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CONTRIBUTING.md
using a job called "copybara". **5. Copy to Google Internal codebase and run internal CI** - Once the PR is in the Google codebase, we make sure it integrates well with its dependencies and the rest of the system. - Rarely, If the tests fail at this stage, we cannot merge the code. - If needed, we may come to you to make some changes. At times, it may not be
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tensorflow/c/eager/tape.h
// // Below here we do the gradient algorithm. It works as follows: // // First we filter the tape to just the subset of operations we want to // differentiate. In the process of doing so we count how many times each Tensor // is used as an input to an op (so we know when we're done computing gradients // for that Tensor). We also count, for each tape entry, how many of its output
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tensorflow/c/BUILD
"//conditions:default": [], }), tags = [ "no_cuda_asan", # TODO(b/181771536) "no_windows", # TODO(b/155444728) ], # We must ensure that the dependencies can be dynamically linked since # the shared library must be able to use core:framework. deps = [ ":c_api", ":c_api_internal", ":c_test_util",
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tensorflow/c/eager/c_api_unified_experimental_graph.cc
} if (op_type_.empty()) { return errors::FailedPrecondition( "GraphOperation::Reset must be called before calling SetOpName."); } // TODO(b/145674566): We use Graph::NewName to get a unique name here but // this may not be consistent with python's naming policy. mutex_lock l(g_->mu); op_.reset(new TF_OperationDescription(g_, op_type_.c_str(),
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tensorflow/c/c_api_experimental.cc
gpu_options->set_allow_growth(gpu_memory_allow_growth); (*config.mutable_device_count())["CPU"] = num_cpu_devices; // TODO(b/113217601): This is needed for EagerContext::runner_ to use a // threadpool, so that we avoid the possibility of running the runner_ in the // threadpool of GPU event mgr, as that can trigger more callbacks to be // scheduled on that same threadpool, causing a deadlock in cases where the
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tensorflow/c/eager/dlpack.cc
// There are two ways to represent compact row-major data // 1) nullptr indicates tensor is compact and row-majored. // 2) fill in the strides array as the real case for compact row-major data. // Here we choose option 2, since some frameworks didn't handle the strides // argument properly. dlm_tensor->dl_tensor.strides = stride_arr->data(); dlm_tensor->dl_tensor.byte_offset =
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tensorflow/c/eager/c_api_experimental.cc
tensorflow::unwrap(handles[i]); if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) { // 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);
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tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem.cc
TF_SetStatusFromIOError(status, errno, dst); return; } } else if (S_ISDIR(st.st_mode)) { TF_SetStatus(status, TF_FAILED_PRECONDITION, "target path is a directory"); return; } // We cannot rename directories yet, so prevent this. if (stat(src, &st) != 0) { TF_SetStatusFromIOError(status, errno, src); return; } else if (S_ISDIR(st.st_mode)) {
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tensorflow/c/eager/gradients.cc
// TODO(srbs): It seems like this is used only for performance optimization // and not for correctness. The only downside of keeping this 1 seems to be // that the gradient accumulation is unbounded and we will never // aggressively aggregate accumulated gradients to recover memory. // Revisit and fix. return 1; } // Consumes references to the tensors in the gradient_tensors list and returns
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ci/official/utilities/code_check_full.bats
to a banned CUDA dependency when '--define framework_shared_object=false' is set. This means that a CUDA target was probably included via an is_static condition, used when targeting platforms like Windows where we build statically instead of dynamically. Here's the output from bazel query: EOF cat $BATS_TEST_TMPDIR/out [[ ! -s $BATS_TEST_TMPDIR/out ]] } @test "All tensorflow.org/code links point to real files" {
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