# Copyright (c) 2018 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. from ..wrapped_decorator import contextmanager import numpy as np from paddle.fluid import core from paddle.fluid import framework __all__ = ['enabled', 'guard', 'to_variable'] def enabled(): return framework._in_imperative_mode() @contextmanager def guard(place=None): train = framework.Program() startup = framework.Program() tracer = core.Tracer(train.current_block().desc) if place is None: if core.is_compiled_with_cuda(): place = core.CUDAPlace(0) else: place = core.CPUPlace() with framework.program_guard(train, startup): with framework.unique_name.guard(): with framework._imperative_guard(tracer): with framework._imperative_place_guard(place): yield def to_variable(value, block=None): if isinstance(value, np.ndarray): assert enabled(), "to_variable could only be called in imperative mode" if not block: block = framework.default_main_program().current_block() py_var = framework.Variable( block, type=core.VarDesc.VarType.LOD_TENSOR, name=None, shape=value.shape, dtype=value.dtype) var = py_var._ivar.value() tensor = var.get_tensor() tensor.set(value, framework._current_expected_place()) return py_var elif isinstance(value, framework.Variable): return value