[MLU]: add shape kernel (#43347)

* [MLU]: add shape kernel

* [MLU]: set output from cpu to mlu in shape kernel

paddle/fluid/operators/shape_op_mlu.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_MLU
+#include <algorithm>
+
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+using LoDTensor = framework::LoDTensor;
+using SelectedRows = phi::SelectedRows;
+
+template <typename T>
+class ShapeMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* in_var = ctx.InputVar("Input");
+    framework::DDim in_dims;
+    if (in_var->IsType<phi::SelectedRows>()) {
+      in_dims = in_var->Get<phi::SelectedRows>().value().dims();
+    } else {
+      in_dims = in_var->Get<LoDTensor>().dims();
+    }
+    auto* out_t = ctx.Output<Tensor>("Out");
+    out_t->Resize({in_dims.size()});
+    out_t->mutable_data<int32_t>(ctx.GetPlace());
+
+    // shape op cpu
+    Tensor shape_on_cpu(
+        framework::TransToPhiDataType(framework::proto::VarType::INT32));
+    shape_on_cpu.Resize({in_dims.size()});
+    auto cpu_data = shape_on_cpu.mutable_data<int32_t>(platform::CPUPlace());
+    for (int i = 0; i < in_dims.size(); ++i) {
+      cpu_data[i] = in_dims[i];
+    }
+
+    // cpu to mlu
+    auto& dev_ctx = ctx.template device_context<platform::MLUDeviceContext>();
+    framework::TensorCopy(shape_on_cpu, ctx.GetPlace(), dev_ctx, out_t);
+    dev_ctx.Wait();
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_MLU_KERNEL(shape, ops::ShapeMLUKernel<bool>,
+                       ops::ShapeMLUKernel<uint8_t>,
+                       ops::ShapeMLUKernel<int8_t>, ops::ShapeMLUKernel<int>,
+                       ops::ShapeMLUKernel<int64_t>,
+                       ops::ShapeMLUKernel<paddle::platform::float16>,
+                       ops::ShapeMLUKernel<float>, ops::ShapeMLUKernel<double>);
+
+#endif

python/paddle/fluid/tests/unittests/mlu/test_shape_op_mlu.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.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+import sys
+
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+# from paddle.fluid import core
+# from paddle.fluid.op import Operator
+
+paddle.enable_static()
+SEED = 2022
+
+
+class TestShape(OpTest):
+
+    def setUp(self):
+        self.set_mlu()
+        self.op_type = "shape"
+        self.place = paddle.MLUPlace(0)
+
+        self.init_dtype()
+        np.random.seed(SEED)
+        x = np.random.uniform(1, 2, [5, 10]).astype(self.dtype)
+        out = np.array([5, 10])
+
+        self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(x)}
+        self.attrs = {}
+        self.outputs = {'Out': out}
+
+    def set_mlu(self):
+        self.__class__.use_mlu = True
+
+    def init_dtype(self):
+        self.dtype = np.float32
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+class TestShape_fp16(TestShape):
+
+    def init_dtype(self):
+        self.dtype = np.float16
+
+
+class TestShape_double(TestShape):
+
+    def init_dtype(self):
+        self.dtype = np.float64
+
+
+class TestShape_int32(TestShape):
+
+    def init_dtype(self):
+        self.dtype = np.int32
+
+
+class TestShape_int64(TestShape):
+
+    def init_dtype(self):
+        self.dtype = np.int64
+
+
+class TestShape_int8(TestShape):
+
+    def init_dtype(self):
+        self.dtype = np.int8
+
+
+class TestShape_uint8(TestShape):
+
+    def init_dtype(self):
+        self.dtype = np.uint8
+
+
+class TestShape_bool(TestShape):
+
+    def init_dtype(self):
+        self.dtype = bool
+
+
+if __name__ == '__main__':
+    unittest.main()