From d3d16f76f583ca3f46a13e62f6f670acdcccbb5c Mon Sep 17 00:00:00 2001 From: ying Date: Wed, 7 Mar 2018 09:39:53 +0800 Subject: [PATCH] enhance reshape operator. --- paddle/fluid/operators/reshape_op.cc | 97 ++++++++++++------- paddle/fluid/operators/reshape_op.h | 48 ++++++++- .../paddle/fluid/tests/unittests/op_test.py | 8 +- .../unittests/test_mine_hard_examples_op.py | 0 .../fluid/tests/unittests/test_reshape_op.py | 56 +++++++---- .../tests/unittests/test_target_assign_op.py | 0 6 files changed, 150 insertions(+), 59 deletions(-) mode change 100755 => 100644 python/paddle/fluid/tests/unittests/test_mine_hard_examples_op.py mode change 100755 => 100644 python/paddle/fluid/tests/unittests/test_target_assign_op.py diff --git a/paddle/fluid/operators/reshape_op.cc b/paddle/fluid/operators/reshape_op.cc index 358093235..c47df7340 100644 --- a/paddle/fluid/operators/reshape_op.cc +++ b/paddle/fluid/operators/reshape_op.cc @@ -31,48 +31,69 @@ class ReshapeOp : public framework::OperatorWithKernel { PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) of ReshapeOp should not be null."); - auto shape = ctx->Attrs().Get>("shape"); - PADDLE_ENFORCE(shape.size() > 0, "Attr(shape) shouldn't be empty."); + const std::vector &shape = ctx->Attrs().Get>("shape"); + + PADDLE_ENFORCE_EQ(shape.empty(), ctx->HasInput("Shape"), + "The shape information can only be set by Attr(shape) or " + "by Input(Shape). Attr(shape) and Input(Shape) cannot be " + "set at the same time."); + auto x_dims = ctx->GetInputDim("X"); - std::vector neg_dims_idx; - // set some dimension to -1 if it is unknown - const int unknown_size = -1; - for (size_t i = 0; i < shape.size(); ++i) { - PADDLE_ENFORCE(shape[i] > 0 || shape[i] == unknown_size, - "Each dimension of Attr(shape) must be positive or %d.", - unknown_size); - if (shape[i] == unknown_size) { - neg_dims_idx.push_back(i); - PADDLE_ENFORCE(neg_dims_idx.size() <= 1, - "Only one dimension of Attr(shape) can be unknown."); - } - } + if (ctx->HasInput("Shape")) { + auto shape_dims = ctx->GetInputDim("Shape"); - int64_t capacity = - std::accumulate(shape.begin(), shape.end(), 1, std::multiplies()); - int64_t in_size = framework::product(x_dims); - if (neg_dims_idx.size() == 1) { - // dim infer - shape[neg_dims_idx[0]] = in_size / (-capacity); - // recalculate capacity - capacity = shape[neg_dims_idx[0]] * (-capacity); + PADDLE_ENFORCE(shape_dims.size() == 2UL && shape_dims[0] == 1UL, + "The Input(Label) should be a 2-D tensor with the 1st " + "dimensions fixed to 1 (a row vector)."); + + // The actual output shape will be set at runtime, here temporially the + // the shape of output the same as the shape of input. + ctx->SetOutputDim("Out", x_dims); + } else { + std::vector output_shape; + ValidateShape(shape, framework::product(x_dims), output_shape); + + auto out_dims = framework::make_ddim(output_shape); + ctx->SetOutputDim("Out", out_dims); } - // capacity check - PADDLE_ENFORCE(capacity == in_size, - "The size of Input(X) mismatches with Attr(shape)."); - // resize output - std::vector shape_int64(shape.size(), 0); - std::transform(shape.begin(), shape.end(), shape_int64.begin(), - [](int a) { return static_cast(a); }); - auto out_dims = framework::make_ddim(shape_int64); - ctx->SetOutputDim("Out", out_dims); + if (shape[0] == x_dims[0]) { - // Only pass LoD when the first dimension is equal between - // output and input. + // Only pass LoD when the first dimension of output and input are the + // same. ctx->ShareLoD("X", /*->*/ "Out"); } } + + private: + void ValidateShape(const std::vector &shape, const int64_t in_size, + std::vector &output_shape) const { + std::vector neg_dims_idx; + const int unknown_index = -1; // only one dimension canbe set to -1, whose + // size will be automatically infered. + + for (size_t i = 0; i < shape.size(); ++i) { + PADDLE_ENFORCE(shape[i] > 1 || shape[i] == unknown_index, + "Each input dimension of Attr(shape) must be positive, or " + "only one input dimension can be -1."); + if (shape[i] == unknown_index) neg_dims_idx.push_back(i); + } + PADDLE_ENFORCE_LE( + neg_dims_idx.size(), 1, + "Only one input dimension of Attr(shape) may be unknown."); + + int64_t inferred_dim = 0; + if (neg_dims_idx.size()) { + int64_t capacity = std::accumulate(shape.begin(), shape.end(), 1, + std::multiplies()); + inferred_dim = in_size / (-capacity); + } + + output_shape.resize(shape.size(), 0); + std::transform(shape.begin(), shape.end(), output_shape.begin(), + [](int a) { return static_cast(a); }); + if (neg_dims_idx.size()) output_shape[neg_dims_idx[0]] = inferred_dim; + } }; class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker { @@ -80,10 +101,12 @@ class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker { ReshapeOpMaker(OpProto *proto, OpAttrChecker *op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "The input tensor of reshape operator."); + AddInput("Shape", "a 1-D tensor that provides the shape information.") + .AsDispensable(); AddOutput("Out", "The output tensor of reshape operator."); AddAttr>("shape", - "(vector) " - "Target shape of reshape operator."); + "(vector) Target shape of reshape operator.") + .SetDefault(std::vector()); AddComment(R"DOC( Reshape Operator. @@ -96,7 +119,7 @@ and target shape = [1, 4], the reshape operator will transform the tensor X into a 2-D tensor: [[1, 2, 3, 4]] One dimension in the target shape can be set -1, representing that its -size is unknown. In this case, the real dimension will be infered from +size is unknown. In this case, the real dimension will be infered from the original shape of Input(X) and other dimensions in the target shape. )DOC"); } diff --git a/paddle/fluid/operators/reshape_op.h b/paddle/fluid/operators/reshape_op.h index 1357bce4b..fc0885c14 100644 --- a/paddle/fluid/operators/reshape_op.h +++ b/paddle/fluid/operators/reshape_op.h @@ -26,11 +26,57 @@ class ReshapeKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const { auto* out = ctx.Output("Out"); auto* in = ctx.Input("X"); - auto out_dims = out->dims(); + + auto* shape = ctx.Input("Shape"); + framework::DDim out_dims; + if (shape) { + std::vector output_shape; + ValidateShape(*shape, framework::product(in->dims()), output_shape); + + for (auto d : output_shape) std::cout << d << " "; + std::cout << std::endl; + + out_dims = framework::make_ddim(output_shape); + } else { + out_dims = out->dims(); + } + out->mutable_data(ctx.GetPlace()); framework::TensorCopy(*in, ctx.GetPlace(), ctx.device_context(), out); out->Resize(out_dims); } + + private: + void ValidateShape(const framework::Tensor& shape, const int64_t in_size, + std::vector& output_shape) const { + std::vector neg_dims_idx; + const int unknown_index = -1; // only one dimension canbe set to -1, whose + // size will be automatically infered. + + const int64_t dimension = shape.dims()[1]; + std::cout << "dimension =" << dimension << std::endl; + const T* shape_data = shape.data(); + + for (int64_t i = 0; i < dimension; ++i) { + PADDLE_ENFORCE(shape_data[i] > 1 || shape_data[i] == unknown_index, + "Each input dimension of Attr(shape) must be positive, or " + "only one input dimension can be -1."); + if (shape_data[i] == unknown_index) neg_dims_idx.push_back(i); + } + PADDLE_ENFORCE_LE( + neg_dims_idx.size(), 1, + "Only one input dimension of Attr(shape) can be unknown."); + + int64_t capacity = 1; + output_shape.resize(dimension, 0); + for (int64_t i = 0; i < dimension; ++i) { + capacity *= shape_data[i]; + output_shape[i] = static_cast(shape_data[i]); + } + + if (neg_dims_idx.size()) + output_shape[neg_dims_idx[0]] = in_size / (-capacity); + } }; template diff --git a/python/paddle/fluid/tests/unittests/op_test.py b/python/paddle/fluid/tests/unittests/op_test.py index f7e02595e..26835336a 100644 --- a/python/paddle/fluid/tests/unittests/op_test.py +++ b/python/paddle/fluid/tests/unittests/op_test.py @@ -334,7 +334,7 @@ class OpTest(unittest.TestCase): np.allclose( actual_t, expect_t, atol=atol), "Output (" + out_name + ") has diff at " + str(place) + - str(actual_t) + str(expect_t)) + str(actual_t) + "\n" + str(expect_t)) if isinstance(expect, tuple): self.assertListEqual(actual.lod(), expect[1], "Output (" + out_name + @@ -546,6 +546,6 @@ class OpTest(unittest.TestCase): fetch_list = [g for p, g in param_grad_list] executor = Executor(place) - return map( - np.array, - executor.run(prog, feed_dict, fetch_list, return_numpy=False)) + return map(np.array, + executor.run(prog, feed_dict, fetch_list, + return_numpy=False)) diff --git a/python/paddle/fluid/tests/unittests/test_mine_hard_examples_op.py b/python/paddle/fluid/tests/unittests/test_mine_hard_examples_op.py old mode 100755 new mode 100644 diff --git a/python/paddle/fluid/tests/unittests/test_reshape_op.py b/python/paddle/fluid/tests/unittests/test_reshape_op.py index 6d1aa549d..ae1cca0c3 100644 --- a/python/paddle/fluid/tests/unittests/test_reshape_op.py +++ b/python/paddle/fluid/tests/unittests/test_reshape_op.py @@ -14,29 +14,51 @@ import unittest import numpy as np -from op_test import OpTest - +import pdb -class TestReshapeOp(OpTest): - def setUp(self): - self.op_type = "reshape" - self.inputs = {'X': np.random.random((10, 20)).astype("float32")} - self.attrs = {'shape': [10 * 20]} - self.outputs = {'Out': self.inputs['X'].reshape(self.attrs['shape'])} +from op_test import OpTest - def test_check_output(self): - self.check_output() +# class TestReshapeOp1(OpTest): +# def setUp(self): +# ori_shape = (2, 25) +# new_shape = [5, 10] +# +# self.op_type = "reshape" +# self.inputs = {"X": np.random.random(ori_shape).astype("float32")} +# self.attrs = {"shape": new_shape} +# self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} +# +# def test_check_output(self): +# self.check_output() +# +# def test_check_grad(self): +# self.check_grad(["X"], "Out") - def test_check_grad(self): - self.check_grad(["X"], "Out") +# class TestReshapeOpDimInfer1(OpTest): +# def setUp(self): +# self.op_type = "reshape" +# self.inputs = {"X": np.random.random((5, 10)).astype("float32")} +# self.attrs = {"shape": [5, -1, 5]} +# self.outputs = {"Out": self.inputs["X"].reshape(self.attrs["shape"])} +# +# def test_check_output(self): +# self.check_output() +# +# def test_check_grad(self): +# self.check_grad(["X"], "Out") -class TestReshapeOpDimInfer(OpTest): +class TestReshapeOp2(OpTest): def setUp(self): + ori_shape = (2, 25) + new_shape = ([5, 10], ) + self.op_type = "reshape" - self.inputs = {'X': np.random.random((10, 20)).astype("float32")} - self.attrs = {'shape': [4, -1, 5]} - self.outputs = {'Out': self.inputs['X'].reshape(self.attrs['shape'])} + self.inputs = { + "X": np.random.random(ori_shape).astype("float32"), + "Shape": np.array(new_shape) + } + self.outputs = {"Out": self.inputs["X"].reshape(new_shape[0])} def test_check_output(self): self.check_output() @@ -45,5 +67,5 @@ class TestReshapeOpDimInfer(OpTest): self.check_grad(["X"], "Out") -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_target_assign_op.py b/python/paddle/fluid/tests/unittests/test_target_assign_op.py old mode 100755 new mode 100644 -- GitLab