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fix error message for elementwise_add/mul (#20283)

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revert-20712-fix_depthwise_conv
danleifeng 6 years ago committed by Tao Luo
parent 670937e11d
commit 3a0f93b3f9
5 changed files with 104 additions and 11 deletions
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32
paddle/fluid/operators/elementwise/elementwise_op.h
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@ -52,14 +52,25 @@ class ElementwiseOp : public framework::OperatorWithKernel {
framework::proto::VarType::LOD_TENSOR) {
auto x_dim = ctx->GetInputDim("X");
auto y_dim = ctx->GetInputDim("Y");
PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(),
"Rank of first input must >= rank of second input.");
PADDLE_ENFORCE_GE(
x_dim.size(), y_dim.size(),
"ShapeError: the dimension of input X must greater than or equal to "
"the one of input Y. But received: the shape of input X = [%s], the "
"dimension of input X = %d, the shape of input Y = [%s], the "
"dimension of input Y = %d",
x_dim, x_dim.size(), y_dim, y_dim.size());
} else if (ctx->GetInputsVarType("X").front() ==
framework::proto::VarType::SELECTED_ROWS) {
PADDLE_ENFORCE((ctx->GetInputDim("Y").size() == 1u) &&
(ctx->GetInputDim("Y")[0] == 1),
"For elementwise_op, if X is Sparse, "
"Y must be scalar.");
PADDLE_ENFORCE_EQ(
ctx->GetInputDim("Y").size(), 1u,
"ShapeError: For elementwise_op, if X is Sparse(VarType.SELECTED_ROWS"
"), Y must be scalar. But reveived the dimension of Y = %s",
ctx->GetInputDim("Y").size());
PADDLE_ENFORCE_EQ(
ctx->GetInputDim("Y")[0], 1,
"ShapeError: For elementwise_op, if X is Sparse(VarType.SELECTED_ROWS"
"), Y must be scalar. But reveived the first dimension of Y = %s",
ctx->GetInputDim("Y")[0]);
} else {
PADDLE_THROW("X's type[%s] is not supported by elementwise_op.",
ctx->GetInputsVarType("X").front());
@ -203,8 +214,13 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
auto x_dims = ctx->GetInputDim(out_grad_name);
auto y_dims = ctx->GetInputDim("Y");
PADDLE_ENFORCE_GE(x_dims.size(), y_dims.size(),
"Rank of first input must >= rank of second input.");
PADDLE_ENFORCE_GE(
x_dims.size(), y_dims.size(),
"ShapeError: the dimension of Out@GRAD must greater than or equal to "
"the one of input Y. But received: the shape of Out@GRAD = [%s], the "
"dimension of Out@GRAD = %d, the shape of input Y = [%s], the "
"dimension of of input Y = %d",
x_dims, x_dims.size(), y_dims, y_dims.size());
auto x_grad_name = framework::GradVarName("X");
auto y_grad_name = framework::GradVarName("Y");

16
paddle/fluid/operators/elementwise/elementwise_op_function.h
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@ -71,7 +71,12 @@ inline void get_mid_dims(const framework::DDim &x_dims,
// only support single y_dims[i] = 1 now.
PADDLE_ENFORCE_EQ(*mid_flag, 0,
"Broadcast support y_dims with single 1.");
PADDLE_ENFORCE_EQ(y_dims[i], 1, "Broadcast dimension mismatch.");
PADDLE_ENFORCE_EQ(y_dims[i], 1,
"ShapeError: broadcast dimension mismatch. Operands "
"could not be broadcast together with the shape of "
"X = [%s] and the shape of Y = [%s]. Received [%d] "
"in X is not equal to [%d] in Y",
x_dims, y_dims, x_dims[i + axis], y_dims[i]);
// m*n*k m*1*k
for (int j = 0; j < i; ++j) {
(*pre) *= y_dims[j];
@ -823,8 +828,13 @@ void ElementwiseComputeEx(const framework::ExecutionContext &ctx,
x, y, z, ctx.template device_context<DeviceContext>(), func);
auto x_dims = x->dims();
auto y_dims_untrimed = y->dims();
PADDLE_ENFORCE_GE(x_dims.size(), y_dims_untrimed.size(),
"Rank of first input must >= rank of second input.");
PADDLE_ENFORCE_GE(
x_dims.size(), y_dims_untrimed.size(),
"ShapeError: the dimension of input X must greater than or equal to "
"the one of input Y. But received: the shape of input X = [%s], the "
"dimension of input X = %d, the shape of input Y = [%s], the dimension "
"of of input Y = %d",
x_dims, x_dims.size(), y_dims_untrimed, y_dims_untrimed.size());
if (x_dims == y_dims_untrimed) {
functor.Run();
return;

29
python/paddle/fluid/layers/nn.py
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@ -12553,6 +12553,35 @@ def _elementwise_op(helper):
assert x is not None, 'x cannot be None in {}'.format(op_type)
assert y is not None, 'y cannot be None in {}'.format(op_type)
if not isinstance(x, Variable):
raise TypeError(
"The type of 'x' in %s must be Variable, but received %s" %
(op_type, type(x)))
if not isinstance(y, Variable):
raise TypeError(
"The type of 'y' in %s must be Variable, but received %s" %
(op_type, type(y)))
if convert_dtype(x.dtype) in ['float16']:
warnings.warn(
"The data type of 'x' in batch_norm only support float16 on GPU now."
)
if convert_dtype(y.dtype) in ['float16']:
warnings.warn(
"The data type of 'y' in batch_norm only support float16 on GPU now."
)
if convert_dtype(x.dtype) not in [
'float16', 'float32', 'float64', 'int32', 'int64'
]:
raise TypeError(
"The data type of 'x' in batch_norm must be float16 or float32 or float64 or int32 or int64, but received %s."
% (convert_dtype(x.dtype)))
if convert_dtype(y.dtype) not in [
'float16', 'float32', 'float64', 'int32', 'int64'
]:
raise TypeError(
"The data type of 'y' in batch_norm must be float16 or float32 or float64 or int32 or int64, but received %s."
% (convert_dtype(y.dtype)))
axis = helper.kwargs.get('axis', -1)
use_mkldnn = helper.kwargs.get('use_mkldnn', False)
name = helper.kwargs.get('name', None)

19
python/paddle/fluid/tests/unittests/test_elementwise_add_op.py
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@ -17,6 +17,8 @@ import unittest
import numpy as np
import paddle.fluid.core as core
from op_test import OpTest
import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard
class TestElementwiseAddOp(OpTest):
@ -306,5 +308,22 @@ class TestFP16ElementwiseAddOp_channelwise_add(TestFP16ElementwiseAddOp):
self.axis = -1
class TestElementwiseAddOpError(OpTest):
def test_errors(self):
with program_guard(Program(), Program()):
# the input of elementwise_add must be Variable.
x1 = fluid.create_lod_tensor(
np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
y1 = fluid.create_lod_tensor(
np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
self.assertRaises(TypeError, fluid.layers.elementwise_add, x1, y1)
# the input dtype of elementwise_add must be float16 or float32 or float64 or int32 or int64
# float16 only can be set on GPU place
x2 = fluid.layers.data(name='x2', shape=[3, 4, 5, 6], dtype="uint8")
y2 = fluid.layers.data(name='y2', shape=[3, 4, 5, 6], dtype="uint8")
self.assertRaises(TypeError, fluid.layers.elementwise_add, x2, y2)
if __name__ == '__main__':
unittest.main()

19
python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py
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@ -18,6 +18,8 @@ import numpy as np
from op_test import OpTest
import paddle.fluid.core as core
from paddle.fluid.op import Operator
import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard
class ElementwiseMulOp(OpTest):
@ -160,5 +162,22 @@ class TestElementwiseMulOpFp16(ElementwiseMulOp):
self.dtype = np.float16
class TestElementwiseMulOpError(OpTest):
def test_errors(self):
with program_guard(Program(), Program()):
# the input of elementwise_mul must be Variable.
x1 = fluid.create_lod_tensor(
np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
y1 = fluid.create_lod_tensor(
np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
self.assertRaises(TypeError, fluid.layers.elementwise_mul, x1, y1)
# the input dtype of elementwise_mul must be float16 or float32 or float64 or int32 or int64
# float16 only can be set on GPU place
x2 = fluid.layers.data(name='x2', shape=[3, 4, 5, 6], dtype="uint8")
y2 = fluid.layers.data(name='y2', shape=[3, 4, 5, 6], dtype="uint8")
self.assertRaises(TypeError, fluid.layers.elementwise_mul, x2, y2)
if __name__ == '__main__':
unittest.main()

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