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Results 1 - 6 of 6 for needType (0.12 sec)
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src/cmd/cgo/gcc.go
continue } n := &Name{ Go: info.typedef, C: info.typedef, } f.Name[info.typedef] = n f.NamePos[n] = info.pos } needType := p.guessKinds(f) if len(needType) > 0 { p.loadDWARF(f, &conv, needType) } // In godefs mode we're OK with the typedefs, which // will presumably also be defined in the file, we // don't want to resolve them to their base types.
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon May 20 15:50:06 UTC 2024 - 97K bytes - Viewed (0) -
tensorflow/cc/client/client_session.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 09:04:10 UTC 2024 - 7.1K bytes - Viewed (0) -
tensorflow/cc/client/client_session.h
/// Same as above, but use the mapping in `inputs` as feeds. Status Run(const FeedType& inputs, const std::vector<Output>& fetch_outputs, std::vector<Tensor>* outputs) const; /// Same as above. Additionally runs the operations ins `run_outputs`. Status Run(const FeedType& inputs, const std::vector<Output>& fetch_outputs, const std::vector<Operation>& run_outputs,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 20 08:11:46 UTC 2022 - 6.1K bytes - Viewed (0) -
tensorflow/cc/client/client_session_test.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/cc/ops/while_loop_test.cc
const std::vector<T>& expected_output_values) { ClientSession session(scope_); DCHECK_EQ(input_values.size(), inputs_.size()); ClientSession::FeedType feeds; for (int i = 0; i < inputs_.size(); ++i) { feeds.emplace(inputs_[i], input_values[i]); } std::vector<Tensor> out_tensors; TF_ASSERT_OK(session.Run(feeds, outputs_, &out_tensors));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 13 22:30:58 UTC 2023 - 6.4K bytes - Viewed (0) -
tensorflow/cc/framework/gradient_checker.cc
dy_datas[i] = Tensor(ys[i].type(), y_shapes[i]); auto dy_data_flat = dy_datas[i].flat<Y_T>(); dy_data_flat.setZero(); } // Create the feed list. ClientSession::FeedType feed_list; for (int i = 0; i < x_num; i++) { feed_list.insert({xs[i], x_datas[i]}); } for (int i = 0; i < y_num; i++) { feed_list.insert({dys[i], dy_datas[i]}); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 05:57:22 UTC 2024 - 18.2K bytes - Viewed (0)