From bc28cf613f9e41908d6da9a889cbb3242e0589d2 Mon Sep 17 00:00:00 2001 From: Haichao Zhang Date: Wed, 27 Jun 2018 16:56:41 -0700 Subject: [PATCH] Extend fill_zeros_like_op for zero-filling an LoDTensorArray (#11496) * Add fill_zeros_array op. This op is used for zero-filling an LoDTensorArray. * merge fill_zeros_array_op with fill_zeros_like_op * add unit_test for fill_zeros_like for array --- paddle/fluid/framework/operator.cc | 4 + paddle/fluid/operators/fill_zeros_like_op.cc | 10 ++- paddle/fluid/operators/fill_zeros_like_op.h | 30 +++++-- python/paddle/fluid/layers/nn.py | 38 ++++++++ .../test_fill_zeros_like_op_for_array.py | 88 +++++++++++++++++++ 5 files changed, 161 insertions(+), 9 deletions(-) create mode 100644 python/paddle/fluid/tests/unittests/test_fill_zeros_like_op_for_array.py diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc index 122ee1dab35..c1329b06d7e 100644 --- a/paddle/fluid/framework/operator.cc +++ b/paddle/fluid/framework/operator.cc @@ -713,6 +713,10 @@ proto::VarType::Type OperatorWithKernel::IndicateDataType( t = &var->Get(); } else if (var->IsType()) { t = &(var->Get().value()); + } else if (var->IsType()) { + const LoDTensorArray& arr = var->Get(); + PADDLE_ENFORCE(arr.size() > 0); + t = &(arr[0]); } if (t != nullptr) { int tmp = static_cast(ToDataType(t->type())); diff --git a/paddle/fluid/operators/fill_zeros_like_op.cc b/paddle/fluid/operators/fill_zeros_like_op.cc index d67bec36b32..a9d47c01727 100644 --- a/paddle/fluid/operators/fill_zeros_like_op.cc +++ b/paddle/fluid/operators/fill_zeros_like_op.cc @@ -26,8 +26,12 @@ class FillZerosLikeOp : public framework::OperatorWithKernel { "Input(X) of FillZerosLikeOp should not be null."); PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) of FillZerosLikeOp should not be null."); - ctx->SetOutputDim("Out", ctx->GetInputDim("X")); - ctx->ShareLoD("X", /*->*/ "Out"); + + if (ctx->IsRuntime() && + ctx->GetOutputsVarType("Out")[0] == + framework::proto::VarType::LOD_TENSOR_ARRAY) { + return; // skip runtime infershape when is tensor array; + } } }; @@ -39,7 +43,7 @@ class FillZerosLikeOpMaker : public framework::OpProtoAndCheckerMaker { AddComment(R"DOC( FillZerosLike Operator. -Fill up a variable with zeros. +Fill up a variable with zeros, supporting both LoDTensor and LoDTensorArray. The output will have the same size as the input. )DOC"); diff --git a/paddle/fluid/operators/fill_zeros_like_op.h b/paddle/fluid/operators/fill_zeros_like_op.h index 4bbe0df6b68..daa6521b32e 100644 --- a/paddle/fluid/operators/fill_zeros_like_op.h +++ b/paddle/fluid/operators/fill_zeros_like_op.h @@ -13,6 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once +#include "paddle/fluid/framework/lod_tensor_array.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/math/math_function.h" @@ -23,12 +24,29 @@ template class FillZerosLikeKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { - auto* out = context.Output("Out"); - out->mutable_data(context.GetPlace()); - - math::SetConstant setter; - setter(context.template device_context(), out, - static_cast(0)); + auto var = context.InputVar("X"); + if (var->IsType()) { + auto& input = *context.Input("X"); + auto& output = *context.Output("Out"); + output.Resize(input.dims()); + output.set_lod(input.lod()); + output.mutable_data(context.GetPlace()); + math::SetConstant setter; + setter(context.template device_context(), &(output), + static_cast(0)); + } else if (var->IsType()) { + auto& input = *context.Input("X"); + auto& output = *context.Output("Out"); + output.resize(input.size()); + for (auto i = 0; i < input.size(); i++) { + output[i].Resize(input[i].dims()); + output[i].set_lod(input[i].lod()); + output[i].mutable_data(context.GetPlace()); + math::SetConstant setter; + setter(context.template device_context(), &(output[i]), + static_cast(0)); + } + } } }; diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 64f48e259ad..bc379da4e3b 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -95,6 +95,7 @@ __all__ = [ 'relu', 'log', 'crop', + 'fill_zeros_like', ] @@ -5184,3 +5185,40 @@ def crop(x, shape=None, offsets=None, name=None): outputs={'Out': out}, attrs=None if len(attrs) == 0 else attrs) return out + + +def fill_zeros_like(x): + """ + This layer takes an input and outputs a variable that has the same structure as + the input and with all the element values as zero. The variable can be a Tensor + or TensorArray. + + .. code-block:: text + + + Given + X = [[0, 1, 2, 0], + [0, 3, 4, 0], + [0, 0, 0, 0]], + output is: + Out = [[0, 0, 0, 0], + [0, 0, 0, 0], + [0, 0, 0, 0]]. + + Args: + x (Variable): The input variable, which could be a tensor or tensor array + + Returns: + Variable: The zero-filled variable, which has the same type and shape as + the input variable. + + Examples: + + .. code-block:: python + y = fluid.layers.fill_zeros_like(x) + """ + helper = LayerHelper('fill_zeros_like', **locals()) + out = helper.create_tmp_variable(dtype=x.dtype) + helper.append_op( + type='fill_zeros_like', inputs={'X': [x]}, outputs={'Out': [out]}) + return out diff --git a/python/paddle/fluid/tests/unittests/test_fill_zeros_like_op_for_array.py b/python/paddle/fluid/tests/unittests/test_fill_zeros_like_op_for_array.py new file mode 100644 index 00000000000..23871508d80 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_fill_zeros_like_op_for_array.py @@ -0,0 +1,88 @@ +# 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. + +import unittest +import paddle.fluid.core as core +import numpy +import paddle.fluid.layers as layers +from paddle.fluid.framework import Program, program_guard +from paddle.fluid.executor import Executor + +import paddle.fluid as fluid +import paddle.fluid.core as core + + +class TestFillZerosLikeOpForTensorArray(unittest.TestCase): + def place(self): + return core.CPUPlace() + + def test_zero_filling_lod_tensor_array(self): + tensor = core.LoDTensor() + tensor.set( + numpy.arange(20).reshape(20, 1).astype('int32'), self.place()) + tensor.set_lod([[0, 2, 5], [0, 3, 9, 11, 17, 20]]) + + expect = [ + numpy.array( + [0, 0, 0, 0, 0], dtype='int32'), numpy.array( + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype='int32'), + numpy.array( + [0, 0, 0], dtype='int32') + ] + + lod = [[[0, 2, 5]], [[0, 6, 12]], [[0, 3]]] + self.main( + tensor=tensor, + expect_array=expect, + expect_lod=lod, + expect_max_len=3) + + def main(self, tensor, expect_array, expect_lod, expect_max_len, level=0): + place = self.place() + program = Program() + with program_guard(program): + x = layers.data(name='x', shape=[10]) + x.persistable = True + table = layers.lod_rank_table(x, level=level) + max_len = layers.max_sequence_len(table) + max_len.persistable = True + array = layers.lod_tensor_to_array(x, table) + array = layers.fill_zeros_like(array) + array.persistable = True + + result = layers.array_to_lod_tensor(array, table) + result.persistable = True + exe = Executor(place) + scope = core.Scope() + exe.run(program, feed={'x': tensor}, scope=scope) + var = scope.find_var(array.name) + array = var.get_lod_tensor_array() + if expect_array is not None and expect_lod is not None: + self.check_array_same(array, expect_array, expect_lod) + + self.assertEqual( + numpy.array(scope.find_var(max_len.name).get_tensor())[0], + expect_max_len) + + def check_array_same(self, array, expect_tensor, expect_lod): + self.assertEqual(len(expect_tensor), len(array)) + for i, exp in enumerate(zip(expect_tensor, expect_lod)): + exp_tensor, exp_lod = exp + exp_tensor = numpy.expand_dims(exp_tensor, axis=1) + self.assertTrue(numpy.allclose(exp_tensor, numpy.array(array[i]))) + self.assertEqual(exp_lod, array[i].lod()) + + +if __name__ == '__main__': + unittest.main() -- GitLab