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// need for `Env::Default()`. At that time, we might decide to remove the need
// for `Env::Default()` altogether, but that's a different project, not in
// scope for now. I'm just mentioning this here as that transition will mean
// removal of the registration part from `Env` and adding it here instead: we
// will need tables to hold for each scheme the function tables that implement

# Enables RBE as long as RBE is available for the selected platform.
# The "selected" platform is considered to be
# TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX. "Available" means there is
# an entry in tensorflow/.bazelrc for build:rbe_TFCI_BAZEL_TARGET...
#                                           ^^^^
# This env is only valid when RBE is available on the selected platform, since

# by whitespace. The flag "-F<x>" changes the behavior such that fields are now strings
# separated by the character <x>. Therefore, -F\' (escaped single quote) means that field
# $2 in <Tensor'flow'> is <flow>. This is useful for reading string literals like below.
export TF_VER_SUFFIX=$(awk -F\" '/#define TF_VERSION_SUFFIX/ {print $2}' tensorflow/core/public/version.h)

*   `tf.sparse.segment_sum` `tf.sparse.segment_mean` `tf.sparse.segment_sqrt_n` `SparseSegmentSum/Mean/SqrtN[WithNumSegments]`

    *   Added `sparse_gradient` option (default=false) that makes the gradient of these functions/ops sparse (`IndexedSlices`) instead of dense (`Tensor`), using new `SparseSegmentSum/Mean/SqrtNGradV2` ops.

*   `tf.nn.embedding_lookup_sparse`

# On linux, we dynamically link small amount of kernels
build:linux --config=dynamic_kernels

# Make sure to include as little of windows.h as possible
build:windows --copt=-DWIN32_LEAN_AND_MEAN
build:windows --host_copt=-DWIN32_LEAN_AND_MEAN
build:windows --copt=-DNOGDI
build:windows --host_copt=-DNOGDI

# MSVC (Windows): Standards-conformant preprocessor mode

  cat <<EOF
There was a path found connecting //tensorflow/tools/pip_package:build_pip_package
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

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After
the change has been submitted internally, your pull request will be merged
automatically on GitHub.

        InvalidArgument("Node ", node->name(), " was not found in the graph");
    return -1;
  }

  tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index);

  // Unknown rank means the number of dimensions is -1.
  if (!ic->RankKnown(shape)) {
    return -1;
  }

  return ic->Rank(shape);
}

void TF_GraphGetTensorShape(TF_Graph* graph, TF_Output output, int64_t* dims,