[Environment]::SetEnvironmentVariable('HOME', 'C:\Users\ContainerAdministrator\', 'Machine'); \
    [Environment]::SetEnvironmentVariable('HOMEDRIVE', 'C:', 'Machine'); \
    [Environment]::SetEnvironmentVariable('HOMEPATH', '\Users\ContainerAdministrator\', 'Machine'); \
    [Environment]::SetEnvironmentVariable('GOROOT', 'C:\Program Files\Go\', 'Machine'); \

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)

Status ModularFileSystem::GetMatchingPaths(const std::string& pattern,
                                           TransactionToken* token,
                                           std::vector<std::string>* result) {
  if (ops_->get_matching_paths == nullptr)
    return internal::GetMatchingPaths(this, Env::Default(), pattern, result);

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);

#include "tensorflow/c/experimental/grappler/grappler_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/grappler/clusters/single_machine.h"
#include "tensorflow/core/grappler/costs/graph_properties.h"
#include "tensorflow/core/grappler/grappler_item.h"
#include "tensorflow/core/grappler/inputs/trivial_test_graph_input_yielder.h"

setup_file() {
    cd /tf/tensorflow
    bazel version  # Start the bazel server
}

# Do a bazel query specifically for the licenses checker. It searches for
# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those
# targets.

void DeleteDir(const TF_Filesystem* filesystem, const char* path,
               TF_Status* status) {
  // A directory is considered empty either if there are no matching objects
  // with the corresponding name prefix or if there is exactly one matching
  // object and it is the directory marker. Therefore we need to retrieve
  // at most two children for the prefix to detect if a directory is empty.

setup_file() {
    bazel version  # Start the bazel server
}

# Do a bazel query specifically for the licenses checker. It searches for
# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those
# targets.

    for (auto accumulated : accumulated_gradients_) {
      vspace_.DeleteGradient(accumulated.second);
    }
  }

  // Tell the forward accumulator to watch tensor_id, with a Tensor tangent
  // vector `tangent` of matching shape and dtype. Tangents are the "vector" in
  // "Jacobian-vector product"; `Watch`ing a new Tensor and immediately calling
  // FetchJVP for it would return `tangent`.
  void Watch(int64_t tensor_id, Gradient* tangent);

      if command:
        failure_msg = (f'\nThe command was:\n\n'
                       f'{command}\n\n')
      else:
        failure_msg = ('\nCouldn\'t parse a bazel command '
                       'matching the invocation, inside the log. '
                       'Please look for it in the build log.\n\n')
      failure_msg += (
          f'See the ResultStore link for a detailed view of failed targets:\n'