[MLU] add floordiv kernel (#1344)

Author: PeiyuLau

backends/mlu/kernels/elementwise_floordiv_kernel.cc

@@ -0,0 +1,99 @@
+// Copyright (c) 2024 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 "kernels/funcs/mlu_baseop.h"
+#include "kernels/funcs/mlu_funcs.h"
+
+namespace custom_kernel {
+template <typename T, typename Context>
+void FloorDivideKernel(const Context& dev_ctx,
+                       const phi::DenseTensor& x,
+                       const phi::DenseTensor& y,
+                       phi::DenseTensor* out) {
+  dev_ctx.template Alloc<T>(out);
+
+  MLUCnnlTensorDesc input_x_desc(x);
+  MLUCnnlTensorDesc input_y_desc(y);
+  MLUCnnlTensorDesc output_desc(*out);
+
+  cnnlComputationPreference_t prefer = CNNL_COMPUTATION_HIGH_PRECISION;
+
+  // when input x and input y dtype are int64
+  // cast datatype to int32 for cnnlFloorDiv usage
+  Tensor x_temp, y_temp, out_temp;
+  x_temp.Resize(x.dims());
+  y_temp.Resize(y.dims());
+  out_temp.Resize(out->dims());
+  if (x.dtype() != DataType::INT64 && y.dtype() != DataType::INT64) {
+    MLUCnnl::FloorDiv(dev_ctx,
+                      prefer,
+                      input_x_desc.get(),
+                      GetBasePtr(&x),
+                      input_y_desc.get(),
+                      GetBasePtr(&y),
+                      output_desc.get(),
+                      GetBasePtr(out));
+  } else {
+    dev_ctx.template Alloc<int32_t>(&x_temp);
+    dev_ctx.template Alloc<int32_t>(&y_temp);
+    dev_ctx.template Alloc<int32_t>(&out_temp);
+    MLUCnnlTensorDesc x_temp_desc(x_temp);
+    MLUCnnlTensorDesc y_temp_desc(y_temp);
+    MLUCnnlTensorDesc out_temp_desc(out_temp);
+    cnnlCastDataType_t cast_int32 = GetCastDataType(x.dtype(), DataType::INT32);
+
+    MLUCnnl::Cast(dev_ctx,
+                  cast_int32,
+                  input_x_desc.get(),
+                  GetBasePtr(&x),
+                  x_temp_desc.get(),
+                  GetBasePtr(&x_temp));
+
+    MLUCnnl::Cast(dev_ctx,
+                  cast_int32,
+                  input_y_desc.get(),
+                  GetBasePtr(&y),
+                  y_temp_desc.get(),
+                  GetBasePtr(&y_temp));
+
+    MLUCnnl::FloorDiv(dev_ctx,
+                      prefer,
+                      x_temp_desc.get(),
+                      GetBasePtr(&x_temp),
+                      y_temp_desc.get(),
+                      GetBasePtr(&y_temp),
+                      out_temp_desc.get(),
+                      GetBasePtr(&out_temp));
+
+    cnnlCastDataType_t cast_int64 =
+        GetCastDataType(x_temp.dtype(), DataType::INT64);
+
+    MLUCnnl::Cast(dev_ctx,
+                  cast_int64,
+                  out_temp_desc.get(),
+                  GetBasePtr(&out_temp),
+                  output_desc.get(),
+                  GetBasePtr(out));
+  }
+}
+}  // namespace custom_kernel
+
+PD_REGISTER_PLUGIN_KERNEL(floor_divide,
+                          mlu,
+                          ALL_LAYOUT,
+                          custom_kernel::FloorDivideKernel,
+                          int,
+                          int64_t,
+                          float,
+                          phi::dtype::float16) {}

backends/mlu/tests/unittests/test_elementwise_floordiv_op_mlu.py

@@ -0,0 +1,62 @@
+# Copyright (c) 2024 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 numpy as np
+import unittest
+
+from tests.op_test import OpTest
+import paddle
+
+paddle.enable_static()
+
+
+class TestElementwiseFloorDiv(OpTest):
+    def setUp(self):
+        self.op_type = "elementwise_floordiv"
+        self.set_mlu()
+        self.init_dtype()
+        self.init_input_output()
+
+        self.inputs = {
+            "X": OpTest.np_dtype_to_base_dtype(self.x),
+            "Y": OpTest.np_dtype_to_base_dtype(self.y),
+        }
+        self.attrs = {}
+        self.outputs = {"Out": self.out}
+
+    def set_mlu(self):
+        self.__class__.use_custom_device = True
+        self.place = paddle.CustomPlace("mlu", 0)
+
+    def init_input_output(self):
+        self.x = np.random.uniform(1, 1000, [10, 10]).astype(self.dtype)
+        self.y = np.random.uniform(1, 1000, [10, 10]).astype(self.dtype)
+        self.out = np.floor_divide(self.x, self.y)
+
+    def init_dtype(self):
+        self.dtype = "int64"
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+class TestElementwiseFloorDiv2(TestElementwiseFloorDiv):
+    def init_dtype(self):
+        self.dtype = "int32"
+
+
+if __name__ == "__main__":
+    unittest.main()