diff options
20 files changed, 80 insertions, 135 deletions
diff --git a/tensorflow/cc/gradients/math_grad.cc b/tensorflow/cc/gradients/math_grad.cc index 5dcf00857d..1329b568ab 100644 --- a/tensorflow/cc/gradients/math_grad.cc +++ b/tensorflow/cc/gradients/math_grad.cc @@ -441,21 +441,20 @@ Status RealDivGrad(const Scope& scope, const Operation& op, } REGISTER_GRADIENT_OP("RealDiv", RealDivGrad); -Status UnsafeDivGrad(const Scope& scope, const Operation& op, - const std::vector<Output>& grad_inputs, - std::vector<Output>* grad_outputs) { +Status DivNoNanGrad(const Scope& scope, const Operation& op, + const std::vector<Output>& grad_inputs, + std::vector<Output>* grad_outputs) { auto x_1 = ConjugateHelper(scope, op.input(0)); auto x_2 = ConjugateHelper(scope, op.input(1)); // y = x_1 / x_2 // dy/dx_1 = 1/x_2 // dy/dx_2 = -x_1/x_2^2 - auto gx_1 = UnsafeDiv(scope, grad_inputs[0], x_2); - auto gx_2 = - Mul(scope, grad_inputs[0], - UnsafeDiv(scope, UnsafeDiv(scope, Neg(scope, x_1), x_2), x_2)); + auto gx_1 = DivNoNan(scope, grad_inputs[0], x_2); + auto gx_2 = Mul(scope, grad_inputs[0], + DivNoNan(scope, DivNoNan(scope, Neg(scope, x_1), x_2), x_2)); return BinaryGradCommon(scope, op, grad_outputs, gx_1, gx_2); } -REGISTER_GRADIENT_OP("UnsafeDiv", UnsafeDivGrad); +REGISTER_GRADIENT_OP("DivNoNan", DivNoNanGrad); Status SquaredDifferenceGrad(const Scope& scope, const Operation& op, const std::vector<Output>& grad_inputs, diff --git a/tensorflow/cc/gradients/math_grad_test.cc b/tensorflow/cc/gradients/math_grad_test.cc index 88aef1fab4..c16938322c 100644 --- a/tensorflow/cc/gradients/math_grad_test.cc +++ b/tensorflow/cc/gradients/math_grad_test.cc @@ -33,6 +33,7 @@ using ops::AddN; using ops::BatchMatMul; using ops::Const; using ops::Div; +using ops::DivNoNan; using ops::MatMul; using ops::Max; using ops::Maximum; @@ -48,7 +49,6 @@ using ops::SegmentSum; using ops::SquaredDifference; using ops::Sub; using ops::Sum; -using ops::UnsafeDiv; // TODO(andydavis) Test gradient function against numeric gradients output. // TODO(andydavis) As more gradients are added move common test functions @@ -854,13 +854,13 @@ TEST_F(NaryGradTest, RealDiv) { RunTest({x}, {x_shape}, {y}, {x_shape}); } -TEST_F(NaryGradTest, UnsafeDiv) { +TEST_F(NaryGradTest, DivNoNan) { { TensorShape x_shape({3, 2, 5}); const auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); // Test x / (1 + |x|) rather than x_1 / x_2 to avoid triggering large // division errors in the numeric estimator used by the gradient checker. - const auto y = UnsafeDiv( + const auto y = DivNoNan( scope_, x, Add(scope_, Const<float>(scope_, 1), Abs(scope_, x))); RunTest({x}, {x_shape}, {y}, {x_shape}); } @@ -868,7 +868,7 @@ TEST_F(NaryGradTest, UnsafeDiv) { // Return 0 gradient (rather than NaN) for division by zero. const auto x = Placeholder(scope_, DT_FLOAT); const auto zero = Const<float>(scope_, 0.0); - const auto y = UnsafeDiv(scope_, x, zero); + const auto y = DivNoNan(scope_, x, zero); std::vector<Output> grad_outputs; TF_EXPECT_OK(AddSymbolicGradients(scope_, {y}, {x}, &grad_outputs)); diff --git a/tensorflow/core/api_def/base_api/api_def_DivNoNan.pbtxt b/tensorflow/core/api_def/base_api/api_def_DivNoNan.pbtxt new file mode 100644 index 0000000000..5604a1a89e --- /dev/null +++ b/tensorflow/core/api_def/base_api/api_def_DivNoNan.pbtxt @@ -0,0 +1,9 @@ +op { + graph_op_name: "DivNoNan" + summary: "Returns 0 if the denominator is zero." + description: <<END + +*NOTE*: `DivNoNan` supports broadcasting. More about broadcasting +[here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html) +END +} diff --git a/tensorflow/core/api_def/base_api/api_def_UnsafeDiv.pbtxt b/tensorflow/core/api_def/base_api/api_def_UnsafeDiv.pbtxt deleted file mode 100644 index 82c913d15e..0000000000 --- a/tensorflow/core/api_def/base_api/api_def_UnsafeDiv.pbtxt +++ /dev/null @@ -1,5 +0,0 @@ -op { - graph_op_name: "UnsafeDiv" - summary: "Returns 0 if the denominator is zero." - description: "" -} diff --git a/tensorflow/core/api_def/python_api/api_def_DivNoNan.pbtxt b/tensorflow/core/api_def/python_api/api_def_DivNoNan.pbtxt new file mode 100644 index 0000000000..1bf3fba3c6 --- /dev/null +++ b/tensorflow/core/api_def/python_api/api_def_DivNoNan.pbtxt @@ -0,0 +1,4 @@ +op { + graph_op_name: "DivNoNan" + visibility: HIDDEN +} diff --git a/tensorflow/core/api_def/python_api/api_def_UnsafeDiv.pbtxt b/tensorflow/core/api_def/python_api/api_def_UnsafeDiv.pbtxt deleted file mode 100644 index 56caabcf3c..0000000000 --- a/tensorflow/core/api_def/python_api/api_def_UnsafeDiv.pbtxt +++ /dev/null @@ -1,4 +0,0 @@ -op { - graph_op_name: "UnsafeDiv" - visibility: HIDDEN -} diff --git a/tensorflow/core/kernels/cwise_op_div.cc b/tensorflow/core/kernels/cwise_op_div.cc index d6a2403816..35662e278f 100644 --- a/tensorflow/core/kernels/cwise_op_div.cc +++ b/tensorflow/core/kernels/cwise_op_div.cc @@ -24,8 +24,7 @@ REGISTER5(BinaryOp, CPU, "TruncateDiv", functor::safe_div, uint8, uint16, int16, int32, int64); REGISTER6(BinaryOp, CPU, "RealDiv", functor::div, float, Eigen::half, double, bfloat16, complex64, complex128); -REGISTER5(BinaryOp, CPU, "UnsafeDiv", functor::unsafe_div, float, double, int16, - int32, int64); +REGISTER2(BinaryOp, CPU, "DivNoNan", functor::div_no_nan, float, double); #if GOOGLE_CUDA REGISTER9(BinaryOp, GPU, "Div", functor::div, float, Eigen::half, double, uint8, diff --git a/tensorflow/core/kernels/cwise_ops.h b/tensorflow/core/kernels/cwise_ops.h index 1014519059..de164c1c09 100644 --- a/tensorflow/core/kernels/cwise_ops.h +++ b/tensorflow/core/kernels/cwise_ops.h @@ -154,8 +154,8 @@ struct functor_traits<safe_div_or_mod_op<T, DivOrMod>> { }; template <typename T> -struct unsafe_div_op { - EIGEN_EMPTY_STRUCT_CTOR(unsafe_div_op) +struct div_no_nan_op { + EIGEN_EMPTY_STRUCT_CTOR(div_no_nan_op) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T operator()(const T& a, const T& b) const { if (b != 0) { @@ -167,7 +167,7 @@ struct unsafe_div_op { }; template <typename T> -struct functor_traits<unsafe_div_op<T>> { +struct functor_traits<div_no_nan_op<T>> { enum { Cost = functor_traits<scalar_quotient_op<T>>::Cost + NumTraits<T>::AddCost, PacketAccess = false, @@ -742,7 +742,7 @@ struct safe_div : base<T, Eigen::internal::safe_div_or_mod_op< }; template <typename T> -struct unsafe_div : base<T, Eigen::internal::unsafe_div_op<T>> {}; +struct div_no_nan : base<T, Eigen::internal::div_no_nan_op<T>> {}; template <typename T> struct fmod : base<T, Eigen::internal::scalar_fmod_op<T>> {}; diff --git a/tensorflow/core/ops/compat/ops_history.v1.pbtxt b/tensorflow/core/ops/compat/ops_history.v1.pbtxt index d0dd01ad99..88feecee66 100644 --- a/tensorflow/core/ops/compat/ops_history.v1.pbtxt +++ b/tensorflow/core/ops/compat/ops_history.v1.pbtxt @@ -73443,41 +73443,6 @@ op { } } op { - name: "UnsafeDiv" - input_arg { - name: "x" - type_attr: "T" - } - input_arg { - name: "y" - type_attr: "T" - } - output_arg { - name: "z" - type_attr: "T" - } - attr { - name: "T" - type: "type" - allowed_values { - list { - type: DT_BFLOAT16 - type: DT_HALF - type: DT_FLOAT - type: DT_DOUBLE - type: DT_UINT8 - type: DT_INT8 - type: DT_UINT16 - type: DT_INT16 - type: DT_INT32 - type: DT_INT64 - type: DT_COMPLEX64 - type: DT_COMPLEX128 - } - } - } -} -op { name: "UnsortedSegmentMax" input_arg { name: "data" diff --git a/tensorflow/core/ops/math_grad.cc b/tensorflow/core/ops/math_grad.cc index 57499a6f1d..07f876cb90 100644 --- a/tensorflow/core/ops/math_grad.cc +++ b/tensorflow/core/ops/math_grad.cc @@ -495,18 +495,18 @@ Status RealDivGrad(const AttrSlice& attrs, FunctionDef* g) { } REGISTER_OP_GRADIENT("RealDiv", RealDivGrad); -Status UnsafeDivGrad(const AttrSlice& attrs, FunctionDef* g) { +Status DivNoNanGrad(const AttrSlice& attrs, FunctionDef* g) { // clang-format off return GradForBinaryCwise(g, { - {{"gx"}, "UnsafeDiv", {"dz", "y"}}, + {{"gx"}, "DivNoNan", {"dz", "y"}}, {{"nx"}, "Neg", {"x"}, {}, {"dz"}}, {{"y2"}, "Square", {"y"}, {}, {"dz"}}, - {{"nx_y2"}, "UnsafeDiv", {"nx", "y2"}}, + {{"nx_y2"}, "DivNoNan", {"nx", "y2"}}, {{"gy"}, "Mul", {"dz", "nx_y2"}}, // dz * (- x / y^2) }); // clang-format on } -REGISTER_OP_GRADIENT("UnsafeDiv", UnsafeDivGrad); +REGISTER_OP_GRADIENT("DivNoNan", DivNoNanGrad); Status PowGrad(const AttrSlice& attrs, FunctionDef* g) { // clang-format off diff --git a/tensorflow/core/ops/math_grad_test.cc b/tensorflow/core/ops/math_grad_test.cc index b0d1595c31..5ee79809ac 100644 --- a/tensorflow/core/ops/math_grad_test.cc +++ b/tensorflow/core/ops/math_grad_test.cc @@ -753,14 +753,14 @@ TEST_F(MathGradTest, Div) { } } -TEST_F(MathGradTest, UnsafeDiv) { +TEST_F(MathGradTest, DivNoNan) { auto x = test::AsTensor<float>( {0.f, -3.f, -2.f, -1.f, 0.f, 1.f, 2.f, 3.f, 0.f}, TensorShape({3, 3})); auto y = test::AsTensor<float>({-10.f, 0.f, 10.f}, TensorShape({3, 1})); Tensor dx; Tensor dy; { - SymGrad("UnsafeDiv", x, y, &dx, &dy); + SymGrad("DivNoNan", x, y, &dx, &dy); { auto g = [](float x, float y) { if (y == 0.f) { @@ -792,7 +792,7 @@ TEST_F(MathGradTest, UnsafeDiv) { } } { // Swap x and y. - SymGrad("UnsafeDiv", y, x, &dy, &dx); + SymGrad("DivNoNan", y, x, &dy, &dx); { auto g = [](float x, float y) { if (y == 0.f) { diff --git a/tensorflow/core/ops/math_ops.cc b/tensorflow/core/ops/math_ops.cc index 49646f1f3a..717263a9b0 100644 --- a/tensorflow/core/ops/math_ops.cc +++ b/tensorflow/core/ops/math_ops.cc @@ -392,8 +392,11 @@ Returns x * y element-wise. REGISTER_OP("Div").BINARY_MORE().SetShapeFn( shape_inference::BroadcastBinaryOpShapeFn); -REGISTER_OP("UnsafeDiv") - .BINARY_MORE() +REGISTER_OP("DivNoNan") + .Input("x: T") + .Input("y: T") + .Output("z: T") + .Attr("T: {float, double}") .SetShapeFn(shape_inference::BroadcastBinaryOpShapeFn); REGISTER_OP("FloorDiv") diff --git a/tensorflow/core/ops/math_ops_test.cc b/tensorflow/core/ops/math_ops_test.cc index ebeb048157..be4c3ed2b6 100644 --- a/tensorflow/core/ops/math_ops_test.cc +++ b/tensorflow/core/ops/math_ops_test.cc @@ -121,7 +121,7 @@ TEST(MathOpsTest, BroadcastBinaryOps_ShapeFn) { "Mod", "Mul", "NotEqual", "Pow", "Sub", "SquaredDifference", - "UnsafeDiv"}) { + "DivNoNan"}) { ShapeInferenceTestOp op(op_name); INFER_OK(op, "?;?", "?"); INFER_OK(op, "[1,2];?", "?"); diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt index 40b3dbe564..359bfa904f 100644 --- a/tensorflow/core/ops/ops.pbtxt +++ b/tensorflow/core/ops/ops.pbtxt @@ -34986,41 +34986,6 @@ op { } } op { - name: "UnsafeDiv" - input_arg { - name: "x" - type_attr: "T" - } - input_arg { - name: "y" - type_attr: "T" - } - output_arg { - name: "z" - type_attr: "T" - } - attr { - name: "T" - type: "type" - allowed_values { - list { - type: DT_BFLOAT16 - type: DT_HALF - type: DT_FLOAT - type: DT_DOUBLE - type: DT_UINT8 - type: DT_INT8 - type: DT_UINT16 - type: DT_INT16 - type: DT_INT32 - type: DT_INT64 - type: DT_COMPLEX64 - type: DT_COMPLEX128 - } - } - } -} -op { name: "UnsortedSegmentMax" input_arg { name: "data" diff --git a/tensorflow/python/ops/math_grad.py b/tensorflow/python/ops/math_grad.py index 2a7a2fd51f..8e11c4bce1 100644 --- a/tensorflow/python/ops/math_grad.py +++ b/tensorflow/python/ops/math_grad.py @@ -972,9 +972,9 @@ def _RealDivGrad(op, grad): grad * math_ops.realdiv(math_ops.realdiv(-x, y), y), ry), sy)) -@ops.RegisterGradient("UnsafeDiv") -def _UnsafeDivGrad(op, grad): - """UnsafeDiv op gradient.""" +@ops.RegisterGradient("DivNoNan") +def _DivNoNanGrad(op, grad): + """DivNoNan op gradient.""" x = op.inputs[0] y = op.inputs[1] sx = array_ops.shape(x) @@ -983,10 +983,10 @@ def _UnsafeDivGrad(op, grad): x = math_ops.conj(x) y = math_ops.conj(y) return (array_ops.reshape( - math_ops.reduce_sum(math_ops.unsafe_div(grad, y), rx), sx), + math_ops.reduce_sum(math_ops.div_no_nan(grad, y), rx), sx), array_ops.reshape( math_ops.reduce_sum( - grad * math_ops.unsafe_div(math_ops.unsafe_div(-x, y), y), + grad * math_ops.div_no_nan(math_ops.div_no_nan(-x, y), y), ry), sy)) diff --git a/tensorflow/python/ops/math_grad_test.py b/tensorflow/python/ops/math_grad_test.py index f9bb60e7fe..059c8ebd7e 100644 --- a/tensorflow/python/ops/math_grad_test.py +++ b/tensorflow/python/ops/math_grad_test.py @@ -231,11 +231,12 @@ class FloorModGradientTest(test.TestCase): self.assertLess(error, 1e-4) -class UnsafeDivGradientTest(test.TestCase): +class DivNoNanGradientTest(test.TestCase): def testBasicGradient(self): - inputs = constant_op.constant(np.arange(-3, 3), dtype=dtypes.float32) - outputs = math_ops.unsafe_div(inputs, 1 + math_ops.abs(inputs)) + inputs = constant_op.constant(np.arange(-3, 3), + dtype=dtypes.float32) + outputs = math_ops.div_no_nan(inputs, 1 + math_ops.abs(inputs)) with self.test_session(): error = gradient_checker.compute_gradient_error( inputs, @@ -244,9 +245,11 @@ class UnsafeDivGradientTest(test.TestCase): self.assertLess(error, 1e-4) def testGradientWithDenominatorIsZero(self): - x = constant_op.constant(np.arange(-3, 3), dtype=dtypes.float32) - y = array_ops.zeros_like(x, dtype=dtypes.float32) - outputs = math_ops.unsafe_div(x, y) + x = constant_op.constant(np.arange(-3, 3), + dtype=dtypes.float32) + y = array_ops.zeros_like(x, + dtype=dtypes.float32) + outputs = math_ops.div_no_nan(x, y) with self.test_session(): dx, dy = gradients.gradients(outputs, [x, y]) self.assertAllClose(dx.eval(), np.zeros(x.shape.as_list())) diff --git a/tensorflow/python/ops/math_ops.py b/tensorflow/python/ops/math_ops.py index 4033d5f079..67ea534639 100644 --- a/tensorflow/python/ops/math_ops.py +++ b/tensorflow/python/ops/math_ops.py @@ -1038,29 +1038,27 @@ def div(x, y, name=None): return _div_python2(x, y, name) -def unsafe_div(x, y, name=None): +@tf_export("div_no_nan") +def div_no_nan(x, y, name=None): """Computes an unsafe divide which returns 0 if the y is zero. - Note that the function uses Python 3 division operator semantics. - Args: - x: A `Tensor`. Must be one of the following types: - `float32`, `float64`, `int16`, `int32`, `int64`. + x: A `Tensor`. Must be one of the following types: `float32`, `float64`. y: A `Tensor` whose dtype is compatible with `x`. name: A name for the operation (optional). Returns: The element-wise value of the x divided by y. """ - with ops.name_scope(name, "unsafe_div", [x, y]) as name: + with ops.name_scope(name, "div_no_nan", [x, y]) as name: x = ops.convert_to_tensor(x, name="x") y = ops.convert_to_tensor(y, name="y", dtype=x.dtype.base_dtype) x_dtype = x.dtype.base_dtype y_dtype = y.dtype.base_dtype if x_dtype != y_dtype: - raise TypeError( - "x and y must have the same dtype, got %r != %r" % (x_dtype, y_dtype)) - return gen_math_ops.unsafe_div(x, y, name=name) + raise TypeError("x and y must have the same dtype, got %r != %r" % + (x_dtype, y_dtype)) + return gen_math_ops.div_no_nan(x, y, name=name) # TODO(aselle): This should be removed diff --git a/tensorflow/python/ops/math_ops_test.py b/tensorflow/python/ops/math_ops_test.py index 5fe7bbca11..5ac7e133d9 100644 --- a/tensorflow/python/ops/math_ops_test.py +++ b/tensorflow/python/ops/math_ops_test.py @@ -473,18 +473,19 @@ class DivAndModTest(test_util.TensorFlowTestCase): self.assertAllEqual(tf_result, expanded_nums) -class UnsafeDivTest(test_util.TensorFlowTestCase): +class DivNoNanTest(test_util.TensorFlowTestCase): def testBasic(self): - nums = np.arange(-10, 10, .25).reshape(80, 1) - divs = np.arange(-3, 3, .25).reshape(1, 24) + for dtype in [np.float32, np.float64]: + nums = np.arange(-10, 10, .25, dtype=dtype).reshape(80, 1) + divs = np.arange(-3, 3, .25, dtype=dtype).reshape(1, 24) - np_result = np.true_divide(nums, divs) - np_result[:, divs[0] == 0] = 0 + np_result = np.true_divide(nums, divs) + np_result[:, divs[0] == 0] = 0 - with self.test_session(): - tf_result = math_ops.unsafe_div(nums, divs).eval() - self.assertAllEqual(tf_result, np_result) + with self.test_session(): + tf_result = math_ops.div_no_nan(nums, divs).eval() + self.assertAllEqual(tf_result, np_result) if __name__ == "__main__": diff --git a/tensorflow/tools/api/golden/v1/tensorflow.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.pbtxt index 4de662fe33..8040eae01a 100644 --- a/tensorflow/tools/api/golden/v1/tensorflow.pbtxt +++ b/tensorflow/tools/api/golden/v1/tensorflow.pbtxt @@ -1005,6 +1005,10 @@ tf_module { argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " } member_method { + name: "div_no_nan" + argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " + } + member_method { name: "divide" argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " } diff --git a/tensorflow/tools/api/golden/v2/tensorflow.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.pbtxt index 4de662fe33..8040eae01a 100644 --- a/tensorflow/tools/api/golden/v2/tensorflow.pbtxt +++ b/tensorflow/tools/api/golden/v2/tensorflow.pbtxt @@ -1005,6 +1005,10 @@ tf_module { argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " } member_method { + name: "div_no_nan" + argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " + } + member_method { name: "divide" argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], " } |