* **Machine Learning**: normalmente requiere muchas multiplicaciones de "matrices" y "vectores". Piensa en una enorme hoja de cálculo con números y multiplicando todos juntos al mismo tiempo.

		{math.MaxInt64, 12, true},
		{0, 12, true},
		{math.MinInt64, 12, true},
	}

	for _, v := range vectors {
		ok := fitsInBase256(v.width, v.in)
		if ok != v.ok {
			t.Errorf("fitsInBase256(%d, %d): got %v, want %v", v.in, v.width, ok, v.ok)
		}
	}
}

func TestParseNumeric(t *testing.T) {
	vectors := []struct {
		in   string
		want int64
		ok   bool
	}{
		// Test base-256 (binary) encoded values.

    BaseEncoding separated = base64().withSeparator("\n", 3);
    assertThrows(UnsupportedOperationException.class, () -> separated.withSeparator("$", 4));
  }

  public void testBase64() {
    // The following test vectors are specified in RFC 4648 itself
    testEncodingWithSeparators(base64(), "", "");
    testEncodingWithSeparators(base64(), "f", "Zg==");
    testEncodingWithSeparators(base64(), "fo", "Zm8=");

	VFWCVTXUFV	X10, V3				// ERROR "expected vector register in vs2 position"
	VFWCVTXFV	X10, V3				// ERROR "expected vector register in vs2 position"
	VFWCVTRTZXUFV	X10, V3				// ERROR "expected vector register in vs2 position"
	VFWCVTRTZXFV	X10, V3				// ERROR "expected vector register in vs2 position"
	VFWCVTFXUV	X10, V3				// ERROR "expected vector register in vs2 position"
	VFWCVTFXV	X10, V3				// ERROR "expected vector register in vs2 position"

	"hash/crc32"
	"internal/obscuretestdata"
	"io"
	"maps"
	"math"
	"os"
	"path"
	"reflect"
	"slices"
	"strconv"
	"strings"
	"testing"
	"time"
)

func TestReader(t *testing.T) {
	vectors := []struct {
		file     string    // Test input file
		obscured bool      // Obscured with obscuretestdata package
		headers  []*Header // Expected output headers

	VLUXEI8V	(X10), V2, V1, V3		// ERROR "invalid vector mask register"
	VSUXEI8V	V3, V2, V1, (X10)		// ERROR "invalid vector mask register"
	VLOXEI8V	(X10), V2, V1, V3		// ERROR "invalid vector mask register"
	VSOXEI8V	V3, V2, V1, (X10)		// ERROR "invalid vector mask register"
	VLSEG2E8V	(X10), V1, V3			// ERROR "invalid vector mask register"
	VLSEG2E8FFV	(X10), V1, V3			// ERROR "invalid vector mask register"

		return 0, testError{fmt.Errorf("got Seek(%d, %d), want Seek(%d, %d)", pos, whence, s, io.SeekCurrent)}
	}
	f.pos += s
	f.ops = f.ops[1:]
	return f.pos, nil
}

func TestSparseEntries(t *testing.T) {
	vectors := []struct {
		in   []sparseEntry
		size int64

		wantValid    bool          // Result of validateSparseEntries
		wantAligned  []sparseEntry // Result of alignSparseEntries

                           const string& op_name) {
  std::vector<int64_t> input_ids(inputs.size());
  std::vector<tensorflow::DataType> input_dtypes(inputs.size());
  for (int i = 0; i < inputs.size(); i++) {
    input_ids[i] = ToId(inputs[i]);
    input_dtypes[i] = inputs[i]->DataType();
  }
  std::vector<TapeTensor> tape_tensors;
  tape_tensors.reserve(outputs.size());
  for (auto t : outputs) {

  if (!status->status.ok()) return;

  // Initialize a input_tensor vector with `nullptr` values.
  std::vector<const Tensor*> input_tensors_vector(num_inputs, nullptr);
  // A vector to keep track of newly created `tf::Tensor` objects.
  std::vector<Tensor> all_input_tensors;
  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {

  virtual bool UsesTFRT() = 0;

  // List attributes of available devices
  virtual void ListDevices(std::vector<DeviceAttributes>* devices) = 0;

  // Add `devices` into context's device manager. Context's device manager
  // will take ownership and maintain devices' lifetime.
  virtual absl::Status AddDevices(
      std::vector<std::unique_ptr<Device>> devices) = 0;

  // Block until all pending nodes are finished.