revert logsumexp op(#27145)

paddle/fluid/operators/reduce_ops/logsumexp_op.cc

-// Copyright (c) 2020 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/reduce_ops/logsumexp_op.h"
-#include <memory>
-#include <string>
-#include <utility>
-#include <vector>
-
-namespace paddle {
-namespace operators {
-
-class LogsumexpOpMaker : public ops::ReduceOpMaker {
- protected:
-  virtual std::string GetName() const { return "logsumexp"; }
-  virtual std::string GetOpType() const { return "Reduce logsumexp"; }
-};
-
-template <typename T>
-class LogsumexpGradOpMaker : public framework::SingleGradOpMaker<T> {
- public:
-  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
-
- protected:
-  void Apply(GradOpPtr<T> op) const override {
-    op->SetType("logsumexp_grad");
-    op->SetInput("X", this->Input("X"));
-    op->SetInput("Out", this->Output("Out"));
-    op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
-    op->SetAttrMap(this->Attrs());
-    op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-REGISTER_OPERATOR(logsumexp, ops::ReduceOp, ops::LogsumexpOpMaker,
-                  ops::LogsumexpGradOpMaker<paddle::framework::OpDesc>,
-                  ops::LogsumexpGradOpMaker<paddle::imperative::OpBase>);
-REGISTER_OPERATOR(logsumexp_grad, ops::ReduceGradOp);
-
-REGISTER_OP_CPU_KERNEL(logsumexp,
-                       ops::ReduceKernel<paddle::platform::CPUDeviceContext,
-                                         float, ops::LogsumexpFunctor>,
-                       ops::ReduceKernel<paddle::platform::CPUDeviceContext,
-                                         double, ops::LogsumexpFunctor>);
-REGISTER_OP_CPU_KERNEL(
-    logsumexp_grad, ops::ReduceGradKernel<paddle::platform::CPUDeviceContext,
-                                          float, ops::LogsumexpGradFunctor>,
-    ops::ReduceGradKernel<paddle::platform::CPUDeviceContext, double,
-                          ops::LogsumexpGradFunctor>);

paddle/fluid/operators/reduce_ops/logsumexp_op.cu

-// 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.
-
-#include "paddle/fluid/operators/reduce_ops/logsumexp_op.h"
-
-REGISTER_OP_CUDA_KERNEL(logsumexp,
-                        ops::ReduceKernel<paddle::platform::CUDADeviceContext,
-                                          float, ops::LogsumexpFunctor>,
-                        ops::ReduceKernel<paddle::platform::CUDADeviceContext,
-                                          double, ops::LogsumexpFunctor>);

paddle/fluid/operators/reduce_ops/logsumexp_op.h

-// Copyright (c) 2020 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 "paddle/fluid/operators/reduce_ops/reduce_op.h"
-
-namespace paddle {
-namespace operators {
-
-struct LogsumexpFunctor {
-  template <typename DeviceContext, typename X, typename Y, typename Dim>
-  void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) {
-    auto x_dim = x->dimensions();
-    auto t_dim = x_dim;
-    for (int i = 0; i < static_cast<int>(dim.size()); i++) {
-      t_dim[dim[i]] = 1;
-    }
-
-    auto r_dim = x_dim;
-    for (int i = 0; i < static_cast<int>(r_dim.size()); i++) {
-      r_dim[i] = 1;
-    }
-    for (int i = 0; i < static_cast<int>(dim.size()); i++) {
-      r_dim[dim[i]] = x_dim[dim[i]];
-    }
-
-    auto y_dim = y->dimensions();
-    auto x_max = x->maximum(dim);
-    y->device(place) =
-        (x_max +
-         (*x - x_max.reshape(t_dim).broadcast(r_dim)).exp().sum(dim).log())
-            .reshape(y_dim);
-  }
-};
-
-struct LogsumexpGradFunctor {
-  template <typename DeviceContext, typename X, typename Y, typename DX,
-            typename DY, typename Dim>
-  void operator()(const DeviceContext& place, X* x, Y* y, DX* dx, DY* dy,
-                  const Dim& dim, int size) {
-    dx->device(place) = dy->broadcast(dim) * (*x - y->broadcast(dim)).exp();
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle

paddle/fluid/operators/reduce_ops/logsumexp_op.part.cu

-// 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.
-
-// .part used to speed up nvcc compile
-#include "paddle/fluid/operators/reduce_ops/logsumexp_op.h"
-
-REGISTER_OP_CUDA_KERNEL(
-    logsumexp_grad, ops::ReduceGradKernel<paddle::platform::CUDADeviceContext,
-                                          float, ops::LogsumexpGradFunctor>,
-    ops::ReduceGradKernel<paddle::platform::CUDADeviceContext, double,
-                          ops::LogsumexpGradFunctor>);

python/paddle/fluid/tests/unittests/test_logsumexp.py

@@ -12,128 +12,60 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from __future__ import print_function
 import paddle
+import paddle.fluid as fluid
 import unittest
 import numpy as np
 from op_test import OpTest
+from paddle.fluid import Program, program_guard
+from paddle.fluid.layer_helper import LayerHelper
 
 
-def ref_logsumexp(x, axis=None, keepdim=False, reduce_all=False):
-    if isinstance(axis, int):
-        axis = (axis, )
-    elif isinstance(axis, list):
-        axis = tuple(axis)
-    if reduce_all:
-        axis = None
-    out = np.log(np.exp(x).sum(axis=axis, keepdims=keepdim))
-    return out
-
-
-class TestLogsumexp(OpTest):
-    def setUp(self):
-        self.op_type = 'logsumexp'
-        self.shape = [2, 3, 4, 5]
-        self.dtype = 'float64'
-        self.axis = [-1]
-        self.keepdim = False
-        self.reduce_all = False
-        self.set_attrs()
-
-        np.random.seed(10)
-        x = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
-        out = ref_logsumexp(x, self.axis, self.keepdim, self.reduce_all)
-
-        self.inputs = {'X': x}
-        self.outputs = {'Out': out}
-        self.attrs = {
-            'dim': self.axis,
-            'keep_dim': self.keepdim,
-            'reduce_all': self.reduce_all
-        }
-
-    def set_attrs(self):
-        pass
-
-    def test_check_output(self):
-        self.check_output()
-
-    def test_check_grad(self):
-        self.check_grad(['X'], ['Out'])
-
-
-class TestLogsumexp_shape(TestLogsumexp):
-    def set_attrs(self):
-        self.shape = [4, 5, 6]
-
-
-class TestLogsumexp_axis(TestLogsumexp):
-    def set_attrs(self):
-        self.axis = [0, -1]
-
-
-class TestLogsumexp_axis_all(TestLogsumexp):
-    def set_attrs(self):
-        self.axis = [0, 1, 2, 3]
-
-
-class TestLogsumexp_keepdim(TestLogsumexp):
-    def set_attrs(self):
-        self.keepdim = True
-
-
-class TestLogsumexp_reduce_all(TestLogsumexp):
-    def set_attrs(self):
-        self.reduce_all = True
-
-
-class TestLogsumexpError(unittest.TestCase):
+class TestLogSumOpError(unittest.TestCase):
     def test_errors(self):
-        with paddle.static.program_guard(paddle.static.Program()):
-            self.assertRaises(TypeError, paddle.logsumexp, 1)
-            x1 = paddle.data(name='x1', shape=[120], dtype="int32")
-            self.assertRaises(TypeError, paddle.logsumexp, x1)
-
-
-class TestLogsumexpAPI(unittest.TestCase):
-    def setUp(self):
-        self.shape = [2, 3, 4, 5]
-        self.x = np.random.uniform(-1, 1, self.shape).astype(np.float32)
-        self.place = paddle.CUDAPlace(0) if paddle.fluid.core.is_compiled_with_cuda() \
-            else paddle.CPUPlace()
-
-    def api_case(self, axis=None, keepdim=False):
-        out_ref = ref_logsumexp(self.x, axis, keepdim)
-        with paddle.static.program_guard(paddle.static.Program()):
-            x = paddle.data('X', self.shape)
-            out = paddle.logsumexp(x, axis, keepdim)
-            exe = paddle.static.Executor(self.place)
-            res = exe.run(feed={'X': self.x}, fetch_list=[out])
-        self.assertTrue(np.allclose(res[0], out_ref))
-
-        paddle.disable_static(self.place)
-        x = paddle.to_variable(self.x)
-        out = paddle.logsumexp(x, axis, keepdim)
-        self.assertTrue(np.allclose(out.numpy(), out_ref))
-        paddle.enable_static()
-
-    def test_api(self):
-        self.api_case()
-        self.api_case(2)
-        self.api_case([-1])
-        self.api_case([2, -3])
-        self.api_case((0, 1, -1))
-        self.api_case(keepdim=True)
-
-    def test_alias(self):
-        paddle.disable_static(self.place)
-        x = paddle.to_variable(self.x)
-        out1 = paddle.logsumexp(x)
-        out2 = paddle.tensor.logsumexp(x)
-        out3 = paddle.tensor.math.logsumexp(x)
-        out_ref = ref_logsumexp(self.x)
-        for out in [out1, out2, out3]:
-            self.assertTrue(np.allclose(out.numpy(), out_ref))
-        paddle.enable_static()
+        with program_guard(Program(), Program()):
+
+            x1 = fluid.layers.data(name='x1', shape=[120], dtype="uint8")
+            self.assertRaises(Exception, paddle.logsumexp, x1)
+
+            x2 = fluid.layers.data(name='x2', shape=[2, 3], dtype="int")
+            self.assertRaises(Exception, paddle.logsumexp, x2)
+
+            x3 = fluid.layers.data(name='x3', shape=[3], dtype="float16")
+            self.assertRaises(Exception, paddle.logsumexp, x3)
+
+
+class TestLogSumExpOp(unittest.TestCase):
+    def test_dygraph(self):
+        with fluid.dygraph.guard():
+            np_x = np.random.uniform(0.1, 1, [123]).astype(np.float32)
+            x = fluid.dygraph.to_variable(np_x)
+            self.assertTrue(
+                np.allclose(
+                    paddle.logsumexp(x).numpy(), np.log(np.sum(np.exp(np_x)))))
+
+            np_x = np.random.uniform(0.1, 1, [2, 3, 4]).astype(np.float32)
+            x = fluid.dygraph.to_variable(np_x)
+            self.assertTrue(
+                np.allclose(
+                    paddle.logsumexp(x, [1, 2]).numpy(),
+                    np.log(np.sum(np.exp(np_x), axis=(1, 2)))))
+
+            np_x = np.random.uniform(0.1, 1, [2, 3, 4]).astype(np.float32)
+            x = fluid.dygraph.to_variable(np_x)
+            self.assertTrue(
+                np.allclose(
+                    paddle.logsumexp(x, [2]).numpy(),
+                    np.log(np.sum(np.exp(np_x), axis=(2)))))
+
+            np_x = np.random.uniform(0.1, 1, [2, 3, 4]).astype(np.float32)
+            x = fluid.dygraph.to_variable(np_x)
+            self.assertTrue(
+                np.allclose(
+                    paddle.logsumexp(
+                        x, keepdim=True).numpy(),
+                    np.log(np.sum(np.exp(np_x), keepdims=True))))
 
 
 if __name__ == '__main__':

python/paddle/tensor/math.py

@@ -86,7 +86,6 @@ __all__ = [
         'floor',
         'increment',
         'log',
-        'logsumexp',
         'mul',
         'multiplex',
         'pow',
@@ -1177,35 +1176,24 @@ def logsumexp(x, axis=None, keepdim=False, name=None):
     .. code-block:: python
 
         import paddle
+        import numpy as np
 
         paddle.disable_static()
-
-        x = paddle.to_tensor([[-1.5, 0., 2.], [3., 1.2, -2.4]])
+        
+        x = np.array([[-1.5, 0., 2.], [3., 1.2, -2.4]])
+        x = paddle.to_tensor(x)
         out1 = paddle.logsumexp(x) # [3.4691226]
         out2 = paddle.logsumexp(x, 1) # [2.15317821, 3.15684602]
 
     """
-    if isinstance(axis, int):
-        axis = [axis]
-    reduce_all = True if axis is None \
-        or len(axis)==0 \
-        or len(axis) == len(x.shape) else False
-    if axis is None or len(axis) == 0:
-        axis = [0]
-
-    if in_dygraph_mode():
-        return core.ops.logsumexp(x, 'dim', axis, 'keep_dim', keepdim,
-                                    'reduce_all', reduce_all)
-
-    check_variable_and_dtype(x, 'x',
+    if not in_dygraph_mode():
+        check_variable_and_dtype(x, 'x',
                              ['float32', 'float64'],
                              'logsumexp')
 
-    helper = LayerHelper('logsumexp', **locals())
-    attrs = {'dim': axis, 'keep_dim': keepdim, 'reduce_all': reduce_all}
-    out = helper.create_variable_for_type_inference(x.dtype)
-    helper.append_op(
-        type='logsumexp', inputs={'X': x}, outputs={'Out': out}, attrs=attrs)
+    out = paddle.exp(x, name)
+    out = paddle.sum(out, axis=axis, keepdim=keepdim, name=name)
+    out = paddle.log(out, name)
     return out