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1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
2 
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6 
7     http://www.apache.org/licenses/LICENSE-2.0
8 
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 
16 // See docs in ../ops/array_ops.cc.
17 
18 #include "tensorflow/core/framework/bounds_check.h"
19 #include "tensorflow/core/framework/op_kernel.h"
20 #include "tensorflow/core/framework/register_types.h"
21 #include "tensorflow/core/framework/tensor.h"
22 #include "tensorflow/core/framework/variant.h"
23 #include "tensorflow/core/framework/variant_encode_decode.h"
24 #include "tensorflow/core/kernels/gather_functor.h"
25 #include "tensorflow/core/platform/mem.h"
26 #include "tensorflow/core/platform/types.h"
27 #include "tensorflow/core/util/util.h"
28 
29 namespace tensorflow {
30 
31 typedef Eigen::ThreadPoolDevice CPUDevice;
32 typedef Eigen::GpuDevice GPUDevice;
33 
34 template <typename Device, typename T, typename Index>
35 class GatherOp : public OpKernel {
36  public:
37   //   QUESTION: It'd be nice to support DT_INT16, DT_UINT8,
38   //   etc. here for the type of the second input argument.  Should
39   //   we have the framework do some sort of integer promotion
40   //   automatically, or should that be something that users have to
41   //   do explicitly with a conversion operator in the graph?
GatherOp(OpKernelConstruction * c)42   explicit GatherOp(OpKernelConstruction* c) : OpKernel(c) {}
43 
Compute(OpKernelContext * c)44   void Compute(OpKernelContext* c) override {
45     const Tensor& params = c->input(0);
46     const Tensor& indices = c->input(1);
47     OP_REQUIRES(
48         c, TensorShapeUtils::IsVectorOrHigher(params.shape()),
49         errors::InvalidArgument("params must be at least 1 dimensional"));
50 
51     // GatherV2 added an axis argument. For backwards compatibility with Gather,
52     // fall back to axis 0 if the op does not have an axis input.
53     int64 axis = 0;
54     if (c->num_inputs() == 3) {
55       const Tensor& axis_tensor = c->input(2);
56       OP_REQUIRES(c, TensorShapeUtils::IsScalar(axis_tensor.shape()),
57                   errors::InvalidArgument("axis must be scalar"));
58 
59       if (axis_tensor.dtype() == DT_INT32) {
60         axis = axis_tensor.scalar<int32>()();
61       } else if (axis_tensor.dtype() == DT_INT64) {
62         axis = axis_tensor.scalar<int64>()();
63       } else {
64         OP_REQUIRES(c, false,
65                     errors::InvalidArgument("axis must be int32 or int64."));
66       }
67     }
68 
69     OP_REQUIRES(
70         c, axis >= -params.dims() && axis < params.dims(),
71         errors::InvalidArgument("Expected axis in the range [", -params.dims(),
72                                 ", ", params.dims(), "), but got ", axis));
73     if (axis < 0) {
74       axis = params.dims() + axis;
75     }
76 
77     // Check that we have enough index space
78     const int64 gather_dim_size = params.dim_size(axis);
79     const int64 N = indices.NumElements();
80     OP_REQUIRES(
81         c, gather_dim_size <= std::numeric_limits<Index>::max(),
82         errors::InvalidArgument("params.shape[", axis, "] too large for ",
83                                 DataTypeString(DataTypeToEnum<Index>::v()),
84                                 " indexing: ", gather_dim_size, " > ",
85                                 std::numeric_limits<Index>::max()));
86 
87     // The result shape is params.shape[0:axis] + indices.shape +
88     // params.shape[axis + 1:].
89     TensorShape result_shape;
90     int64 outer_size = 1;
91     int64 inner_size = 1;
92     for (int i = 0; i < axis; i++) {
93       result_shape.AddDim(params.dim_size(i));
94       outer_size *= params.dim_size(i);
95     }
96     result_shape.AppendShape(indices.shape());
97     for (int i = axis + 1; i < params.dims(); i++) {
98       result_shape.AddDim(params.dim_size(i));
99       inner_size *= params.dim_size(i);
100     }
101 
102     Tensor* out = nullptr;
103     OP_REQUIRES_OK(c, c->allocate_output(0, result_shape, &out));
104     if (N > 0 && outer_size > 0 && inner_size > 0) {
105       auto params_flat =
106           params.shaped<T, 3>({outer_size, gather_dim_size, inner_size});
107       auto indices_flat = indices.flat<Index>();
108       auto out_flat = out->shaped<T, 3>({outer_size, N, inner_size});
109 
110       functor::GatherFunctor<Device, T, Index> functor;
111       int64 bad_i = functor(c, params_flat, indices_flat, out_flat);
112 
113       OP_REQUIRES(
114           c, bad_i < 0,
115           errors::InvalidArgument(
116               "indices", SliceDebugString(indices.shape(), bad_i), " = ",
117               indices_flat(bad_i), " is not in [0, ", gather_dim_size, ")"));
118     }
119   }
120 };
121 
122 #define REGISTER_GATHER_FULL(dev, type, index_type)                    \
123   REGISTER_KERNEL_BUILDER(Name("Gather")                               \
124                               .Device(DEVICE_##dev)                    \
125                               .TypeConstraint<type>("Tparams")         \
126                               .TypeConstraint<index_type>("Tindices"), \
127                           GatherOp<dev##Device, type, index_type>);    \
128   REGISTER_KERNEL_BUILDER(Name("GatherV2")                             \
129                               .Device(DEVICE_##dev)                    \
130                               .TypeConstraint<type>("Tparams")         \
131                               .TypeConstraint<index_type>("Tindices")  \
132                               .HostMemory("axis"),                     \
133                           GatherOp<dev##Device, type, index_type>)
134 
135 #define REGISTER_GATHER_ALL_INDICES(dev, type) \
136   REGISTER_GATHER_FULL(dev, type, int32);      \
137   REGISTER_GATHER_FULL(dev, type, int64)
138 
139 #define REGISTER_GATHER_CPU(type) REGISTER_GATHER_ALL_INDICES(CPU, type)
140 
141 // Registration of the CPU implementations.
142 TF_CALL_ALL_TYPES(REGISTER_GATHER_CPU);
143 TF_CALL_QUANTIZED_TYPES(REGISTER_GATHER_CPU);
144 TF_CALL_quint16(REGISTER_GATHER_CPU);
145 TF_CALL_qint16(REGISTER_GATHER_CPU);
146 TF_CALL_uint32(REGISTER_GATHER_CPU);
147 TF_CALL_uint64(REGISTER_GATHER_CPU);
148 
149 #undef REGISTER_GATHER_CPU
150 
151 #if GOOGLE_CUDA
152 
153 // Registration of the GPU implementations.
154 #define REGISTER_GATHER_GPU(type) REGISTER_GATHER_ALL_INDICES(GPU, type)
155 
156 TF_CALL_bool(REGISTER_GATHER_GPU);
157 TF_CALL_int32(REGISTER_GATHER_GPU);
158 TF_CALL_int64(REGISTER_GATHER_GPU);
159 TF_CALL_GPU_NUMBER_TYPES(REGISTER_GATHER_GPU);
160 TF_CALL_complex64(REGISTER_GATHER_GPU);
161 TF_CALL_complex128(REGISTER_GATHER_GPU);
162 
163 #undef REGISTER_GATHER_GPU
164 
165 #endif  // GOOGLE_CUDA
166 
167 #undef REGISTER_GATHER_ALL_INDICES
168 #undef REGISTER_GATHER_FULL
169 
170 }  // namespace tensorflow
171