!47535 fix cpu dropout seed

Merge pull request !47535 from 王禹程/fix_drop_seed

docs/api/api_python/ops/mindspore.ops.func_dropout.rst

@@ -3,7 +3,7 @@ mindspore.ops.dropout
 
 .. py:function:: mindspore.ops.dropout(x, p=0.5, seed0=0, seed1=0)
 
-    在训练期间，以服从伯努利分布的概率 `p` 随机将输入Tensor的某些值归零，起到减少神经元相关性的作用，避免过拟合。此概率与 `ops.dropout` 和 `nn.dropout` 中的含义相反。
+    在训练期间，以服从伯努利分布的概率 `p` 随机将输入Tensor的某些值归零，起到减少神经元相关性的作用，避免过拟合。此概率与 `ops.Dropout` 和 `nn.Dropout` 中的含义相反。
 
     参数：
         - **x** (Tensor) - dropout的输入，任意维度的Tensor，其数据类型为float16或float32。

mindspore/ccsrc/plugin/device/cpu/kernel/dropout_cpu_kernel.cc

@@ -51,6 +51,14 @@ bool DropoutCpuKernelMod::Init(const BaseOperatorPtr &base_operator, const std::
   if (keep_prob_ <= 0.0 || keep_prob_ > 1.0) {
     MS_LOG(EXCEPTION) << "For '" << kernel_name_ << ", the 'keep_prob' must be in (0.0, 1.0], but got " << keep_prob_;
   }
+  auto seed = GetValue<int64_t>(base_operator->GetAttr("Seed0"));
+  if (seed == 0) {
+    seed = GetValue<int64_t>(base_operator->GetAttr("Seed1"));
+    if (seed == 0) {
+      seed = time(nullptr);
+    }
+  }
+  seed_ = static_cast<uint64_t>(seed);
   return MatchKernelFunc(base_operator, inputs, outputs);
 }
 
@@ -78,8 +86,7 @@ bool DropoutCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressPtr> &in
   auto *output_addr = reinterpret_cast<T *>(outputs[0]->addr);
   auto mask_addr = reinterpret_cast<T *>(outputs[1]->addr);
   T scale = static_cast<T>(1.f / keep_prob_);
-  std::random_device rd;
-  std::default_random_engine generator(rd());
+  std::default_random_engine generator(seed_ + seed_offset_);
   std::uniform_real_distribution<float> uniform(0.f, 1.f);
   auto task = [input_addr, output_addr, mask_addr, scale, &uniform, &generator, this](size_t start, size_t end) {
     for (size_t i = start; i < end; i++) {
@@ -88,6 +95,7 @@ bool DropoutCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressPtr> &in
     }
   };
   ParallelLaunchAutoSearch(task, tensor_size_, this, &parallel_search_info_);
+  seed_offset_ += 1;
   return true;
 }
 

mindspore/ccsrc/plugin/device/cpu/kernel/dropout_cpu_kernel.h

@@ -53,6 +53,8 @@ class DropoutCpuKernelMod : public NativeCpuKernelMod, public MatchKernelHelper<
 
   ShapeVector input_shape_;
   float keep_prob_{0.0};
+  uint64_t seed_{0};
+  uint64_t seed_offset_{0};
   size_t tensor_size_{1};
 };
 }  // namespace kernel

mindspore/python/mindspore/ops/function/nn_func.py

@@ -1064,7 +1064,7 @@ def dropout(x, p=0.5, seed0=0, seed1=0):
     During training, randomly zeroes some of the elements of the input tensor
     with probability `p` from a Bernoulli distribution. It plays the role of
     reducing neuron correlation and avoid overfitting. The meaning of probability
-    here is opposite to that in `ops.dropout` and `nn.dropout`.
+    here is opposite to that in `ops.Dropout` and `nn.Dropout`.
 
     Args:
         x (Tensor): The input of Dropout, a Tensor of any shape with data type of float16 or float32.

tests/st/ops/cpu/test_dropout_op.py

@@ -20,6 +20,7 @@ import mindspore.context as context
 import mindspore.nn as nn
 from mindspore import Tensor
 from mindspore.ops import operations as P
+from mindspore import ops
 
 context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
 
@@ -87,7 +88,52 @@ def test_net2():
     print(mask)
 
 
+class Net3(nn.Cell):
+    def __init__(self):
+        super(Net3, self).__init__()
+        self.dropout = P.Dropout(keep_prob=0.5)
+
+    def construct(self, x):
+        return self.dropout(x)
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.env_onecard
+def test_net3():
+    """
+    Feature: test dropout mask diff by diff step.
+    Description: dropout.
+    Expectation: No exception.
+    """
+    x = np.arange(0, 12).reshape(3, 4).astype(np.float16)
+    dropout = Net3()
+    output1, mask1 = dropout(Tensor(x))
+    output2, mask2 = dropout(Tensor(x))
+    assert np.allclose(mask1.asnumpy(), mask2.asnumpy()) is False
+    assert np.allclose(output1.asnumpy(), output2.asnumpy()) is False
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.env_onecard
+def test_op1():
+    """
+    Feature: test dropout mask equal by equal seed.
+    Description: dropout.
+    Expectation: No exception.
+    """
+    x = Tensor(np.arange(0, 12).reshape(3, 4).astype(np.float16))
+    output1, mask1 = ops.dropout(x, p=0.5, seed0=1, seed1=100)
+    output2, mask2 = ops.dropout(x, p=0.5, seed0=1, seed1=100)
+
+    assert mask1.shape == mask2.shape
+    assert np.allclose(output1.asnumpy(), output2.asnumpy())
+    assert np.allclose(mask1.asnumpy(), mask2.asnumpy())
+
+
 if __name__ == '__main__':
     test_net()
     test_net1()
     test_net2()
+    test_op1()