082) --- python/paddle/framework/__init__.py | 7 +- python/paddle/tensor/attribute.py | 7 +- python/paddle/tensor/creation.py | 32 ++++--- python/paddle/tensor/einsum.py | 9 +- python/paddle/tensor/linalg.py | 69 ++++++++------- python/paddle/tensor/logic.py | 26 +++--- python/paddle/tensor/manipulation.py | 48 +++++----- python/paddle/tensor/math.py | 128 ++++++++++++++------------- python/paddle/tensor/random.py | 27 +++--- python/paddle/tensor/search.py | 73 +++++++-------- python/paddle/tensor/stat.py | 13 ++- python/paddle/tensor/to_string.py | 2 +- 12 files changed, 223 insertions(+), 218 deletions(-) diff --git a/python/paddle/framework/__init__.py b/python/paddle/framework/__init__.py index 7da9c0accfb..b13aefb58c0 100644 --- a/python/paddle/framework/__init__.py +++ b/python/paddle/framework/__init__.py @@ -32,7 +32,7 @@ from ..fluid.core import MLUPlace # noqa: F401 from ..fluid.core import CustomPlace # noqa: F401 from ..fluid.core import VarBase # noqa: F401 -from paddle.fluid import core # noqa: F401 +from ..fluid import core # noqa: F401 from ..fluid.dygraph.base import no_grad_ as no_grad # noqa: F401 from ..fluid.dygraph.base import grad # noqa: F401 from .io import save # noqa: F401 @@ -47,5 +47,10 @@ from ..fluid.framework import set_flags # noqa: F401 from ..fluid.dygraph.base import enable_dygraph as disable_static # noqa: F401 from ..fluid.dygraph.base import disable_dygraph as enable_static # noqa: F401 from ..fluid.framework import in_dygraph_mode as in_dynamic_mode # noqa: F401 +from ..fluid.framework import _current_expected_place, _get_paddle_place # noqa: F401 +from ..fluid.framework import dygraph_only # noqa: F401 +from ..fluid.framework import convert_np_dtype_to_dtype_, _varbase_creator, OpProtoHolder # noqa: F401 +from ..fluid.framework import _in_eager_mode # noqa: F401 +from ..fluid.framework import _dygraph_tracer # noqa: F401 __all__ = [] diff --git a/python/paddle/tensor/attribute.py b/python/paddle/tensor/attribute.py index ee84b43e13f..b851f6db4ac 100644 --- a/python/paddle/tensor/attribute.py +++ b/python/paddle/tensor/attribute.py @@ -14,7 +14,7 @@ from __future__ import print_function -from ..fluid.framework import core, in_dygraph_mode, Variable +from ..framework import core from ..fluid.layer_helper import LayerHelper from ..fluid.data_feeder import check_variable_and_dtype @@ -23,6 +23,7 @@ from ..fluid.layers import rank # noqa: F401 from ..fluid.layers import shape # noqa: F401 import paddle from paddle import _C_ops +from paddle.static import Variable __all__ = [] @@ -184,7 +185,7 @@ def real(x, name=None): # [[1., 2., 3.], # [4., 5., 6.]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.real(x) check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'real') @@ -228,7 +229,7 @@ def imag(x, name=None): # [[6., 5., 4.], # [3., 2., 1.]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.imag(x) check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'imag') diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py index 934ccfa7264..ae563e641e3 100644 --- a/python/paddle/tensor/creation.py +++ b/python/paddle/tensor/creation.py @@ -18,21 +18,19 @@ from paddle.common_ops_import import fill_constant from ..fluid.layers import utils from ..fluid.layers import tensor -from ..fluid.framework import Variable -from ..fluid.framework import unique_name -from ..fluid.framework import _current_expected_place, _get_paddle_place -from ..fluid.framework import dygraph_only -from ..fluid.initializer import Constant -from ..fluid.layers import core +from ..static import Variable, device_guard +from ..framework import _current_expected_place, _get_paddle_place +from ..framework import dygraph_only +from ..framework import core from ..fluid.layer_helper import LayerHelper from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, convert_dtype -from ..fluid.framework import convert_np_dtype_to_dtype_, in_dygraph_mode, _varbase_creator, device_guard, OpProtoHolder +from ..framework import convert_np_dtype_to_dtype_, _varbase_creator, OpProtoHolder from paddle.tensor.attribute import _complex_to_real_dtype, _real_to_complex_dtype # TODO: define functions to get create a tensor from ..fluid.layers import linspace # noqa: F401 import paddle from paddle import _C_ops -from ..fluid.framework import _in_eager_mode +from ..framework import _in_eager_mode __all__ = [] @@ -214,7 +212,7 @@ def full_like(x, fill_value, dtype=None, name=None): if not isinstance(dtype, core.VarDesc.VarType): dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.fill_any_like(x, 'value', fill_value, 'dtype', dtype) helper = LayerHelper("full_like", **locals()) @@ -648,7 +646,7 @@ def tril(x, diagonal=0, name=None): # [ 9, 10, 0, 0]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): op = getattr(_C_ops, 'tril_triu') return op(x, 'diagonal', diagonal, "lower", True) @@ -715,7 +713,7 @@ def triu(x, diagonal=0, name=None): # [ 0, 10, 11, 12]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): op = getattr(_C_ops, 'tril_triu') return op(x, 'diagonal', diagonal, "lower", False) @@ -757,7 +755,7 @@ def meshgrid(*args, **kwargs): if len(args) == 1 and isinstance(args[0], (list, tuple)): args = args[0] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): num = len(args) out = _C_ops.meshgrid(list(args), num) return out @@ -862,7 +860,7 @@ def diagflat(x, offset=0, name=None): # [0 0 0 4 0]] """ padding_value = 0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if len(x.shape) == 1: return _C_ops.diag_v2(x, "offset", offset, "padding_value", padding_value) @@ -976,7 +974,7 @@ def diag(x, offset=0, padding_value=0, name=None): print(y.numpy()) # [4] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.diag_v2(x, "offset", offset, "padding_value", padding_value) @@ -1057,7 +1055,7 @@ def empty(shape, dtype=None, name=None): dtype = convert_dtype(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): shape = utils.convert_shape_to_list(shape) out = _C_ops.empty('shape', shape, 'dtype', convert_np_dtype_to_dtype_(dtype)) @@ -1125,7 +1123,7 @@ def empty_like(x, dtype=None, name=None): dtype = x.dtype dtype = convert_dtype(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out = _C_ops.empty('shape', x.shape, 'dtype', convert_np_dtype_to_dtype_(dtype)) out.stop_gradient = True @@ -1309,7 +1307,7 @@ def complex(real, imag, name=None): # [[0.+0.j 0.+1.j 0.+2.j] # [1.+0.j 1.+1.j 1.+2.j]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return paddle._C_ops.complex(real, imag) check_variable_and_dtype(real, 'real', ['float32', 'float64'], 'complex') diff --git a/python/paddle/tensor/einsum.py b/python/paddle/tensor/einsum.py index e5d947294d9..040480c26fa 100644 --- a/python/paddle/tensor/einsum.py +++ b/python/paddle/tensor/einsum.py @@ -15,9 +15,8 @@ import itertools import re -from ..fluid.layers import reshape, transpose -from .linalg import matmul -from .manipulation import squeeze, unsqueeze +from .linalg import matmul, transpose +from .manipulation import squeeze, unsqueeze, reshape from .math import multiply from .math import sum as paddle_sum @@ -792,10 +791,10 @@ def einsum(equation, *operands): - For any free label which is not present for the output, it's lowered to a dummy label. - Examples - - '...ij, ...jk'，where i and k are free labels, j is dummy. The output label + - '...ij, ...jk', where i and k are free labels, j is dummy. The output label string is '...ik' - 'ij -> i', where i is a free label and j is a dummy label. - - '...ij, ...jk -> ...ijk'，where i, j and k are all free labels. + - '...ij, ...jk -> ...ijk', where i, j and k are all free labels. - '...ij, ...jk -> ij', an invalid equation since `...` is not present for the output. diff --git a/python/paddle/tensor/linalg.py b/python/paddle/tensor/linalg.py index 170889588aa..91d688b761a 100644 --- a/python/paddle/tensor/linalg.py +++ b/python/paddle/tensor/linalg.py @@ -14,8 +14,9 @@ import numpy as np from ..fluid.layer_helper import LayerHelper -from ..fluid.framework import in_dygraph_mode, _varbase_creator, Variable, _dygraph_tracer +from ..framework import _varbase_creator, _dygraph_tracer from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype +from ..static import Variable from ..fluid.layers import transpose, cast # noqa: F401 from ..fluid import layers @@ -133,7 +134,7 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None): """ op_type = 'matmul_v2' - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): op = getattr(_C_ops, op_type) return op(x, y, 'trans_x', transpose_x, 'trans_y', transpose_y) @@ -245,7 +246,7 @@ def norm(x, p='fro', axis=None, keepdim=False, name=None): raise ValueError( "The dim of frobenius norm op should be None or two elements list!" ) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if dim is None: return _C_ops.frobenius_norm(input, 'keep_dim', keepdim, 'reduce_all', True) @@ -282,7 +283,7 @@ def norm(x, p='fro', axis=None, keepdim=False, name=None): axis (int, optional): None for last dimension. keepdim (bool, optional): Whether keep the dimensions as the `input`, Default False. """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if axis is None: axis = -1 return _C_ops.p_norm(input, 'porder', porder, 'axis', axis, 'keepdim', keepdim, 'asvector', asvector) @@ -642,7 +643,7 @@ def cond(x, p=None, name=None): axis = axis if axis != None and axis != [] else [0] keepdim = False - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): abs_out = _C_ops.abs(input) sum_out = _C_ops.reduce_sum(abs_out, 'dim', axis, 'keepdim', keepdim, 'reduce_all', reduce_all) @@ -699,7 +700,7 @@ def cond(x, p=None, name=None): reduce_all = True if axis is None or axis == [] else False keepdim = False - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): pow_out = _C_ops.pow(input, 'factor', porder) sum_out_1 = _C_ops.reduce_sum(pow_out, 'dim', axis, 'keepdim', keepdim, 'reduce_all', reduce_all) @@ -753,7 +754,7 @@ def cond(x, p=None, name=None): u, s, vh = svd(input, full_matrices=False) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if porder == "nuc": return _C_ops.reduce_sum(s, 'dim', axis, 'keepdim', keepdim, 'reduce_all', reduce_all) @@ -820,7 +821,7 @@ def cond(x, p=None, name=None): return out def empty_tensor(input, shape): - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return input.reshape(shape) raise ValueError("only support x is nonempty tensor in static mode") @@ -895,7 +896,7 @@ def dot(x, y, name=None): """ op_type = 'dot' # skip var type check in dygraph mode to improve efficiency - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): op = getattr(_C_ops, op_type) return op(x, y) @@ -1079,7 +1080,7 @@ def t(input, name=None): "Input(input) only support N-D (N<=2) tensor, but received " "length of Input(input) is %s. Perhaps you can use paddle." "tensor.transpose() instead." % len(input.shape)) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if len(input.shape) == 1: return input # 2-D tensor @@ -1144,7 +1145,7 @@ def cross(x, y, axis=None, name=None): # [0. 0. 0.] # [0. 0. 0.]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if axis is not None: return _C_ops.cross(x, y, 'dim', axis) else: @@ -1203,7 +1204,7 @@ def cholesky(x, upper=False, name=None): # [1.25450498 0.05600871 0.06400121]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.cholesky(x, "upper", upper) check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'cholesky') check_type(upper, 'upper', bool, 'cholesky') @@ -1257,7 +1258,7 @@ def matrix_rank(x, tol=None, hermitian=False, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if tol is None: tol_tensor = None tol_attr = 0.0 @@ -1355,7 +1356,7 @@ def bmm(x, y, name=None): "x's batch (shape[0]) must be equal with y's batch (shape[0]). But received x's shape: {}, y's shape: {}". format(x_shape, y_shape)) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.bmm(x, y) helper = LayerHelper('bmm', **locals()) @@ -1388,7 +1389,7 @@ def histogram(input, bins=100, min=0, max=0, name=None): result = paddle.histogram(inputs, bins=4, min=0, max=3) print(result) # [0, 2, 1, 0] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.histogram(input, "bins", bins, "min", min, "max", max) helper = LayerHelper('histogram', **locals()) @@ -1435,7 +1436,7 @@ def bincount(x, weights=None, minlength=0, name=None): if x.dtype not in [paddle.int32, paddle.int64]: raise TypeError("Elements in Input(x) should all be integers") - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.bincount(x, weights, "minlength", minlength) helper = LayerHelper('bincount', **locals()) @@ -1488,7 +1489,7 @@ def mv(x, vec, name=None): vec = paddle.to_tensor(vec_data).astype("float64") out = paddle.mv(x, vec) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out = _C_ops.mv(x, vec) return out @@ -1541,7 +1542,7 @@ def det(x, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.determinant(x) check_dtype(x.dtype, 'Input', ['float32', 'float64'], 'det') @@ -1596,7 +1597,7 @@ def slogdet(x, name=None): # [-0.98610914, -0.43010661, -0.10872950]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.slogdeterminant(x) check_dtype(x.dtype, 'Input', ['float32', 'float64'], 'slogdet') @@ -1669,7 +1670,7 @@ def svd(x, full_matrices=False, name=None): # V * VH == I """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.svd(x, 'full_matrices', full_matrices) check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'svd') check_type(full_matrices, 'full_matrices', bool, 'svd') @@ -1744,7 +1745,7 @@ def matrix_power(x, n, name=None): # [-7.66666667 , 8. , -1.83333333 ], # [ 1.80555556 , -1.91666667 , 0.44444444 ]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.matrix_power(x, "n", n) check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'matrix_power') @@ -1801,7 +1802,7 @@ def qr(x, mode="reduced", name=None): # one can verify : X = Q * R ; """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): q, r = _C_ops.qr(x, 'mode', mode) if mode == "r": return r @@ -1900,7 +1901,7 @@ def lu(x, pivot=True, get_infos=False, name=None): # one can verify : X = P @ L @ U ; """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): LU, Piv, Info = _C_ops.lu(x, 'pivots', pivot) if get_infos: return LU, Piv, Info @@ -1997,7 +1998,7 @@ def lu_unpack(x, y, unpack_ludata=True, unpack_pivots=True, name=None): # one can verify : X = P @ L @ U ; """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): P, L, U = _C_ops.lu_unpack(x, y, 'unpack_ludata', unpack_ludata, 'unpack_pivots', unpack_pivots) return P, L, U @@ -2070,7 +2071,7 @@ def eig(x, name=None): # [ (16.50471283351188+0j) , (-5.5034820550763515+0j) , # (-0.21026087843552282+0j)]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): w, v = _C_ops.eig(x) return w, v @@ -2139,7 +2140,7 @@ def eigvals(x, name=None): "The last two dimensions of Input(x) should be equal, but received x's shape = {}". format(x_shape)) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.eigvals(x) helper = LayerHelper('eigvals', **locals()) @@ -2210,7 +2211,7 @@ def multi_dot(x, name=None): # [10, 7] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.multi_dot(x) check_type(x, 'x', (list, tuple), 'multi_dot') @@ -2262,7 +2263,7 @@ def eigh(x, UPLO='L', name=None): #[ 0.3826834323650898j , -0.9238795325112867j ]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.eigh(x, 'UPLO', UPLO) def __check_input(x, UPLO): @@ -2361,7 +2362,7 @@ def pinv(x, rcond=1e-15, hermitian=False, name=None): # or out * x * out = x ; """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if not hermitian: # combine svd and matmul op u, s, vt = _C_ops.svd(x, 'full_matrices', False) @@ -2611,7 +2612,7 @@ def solve(x, y, name=None): print(out) # [2., 3.]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.solve(x, y) inputs = {"X": [x], "Y": [y]} @@ -2675,7 +2676,7 @@ def triangular_solve(x, print(out) # [7, -2, -5] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.triangular_solve(x, y, 'upper', upper, 'transpose', transpose, 'unitriangular', unitriangular) @@ -2732,7 +2733,7 @@ def cholesky_solve(x, y, upper=False, name=None): print(out) # [-2.5, -7, 9.5] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.cholesky_solve(x, y, 'upper', upper) helper = LayerHelper("cholesky_solve", **locals()) @@ -2776,7 +2777,7 @@ def eigvalsh(x, UPLO='L', name=None): print(out_value) #[0.17157288, 5.82842712] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): is_test = x.stop_gradient values, _ = _C_ops.eigvalsh(x, 'UPLO', UPLO, 'is_test', is_test) return values @@ -2904,7 +2905,7 @@ def lstsq(x, y, rcond=None, driver=None, name=None): elif x.dtype == paddle.float64: rcond = 1e-15 * max(x.shape[-2], x.shape[-1]) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): solution, rank, singular_values = _C_ops.lstsq(x, y, "rcond", rcond, "driver", driver) if x.shape[-2] > x.shape[-1]: diff --git a/python/paddle/tensor/logic.py b/python/paddle/tensor/logic.py index a9ec4891182..858f9139231 100755 --- a/python/paddle/tensor/logic.py +++ b/python/paddle/tensor/logic.py @@ -15,8 +15,7 @@ from ..fluid.layer_helper import LayerHelper from ..fluid.data_feeder import check_type, check_variable_and_dtype from ..fluid.layers.layer_function_generator import templatedoc -from .. import fluid -from ..fluid.framework import in_dygraph_mode, Variable +from ..static import Variable from ..framework import VarBase as Tensor # TODO: define logic functions of a tensor @@ -25,8 +24,7 @@ from ..fluid.layers import logical_and # noqa: F401 from ..fluid.layers import logical_not # noqa: F401 from ..fluid.layers import logical_or # noqa: F401 from ..fluid.layers import logical_xor # noqa: F401 - -from paddle.common_ops_import import core +import paddle from paddle import _C_ops from paddle.tensor.creation import full @@ -61,7 +59,7 @@ def equal_all(x, y, name=None): result2 = paddle.equal_all(x, z) print(result2) # result2 = [False ] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.equal_all(x, y) helper = LayerHelper("equal_all", **locals()) @@ -124,7 +122,7 @@ def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None): # [True] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.allclose(x, y, 'rtol', str(rtol), 'atol', str(atol), 'equal_nan', equal_nan) @@ -182,7 +180,7 @@ def equal(x, y, name=None): if not isinstance(y, Variable): y = full(shape=[1], dtype=x.dtype, fill_value=y) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.equal(x, y) check_variable_and_dtype( @@ -224,7 +222,7 @@ def greater_equal(x, y, name=None): result1 = paddle.greater_equal(x, y) print(result1) # result1 = [True False True] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.greater_equal(x, y) check_variable_and_dtype(x, "x", @@ -270,7 +268,7 @@ def greater_than(x, y, name=None): result1 = paddle.greater_than(x, y) print(result1) # result1 = [False False True] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.greater_than(x, y) check_variable_and_dtype(x, "x", @@ -317,7 +315,7 @@ def less_equal(x, y, name=None): result1 = paddle.less_equal(x, y) print(result1) # result1 = [True True False] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.less_equal(x, y) check_variable_and_dtype( @@ -360,7 +358,7 @@ def less_than(x, y, name=None): result1 = paddle.less_than(x, y) print(result1) # result1 = [False True False] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.less_than(x, y) check_variable_and_dtype( @@ -403,7 +401,7 @@ def not_equal(x, y, name=None): result1 = paddle.not_equal(x, y) print(result1) # result1 = [False True True] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.not_equal(x, y) check_variable_and_dtype( @@ -449,7 +447,7 @@ def is_tensor(x): def _bitwise_op(op_name, x, y, out=None, name=None, binary_op=True): - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): op = getattr(_C_ops, op_name) if binary_op: return op(x, y) @@ -637,7 +635,7 @@ def isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None): # [True, True] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.isclose(x, y, 'rtol', str(rtol), 'atol', str(atol), 'equal_nan', equal_nan) diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py index 4df026cfa48..53bb9a88075 100755 --- a/python/paddle/tensor/manipulation.py +++ b/python/paddle/tensor/manipulation.py @@ -15,11 +15,11 @@ from __future__ import print_function from collections import Counter -from ..fluid.layers import core +from ..static import Variable, device_guard +from ..framework import core from ..fluid.layer_helper import LayerHelper -from ..fluid.framework import Variable, OpProtoHolder, in_dygraph_mode, convert_np_dtype_to_dtype_, device_guard, dygraph_only +from ..framework import OpProtoHolder, convert_np_dtype_to_dtype_, dygraph_only from ..fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype -from ..fluid.layers.tensor import fill_constant from ..fluid.layers import utils import numpy as np # TODO: define functions to manipulate a tensor @@ -378,7 +378,7 @@ def broadcast_tensors(input, name=None): """ num_inputs = len(input) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.broadcast_tensors(input, num_inputs) check_type(input, 'input', (list, tuple), 'broadcast_tensors') @@ -475,7 +475,7 @@ def flip(x, axis, name=None): """ if isinstance(axis, int): axis = [axis] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.flip(x, "axis", axis) helper = LayerHelper("flip", **locals()) @@ -671,7 +671,7 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None): if not (isinstance(x, Variable)): raise ValueError("The input x should be a Tensor") - if not in_dygraph_mode(): + if not paddle.in_dynamic_mode(): check_variable_and_dtype( x, 'x', ['float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8'], @@ -693,7 +693,7 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None): if start_axis > stop_axis: raise ValueError("The stop_axis should be larger than stat_axis") - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): dy_out, _ = _C_ops.flatten_contiguous_range(x, 'start_axis', start_axis, 'stop_axis', stop_axis) return dy_out @@ -792,7 +792,7 @@ def roll(x, shifts, axis=None, name=None): else: axis = [] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.roll(x, 'axis', axis, 'shifts', shifts) helper = LayerHelper("roll", **locals()) @@ -1108,7 +1108,7 @@ def unique_consecutive(x, else: axis = [axis] attr_dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out, inverse, counts = _C_ops.unique_consecutive( x, 'dtype', attr_dtype, 'return_inverse', return_inverse, 'return_counts', return_counts, 'axis', axis) @@ -1213,7 +1213,7 @@ def unique(x, else: axis = [axis] attr_dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out, inverse, indices, counts = _C_ops.unique( x, 'dtype', attr_dtype, 'return_index', return_index, 'return_inverse', return_inverse, 'return_counts', return_counts, @@ -1397,7 +1397,7 @@ def gather(x, index, axis=None, name=None): if axis is None: axis = 0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): axis = axis.item() if isinstance(axis, paddle.Tensor) else axis return _C_ops.gather(x, index, None, "axis", axis, "overwrite", False) @@ -1471,7 +1471,7 @@ def unbind(input, axis=0): input_shape = input.shape axis_ = axis if axis >= 0 else len(input_shape) + axis num = input_shape[axis_] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.unbind(input, num, 'axis', axis) helper = LayerHelper("unbind", **locals()) @@ -1565,7 +1565,7 @@ def scatter(x, index, updates, overwrite=True, name=None): # [2., 2.], # [1., 1.]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.scatter(x, index, updates, 'overwrite', overwrite) check_variable_and_dtype( @@ -1744,7 +1744,7 @@ def tile(x, repeat_times, name=None): np_out = out.numpy() # [[1, 2, 3], [1, 2, 3]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.tile(x, 'repeat_times', repeat_times) check_type(repeat_times, 'repeat_times', (list, tuple, Variable), 'tile') if isinstance(repeat_times, Variable): @@ -1827,7 +1827,7 @@ def expand_as(x, y, name=None): np_out = out.numpy() # [[1, 2, 3], [1, 2, 3]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.expand_as_v2(x, 'target_shape', y.shape) check_variable_and_dtype( @@ -1881,7 +1881,7 @@ def broadcast_to(x, shape, name=None): print(out) # [[1, 2, 3], [1, 2, 3]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.expand_v2(x, 'shape', shape) if isinstance(shape, Variable): @@ -1968,7 +1968,7 @@ def expand(x, shape, name=None): print(out) # [[1, 2, 3], [1, 2, 3]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.expand_v2(x, 'shape', shape) if isinstance(shape, Variable): @@ -2407,7 +2407,7 @@ def tensordot(x, y, axes=2, name=None): check_type(axes, 'axes', (int, tuple, list, Variable), op_type) def _var_to_list(var): - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return tolist(var) raise TypeError( "The 'axes' with type 'Tensor' in " + op_type + @@ -2523,7 +2523,7 @@ def as_complex(x, name=None): # [[ 0. +1.j 2. +3.j 4. +5.j] # [ 6. +7.j 8. +9.j 10.+11.j]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return paddle._C_ops.as_complex(x) check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'as_complex') @@ -2572,7 +2572,7 @@ def as_real(x, name=None): # [ 8. 9.] # [10. 11.]]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return paddle._C_ops.as_real(x) check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'as_real') @@ -2626,7 +2626,7 @@ def repeat_interleave(x, repeats, axis=None, name=None): x = paddle.flatten(x) axis = 0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if isinstance(repeats, int): return _C_ops.repeat_interleave(x, None, 'Repeats', repeats, 'dim', axis) @@ -2733,7 +2733,7 @@ def moveaxis(x, source, destination, name=None): for i in range(len(src_dims)): perm[dst_dims[i]] = src_dims[i] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out, _ = _C_ops.transpose2(x, 'axis', perm) return out @@ -2814,7 +2814,7 @@ def take_along_axis(arr, indices, axis): if not broadcast_shape: # if indices matrix have larger size than arr, arr should broadcast into indices shape. broadcast_shape = indices.shape - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): indices = paddle.broadcast_to(indices, broadcast_shape) broadcast_shape_list = list(broadcast_shape) broadcast_shape_list[axis] = list(arr.shape)[axis] @@ -2879,7 +2879,7 @@ def put_along_axis(arr, indices, values, axis, reduce='assign'): "`indices` and `arr` must have the same number of dimensions!") axis = non_negative_axis(arr, axis) broadcast_shape = infer_broadcast_shape(arr, indices, axis) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): values = paddle.to_tensor(values) if not isinstance( values, paddle.Tensor) else values if broadcast_shape: diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py index ba8a4d7f119..a36bf1c4325 100755 --- a/python/paddle/tensor/math.py +++ b/python/paddle/tensor/math.py @@ -26,8 +26,9 @@ from paddle.common_ops_import import dygraph_utils from paddle.tensor import cast from paddle.tensor.attribute import _complex_to_real_dtype import paddle -from ..fluid import layers -from ..fluid.framework import core, _varbase_creator, in_dygraph_mode, Variable, convert_np_dtype_to_dtype_ +from paddle.static import Variable +from ..framework import core +from ..framework import _varbase_creator, convert_np_dtype_to_dtype_ from ..fluid.layer_helper import LayerHelper from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, convert_dtype from ..fluid.layers.layer_function_generator import _generate_doc_string_, generate_activation_fn, generate_layer_fn @@ -70,7 +71,8 @@ from ..fluid.layers import acosh # noqa: F401 from ..fluid.layers import atanh # noqa: F401 from ..fluid.layers import multiplex # noqa: F401 -from ..fluid import layers +from ..fluid.layers import reduce_prod +from ..fluid.layers import elementwise_sub from paddle import _C_ops __all__ = [] @@ -147,7 +149,7 @@ def pow(x, y, name=None): """ # in dynamic graph mode - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if isinstance(y, (int, float)): return _C_ops.pow(x, 'factor', y) elif isinstance(y, (paddle.Tensor, Variable)): @@ -240,7 +242,7 @@ def add(x, y, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.elementwise_add(x, y) return _elementwise_op(LayerHelper('elementwise_add', **locals())) @@ -319,7 +321,7 @@ def subtract(x, y, name=None): op_type = 'elementwise_sub' axis = -1 act = None - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) return _elementwise_op(LayerHelper(op_type, **locals())) @@ -376,7 +378,7 @@ def divide(x, y, name=None): op_type = 'elementwise_div' axis = -1 act = None - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) @@ -415,7 +417,7 @@ def floor_divide(x, y, name=None): """ op_type = 'elementwise_floordiv' axis = -1 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, op_name=op_type) @@ -455,7 +457,7 @@ def remainder(x, y, name=None): """ op_type = 'elementwise_mod' axis = -1 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, op_name=op_type) @@ -505,7 +507,7 @@ def multiply(x, y, name=None): act = None axis = -1 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) @@ -570,7 +572,7 @@ def maximum(x, y, name=None): op_type = 'elementwise_max' axis = -1 act = None - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) return _elementwise_op(LayerHelper(op_type, **locals())) @@ -629,7 +631,7 @@ def minimum(x, y, name=None): op_type = 'elementwise_min' axis = -1 act = None - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) return _elementwise_op(LayerHelper(op_type, **locals())) @@ -690,7 +692,7 @@ def fmax(x, y, name=None): op_type = 'elementwise_fmax' axis = -1 act = None - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) return _elementwise_op(LayerHelper(op_type, **locals())) @@ -751,7 +753,7 @@ def fmin(x, y, name=None): op_type = 'elementwise_fmin' axis = -1 act = None - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _elementwise_op_in_dygraph( x, y, axis=axis, act=act, op_name=op_type) return _elementwise_op(LayerHelper(op_type, **locals())) @@ -860,7 +862,7 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None): return (False, src_type) dtype_flag, dtype = get_dtype(x, dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): axis = axis if axis != None and axis != [] else [0] if dtype_flag: return _C_ops.reduce_sum(x, 'dim', axis, 'keep_dim', keepdim, @@ -1024,7 +1026,7 @@ def add_n(inputs, name=None): # [[8., 10., 12.], # [14., 16., 18.]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if isinstance(inputs, Variable): inputs = [inputs] return _C_ops.sum(inputs, 'use_mkldnn', False) @@ -1080,7 +1082,7 @@ def trunc(input, name=None): # [[0., 0.], # [0., 0.]])) ''' - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.trunc(input) else: inputs = {"X": input} @@ -1164,7 +1166,7 @@ def mm(input, mat2, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.matmul_v2(input, mat2) def __check_input(x, y): @@ -1269,7 +1271,7 @@ def addmm(input, x, y, beta=1.0, alpha=1.0, name=None): - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out = _C_ops.addmm(input, x, y, "Alpha", alpha, "Beta", beta) return out @@ -1328,7 +1330,7 @@ def renorm(x, p, axis, max_norm): if not axis >= -1 * len(input_shape): raise ValueError("the axis:{} should not be less than -1 * length of input_shape:{}".format(axis,-1 * len(input_shape))) axis = axis + len(input_shape) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out = core.ops.renorm(x, 'p',p, 'axis',axis, 'max_norm', max_norm) return out @@ -1384,7 +1386,7 @@ def inner(x, y, name=None): nx = x.reshape((-1, xshape[-1])) ny = y.reshape((-1, yshape[-1])) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.matmul_v2(nx, ny.T).reshape(dstshape) def __check_input(x, y): @@ -1447,7 +1449,7 @@ def outer(x, y, name=None): nx = x.reshape((-1, 1)) ny = y.reshape((1, -1)) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.matmul_v2(nx, ny) def __check_input(x, y): @@ -1516,7 +1518,7 @@ def logsumexp(x, axis=None, keepdim=False, name=None): if axis is None or len(axis) == 0: axis = [0] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.logsumexp(x, 'axis', axis, 'keepdim', keepdim, 'reduce_all', reduce_all) check_variable_and_dtype(x, 'x', @@ -1560,7 +1562,7 @@ def inverse(x, name=None): print(inv) # [[0.5, 0], [0, 0.5]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.inverse(x) def _check_input(x): @@ -1676,7 +1678,7 @@ def max(x, axis=None, keepdim=False, name=None): """ reduce_all, axis = _get_reduce_all_value(axis) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.reduce_max(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all) @@ -1776,7 +1778,7 @@ def min(x, axis=None, keepdim=False, name=None): """ reduce_all, axis = _get_reduce_all_value(axis) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.reduce_min(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all) @@ -1889,7 +1891,7 @@ def amax(x, axis=None, keepdim=False, name=None): """ reduce_all, axis = _get_reduce_all_value(axis) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.reduce_amax(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all) helper = LayerHelper('amax', **locals()) @@ -2002,7 +2004,7 @@ def amin(x, axis=None, keepdim=False, name=None): """ reduce_all, axis = _get_reduce_all_value(axis) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.reduce_amin(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all) helper = LayerHelper('amin', **locals()) @@ -2046,7 +2048,7 @@ def log1p(x, name=None): # [[0.], [0.6931472]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.log1p(x) check_variable_and_dtype(x, 'x', ['float32', 'float64'], "log1p") @@ -2095,7 +2097,7 @@ def log2(x, name=None): res = paddle.log2(x_i) print(res) # [1.0] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.log2(x) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], "log2") @@ -2145,7 +2147,7 @@ def log10(x, name=None): res = paddle.log10(x_i) print(res) # [1.0] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.log10(x) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], "log10") @@ -2206,7 +2208,7 @@ def clip(x, min=None, max=None, name=None): min_ = float(np.finfo(np.float32).min) max_ = float(np.finfo(np.float32).max) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if isinstance(min, Variable): min = min.numpy().item(0) if isinstance(max, Variable): @@ -2339,7 +2341,7 @@ def trace(x, offset=0, axis1=0, axis2=1, name=None): "But received axis1 = %d, axis2 = %d\n"%(axis1, axis2) __check_input(input, offset, axis1, axis2) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.trace(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2) inputs = {'Input': [x]} @@ -2422,7 +2424,7 @@ def diagonal(x, offset=0, axis1=0, axis2=1, name=None): # [0.17020577, 0.27325270]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.diagonal(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2) def __check_input(input, offset, dim1, dim2): @@ -2499,7 +2501,7 @@ ${comment} # [12, 15, 18, 16, 20, 24], # [21, 24, 27, 28, 32, 36]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.kron(x, y) helper = LayerHelper('kron', **locals()) @@ -2557,9 +2559,9 @@ def cumsum(x, axis=None, dtype=None, name=None): else: flatten = False if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype): - x = layers.cast(x, dtype) + x = cast(x, dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if axis is None: return _C_ops.cumsum(x, 'flatten', flatten) else: @@ -2622,9 +2624,9 @@ def cumprod(x, dim=None, dtype=None, name=None): """ if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype): - x = layers.cast(x, dtype) + x = cast(x, dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.cumprod(x, 'dim', dim) check_variable_and_dtype(x, "x", ['complex64', 'complex128', 'float32', 'float64', 'int32', 'int64'], 'cumprod') @@ -2656,7 +2658,7 @@ def isfinite(x, name=None): out = paddle.tensor.isfinite(x) print(out) # [False True True False True False False] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.isfinite_v2(x) helper = LayerHelper("isfinite_v2", **locals()) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isfinite') @@ -2684,7 +2686,7 @@ def isinf(x, name=None): out = paddle.tensor.isinf(x) print(out) # [ True False False True False False False] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.isinf_v2(x) helper = LayerHelper("isinf_v2", **locals()) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isinf') @@ -2712,7 +2714,7 @@ def isnan(x, name=None): out = paddle.tensor.isnan(x) print(out) # [False False False False False True True] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.isnan_v2(x) helper = LayerHelper("isnan_v2", **locals()) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], 'isnan') @@ -2783,9 +2785,9 @@ def prod(x, axis=None, keepdim=False, dtype=None, name=None): if dtype is not None: check_dtype(dtype, 'dtype', ['float32', 'float64', 'int32', 'int64'], 'prod') if x.dtype != convert_np_dtype_to_dtype_(dtype): - x = layers.cast(x, dtype) + x = cast(x, dtype) - return layers.reduce_prod(input=x, dim=axis, keep_dim=keepdim, name=name) + return reduce_prod(input=x, dim=axis, keep_dim=keepdim, name=name) def sign(x, name=None): @@ -2809,7 +2811,7 @@ def sign(x, name=None): out = paddle.sign(x=x) print(out) # [1.0, 0.0, -1.0, 1.0] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.sign(x) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'sign') @@ -2846,7 +2848,7 @@ def tanh(x, name=None): print(out) # [-0.37994896 -0.19737532 0.09966799 0.29131261] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.tanh(x) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'tanh') @@ -2888,7 +2890,7 @@ def increment(x, value=1.0, name=None): # [1.] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.increment(x, 'step', value) check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'], @@ -2969,7 +2971,7 @@ def all(x, axis=None, keepdim=False, name=None): else: reduce_all_flag = False - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): axis = axis if axis != None and axis != [] else [0] return _C_ops.reduce_all(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all_flag) @@ -3061,7 +3063,7 @@ def any(x, axis=None, keepdim=False, name=None): else: reduce_all_flag = False - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): axis = axis if axis != None and axis != [] else [0] return _C_ops.reduce_any(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all_flag) @@ -3142,7 +3144,7 @@ def conj(x, name=None): # [(4-4j), (5-5j), (6-6j)]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.conj(x) check_variable_and_dtype(x, "x", ['complex64', 'complex128', 'float32', 'float64', 'int32', 'int64'], 'conj') @@ -3181,7 +3183,7 @@ def digamma(x, name=None): # [ nan , 5.32286835]]) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.digamma(x) check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'digamma') @@ -3212,7 +3214,7 @@ def neg(x, name=None): # [0.4 0.2 -0.1 -0.3] """ - return layers.scale(x, scale=-1.0, bias=0.0, bias_after_scale=True, act=None, name=name) + return scale(x, scale=-1.0, bias=0.0, bias_after_scale=True, act=None, name=name) def atan2(x, y, name=None): r""" @@ -3257,7 +3259,7 @@ def atan2(x, y, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.atan2(x, y) else: check_variable_and_dtype(x, 'x', ['int32', 'int64', 'float16', 'float32', 'float64'], 'atan2') @@ -3313,7 +3315,7 @@ def logit(x, eps=None, name=None): if eps == None: eps = 0.0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.logit(x, 'eps', eps) check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'logit') @@ -3356,7 +3358,7 @@ def lerp(x, y, weight, name=None): # out: [5.5., 6., 6.5, 7.] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): check_type(weight, 'weight', (float, paddle.Tensor, Variable), 'lerp') if isinstance(weight, float): weight = paddle.to_tensor(weight, dtype=x.dtype) @@ -3419,7 +3421,7 @@ def erfinv(x, name=None): """ check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'erfinv') - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.erfinv(x) helper = LayerHelper('erfinv', **locals()) @@ -3478,7 +3480,7 @@ def rad2deg(x, name=None): # [57.29578018]) """ rad2deg_scale = 180 / np.pi - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if convert_dtype(x.dtype) in ['int32', 'int64']: x = cast(x, dtype="float32") return _C_ops.scale(x, 'scale', rad2deg_scale) @@ -3531,7 +3533,7 @@ def deg2rad(x, name=None): # [3.14159274]) """ deg2rad_scale = np.pi / 180.0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if convert_dtype(x.dtype) in ['int32', 'int64']: x = cast(x, dtype="float32") return _C_ops.scale(x, 'scale', deg2rad_scale) @@ -3615,7 +3617,7 @@ def gcd(x, y, name=None): paddle.where(y_not_equal_0, paddle.mod(x, y_safe),paddle.zeros(y.shape, y.dtype))) return (paddle.where(x < y, y, x), paddle.where(x < y, x, y)) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): while _gcd_cond_fn(x, y): x, y = _gcd_body_fn(x, y) @@ -3749,7 +3751,7 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None): dtype = x.dtype axes = [axis] infer_flags = list(1 for i in range(len(axes))) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): has_pend = False input_list = [] if prepend is not None and append is not None: @@ -3788,7 +3790,7 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None): op = getattr(_C_ops, "logical_xor") out = op(input_back, input_front) else: - out = layers.elementwise_sub(input_back, input_front, axis=axis) + out = elementwise_sub(input_back, input_front, axis=axis) return out else: check_variable_and_dtype(x, 'x', ['float32', 'float64', 'bool', 'int32', 'int64'], 'diff') @@ -3840,7 +3842,7 @@ def diff(x, n=1, axis=-1, prepend=None, append=None, name=None): type='logical_xor', inputs={"X": input_back, "Y": input_front}, outputs={"Out": out} ) else: - out = layers.elementwise_sub(input_back, input_front, axis=axis) + out = elementwise_sub(input_back, input_front, axis=axis) return out @@ -3883,7 +3885,7 @@ def angle(x, name=None): # [-1.1071488 -0.7853982 0. 0.7853982]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.angle(x) check_variable_and_dtype(x, 'x', diff --git a/python/paddle/tensor/random.py b/python/paddle/tensor/random.py index 5adb9371183..c4e7e96191a 100644 --- a/python/paddle/tensor/random.py +++ b/python/paddle/tensor/random.py @@ -14,13 +14,14 @@ # TODO: define random functions -from ..fluid import core -from ..fluid.framework import in_dygraph_mode, Variable, convert_np_dtype_to_dtype_, dygraph_only +from ..framework import core +from ..framework import convert_np_dtype_to_dtype_, dygraph_only from ..fluid.layer_helper import LayerHelper from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, check_shape from ..fluid.layers import utils import paddle from paddle import _C_ops +from paddle.static import Variable __all__ = [] @@ -65,7 +66,7 @@ def bernoulli(x, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.bernoulli(x) check_variable_and_dtype(x, "x", ["float32", "float64"], "bernoulli") @@ -110,7 +111,7 @@ def poisson(x, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.poisson(x) check_variable_and_dtype(x, "x", ["float32", "float64"], "poisson") @@ -173,7 +174,7 @@ def multinomial(x, num_samples=1, replacement=False, name=None): assert core.is_compiled_with_rocm() == False, ( "multinomial op is not supported on ROCM yet.") - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.multinomial(x, 'num_samples', num_samples, 'replacement', replacement) @@ -231,7 +232,7 @@ def gaussian(shape, mean=0.0, std=1.0, dtype=None, name=None): if not isinstance(dtype, core.VarDesc.VarType): dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): shape = utils.convert_shape_to_list(shape) return _C_ops.gaussian_random('shape', shape, 'mean', float(mean), 'std', @@ -422,7 +423,7 @@ def normal(mean=0.0, std=1.0, shape=None, name=None): # [1.00780561 3.78457445 5.81058198] # random """ - if not in_dygraph_mode(): + if not paddle.in_dynamic_mode(): check_type(mean, 'mean', (int, float, Variable), 'normal') check_type(std, 'std', (int, float, Variable), 'normal') if isinstance(mean, Variable): @@ -454,7 +455,7 @@ def normal(mean=0.0, std=1.0, shape=None, name=None): return gaussian(shape=shape, mean=mean, std=std, name=name) out = out * std + mean - if not in_dygraph_mode(): + if not paddle.in_dynamic_mode(): out.stop_grediant = True return out @@ -540,7 +541,7 @@ def uniform(shape, dtype=None, min=-1.0, max=1.0, seed=0, name=None): if not isinstance(dtype, core.VarDesc.VarType): dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): shape = utils.convert_shape_to_list(shape) return _C_ops.uniform_random('shape', shape, 'min', float(min), 'max', @@ -679,7 +680,7 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None): if not isinstance(dtype, core.VarDesc.VarType): dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): shape = utils.convert_shape_to_list(shape) return _C_ops.randint('shape', shape, 'low', low, 'high', high, 'seed', 0, 'dtype', dtype) @@ -846,7 +847,7 @@ def randint_like(x, low=0, high=None, dtype=None, name=None): "randint_like's low must less then high, but received low = {0}, " "high = {1}".format(low, high)) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): shape = utils.convert_shape_to_list(shape) out = _C_ops.randint('shape', shape, 'low', low, 'high', high, 'seed', 0, 'dtype', core.VarDesc.VarType.INT64) @@ -911,7 +912,7 @@ def randperm(n, dtype="int64", name=None): if not isinstance(dtype, core.VarDesc.VarType): dtype = convert_np_dtype_to_dtype_(dtype) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.randperm('n', n, 'seed', 0, 'dtype', dtype) if n < 1: @@ -1014,7 +1015,7 @@ def exponential_(x, lam=1.0, name=None): # [0.72520673, 0.45208144, 0.30234432]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.exponential_(x, "lambda", lam) check_variable_and_dtype(x, "x", ["float32", "float64"], "exponential") diff --git a/python/paddle/tensor/search.py b/python/paddle/tensor/search.py index 2a2e7d000a1..5c5517e54f7 100644 --- a/python/paddle/tensor/search.py +++ b/python/paddle/tensor/search.py @@ -13,14 +13,16 @@ # limitations under the License. from __future__ import print_function import numpy as np +import paddle from ..fluid.layer_helper import LayerHelper from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype -from ..fluid import core, layers -from paddle.common_ops_import import in_dygraph_mode +from ..fluid import layers +from ..framework import core from paddle.common_ops_import import convert_np_dtype_to_dtype_ from paddle.common_ops_import import Variable from paddle.common_ops_import import VarDesc from paddle import _C_ops +from .logic import logical_not # TODO: define searching & indexing functions of a tensor # from ..fluid.layers import has_inf #DEFINE_ALIAS @@ -88,7 +90,7 @@ def argsort(x, axis=-1, descending=False, name=None): # [1 1 0 2] # [0 2 1 1]]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): _, ids = _C_ops.argsort(x, 'axis', axis, 'descending', descending) return ids check_variable_and_dtype( @@ -165,7 +167,7 @@ def argmax(x, axis=None, keepdim=False, dtype="int64", name=None): flatten = True axis = 0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out = _C_ops.arg_max(x, 'axis', axis, 'dtype', var_dtype, 'keepdims', keepdim, 'flatten', flatten) return out @@ -242,7 +244,7 @@ def argmin(x, axis=None, keepdim=False, dtype="int64", name=None): flatten = True axis = 0 - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out = _C_ops.arg_min(x, 'axis', axis, 'dtype', var_dtype, 'keepdims', keepdim, 'flatten', flatten) return out @@ -302,7 +304,7 @@ def index_select(x, index, axis=0, name=None): # [ 9. 10. 10.]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.index_select(x, index, 'dim', axis) helper = LayerHelper("index_select", **locals()) @@ -378,7 +380,7 @@ def nonzero(x, as_tuple=False): shape = x.shape rank = len(shape) - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): outs = _C_ops.where_index(x) else: outs = layers.where(x) @@ -390,7 +392,7 @@ def nonzero(x, as_tuple=False): else: for i in range(rank): list_out.append( - layers.slice( + paddle.slice( outs, axes=[1], starts=[i], ends=[i + 1])) return tuple(list_out) @@ -452,7 +454,7 @@ def sort(x, axis=-1, descending=False, name=None): # [4. 7. 4. 6.] # [5. 7. 7. 9.]]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): out, _ = _C_ops.argsort(x, 'axis', axis, 'descending', descending) return out helper = LayerHelper("sort", **locals()) @@ -501,7 +503,7 @@ def mode(x, axis=-1, keepdim=False, name=None): # [1, 0]])) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.mode(x, "axis", axis, "keepdim", keepdim) helper = LayerHelper("mode", **locals()) @@ -575,7 +577,7 @@ def where(condition, x=None, y=None, name=None): if x is None or y is None: raise ValueError("either both or neither of x and y should be given") - if not in_dygraph_mode(): + if not paddle.in_dynamic_mode(): check_variable_and_dtype(condition, 'condition', ['bool'], 'where') check_variable_and_dtype( x, 'x', ['float32', 'float64', 'int32', 'int64'], 'where') @@ -592,28 +594,27 @@ def where(condition, x=None, y=None, name=None): broadcast_y = y else: if core.is_compiled_with_xpu(): - cond_int = layers.cast(condition, x.dtype) - cond_not_int = layers.cast(layers.logical_not(condition), x.dtype) - out1 = layers.elementwise_mul(x, cond_int) - out2 = layers.elementwise_mul(y, cond_not_int) - out = layers.elementwise_add(out1, out2) + cond_int = paddle.cast(condition, x.dtype) + cond_not_int = paddle.cast(logical_not(condition), x.dtype) + out1 = paddle.multiply(x, cond_int) + out2 = paddle.multiply(y, cond_not_int) + out = paddle.add(out1, out2) return out - zeros_like_x = layers.zeros_like(x) - zeros_like_y = layers.zeros_like(y) - zeros_like_condition = layers.zeros_like(condition) - zeros_like_condition = layers.cast(zeros_like_condition, x.dtype) - cast_cond = layers.cast(condition, x.dtype) - - broadcast_zeros = layers.elementwise_add(zeros_like_x, zeros_like_y) - broadcast_zeros = layers.elementwise_add(broadcast_zeros, - zeros_like_condition) - broadcast_x = layers.elementwise_add(x, broadcast_zeros) - broadcast_y = layers.elementwise_add(y, broadcast_zeros) - broadcast_condition = layers.elementwise_add(cast_cond, broadcast_zeros) - broadcast_condition = layers.cast(broadcast_condition, 'bool') - - if in_dygraph_mode(): + zeros_like_x = paddle.zeros_like(x) + zeros_like_y = paddle.zeros_like(y) + zeros_like_condition = paddle.zeros_like(condition) + zeros_like_condition = paddle.cast(zeros_like_condition, x.dtype) + cast_cond = paddle.cast(condition, x.dtype) + + broadcast_zeros = paddle.add(zeros_like_x, zeros_like_y) + broadcast_zeros = paddle.add(broadcast_zeros, zeros_like_condition) + broadcast_x = paddle.add(x, broadcast_zeros) + broadcast_y = paddle.add(y, broadcast_zeros) + broadcast_condition = paddle.add(cast_cond, broadcast_zeros) + broadcast_condition = paddle.cast(broadcast_condition, 'bool') + + if paddle.in_dynamic_mode(): return _C_ops.where(broadcast_condition, broadcast_x, broadcast_y) else: helper = LayerHelper("where", **locals()) @@ -704,7 +705,7 @@ def index_sample(x, index): # [1200 1100]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.index_sample(x, index) helper = LayerHelper("index_sample", **locals()) @@ -752,7 +753,7 @@ def masked_select(x, mask, name=None): #[1.0 5.0 6.0 9.0] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.masked_select(x, mask) helper = LayerHelper("masked_select", **locals()) @@ -822,7 +823,7 @@ def topk(x, k, axis=None, largest=True, sorted=True, name=None): # [[1 1 0 0]] """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): k = k.numpy().item(0) if isinstance(k, Variable) else k if axis is None: out, indices = _C_ops.top_k_v2(x, 'k', @@ -906,7 +907,7 @@ def searchsorted(sorted_sequence, """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.searchsorted(sorted_sequence, values, "out_int32", out_int32, "right", right) @@ -969,7 +970,7 @@ def kthvalue(x, k, axis=None, keepdim=False, name=None): # [[0, 2], # [1, 2]])) """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): if axis is not None: return _C_ops.kthvalue(x, 'k', k, "axis", axis, "keepdim", keepdim) else: diff --git a/python/paddle/tensor/stat.py b/python/paddle/tensor/stat.py index d54c7fe74da..468aa460486 100644 --- a/python/paddle/tensor/stat.py +++ b/python/paddle/tensor/stat.py @@ -15,10 +15,9 @@ # TODO: define statistical functions of a tensor import numpy as np -from ..fluid.framework import Variable +from ..static import Variable from ..fluid.layer_helper import LayerHelper -from ..fluid.framework import core, in_dygraph_mode -from ..fluid import layers +from ..framework import core from .search import where from ..fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype import paddle @@ -88,7 +87,7 @@ def mean(x, axis=None, keepdim=False, name=None): if axis is None or len(axis) == 0: axis = [0] - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.reduce_mean(x, 'dim', axis, 'keep_dim', keepdim, 'reduce_all', reduce_all) @@ -150,7 +149,7 @@ def var(x, axis=None, unbiased=True, keepdim=False, name=None): out2 = paddle.var(x, axis=1) # [1. 4.33333333] """ - if not in_dygraph_mode(): + if not paddle.in_dynamic_mode(): check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'var') u = mean(x, axis, True, name) @@ -209,7 +208,7 @@ def std(x, axis=None, unbiased=True, keepdim=False, name=None): out2 = paddle.std(x, axis=1) # [1. 2.081666] """ - if not in_dygraph_mode(): + if not paddle.in_dynamic_mode(): check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'std') out = var(**locals()) @@ -237,7 +236,7 @@ def numel(x, name=None): """ - if in_dygraph_mode(): + if paddle.in_dynamic_mode(): return _C_ops.size(x) if not isinstance(x, Variable): diff --git a/python/paddle/tensor/to_string.py b/python/paddle/tensor/to_string.py index 0e76d92ca73..85672ec7a36 100644 --- a/python/paddle/tensor/to_string.py +++ b/python/paddle/tensor/to_string.py @@ -14,7 +14,7 @@ import paddle import numpy as np -from paddle.fluid.layers import core +from ..framework import core from paddle.fluid.data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype __all__ = [] -- GitLab