diff --git a/python/paddle/fluid/dygraph/varbase_patch_methods.py b/python/paddle/fluid/dygraph/varbase_patch_methods.py index a62a260969c685a5a99f8848b3b4ffacab7cb90d..83738c1f131943017decea2f67953578ef7154ca 100644 --- a/python/paddle/fluid/dygraph/varbase_patch_methods.py +++ b/python/paddle/fluid/dygraph/varbase_patch_methods.py @@ -99,7 +99,7 @@ def monkey_patch_varbase(): # Note: getattr(self, attr, None) will call x.grad=x.gradient(), but gradient() only available in dygraph. # It will fail. So, for propery that different between dynamic and static graph, should not getattr(self, attr, None). - attr_not_need_keys = ['grad', 'T'] + attr_not_need_keys = ['grad', 'T', 'place', '_place_str'] if isinstance(self, (ParamBase, EagerParamBase)): attr_kwargs = self.__dict__.copy() else: diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py index 1cac55170476fd85e45932788ff9db288faf4b84..26913db87c393a301ba453dad78f5907cbf07297 100644 --- a/python/paddle/fluid/layers/tensor.py +++ b/python/paddle/fluid/layers/tensor.py @@ -846,6 +846,18 @@ def fill_constant_batch_size_like(input, input=like, shape=[1], value=0, dtype='int64') #like=[[10, 10]] data=[0] """ + if in_dygraph_mode(): + if not isinstance(dtype, core.VarDesc.VarType): + dtype = convert_np_dtype_to_dtype_(dtype) + + place = _current_expected_place() + if force_cpu: + place = core.CPUPlace() + out = _C_ops.final_state_full_batch_size_like( + input, shape, dtype, value, input_dim_idx, output_dim_idx, place) + out.stop_gradient = True + return out + helper = LayerHelper("fill_constant_batch_size_like", **locals()) out = helper.create_variable_for_type_inference(dtype=dtype) attrs = { diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index b02494d52451766a428abfec612312fa74d0539b..9c3ca133270226e0010283bd430fdeb3c33021db 100755 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -596,6 +596,13 @@ foreach(TEST_OP ${TEST_OPS_WITH_GC}) py_test_modules(${TEST_OP} MODULES ${TEST_OP} ENVS ${GC_ENVS}) endforeach() +# Switch some dy2st UT to eager mode +set(TEST_EAGER_OPS test_jit_save_load test_translated_layer) +foreach(TEST_OP ${TEST_EAGER_OPS}) + list(REMOVE_ITEM TEST_OPS ${TEST_OP}) + py_test_modules(${TEST_OP} MODULES ${TEST_OP} ENVS FLAGS_enable_eager_mode=1) +endforeach() + if ((NOT WITH_GPU) AND (NOT WITH_XPU) AND NOT (WITH_ASCEND OR WITH_ASCEND_CL)) list(REMOVE_ITEM TEST_OPS "test_fleet_graph_execution_meta_optimizer") list(REMOVE_ITEM TEST_OPS "test_gen_nccl_id_op") diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/CMakeLists.txt b/python/paddle/fluid/tests/unittests/dygraph_to_static/CMakeLists.txt index eeb377ff3b4a2b75499bafb20a2d04582b69cdfb..f046c7b73927e8ea8a1b309951edec4a6189473c 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/CMakeLists.txt @@ -6,7 +6,7 @@ set(DY2ST_EAGER_TEST_ENVS ${GC_ENVS} FLAGS_enable_eager_mode=1) set(TEST_EAGER_OPS test_bmn test_break_continue test_ifelse test_loop test_mnist_amp test_mnist_pure_fp16 test_mobile_net test_program_translator test_ptb_lm test_reinforcement_learning test_resnet test_resnet_amp test_resnet_pure_fp16 test_se_resnet test_sentiment test_seq2seq - test_tsm test_word2vec test_yolov3) + test_tsm test_word2vec test_yolov3 test_bert test_cycle_gan test_lstm test_simnet) list(REMOVE_ITEM TEST_OPS test_lac) # NOTE(Aurelius84): In case of Windows CI, if open ON_INFER, RWLOCK of Scope will # be removed and will cause some random failed in multi-thread. diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_resnet_v2.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_resnet_v2.py index ae7a58857905916d07750a10e0012a3870283ba4..0cf96b7159579fd1323f883a850ec08131338ce8 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_resnet_v2.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_resnet_v2.py @@ -14,6 +14,8 @@ from __future__ import print_function +import os +os.environ["FLAGS_enable_eager_mode"] = "0" import math import time import unittest diff --git a/python/paddle/fluid/tests/unittests/test_fill_constant_batch_size_like.py b/python/paddle/fluid/tests/unittests/test_fill_constant_batch_size_like.py new file mode 100644 index 0000000000000000000000000000000000000000..774134f7a9960f37d3281a1840d125e0f0f518f6 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_fill_constant_batch_size_like.py @@ -0,0 +1,75 @@ +# Copyright (c) 2019 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 __future__ import print_function + +import paddle +import paddle.fluid.core as core +from paddle.static import program_guard, Program +import paddle.compat as cpt +import unittest +import numpy as np +from op_test import OpTest +from paddle.fluid.framework import convert_np_dtype_to_dtype_ + +paddle.enable_static() + + +def fill_constant_batch_size_like(input, + shape, + value, + data_type, + input_dim_idx=0, + output_dim_idx=0, + force_cpu=False): + return paddle.fluid.layers.fill_constant_batch_size_like( + input, shape, data_type, value, input_dim_idx, output_dim_idx, + force_cpu) + + +class TestFillConstatnBatchSizeLike1(OpTest): + # test basic + def setUp(self): + self.op_type = "fill_constant_batch_size_like" + self.python_api = fill_constant_batch_size_like + self.init_data() + + input = np.zeros(self.shape) + out = np.full_like(input, self.value, self.dtype) + + self.inputs = {'Input': input} + self.outputs = {'Out': out} + self.attrs = { + 'shape': self.shape, + 'dtype': convert_np_dtype_to_dtype_(self.dtype), + 'value': self.value, + 'input_dim_idx': self.input_dim_idx, + 'output_dim_idx': self.output_dim_idx, + 'force_cpu': self.force_cpu + } + + def init_data(self): + self.shape = [10, 10] + self.dtype = np.float32 + self.value = 100 + self.input_dim_idx = 0 + self.output_dim_idx = 0 + self.force_cpu = False + + def test_check_output(self): + self.check_output(check_eager=True) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_run_program_op.py b/python/paddle/fluid/tests/unittests/test_run_program_op.py index 57281eafff7ee1de6d4685ba7cff54cbf4e056ac..68f24bf25700848222843cb06852583d0f4db377 100644 --- a/python/paddle/fluid/tests/unittests/test_run_program_op.py +++ b/python/paddle/fluid/tests/unittests/test_run_program_op.py @@ -99,7 +99,7 @@ class RunProgramOpTest(unittest.TestCase): def prepare_attrs(self): return ('global_block', self.program_desc.block(0), 'start_op_index', 0, 'end_op_index', self.fwd_op_num, 'program_id', - _hash_with_id(self.program_desc)) + _hash_with_id(self.program_desc, self)) def get_param_grad_names(self): grad_names = [] diff --git a/python/paddle/utils/code_gen/api.yaml b/python/paddle/utils/code_gen/api.yaml index 93d14b1744e93674f775e146b0aa1960fdc295bd..acaab007e03fb6a74857bb3305f091dd1146a66a 100644 --- a/python/paddle/utils/code_gen/api.yaml +++ b/python/paddle/utils/code_gen/api.yaml @@ -687,6 +687,18 @@ data_type : dtype backend : place +- api : full_batch_size_like + args : (Tensor input, int[] shape, DataType dtype, Scalar value, int input_dim_idx, int output_dim_idx, Place place=CPUPlace()) + output: Tensor + infer_meta : + func : FullBatchSizeLikeInferMeta + param : [input, shape, value, dtype, input_dim_idx, output_dim_idx] + kernel : + func : full_batch_size_like + param : [input, shape, value, dtype, input_dim_idx, output_dim_idx] + data_type : dtype + backend : place + - api : full_like args : (Tensor x, Scalar value, DataType dtype = DataType::UNDEFINED, Place place = {}) output: Tensor