TF_TString* data = static_cast<TF_TString*>(TF_TensorData(t));
  for (int i = 0; i < batch_size; ++i) {
    TF_TString_Init(&data[i]);
    // The following input string length is large enough to make sure that
    // copy to tstring in large mode.
    std::string source =
        "This is the " + std::to_string(i + 1) + "th. data element\n";
    TF_TString_Copy(&data[i], source.c_str(), source.length());
  }

  // make sure there is no information loss.
  if (proto_len > std::numeric_limits<int>::max()) {
    status->status = InvalidArgument(
        "proto_len (", proto_len,
        " bytes) is too large to be parsed by the protocol buffer library");
    return;
  }
  TensorShapeProto shape;
  if (shape.ParseFromArray(proto, static_cast<int>(proto_len))) {
    desc->node_builder.Attr(attr_name, shape);

// setting the same key will lead to errors.
//
// Note that the key-values are only expected to be used for cluster
// configuration data, and should not be used for storing a large amount of data
// or being accessed very frequently.
TF_CAPI_EXPORT extern void TFE_InsertConfigKeyValue(TFE_Context* ctx,
                                                    const char* key,

*   Fixes an overflow producing a crash in `tf.image.resize` when size is large
    ([CVE-2021-41199](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-41199))
*   Fixes an overflow producing a crash in `tf.tile` when tiling tensor is large
    ([CVE-2021-41198](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-41198))

# Debug config
build:dbg -c dbg
# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g

of them that contain failures into one file. The TensorFlow DevInfra team
uses this to generate a simple overview of an entire pip and nonpip test
invocation, since the normal logs that Bazel creates are too large for the
internal invocation viewer.
"""
import collections
import os
import re
import subprocess
import sys
from junitparser import JUnitXml

result = JUnitXml()
try:

                                                   TF_Status* status);

// Returns the shape of the Tensor referenced by `output` in `graph`
// into `dims`. `dims` must be an array large enough to hold `num_dims`
// entries (e.g., the return value of TF_GraphGetTensorNumDims).
//
// If the number of dimensions in the shape is unknown or the shape is

  TFE_DeleteContextOptions(opts);

  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Use large matrices so that RPCs don't return before we get a chance
  // to call TFE_DeleteContext.
  TFE_TensorHandle* h0_task0 = TestMatrixTensorHandle100x100(ctx);
  TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle100x100(ctx);