experiments
/
STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Add Registration for non-stateful scatter_nd_min and scatter_nd_max. 

Manual import of #26923. Closes #26923. Fixes #20402

PiperOrigin-RevId: 314561995
Change-Id: Ibe1629d5ef769713d9058a6a72dc1421aa252ec4
This commit is contained in:
A. Unique TensorFlower 2020-06-03 10:54:24 -07:00 committed by TensorFlower Gardener
parent 0836e5e4ea
commit 23384f2ef1
24 changed files with 684 additions and 27 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

31
tensorflow/core/api_def/base_api/api_def_ResourceScatterNdMax.pbtxt Normal file
View File

@ -0,0 +1,31 @@
op {
graph_op_name: "ResourceScatterNdMax"
in_arg {
name: "ref"
description: <<END
A resource handle. Must be from a VarHandleOp.
END
}
in_arg {
name: "indices"
description: <<END
A Tensor. Must be one of the following types: int32, int64.
A tensor of indices into ref.
END
}
in_arg {
name: "updates"
description: <<END
A Tensor. Must have the same type as ref. A tensor of
values whose element wise max is taken with ref
END
}
attr {
name: "use_locking"
description: <<END
An optional bool. Defaults to True. If True, the assignment will
be protected by a lock; otherwise the behavior is undefined,
but may exhibit less contention.
END
}
}

31
tensorflow/core/api_def/base_api/api_def_ResourceScatterNdMin.pbtxt Normal file
View File

@ -0,0 +1,31 @@
op {
graph_op_name: "ResourceScatterNdMin"
in_arg {
name: "ref"
description: <<END
A resource handle. Must be from a VarHandleOp.
END
}
in_arg {
name: "indices"
description: <<END
A Tensor. Must be one of the following types: int32, int64.
A tensor of indices into ref.
END
}
in_arg {
name: "updates"
description: <<END
A Tensor. Must have the same type as ref. A tensor of
values whose element wise min is taken with ref.
END
}
attr {
name: "use_locking"
description: <<END
An optional bool. Defaults to True. If True, the assignment will
be protected by a lock; otherwise the behavior is undefined,
but may exhibit less contention.
END
}
}

40
tensorflow/core/api_def/base_api/api_def_ScatterNdMax.pbtxt Normal file
View File

@ -0,0 +1,40 @@
op {
graph_op_name: "ScatterNdMax"
visibility: HIDDEN
in_arg {
name: "ref"
description: <<END
A mutable Tensor. Should be from a Variable node.
END
}
in_arg {
name: "indices"
description: <<END
A Tensor. Must be one of the following types: int32, int64.
A tensor of indices into ref.
END
}
in_arg {
name: "updates"
description: <<END
A Tensor. Must have the same type as ref. A tensor of updated values
to add to ref.
END
}
out_arg {
name: "output_ref"
description: <<END
Same as ref. Returned as a convenience for operations that want
to use the updated values after the update is done.
END
}
attr {
name: "use_locking"
description: <<END
An optional bool. Defaults to True. If True, the assignment will
be protected by a lock; otherwise the behavior is undefined,
but may exhibit less contention.
END
}
summary: "Computes element-wise maximum."
}

40
tensorflow/core/api_def/base_api/api_def_ScatterNdMin.pbtxt Normal file
View File

@ -0,0 +1,40 @@
op {
graph_op_name: "ScatterNdMin"
visibility: HIDDEN
in_arg {
name: "ref"
description: <<END
A mutable Tensor. Should be from a Variable node.
END
}
in_arg {
name: "indices"
description: <<END
A Tensor. Must be one of the following types: int32, int64.
A tensor of indices into ref.
END
}
in_arg {
name: "updates"
description: <<END
A Tensor. Must have the same type as ref. A tensor of updated values
to add to ref.
END
}
out_arg {
name: "output_ref"
description: <<END
Same as ref. Returned as a convenience for operations that want
to use the updated values after the update is done.
END
}
attr {
name: "use_locking"
description: <<END
An optional bool. Defaults to True. If True, the assignment will
be protected by a lock; otherwise the behavior is undefined,
but may exhibit less contention.
END
}
summary: "Computes element-wise minimum."
}

27
tensorflow/core/api_def/base_api/api_def_TensorScatterMax.pbtxt Normal file
View File

@ -0,0 +1,27 @@
op {
graph_op_name: "TensorScatterMax"
in_arg {
name: "tensor"
description: <<END
Tensor to update.
END
}
in_arg {
name: "indices"
description: <<END
Index tensor.
END
}
in_arg {
name: "updates"
description: <<END
Updates to scatter into output.
END
}
out_arg {
name: "output"
description: <<END
A new tensor copied from tensor whose values are element-wise maximum between tensor and updates according to the indices.
END
}
}

27
tensorflow/core/api_def/base_api/api_def_TensorScatterMin.pbtxt Normal file
View File

@ -0,0 +1,27 @@
op {
graph_op_name: "TensorScatterMin"
in_arg {
name: "tensor"
description: <<END
Tensor to update.
END
}
in_arg {
name: "indices"
description: <<END
Index tensor.
END
}
in_arg {
name: "updates"
description: <<END
Updates to scatter into output.
END
}
out_arg {
name: "output"
description: <<END
A new tensor copied from tensor whose values are element-wise minimum between tensor and updates according to the indices.
END
}
}

4
tensorflow/core/api_def/python_api/api_def_ResourceScatterNdMax.pbtxt Normal file
View File

@ -0,0 +1,4 @@
op {
graph_op_name: "ResourceScatterNdMax"
visibility: HIDDEN
}

4
tensorflow/core/api_def/python_api/api_def_ResourceScatterNdMin.pbtxt Normal file
View File

@ -0,0 +1,4 @@
op {
graph_op_name: "ResourceScatterNdMin"
visibility: HIDDEN
}

6
tensorflow/core/api_def/python_api/api_def_TensorScatterMax.pbtxt Normal file
View File

@ -0,0 +1,6 @@
op {
graph_op_name: "TensorScatterMax"
endpoint {
name: "tensor_scatter_nd_max"
}
}

6
tensorflow/core/api_def/python_api/api_def_TensorScatterMin.pbtxt Normal file
View File

@ -0,0 +1,6 @@
op {
graph_op_name: "TensorScatterMin"
endpoint {
name: "tensor_scatter_nd_min"
}
}

87
tensorflow/core/kernels/scatter_nd_op.cc
View File

@ -368,6 +368,16 @@ class ScatterNdUpdateOp : public OpKernel {
REGISTER_RESOURCE_SCATTER_ND_UPDATE_KERNEL( \
type, dev, "ResourceScatterNdUpdate", scatter_nd_op::UpdateOp::ASSIGN);
#define REGISTER_SCATTER_ND_MIN_MAX(type, dev) \
REGISTER_SCATTER_ND_UPDATE_KERNEL(type, dev, "ScatterNdMax", \
scatter_nd_op::UpdateOp::MAX); \
REGISTER_SCATTER_ND_UPDATE_KERNEL(type, dev, "ScatterNdMin", \
scatter_nd_op::UpdateOp::MIN); \
REGISTER_RESOURCE_SCATTER_ND_UPDATE_KERNEL( \
type, dev, "ResourceScatterNdMin", scatter_nd_op::UpdateOp::MIN); \
REGISTER_RESOURCE_SCATTER_ND_UPDATE_KERNEL( \
type, dev, "ResourceScatterNdMax", scatter_nd_op::UpdateOp::MAX);
// Registers CPU kernels.
#define REGISTER_SCATTER_ND_ADD_SUB_CPU(type) \
REGISTER_SCATTER_ND_ADD_SUB(type, CPU);
@ -375,6 +385,9 @@ class ScatterNdUpdateOp : public OpKernel {
#define REGISTER_SCATTER_ND_UPDATE_CPU(type) \
REGISTER_SCATTER_ND_UPDATE(type, CPU);
#define REGISTER_SCATTER_ND_MIN_MAX_CPU(type) \
REGISTER_SCATTER_ND_MIN_MAX(type, CPU);
#define REGISTER_SCATTER_ND_CPU(type) REGISTER_SCATTER_ND(type, CPU);
#define REGISTER_SCATTER_ND_GPU(type) REGISTER_SCATTER_ND(type, GPU);
@ -386,6 +399,7 @@ TF_CALL_tstring(REGISTER_SCATTER_ND_UPDATE_CPU);
TF_CALL_bool(REGISTER_SCATTER_ND_ADD_SUB_CPU);
TF_CALL_bool(REGISTER_SCATTER_ND_UPDATE_CPU);
TF_CALL_bool(REGISTER_SCATTER_ND_CPU);
TF_CALL_REAL_NUMBER_TYPES(REGISTER_SCATTER_ND_MIN_MAX_CPU);
#define REGISTER_SCATTER_ND_TENSOR_UPDATE_TYPE_INDEX_TYPE(type, index_type, \
dev) \
@ -412,6 +426,22 @@ TF_CALL_bool(REGISTER_SCATTER_ND_CPU);
TensorScatterOp<dev##Device, type, index_type, \
scatter_nd_op::UpdateOp::SUB>)
#define REGISTER_SCATTER_ND_TENSOR_MIN_TYPE_INDEX_TYPE(type, index_type, dev) \
REGISTER_KERNEL_BUILDER(Name("TensorScatterMin") \
.Device(DEVICE_##dev) \
.TypeConstraint<type>("T") \
.TypeConstraint<index_type>("Tindices"), \
TensorScatterOp<dev##Device, type, index_type, \
scatter_nd_op::UpdateOp::MIN>)
#define REGISTER_SCATTER_ND_TENSOR_MAX_TYPE_INDEX_TYPE(type, index_type, dev) \
REGISTER_KERNEL_BUILDER(Name("TensorScatterMax") \
.Device(DEVICE_##dev) \
.TypeConstraint<type>("T") \
.TypeConstraint<index_type>("Tindices"), \
TensorScatterOp<dev##Device, type, index_type, \
scatter_nd_op::UpdateOp::MAX>)
#define REGISTER_SCATTER_ND_TENSOR_UPDATE_CPU(type) \
REGISTER_SCATTER_ND_TENSOR_UPDATE_TYPE_INDEX_TYPE(type, int32, CPU); \
REGISTER_SCATTER_ND_TENSOR_UPDATE_TYPE_INDEX_TYPE(type, int64, CPU);
@ -424,6 +454,14 @@ TF_CALL_bool(REGISTER_SCATTER_ND_CPU);
REGISTER_SCATTER_ND_TENSOR_SUB_TYPE_INDEX_TYPE(type, int32, CPU); \
REGISTER_SCATTER_ND_TENSOR_SUB_TYPE_INDEX_TYPE(type, int64, CPU);
#define REGISTER_SCATTER_ND_TENSOR_MIN_CPU(type) \
REGISTER_SCATTER_ND_TENSOR_MIN_TYPE_INDEX_TYPE(type, int32, CPU); \
REGISTER_SCATTER_ND_TENSOR_MIN_TYPE_INDEX_TYPE(type, int64, CPU);
#define REGISTER_SCATTER_ND_TENSOR_MAX_CPU(type) \
REGISTER_SCATTER_ND_TENSOR_MAX_TYPE_INDEX_TYPE(type, int32, CPU); \
REGISTER_SCATTER_ND_TENSOR_MAX_TYPE_INDEX_TYPE(type, int64, CPU);
#define REGISTER_SCATTER_ND_TENSOR_CPU(type) \
REGISTER_SCATTER_ND_TENSOR_UPDATE_CPU(type); \
REGISTER_SCATTER_ND_TENSOR_ADD_CPU(type); \
@ -431,6 +469,9 @@ TF_CALL_bool(REGISTER_SCATTER_ND_CPU);
// Register TensorScatterUpdate/Add/Sub for all number types.
TF_CALL_NUMBER_TYPES(REGISTER_SCATTER_ND_TENSOR_CPU);
// Register min/max operations only for Real number types
TF_CALL_REAL_NUMBER_TYPES(REGISTER_SCATTER_ND_TENSOR_MIN_CPU);
TF_CALL_REAL_NUMBER_TYPES(REGISTER_SCATTER_ND_TENSOR_MAX_CPU);
// Register only TensorScatterUpdate for string/bool types as well.
TF_CALL_tstring(REGISTER_SCATTER_ND_TENSOR_UPDATE_CPU);
TF_CALL_bool(REGISTER_SCATTER_ND_TENSOR_UPDATE_CPU);
@ -446,6 +487,9 @@ TF_CALL_bool(REGISTER_SCATTER_ND_TENSOR_UPDATE_CPU);
#define REGISTER_SCATTER_ND_UPDATE_GPU(type) \
REGISTER_SCATTER_ND_UPDATE(type, GPU);
#define REGISTER_SCATTER_ND_MIN_MAX_GPU(type) \
REGISTER_SCATTER_ND_MIN_MAX(type, GPU);
#define REGISTER_SCATTER_ND_ALL_GPU(type) \
REGISTER_SCATTER_ND_ADD_SUB_GPU(type); \
REGISTER_SCATTER_ND_UPDATE_GPU(type); \
@ -453,8 +497,11 @@ TF_CALL_bool(REGISTER_SCATTER_ND_TENSOR_UPDATE_CPU);
// TODO(b/155931747): Use HostMemory for int32
TF_CALL_int32(REGISTER_SCATTER_ND_ALL_GPU);
TF_CALL_int32(REGISTER_SCATTER_ND_MIN_MAX_GPU);
TF_CALL_int64(REGISTER_SCATTER_ND_ALL_GPU);
TF_CALL_int64(REGISTER_SCATTER_ND_MIN_MAX_GPU);
TF_CALL_GPU_NUMBER_TYPES(REGISTER_SCATTER_ND_ALL_GPU);
TF_CALL_GPU_NUMBER_TYPES(REGISTER_SCATTER_ND_MIN_MAX_GPU);
TF_CALL_complex64(REGISTER_SCATTER_ND_ALL_GPU);
TF_CALL_complex128(REGISTER_SCATTER_ND_ALL_GPU);
@ -467,12 +514,19 @@ TF_CALL_complex128(REGISTER_SCATTER_ND_ALL_GPU);
#define REGISTER_SCATTER_ND_UPDATE_SYCL(type) \
REGISTER_SCATTER_ND_UPDATE(type, SYCL);
#define REGISTER_SCATTER_ND_MIN_MAX_GPU(type) \
REGISTER_SCATTER_ND_MIN_MAX(type, SYCL);
TF_CALL_int32(REGISTER_SCATTER_ND_ADD_SUB_SYCL);
TF_CALL_int32(REGISTER_SCATTER_ND_UPDATE_SYCL);
TF_CALL_int32(REGISTER_SCATTER_ND_MIN_MAX_SYCL);
TF_CALL_bool(REGISTER_SCATTER_ND_UPDATE_SYCL);
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_ADD_SUB_SYCL);
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_UPDATE_SYCL);
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_MIN_MAX_SYCL);
#undef REGISTER_SCATTER_ND_ADD_SUB_SYCL
#undef REGISTER_SCATTER_ND_MIN_MAX_SYCL
#undef REGISTER_SCATTER_ND_UPDATE_SYCL
#endif // TENSORFLOW_USE_SYCL
@ -488,13 +542,27 @@ TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_UPDATE_SYCL);
REGISTER_SCATTER_ND_TENSOR_SUB_TYPE_INDEX_TYPE(type, int32, GPU); \
REGISTER_SCATTER_ND_TENSOR_SUB_TYPE_INDEX_TYPE(type, int64, GPU);
#define REGISTER_SCATTER_ND_TENSOR_MIN_GPU(type) \
REGISTER_SCATTER_ND_TENSOR_MIN_TYPE_INDEX_TYPE(type, int32, GPU); \
REGISTER_SCATTER_ND_TENSOR_MIN_TYPE_INDEX_TYPE(type, int64, GPU);
#define REGISTER_SCATTER_ND_TENSOR_MAX_GPU(type) \
REGISTER_SCATTER_ND_TENSOR_MAX_TYPE_INDEX_TYPE(type, int32, GPU); \
REGISTER_SCATTER_ND_TENSOR_MAX_TYPE_INDEX_TYPE(type, int64, GPU);
#define REGISTER_SCATTER_ND_TENSOR_GPU(type) \
REGISTER_SCATTER_ND_TENSOR_ADD_GPU(type); \
REGISTER_SCATTER_ND_TENSOR_UPDATE_GPU(type); \
REGISTER_SCATTER_ND_TENSOR_SUB_GPU(type);
#define REGISTER_SCATTER_ND_TENSOR_GPU_MIN_MAX(type) \
REGISTER_SCATTER_ND_TENSOR_MIN_GPU(type); \
REGISTER_SCATTER_ND_TENSOR_MAX_GPU(type);
TF_CALL_int64(REGISTER_SCATTER_ND_TENSOR_GPU);
TF_CALL_int64(REGISTER_SCATTER_ND_TENSOR_GPU_MIN_MAX);
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_TENSOR_GPU);
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_TENSOR_GPU_MIN_MAX);
TF_CALL_complex64(REGISTER_SCATTER_ND_TENSOR_GPU);
TF_CALL_complex128(REGISTER_SCATTER_ND_TENSOR_GPU);
@ -502,6 +570,9 @@ TF_CALL_complex128(REGISTER_SCATTER_ND_TENSOR_GPU);
#undef REGISTER_SCATTER_ND_ADD_SUB
#undef REGISTER_SCATTER_ND_ADD_SUB_CPU
#undef REGISTER_SCATTER_ND_ADD_SUB_GPU
#undef REGISTER_SCATTER_ND_MIN_MAX
#undef REGISTER_SCATTER_ND_MIN_MAX_CPU
#undef REGISTER_SCATTER_ND_MIN_MAX_GPU
#undef REGISTER_SCATTER_ND_UPDATE
#undef REGISTER_SCATTER_ND_UPDATE_CPU
#undef REGISTER_SCATTER_ND_UPDATE_GPU
@ -513,9 +584,13 @@ TF_CALL_complex128(REGISTER_SCATTER_ND_TENSOR_GPU);
#undef REGISTER_SCATTER_ND_TENSOR_UPDATE_TYPE_INDEX_TYPE
#undef REGISTER_SCATTER_ND_TENSOR_ADD_TYPE_INDEX_TYPE
#undef REGISTER_SCATTER_ND_TENSOR_SUB_TYPE_INDEX_TYPE
#undef REGISTER_SCATTER_ND_TENSOR_MIN_TYPE_INDEX_TYPE
#undef REGISTER_SCATTER_ND_TENSOR_MAX_TYPE_INDEX_TYPE
#undef REGISTER_SCATTER_ND_TENSOR_UPDATE_GPU
#undef REGISTER_SCATTER_ND_TENSOR_ADD_GPU
#undef REGISTER_SCATTER_ND_TENSOR_SUB_GPU
#undef REGISTER_SCATTER_ND_TENSOR_MIN_GPU
#undef REGISTER_SCATTER_ND_TENSOR_MAX_GPU
#undef REGISTER_SCATTER_ND_TENSOR_GPU
#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
@ -771,16 +846,28 @@ namespace functor {
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::ADD); \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::SUB)
#define DECLARE_GPU_SPECS_INDEX_MIN_MAX(T, Index) \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::MIN); \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::MAX)
#define DECLARE_GPU_SPECS(T) \
DECLARE_GPU_SPECS_INDEX(T, int32); \
DECLARE_GPU_SPECS_INDEX(T, int64)
#define DECLARE_GPU_SPECS_MIN_MAX(T) \
DECLARE_GPU_SPECS_INDEX_MIN_MAX(T, int32); \
DECLARE_GPU_SPECS_INDEX_MIN_MAX(T, int64)
TF_CALL_int32(DECLARE_GPU_SPECS);
TF_CALL_int32(DECLARE_GPU_SPECS_MIN_MAX);
TF_CALL_GPU_NUMBER_TYPES(DECLARE_GPU_SPECS);
TF_CALL_GPU_NUMBER_TYPES(DECLARE_GPU_SPECS_MIN_MAX);
TF_CALL_complex64(DECLARE_GPU_SPECS);
TF_CALL_complex128(DECLARE_GPU_SPECS);
#undef DECLARE_GPU_SPECS_MIN_MAX
#undef DECLARE_GPU_SPECS
#undef DECLARE_GPU_SPECS_INDEX_MIN_MAX
#undef DECLARE_GPU_SPECS_INDEX
#undef DECLARE_GPU_SPECS_INDEX_OP

2
tensorflow/core/kernels/scatter_nd_op.h
View File

@ -37,7 +37,7 @@ class OpKernelContext;
namespace scatter_nd_op {
enum class UpdateOp { ASSIGN, ADD, SUB };
enum class UpdateOp { ASSIGN, ADD, SUB, MIN, MAX };
} // namespace scatter_nd_op

80
tensorflow/core/kernels/scatter_nd_op_cpu_impl.h
View File

@ -47,38 +47,57 @@ class OpKernelContext;
// Specialization of UpdateExecutor to CPU
namespace update_executor {
template <typename Input, typename Update, typename Output,
template <typename T, typename Input, typename Update, typename Output,
scatter_nd_op::UpdateOp OP>
class UpdateExecutor {
public:
EIGEN_STRONG_INLINE static void Execute(Input value, Update update,
Output output);
EIGEN_STRONG_INLINE static void Execute(const T& device, Input value,
Update update, Output output);
};
template <typename Input, typename Update, typename Output>
class UpdateExecutor<Input, Update, Output, scatter_nd_op::UpdateOp::ASSIGN> {
template <typename T, typename Input, typename Update, typename Output>
class UpdateExecutor<T, Input, Update, Output,
scatter_nd_op::UpdateOp::ASSIGN> {
public:
EIGEN_STRONG_INLINE static void Execute(Input /* input */, Update update,
Output output) {
output = update;
EIGEN_STRONG_INLINE static void Execute(const T& device, Input /* input */,
Update update, Output output) {
output.device(device) = update;
}
};
template <typename Input, typename Update, typename Output>
class UpdateExecutor<Input, Update, Output, scatter_nd_op::UpdateOp::ADD> {
template <typename T, typename Input, typename Update, typename Output>
class UpdateExecutor<T, Input, Update, Output, scatter_nd_op::UpdateOp::ADD> {
public:
EIGEN_STRONG_INLINE static void Execute(Input /* input */, Update update,
Output output) {
output += update;
EIGEN_STRONG_INLINE static void Execute(const T& device, Input /* input */,
Update update, Output output) {
output.device(device) += update;
}
};
template <typename Input, typename Update, typename Output>
class UpdateExecutor<Input, Update, Output, scatter_nd_op::UpdateOp::SUB> {
template <typename T, typename Input, typename Update, typename Output>
class UpdateExecutor<T, Input, Update, Output, scatter_nd_op::UpdateOp::SUB> {
public:
EIGEN_STRONG_INLINE static void Execute(Input /* input */, Update update,
Output output) {
output -= update;
EIGEN_STRONG_INLINE static void Execute(const T& device, Input /* input */,
Update update, Output output) {
output.device(device) -= update;
}
};
template <typename T, typename Input, typename Update, typename Output>
class UpdateExecutor<T, Input, Update, Output, scatter_nd_op::UpdateOp::MIN> {
public:
EIGEN_STRONG_INLINE static void Execute(const T& device, Input /* input */,
Update update, Output output) {
output.device(device) = output.cwiseMin(update);
}
};
template <typename T, typename Input, typename Update, typename Output>
class UpdateExecutor<T, Input, Update, Output, scatter_nd_op::UpdateOp::MAX> {
public:
EIGEN_STRONG_INLINE static void Execute(const T& device, Input /* input */,
Update update, Output output) {
output.device(device) = output.cwiseMax(update);
}
};
@ -125,11 +144,12 @@ struct ScatterNdFunctor<CPUDevice, T, Index, OP, IXDIM> {
break;
} else {
auto input_chip = Toutput.template chip<0>(i);
auto output_chip = input_chip.device(d);
auto output_chip = input_chip;
auto update_chip = Tupdates.template chip<0>(loc);
update_executor::UpdateExecutor<
decltype(input_chip), decltype(update_chip), decltype(output_chip),
OP>::Execute(input_chip, update_chip, output_chip);
CPUDevice, decltype(input_chip), decltype(update_chip),
decltype(output_chip), OP>::Execute(d, input_chip, update_chip,
output_chip);
}
}
@ -159,11 +179,18 @@ struct ScatterNdFunctor<CPUDevice, T, Index, OP, IXDIM> {
REGISTER_SCATTER_ND_INDEX(type, scatter_nd_op::UpdateOp::ADD); \
REGISTER_SCATTER_ND_INDEX(type, scatter_nd_op::UpdateOp::SUB);
#define REGISTER_SCATTER_ND_MIN_MAX(type) \
REGISTER_SCATTER_ND_INDEX(type, scatter_nd_op::UpdateOp::MAX); \
REGISTER_SCATTER_ND_INDEX(type, scatter_nd_op::UpdateOp::MIN);
TF_CALL_ALL_TYPES(REGISTER_SCATTER_ND_UPDATE);
REGISTER_SCATTER_ND_INDEX(tstring, scatter_nd_op::UpdateOp::ADD);
TF_CALL_NUMBER_TYPES(REGISTER_SCATTER_ND_MATH);
TF_CALL_REAL_NUMBER_TYPES(REGISTER_SCATTER_ND_MIN_MAX);
TF_CALL_bool(REGISTER_SCATTER_ND_MATH);
#undef REGISTER_SCATTER_ND_MATH
#undef REGISTER_SCATTER_ND_MIN_MAX
#undef REGISTER_SCATTER_ND_UPDATE
#undef REGISTER_SCATTER_ND_INDEX
#undef REGISTER_SCATTER_ND_FULL
@ -209,11 +236,12 @@ struct ScatterNdFunctor<SYCLDevice, T, Index, OP, IXDIM> {
break;
} else {
auto input_chip = Toutput.template chip<0>(i);
auto output_chip = input_chip.device(d);
auto output_chip = input_chip;
auto update_chip = Tupdates.template chip<0>(loc);
update_executor::UpdateExecutor<
decltype(input_chip), decltype(update_chip), decltype(output_chip),
OP>::Execute(input_chip, update_chip, output_chip);
SYCLDevice, decltype(input_chip), decltype(update_chip),
decltype(output_chip), OP>::Execute(d, input_chip, update_chip,
output_chip);
}
}
@ -241,7 +269,9 @@ struct ScatterNdFunctor<SYCLDevice, T, Index, OP, IXDIM> {
#define REGISTER_SCATTER_ND_MATH_SYCL(type) \
REGISTER_SCATTER_ND_INDEX_SYCL(type, scatter_nd_op::UpdateOp::ADD); \
REGISTER_SCATTER_ND_INDEX_SYCL(type, scatter_nd_op::UpdateOp::SUB);
REGISTER_SCATTER_ND_INDEX_SYCL(type, scatter_nd_op::UpdateOp::SUB); \
REGISTER_SCATTER_ND_INDEX_SYCL(type, scatter_nd_op::UpdateOp::MIN); \
REGISTER_SCATTER_ND_INDEX_SYCL(type, scatter_nd_op::UpdateOp::MAX);
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_UPDATE_SYCL)
TF_CALL_GPU_NUMBER_TYPES_NO_HALF(REGISTER_SCATTER_ND_MATH_SYCL)

29
tensorflow/core/kernels/scatter_nd_op_gpu.cu.cc
View File

@ -55,6 +55,20 @@ struct LeftUpdate<T, scatter_nd_op::UpdateOp::SUB> {
}
};
template <typename T>
struct LeftUpdate<T, scatter_nd_op::UpdateOp::MAX> {
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC void operator()(T* out, const T& val) {
CudaAtomicMax(out, val);
}
};
template <typename T>
struct LeftUpdate<T, scatter_nd_op::UpdateOp::MIN> {
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC void operator()(T* out, const T& val) {
CudaAtomicMin(out, val);
}
};
// Specializations for std::complex, updating real and imaginary part
// individually. Even though this is not an atomic op anymore, it is safe
// because there is only one type of op per kernel.
@ -166,20 +180,33 @@ struct ScatterNdFunctor<GPUDevice, T, Index, op, IXDIM> {
#define DECLARE_GPU_SPECS_INDEX(T, Index) \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::ASSIGN); \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::ADD); \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::SUB)
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::SUB);
#define DECLARE_GPU_SPECS_INDEX_MINMAX(T, Index) \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::MAX) \
DECLARE_GPU_SPECS_INDEX_OP(T, Index, scatter_nd_op::UpdateOp::MIN);
#define DECLARE_GPU_SPECS(T) \
DECLARE_GPU_SPECS_INDEX(T, int32); \
DECLARE_GPU_SPECS_INDEX(T, int64)
#define DECLARE_GPU_SPECS_MINMAX(T) \
DECLARE_GPU_SPECS_INDEX_MINMAX(T, int32); \
DECLARE_GPU_SPECS_INDEX_MINMAX(T, int64)
TF_CALL_int32(DECLARE_GPU_SPECS);
TF_CALL_int32(DECLARE_GPU_SPECS_MINMAX);
TF_CALL_int64(DECLARE_GPU_SPECS);
TF_CALL_int64(DECLARE_GPU_SPECS_MINMAX);
TF_CALL_GPU_NUMBER_TYPES(DECLARE_GPU_SPECS);
TF_CALL_GPU_NUMBER_TYPES(DECLARE_GPU_SPECS_MINMAX);
TF_CALL_complex64(DECLARE_GPU_SPECS);
TF_CALL_complex128(DECLARE_GPU_SPECS);
#undef DECLARE_GPU_SPECS
#undef DECLARE_GPU_SPECS_MINMAX
#undef DECLARE_GPU_SPECS_INDEX
#undef DECLARE_GPU_SPECS_INDEX_MINMAX
#undef DECLARE_GPU_SPECS_INDEX_OP
} // namespace tensorflow

18
tensorflow/core/ops/array_ops.cc
View File

@ -3117,6 +3117,24 @@ REGISTER_OP("TensorScatterSub")
.Attr("Tindices: {int32, int64}")
.SetShapeFn(ScatterNdTensorShape);
REGISTER_OP("TensorScatterMin")
.Input("tensor: T")
.Input("indices: Tindices")
.Input("updates: T")
.Output("output: T")
.Attr("T: type")
.Attr("Tindices: {int32, int64}")
.SetShapeFn(ScatterNdTensorShape);
REGISTER_OP("TensorScatterMax")
.Input("tensor: T")
.Input("indices: Tindices")
.Input("updates: T")
.Output("output: T")
.Attr("T: type")
.Attr("Tindices: {int32, int64}")
.SetShapeFn(ScatterNdTensorShape);
REGISTER_OP("ScatterNdNonAliasingAdd")
.Input("input: T")
.Input("indices: Tindices")

38
tensorflow/core/ops/state_ops.cc
View File

@ -240,6 +240,24 @@ REGISTER_OP("ResourceScatterNdSub")
.Attr("use_locking: bool = true")
.SetShapeFn(shape_inference::ScatterNdUpdateShape);
REGISTER_OP("ResourceScatterNdMin")
.Input("ref: resource")
.Input("indices: Tindices")
.Input("updates: T")
.Attr("T: type")
.Attr("Tindices: {int32, int64}")
.Attr("use_locking: bool = true")
.SetShapeFn(shape_inference::ScatterNdUpdateShape);
REGISTER_OP("ResourceScatterNdMax")
.Input("ref: resource")
.Input("indices: Tindices")
.Input("updates: T")
.Attr("T: type")
.Attr("Tindices: {int32, int64}")
.Attr("use_locking: bool = true")
.SetShapeFn(shape_inference::ScatterNdUpdateShape);
REGISTER_OP("ScatterNdAdd")
.Input("ref: Ref(T)")
.Input("indices: Tindices")
@ -260,6 +278,26 @@ REGISTER_OP("ScatterNdSub")
.Attr("use_locking: bool = false")
.SetShapeFn(shape_inference::ScatterNdUpdateShape);
REGISTER_OP("ScatterNdMax")
.Input("ref: Ref(T)")
.Input("indices: Tindices")
.Input("updates: T")
.Output("output_ref: Ref(T)")
.Attr("T: numbertype")
.Attr("Tindices: {int32, int64}")
.Attr("use_locking: bool = false")
.SetShapeFn(shape_inference::ScatterNdUpdateShape);
REGISTER_OP("ScatterNdMin")
.Input("ref: Ref(T)")
.Input("indices: Tindices")
.Input("updates: T")
.Output("output_ref: Ref(T)")
.Attr("T: numbertype")
.Attr("Tindices: {int32, int64}")
.Attr("use_locking: bool = false")
.SetShapeFn(shape_inference::ScatterNdUpdateShape);
REGISTER_OP("CountUpTo")
.Input("ref: Ref(T)")
.Output("output: T")

27
tensorflow/python/kernel_tests/scatter_nd_ops_test.py
View File

@ -96,6 +96,14 @@ def _NumpyDiv(ref, indices, updates):
return _NumpyScatterNd(ref, indices, updates, lambda p, u: p / u)
def _NumpyMin(ref, indices, updates):
return _NumpyScatterNd(ref, indices, updates, np.minimum)
def _NumpyMax(ref, indices, updates):
return _NumpyScatterNd(ref, indices, updates, np.maximum)
class StatefulScatterNdTest(test.TestCase):
def _VariableRankTest(self,
@ -253,6 +261,8 @@ class StatefulScatterNdTest(test.TestCase):
"""This tests scatter_add using indices that repeat."""
self._ScatterRepeatIndicesTest(_NumpyAdd, state_ops.scatter_nd_add)
self._ScatterRepeatIndicesTest(_NumpySub, state_ops.scatter_nd_sub)
self._ScatterRepeatIndicesTest(_NumpyMin, state_ops.scatter_nd_min)
self._ScatterRepeatIndicesTest(_NumpyMax, state_ops.scatter_nd_max)
# TODO(ebrevdo): Re-enable when we need ScatterNdMul and ScatterNdDiv.
# self._ScatterRepeatIndicesTest(_NumpyMul, state_ops.scatter_nd_mul)
# self._ScatterRepeatIndicesTest(_NumpyDiv, state_ops.scatter_nd_div)
@ -276,6 +286,7 @@ class StatefulScatterNdTest(test.TestCase):
# scatter_nd ops is under control.
# tf.scatter_nd_mul, tf.scatter_nd_div,
for op in (state_ops.scatter_nd_add, state_ops.scatter_nd_sub,
state_ops.scatter_nd_min, state_ops.scatter_nd_max,
state_ops.scatter_nd_update):
params = np.array([1, 2, 3, 4, 5, 6]).astype(np.float32)
updates = np.array([-3, -4, -5]).astype(np.float32)
@ -763,6 +774,22 @@ class ScatterNdTensorTest(test.TestCase):
self.assertLess(err_added_wrt_updates, 2e-4)
self.assertLess(err_subbed_wrt_updates, 2e-4)
@test_util.run_in_graph_and_eager_modes
def testUpdateMinMax(self):
indices = constant_op.constant([[4], [3], [1], [7]])
updates = constant_op.constant([0, 2, -1, 1.2], dtype=dtypes.float32)
t = array_ops.ones([8], dtype=dtypes.float32)
assigned = array_ops.tensor_scatter_update(t, indices, updates)
min_result = array_ops.tensor_scatter_min(t, indices, updates)
max_result = array_ops.tensor_scatter_max(t, indices, updates)
self.assertAllEqual(assigned,
constant_op.constant([1, -1, 1, 2, 0, 1, 1, 1.2]))
self.assertAllEqual(min_result,
constant_op.constant([1, -1, 1, 1, 0, 1, 1, 1]))
self.assertAllEqual(max_result,
constant_op.constant([1, 1, 1, 2, 1, 1, 1, 1.2]))
def testTensorScatterUpdateWithForwarding(self):
@def_function.function
def _TestFn():

80
tensorflow/python/ops/resource_variable_ops.py
View File

@ -1202,6 +1202,78 @@ class BaseResourceVariable(variables.VariableV1, core.Tensor):
self.handle, indices, ops.convert_to_tensor(updates, self.dtype),
name=name))
def scatter_nd_max(self, indices, updates, name=None):
"""Updates this variable with the max of `tf.IndexedSlices` and itself.
`ref` is a `Tensor` with rank `P` and `indices` is a `Tensor` of rank `Q`.
`indices` must be integer tensor, containing indices into `ref`.
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.
The innermost dimension of `indices` (with length `K`) corresponds to
indices into elements (if `K = P`) or slices (if `K < P`) along the `K`th
dimension of `ref`.
`updates` is `Tensor` of rank `Q-1+P-K` with shape:
```
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
```
See `tf.scatter_nd` for more details about how to make updates to
slices.
Args:
indices: The indices to be used in the operation.
updates: The values to be used in the operation.
name: the name of the operation.
Returns:
The updated variable.
"""
return self._lazy_read(
gen_state_ops.resource_scatter_nd_max(
self.handle,
indices,
ops.convert_to_tensor(updates, self.dtype),
name=name))
def scatter_nd_min(self, indices, updates, name=None):
"""Updates this variable with the min of `tf.IndexedSlices` and itself.
`ref` is a `Tensor` with rank `P` and `indices` is a `Tensor` of rank `Q`.
`indices` must be integer tensor, containing indices into `ref`.
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.
The innermost dimension of `indices` (with length `K`) corresponds to
indices into elements (if `K = P`) or slices (if `K < P`) along the `K`th
dimension of `ref`.
`updates` is `Tensor` of rank `Q-1+P-K` with shape:
```
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
```
See `tf.scatter_nd` for more details about how to make updates to
slices.
Args:
indices: The indices to be used in the operation.
updates: The values to be used in the operation.
name: the name of the operation.
Returns:
The updated variable.
"""
return self._lazy_read(
gen_state_ops.resource_scatter_nd_min(
self.handle,
indices,
ops.convert_to_tensor(updates, self.dtype),
name=name))
def _strided_slice_assign(self, begin, end, strides, value, name, begin_mask,
end_mask, ellipsis_mask, new_axis_mask,
shrink_axis_mask):
@ -1949,6 +2021,14 @@ class _UnreadVariable(BaseResourceVariable):
return super(_UnreadVariable, self).scatter_nd_update(indices, updates,
name)
def scatter_nd_max(self, indices, updates, name=None):
with ops.control_dependencies([self._parent_op]):
return super(_UnreadVariable, self).scatter_nd_max(indices, updates, name)
def scatter_nd_min(self, indices, updates, name=None):
with ops.control_dependencies([self._parent_op]):
return super(_UnreadVariable, self).scatter_nd_min(indices, updates, name)
@property
def op(self):
"""The op for this variable."""

66
tensorflow/python/ops/variables.py
View File

@ -2467,6 +2467,72 @@ class RefVariable(VariableV1, core.Tensor):
return gen_state_ops.scatter_nd_update(
self._variable, indices, updates, use_locking=True, name=name)
def scatter_nd_max(self, indices, updates, name=None):
"""Updates this variable with the max of `tf.IndexedSlices` and itself.
`ref` is a `Tensor` with rank `P` and `indices` is a `Tensor` of rank `Q`.
`indices` must be integer tensor, containing indices into `ref`.
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.
The innermost dimension of `indices` (with length `K`) corresponds to
indices into elements (if `K = P`) or slices (if `K < P`) along the `K`th
dimension of `ref`.
`updates` is `Tensor` of rank `Q-1+P-K` with shape:
```
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
```
See `tf.scatter_nd` for more details about how to make updates to
slices.
Args:
indices: The indices to be used in the operation.
updates: The values to be used in the operation.
name: the name of the operation.
Returns:
A `Tensor` that will hold the new value of this variable after
the scattered addition has completed.
"""
return gen_state_ops.scatter_nd_max(
self._variable, indices, updates, use_locking=True, name=name)
def scatter_nd_min(self, indices, updates, name=None):
"""Updates this variable with the min of `tf.IndexedSlices` and itself.
`ref` is a `Tensor` with rank `P` and `indices` is a `Tensor` of rank `Q`.
`indices` must be integer tensor, containing indices into `ref`.
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.
The innermost dimension of `indices` (with length `K`) corresponds to
indices into elements (if `K = P`) or slices (if `K < P`) along the `K`th
dimension of `ref`.
`updates` is `Tensor` of rank `Q-1+P-K` with shape:
```
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
```
See `tf.scatter_nd` for more details about how to make updates to
slices.
Args:
indices: The indices to be used in the operation.
updates: The values to be used in the operation.
name: the name of the operation.
Returns:
A `Tensor` that will hold the new value of this variable after
the scattered addition has completed.
"""
return gen_state_ops.scatter_nd_min(
self._variable, indices, updates, use_locking=True, name=name)
def _strided_slice_assign(self, begin, end, strides, value, name, begin_mask,
end_mask, ellipsis_mask, new_axis_mask,
shrink_axis_mask):

8
tensorflow/tools/api/golden/v1/tensorflow.pbtxt
View File

@ -2344,6 +2344,14 @@ tf_module {
name: "tensor_scatter_nd_add"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "tensor_scatter_nd_max"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "tensor_scatter_nd_min"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "tensor_scatter_nd_sub"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "

24
tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
View File

@ -3520,6 +3520,14 @@ tf_module {
name: "ResourceScatterNdAdd"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
}
member_method {
name: "ResourceScatterNdMax"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
}
member_method {
name: "ResourceScatterNdMin"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
}
member_method {
name: "ResourceScatterNdSub"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
@ -3788,6 +3796,14 @@ tf_module {
name: "ScatterNdAdd"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
}
member_method {
name: "ScatterNdMax"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
}
member_method {
name: "ScatterNdMin"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
}
member_method {
name: "ScatterNdNonAliasingAdd"
argspec: "args=[\'input\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@ -4864,6 +4880,14 @@ tf_module {
name: "TensorScatterAdd"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "TensorScatterMax"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "TensorScatterMin"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "TensorScatterSub"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "

8
tensorflow/tools/api/golden/v2/tensorflow.pbtxt
View File

@ -1068,6 +1068,14 @@ tf_module {
name: "tensor_scatter_nd_add"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "tensor_scatter_nd_max"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "tensor_scatter_nd_min"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "tensor_scatter_nd_sub"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "

24
tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
View File

@ -3520,6 +3520,14 @@ tf_module {
name: "ResourceScatterNdAdd"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
}
member_method {
name: "ResourceScatterNdMax"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
}
member_method {
name: "ResourceScatterNdMin"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
}
member_method {
name: "ResourceScatterNdSub"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
@ -3788,6 +3796,14 @@ tf_module {
name: "ScatterNdAdd"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
}
member_method {
name: "ScatterNdMax"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
}
member_method {
name: "ScatterNdMin"
argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
}
member_method {
name: "ScatterNdNonAliasingAdd"
argspec: "args=[\'input\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@ -4864,6 +4880,14 @@ tf_module {
name: "TensorScatterAdd"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "TensorScatterMax"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "TensorScatterMin"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "TensorScatterSub"
argspec: "args=[\'tensor\', \'indices\', \'updates\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "

4
tensorflow/tools/compatibility/renames_v2.py
View File

@ -1128,6 +1128,10 @@ renames = {
'tf.compat.v1.scatter_nd_add',
'tf.scatter_nd_sub':
'tf.compat.v1.scatter_nd_sub',
'tf.scatter_nd_max':
'tf.compat.v1.scatter_nd_max',
'tf.scatter_nd_min':
'tf.compat.v1.scatter_nd_min',
'tf.scatter_nd_update':
'tf.compat.v1.scatter_nd_update',
'tf.scatter_sub':