* the segment.
   */
  final int segmentMask;

  /**
   * Shift value for indexing within segments. Helps prevent entries that end up in the same segment
   * from also ending up in the same bucket.
   */
  final int segmentShift;

  /** The segments, each of which is a specialized hash table. */
  final Segment<K, V>[] segments;

  /** The concurrency level. */

        padding_array.emplace_back(v);
      }

      if (IsSamePadding(conv_op, strides, dilation, padding_array)) {
        // Check if padding is "SAME".
        padding = "SAME";
      } else {
        padding = "EXPLICIT";
        explicit_padding.push_back(0);
        explicit_padding.push_back(0);
        explicit_padding.append(padding_array);

    const auto [stride_height, stride_width] = GetStrides(op);

    // Below convolution arithmetic for `SAME` padding calculation is
    // referenced from
    // https://www.tensorflow.org/api_docs/python/tf/nn/convolution. The
    // following condition must hold true for padding to be `SAME`:
    // output_spatial_shape[i] = ceil(input_spatial_shape[i] / strides[i])

(NeqInter x y) => (NeqPtr (ITab x) (ITab y))
(EqSlice x y)  => (EqPtr  (SlicePtr x) (SlicePtr y))
(NeqSlice x y) => (NeqPtr (SlicePtr x) (SlicePtr y))

// Load of store of same address, with compatibly typed value and same size
(Load <t1> p1 (Store {t2} p2 x _))
	&& isSamePtr(p1, p2)
	&& t1.Compare(x.Type) == types.CMPeq
	&& t1.Size() == t2.Size()
	=> x
(Load <t1> p1 (Store {t2} p2 _ (Store {t3} p3 x _)))

	// used for storing the uploadID's parsed on concurrent HTTP requests for NewMultipart upload on the same object.
	testUploads := struct {
		sync.Mutex
		uploads []string
	}{}

	objectName := "test-object-new-multipart-parallel"
	var wg sync.WaitGroup
	for i := 0; i < 10; i++ {
		wg.Add(1)
		// Initiate NewMultipart upload on the same object 10 times concurrrently.
		go func() {
			defer wg.Done()

  %0 = "tf.Conv3D"(%arg0, %arg1) {padding = "SAME", strides = [2, 1, 1, 1, 1]} : (tensor<?x?x?x?x?xf32>, tensor<?x?x?x?x?xf32>) -> tensor<?x?x?x?x?xf32>
  func.return %0: tensor<?x?x?x?x?xf32>
  // CHECK-LABEL: conv3d_invalid_strides
  // CHECK:  [[BCT:%.*]] = "tf.Conv3D"(%arg0, %arg1) <{padding = "SAME", strides = [2, 1, 1, 1, 1]}> : (tensor<?x?x?x?x?xf32>, tensor<?x?x?x?x?xf32>) -> tensor<?x?x?x?x?xf32>

			} else {
				ro = append(ro, s)
			}
		}

		// Check that we haven't made two symbols with the same .Outer into
		// different types (because references two symbols with non-nil Outer
		// become references to the outer symbol + offset it's vital that the
		// symbol and the outer end up in the same section).
		for _, s := range relro {
			if outer := ldr.OuterSym(s); outer != 0 {
				st := state.symType(s)

}

// Follow the use chain of TensorList and return true iff all elements written
// to TensorList have same static shape. If all elements have same shape, assign
// it to `potential_element_type`.
//
// This can handle multiple mutations of a TensorList object and would return
// true if across all mutations the elements written have the same shape.
bool CanInferTensorListElementType(Value tensorlist,

	// Get request range.
	var rs *HTTPRangeSpec
	var rangeErr error
	rangeHeader := r.Header.Get(xhttp.Range)
	if rangeHeader != "" {
		// Both 'Range' and 'partNumber' cannot be specified at the same time
		if opts.PartNumber > 0 {
			writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrInvalidRangePartNumber), r.URL)
			return
		}

		rs, rangeErr = parseRequestRangeSpec(rangeHeader)

    return new TreeMap<>();
  }

  /**
   * Creates a <i>mutable</i> {@code TreeMap} instance with the same mappings as the specified map
   * and using the same ordering as the specified map.
   *
   * <p><b>Note:</b> if mutability is not required, use {@link
   * ImmutableSortedMap#copyOfSorted(SortedMap)} instead.
   *