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Results 1 - 3 of 3 for liven (0.17 sec)
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tensorflow/c/experimental/gradients/nn_grad.cc
Status Compute(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> grad_outputs, absl::Span<AbstractTensorHandle*> grad_inputs) override { /* Given upstream grad U and a BiasAdd: A + bias, the gradients are: * * dA = U * dbias = reduceSum(U, dims = channel_dim) */ AbstractTensorHandle* upstream_grad = grad_outputs[0];
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5.7K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental.cc
void TF_SetTracingImplementation(const char* name, TF_Status* s) { tsl::Set_TF_Status_from_Status(s, SetDefaultTracingEngine(name)); } // Creates a new TensorFlow function, it is an execution context attached to a // given tracing context. TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* s) { return wrap(CreateTracingExecutionContext(fn_name, s)); } TF_AbstractFunction* TF_FinalizeFunction(TF_ExecutionContext* ctx,
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 9K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
// ================== Helper functions ================= // Fills data with values [start,end) with given step size. void Range(vector<int32_t>* data, int32_t start, int32_t end, int32_t step = 1) { for (int32_t i = start; i < end; i += step) { (*data)[i] = i; } } // Fills out_dims with the dimensions of the given tensor. void GetDims(const TF_Tensor* t, int64_t* out_dims) { int num_dims = TF_NumDims(t);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0)