// E.g. it could know whether we're in eager mode or graph mode, keeps track
// of gradient tapes, etc.
typedef struct TF_ExecutionContext TF_ExecutionContext;

// A TF_AbstractTensor is an input to an operation. E.g. it could be a union
// type of eager and graph tensors. It is also the result of executing an
// operation.
typedef struct TF_AbstractTensor TF_AbstractTensor;

// A TF_AbstractOp is the metadata we need to execute an operation. E.g. this

  memset(&option_value, 0, sizeof(option_value));
  option_value.type_tag = TF_Filesystem_Option_Type_Buffer;
  option_value.num_values = values.size();
  std::vector<TF_Filesystem_Option_Value_Union> option_values(values.size());
  for (size_t i = 0; i < values.size(); i++) {
    memset(&option_values[i], 0, sizeof(option_values[i]));
    option_values[i].buffer_val.buf = const_cast<char*>(values[i].c_str());

form of JUnit-based XML.
"""
import argparse
import datetime
import os
import re
from typing import Dict, Union
import xml.etree.ElementTree as ElemTree


ResultDictType = Dict[str, Dict[str, Union[str, int]]]

RESULT_STORE_LINK_RE = re.compile(
    r'^INFO: Streaming build results to: (https://[\w./\-]+)')
FAILED_BUILD_LINE = 'FAILED: Build did NOT complete successfully'

-
-#   define __memset_1(s, c) ({ void *__s = (s);				      \
-			    *((__uint8_t *) __s) = (__uint8_t) c; __s; })
-
-#   define __memset_gc(s, c, n) \
-  ({ void *__s = (s);							      \
-     union {								      \
-       unsigned int __ui;						      \
-       unsigned short int __usi;					      \
-       unsigned char __uc;						      \
-     } *__u = __s;							      \

  TF_Filesystem* owner;
} TF_TransactionToken;

// The named union is needed here (as opposed to
// inside the `TF_Filesystem_Option_Value` struct)
// as MSVC does not recognize `typeof`.
typedef union TF_Filesystem_Option_Value_Union {
  int64_t int_val;
  double real_val;
  struct {
    char* buf;
    int buf_length;
  } buffer_val;
} TF_Filesystem_Option_Value_Union;

typedef struct TF_Filesystem_Option_Value {

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,

    for details of what operations are supported and what are the differences
    from NumPy.
*   `tf.types.experimental.TensorLike` is a new `Union` type that can be used as
    type annotation for variables representing a Tensor or a value that can be
    converted to Tensor by `tf.convert_to_tensor`.