bind elementwise_mod_op_xpu (#42175)

* bind elementwise_mod_op_xpu *test=kunlun

* add more supported dtypes and UTs *test=kunlun

* fix datatype error

* add op to in xpu1_op_list

* Update Mac cmake version >=3.15 (#41456)

* Update Mac cmake version >=3.15

* notest;read test1

notest;read test2

notest;read test3

* fix inference link error

* fix inference link error

* fix windows link error

* fix cmake_policy

* fix build big size

* Add paddle::variant and replace paddle::any (#42139)

* add variant and replace any

* split attribute

* disable unittest failed in eager CI in temporary (#42101)

* test=py3-eager

* test=py3-eager

* test=py3-eager

* combine graph_table and feature_table in graph_engine (#42134)

* extract sub-graph

* graph-engine merging

* fix

* fix

* fix heter-ps config

* test performance

* test performance

* test performance

* test

* test

* update bfs

* change cmake

* test

* test gpu speed

* gpu_graph_engine optimization

* add dsm sample method

* add graph_neighbor_sample_v2

* Add graph_neighbor_sample_v2

* fix for loop

* add cpu sample interface

* fix kernel judgement

* add ssd layer to graph_engine

* fix allocation

* fix syntax error

* fix syntax error

* fix pscore class

* fix

* change index settings

* recover test

* recover test

* fix spelling

* recover

* fix

* move cudamemcpy after cuda stream sync

* fix linking problem

* remove comment

* add cpu test

* test

* add cpu test

* change comment

* combine feature table and graph table

* test

* test

* pybind

* test

* test

* test

* test

* pybind

* pybind

* fix cmake

* pybind

* fix

* fix

* add pybind

* add pybind
Co-authored-by: NDesmonDay <908660116@qq.com>

* [CustomDevice] add eager mode support (#42034)

* fix FlattenContiguousRangeOpConverter out dim error (#42087)

* fix FlattenContiguousRangeOpConverter out dim error

* update code

* fix python3.10 compile bug on windows (#42140)

* Optimize dygraph GetExpectedKernelType perf (#42154)

* opt dygraph scheduling

* revert part impl

* fix incorrect usages of std::move and other compile errors (#41045)

* fix bug of std::move and others

* fix an compile error in debug mode

* fix wrong copy assignment operator
Signed-off-by: Ntiancaishaonvjituizi <452565578@qq.com>

* reformat
Signed-off-by: Ntiancaishaonvjituizi <452565578@qq.com>

* reformat
Signed-off-by: Ntiancaishaonvjituizi <452565578@qq.com>

* fix ArrayRef constructor following llvm

* fix format

* fix conflict with master

* fix variant compile error (#42203)

* [Eager] Support numpy.ndarry in CastNumpy2Scalar (#42136)

* [Eager] Remove redundancy code, fix fp16 case (#42169)

* [Eager] Support div(scalar) in eager mode (#42148)

* [Eager] Support div scalar in eager mode

* Updated and remove debug logs

* Remove list, use 'or' directly

* Remove useless statement

* fix recompute (#42128)

* fix recompute

* modify return

* add LICENSE in wheel dist-info package (#42187)

* replace any by variant in infermeta (#42181)

* 【PaddlePaddle Hackathon 2】24、为 Paddle 新增 nn.ChannelShuffle 组网 API (#40743)

* Add infermeta for ChannelShuffle

* Create channel_shuffle_grad_kernel.h

* Create channel_shuffle_kernel.h

* Create channel_shuffle_sig.cc

* Create channel_shuffle_op.cc

ChannelShuffle算子的描述

* Create channel_shuffle_kernel_impl.h

ChannelShuffle核函数的实现

* Create channel_shuffle_grad_kernel_impl.h

ChannelShuffle反向核函数的实现

* Add kernel register of channel shuffle and grad

注册ChannelShuffle及其反向的核函数

* add nn.functional.channel_shuffle

* add nn.ChannelShuffle

* Create test_channel_shuffle.py

* Update example of ChannelShuffle in vision.py

* Update test_channel_shuffle.py

* 修改channel_shuffle核函数的实现位置

* 修正代码格式

* 删除多余空格

* 完善channel_shuffle的错误检查

* Update unary.cc

* Update channel_shuffle_op.cc

* Update test_channel_shuffle.py

* Update unary.cc

* add channel_shuffle

* Update test_channel_shuffle.py

* Update vision.py

* 调整代码格式

* Update channel_shuffle_sig.cc

* 更新ChannelShuffle的文档

* 更新channel_shuffle的文档

* remove ChannelShuffleOpArgumentMapping

* add ChannelShuffleGradInferMeta

* Update channel_shuffle_op.cc

* 调整channel_shuffle及其梯度的核函数的位置

* Do not reset default stream for StreamSafeCUDAAllocator (#42149)

* remove redundant computation in Categorical.probs (#42114)

* Downloading data for test_analyzer_vit_ocr (#42041)

* Change server URL

* update config

* add test to parallel UT rule

* add checksum to ensure files are downloaded

* change downloading target

* reuse existing variable

* change target directory

* fix en docs of some Apis (gradients, scope_guard, cuda_places, name_scope, device_guard, load_program_state, scale, ParamAttr and WeightNormParamAttr) (#41604)

* Update scope_guard; test=document_fix

* gradients; test=document_fix

* gradients; test=document_fix

* name_scope; test=document_fix

* cpu_places; test=document_fix

* WeightNormParamAttr; test=document_fix

* cuda_places; test=document_fix

* load_program_state; test=document_fix

* device_guard; test=document_fix

* device_guard; test=document_fix

* ParamAttr; test=document_fix

* scale; test=document_fix

* scale; test=document_fix

* update code example；test=document_fix
Co-authored-by: NChen Long <1300851984@qq.com>

* fix datatype error

add op to in xpu1_op_list

*test=kunlun

* fix elementwise_mod op path error  *test=kunlun

* fix elementwise_mod UT error  *test=kunlun

* fix datatype error

add op to in xpu1_op_list

*test=kunlun

add op to in xpu1_op_list

fix elementwise_mod op path error  *test=kunlun

fix elementwise_mod UT error  *test=kunlun
Co-authored-by: Ntianshuo78520a <707759223@qq.com>
Co-authored-by: NChen Weihang <chenweihang@baidu.com>
Co-authored-by: Npangyoki <pangyoki@126.com>
Co-authored-by: Nseemingwang <seemingwang@users.noreply.github.com>
Co-authored-by: NDesmonDay <908660116@qq.com>
Co-authored-by: Nronnywang <524019753@qq.com>
Co-authored-by: Nbaoachun <962571062@qq.com>
Co-authored-by: Zhou Wei <1183042833@qq.com>
Co-authored-by: Ntiancaishaonvjituizi <452565578@qq.com>
Co-authored-by: NWeilong Wu <veyron_wu@163.com>
Co-authored-by: NRoc <30228238+sljlp@users.noreply.github.com>
Co-authored-by: NBrilliantYuKaimin <91609464+BrilliantYuKaimin@users.noreply.github.com>
Co-authored-by: NRuibiao Chen <chenruibiao@baidu.com>
Co-authored-by: NFeiyu Chan <chenfeiyu@baidu.com>
Co-authored-by: NSławomir Siwek <slawomir.siwek@intel.com>
Co-authored-by: NYilingyelu <103369238+Yilingyelu@users.noreply.github.com>
Co-authored-by: NChen Long <1300851984@qq.com>

paddle/fluid/operators/elementwise/elementwise_mod_op_xpu.cc

+/* Copyright (c) 2022 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. */
+
+#ifdef PADDLE_WITH_XPU
+#include <memory>
+#include <string>
+#include "paddle/fluid/framework/data_layout.h"
+#include "paddle/fluid/framework/op_version_registry.h"
+#include "paddle/fluid/operators/common_infer_shape_functions.h"
+#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
+
+#include "paddle/fluid/operators/elementwise/elementwise_xpu.h"
+#include "paddle/fluid/platform/device/device_wrapper.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class ElementwiseModXPUKernel : public framework::OpKernel<T> {
+  using XPUType = typename XPUTypeTrait<T>::Type;
+
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    XPUElementwise<T, XPUType>(ctx, xpu::broadcast_mod<XPUType>);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_XPU_KERNEL(elementwise_mod, ops::ElementwiseModXPUKernel<float>,
+                       ops::ElementwiseModXPUKernel<paddle::platform::float16>,
+                       ops::ElementwiseModXPUKernel<int32_t>,
+                       ops::ElementwiseModXPUKernel<int64_t>);
+
+#endif

paddle/fluid/platform/device/xpu/xpu2_op_list.h

@@ -130,6 +130,11 @@ XPUOpMap& get_kl2_ops() {
       {"elementwise_sub",
        XPUKernelSet({pOpKernelType(vartype::FP32, XPUPlace()),
                      pOpKernelType(vartype::FP16, XPUPlace())})},
+      {"elementwise_mod",
+       XPUKernelSet({pOpKernelType(vartype::FP32, XPUPlace()),
+                     pOpKernelType(vartype::FP16, XPUPlace()),
+                     pOpKernelType(vartype::INT64, XPUPlace()),
+                     pOpKernelType(vartype::INT32, XPUPlace())})},
       {"equal", XPUKernelSet({pOpKernelType(vartype::INT64, XPUPlace()),
                               pOpKernelType(vartype::INT32, XPUPlace()),
                               pOpKernelType(vartype::FP32, XPUPlace())})},

python/paddle/fluid/tests/unittests/xpu/test_elementwise_mod_op_xpu.py

+#  Copyright (c) 2022 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.
+import sys
+sys.path.append("..")
+import unittest
+import numpy as np
+from op_test import OpTest
+import paddle.fluid as fluid
+from paddle.fluid import compiler, Program, program_guard
+
+import paddle
+from op_test_xpu import XPUOpTest
+from xpu.get_test_cover_info import create_test_class, get_xpu_op_support_types, XPUOpTestWrapper
+
+paddle.enable_static()
+
+
+class XPUTestElementwiseModOp(XPUOpTestWrapper):
+    def __init__(self) -> None:
+        self.op_name = 'elementwise_mod'
+        self.use_dynamic_create_class = False
+
+    class ElementwiseModOp(XPUOpTest):
+        def init_kernel_type(self):
+            self.use_mkldnn = False
+
+        def init_input_output(self):
+            self.x = np.random.uniform(0, 10000, [10, 10]).astype(self.dtype)
+            self.y = np.random.uniform(0, 1000, [10, 10]).astype(self.dtype)
+            self.out = np.mod(self.x, self.y)
+            self.inputs = {
+                'X': OpTest.np_dtype_to_fluid_dtype(self.x),
+                'Y': OpTest.np_dtype_to_fluid_dtype(self.y)
+            }
+            self.outputs = {'Out': self.out}
+            self.attrs = {'axis': self.axis, 'use_mkldnn': self.use_mkldnn}
+
+        def init_dtype(self):
+            pass
+
+        def init_axis(self):
+            pass
+
+        def setUp(self):
+            self.op_type = 'elementwise_mod'
+            self.use_xpu = True
+            self.dtype = self.in_type
+            self.axis = -1
+            self.init_dtype()
+            self.init_input_output()
+            self.init_kernel_type()
+            self.init_axis()
+
+        def test_check_output(self):
+            if paddle.is_compiled_with_xpu():
+                place = paddle.XPUPlace(0)
+                self.check_output_with_place(place)
+
+    class TestElementwiseModOp_broadcast_1(ElementwiseModOp):
+        def init_input_output(self):
+            self.inputs = {
+                'X': np.random.rand(2, 100, 3).astype(self.dtype),
+                'Y': np.random.rand(2, 100, 3).astype(self.dtype)
+            }
+
+            self.attrs = {'axis': 1}
+            self.outputs = {'Out': self.inputs['X'] % self.inputs['Y']}
+
+    class TestElementwiseModOp_broadcast_2(ElementwiseModOp):
+        def init_input_output(self):
+            self.inputs = {
+                'X': np.random.rand(22, 128, 3).astype(self.dtype),
+                'Y': np.random.rand(22, 128, 3).astype(self.dtype)
+            }
+
+            self.attrs = {'axis': 1}
+            self.outputs = {'Out': self.inputs['X'] % self.inputs['Y']}
+
+    class TestRemainderOp(unittest.TestCase):
+        def test_dygraph(self):
+            with fluid.dygraph.guard():
+                np_x = np.random.rand(22, 128, 3).astype('int64')
+                np_y = np.random.rand(22, 128, 3).astype('int64')
+                x = paddle.to_tensor(np_x)
+                y = paddle.to_tensor(np_y)
+                z = paddle.remainder(x, y)
+                np_z = z.numpy()
+                z_expected = np.mod(np_x, np_y)
+                self.assertEqual((np_z == z_expected).all(), True)
+
+                np_x = np.array([-3.3, 11.5, -2, 3.5])
+                np_y = np.array([-1.2, 2., 3.3, -2.3])
+                x = paddle.to_tensor(np_x)
+                y = paddle.to_tensor(np_y)
+                z = x % y
+                z_expected = np.array([-0.9, 1.5, 1.3, -1.1])
+                self.assertEqual(np.allclose(z_expected, z.numpy()), True)
+
+                np_x = np.random.rand(22, 128, 3).astype('int32')
+                np_y = np.random.rand(22, 128, 3).astype('int32')
+                x = paddle.to_tensor(np_x)
+                y = paddle.to_tensor(np_y)
+                z = paddle.remainder(x, y)
+                np_z = z.numpy()
+                z_expected = np.mod(np_x, np_y)
+                self.assertEqual((np_z == z_expected).all(), True)
+
+                np_x = np.array([-3, 11, -2, 3])
+                np_y = np.array([-1, 2, 3, -2])
+                x = paddle.to_tensor(np_x, dtype="float16")
+                y = paddle.to_tensor(np_y, dtype="float16")
+                z = x % y
+                z_expected = np.array([0, 1, 1, -1])
+                self.assertEqual(np.allclose(z_expected, z.numpy()), True)
+
+
+support_types = get_xpu_op_support_types('elementwise_mod')
+for stype in support_types:
+    create_test_class(globals(), XPUTestElementwiseModOp, stype)
+
+if __name__ == '__main__':
+    unittest.main()