// Convert updates into canonical form as expected by tf.scatter ops.
//
// tf.scatter expects `update_window_dims` to be the trailing dimensions.
//
// To support scatter ops generated by numpy-like slice updates:
//   nd_array[:, [i,j]] = [i_values, j_values]
//
// `updates` must be transposed when the update_window_dims are the leading
// dimensions of `updates`.
//
// Other values of `update_window_dims` are left unsupported.
//

        reader.beginArray();
        while (reader.peek() != JsonToken.END_ARRAY) {
            consumeVariant(reader, metadata);
        }
        reader.endArray();
    }

    private void consumeVariant(JsonReader reader, MutableModuleComponentResolveMetadata metadata) throws IOException {
        String variantName = null;

          sample, signature_def
      )
      input_tensor_data = input_tensor.eval()

    self.assertLen(feed_dict, 1)
    self.assertIn('input:0', feed_dict)
    self.assertIsInstance(feed_dict['input:0'], np.ndarray)
    self.assertAllEqual(feed_dict['input:0'], input_tensor_data)

  @test_util.deprecated_graph_mode_only
  def test_create_feed_dict_from_input_data_empty(self):
    signature_def = meta_graph_pb2.SignatureDef(

        final String[] newArray = ArrayUtil.remove(array, "333");
        assertThat(newArray.length, is(2));
        assertThat(newArray[0], is("111"));
        assertThat(newArray[1], is("222"));
    }

    /**
     * @throws Exception
     */
    @Test
    public void testRemoveNothing() throws Exception {
        final String[] array = new String[] { "111", "222", "333" };

from tensorflow.python.types import core
from tensorflow.python.util import tf_export

# A representative sample is a map of: input_key -> input_value.
# Ex.: {'dense_input': tf.constant([1, 2, 3])}
# Ex.: {'x1': np.ndarray([4, 5, 6]}
RepresentativeSample = Mapping[str, core.TensorLike]

# A representative dataset is an iterable of representative samples.
RepresentativeDataset = Iterable[RepresentativeSample]

	}{
		{
			name:    "bothValid",
			old:     &unstructured.Unstructured{Object: map[string]interface{}{"apiVersion": "test/v1", "kind": "Foo", "numArray": []interface{}{1, 2}}},
			obj:     &unstructured.Unstructured{Object: map[string]interface{}{"apiVersion": "test/v1", "kind": "Foo", "numArray": []interface{}{1, 3}, "metadata": map[string]interface{}{"resourceVersion": "1"}}},
			isValid: true,
		},
		{
			name:    "change to invalid",

        jsonWriter.beginArray();
        contents.write();
        endArray();
    }

    protected void beginArray(String name) throws IOException {
        jsonWriter.name(name);
        jsonWriter.beginArray();
    }

    protected void endArray() throws IOException {
        jsonWriter.endArray();
    }

    protected void writeObject(String name, Contents contents) throws IOException {

package types2

// An Array represents an array type.
type Array struct {
	len  int64
	elem Type
}

// NewArray returns a new array type for the given element type and length.
// A negative length indicates an unknown length.
func NewArray(elem Type, len int64) *Array { return &Array{len: len, elem: elem} }

// Len returns the length of array a.
// A negative result indicates an unknown length.

        final T[] newArray = (T[]) Array.newInstance(array.getClass().getComponentType(), array.length - 1);
        if (index > 0) {
            System.arraycopy(array, 0, newArray, 0, index);
        }
        if (index < array.length - 1) {
            System.arraycopy(array, index + 1, newArray, index, newArray.length - index);
        }
        return newArray;
    }

    /**

        var first = true
        list.forEach {
            if (first) first = false else comma()
            body(it)
        }
        endArray()
    }

    private
    fun beginArray() {
        write('[')
    }

    private
    fun endArray() {
        write(']')
    }

    private
    fun property(name: String, value: String) {
        property(name) { jsonString(value) }