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Results 1 - 10 of 24 for tf_outputs (0.17 sec)
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tensorflow/c/eager/c_api_unified_experimental_graph.cc
std::vector<TF_Output> tf_outputs(inputs.size()); for (int i = 0; i < inputs.size(); i++) { GraphTensor* t = dyn_cast<GraphTensor>(inputs[i]); if (!t) { return tensorflow::errors::InvalidArgument( "Unable to cast input to GraphTensor"); } tf_outputs[i] = t->output_; } TF_AddInputList(op_.get(), tf_outputs.data(), tf_outputs.size());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 20:00:09 UTC 2024 - 15.4K bytes - Viewed (0) -
tensorflow/c/c_api.cc
cond_graph->parent_inputs = inputs; body_graph->parent = g; body_graph->parent_inputs = inputs; TF_Output* cond_inputs = new TF_Output[ninputs]; TF_Output cond_output = {nullptr, -1}; TF_Output* body_inputs = new TF_Output[ninputs]; TF_Output* body_outputs = new TF_Output[ninputs]; for (int i = 0; i < ninputs; ++i) body_outputs[i] = {nullptr, -1}; const char* name = nullptr;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/c/c_api.h
TF_Graph* const cond_graph; const TF_Output* const cond_inputs; TF_Output cond_output; // The loop body graph. The inputs are the current values of the loop // variables. The outputs are the updated values of the loop variables. TF_Graph* const body_graph; const TF_Output* const body_inputs; TF_Output* const body_outputs;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Oct 26 21:08:15 UTC 2023 - 82.3K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
TF_RETURN_IF_ERROR( RunAndMaybeSum(ctx, forward, theta_inputs, f_outputs, use_function)); AbstractTensorHandlePtr fPlus(f_outputs[0]); // Get f(theta - eps): theta_inputs[input_index] = thetaMinus.get(); TF_RETURN_IF_ERROR( RunAndMaybeSum(ctx, forward, theta_inputs, f_outputs, use_function)); AbstractTensorHandlePtr fMinus(f_outputs[0]);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/c_api_test.cc
TF_SessionOptions* opts = TF_NewSessionOptions(); TF_Session* sess = TF_NewSession(graph, opts, s); TF_DeleteSessionOptions(opts); TF_Output feeds[] = {TF_Output{a, 0}, TF_Output{b, 0}}; TF_Output fetches[] = {TF_Output{plus2, 0}, TF_Output{plusB, 0}}; const char* handle = nullptr; TF_SessionPRunSetup(sess, feeds, TF_ARRAYSIZE(feeds), fetches,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 96.9K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/nn_grad.cc
namespace tensorflow { namespace gradients { namespace { class ReluGradientFunction : public GradientFunction { public: explicit ReluGradientFunction(vector<AbstractTensorHandle*> f_outputs) : forward_outputs_(f_outputs) { for (auto output : forward_outputs_) { if (output) { output->Ref(); } } } Status Compute(AbstractContext* ctx,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 09 06:38:45 UTC 2024 - 5.7K bytes - Viewed (0) -
tensorflow/c/c_api_function.cc
TF_Function* TF_GraphToFunctionWithControlOutputs( const TF_Graph* fn_body, const char* fn_name, unsigned char append_hash_to_fn_name, int num_opers, const TF_Operation* const* opers, int ninputs, const TF_Output* inputs, int noutputs, const TF_Output* outputs, const char* const* output_names, int ncontrol_outputs, const TF_Operation* const* control_outputs, const char* const* control_output_names, const TF_FunctionOptions* opts,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 13.6K bytes - Viewed (0) -
tensorflow/c/while_loop_test.cc
DCHECK(success); TF_DeleteBuffer(buf); return def.DebugString(); } TF_Status* s_; TF_Graph* graph_; std::vector<TF_Output> inputs_; // The inputs to the while loop std::vector<TF_Output> outputs_; // The final outputs of the while loop std::unique_ptr<TF_WhileParams> params_; std::unique_ptr<CSession> csession_; private:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 11 06:05:56 UTC 2024 - 15.3K bytes - Viewed (0) -
tensorflow/c/eager/unified_api_testutil.cc
std::vector<AbstractTensorHandle*> fn_outputs(retvals); TF_RETURN_IF_ERROR(fn_op->Execute( absl::Span<AbstractTensorHandle*>(fn_outputs.data(), fn_outputs.size()), &retvals)); int skipped_indices = 0; for (int i = 0; i < outputs.size(); i++) { if (!null_indices.contains(i)) { outputs[i] = fn_outputs[i - skipped_indices]; } else { skipped_indices += 1;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 27 13:57:45 UTC 2024 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/cluster_outlining.mlir
// CHECK: %[[E_OUTPUT:[0-9]*]] = "tf.E"(%[[CLUSTER_1_ARG_0]]) // CHECK: %[[F_OUTPUT:[0-9]*]] = "tf.F"(%[[CLUSTER_1_ARG_1]], %[[E_OUTPUT]]) // CHECK: return %[[F_OUTPUT]] // ----- // Tests outlining clusters with no live-in values. // CHECK-LABEL: func @cluster_operands // CHECK-SAME: (%[[ARG_0:[a-z0-9]*]]: tensor<?xi32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 21:25:12 UTC 2024 - 4.8K bytes - Viewed (0)