log_softmax_op_v1

Author: juneweng

paddle/fluid/operators/log_softmax_op_npu.cc

@@ -13,7 +13,6 @@
 // limitations under the License.
 
 #include "paddle/fluid/operators/log_softmax_op.h"
-#include "paddle/fluid/framework/tensor_util.h"
 #include "paddle/fluid/operators/npu_op_runner.h"
 namespace paddle {
 namespace operators {
@@ -43,9 +42,4 @@ namespace plat = paddle::platform;
 
 REGISTER_OP_NPU_KERNEL(
     log_softmax,
-    ops::LogSoftmaxNPUKernel<paddle::platform::NPUDeviceContext, float>,
-    ops::LogSoftmaxNPUKernel<paddle::platform::NPUDeviceContext, double>,
-    // ops::LogSoftmaxNPUKernel<paddle::platform::NPUDeviceContext, int>, //
-    // used to debug
-    ops::LogSoftmaxNPUKernel<paddle::platform::NPUDeviceContext,
-                             paddle::platform::float16>);
+    ops::LogSoftmaxNPUKernel<paddle::platform::NPUDeviceContext, float>);

python/paddle/fluid/tests/unittests/npu/test_log_softmax_op_npu.py

@@ -22,27 +22,11 @@
 import paddle.fluid as fluid
 from paddle.fluid import core
 import paddle.nn.functional as F
+from test_log_softmax import ref_log_softmax, test_log_softmax
 paddle.enable_static()
 np.random.seed(10)
 
 
-def ref_log_softmax(x):
-    shiftx = (x - np.max(x))
-    out = shiftx - np.log(np.exp(shiftx).sum())
-    return out
-
-
-def ref_log_softmax_grad(x, axis):
-    if axis < 0:
-        axis += len(x.shape)
-    out = np.apply_along_axis(ref_log_softmax, axis, x)
-    axis_dim = x.shape[axis]
-    dout = np.full_like(x, fill_value=1. / x.size)
-    dx = dout - np.exp(out) * dout.copy().sum(axis=axis, keepdims=True).repeat(
-        axis_dim, axis=axis)
-    return dx
-
-
 class TestLogSoftmaxNPUOp(OpTest):
     def setUp(self):
         self.set_npu()