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tensorflow/c/eager/parallel_device/parallel_device_testlib.h
const std::array<const char*, num_devices>& underlying_devices, TF_Status* status); // Create and modify a variable placed on a parallel device which composes // `first_device` and `second_device`. void BasicTestsForTwoDevices(TFE_Context* context, const char* first_device, const char* second_device); // Implementations of templated functions ******************************
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Feb 09 01:12:35 GMT 2021 - 6.9K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device.h
// TPUReplicatedInput and TPUReplicatedOutput respectively. For example, with // two component devices, running `x = TPUReplicatedInput(inputs=[a, b])` on the // parallel device creates a parallel tensor `x` with `a` on the first of // `underlying_devices` and `b` on the second. Running `a_unpacked, b_unpacked = // TPUReplicatedOutput(input=x, num_replicas=2)` un-packs the parallel tensor // into its components. //
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Jun 04 21:49:16 GMT 2020 - 2.9K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib.h
// before `StartExecute` is called again. Using `StartExecute` with `Join` // allows the caller to schedule computation on multiple ParallelDevices // without sequencing those operations (first call `StartExecute` on each // parallel device, then call `Join` on each; even if some of the `Join`s // return a bad status the caller must run all of the `Join`s or any future // `StartExecute`s will deadlock). //
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 25 15:21:13 GMT 2023 - 12.9K bytes - Viewed (0) -
tensorflow/c/c_api.h
// .Output("output: T") // .Attr("N: int >= 2") // .Attr("T: type"); // that defines two inputs, "concat_dim" and "values" (in that order). // You must use TF_AddInput() for the first input (since it takes a // single tensor), and TF_AddInputList() for the second input (since // it takes a list, even if you were to pass a list with a single // tensor), as in:
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Oct 26 21:08:15 GMT 2023 - 82.3K bytes - Viewed (3) -
tensorflow/c/eager/tape.h
const std::unordered_map<int64_t, int64_t>& op_missing_tensor) { std::vector<int64_t> result; for (auto& op_entry : op_tape) { if (op_missing_tensor.find(op_entry.first) == op_missing_tensor.end()) { result.push_back(op_entry.first); } } return result; } template <typename Gradient, typename BackwardFunction, typename TapeTensor> Status InitialGradients(
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 02 12:40:29 GMT 2024 - 47.2K bytes - Viewed (1) -
tensorflow/c/experimental/filesystem/plugins/gcs/expiring_lru_cache.h
Entry entry{timer_seconds_(), value, lru_list_.begin()}; auto insert = cache_.insert(std::make_pair(key, entry)); if (!insert.second) { lru_list_.erase(insert.first->second.lru_iterator); insert.first->second = entry; } else if (max_entries_ > 0 && cache_.size() > max_entries_) { cache_.erase(lru_list_.back()); lru_list_.pop_back(); } }
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Jul 09 19:31:22 GMT 2020 - 6.3K bytes - Viewed (0) -
tensorflow/c/eager/c_api.h
// can correspond to the data contained in another dimension in on-host // representation. The dimensions are indexed using the standard TensorFlow // major-to-minor order (slowest varying dimension first), // not the XLA's minor-to-major order. // On-device dimensions can be padded. TFE_TensorDebugInfoOnDeviceDim returns // the number of elements in a dimension after padding.
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Apr 27 21:07:00 GMT 2023 - 22.8K bytes - Viewed (1) -
tensorflow/c/experimental/grappler/grappler.h
size_t struct_size; void* ext; // reserved for future use // [Optional] // Create function for optimizer. void* (*create_func)(); // Optimizer function for optimizer. The first param is an optimizer created // by create_func. The second param is input graph. The third param is // GrapplerItem. The fourth param is output graph. void (*optimize_func)(void*, const TF_Buffer*, const TF_GrapplerItem*,
C - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Wed Aug 03 18:08:43 GMT 2022 - 12.5K bytes - Viewed (0) -
tensorflow/c/c_test_util.h
TF_Operation* RandomUniform(TF_Operation* shape, TF_DataType dtype, TF_Graph* graph, TF_Status* s); // Split `input` along the first dimension into 3 tensors TF_Operation* Split3(TF_Operation* input, TF_Graph* graph, TF_Status* s, const char* name = "split3"); bool IsPlaceholder(const tensorflow::NodeDef& node_def);
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 09 01:06:53 GMT 2018 - 6K bytes - Viewed (0) -
tensorflow/c/experimental/filesystem/filesystem_interface.h
/// `ReadOnlyMemoryRegion`) and one for all the operations a `Filesystem` /// implements. Each of them is in a 1-to-1 correspondence with the wrapper /// structures from the first section: these tables only contain function /// pointers that operate on the corresponding data. Thus, the first argument of /// each of these functions is a pointer to the paired struct and this argument /// can be used to track state in between calls (from an object oriented point
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri May 27 17:36:54 GMT 2022 - 53.1K bytes - Viewed (0)