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1 change: 1 addition & 0 deletions paddle/fluid/API.spec
Original file line number Diff line number Diff line change
Expand Up @@ -252,6 +252,7 @@ paddle.fluid.layers.reverse ArgSpec(args=['x', 'axis'], varargs=None, keywords=N
paddle.fluid.layers.has_inf ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.has_nan ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.isfinite ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.range ArgSpec(args=['start', 'end', 'step', 'dtype'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.While.__init__ ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.While.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.Switch.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
Expand Down
69 changes: 69 additions & 0 deletions paddle/fluid/operators/range_op.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,69 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/fluid/operators/range_op.h"

namespace paddle {
namespace operators {

class RangeOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::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].");
}
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].");
}
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].");
}
ctx->SetOutputDim("Out", {-1});
}
};

class RangeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("Start",
"Start of interval. The interval includes this value. It is a "
"tensor with shape=[1].");
AddInput("End",
"End of interval. The interval does not include this value, "
"except in some cases where step is not an integer and floating "
"point round-off affects the length of out. It is a tensor with "
"shape=[1].");
AddInput("Step", "Spacing between values. It is a tensor with shape=[1].");
AddOutput("Out", "A sequence of numbers.");
AddComment(R"DOC(
Return evenly spaced values within a given interval. Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop). Like arange function of numpy.
)DOC");
}
};
} // namespace operators
} // namespace paddle

namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(range, ops::RangeOp, ops::RangeOpMaker);
REGISTER_OP_CPU_KERNEL(range, ops::CPURangeKernel<int>,
ops::CPURangeKernel<float>, ops::CPURangeKernel<double>,
ops::CPURangeKernel<int64_t>);
67 changes: 67 additions & 0 deletions paddle/fluid/operators/range_op.cu
Original file line number Diff line number Diff line change
@@ -0,0 +1,67 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/range_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"

namespace paddle {
namespace operators {

#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < (n); \
i += blockDim.x * gridDim.x)

template <typename T>
__global__ void RangeKernel(T start, T step, int64_t size, T* out) {
CUDA_1D_KERNEL_LOOP(index, size) { out[index] = start + step * index; }
}

template <typename T>
class CUDARangeKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto* start_t = context.Input<framework::Tensor>("Start");
auto* end_t = context.Input<framework::Tensor>("End");
auto* step_t = context.Input<framework::Tensor>("Step");
auto* out = context.Output<framework::Tensor>("Out");

framework::Tensor n;
framework::TensorCopy(*start_t, platform::CPUPlace(), &n);
T start = n.data<T>()[0];
framework::TensorCopy(*end_t, platform::CPUPlace(), &n);
T end = n.data<T>()[0];
framework::TensorCopy(*step_t, platform::CPUPlace(), &n);
T step = n.data<T>()[0];

int64_t size = 0;
GetSize(start, end, step, &size);
out->Resize(framework::make_ddim({size}));
T* out_data = out->mutable_data<T>(context.GetPlace());

auto stream = context.cuda_device_context().stream();
int block = 512;
int grid = (size + block - 1) / block;
RangeKernel<T><<<grid, block, 0, stream>>>(start, step, size, out_data);
}
};

} // namespace operators
} // namespace paddle

namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(range, ops::CUDARangeKernel<int>,
ops::CUDARangeKernel<int64_t>,
ops::CUDARangeKernel<float>,
ops::CUDARangeKernel<double>);
56 changes: 56 additions & 0 deletions paddle/fluid/operators/range_op.h
Original file line number Diff line number Diff line change
@@ -0,0 +1,56 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#pragma once
#include <functional>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/math_function.h"

namespace paddle {
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.");
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现在应该还不支持step<0吧

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已修复支持,多谢提醒。

*size = std::is_integral<T>::value
? ((std::abs(end - start) + std::abs(step) - 1) / std::abs(step))
: std::ceil(std::abs((end - start) / step));
}

template <typename T>
class CPURangeKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
T start = context.Input<framework::Tensor>("Start")->data<T>()[0];
T end = context.Input<framework::Tensor>("End")->data<T>()[0];
T step = context.Input<framework::Tensor>("Step")->data<T>()[0];
auto* out = context.Output<framework::Tensor>("Out");
int64_t size = 0;
GetSize(start, end, step, &size);
out->Resize(framework::make_ddim({size}));
T* out_data = out->mutable_data<T>(context.GetPlace());
T value = start;
for (int64_t i = 0; i < size; ++i) {
out_data[i] = value;
value += step;
}
}
};

} // namespace operators
} // namespace paddle
73 changes: 68 additions & 5 deletions python/paddle/fluid/layers/tensor.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,10 +25,26 @@
import numpy

__all__ = [
'create_tensor', 'create_parameter', 'create_global_var', 'cast',
'tensor_array_to_tensor', 'concat', 'sums', 'assign',
'fill_constant_batch_size_like', 'fill_constant', 'argmin', 'argmax',
'argsort', 'ones', 'zeros', 'reverse', 'has_inf', 'has_nan', 'isfinite'
'create_tensor',
'create_parameter',
'create_global_var',
'cast',
'tensor_array_to_tensor',
'concat',
'sums',
'assign',
'fill_constant_batch_size_like',
'fill_constant',
'argmin',
'argmax',
'argsort',
'ones',
'zeros',
'reverse',
'has_inf',
'has_nan',
'isfinite',
'range',
]


Expand Down Expand Up @@ -398,7 +414,7 @@ def fill_constant_batch_size_like(input,
"""
${comment}

It also sets *stop_gradient* to True.
It also sets *stop_gradient* to true.

Args:
input(${input_type}): ${input_comment}.
Expand Down Expand Up @@ -759,3 +775,50 @@ def isfinite(x):
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(type="isfinite", inputs={"X": x}, outputs={"Out": out})
return out


def range(start, end, step, dtype):
"""
Return evenly spaced values within a given interval.

Values are generated within the half-open interval [start, stop) (in other words,
the interval including start but excluding stop).

args:
start(int|float|Variable): Start of interval. The interval includes this value.
end(int|float|Variable): End of interval. The interval does not include this
value, except in some cases where step is not an integer
and floating point round-off affects the length of out.
step(int|float|Variable): Spacing between values. For any output out, this is the
distance between two adjacent values, out[i+1] - out[i].
The default step size is 1.
dtype(string): 'float32'|'int32'|..., the data type of the output tensor.

returns:
Evenly spaced values within a given interval.

examples:

.. code-block:: python

data = fluid.layers.range(0, 10, 2, 'int32')

"""
helper = LayerHelper("range", **locals())

if not isinstance(start, Variable):
start = fill_constant([1], dtype, start)
if not isinstance(end, Variable):
end = fill_constant([1], dtype, end)
if not isinstance(step, Variable):
step = fill_constant([1], dtype, step)

out = helper.create_variable_for_type_inference(dtype=start.dtype)

helper.append_op(
type='range',
inputs={'Start': start,
'End': end,
'Step': step},
outputs={'Out': [out]})
return out
7 changes: 7 additions & 0 deletions python/paddle/fluid/tests/unittests/test_layers.py
Original file line number Diff line number Diff line change
Expand Up @@ -1024,6 +1024,13 @@ def test_batch_norm(self):

print(str(program))

def test_range(self):
program = Program()
with program_guard(program):
layers.range(0, 10, 2, 'int32')
layers.range(0.1, 10.0, 0.2, 'float32')
print(str(program))

def test_shuffle_channel(self):
program = Program()
with program_guard(program):
Expand Down
70 changes: 70 additions & 0 deletions python/paddle/fluid/tests/unittests/test_range.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,70 @@
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import print_function

import unittest
import numpy as np
from op_test import OpTest


class TestRangeOp(OpTest):
def setUp(self):
self.op_type = "range"
self.init_config()
self.inputs = {
'Start': np.array([self.case[0]]).astype(self.dtype),
'End': np.array([self.case[1]]).astype(self.dtype),
'Step': np.array([self.case[2]]).astype(self.dtype)
}

self.outputs = {
'Out': np.arange(self.case[0], self.case[1],
self.case[2]).astype(self.dtype)
}

def init_config(self):
self.dtype = np.float32
self.case = (0, 1, 0.2)

def test_check_output(self):
self.check_output()


class TestFloatRangeOpCase0(TestRangeOp):
def init_config(self):
self.dtype = np.float32
self.case = (0, 5, 1)


class TestInt32RangeOpCase0(TestRangeOp):
def init_config(self):
self.dtype = np.int32
self.case = (0, 5, 2)


class TestInt32RangeOpCase1(TestRangeOp):
def init_config(self):
self.dtype = np.int32
self.case = (10, 1, -2)


class TestInt32RangeOpCase2(TestRangeOp):
def init_config(self):
self.dtype = np.int32
self.case = (-1, -10, -2)


if __name__ == "__main__":
unittest.main()