| /*! |
| * Copyright (c) 2015 by Contributors |
| * \file fully_connected.cc |
| * \brief fully connect operator |
| */ |
| #include "./fully_connected-inl.h" |
| #if MXNET_USE_NNPACK == 1 |
| #include "./nnpack/nnpack_fully_connected-inl.h" |
| #endif // MXNET_USE_NNPACK |
| |
| namespace mxnet { |
| namespace op { |
| template<> |
| Operator* CreateOp<cpu>(FullyConnectedParam param, int dtype, |
| std::vector<TShape> *in_shape, |
| std::vector<TShape> *out_shape, |
| Context ctx) { |
| Operator *op = NULL; |
| #if MXNET_USE_NNPACK == 1 |
| const size_t batch_size = (*in_shape)[0][0]; |
| // nnp_fully_connected_inference will do optimization for batch-size = 1 |
| // nnp_fully_connected_output will do optimization for batch-size > 1 |
| switch (dtype) { |
| case mshadow::kFloat32: |
| return new NNPACKFullyConnectedOp<cpu, float>(param); |
| default: |
| break; |
| } |
| #endif |
| switch (dtype) { |
| case mshadow::kFloat32: |
| op = new FullyConnectedOp<cpu, float>(param); |
| break; |
| case mshadow::kFloat64: |
| op = new FullyConnectedOp<cpu, double>(param); |
| break; |
| case mshadow::kFloat16: |
| LOG(FATAL) << "float16 fully connected layer is currently" |
| "only supported by CuDNN version."; |
| break; |
| default: |
| LOG(FATAL) << "Unsupported type " << dtype; |
| } |
| |
| return op; |
| } |
| |
| // DO_BIND_DISPATCH comes from operator_common.h |
| Operator *FullyConnectedProp::CreateOperatorEx(Context ctx, std::vector<TShape> *in_shape, |
| std::vector<int> *in_type) const { |
| std::vector<TShape> out_shape(1, TShape()), aux_shape; |
| std::vector<int> out_type(1, -1), aux_type; |
| CHECK(InferType(in_type, &out_type, &aux_type)); |
| CHECK(InferShape(in_shape, &out_shape, &aux_shape)); |
| DO_BIND_DISPATCH(CreateOp, param_, (*in_type)[0], in_shape, &out_shape, ctx); |
| } |
| |
| DMLC_REGISTER_PARAMETER(FullyConnectedParam); |
| |
| MXNET_REGISTER_OP_PROPERTY(FullyConnected, FullyConnectedProp) |
| .describe(R"code(Applies a linear transformation: :math:`Y = XW^T + b`. |
| |
| Shapes: |
| |
| - **data**: `(batch_size, input_dim)` |
| - **weight**: `(num_hidden, input_dim)` |
| - **bias**: `(num_hidden,)` |
| - **out**: `(batch_size, num_hidden)` |
| |
| The learnable parameters include both ``weight`` and ``bias``. |
| |
| If ``no_bias`` is set to be true, then the ``bias`` term is ignored. |
| |
| )code" ADD_FILELINE) |
| .add_argument("data", "NDArray-or-Symbol", "Input data.") |
| .add_argument("weight", "NDArray-or-Symbol", "Weight matrix.") |
| .add_argument("bias", "NDArray-or-Symbol", "Bias parameter.") |
| .add_arguments(FullyConnectedParam::__FIELDS__()); |
| } // namespace op |
| } // namespace mxnet |