From 58730ba131a468df2c8873d41b189d5690be10be Mon Sep 17 00:00:00 2001 From: yangyaming Date: Fri, 16 Mar 2018 19:51:56 +0800 Subject: [PATCH] Enhance unit test. --- paddle/fluid/operators/sequence_expand_op.cc | 102 +++++++++--------- paddle/fluid/operators/sequence_expand_op.h | 40 ++++--- python/paddle/fluid/layers/nn.py | 49 +++++---- .../fluid/tests/unittests/test_layers.py | 4 +- .../tests/unittests/test_sequence_expand.py | 51 ++++++--- 5 files changed, 145 insertions(+), 101 deletions(-) diff --git a/paddle/fluid/operators/sequence_expand_op.cc b/paddle/fluid/operators/sequence_expand_op.cc index 25a8283858..2c88a53bc7 100644 --- a/paddle/fluid/operators/sequence_expand_op.cc +++ b/paddle/fluid/operators/sequence_expand_op.cc @@ -33,10 +33,11 @@ class SequenceExpandOp : public framework::OperatorWithKernel { "Output(Out) of SequenceExpandOp should not be null."); auto x_dims = ctx->GetInputDim("X"); + auto out_dims = x_dims; int ref_level = ctx->Attrs().Get("ref_level"); - PADDLE_ENFORCE_EQ(x_dims.size(), 2U, - "Dimension number of Input(X) should be 2."); + PADDLE_ENFORCE_GE(x_dims.size(), 2, + "Dimension number of Input(X) should be at least 2."); if (ctx->IsRuntime()) { framework::Variable* x_var = @@ -50,15 +51,9 @@ class SequenceExpandOp : public framework::OperatorWithKernel { PADDLE_ENFORCE_LE(x_lod.size(), 1, "Number of lod level of Input(X) should not be " "greater than 1."); - - PADDLE_ENFORCE(x_lod.size() == y_lod.size() || x_lod.size() == 0, - "Level number of Input(X)'s lod should be either equal " - "to 0 or equal to that of Input(Y)."); - PADDLE_ENFORCE_GT(y_lod.size(), 0, "Level number of Input(Y)'s lod should be " "greater than 0."); - PADDLE_ENFORCE( ref_level == -1 || (ref_level >= 0 && ref_level < static_cast(y_lod.size())), @@ -68,6 +63,14 @@ class SequenceExpandOp : public framework::OperatorWithKernel { if (ref_level == -1) ref_level = y_lod.size() - 1; + if (x_lod.size() > 0) { + PADDLE_ENFORCE( + x_lod.size() == 0 || x_lod[0].size() == y_lod[ref_level].size(), + "Level number of Input(X)'s lod should be 0. Otherwise " + "size of Input(X)'s first level lod should be equal to " + "size of Input(Y)'s lod of referred level."); + } + int64_t out_first_dim = 0; if (y_lod[ref_level].size() <= 1) { out_first_dim = x_dims[0]; @@ -81,9 +84,12 @@ class SequenceExpandOp : public framework::OperatorWithKernel { (y_lod[ref_level][i] - y_lod[ref_level][i - 1]) * x_seq_len; } } - ctx->SetOutputDim("Out", {out_first_dim, x_dims[1]}); + out_dims[0] = out_first_dim; + ctx->SetOutputDim("Out", out_dims); } else { - ctx->SetOutputDim("Out", {-1, x_dims[1]}); + out_dims[0] = -1; + ctx->SetOutputDim("Out", out_dims); + ctx->ShareLoD("X", /*->*/ "Out"); } } }; @@ -105,69 +111,69 @@ class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker { AddComment(R"DOC( Sequence Expand Operator. -This operator expands input(X) according to LOD of input(Y). +This operator expands `X` according to specified level lod of `Y`. Current +implementation constaints that lod level of `X` should be at most 1. Attribute +`ref_level` is used to specify which level lod of `Y` is referred to expand `X`. +If set `ref_level` to -1, then last level lod of `Y` would be referred. +Please note, rank of `X` should be at least 2, when the rank exceeds 2, `X` +would be viewed as a 2-D tensor. + Following are cases to better explain how this works: + Case 1: -Given a 2-level LoDTensor input(X) - X.lod = [[0, 2, 3], - [0, 1, 3, 4]] - X.data = [a, b, c, d] +Given a 1-level LoDTensor input(X) + X.lod = [[0, 2, 4]] + X.data = [[a], [b], [c], [d]] X.dims = [4, 1] and input(Y) Y.lod = [[0, 2, 4], [0, 3, 6, 7, 8]] -with condition len(Y.lod[-1]) -1 == X.dims[0] -then we get 2-level LoDTensor - Out.lod = [[0, 2, 4], - [0, 3, 6, 7, 8]] - Out.data = [a, a, a, b, b, b, c, d] +ref_level: 0 +then we get 1-level LoDTensor + Out.lod = [[0, 2, 4, 6, 8]] + Out.data = [[a], [b], [a], [b], [c], [d], [c], [d]] Out.dims = [8, 1] Case 2: +Given 1-level LoDTensor input(X) + X.lod = [[0, 1, 4]] + X.data = [[a], [b], [c], [d]] + X.dims = [4, 1] +and input(Y) + Y.lod = [[0, 2, 4], + [0, 3, 6, 6, 8]] +ref_level: 0 +then we get 1-level LoDTensor + Out.lod = [[0, 2, 5, 8]] + Out.data = [[a], [a], [b], [c], [d], [b], [c], [d]] + Out.dims = [8, 1] + +Case 3: + Given a common Tensor input(X) - X.data = [a, b, c] + X.data = [[a], [b], [c]] X.dims = [3, 1] and input(Y) Y.lod = [[0, 2, 3, 6]] -with condition len(Y.lod[-1]) -1 == X.dims[0] -then we get 1-level LoDTensor - Out.lod = [[0, 2, 3, 6]] - Out.data = [a, a, b, c, c, c] +ref_level: -1 +then we a common Tensor + Out.data = [[a], [a], [b], [c], [c], [c]] Out.dims = [6, 1] -Case 3: +Case 4: Given a common Tensor input(X) X.data = [[a, b], [c, d], [e, f]] X.dims = [3, 2] and input(Y) Y.lod = [[0, 2, 3, 6]] -with condition len(Y.lod[-1]) -1 == X.dims[0] -then we get 1-level LoDTensor - Out.lod = [[0, 2, 3, 6]] - Out.data = [[a,b], [a,b] [c,d], [e, f], [e, f], [e, f]] +ref_level: 0 +then we get a common LoDTensor + Out.data = [[a, b], [a, b] [c, d], [e, f], [e, f], [e, f]] Out.dims = [6, 2] -Case 4: - -Given 2-level a LoDTensor input(X) - X.lod = [[0, 2, 3], - [0, 1, 3, 4]] - X.data = [a, b, c, d] - X.dims = [4, 1] -and input(Y) - Y.lod = [[0, 2, 4], - [0, 3, 6, 6, 8]] -with condition len(Y.lod[-1]) -1 == X.dims[0] -then we get 2-level LoDTensor - Out.lod = [[0, 2, 4], - [0, 3, 6, 6, 8]] - Out.data = [a, a, a, b, b, b, d, d] - Out.dims = [8, 1] - - )DOC"); } }; diff --git a/paddle/fluid/operators/sequence_expand_op.h b/paddle/fluid/operators/sequence_expand_op.h index 8cbfdf177e..eea3cf0440 100644 --- a/paddle/fluid/operators/sequence_expand_op.h +++ b/paddle/fluid/operators/sequence_expand_op.h @@ -22,6 +22,9 @@ namespace paddle { namespace operators { using LoDTensor = framework::LoDTensor; +template +using EigenMatrix = framework::EigenMatrix; template class SequenceExpandKernel : public framework::OpKernel { @@ -30,15 +33,12 @@ class SequenceExpandKernel : public framework::OpKernel { auto* x = context.Input("X"); auto* y = context.Input("Y"); auto* out = context.Output("Out"); - int ref_level = context.Attr("ref_level"); - out->mutable_data(context.GetPlace()); + int ref_level = context.Attr("ref_level"); auto& x_lod = x->lod(); auto& y_lod = y->lod(); - PADDLE_ENFORCE_GT(y_lod.size(), 0, "Level number of `Y`'s lod should be greater than 0."); - PADDLE_ENFORCE( ref_level == -1 || (ref_level >= 0 && ref_level < y_lod.size()), "Invlid `ref_level`, which should be either equal to -1 " @@ -47,6 +47,8 @@ class SequenceExpandKernel : public framework::OpKernel { if (ref_level == -1) ref_level = y_lod.size() - 1; + out->mutable_data(context.GetPlace()); + if (y_lod[ref_level].size() <= 1) { framework::TensorCopy(*x, context.GetPlace(), out); return; @@ -59,6 +61,8 @@ class SequenceExpandKernel : public framework::OpKernel { } int out_offset = 0; + auto& eigen_place = + *context.template device_context().eigen_device(); for (size_t i = 1; i < y_lod[ref_level].size(); ++i) { int repeat_num = y_lod[ref_level][i] - y_lod[ref_level][i - 1]; int x_start = i - 1; @@ -68,16 +72,24 @@ class SequenceExpandKernel : public framework::OpKernel { x_end = x_lod[0][i]; } int x_seq_len = x_end - x_start; - auto x_sub_tensor = x->Slice(x_start, x_end); - for (size_t j = 0; j < repeat_num; ++j) { + if (repeat_num > 0) { + auto x_sub_tensor = x->Slice(x_start, x_end); + x_sub_tensor.Resize({1, x_sub_tensor.numel()}); int out_start = out_offset; if (x_lod.size() == 1) { out_start = out_lod[0][out_offset]; - out_lod[0].push_back(x_seq_len); } - auto out_sub_tensor = out->Slice(out_start, out_start + x_seq_len); - framework::TensorCopy(x_sub_tensor, context.GetPlace(), - &out_sub_tensor); + auto out_sub_tensor = + out->Slice(out_start, out_start + x_seq_len * repeat_num); + out_sub_tensor.Resize({repeat_num, x_sub_tensor.dims()[1]}); + EigenMatrix::From(out_sub_tensor).device(eigen_place) = + EigenMatrix::From(x_sub_tensor) + .broadcast(Eigen::array({{repeat_num, 1}})); + } + for (int j = 0; j < repeat_num; ++j) { + if (x_lod.size() == 1) { + out_lod[0].push_back(out_lod[0].back() + x_seq_len); + } out_offset++; } } @@ -122,6 +134,9 @@ class SequenceExpandGradKernel : public framework::OpKernel { auto& dev_ctx = context.template device_context(); + math::SetConstant set_zero; + set_zero(dev_ctx, g_x, static_cast(0)); + int g_out_offset = 0; for (size_t i = 1; i < y_lod[ref_level].size(); ++i) { int repeat_num = y_lod[ref_level][i] - y_lod[ref_level][i - 1]; @@ -133,12 +148,11 @@ class SequenceExpandGradKernel : public framework::OpKernel { x_end = x_lod[0][i]; } int x_seq_len = x_end - x_start; - auto column = x_seq_len * x->dims()[1]; auto g_x_sub = g_x->Slice(x_start, x_end); - g_x_sub = framework::ReshapeToMatrix(g_x_sub, column); + g_x_sub.Resize(flatten_to_1d(g_x_sub.dims())); int g_out_end = g_out_offset + repeat_num * x_seq_len; auto g_out_sub = g_out->Slice(g_out_offset, g_out_end); - g_out_sub = framework::ReshapeToMatrix(g_out_sub, column); + g_out_sub.Resize({repeat_num, g_x_sub.dims()[0]}); math::ColwiseSum col_sum; col_sum(dev_ctx, g_out_sub, &g_x_sub); g_out_offset += repeat_num * x_seq_len; diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index bc2be4cdfe..4e6f76206e 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -1781,52 +1781,52 @@ def conv2d_transpose(input, return out -def sequence_expand(x, y, name=None): +def sequence_expand(x, y, ref_level=-1, name=None): """Sequence Expand Layer. This layer will expand the input variable **x** - according to LoD information of **y**. And the following examples will - explain how sequence_expand works: + according to specified level lod of **y**. Please note that lod level of + **x** is at most 1 and rank of **x** is at least 2. When rank of **x** + is greater than 2, then it would be viewed as a 2-D tensor. + Following examples will explain how sequence_expand works: .. code-block:: text * Case 1 x is a LoDTensor: - x.lod = [[0, 2, 3], - [0, 1, 3, 4]] - x.data = [a, b, c, d] + x.lod = [[0, 2, 4]] + x.data = [[a], [b], [c], [d]] x.dims = [4, 1] y is a LoDTensor: y.lod = [[0, 2, 4], [0, 3, 6, 7, 8]] - with condition len(y.lod[-1]) - 1 == x.dims[0] + ref_level: 0 - then output is a 2-level LoDTensor: - out.lod = [[0, 2, 4], - [0, 3, 6, 7, 8]] - out.data = [a, a, a, b, b, b, c, d] + then output is a 1-level LoDTensor: + out.lod = [[0, 2, 4, 6, 8]] + out.data = [[a], [b], [a], [b], [c], [d], [c], [d]] out.dims = [8, 1] * Case 2 x is a Tensor: - x.data = [a, b, c] + x.data = [[a], [b], [c]] x.dims = [3, 1] y is a LoDTensor: - y.lod = [[0, 2, 3, 6]] - - with condition len(y.lod[-1]) - 1 == x.dims[0] + y.lod = [[0, 2, 2, 5]] - then output is a 1-level LoDTensor: - out.lod = [[0, 2, 3, 6]] - out.data = [a, a, b, c, c, c] - out.dims = [6, 1] + ref_level: -1 + then output is a Tensor: + out.data = [[a], [a], [c], [c], [c]] + out.dims = [5, 1] Args: x (Variable): The input variable which is a Tensor or LoDTensor. y (Variable): The input variable which is a LoDTensor. + ref_level (int): Lod level of `y` to be referred by `x`. If set to -1, + refer the last level of lod. name(str|None): A name for this layer(optional). If set None, the layer - will be named automatically. + will be named automatically. Returns: Variable: The expanded variable which is a LoDTensor. @@ -1837,14 +1837,17 @@ def sequence_expand(x, y, name=None): x = fluid.layers.data(name='x', shape=[10], dtype='float32') y = fluid.layers.data(name='y', shape=[10, 20], dtype='float32', lod_level=1) - out = layers.sequence_expand(x=x, y=y) + out = layers.sequence_expand(x=x, y=y, ref_level=0) """ helper = LayerHelper('sequence_expand', input=x, **locals()) dtype = helper.input_dtype() tmp = helper.create_tmp_variable(dtype) helper.append_op( - type='sequence_expand', inputs={'X': x, - 'Y': y}, outputs={'Out': tmp}) + type='sequence_expand', + inputs={'X': x, + 'Y': y}, + outputs={'Out': tmp}, + attrs={'ref_level': ref_level}) return tmp diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index 6944cca394..e56d78ae8b 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -181,8 +181,8 @@ class TestBook(unittest.TestCase): with program_guard(program): x = layers.data(name='x', shape=[10], dtype='float32') y = layers.data( - name='y', shape=[10, 20], dtype='float32', lod_level=1) - self.assertIsNotNone(layers.sequence_expand(x=x, y=y)) + name='y', shape=[10, 20], dtype='float32', lod_level=2) + self.assertIsNotNone(layers.sequence_expand(x=x, y=y, ref_level=1)) print(str(program)) def test_lstm_unit(self): diff --git a/python/paddle/fluid/tests/unittests/test_sequence_expand.py b/python/paddle/fluid/tests/unittests/test_sequence_expand.py index 957fa5d2c4..7feb509c4d 100644 --- a/python/paddle/fluid/tests/unittests/test_sequence_expand.py +++ b/python/paddle/fluid/tests/unittests/test_sequence_expand.py @@ -27,12 +27,36 @@ class TestSequenceExpand(OpTest): def compute(self): x = self.inputs['X'] x_data, x_lod = x if type(x) == tuple else (x, None) - n = 1 + x_data.shape[0] if not x_lod else len(x_lod[0]) y_data, y_lod = self.inputs['Y'] - repeats = [((y_lod[-1][i + 1] - y_lod[-1][i])) - for i in range(len(y_lod[-1]) - 1)] - out = x_data.repeat(repeats, axis=0) - self.outputs = {'Out': out} + + if hasattr(self, 'attrs'): + ref_level = self.attrs['ref_level'] + else: + ref_level = len(y_lod) - 1 + + out = np.zeros(shape=((0, ) + x_data.shape[1:]), dtype=x_data.dtype) + + if x_lod is None: + x_idx = [i for i in xrange(x_data.shape[0] + 1)] + else: + x_idx = x_lod[0] + out_lod = [[0]] + + for i in xrange(1, len(y_lod[ref_level])): + repeat_num = y_lod[ref_level][i] - y_lod[ref_level][i - 1] + x_len = x_idx[i] - x_idx[i - 1] + if repeat_num > 0: + x_sub = x_data[x_idx[i - 1]:x_idx[i], :] + x_sub = np.repeat(x_sub, repeat_num, axis=0) + out = np.vstack((out, x_sub)) + if x_lod is not None: + for j in xrange(repeat_num): + out_lod[0].append(out_lod[0][-1] + x_len) + + if x_lod is None: + self.outputs = {'Out': out} + else: + self.outputs = {'Out': (out, out_lod)} def setUp(self): self.op_type = 'sequence_expand' @@ -52,7 +76,8 @@ class TestSequenceExpandCase1(TestSequenceExpand): x_lod = [[0, 2, 5]] y_data = np.random.uniform(0.1, 1, [13, 1]).astype('float32') y_lod = [[0, 2, 5], [0, 2, 4, 7, 10, 13]] - self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)} + self.inputs = {'X': x_data, 'Y': (y_data, y_lod)} + self.attrs = {'ref_level': 0} class TestSequenceExpandCase2(TestSequenceExpand): @@ -60,8 +85,9 @@ class TestSequenceExpandCase2(TestSequenceExpand): x_data = np.random.uniform(0.1, 1, [1, 2, 2]).astype('float32') x_lod = [[0, 1]] y_data = np.random.uniform(0.1, 1, [2, 2, 2]).astype('float32') - y_lod = [[0, 2]] + y_lod = [[0, 2], [0, 2]] self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)} + self.attrs = {'ref_level': 0} class TestSequenceExpandCase3(TestSequenceExpand): @@ -75,14 +101,9 @@ class TestSequenceExpandCase3(TestSequenceExpand): class TestSequenceExpandCase4(TestSequenceExpand): def set_data(self): - x_data = np.array( - [0.1, 0.3, 0.2, 0.15, 0.25, 0.2, 0.15, 0.25, 0.1, 0.3]).reshape( - [2, 5]).astype('float32') - x_lod = [[ - 0, - 1, - 2, - ]] + data = [0.1, 0.3, 0.2, 0.15, 0.25, 0.2, 0.15, 0.25, 0.1, 0.3] + x_data = np.array(data).reshape([5, 2]).astype('float32') + x_lod = [[0, 2, 5]] y_data = np.random.uniform(0.1, 1, [2, 1]).astype('float32') y_lod = [[0, 1, 2], [0, 1, 2]] self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)} -- GitLab