| 70 | } |
| 71 | |
| 72 | Status BatchCall::BatchRequest() { |
| 73 | TF_RETURN_IF_ERROR(ValidateShape(request)); |
| 74 | for (int i = 0; i < request[0].inputs.size(); ++i) { |
| 75 | auto& t = request[0].inputs[i].second; |
| 76 | switch (t.dtype()) { |
| 77 | case DT_FLOAT: { |
| 78 | auto batched_tensor = BatchOneInput<float>(request, i); |
| 79 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 80 | batched_tensor); |
| 81 | break; |
| 82 | } |
| 83 | case DT_DOUBLE: { |
| 84 | auto batched_tensor = BatchOneInput<double>(request, i); |
| 85 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 86 | batched_tensor); |
| 87 | break; |
| 88 | } |
| 89 | case DT_INT32: { |
| 90 | auto batched_tensor = BatchOneInput<int32_t>(request, i); |
| 91 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 92 | batched_tensor); |
| 93 | break; |
| 94 | } |
| 95 | case DT_UINT8: { |
| 96 | auto batched_tensor = BatchOneInput<uint8>(request, i); |
| 97 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 98 | batched_tensor); |
| 99 | break; |
| 100 | } |
| 101 | case DT_INT16: { |
| 102 | auto batched_tensor = BatchOneInput<int16>(request, i); |
| 103 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 104 | batched_tensor); |
| 105 | break; |
| 106 | } |
| 107 | case DT_UINT16: { |
| 108 | auto batched_tensor = BatchOneInput<uint16>(request, i); |
| 109 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 110 | batched_tensor); |
| 111 | break; |
| 112 | } |
| 113 | case DT_INT8: { |
| 114 | auto batched_tensor = BatchOneInput<int8>(request, i); |
| 115 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 116 | batched_tensor); |
| 117 | break; |
| 118 | } |
| 119 | case DT_COMPLEX64: { |
| 120 | auto batched_tensor = BatchOneInput<complex64>(request, i); |
| 121 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 122 | batched_tensor); |
| 123 | break; |
| 124 | } |
| 125 | case DT_COMPLEX128: { |
| 126 | auto batched_tensor = BatchOneInput<complex128>(request, i); |
| 127 | batched_request.inputs.emplace_back(request[0].inputs[i].first, |
| 128 | batched_tensor); |
| 129 | break; |
no test coverage detected