Created by: T8T9

PR types

Function optimization

PR changes

OPs

Describe

合并 elementwise_pow 和 pow，命名为 power，完全兼容elementwise_pow 和 pow。

测试代码

import paddle
import numpy as np
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard

# x ** y
def run_power(mode, x, y):
    # dynamic mode
    if mode=='dynamic':
        paddle.enable_imperative()
        # y is scalar
        if isinstance(y, (int, long, float)):
            x_ = paddle.imperative.to_variable(x)
            y_ = y
            res = paddle.power(x_, y)
            print("{}, scalar, {} ** {} = {}".format(mode, x, y, res.numpy()))
        # y is tensor
        else:
            x_ = paddle.imperative.to_variable(x)
            y_ = paddle.imperative.to_variable(y)
            res = paddle.power(x_, y_)
            print("{}, tensor, {} ** {} = {}".format(mode, x, y, res.numpy()))
    # static mode
    elif mode=='static':
        paddle.disable_imperative()
        # y is scalar
        if isinstance(y, (int, long, float)):
            with program_guard(Program(), Program()):
                x_ = paddle.nn.data(name="x", shape=x.shape, dtype=x.dtype)
                y_ = y
                res = paddle.power(x_, y_)
                place = fluid.CPUPlace()
                exe = fluid.Executor(place)
                outs = exe.run(feed={'x':x}, fetch_list=[res])
                print("{}, scalar, {} ** {} = {}".format(mode, x, y, outs[0]))
        # y is tensor
        else:
            with program_guard(Program(), Program()):
                x_ = paddle.nn.data(name="x", shape=x.shape, dtype=x.dtype)
                y_ = paddle.nn.data(name="y", shape=y.shape, dtype=y.dtype)
                res = paddle.power(x_, y_)
                place = fluid.CPUPlace()
                exe = fluid.Executor(place)
                outs = exe.run(feed={'x':x, 'y': y}, fetch_list=[res])
                print("{}, tensor, {} ** {} = {}".format(mode, x, y, outs[0]))

def batch_run(x, y):
    run_power('dynamic', x, y)
    run_power('dynamic', x, y)
    run_power('static', x, y)
    run_power('static', x, y)
    print('-'*10)

x = np.array([1.5, 2.5, 3.5], dtype=np.int32)
y = 2.5
batch_run(x, y)

x = np.array([1.5, 2.5, 3.5], dtype=np.float32)
y = 2.5
batch_run(x, y)
    
x = np.array([1.5, 2.5, 3.5], dtype=np.float32)
y = np.array([2.5], dtype=np.float32)
batch_run(x, y)

x = np.array([1.5, 2.5, 3.5], dtype=np.int32)
y = np.array([2.5], dtype=np.float32)
try:
    batch_run(x, y)
except Exception as e:
    print(e)

输出：

dynamic, scalar, [1 2 3] ** 2.5 = [1 4 9]
dynamic, scalar, [1 2 3] ** 2.5 = [1 4 9]
static, scalar, [1 2 3] ** 2.5 = [1 4 9]
static, scalar, [1 2 3] ** 2.5 = [1 4 9]
----------
dynamic, scalar, [1.5 2.5 3.5] ** 2.5 = [ 2.755676  9.882117 22.917652]
dynamic, scalar, [1.5 2.5 3.5] ** 2.5 = [ 2.755676  9.882117 22.917652]
static, scalar, [1.5 2.5 3.5] ** 2.5 = [ 2.755676  9.882117 22.917652]
static, scalar, [1.5 2.5 3.5] ** 2.5 = [ 2.755676  9.882117 22.917652]
----------
dynamic, tensor, [1.5 2.5 3.5] ** [2.5] = [ 2.755676  9.882117 22.917652]
dynamic, tensor, [1.5 2.5 3.5] ** [2.5] = [ 2.755676  9.882117 22.917652]
static, tensor, [1.5 2.5 3.5] ** [2.5] = [ 2.755676  9.882117 22.917652]
static, tensor, [1.5 2.5 3.5] ** [2.5] = [ 2.755676  9.882117 22.917652]
----------


--------------------------------------------
C++ Call Stacks (More useful to developers):
--------------------------------------------
0   std::string paddle::platform::GetTraceBackString<std::string const&>(std::string const&, char const*, int)
1   paddle::platform::EnforceNotMet::EnforceNotMet(std::string const&, char const*, int)
2   int const* paddle::framework::Tensor::data<int>() const
3   void paddle::operators::ElementwiseComputeEx<paddle::operators::PowFunctor<int>, paddle::platform::CPUDeviceContext, int, int>(paddle::framework::ExecutionContext const&, paddle::framework::Tensor const*, paddle::framework::Tensor const*, int, paddle::operators::PowFunctor<int>, paddle::framework::Tensor*)
4   paddle::operators::ElementwisePowKernel<paddle::platform::CPUDeviceContext, int>::Compute(paddle::framework::ExecutionContext const&) const
5   std::_Function_handler<void (paddle::framework::ExecutionContext const&), paddle::framework::OpKernelRegistrarFunctor<paddle::platform::CPUPlace, false, 2ul, paddle::operators::ElementwisePowKernel<paddle::platform::CPUDeviceContext, float>, paddle::operators::ElementwisePowKernel<paddle::platform::CPUDeviceContext, double>, paddle::operators::ElementwisePowKernel<paddle::platform::CPUDeviceContext, int>, paddle::operators::ElementwisePowKernel<paddle::platform::CPUDeviceContext, long> >::operator()(char const*, char const*, int) const::{lambda(paddle::framework::ExecutionContext const&)#1}>::_M_invoke(std::_Any_data const&, paddle::framework::ExecutionContext const&)
6   paddle::imperative::PreparedOp::Run(paddle::imperative::NameVarBaseMap const&, paddle::imperative::NameVarBaseMap const&, paddle::framework::AttributeMap const&)
7   paddle::imperative::OpBase::Run(paddle::framework::OperatorBase const&, paddle::imperative::NameVarBaseMap const&, paddle::imperative::NameVarBaseMap const&, paddle::framework::AttributeMap const&, paddle::platform::Place const&)
8   paddle::imperative::Tracer::TraceOp(std::string const&, paddle::imperative::NameVarBaseMap const&, paddle::imperative::NameVarBaseMap const&, paddle::framework::AttributeMap, paddle::platform::Place const&, bool)
9   paddle::imperative::Tracer::TraceOp(std::string const&, paddle::imperative::NameVarBaseMap const&, paddle::imperative::NameVarBaseMap const&, paddle::framework::AttributeMap)

----------------------
Error Message Summary:
----------------------
InvalidArgumentError: Tensor holds the wrong type, it holds float, but desires to be int.
  [Hint: Expected valid == true, but received valid:0 != true:1.] at (/paddle/paddle/fluid/framework/tensor_impl.h:33)
  [operator < elementwise_pow > error]