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fix error log, test=develop (#24419)

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* fix error log: resahpe, range, reverse.
release/2.0-alpha
mapingshuo 6 years ago committed by GitHub
parent 8b88cd5167
commit d1bb76a2f7
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GPG Key ID: 4AEE18F83AFDEB23
9 changed files with 120 additions and 38 deletions
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38
paddle/fluid/operators/range_op.cc
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@ -24,18 +24,44 @@ class RangeOp : public framework::OperatorWithKernel {
void InferShape(framework::InferShapeContext *ctx) const override {
if (ctx->HasInput("Start")) {
auto s_dims = ctx->GetInputDim("Start");
PADDLE_ENFORCE((s_dims.size() == 1) && (s_dims[0] == 1),
"The shape of Input(Start) should be [1].");
PADDLE_ENFORCE_EQ(
s_dims.size(), 1,
platform::errors::InvalidArgument(
"The dim of the shape of Input(Start) should be 1, but got %d",
s_dims.size()));
PADDLE_ENFORCE_EQ(s_dims[0], 1,
platform::errors::InvalidArgument(
"The first dim of the shape of Input(Start) should "
"be 1, but got %d",
s_dims[0]));
}
if (ctx->HasInput("End")) {
auto e_dims = ctx->GetInputDim("End");
PADDLE_ENFORCE((e_dims.size() == 1) && (e_dims[0] == 1),
"The shape of Input(End) should be [1].");
PADDLE_ENFORCE_EQ(
e_dims.size(), 1,
platform::errors::InvalidArgument(
"The dim of the shape of Input(End) should be 1, but got %d",
e_dims.size()));
PADDLE_ENFORCE_EQ(e_dims[0], 1, platform::errors::InvalidArgument(
"The first dim of the shape of "
"Input(End) should be 1, but got %d",
e_dims[0]));
}
if (ctx->HasInput("Step")) {
auto step_dims = ctx->GetInputDim("Step");
PADDLE_ENFORCE((step_dims.size() == 1) && (step_dims[0] == 1),
"The shape of Input(Step) should be [1].");
PADDLE_ENFORCE_EQ(
step_dims.size(), 1,
platform::errors::InvalidArgument(
"The dim of the shape of Input(Step) should be 1, but got %d",
step_dims.size()));
PADDLE_ENFORCE_EQ(step_dims[0], 1,
platform::errors::InvalidArgument(
"The first dim of the shape of Input(Step) should "
"be 1, but got %d",
step_dims[0]));
}
ctx->SetOutputDim("Out", {-1});
}

20
paddle/fluid/operators/range_op.h
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@ -22,11 +22,21 @@ namespace operators {
template <typename T>
void GetSize(T start, T end, T step, int64_t* size) {
PADDLE_ENFORCE(!std::equal_to<T>()(step, 0),
"The step of range op should not be 0.");
PADDLE_ENFORCE(((start < end) && (step > 0)) || ((start > end) && (step < 0)),
"The step should be greater than 0 while start < end. And the "
"step should be less than 0 while start > end.");
PADDLE_ENFORCE_NE(step, 0, platform::errors::InvalidArgument(
"The step of range op should not be 0."));
if (start < end) {
PADDLE_ENFORCE_GT(
step, 0, platform::errors::InvalidArgument(
"The step should be greater than 0 while start < end."));
}
if (start > end) {
PADDLE_ENFORCE_LT(step, 0,
platform::errors::InvalidArgument(
"step should be less than 0 while start > end."));
}
*size = std::is_integral<T>::value
? ((std::abs(end - start) + std::abs(step) - 1) / std::abs(step))
: std::ceil(std::abs((end - start) / step));

28
paddle/fluid/operators/reshape_op.cc
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@ -56,9 +56,11 @@ class ReshapeOp : public framework::OperatorWithKernel {
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(ctx->HasInput("X"), true,
"Input(X) of ReshapeOp should not be null.");
platform::errors::InvalidArgument(
"Input(X) of ReshapeOp should not be null."));
PADDLE_ENFORCE_EQ(ctx->HasOutput("Out"), true,
"Output(Out) of ReshapeOp should not be null.");
platform::errors::InvalidArgument(
"Output(Out) of ReshapeOp should not be null."));
if (ctx->HasInputs("ShapeTensor")) {
// top prority shape
@ -304,9 +306,12 @@ class ReshapeGradOp : public framework::OperatorWithKernel {
: OperatorWithKernel(type, inputs, outputs, attrs) {}
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(ctx->HasInput("X"), true, "Input(X) shouldn't be null.");
PADDLE_ENFORCE_EQ(
ctx->HasInput("X"), true,
platform::errors::InvalidArgument("Input(X) shouldn't be null."));
PADDLE_ENFORCE_EQ(ctx->HasInput(framework::GradVarName("Out")), true,
"Input(Out@GRAD) shouldn't be null.");
platform::errors::InvalidArgument(
"Input(Out@GRAD) shouldn't be null."));
ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
}
@ -403,7 +408,8 @@ class Reshape2Op : public ReshapeOp {
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(ctx->HasOutput("XShape"), true,
"Output(XShape) of ReshapeOp should not be null.");
platform::errors::InvalidArgument(
"Output(XShape) of ReshapeOp should not be null."));
const auto &x_dims = ctx->GetInputDim("X");
std::vector<int64_t> xshape_dims(x_dims.size() + 1);
xshape_dims[0] = 0;
@ -472,10 +478,12 @@ class Reshape2GradOp : public framework::OperatorWithKernel {
: OperatorWithKernel(type, inputs, outputs, attrs) {}
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(ctx->HasInput("XShape"), true,
"Input(XShape) shouldn't be null.");
PADDLE_ENFORCE_EQ(
ctx->HasInput("XShape"), true,
platform::errors::InvalidArgument("Input(XShape) shouldn't be null."));
PADDLE_ENFORCE_EQ(ctx->HasInput(framework::GradVarName("Out")), true,
"Input(Out@GRAD) shouldn't be null.");
platform::errors::InvalidArgument(
"Input(Out@GRAD) shouldn't be null."));
auto xshape_dims = ctx->GetInputDim("XShape");
auto x_dims = framework::slice_ddim(xshape_dims, 1, xshape_dims.size());
ctx->SetOutputDim(framework::GradVarName("X"), x_dims);
@ -511,8 +519,8 @@ class Reshape2DoubleGradOp : public framework::OperatorWithKernel {
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(ctx->HasInput("DDX"), true,
"Input(X@GRAD_GRAD) shouldn't be null.");
platform::errors::InvalidArgument(
"Input(X@GRAD_GRAD) shouldn't be null."));
if (ctx->HasOutput("DDOut") && ctx->HasInput("DDX")) {
ctx->ShareDim("DOut", "DDOut");
}

18
paddle/fluid/operators/reverse_op.cc
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@ -24,20 +24,28 @@ class ReverseOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null");
PADDLE_ENFORCE_EQ(
ctx->HasInput("X"), true,
platform::errors::InvalidArgument("Input(X) should not be null"));
PADDLE_ENFORCE_EQ(
ctx->HasOutput("Out"), true,
platform::errors::InvalidArgument("Output(Out) should not be null"));
const auto& x_dims = ctx->GetInputDim("X");
const auto& axis = ctx->Attrs().Get<std::vector<int>>("axis");
PADDLE_ENFORCE(!axis.empty(), "'axis' can not be empty.");
PADDLE_ENFORCE_NE(axis.empty(), true, platform::errors::InvalidArgument(
"'axis' can not be empty."));
for (int a : axis) {
PADDLE_ENFORCE_LT(a, x_dims.size(),
paddle::platform::errors::OutOfRange(
"The axis must be less than input tensor's rank."));
"The axis must be less than input tensor's rank. "
"but got %d >= %d",
a, x_dims.size()));
PADDLE_ENFORCE_GE(
a, -x_dims.size(),
paddle::platform::errors::OutOfRange(
"The axis must be greater than the negative number of "
"input tensor's rank."));
"input tensor's rank, but got %d < %d",
a, -x_dims.size()));
}
ctx->SetOutputDim("Out", x_dims);
}

6
paddle/fluid/operators/reverse_op.h
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@ -80,9 +80,9 @@ class ReverseKernel : public framework::OpKernel<T> {
functor6(dev_ctx, *x, out, axis);
break;
default:
PADDLE_THROW(
"Reserve operator doesn't supports tensors whose ranks are greater "
"than 6.");
PADDLE_THROW(paddle::platform::errors::OutOfRange(
"The reserve operator does not support input tensors"
"whose ranks are greater than 6."));
}
}
};

10
paddle/fluid/operators/shape_op.cc
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@ -24,10 +24,12 @@ class ShapeOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Input"),
"Input (Input) of get_shape op should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output (Out) of get_shape op should not be null.");
PADDLE_ENFORCE_EQ(ctx->HasInput("Input"), true,
platform::errors::InvalidArgument(
"Input (Input) of get_shape op should not be null."));
PADDLE_ENFORCE_EQ(ctx->HasOutput("Out"), true,
platform::errors::InvalidArgument(
"Output (Out) of get_shape op should not be null."));
auto in_dim = ctx->GetInputDim("Input");
ctx->SetOutputDim("Out", {in_dim.size()});
}

3
python/paddle/fluid/layers/nn.py
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@ -10798,7 +10798,8 @@ def shape(input):
res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output])
print(res) # [array([ 3, 100, 100], dtype=int32)]
"""
check_variable_and_dtype(input, 'input',
['float32', 'float64', 'int32', 'int64'], 'shape')
helper = LayerHelper('shape', **locals())
out = helper.create_variable_for_type_inference(dtype='int32')
helper.append_op(

6
python/paddle/fluid/layers/tensor.py
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@ -1081,6 +1081,9 @@ def reverse(x, axis):
result1 = fluid.layers.reverse(data, 0) # [[6., 7., 8.], [3., 4., 5.], [0., 1., 2.]]
result2 = fluid.layers.reverse(data, [0, 1]) # [[8., 7., 6.], [5., 4., 3.], [2., 1., 0.]]
"""
check_variable_and_dtype(
x, 'x', ('float32', 'float64', 'int32', 'int64', 'uint8'), 'reverse')
check_type(axis, 'axis', (int, tuple, list), 'reverse')
if isinstance(axis, int):
axis = [axis]
helper = LayerHelper("reverse", **locals())
@ -1276,6 +1279,9 @@ def range(start, end, step, dtype):
data = fluid.layers.range(0, 10, 2, 'int32')
"""
check_type(start, 'start', (float, int, Variable), 'range')
check_type(end, 'end', (float, int, Variable), 'range')
check_type(step, 'step', (float, int, Variable), 'range')
helper = LayerHelper("range", **locals())
check_dtype(dtype, 'create data type',

29
python/paddle/fluid/tests/unittests/test_reverse_op.py
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@ -17,6 +17,8 @@ from __future__ import print_function
import unittest
import numpy as np
from op_test import OpTest
import paddle.fluid as fluid
from paddle.fluid import core
class TestReverseOp(OpTest):
@ -47,7 +49,7 @@ class TestCase0(TestReverseOp):
self.axis = [1]
class TestCase0(TestReverseOp):
class TestCase0_neg(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 40)).astype('float64')
self.axis = [-1]
@ -59,7 +61,7 @@ class TestCase1(TestReverseOp):
self.axis = [0, 1]
class TestCase0(TestReverseOp):
class TestCase1_neg(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 40)).astype('float64')
self.axis = [0, -1]
@ -71,7 +73,7 @@ class TestCase2(TestReverseOp):
self.axis = [0, 2]
class TestCase2(TestReverseOp):
class TestCase2_neg(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 4, 10)).astype('float64')
self.axis = [0, -2]
@ -83,11 +85,30 @@ class TestCase3(TestReverseOp):
self.axis = [1, 2]
class TestCase3(TestReverseOp):
class TestCase3_neg(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 4, 10)).astype('float64')
self.axis = [-1, -2]
class TestCase4(unittest.TestCase):
def test_error(self):
place = fluid.CPUPlace()
exe = fluid.Executor(place)
train_program = fluid.Program()
startup_program = fluid.Program()
with fluid.program_guard(train_program, startup_program):
label = fluid.layers.data(
name="label", shape=[1, 1, 1, 1, 1, 1, 1, 1], dtype="int64")
rev = fluid.layers.reverse(label, axis=[-1, -2])
def _run_program():
x = np.random.random(size=(10, 1, 1, 1, 1, 1, 1)).astype('int64')
exe.run(train_program, feed={"label": x})
self.assertRaises(core.EnforceNotMet, _run_program)
if __name__ == '__main__':
unittest.main()

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