未验证 提交 8e555ba6 编写于 作者: L liu zhengxi 提交者: GitHub

OP(pad, pad2d, pad_constant_like) error message enhancement (#23882)

* enhance pad.* error message, test=develop
上级 19235e85
...@@ -466,34 +466,43 @@ class Pad2dOp : public framework::OperatorWithKernel { ...@@ -466,34 +466,43 @@ class Pad2dOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override { void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Pad2d");
"Input(X) of Pad2dOp should not be null."); OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Pad2d");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of Pad2dOp should not be null.");
auto x_dim = ctx->GetInputDim("X"); auto x_dim = ctx->GetInputDim("X");
PADDLE_ENFORCE_EQ(x_dim.size(), 4, PADDLE_ENFORCE_EQ(x_dim.size(), 4,
"The size of input(X)'s dimension should be equal to 4."); platform::errors::InvalidArgument(
"The size of Input(X)'s dimension should be equal to "
"4, but received %d. ",
x_dim.size()));
std::vector<int64_t> out_dims(x_dim.size()); std::vector<int64_t> out_dims(x_dim.size());
auto data_format = ctx->Attrs().Get<std::string>("data_format"); auto data_format = ctx->Attrs().Get<std::string>("data_format");
out_dims[0] = x_dim[0]; out_dims[0] = x_dim[0];
if (ctx->HasInput("Paddings")) { if (ctx->HasInput("Paddings")) {
auto paddings_dim = ctx->GetInputDim("Paddings"); auto paddings_dim = ctx->GetInputDim("Paddings");
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(paddings_dim.size(), 1,
paddings_dim.size(), 1, platform::errors::InvalidArgument(
"Size of Input(Paddings)'s dimension should be equal to 1."); "Size of Input(Paddings)'s dimension should be "
"equal to 1, but received %d.",
paddings_dim.size()));
if (ctx->IsRuntime()) { if (ctx->IsRuntime()) {
PADDLE_ENFORCE_EQ(paddings_dim[0], 4, PADDLE_ENFORCE_EQ(paddings_dim[0], 4,
"Shape of Input(Paddings) should be equal to [4]."); platform::errors::InvalidArgument(
"Shape of Input(Paddings) should be equal to "
"[4], but received [%d].",
paddings_dim[0]));
} }
out_dims[1] = x_dim[1]; out_dims[1] = x_dim[1];
out_dims[2] = x_dim[2]; out_dims[2] = x_dim[2];
out_dims[3] = x_dim[3]; out_dims[3] = x_dim[3];
} else { } else {
auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings"); auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
PADDLE_ENFORCE_EQ(paddings.size(), 4, PADDLE_ENFORCE_EQ(
"Size of paddings should be equal to 4."); paddings.size(), 4,
platform::errors::InvalidArgument(
"Size of paddings should be equal to 4, but received %d.",
static_cast<int>(paddings.size())));
if (data_format == "NCHW") { if (data_format == "NCHW") {
out_dims[1] = x_dim[1]; // channel out_dims[1] = x_dim[1]; // channel
out_dims[2] = ((!ctx->IsRuntime()) && (x_dim[2] < 0)) out_dims[2] = ((!ctx->IsRuntime()) && (x_dim[2] < 0))
...@@ -608,9 +617,10 @@ class Pad2dOpGrad : public framework::OperatorWithKernel { ...@@ -608,9 +617,10 @@ class Pad2dOpGrad : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override { void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null"); OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Pad2d@Grad");
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")), OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
"Input(Out@GRAD) should not be null"); framework::GradVarName("Out"), "Pad2d@Grad");
auto x_dims = ctx->GetInputDim("X"); auto x_dims = ctx->GetInputDim("X");
auto x_grad_name = framework::GradVarName("X"); auto x_grad_name = framework::GradVarName("X");
if (ctx->HasOutput(x_grad_name)) { if (ctx->HasOutput(x_grad_name)) {
......
...@@ -25,18 +25,19 @@ class PadConstantLikeOp : public framework::OperatorWithKernel { ...@@ -25,18 +25,19 @@ class PadConstantLikeOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *ctx) const override { void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "PadConstantLike");
"Input(X) of PadConstantLikeOp should not be null."); OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "PadConstantLike");
PADDLE_ENFORCE(ctx->HasInput("Y"), OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "PadConstantLike");
"Input(Y) of PadConstantLikeOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of PadConstantLikeOp should not be null.");
auto x_dim = ctx->GetInputDim("X"); auto x_dim = ctx->GetInputDim("X");
auto y_dim = ctx->GetInputDim("Y"); auto y_dim = ctx->GetInputDim("Y");
PADDLE_ENFORCE_EQ(x_dim.size(), y_dim.size(), PADDLE_ENFORCE_EQ(x_dim.size(), y_dim.size(),
"The dimension of X and Y should be the same."); platform::errors::InvalidArgument(
"The size of Input(X)'s dimension and the size of "
"Input(Y)'s dimension should be the same, but "
"received %d for Input(X) vs %d for Input(Y).",
x_dim.size(), y_dim.size()));
for (int i = 0; i < x_dim.size(); ++i) { for (int i = 0; i < x_dim.size(); ++i) {
if ((!ctx->IsRuntime()) && ((x_dim[i] == -1) || (y_dim[i] == -1))) { if ((!ctx->IsRuntime()) && ((x_dim[i] == -1) || (y_dim[i] == -1))) {
...@@ -44,8 +45,11 @@ class PadConstantLikeOp : public framework::OperatorWithKernel { ...@@ -44,8 +45,11 @@ class PadConstantLikeOp : public framework::OperatorWithKernel {
} else { } else {
PADDLE_ENFORCE_GE( PADDLE_ENFORCE_GE(
x_dim[i], y_dim[i], x_dim[i], y_dim[i],
"expected X_dim[i] >= Y_dim[i], but received %d < %d for dim %d", platform::errors::InvalidArgument(
x_dim[i], y_dim[i], i); "The size of each dimension of Input(X) expected to be greater "
"than or equal to size of corresponding dimension of Input(Y) "
"(X_dim[i] >= Y_dim[i]), but received %d < %d for dimension %d",
x_dim[i], y_dim[i], i));
} }
} }
...@@ -157,14 +161,20 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel { ...@@ -157,14 +161,20 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *ctx) const override { void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(Y) should not be null"); OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "PadConstantLike@Grad");
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")), OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
"Input(Out@GRAD) should not be null"); framework::GradVarName("Out"), "PadConstantLike@Grad");
auto y_dim = ctx->GetInputDim("Y"); auto y_dim = ctx->GetInputDim("Y");
auto dout_dim = ctx->GetInputDim(framework::GradVarName("Out")); auto dout_dim = ctx->GetInputDim(framework::GradVarName("Out"));
PADDLE_ENFORCE_EQ(dout_dim.size(), y_dim.size(), PADDLE_ENFORCE_EQ(
"The dimension of X and Y should be the same."); dout_dim.size(), y_dim.size(),
platform::errors::InvalidArgument(
"Op(PadConstantLike@Grad) the size of Input(Out@Grad)'s dimension "
"and the size of Input(Y)'s dimension should be the same, but "
"received %d for Input(Out@Grad) vs %d for Input(Y).",
dout_dim.size(), y_dim.size()));
auto y_grad_name = framework::GradVarName("Y"); auto y_grad_name = framework::GradVarName("Y");
if (ctx->HasOutput(y_grad_name)) { if (ctx->HasOutput(y_grad_name)) {
...@@ -175,10 +185,14 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel { ...@@ -175,10 +185,14 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel {
if ((!ctx->IsRuntime()) && ((dout_dim[i] == -1) || (y_dim[i] == -1))) { if ((!ctx->IsRuntime()) && ((dout_dim[i] == -1) || (y_dim[i] == -1))) {
continue; continue;
} else { } else {
PADDLE_ENFORCE_GE(dout_dim[i], y_dim[i], PADDLE_ENFORCE_GE(
"expected Out_dim[i] >= Y_dim[i], but received %d " dout_dim[i], y_dim[i],
"< %d for dim %d", platform::errors::InvalidArgument(
dout_dim[i], y_dim[i], i); "The size of each dimension of Input(Out@Grad) expected to "
"be greater than or equal to size of corresponding dimension "
"of Input(Y) (Out_dim[i] >= Y_dim[i]), but received %d < %d "
"for dimension %d",
dout_dim[i], y_dim[i], i));
} }
} }
} }
......
...@@ -25,17 +25,24 @@ class PadOp : public framework::OperatorWithKernel { ...@@ -25,17 +25,24 @@ class PadOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override { void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of PadOp should not be null."); OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Pad");
PADDLE_ENFORCE(ctx->HasOutput("Out"), OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Pad");
"Output(Out) of PadOp should not be null.");
auto x_dim = ctx->GetInputDim("X"); auto x_dim = ctx->GetInputDim("X");
auto& paddings = ctx->Attrs().Get<std::vector<int>>("paddings"); auto& paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
PADDLE_ENFORCE_EQ(x_dim.size() * 2, int64_t(paddings.size()), PADDLE_ENFORCE_EQ(
"Size of paddings should be equal to 2 * dimension size " static_cast<int>(paddings.size()), x_dim.size() * 2,
"of input tensor."); platform::errors::InvalidArgument(
"Size of 'paddings' dimension should be equal to 2 * size of "
"Input(X)'s dimension, but received (size of 'paddings' dimension "
"is) %d vs (2 * size of Input(X)'s dimension is) %d.",
static_cast<int>(paddings.size()), x_dim.size() * 2));
for (size_t i = 0; i < paddings.size(); ++i) { for (size_t i = 0; i < paddings.size(); ++i) {
PADDLE_ENFORCE_GE(paddings[i], 0, "paddings should >= 0."); PADDLE_ENFORCE_GE(paddings[i], 0,
platform::errors::InvalidArgument(
"The element of 'paddings' should >= 0, but "
"received %d for index %d.",
paddings[i], static_cast<int>(i)));
} }
std::vector<int64_t> out_dims(x_dim.size()); std::vector<int64_t> out_dims(x_dim.size());
for (int i = 0; i < x_dim.size(); ++i) { for (int i = 0; i < x_dim.size(); ++i) {
......
...@@ -6487,6 +6487,9 @@ def pad(x, paddings, pad_value=0., name=None): ...@@ -6487,6 +6487,9 @@ def pad(x, paddings, pad_value=0., name=None):
x = fluid.data(name='data', shape=[300, 300], dtype='float32') x = fluid.data(name='data', shape=[300, 300], dtype='float32')
out = fluid.layers.pad(x=x, paddings=[0, 1, 1, 2], pad_value=0.) out = fluid.layers.pad(x=x, paddings=[0, 1, 1, 2], pad_value=0.)
""" """
check_variable_and_dtype(
x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], "pad")
helper = LayerHelper('pad', input=x, **locals()) helper = LayerHelper('pad', input=x, **locals())
dtype = helper.input_dtype() dtype = helper.input_dtype()
out = helper.create_variable_for_type_inference(dtype) out = helper.create_variable_for_type_inference(dtype)
...@@ -6578,6 +6581,10 @@ def pad_constant_like(x, y, pad_value=0., name=None): ...@@ -6578,6 +6581,10 @@ def pad_constant_like(x, y, pad_value=0., name=None):
out = fluid.layers.pad_constant_like(x=x, y=y, pad_value=0.) out = fluid.layers.pad_constant_like(x=x, y=y, pad_value=0.)
# out is a rank 4 tensor variable, and out.shape = [2, 3 ,2 , 3] # out is a rank 4 tensor variable, and out.shape = [2, 3 ,2 , 3]
""" """
check_type(x, 'x', (Variable), 'pad_constant_like')
check_variable_and_dtype(y, 'y', ['float32', 'float64', 'int32', 'int64'],
"pad_constant_like")
helper = LayerHelper('pad_constant_like', input=x, **locals()) helper = LayerHelper('pad_constant_like', input=x, **locals())
dtype = helper.input_dtype() dtype = helper.input_dtype()
out = helper.create_variable_for_type_inference(dtype) out = helper.create_variable_for_type_inference(dtype)
...@@ -8862,6 +8869,9 @@ def pad2d(input, ...@@ -8862,6 +8869,9 @@ def pad2d(input,
data = fluid.data(name='data', shape=[None, 3, 32, 32], dtype='float32') data = fluid.data(name='data', shape=[None, 3, 32, 32], dtype='float32')
result = fluid.layers.pad2d(input=data, paddings=[0, 1, 2, 3], mode='reflect') result = fluid.layers.pad2d(input=data, paddings=[0, 1, 2, 3], mode='reflect')
""" """
check_variable_and_dtype(
input, 'input', ['float16', 'float32', 'float64', 'int32', 'int64'],
"pad2d")
if in_dygraph_mode(): if in_dygraph_mode():
_paddings = paddings.numpy().tolist() if isinstance( _paddings = paddings.numpy().tolist() if isinstance(
......
...@@ -15,6 +15,8 @@ ...@@ -15,6 +15,8 @@
import unittest import unittest
import numpy as np import numpy as np
from op_test import OpTest from op_test import OpTest
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
class TestPad2dOp(OpTest): class TestPad2dOp(OpTest):
...@@ -124,5 +126,20 @@ class TestCase7(TestPad2dOp): ...@@ -124,5 +126,20 @@ class TestCase7(TestPad2dOp):
self.variable_paddings = True self.variable_paddings = True
class TestPad2dOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
input_data = np.random.random((2, 2, 2, 2)).astype("float32")
def test_Variable():
fluid.layers.pad2d(input=input_data, paddings=[1, 1, 1, 1])
self.assertRaises(TypeError, test_Variable)
data = fluid.data(
name='data', shape=[None, 3, 20, 20], dtype='float16')
fluid.layers.pad2d(input=data, paddings=[1, 1, 1, 1])
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()
...@@ -17,9 +17,11 @@ from __future__ import print_function ...@@ -17,9 +17,11 @@ from __future__ import print_function
import unittest import unittest
import numpy as np import numpy as np
from op_test import OpTest from op_test import OpTest
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
class TestPadOp(OpTest): class TestPadConstantLikeOp(OpTest):
def setUp(self): def setUp(self):
self.initTestCase() self.initTestCase()
self.op_type = "pad_constant_like" self.op_type = "pad_constant_like"
...@@ -49,7 +51,7 @@ class TestPadOp(OpTest): ...@@ -49,7 +51,7 @@ class TestPadOp(OpTest):
self.paddings = [(0, 13), (0, 0)] self.paddings = [(0, 13), (0, 0)]
class TestCase1(TestPadOp): class TestCase1(TestPadConstantLikeOp):
def initTestCase(self): def initTestCase(self):
self.x_shape = (4, 3, 4, 5) self.x_shape = (4, 3, 4, 5)
self.y_shape = (2, 3, 4, 5) self.y_shape = (2, 3, 4, 5)
...@@ -57,7 +59,7 @@ class TestCase1(TestPadOp): ...@@ -57,7 +59,7 @@ class TestCase1(TestPadOp):
self.pad_value = 0.5 self.pad_value = 0.5
class TestCase2(TestPadOp): class TestCase2(TestPadConstantLikeOp):
def initTestCase(self): def initTestCase(self):
self.x_shape = (4, 3, 4, 10) self.x_shape = (4, 3, 4, 10)
self.y_shape = (2, 3, 2, 10) self.y_shape = (2, 3, 2, 10)
...@@ -65,5 +67,26 @@ class TestCase2(TestPadOp): ...@@ -65,5 +67,26 @@ class TestCase2(TestPadOp):
self.pad_value = 0.5 self.pad_value = 0.5
class TestPadConstantLikeOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
x_data = np.random.random((2, 2, 2, 2)).astype("float32")
y_data = np.random.random((2, 2, 2, 2)).astype("float32")
def test_Variable_x():
var_y = fluid.data(
name="data_y", shape=[2, 2, 2, 2], dtype="float32")
fluid.layers.pad_constant_like(x=x_data, y=var_y)
self.assertRaises(TypeError, test_Variable_x)
def test_Variable_y():
var_x = fluid.data(
name="data_x", shape=[2, 2, 2, 2], dtype="float32")
fluid.layers.pad_constant_like(x=var_x, y=y_data)
self.assertRaises(TypeError, test_Variable_y)
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()
...@@ -18,6 +18,8 @@ import unittest ...@@ -18,6 +18,8 @@ import unittest
import numpy as np import numpy as np
from op_test import OpTest from op_test import OpTest
import paddle.fluid.core as core import paddle.fluid.core as core
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
class TestPadOp(OpTest): class TestPadOp(OpTest):
...@@ -95,5 +97,20 @@ create_test_fp16(TestCase1) ...@@ -95,5 +97,20 @@ create_test_fp16(TestCase1)
create_test_fp16(TestCase2) create_test_fp16(TestCase2)
create_test_fp16(TestCase3) create_test_fp16(TestCase3)
class TestPadOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
input_data = np.random.random((2, 2)).astype("float32")
def test_Variable():
fluid.layers.pad(x=input_data, paddings=[1, 1, 1, 1])
self.assertRaises(TypeError, test_Variable)
data = fluid.data(name='data', shape=[4], dtype='float16')
fluid.layers.pad(x=data, paddings=[0, 1])
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()
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