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Add support for tuple of concat Op test=develop (#25800)

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revert-24895-update_cub
wangchaochaohu 5 years ago committed by GitHub
parent e5514935cb
commit ff717d5158
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 47 additions and 44 deletions
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2
paddle/fluid/operators/concat_op.cc
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@ -207,6 +207,7 @@ REGISTER_OPERATOR(concat_grad, ops::ConcatOpGrad,
REGISTER_OP_CPU_KERNEL(
concat, ops::ConcatKernel<paddle::platform::CPUDeviceContext, double>,
ops::ConcatKernel<paddle::platform::CPUDeviceContext, float>,
ops::ConcatKernel<paddle::platform::CPUDeviceContext, bool>,
ops::ConcatKernel<paddle::platform::CPUDeviceContext, int64_t>,
ops::ConcatKernel<paddle::platform::CPUDeviceContext,
paddle::platform::float16>,
@ -215,6 +216,7 @@ REGISTER_OP_CPU_KERNEL(
concat_grad,
ops::ConcatGradKernel<paddle::platform::CPUDeviceContext, double>,
ops::ConcatGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::ConcatGradKernel<paddle::platform::CPUDeviceContext, bool>,
ops::ConcatGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
ops::ConcatGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::float16>,

2
paddle/fluid/operators/concat_op.cu.cc
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@ -20,6 +20,7 @@ namespace plat = paddle::platform;
REGISTER_OP_CUDA_KERNEL(
concat, ops::ConcatKernel<paddle::platform::CUDADeviceContext, double>,
ops::ConcatKernel<paddle::platform::CUDADeviceContext, float>,
ops::ConcatKernel<paddle::platform::CUDADeviceContext, bool>,
ops::ConcatKernel<paddle::platform::CUDADeviceContext, plat::float16>,
ops::ConcatKernel<paddle::platform::CUDADeviceContext, int64_t>,
ops::ConcatKernel<paddle::platform::CUDADeviceContext, int>);
@ -27,6 +28,7 @@ REGISTER_OP_CUDA_KERNEL(
concat_grad,
ops::ConcatGradKernel<paddle::platform::CUDADeviceContext, double>,
ops::ConcatGradKernel<paddle::platform::CUDADeviceContext, float>,
ops::ConcatGradKernel<paddle::platform::CUDADeviceContext, bool>,
ops::ConcatGradKernel<paddle::platform::CUDADeviceContext, plat::float16>,
ops::ConcatGradKernel<paddle::platform::CUDADeviceContext, int64_t>,
ops::ConcatGradKernel<paddle::platform::CUDADeviceContext, int>);

2
python/paddle/fluid/framework.py
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@ -1958,7 +1958,7 @@ class Operator(object):
in_proto.name)
if found:
in_args = inputs[in_proto.name]
if not isinstance(in_args, list):
if not isinstance(in_args, (list, tuple)):
in_args = [in_args]
if not in_proto.duplicable and len(in_args) > 1:
raise ValueError(

53
python/paddle/fluid/layers/tensor.py
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@ -266,8 +266,8 @@ def concat(input, axis=0, name=None):
This OP concatenates the input along the axis.
Args:
input(list): List of input Tensors with data type float16, float32, float64, int32,
int64. All the Tensors in ``input`` must have the same data type.
input(list|tuple|Tensor): ``input`` can be Tensor, Tensor list or Tensor tuple which is with data type
bool, float16, float32, float64, int32, int64. All the Tensors in ``input`` must have the same data type.
axis(int|Tensor, optional): Specify the axis to operate on the input Tensors.
It's a scalar with data type int or a Tensor with shape [1] and data type int32 or int64.
The effective range is [-R, R), where R is Rank(x). When ``axis < 0``, it works the same way
@ -276,7 +276,8 @@ def concat(input, axis=0, name=None):
need for user to set this property. For more information, please
refer to :ref:`api_guide_Name`.
Raises:
TypeError: The dtype of ``input`` must be one of float16, float32, float64, int32 and int64.
TypeError: ``input`` must be one of list, tuple or Tensor.
TypeError: The data type of ``input`` must be one of bool, float16, float32, float64, int32 and int64.
TypeError: The ``axis`` must be int or Tensor. The dtype of ``axis`` must be int32 or int64 when it's a Tensor.
TypeError: All the Tensors in ``input`` must have the same data type.
@ -289,20 +290,20 @@ def concat(input, axis=0, name=None):
import paddle.fluid as fluid
import numpy as np
in1 = np.array([[1,2,3],
[4,5,6]])
in2 = np.array([[11,12,13],
[14,15,16]])
in3 = np.array([[21,22],
[23,24]])
in1 = np.array([[1, 2, 3],
[4, 5, 6]])
in2 = np.array([[11, 12, 13],
[14, 15, 16]])
in3 = np.array([[21, 22],
[23, 24]])
with fluid.dygraph.guard():
x1 = fluid.dygraph.to_variable(in1)
x2 = fluid.dygraph.to_variable(in2)
x3 = fluid.dygraph.to_variable(in3)
# When the axis is negative, the real axis is (axis + Rank(x)).
# As follows, axis is -1, Rank(x) is 2, the real axis is 1
out1 = fluid.layers.concat(input=[x1,x2,x3], axis=-1)
out2 = fluid.layers.concat(input=[x1,x2], axis=0)
out1 = fluid.layers.concat(input=[x1, x2, x3], axis=-1)
out2 = fluid.layers.concat(input=[x1, x2], axis=0)
print(out1.numpy())
# [[ 1 2 3 11 12 13 21 22]
# [ 4 5 6 14 15 16 23 24]]
@ -319,18 +320,18 @@ def concat(input, axis=0, name=None):
axis = axis[0]
return core.ops.concat(input, 'axis', axis)
if not isinstance(input, list):
warnings.warn(
"The type of input in concat should be list, but received %s." %
(type(input)))
check_type(input, 'input', (list, tuple, Variable), 'concat')
if not isinstance(input, Variable):
for id, x in enumerate(input):
check_variable_and_dtype(
x, 'input[' + str(id) + ']',
['bool', 'float16', 'float32', 'float64', 'int32', 'int64'],
'concat')
if x.dtype != input[0].dtype:
raise TypeError(
"All the Tensors in the input must have the same data type.")
else:
input = [input]
for id, x in enumerate(input):
check_variable_and_dtype(
x, 'input[' + str(id) + ']',
['float16', 'float32', 'float64', 'int32', 'int64'], 'concat')
if x.dtype != input[0].dtype:
raise TypeError(
"All the Tensors in the input must have the same data type.")
check_type(axis, 'axis', (int, Variable), 'concat')
if isinstance(axis, Variable):
@ -343,7 +344,7 @@ def concat(input, axis=0, name=None):
if input[0].desc.type() == core.VarDesc.VarType.LOD_TENSOR_ARRAY:
assert len(input) == 1, "If the elements of 'input' in concat are Variable(LoDTensorArray), " \
"number of the elements must be 1, but received %s." % len(x)
"number of the elements must be 1, but received %s." % len(input)
out_index = helper.create_variable_for_type_inference(dtype="int32")
helper.append_op(
type='tensor_array_to_tensor',
@ -1045,8 +1046,7 @@ def ones(shape, dtype, force_cpu=False):
Returns:
Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 1.
Raises:
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64 and None
and the data type of out Tensor must be the same as the dtype.
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64.
TypeError: The ``shape`` must be one of list, tuple and Tensor. The data type of ``shape`` must
be int32 or int64 when it's a Tensor.
@ -1082,8 +1082,7 @@ def zeros(shape, dtype, force_cpu=False, name=None):
Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 0.
Raises:
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64 and None
and the data type of out Tensor must be the same as the dtype.
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64.
TypeError: The ``shape`` must be one of list, tuple and Tensor. The data type of ``shape`` must
be int32 or int64 when it's a Tensor.
Examples:

6
python/paddle/tensor/creation.py
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@ -136,8 +136,7 @@ def ones(shape, dtype=None, name=None):
Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 1.
Raises:
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64 and None
and the data type of out Tensor must be the same as the dtype.
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64 and None.
TypeError: The ``shape`` must be one of list, tuple and Tensor. The data type of ``shape`` must
be int32 or int64 when it's a Tensor.
@ -229,8 +228,7 @@ def zeros(shape, dtype=None, name=None):
Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 0.
Raises:
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64 and None
and the data type of out Tensor must be the same as the dtype.
TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64 and None.
TypeError: The ``shape`` must be one of list, tuple and Tensor. The data type of ``shape`` must
be int32 or int64 when it's a Tensor.

26
python/paddle/tensor/manipulation.py
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@ -59,8 +59,8 @@ def concat(x, axis=0, name=None):
This OP concatenates the input along the axis.
Args:
x(list): List of input Tensors with data type float16, float32, float64, int32, int64.
All the Tensors in ``x`` must have same data type.
x(list|tuple): ``x`` is a Tensor list or Tensor tuple which is with data type bool, float16,
float32, float64, int32, int64. All the Tensors in ``x`` must have same data type.
axis(int|Tensor, optional): Specify the axis to operate on the input Tensors.
It's a scalar with data type int or a Tensor with shape [1] and data type int32
or int64. The effective range is [-R, R), where R is Rank(x). When ``axis < 0``,
@ -69,7 +69,8 @@ def concat(x, axis=0, name=None):
need for user to set this property. For more information, please
refer to :ref:`api_guide_Name`.
Raises:
TypeError: The dtype of ``x`` must be one of float16, float32, float64, int32 and int64.
TypeError: ``x`` must be list or tuple.
TypeError: The data type of ``x`` must be one of bool, float16, float32, float64, int32 and int64.
TypeError: The ``axis`` must be int or Tensor. The dtype of ``axis`` must be int32 or int64 when it's a Tensor.
TypeError: All the Tensors in ``x`` must have the same data type.
@ -83,21 +84,21 @@ def concat(x, axis=0, name=None):
import numpy as np
paddle.enable_imperative() # Now we are in imperative mode
in1 = np.array([[1,2,3],
[4,5,6]])
in2 = np.array([[11,12,13],
[14,15,16]])
in3 = np.array([[21,22],
[23,24]])
in1 = np.array([[1, 2, 3],
[4, 5, 6]])
in2 = np.array([[11, 12, 13],
[14, 15, 16]])
in3 = np.array([[21, 22],
[23, 24]])
x1 = paddle.imperative.to_variable(in1)
x2 = paddle.imperative.to_variable(in2)
x3 = paddle.imperative.to_variable(in3)
zero = paddle.full(shape=[1], dtype='int32', fill_value=0)
# When the axis is negative, the real axis is (axis + Rank(x))
# As follow, axis is -1, Rank(x) is 2, the real axis is 1
out1 = paddle.concat(x=[x1,x2,x3], axis=-1)
out2 = paddle.concat(x=[x1,x2], axis=0)
out3 = paddle.concat(x=[x1,x2], axis=zero)
out1 = paddle.concat(x=[x1, x2, x3], axis=-1)
out2 = paddle.concat(x=[x1, x2], axis=0)
out3 = paddle.concat(x=[x1, x2], axis=zero)
# out1
# [[ 1 2 3 11 12 13 21 22]
# [ 4 5 6 14 15 16 23 24]]
@ -107,6 +108,7 @@ def concat(x, axis=0, name=None):
# [11 12 13]
# [14 15 16]]
"""
check_type(x, 'x', (list, tuple), 'concat')
return paddle.fluid.layers.concat(input=x, axis=axis, name=name)

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