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tensorflow/c/c_api_test.cc
const int num_dims = 2; int64_t* dims = new int64_t[num_dims]; int64_t num_elements = 1; dims[0] = batch_size; dims[1] = 1; for (int64_t i = 0; i < num_dims; ++i) { num_elements *= dims[i]; } TF_Tensor* t = TF_AllocateTensor(TF_STRING, dims, num_dims, sizeof(TF_TString) * num_elements); delete[] dims;
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 96.9K bytes - Viewed (3) -
RELEASE.md
* Changing `tf.data.experimental.save` to store the type specification of the dataset elements. This avoids the need for explicitly specifying the `element_spec` argument of `tf.data.experimental.load` when loading the previously saved dataset. * Add `.element_spec` property to `tf.data.DatasetSpec` to access the inner spec. This can be used to extract the structure of nested
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) -
tensorflow/c/c_api.cc
shapes.resize(num_shapes); for (int i = 0; i < num_shapes; ++i) { if (proto_lens[i] > std::numeric_limits<int>::max()) { status->status = InvalidArgument( "length of element ", i, " in the list (", proto_lens[i], " bytes) is too large to be parsed by the protocol buffer library"); return; } if (!shapes[i].ParseFromArray(protos[i], static_cast<int>(proto_lens[i]))) {
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/c_api_experimental.cc
std::vector<Tensor> all_input_tensors; // Update the vector with information from `input_tensors` if provided. if (input_tensors != nullptr) { // Note that we take the address of the elements in `all_input_tensors` // below. Allocate enough space so that no reallocation happens, which will // make the pointers invalid. all_input_tensors.reserve(num_inputs); for (int i = 0; i < num_inputs; ++i) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 29.4K bytes - Viewed (0)