From 03530ead40c278e888cbaf7d0d4059af4ea39327 Mon Sep 17 00:00:00 2001
From: pipihugh <jifang5@h-partners.com>
Date: Thu, 17 Feb 2022 17:07:16 +0800
Subject: [PATCH] =?UTF-8?q?log1p=E7=AE=97=E5=AD=90=E7=A7=BB=E6=A4=8D?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 test/test_network_ops/test_log1p.py        | 84 ++++++++++++++++++++++
 torch_npu/csrc/aten/ops/Log1pKernelNpu.cpp | 53 ++++++++++++++
 2 files changed, 137 insertions(+)
 create mode 100644 test/test_network_ops/test_log1p.py
 create mode 100644 torch_npu/csrc/aten/ops/Log1pKernelNpu.cpp

diff --git a/test/test_network_ops/test_log1p.py b/test/test_network_ops/test_log1p.py
new file mode 100644
index 0000000000..878375d0fa
--- /dev/null
+++ b/test/test_network_ops/test_log1p.py
@@ -0,0 +1,84 @@
+# Copyright (c) 2020, Huawei Technologies.All rights reserved.
+#
+# Licensed under the BSD 3-Clause License  (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# https://opensource.org/licenses/BSD-3-Clause
+#
+# 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 torch
+import torch_npu
+import numpy as np
+
+from torch_npu.testing.common_utils import TestCase, run_tests
+from torch_npu.testing.common_device_type import instantiate_device_type_tests
+from torch_npu.testing.util_test import create_common_tensor
+ 
+class TestLog1p(TestCase):
+    def cpu_op_exec(self, input1):
+        output = torch.log1p(input1) 
+        output = output.numpy()
+        return output
+ 
+    def npu_op_exec(self, input1):
+        output = torch.log1p(input1) 
+        output = output.to("cpu")
+        output = output.numpy() 
+        return output  
+
+    def cpu_op_exec_(self, input1):
+        input1.log1p_() 
+        input1 = input1.numpy()
+        return input1
+ 
+    def npu_op_exec_(self, input1):
+        input1.log1p_() 
+        input1 = input1.to("cpu")
+        input1 = input1.numpy() 
+        return input1 
+
+    def cpu_op_exec_fp16(self, input1):
+        input1 = input1.to(torch.float32)
+        output = torch.log1p(input1)
+        output = output.numpy()
+        output = output.astype(np.float16)
+        return output
+
+    def test_log1p_common_shape_format(self, device):    
+        shape_format = [
+                [[np.float32, 0, 1]],
+                [[np.float32, 0, (64, 10)]],
+                [[np.float32, 4, (32, 1, 3, 3)]],
+                [[np.float32, 29, (10, 128)]]
+         ]
+        for item in shape_format:
+            cpu_input, npu_input = create_common_tensor(item[0], -1, 1)
+            cpu_output = self.cpu_op_exec(cpu_input)
+            npu_output = self.npu_op_exec(npu_input)
+            cpu_output1 = self.cpu_op_exec_(cpu_input)
+            npu_output1 = self.npu_op_exec_(npu_input)
+            self.assertRtolEqual(cpu_output, npu_output)
+            self.assertRtolEqual(cpu_output1, npu_output1)
+    
+    def test_log1p_float16_shape_format(self, device):
+        shape_format = [
+                [[np.float16, -1, 1]], 
+                [[np.float16, -1, (64, 10)]],    
+                [[np.float16, -1, (31, 1, 3)]]
+        ] 
+        for item in shape_format:
+            cpu_input, npu_input = create_common_tensor(item[0], -1, 1)
+            cpu_output = self.cpu_op_exec_fp16(cpu_input)
+            npu_output = self.npu_op_exec(npu_input)
+            self.assertRtolEqual(cpu_output, npu_output) 
+
+instantiate_device_type_tests(TestLog1p, globals(), except_for="cpu")
+if __name__ == "__main__":
+    run_tests()
+        
\ No newline at end of file
diff --git a/torch_npu/csrc/aten/ops/Log1pKernelNpu.cpp b/torch_npu/csrc/aten/ops/Log1pKernelNpu.cpp
new file mode 100644
index 0000000000..5b1505134c
--- /dev/null
+++ b/torch_npu/csrc/aten/ops/Log1pKernelNpu.cpp
@@ -0,0 +1,53 @@
+// Copyright (c) 2020, Huawei Technologies.All rights reserved.
+//
+// Licensed under the BSD 3-Clause License  (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// 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 "torch_npu/csrc/framework/utils/OpAdapter.h"
+#include "torch_npu/csrc/framework/utils/OpTemplate.h"
+#include "torch_npu/csrc/framework/utils/KernelNpuOutputSize.h"
+#include "torch_npu/csrc/aten/NPUNativeFunctions.h"
+
+namespace at_npu { 
+namespace native {
+
+at::Tensor& log1p_out_npu_nocheck(const at::Tensor& self, at::Tensor& result){   
+  OpCommand cmd;
+  cmd.Name("Log1p")
+      .Input(self)
+      .Output(result)
+      .Run();
+  return result; 
+}
+
+at::Tensor& NPUNativeFunctions::log1p_out(const at::Tensor& self, at::Tensor& result){ 
+  OpPreparation::CheckOut(
+      {self},
+      result,
+      self);
+  OpPipeWithDefinedOut pipe;
+  return pipe.CheckMemory({self}, {result})
+   .Func([&self](at::Tensor& result){log1p_out_npu_nocheck(self, result);})
+   .Call(result);
+}
+
+at::Tensor NPUNativeFunctions::log1p(const at::Tensor& self) {
+  at::Tensor result = OpPreparation::ApplyTensor(self);
+  log1p_out_npu_nocheck(self, result);
+  return result;
+}
+
+at::Tensor& NPUNativeFunctions::log1p_(at::Tensor& self) {
+  log1p_out(self, self);
+  return self;
+}
+}}
-- 
Gitee