From b9397b26680710c924f6e59bd7988eeb4e161fc1 Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Tue, 13 Mar 2018 11:30:17 +0800 Subject: [PATCH] remove concat_rows --- paddle/fluid/operators/lookup_table_op.cc | 83 ++++++------------- paddle/fluid/operators/lookup_table_op.cu | 12 +-- paddle/fluid/operators/lookup_table_op.h | 13 +-- .../tests/unittests/test_concat_rows_op.py | 76 ----------------- .../tests/unittests/test_lookup_table_op.py | 49 +++++++++++ 5 files changed, 88 insertions(+), 145 deletions(-) delete mode 100644 python/paddle/fluid/tests/unittests/test_concat_rows_op.py diff --git a/paddle/fluid/operators/lookup_table_op.cc b/paddle/fluid/operators/lookup_table_op.cc index f32b8896d..753553a68 100644 --- a/paddle/fluid/operators/lookup_table_op.cc +++ b/paddle/fluid/operators/lookup_table_op.cc @@ -34,9 +34,12 @@ class LookupTableOp : public framework::OperatorWithKernel { auto ids_dims = ctx->GetInputDim("Ids"); auto ids_var_type = ctx->GetInputsVarType("Ids").front(); - // lookup_table and concat_rows use the same InferShape, for lookup_table, - // ids_var_type should be LoDTensor, for concat_rows, it should be - // SelectedRows. + + // The type of Ids(Input) is SelectedRows or LoDTensor, when Ids's type + // is LoDTensor, this tensor contains the ids to be looked up in W + // and it must be a column vector with rank = 2 while the 2nd dimension + // size must be 1, when Ids's type is SelectedRows, the rows of Ids + // contains the ids to be looked up in W; if (ids_var_type == framework::proto::VarType::LOD_TENSOR) { PADDLE_ENFORCE_EQ(ids_dims.size(), 2); PADDLE_ENFORCE_EQ(ids_dims[1], 1); @@ -60,70 +63,41 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker { LookupTableOpMaker(OpProto* proto, OpAttrChecker* op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("W", - "An input represents embedding tensors, " + "(Tensor) The input represents embedding tensors, " "which is a learnable parameter."); - AddInput("Ids", - "An input with type int32 or int64 " - "contains the ids to be looked up in W. " - "Ids must be a column vector with rank = 2. " - "The 2nd dimension size must be 1."); - AddOutput("Out", "The lookup results, which have the same type as W."); - AddAttr("is_sparse", - "(boolean, default false) " - "Sparse update") - .SetDefault(false); - AddAttr("padding_idx", - "(int64, default -1) " - "If the value is -1, it makes no effect to lookup. " - "Otherwise the given value indicates padding the output " - "with zeros whenever lookup encounters it in Ids.") - .SetDefault(-1); - AddComment(R"DOC( -Lookup Table Operator. - -This operator is used to perform lookups on the parameter W, -then concatenated into a dense tensor. - -The input Ids can carry the LoD (Level of Details) information, -or not. And the output only shares the LoD information with input Ids. - -)DOC"); - } -}; - -class ConcatRowsOpMaker : public framework::OpProtoAndCheckerMaker { - public: - ConcatRowsOpMaker(OpProto* proto, OpAttrChecker* op_checker) - : OpProtoAndCheckerMaker(proto, op_checker) { - AddInput("W", - "(Tensor) The input tensor of concat_rows operator. " - "The rank of this tensor is 2."); AddInput( "Ids", - "(SelectedRows) The rows of Ids contains the index to be looked up " + "(Tensor or SelectedRows) Ids's type can be Tensor or " + "SelectedRows, when Ids's type is Tensor, this tensor contains " + "the ids to be looked up in W and it must be a column vector with " + "rank = 2 while the 2nd dimension size must be 1; when Ids's type is " + "SelectedRows, the rows of Ids contains the ids to be looked up " "in W."); AddOutput("Out", - "(SelectedRows or Tensor) The result of concatenating, which " - "have the same type as W."); + "(Tensor or SelectedRows) The lookup results, which have the " + "same type as W."); AddAttr("is_sparse", - "(boolean, default true) This attribution is invalid, it's " - "only used by `Lookup Table Operator`.") - .SetDefault(true); + "(boolean, default false) " + "Sparse update.") + .SetDefault(false); AddAttr("padding_idx", "(int64, default -1) " "If the value is -1, it makes no effect to lookup. " "Otherwise the given value indicates padding the output " "with zeros whenever lookup encounters it in Ids.") .SetDefault(-1); - AddComment(R"DOC( -ConcatRows Operator. +Lookup Table Operator. -This operator is used to perform lookups on the W(dense tensor) according to -rows contained by Idx(sparse tensor), then concatenates them into a sparse -tensor or dense tensor. +This operator is used to perform lookups on the parameter W, +then concatenated into a dense or sparse tensor. -The type of Ids(Input) is SelectedRows. +The type of Ids(Input) is SelectedRows, Tensor or LoDTensor, when Ids's +type is SelectedRows, the rows of Ids contains the ids to be looked up in W; +when Ids's type is Tensor, this tensor contains the ids to be looked up in W +and it must be a column vector with rank = 2 while the 2nd dimension size must be 1, +at this time, Ids can carry the LoD (Level of Details) information, or not, and +the output only shares the LoD information with input Ids. )DOC"); } @@ -189,8 +163,3 @@ REGISTER_OP_CPU_KERNEL(lookup_table, ops::LookupTableKernel, ops::LookupTableKernel); REGISTER_OP_CPU_KERNEL(lookup_table_grad, ops::LookupTableGradKernel, ops::LookupTableGradKernel); - -// concat_rows is used by regularization and it doesn't have gradient operation. -REGISTER_OPERATOR(concat_rows, ops::LookupTableOp, ops::ConcatRowsOpMaker); -REGISTER_OP_CPU_KERNEL(concat_rows, ops::LookupTableKernel, - ops::LookupTableKernel); diff --git a/paddle/fluid/operators/lookup_table_op.cu b/paddle/fluid/operators/lookup_table_op.cu index b880d86cf..7dce6ae55 100644 --- a/paddle/fluid/operators/lookup_table_op.cu +++ b/paddle/fluid/operators/lookup_table_op.cu @@ -74,16 +74,16 @@ class LookupTableCUDAKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* table_t = context.Input("W"); + auto* output_t = context.Output("Out"); int64_t padding_idx = context.Attr("padding_idx"); - auto* ids_var = context.InputVar("Ids"); // int tensor + auto* ids_var = context.InputVar("Ids"); int64_t* ids; int64_t K; - auto* output_t = context.Output("Out"); // float tensor; - - // lookup_table and concat_rows use the same kernel, for lookup_table, - // ids_var_type should be LoDTensor, for concat_rows, ids_var_type and - // out_var_type should be SelectedRows. + // The type of Ids(Input) is SelectedRows or LoDTensor, when Ids's type + // is LoDTensor, this tensor contains the ids to be looked up in W; + // when Ids's type is SelectedRows, the rows of Ids contains the + // ids to be looked up in W. if (ids_var->IsType()) { auto* ids_t = context.Input("Ids"); ids = const_cast(ids_t->data()); diff --git a/paddle/fluid/operators/lookup_table_op.h b/paddle/fluid/operators/lookup_table_op.h index 32a0085e0..8d2839d1b 100644 --- a/paddle/fluid/operators/lookup_table_op.h +++ b/paddle/fluid/operators/lookup_table_op.h @@ -30,15 +30,16 @@ template class LookupTableKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { - auto* table_t = context.Input("W"); // float tensor - auto* ids_var = context.InputVar("Ids"); // int tensor + auto* table_t = context.Input("W"); + auto* output_t = context.Output("Out"); + auto* ids_var = context.InputVar("Ids"); int64_t* ids; int64_t ids_numel; - auto* output_t = context.Output("Out"); - // lookup_table and concat_rows use the same kernel, for lookup_table, - // ids_var_type should be LoDTensor, for concat_rows, ids_var_type and - // out_var_type should be SelectedRows. + // The type of Ids(Input) is SelectedRows or LoDTensor, when Ids's type + // is LoDTensor, this tensor contains the ids to be looked up in W; + // when Ids's type is SelectedRows, the rows of Ids contains the + // ids to be looked up in W. if (ids_var->IsType()) { auto* ids_t = context.Input("Ids"); ids = const_cast(ids_t->data()); diff --git a/python/paddle/fluid/tests/unittests/test_concat_rows_op.py b/python/paddle/fluid/tests/unittests/test_concat_rows_op.py deleted file mode 100644 index 6dd25c2e0..000000000 --- a/python/paddle/fluid/tests/unittests/test_concat_rows_op.py +++ /dev/null @@ -1,76 +0,0 @@ -# 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 numpy as np -import paddle.fluid.core as core -from paddle.fluid.op import Operator -from op_test import OpTest - - -class TestConcatRowsOp(OpTest): - def check_with_place(self, place): - scope = core.Scope() - - # create and initialize Grad Variable - height = 10 - rows = [0, 4, 4, 7] - row_numel = 12 - - ids_selected_rows = scope.var('Ids').get_selected_rows() - ids_selected_rows.set_height(height) - ids_selected_rows.set_rows(rows) - np_array = np.ones((len(rows), row_numel)).astype("float32") - ids_tensor = ids_selected_rows.get_tensor() - ids_tensor.set(np_array, place) - - # create and initialize W Variable - W = scope.var('W').get_tensor() - W_array = np.full((height, row_numel), 1.0).astype("float32") - for i in range(height): - W_array[i] *= i - W.set(W_array, place) - - Out = scope.var('Out').get_selected_rows() - Out_array = np.full((len(rows), row_numel), -1.0).astype("float32") - Out.set_height(height) - Out.set_rows(rows) - Out_tensor = Out.get_tensor() - Out_tensor.set(Out_array, place) - - # create and run concat_rows_op operator - concat_rows_op = Operator( - "concat_rows", - W='W', - Ids='Ids', - Out='Out', - attrs={'is_sparse': True}) - concat_rows_op.run(scope, place) - - # get and compare result - result_array = np.array(Out_tensor) - - for idx, row in enumerate(rows): - assert (row == result_array[idx]).all() - - def test_concat_rows(self): - places = [core.CPUPlace()] - if core.is_compiled_with_cuda(): - places.append(core.CUDAPlace(0)) - for place in places: - self.check_with_place(place) - - -if __name__ == "__main__": - unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_lookup_table_op.py b/python/paddle/fluid/tests/unittests/test_lookup_table_op.py index 03a5bd24a..8bd8913fa 100644 --- a/python/paddle/fluid/tests/unittests/test_lookup_table_op.py +++ b/python/paddle/fluid/tests/unittests/test_lookup_table_op.py @@ -14,6 +14,8 @@ import unittest import numpy as np +import paddle.fluid.core as core +from paddle.fluid.op import Operator from op_test import OpTest @@ -47,5 +49,52 @@ class TestLookupTableOpWithPadding(TestLookupTableOp): pass +# Testing look_up_table when Ids's type is SelectedRows. +class TestLookupTableIdsIsSelectedRows(OpTest): + def check_with_place(self, place): + scope = core.Scope() + + height = 10 + rows = [0, 4, 4, 7] + row_numel = 12 + + ids_selected_rows = scope.var('Ids').get_selected_rows() + ids_selected_rows.set_height(height) + ids_selected_rows.set_rows(rows) + np_array = np.ones((len(rows), row_numel)).astype("float32") + ids_tensor = ids_selected_rows.get_tensor() + ids_tensor.set(np_array, place) + + W = scope.var('W').get_tensor() + W_array = np.full((height, row_numel), 1.0).astype("float32") + for i in range(height): + W_array[i] *= i + W.set(W_array, place) + + Out = scope.var('Out').get_selected_rows() + Out_array = np.full((len(rows), row_numel), -1.0).astype("float32") + Out.set_height(height) + Out.set_rows(rows) + Out_tensor = Out.get_tensor() + Out_tensor.set(Out_array, place) + + # create and run concat_rows_op operator + concat_rows_op = Operator("lookup_table", W='W', Ids='Ids', Out='Out') + concat_rows_op.run(scope, place) + + # get and compare result + result_array = np.array(Out_tensor) + + for idx, row in enumerate(rows): + assert (row == result_array[idx]).all() + + def test_concat_rows(self): + places = [core.CPUPlace()] + if core.is_compiled_with_cuda(): + places.append(core.CUDAPlace(0)) + for place in places: + self.check_with_place(place) + + if __name__ == "__main__": unittest.main() -- GitLab