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tensorflow/c/c_api_test.cc
src.flat<tstring>()(i) = data[i]; } TF_Tensor* dst = TF_TensorFromTensor(src, &status); ASSERT_TRUE(status.ok()) << status.message(); // Convert back to a C++ Tensor and ensure we get expected output. Tensor output; ASSERT_EQ(absl::OkStatus(), TF_TensorToTensor(dst, &output)) << line; ASSERT_EQ(src.NumElements(), output.NumElements()) << line;
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) -
tensorflow/c/c_api.cc
} tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index); int rank = -1; if (ic->RankKnown(shape)) { rank = ic->Rank(shape); } if (num_dims != rank) { status->status = InvalidArgument("Expected rank is ", num_dims, " but actual rank is ", rank); return; } if (num_dims == 0) { // Output shape is a scalar.
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) -
CONTRIBUTING.md
- If the PR passes all the quality checks then we go ahead and assign a reviewer. - If the PR didn't meet the validation criteria, we request for additional changes to be made to PR to pass quality checks and send it back or on a rare occasion we may reject it. **3. Review** - For a valid PR, reviewer (person familiar with the code/functionality) checks if the PR looks good or needs additional changes.
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Thu Mar 21 11:45:51 GMT 2024 - 15.6K bytes - Viewed (0) -
tensorflow/c/eager/c_api.cc
TFE_DeleteTensorHandle(outputs[i]); } } return status.status; } tensorflow::Status Pack(absl::Span<ImmediateExecutionTensorHandle*> handles, ImmediateExecutionTensorHandle** result) override { TF_Status status; *result = tensorflow::unwrap(device_.pack(context_, tensorflow::wrap(handles.data()),
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 12 20:00:09 GMT 2024 - 43.9K bytes - Viewed (2) -
tensorflow/c/eager/c_api_unified_experimental_graph.cc
std::vector<PartialTensorShape> shapes; shapes.reserve(num_values); for (int i = 0; i < num_values; ++i) { if (num_dims[i] < 0) { shapes.emplace_back(); } else { shapes.emplace_back(ArraySlice<int64_t>( reinterpret_cast<const int64_t*>(dims[i]), num_dims[i])); } } op_->node_builder.Attr(attr_name, shapes); return absl::OkStatus(); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 12 20:00:09 GMT 2024 - 15.4K bytes - Viewed (1) -
RELEASE.md
as `tf.tpu.experimental.embedding.serving_embedding_lookup` which can take arbitrary rank of dense and sparse tensor. For ragged tensor, though the input tensor remains to be rank 2, the activations now can be rank 2 or above by specifying the output shape in the feature config or via the build method. * Add
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/eager/c_api_experimental.cc
// One of the inputs we're trying to pack is on a custom device. We'll let // the first custom device we see handle all of the packing. auto* custom_device_handle = tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>( unwrapped_handle); tensorflow::ImmediateExecutionTensorHandle* result; status->status = custom_device_handle->device()->Pack(
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Apr 11 23:52:39 GMT 2024 - 35.9K bytes - Viewed (3) -
tensorflow/c/c_api_experimental.cc
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) -
tensorflow/c/eager/tape.h
// GradientTape which uses ones. Gradient* zero = input_tensors[target_index].ZerosLike(); new_zeros.push_back(zero); in_grads.push_back(zero); } else { in_grads.push_back(nullptr); } } else { in_grads.push_back(current_grad->second); } } // Avoid infinite recursion. Whichever forward function we run, it'll end up
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/c_api_function.cc
for (int i = 0; i < noutputs; ++i) { output_names_vec.push_back(string(output_names[i])); } } // Process control output names. std::vector<string> control_output_names_vec; if (control_output_names) { control_output_names_vec.reserve(ncontrol_outputs); for (int i = 0; i < ncontrol_outputs; ++i) { control_output_names_vec.push_back(string(control_output_names[i])); } }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 13.6K bytes - Viewed (2)