implement det sign

Author: Jopyth

python/mxnet/ndarray/ndarray.py

@@ -1246,6 +1246,14 @@ def sign(self, *args, **kwargs):
         """
         return op.sign(self, *args, **kwargs)
 
+    def det_sign(self, *args, **kwargs):
+        """Convenience fluent method for :py:func:`det_sign`.
+
+        The arguments are the same as for :py:func:`det_sign`, with
+        this array as data.
+        """
+        return op.det_sign(self, *args, **kwargs)
+
     def flatten(self, *args, **kwargs):
         """Convenience fluent method for :py:func:`flatten`.
 

python/mxnet/symbol/symbol.py

@@ -1974,6 +1974,14 @@ def sign(self, *args, **kwargs):
         """
         return op.sign(self, *args, **kwargs)
 
+    def det_sign(self, *args, **kwargs):
+        """Convenience fluent method for :py:func:`det_sign`.
+
+        The arguments are the same as for :py:func:`det_sign`, with
+        this array as data.
+        """
+        return op.det_sign(self, *args, **kwargs)
+
     def flatten(self, *args, **kwargs):
         """Convenience fluent method for :py:func:`flatten`.
 

smd_hpi/tests/test_functions.py

@@ -0,0 +1,17 @@
+import mxnet as mx
+import numpy as np
+from mxnet import autograd
+from mxnet.test_utils import assert_almost_equal
+
+
+def test_det_sign():
+    exp_y = np.array([1.0, 1.0, -1.0])
+    exp_grad = np.array([1.0, 1.0, 1.0])
+
+    x = mx.nd.array([0.0, 0.6, -0.3])
+    x.attach_grad()
+    with autograd.record():
+        y = x.det_sign()
+        assert_almost_equal(exp_y, y.asnumpy())
+    y.backward()
+    assert_almost_equal(exp_grad, x.grad.asnumpy())

src/operator/mshadow_op.h

@@ -299,6 +299,21 @@ struct sign : public mxnet_op::tunable {
 
 MXNET_UNARY_MATH_OP_NC(sign_grad, DType(0));
 
+/*! \brief used for generate element of sign */
+struct det_sign : public mxnet_op::tunable {
+  template<typename DType>
+  MSHADOW_XINLINE static typename enable_if<!is_unsigned<DType>::value, DType>::type
+  Map(DType a) {
+    if (a < DType(0)) return DType(-DType(1));
+    return DType(1);
+  }
+  template<typename DType>
+  MSHADOW_XINLINE static typename enable_if<is_unsigned<DType>::value, DType>::type
+  Map(DType a) {
+    return DType(1);
+  }
+};
+
 /*! \brief used for generate element of power */
 MXNET_BINARY_MATH_OP(power, math::pow(a, b));
 

src/operator/operator_tune.cc

@@ -270,6 +270,8 @@ IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::abs);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::sign);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_BWD(mxnet::op::mshadow_op::sign);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_BWD(mxnet::op::mshadow_op::sign_grad);  // NOLINT()
+IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::det_sign);  // NOLINT()
+IMPLEMENT_UNARY_WORKLOAD_BWD(mxnet::op::mshadow_op::det_sign);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::round);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::floor);  // NOLINT()
 IMPLEMENT_UNARY_WORKLOAD_FWD(mxnet::op::mshadow_op::trunc);  // NOLINT()

src/operator/tensor/elemwise_unary_op_basic.cc

@@ -687,6 +687,25 @@ The storage type of ``sign`` output depends upon the input storage type:
 
 MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU(_backward_sign, unary_bwd<mshadow_op::sign_grad>);
 
+// det_sign
+MXNET_OPERATOR_REGISTER_UNARY_WITH_RSP(det_sign, cpu, mshadow_op::det_sign)
+MXNET_ADD_SPARSE_OP_ALIAS(det_sign)
+.describe(R"code(Returns element-wise sign of the input (but with +1 for 0 values and Straigth Through Estimator).
+
+Example::
+
+   det_sign([-2, 0, 3]) = [-1, 1, 1]
+
+The storage type of ``det_sign`` output depends upon the input storage type:
+
+   - det_sign(default) = default
+   - det_sign(row_sparse) = row_sparse
+
+)code" ADD_FILELINE)
+.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_det_sign"});
+
+MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU(_backward_det_sign, unary_bwd<mshadow_op::identity_grad>);
+
 // round
 MXNET_OPERATOR_REGISTER_UNARY_WITH_RSP_CSR(round, cpu, mshadow_op::round)
 .describe(R"code(Returns element-wise rounded value to the nearest integer of the input.

src/operator/tensor/elemwise_unary_op_basic.cu

@@ -159,6 +159,15 @@ NNVM_REGISTER_OP(_backward_sign)
 .set_attr<FCompute>("FCompute<gpu>", ElemwiseBinaryOp::Compute<
   gpu, unary_bwd<mshadow_op::sign_grad> >);
 
+// det_sign
+NNVM_REGISTER_OP(det_sign)
+.set_attr<FCompute>("FCompute<gpu>", UnaryOp::Compute<gpu, mshadow_op::det_sign>)
+.set_attr<FComputeEx>("FComputeEx<gpu>", UnaryOp::ComputeEx<gpu, mshadow_op::det_sign>);
+
+NNVM_REGISTER_OP(_backward_det_sign)
+.set_attr<FCompute>("FCompute<gpu>", ElemwiseBinaryOp::Compute<
+  gpu, unary_bwd<mshadow_op::identity_grad> >);
+
 // round
 NNVM_REGISTER_OP(round)
 .set_attr<FCompute>("FCompute<gpu>", UnaryOp::Compute<gpu, mshadow_op::round>)