diff --git a/paddle/fluid/operators/lod_reset_op.cc b/paddle/fluid/operators/lod_reset_op.cc index f7d1a90d33c208b64761f910fd356715808c19ac..66c6de45077645ba802684e5dd326f6761ffeb37 100644 --- a/paddle/fluid/operators/lod_reset_op.cc +++ b/paddle/fluid/operators/lod_reset_op.cc @@ -24,16 +24,17 @@ class LoDResetOp : public framework::OperatorWithKernel { using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { - PADDLE_ENFORCE(ctx->HasInput("X"), - "Input(X) of LoDResetOp should not be null."); - PADDLE_ENFORCE(ctx->HasOutput("Out"), - "Output(Out) of LoDResetOp should not be null."); + OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "LoDReset"); + OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "LoDReset"); if (!ctx->HasInput("Y")) { auto level0 = ctx->Attrs().Get>("target_lod"); - PADDLE_ENFORCE_GT(level0.size(), 0, - "If Input(Y) not provided, the target lod should be " - "specified by attribute `target_lod`."); + PADDLE_ENFORCE_GT( + static_cast(level0.size()), 0, + platform::errors::InvalidArgument( + "If Input(Y) not provided, the target lod should be " + "specified by attribute `target_lod`. But the size of " + "`target_lod` is 0.")); } else if (ctx->IsRuntime()) { ctx->ShareLoD("Y", "Out"); } @@ -181,10 +182,9 @@ class LoDResetGradOp : public framework::OperatorWithKernel { using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { - PADDLE_ENFORCE(ctx->HasInput("X"), - "Input(X) of LoDResetGradOp should not be null."); - PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")), - "Input(Out@Grad) of LoDResetGradOp should not be null."); + OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "LoDResetGrad"); + OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Output", + framework::GradVarName("Out"), "LoDResetGrad"); auto x_grad_name = framework::GradVarName("X"); if (ctx->HasOutput(x_grad_name)) { diff --git a/paddle/fluid/operators/lod_reset_op.h b/paddle/fluid/operators/lod_reset_op.h index 87e8c31a9d0ae567de31e7a120d48ec8cadf755c..8a809ece49b4139f9fe37b83ccd5eb2764b83607 100644 --- a/paddle/fluid/operators/lod_reset_op.h +++ b/paddle/fluid/operators/lod_reset_op.h @@ -38,9 +38,14 @@ class LoDResetKernel : public framework::OpKernel { if (lod_t->lod().size() > 0) { auto y_lod = lod_t->lod(); auto last_level = y_lod[y_lod.size() - 1]; - PADDLE_ENFORCE_EQ((int64_t)(last_level.back()), in->dims()[0], - "Last value of `Y`'s last level LoD should be equal " - "to the first dimension of `X`"); + PADDLE_ENFORCE_EQ( + static_cast(last_level.back()), in->dims()[0], + platform::errors::InvalidArgument( + "The last value of `Y`'s last level LoD should be equal " + "to the first dimension of `X`. But received the last value of " + "`Y`'s last level LoD is %d, the first dimension of `X` is " + "%d. ", + static_cast(last_level.back()), in->dims()[0])); out->set_lod(y_lod); return; // early return, since lod already set } else { @@ -56,16 +61,33 @@ class LoDResetKernel : public framework::OpKernel { level0 = ctx.Attr>("target_lod"); } - PADDLE_ENFORCE_GT(level0.size(), 1UL, - "Size of target LoD should be greater than 1."); - PADDLE_ENFORCE_EQ(level0[0], 0, - "Target LoD should be a vector starting from 0."); - PADDLE_ENFORCE_EQ(level0.back(), in->dims()[0], - "Target LoD should be a vector end with the " - "first dimension of Input(X)."); + PADDLE_ENFORCE_GT( + level0.size(), 1UL, + platform::errors::InvalidArgument( + "The size of target LoD should be greater than 1. But received the " + "size of target LoD is %d.", + level0.size())); + PADDLE_ENFORCE_EQ(static_cast(level0[0]), 0, + platform::errors::InvalidArgument( + "Target LoD should be a vector starting from 0. But " + "target LoD starts from %d.", + static_cast(level0[0]))); + PADDLE_ENFORCE_EQ( + static_cast(level0.back()), in->dims()[0], + platform::errors::InvalidArgument( + "The last value of `Target LoD`'s last level LoD should be equal " + "to the first dimension of `X`. But received the last value of " + "`Target LoD`'s last level LoD is %d, the first dimension of `X` " + "is " + "%d. ", + static_cast(level0.back()), in->dims()[0])); for (size_t i = 0; i < level0.size() - 1; ++i) { - PADDLE_ENFORCE(level0[i + 1] >= level0[i], - "Target LoD should be an ascending vector."); + PADDLE_ENFORCE_GE( + level0[i + 1], level0[i], + platform::errors::InvalidArgument( + "Target LoD should be an ascending vector. But the %s element is " + "%s and the %s element of Target LoD is %s.", + i + 1, level0[i + 1], i, level0[i])); } // cast level0 to size_t diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 8770cd932605b882e6e8cce498d93010e07921e3..9d1c1a1c8c5d7914b705a1993eaee31ad14075a8 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -6189,9 +6189,16 @@ def lod_reset(x, y=None, target_lod=None): y = fluid.layers.data(name='y', shape=[10, 20], lod_level=2) out = fluid.layers.lod_reset(x=x, y=y) """ + check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'], + 'lod_reset') helper = LayerHelper("lod_reset", **locals()) out = helper.create_variable_for_type_inference(dtype=x.dtype) if y is not None: + if y.lod_level > 0: + check_variable_and_dtype( + y, 'y', ['float32', 'float64', 'int32', 'int64'], 'lod_reset') + else: + check_variable_and_dtype(y, 'y', ['int32', 'int64'], 'lod_reset') helper.append_op( type="lod_reset", inputs={'X': x, 'Y': y}, outputs={'Out': out}) diff --git a/python/paddle/fluid/tests/unittests/test_lod_reset_op.py b/python/paddle/fluid/tests/unittests/test_lod_reset_op.py index 4c82605e0c89a1f43889b75fe5d94d6410b33090..236c9944145ed46852ec18467bd2190edf073526 100644 --- a/python/paddle/fluid/tests/unittests/test_lod_reset_op.py +++ b/python/paddle/fluid/tests/unittests/test_lod_reset_op.py @@ -17,6 +17,7 @@ from __future__ import print_function import unittest import numpy as np from op_test import OpTest +from paddle.fluid import Program, program_guard class TestLodResetOpByAttr(OpTest): @@ -132,5 +133,32 @@ class TestLodAppendOpByAttr(OpTest): self.check_grad(["X"], "Out", check_dygraph=False) +class TestLodResetOpError(unittest.TestCase): + def test_errors(self): + with program_guard(Program(), Program()): + + def test_Variable(): + # The input must be Variable. + x1 = fluid.create_lod_tensor( + np.ones([6]), [3, 3], fluid.CPUPlace()) + y1 = fluid.create_lod_tensor( + np.ones([6]), [2, 2, 2], fluid.CPUPlace()) + self.assertRaises(TypeError, fluid.layers.lod_reset, [x1, y1]) + + def test_type(): + # dtype must be float32 or float64 or int32 or int64 + x2 = fluid.layers.data(shape=[4], dtype='uint8', name='x2') + y2 = fluid.layers.data( + shape=[4], dtype='uint8', name='x2', lod_level=2) + self.assertRaises(TypeError, fluid.layers.lod_reset, [x2, y2]) + + def test_type2(): + # dtype must be int32 or int64 + x3 = fluid.layers.data(shape=[4], dtype='float32', name='x3') + y3 = fluid.layers.data( + shape=[4], dtype='float32', name='x3', lod_level=0) + self.assertRaises(TypeError, fluid.layers.lod_reset, [x3, y3]) + + if __name__ == '__main__': unittest.main()