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RELEASE.md
with `mask_zero=True` to automatically infer a correct padding mask. * Added a `use_causal_mask` call time argument to the layer. Passing `use_causal_mask=True` will compute a causal attention mask, and optionally combine it with any `attention_mask` passed in directly when calling the layer.
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Apr 29 19:17:57 GMT 2024 - 727.7K bytes - Viewed (8) -
ci/official/containers/linux_arm64/builder.devtoolset/gcc9-fixups.patch
- extern __typeof (name) aliasname __attribute__ ((weak, alias (#name))); + extern __typeof (name) aliasname __attribute__ ((weak, alias (#name))) \ + __attribute_copy__ (name); /* Same as WEAK_ALIAS, but mark symbol as hidden. */ # define weak_hidden_alias(name, aliasname) \ _weak_hidden_alias (name, aliasname) # define _weak_hidden_alias(name, aliasname) \ extern __typeof (name) aliasname \
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tensorflow/c/c_api.cc
} } // end extern "C" namespace tensorflow { void RecordMutation(TF_Graph* graph, const TF_Operation& op, const char* mutation_type) { // If any session has already run this node_id, mark this session as // unrunnable. for (auto it : graph->sessions) { mutex_lock session_lock(it.first->mu); if (it.first->last_num_graph_nodes > op.node.id()) { it.second = strings::StrCat(
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 102.3K bytes - Viewed (0) -
tensorflow/c/eager/c_api_experimental.h
// custom devices will fail. // // `device_name` must not name an existing physical or custom device. It must // follow the format: // // /job:<name>/replica:<replica>/task:<task>/device:<type>:<device_num> // // If the device is successfully registered, `status` is set to TF_OK. Otherwise // the device is not usable. In case of a bad status, `device.delete_device` is
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configure.py
ask_for_var: string for how to ask for user input. var_default: default value string. Returns: string value for var_name """ var = environ_cp.get(var_name) if not var: var = get_input(ask_for_var) print('\n') if not var: var = var_default return var def prompt_loop_or_load_from_env(environ_cp,
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1) -
tensorflow/c/c_api_experimental.cc
TFE_Context* ctx, const char* task, int64_t timeout_in_ms, TF_Status* status) { tensorflow::EagerContext* context = tensorflow::ContextFromInterface(tensorflow::unwrap(ctx)); auto collective_executor_handle = context->GetCollectiveExecutorHandle(); tensorflow::Notification done; collective_executor_handle->get()->remote_access()->CheckPeerHealth( task, timeout_in_ms, [&done, status](const Status& s) {
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tensorflow/c/eager/tape.h
// gradients available initially). // // Then we repeatedly pop an entry from the stack, run its backprop, and update // the gradients of its inputs. Once we have computed all gradients for a single // input we can mark this input as done, and this can trigger adding an entry to // the stack if all outputs of that entry are now done. // // When the stack is empty we have gradients for all tensors we're interested // in. namespace {
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/eager/c_api_distributed_test.cc
// During execution: // * task:0 processes main function `VariableAddFunctionWithGraphError` // and places the 'read0_maybe_with_graph_error' op on task:2 // * task:0 partitions the main function with a subgraph containing // 'read0_maybe_with_graph_error' sent to task:2 // * task:2 graph pass reports an error when it sees
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tensorflow/c/eager/c_api_test_util.h
int64_t init_timeout_in_ms); tensorflow::ServerDef ReplaceTaskInServerDef( const tensorflow::ServerDef& server_def, int task_index); void ReplaceTaskInServerDef(tensorflow::ServerDef* server_def, int task_index, const std::string& host, int port); std::vector<std::string> ListDeviceNames(TFE_Context* ctx);
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Jul 17 23:43:59 GMT 2023 - 7.7K bytes - Viewed (0) -
tensorflow/c/c_api.h
// A Server instance encapsulates a set of devices and a Session target that // can participate in distributed training. A server belongs to a cluster // (specified by a ClusterSpec), and corresponds to a particular task in a // named job. The server can communicate with any other server in the same // cluster. // In-process TensorFlow server. typedef struct TF_Server TF_Server;
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