TEST_P(GradientCheckerTest, TestMatMul) {
  float A_vals[] = {1.0f, 2.0f, 3.0f, 4.0f};
  int64_t A_dims[] = {2, 2};
  AbstractTensorHandlePtr A;
  {
    AbstractTensorHandle* A_raw;
    absl::Status s = TestTensorHandleWithDims<float, TF_FLOAT>(
        ctx_.get(), A_vals, A_dims, 2, &A_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    A.reset(A_raw);
  }
  float B_vals[] = {.5f, -1.0f, 1.0f, 1.0f};

         TF_TensorByteSize(result_tensor));

  // Build expected result & verify.
  float e_vals[] = {19.0f, 22.0f, 43.0f, 50.0f};

  int data_len = 4;  // length of e_vals
  for (int i = 0; i < data_len; i++) {
    EXPECT_EQ(result_data[i], e_vals[i]);
  }

  TF_DeleteTensor(result_tensor);
  TF_DeleteAbstractTensor(result);
  TF_DeleteOutputList(o);

	}
	if key.ItemCount, _ = getItemCount(k); key.ItemCount > 1 {
		key.Name = strings.TrimPrefix(key.Name, fmt.Sprintf("%d:", key.ItemCount))
	}
	if vals := strings.Split(key.Name, "."); len(vals) == 2 {
		key.Extension = "." + vals[1]
		key.Name = strings.TrimSuffix(key.Name, key.Extension)
	}
	return
}

// replayItems - Reads the items from the store and replays.

  AbstractTensorHandlePtr sum_dims;
  {
    vector<int32_t> vals(num_dims_out);
    int64_t vals_shape[] = {num_dims_out};
    Range(&vals, 0, num_dims_out);
    AbstractTensorHandle* sum_dims_raw = nullptr;
    TF_RETURN_IF_ERROR(TestTensorHandleWithDims<int32_t, TF_INT32>(
        ctx, vals.data(), vals_shape, 1, &sum_dims_raw));
    sum_dims.reset(sum_dims_raw);
  }

	var headers []string
	vals := make(http.Header)
	for k, vv := range signedHeaders {
		k = strings.ToLower(k)
		headers = append(headers, k)
		vals[k] = vv
	}
	sort.Strings(headers)

	var buf bytes.Buffer
	for _, k := range headers {
		buf.WriteString(k)
		buf.WriteByte(':')
		for idx, v := range vals[k] {
			if idx > 0 {
				buf.WriteByte(',')
			}

	return !unicode.IsLetter(c) && !unicode.IsNumber(c) && c != '.' && c != '*' && c != '_' && c != '$' && c != '@'
}

// CheckTruth check string true or not
func CheckTruth(vals ...string) bool {
	for _, val := range vals {
		if val != "" && !strings.EqualFold(val, "false") {
			return true
		}
	}
	return false
}

func ToStringKey(values ...interface{}) string {
	results := make([]string, len(values))

func Error[T ErrorConfig, PT interface {
	*T
	setMsg(string)
}](format string, vals ...interface{},
) T {
	pt := PT(new(T))
	pt.setMsg(fmt.Sprintf(format, vals...))
	return *pt
}

// Errorf formats an error and returns it as a generic config error
func Errorf(format string, vals ...interface{}) ErrConfigGeneric {
	return Error[ErrConfigGeneric](format, vals...)
}

// Default keys
const (
	Default = madmin.Default

}

// return URL for creating the bucket.
func getBucketVersioningConfigURL(endPoint, bucketName string) string {
	vals := make(url.Values)
	vals.Set("versioning", "")
	return makeTestTargetURL(endPoint, bucketName, "", vals)
}

// return URL for listing buckets.
func getListBucketURL(endPoint string) string {
	return makeTestTargetURL(endPoint, "", "", url.Values{})
}

					gr.Close()
				},
			}

			opts, err := batchReplicationOpts(ctx, "", gr.ObjInfo)
			if err != nil {
				batchLogIf(ctx, err)
				continue
			}

			for k, vals := range opts.Header() {
				for _, v := range vals {
					snowballObj.Headers.Add(k, v)
				}
			}

			input <- snowballObj
		}
	}()

	// Collect and upload all entries.