[NPU] Support npu kernel for reduceany op (#31422)
* add reduce any npu op * add gather python unittest * update c_plus unittest * update python unittest * del c++ unittest * update c++ unittest * update c++ unittestrevert-31562-mean
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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include <memory>
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#include <string>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/tensor_util.h"
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#include "paddle/fluid/operators/npu_op_runner.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename T>
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class ReduceAnyNPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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const Tensor* x = ctx.Input<Tensor>("X");
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auto* out = ctx.Output<Tensor>("Out");
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bool keep_dim = ctx.Attr<bool>("keep_dim");
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auto dims = ctx.Attr<std::vector<int>>("dim");
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out->mutable_data<T>(ctx.GetPlace());
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// set attr
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NPUAttributeMap attr = {{"keep_dims", keep_dim}, {"axes", dims}};
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auto runner = NpuOpRunner("ReduceAnyD", {*x}, {*out}, attr);
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auto stream =
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ctx.template device_context<paddle::platform::NPUDeviceContext>()
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.stream();
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runner.Run(stream);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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namespace plat = paddle::platform;
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REGISTER_OP_NPU_KERNEL(reduce_any, ops::ReduceAnyNPUKernel<bool>);
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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifndef _WIN32
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#include <unistd.h>
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#endif
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#include <memory>
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#include <string>
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#include <thread> // NOLINT
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#include <vector>
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/memory/malloc.h"
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#include "paddle/fluid/memory/memcpy.h"
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#include "paddle/fluid/operators/math/math_function.h"
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#include "paddle/fluid/string/printf.h"
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namespace f = paddle::framework;
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namespace p = paddle::platform;
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namespace m = paddle::operators::math;
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using Tensor = paddle::framework::Tensor;
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USE_OP(reduce_any);
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USE_OP_DEVICE_KERNEL(reduce_any, NPU);
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template <typename T>
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void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
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// init
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auto x = scope->Var("X");
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auto tensor_x = x->GetMutable<f::LoDTensor>();
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std::vector<bool> init_x = {true, false, false, false};
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f::TensorFromVector<bool>(init_x, ctx, tensor_x);
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tensor_x->Resize(paddle::framework::make_ddim({2}));
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ctx.Wait();
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auto place = ctx.GetPlace();
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auto out = scope->Var("Out");
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auto tensor_out = out->GetMutable<f::LoDTensor>();
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// run
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std::vector<int> axes;
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f::AttributeMap attrs = {{"axes", axes}, {"keep_dims", true}};
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auto op = f::OpRegistry::CreateOp("reduce_any", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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op->Run(*scope, place);
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ctx.Wait();
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std::vector<bool> out_vec;
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f::TensorToVector<bool>(*tensor_out, ctx, &out_vec);
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ctx.Wait();
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std::vector<bool> expected_vec = {true};
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EXPECT_EQ(out_vec.size(), expected_vec.size());
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for (uint32_t i = 0; i < out_vec.size(); i++) {
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EXPECT_EQ(out_vec[i], expected_vec[i]);
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}
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}
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TEST(reduce_any, NPU) {
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f::Scope scope;
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p::NPUDeviceContext ctx(p::NPUPlace(0));
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Compare<bool>(&scope, ctx);
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}
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest, skip_check_grad_ci
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import paddle
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import paddle.fluid.core as core
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import paddle.fluid as fluid
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from paddle.fluid import compiler, Program, program_guard
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from paddle.fluid.framework import convert_np_dtype_to_dtype_
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paddle.enable_static()
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@unittest.skipIf(not paddle.is_compiled_with_npu(),
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"core is not compiled with NPU")
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class TestAny8DOp(OpTest):
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def setUp(self):
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self.set_npu()
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self.op_type = "reduce_any"
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self.place = paddle.NPUPlace(0)
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self.inputs = {
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'X': np.random.randint(0, 2,
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(2, 5, 3, 2, 2, 3, 4, 2)).astype("bool")
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}
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self.attrs = {'dim': (3, 5, 4)}
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self.outputs = {'Out': self.inputs['X'].any(axis=self.attrs['dim'])}
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def set_npu(self):
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self.__class__.use_npu = True
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def test_check_output(self):
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self.check_output_with_place(self.place, check_dygraph=False)
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@unittest.skipIf(not paddle.is_compiled_with_npu(),
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"core is not compiled with NPU")
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class TestAnyOpWithDim(OpTest):
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def setUp(self):
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self.set_npu()
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self.op_type = "reduce_any"
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self.place = paddle.NPUPlace(0)
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self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
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self.attrs = {'dim': [1]}
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self.outputs = {'Out': self.inputs['X'].any(axis=1)}
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def set_npu(self):
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self.__class__.use_npu = True
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def test_check_output(self):
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self.check_output_with_place(self.place, check_dygraph=False)
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@unittest.skipIf(not paddle.is_compiled_with_npu(),
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"core is not compiled with NPU")
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class TestAny8DOpWithDim(OpTest):
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def setUp(self):
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self.set_npu()
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self.op_type = "reduce_any"
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self.place = paddle.NPUPlace(0)
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self.inputs = {
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'X': np.random.randint(0, 2,
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(2, 5, 3, 2, 2, 3, 4, 2)).astype("bool")
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}
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self.attrs = {'dim': (3, 6)}
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self.outputs = {'Out': self.inputs['X'].any(axis=self.attrs['dim'])}
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def set_npu(self):
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self.__class__.use_npu = True
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def test_check_output(self):
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self.check_output_with_place(self.place, check_dygraph=False)
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@unittest.skipIf(not paddle.is_compiled_with_npu(),
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"core is not compiled with NPU")
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class TestAnyOpWithKeepDim(OpTest):
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def setUp(self):
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self.set_npu()
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self.op_type = "reduce_any"
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self.place = paddle.NPUPlace(0)
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self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
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self.attrs = {'dim': (1, ), 'keep_dim': True}
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self.outputs = {
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'Out': np.expand_dims(
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self.inputs['X'].any(axis=self.attrs['dim']), axis=1)
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}
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def set_npu(self):
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self.__class__.use_npu = True
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def test_check_output(self):
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self.check_output_with_place(self.place, check_dygraph=False)
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class TestAny8DOpWithKeepDim(OpTest):
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def setUp(self):
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self.set_npu()
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self.op_type = "reduce_any"
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self.place = paddle.NPUPlace(0)
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self.inputs = {
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'X': np.random.randint(0, 2,
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(2, 5, 3, 2, 2, 3, 4, 2)).astype("bool")
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}
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self.attrs = {'dim': (1, ), 'keep_dim': True}
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self.outputs = {
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'Out': np.expand_dims(
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self.inputs['X'].any(axis=self.attrs['dim']), axis=1)
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}
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def set_npu(self):
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self.__class__.use_npu = True
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def test_check_output(self):
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self.check_output_with_place(self.place, check_dygraph=False)
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if __name__ == '__main__':
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unittest.main()
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