[npu] add cumprod (PaddlePaddle#1377)

Author: wangna11BD

backends/npu/kernels/cumprod_kernel.cc

@@ -0,0 +1,47 @@
+/* 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. */
+
+#include "kernels/funcs/npu_funcs.h"
+#include "kernels/funcs/npu_op_runner.h"
+
+namespace custom_kernel {
+
+template <typename T, typename Context>
+void CumprodKernel(const Context& dev_ctx,
+                   const phi::DenseTensor& input,
+                   const int dim,
+                   bool exclusive,
+                   bool reverse,
+                   phi::DenseTensor* out) {
+  auto stream = dev_ctx.stream();
+  dev_ctx.template Alloc<T>(out);
+
+  NPUAttributeMap attr_input = {
+      {"axis", dim}, {"exclusive", exclusive}, {"reverse", reverse}};
+
+  const auto& runner = NpuOpRunner("Cumprod", {input}, {*out}, attr_input);
+  runner.Run(stream);
+}
+}  // namespace custom_kernel
+
+PD_REGISTER_PLUGIN_KERNEL(cumprod,
+                          npu,
+                          ALL_LAYOUT,
+                          custom_kernel::CumprodKernel,
+                          float,
+                          double,
+                          int,
+                          int64_t,
+                          phi::dtype::complex<float>,
+                          phi::dtype::complex<double>) {}

backends/npu/tests/unittests/test_cumprod_op_npu.py

@@ -0,0 +1,97 @@
+# 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 paddle
+import paddle.base.core as core
+import paddle.base as base
+
+paddle.enable_static()
+
+
+class TestCumprodOp(unittest.TestCase):
+    def run_cases(self):
+        data_np = np.arange(12).reshape(3, 4)
+        data = paddle.to_tensor(data_np)
+
+        y = paddle.cumprod(data)
+        z = np.cumprod(data_np)
+        self.assertTrue(np.array_equal(z, y.numpy()))
+
+        y = paddle.cumprod(data, dim=0)
+        z = np.cumprod(data_np, axis=0)
+        self.assertTrue(np.array_equal(z, y.numpy()))
+
+        y = paddle.cumprod(data, dim=-1)
+        z = np.cumprod(data_np, axis=-1)
+        self.assertTrue(np.array_equal(z, y.numpy()))
+
+        y = paddle.cumprod(data, dtype="float32")
+        self.assertTrue(y.dtype == core.VarDesc.VarType.FP32)
+
+        y = paddle.cumprod(data, dtype="int32")
+        self.assertTrue(y.dtype == core.VarDesc.VarType.INT32)
+
+        y = paddle.cumprod(data, dim=-2)
+        z = np.cumprod(data_np, axis=-2)
+        self.assertTrue(np.array_equal(z, y.numpy()))
+
+    def run_static(self, use_custom_device=False):
+        with base.program_guard(base.Program()):
+            data_np = np.random.random((100, 100)).astype(np.float32)
+            x = paddle.static.data("X", [100, 100])
+            y = paddle.cumprod(x, dim=0)
+            y2 = paddle.cumprod(x, dim=1)
+            y3 = paddle.cumprod(x, dim=-1)
+            y4 = paddle.cumprod(x, dim=0, dtype="float32")
+            y5 = paddle.cumprod(x, dim=0, dtype="int32")
+            y6 = paddle.cumprod(x, dim=-2)
+
+            place = base.CustomPlace("npu", 0) if use_custom_device else base.CPUPlace()
+            exe = base.Executor(place)
+            exe.run(base.default_startup_program())
+            out = exe.run(
+                feed={"X": data_np},
+                fetch_list=[y.name, y2.name, y3.name, y4.name, y5.name, y6.name],
+            )
+
+            z = np.cumprod(data_np, axis=0)
+            self.assertTrue(np.allclose(z, out[0]))
+            z = np.cumprod(data_np, axis=1)
+            self.assertTrue(np.allclose(z, out[1]))
+            z = np.cumprod(data_np, axis=-1)
+            self.assertTrue(np.allclose(z, out[2]))
+            self.assertTrue(out[3].dtype == np.float32)
+            self.assertTrue(out[4].dtype == np.int32)
+            z = np.cumprod(data_np, axis=-2)
+            self.assertTrue(np.allclose(z, out[5]))
+
+    def test_npu(self):
+        # Now, npu tests need setting paddle.enable_static()
+
+        self.run_static(use_custom_device=True)
+
+    def test_name(self):
+        with base.program_guard(base.Program()):
+            x = paddle.static.data("x", [3, 4])
+            y = paddle.cumprod(x, dim=0, name="out")
+            self.assertTrue("out" in y.name)
+
+
+if __name__ == "__main__":
+    unittest.main()