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API/OP(sequence_expand_as) error message enhancement (#23712)

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* API/OP(sequence_expand_as) error message enhancement.
test=develop

Co-authored-by: FrostML <380185688@qq.com>
v1.8
Guo Sheng 5 years ago committed by GitHub
parent 03ba5b748d
commit fe8d006f7e
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 73 additions and 33 deletions
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32
paddle/fluid/operators/sequence_ops/sequence_expand_as_op.cc
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@ -27,18 +27,18 @@ class SequenceExpandAsOp : public framework::OperatorWithKernel {
protected:
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"),
"Input(X) of SequenceExpandAsOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Y"),
"Input(Y) of SequenceExpandAsOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of SequenceExpandAsOp should not be null.");
OP_INOUT_CHECK(ctx->HasInputs("X"), "Input", "X", "SequenceExpandAs");
OP_INOUT_CHECK(ctx->HasInputs("Y"), "Input", "Y", "SequenceExpandAs");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SequenceExpandAs");
auto x_dims = ctx->GetInputDim("X");
auto out_dims = x_dims;
PADDLE_ENFORCE_GE(x_dims.size(), 2,
"Dimension number of Input(X) should be at least 2.");
platform::errors::InvalidArgument(
"Dimension number of Input(X) should be at least 2. "
"But received X's dimensions = %d, X's shape = [%s].",
x_dims.size(), x_dims));
if (ctx->IsRuntime()) {
framework::Variable* x_var =
@ -50,11 +50,17 @@ class SequenceExpandAsOp : public framework::OperatorWithKernel {
auto& y_lod = y_var->Get<LoDTensor>().lod();
PADDLE_ENFORCE_EQ(y_lod.size(), 1,
"Level number of Input(Y)'s lod should be 1.");
platform::errors::InvalidArgument(
"Level number of Input(Y)'s lod should be 1. But "
"received Y's lod level = %d.",
y_lod.size()));
PADDLE_ENFORCE_EQ(static_cast<size_t>(x_dim[0]), y_lod[0].size() - 1,
"The first dimension of Input(X) should be equal "
"to the size of Input(Y)'s 0 level lod.");
platform::errors::InvalidArgument(
"The first dimension of Input(X) should be one "
"less than the size of Input(Y)'s 0 level lod. But "
"received X's shape[0] = %d, Y's lod[0].size = %d.",
x_dim[0], y_lod[0].size()));
int64_t out_first_dim = 0;
if (y_lod[0].size() <= 1) {
@ -138,9 +144,9 @@ class SequenceExpandAsOpGrad : public framework::OperatorWithKernel {
protected:
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null.");
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
"Input(Out@GRAD) should not be null.");
OP_INOUT_CHECK(ctx->HasInputs("X"), "Input", "X", "SequenceExpandAsGrad");
OP_INOUT_CHECK(ctx->HasInputs(framework::GradVarName("Out")), "Input",
"Out@GRAD", "SequenceExpandAsGrad");
auto x_dims = ctx->GetInputDim("X");
auto x_grad_name = framework::GradVarName("X");

22
paddle/fluid/operators/sequence_ops/sequence_expand_as_op.h
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@ -74,13 +74,25 @@ class SequenceExpandAsKernel : public framework::OpKernel<T> {
auto *y = context.Input<framework::LoDTensor>("Y");
auto *out = context.Output<framework::LoDTensor>("Out");
PADDLE_ENFORCE_EQ(y->lod().empty(), false,
"Input(Y) Tensor of SequenceExpandAsOp does not contain "
"LoD information.");
PADDLE_ENFORCE_EQ(
y->lod().empty(), false,
platform::errors::InvalidArgument(
"Input(Y) of SequenceExpandAsOp has wrong LoD information. "
"Expected Y's lod is not empty, but received empty lod."));
auto &y_lod = y->lod();
PADDLE_ENFORCE_EQ(y_lod.size(), 1, "LoD of Y should be 1.");
PADDLE_ENFORCE_GT(y_lod[0].size(), 1, ".");
PADDLE_ENFORCE_EQ(y_lod.size(), 1,
platform::errors::InvalidArgument(
"Input(Y) of SequenceExpandAsOp has wrong LoD "
"information. Expected Y's lod level = 1, but "
"received lod level = %d.",
y_lod.size()));
PADDLE_ENFORCE_GT(y_lod[0].size(), 1,
platform::errors::InvalidArgument(
"Input(Y) of SequenceExpandAsOp has wrong LoD "
"information. Expected the size of Y's lod[0] > 1, "
"but received lod[0].size = %d.",
y_lod[0].size()));
out->mutable_data<T>(context.GetPlace());

33
python/paddle/fluid/layers/sequence_lod.py
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@ -52,7 +52,7 @@ def sequence_conv(input,
act=None,
name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Notes: The Op only receives LoDTensor as input. If your input is Tensor, please use conv2d Op.(fluid.layers.** :ref:`api_fluid_layers_conv2d` ).
@ -176,7 +176,7 @@ def sequence_conv(input,
def sequence_softmax(input, use_cudnn=False, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Note**:
@ -260,7 +260,7 @@ def sequence_softmax(input, use_cudnn=False, name=None):
def sequence_pool(input, pool_type, is_test=False, pad_value=0.0):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Notes: The Op only receives LoDTensor as input. If your input is Tensor, please use pool2d Op.(fluid.layers.** :ref:`api_fluid_layers_pool2d` ).
@ -374,7 +374,7 @@ def sequence_pool(input, pool_type, is_test=False, pad_value=0.0):
@templatedoc()
def sequence_concat(input, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Notes: The Op only receives LoDTensor as input. If your input is Tensor, please use concat Op.(fluid.layers.** :ref:`api_fluid_layers_concat` ).
@ -435,7 +435,7 @@ def sequence_concat(input, name=None):
def sequence_first_step(input):
"""
:api_attr: Static Graph
:api_attr: Static Graph
This operator only supports LoDTensor as input. Given the input LoDTensor, it will
select first time-step feature of each sequence as output.
@ -489,7 +489,7 @@ def sequence_first_step(input):
def sequence_last_step(input):
"""
:api_attr: Static Graph
:api_attr: Static Graph
This operator only supports LoDTensor as input. Given the input LoDTensor, it will
select last time-step feature of each sequence as output.
@ -544,7 +544,7 @@ def sequence_last_step(input):
def sequence_slice(input, offset, length, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Sequence Slice Layer**
@ -632,7 +632,7 @@ def sequence_slice(input, offset, length, name=None):
def sequence_expand(x, y, ref_level=-1, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
Sequence Expand Layer. This layer will expand the input variable ``x`` \
according to specified level ``ref_level`` lod of ``y``. Please note that \
@ -768,7 +768,7 @@ def sequence_expand(x, y, ref_level=-1, name=None):
def sequence_expand_as(x, y, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
Sequence Expand As Layer. This OP will expand the input variable ``x`` \
according to the zeroth level lod of ``y``. Current implementation requires \
@ -815,7 +815,7 @@ def sequence_expand_as(x, y, name=None):
Args:
x (Variable): The input variable which is a Tensor or LoDTensor, with the \
dims ``[M, K]``. The data type should be float32, float64, int8, int32 \
dims ``[M, K]``. The data type should be float32, float64, int32 \
or int64.
y (Variable): The input variable which is a LoDTensor with 1-level lod.
name (str, optional): For detailed information, please refer \
@ -872,6 +872,9 @@ def sequence_expand_as(x, y, name=None):
"""
assert not in_dygraph_mode(), (
"sequence layer is not supported in dygraph mode yet.")
check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
'sequence_expand_as')
check_type(y, 'y', Variable, 'sequence_expand_as')
helper = LayerHelper('sequence_expand_as', input=x, **locals())
dtype = helper.input_dtype()
tmp = helper.create_variable_for_type_inference(dtype)
@ -885,7 +888,7 @@ def sequence_expand_as(x, y, name=None):
def sequence_pad(x, pad_value, maxlen=None, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
This layer padding the sequences in a same batch to a common length (according \
to ``maxlen``). The padding value is defined by ``pad_value``, and will be \
@ -999,7 +1002,7 @@ def sequence_pad(x, pad_value, maxlen=None, name=None):
def sequence_unpad(x, length, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Note**:
@ -1074,7 +1077,7 @@ def sequence_unpad(x, length, name=None):
def sequence_reshape(input, new_dim):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Notes: The Op only receives LoDTensor as input. If your input is Tensor, please use reshape Op.(fluid.layers.** :ref:`api_fluid_layers_reshape` ).
@ -1136,7 +1139,7 @@ def sequence_reshape(input, new_dim):
def sequence_scatter(input, index, updates, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**Note**:
@ -1226,7 +1229,7 @@ def sequence_scatter(input, index, updates, name=None):
def sequence_enumerate(input, win_size, pad_value=0, name=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
Generate a new sequence for the input index sequence with \
shape ``[d_1, win_size]``, which enumerates all the \

19
python/paddle/fluid/tests/unittests/sequence/test_sequence_expand_as.py
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@ -18,7 +18,9 @@ import unittest
import numpy as np
import sys
sys.path.append("../")
import paddle.fluid as fluid
from op_test import OpTest
from paddle.fluid import Program, program_guard
class TestSequenceExpandAs(OpTest):
@ -84,5 +86,22 @@ class TestSequenceExpandAsCase3(TestSequenceExpandAs):
self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)}
class TestSequenceExpandAsOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
# the input x must be Variable
x1 = np.random.random((2, 4)).astype("float32")
self.assertRaises(TypeError, fluid.layers.sequence_expand_as, x1)
# the dtype of input x must be float32, float64, int32 or int64
x2 = fluid.data(name='x2', shape=[None, 4], dtype="bool")
self.assertRaises(TypeError, fluid.layers.sequence_expand_as, x2)
# the input y must be Variable
x3 = fluid.data(name='x3', shape=[None, 4], dtype="float32")
y = np.random.random((2, 4)).astype("float32")
self.assertRaises(TypeError, fluid.layers.sequence_expand_as, x3, y)
if __name__ == '__main__':
unittest.main()

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