Update tf-metadata.json

src/tf-metadata.json

@@ -4377,6 +4377,39 @@
       "summary": "Asserts that the given condition is true."
     }
   },
+  {
+    "name": "AssertCardinalityDataset",
+    "schema": {
+      "attributes": [
+        {
+          "minimum": 1,
+          "name": "output_types",
+          "type": "type[]"
+        },
+        {
+          "minimum": 1,
+          "name": "output_shapes",
+          "type": "shape[]"
+        }
+      ],
+      "inputs": [
+        {
+          "name": "input_dataset",
+          "type": 21
+        },
+        {
+          "name": "cardinality",
+          "type": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "handle",
+          "type": 21
+        }
+      ]
+    }
+  },
   {
     "name": "AssertNextDataset",
     "schema": {
@@ -28534,6 +28567,72 @@
       "summary": "Elementwise computes the bitwise left-shift of `x` and `y`."
     }
   },
+  {
+    "name": "LegacyParallelInterleaveDatasetV2",
+    "schema": {
+      "attributes": [
+        {
+          "description": "A function mapping elements of `input_dataset`, concatenated with\n`other_arguments`, to a Dataset variant that contains elements matching\n`output_types` and `output_shapes`.",
+          "name": "f",
+          "type": "function"
+        },
+        {
+          "default": "default",
+          "name": "deterministic",
+          "type": "string"
+        },
+        {
+          "minimum": 0,
+          "name": "Targuments",
+          "type": "type[]"
+        },
+        {
+          "minimum": 1,
+          "name": "output_types",
+          "type": "type[]"
+        },
+        {
+          "minimum": 1,
+          "name": "output_shapes",
+          "type": "shape[]"
+        }
+      ],
+      "description": "The resulting dataset is similar to the `InterleaveDataset`, with the exception\nthat if retrieving the next value from a dataset would cause the requester to\nblock, it will skip that input dataset. This dataset is especially useful\nwhen loading data from a variable-latency datastores (e.g. HDFS, GCS), as it\nallows the training step to proceed so long as some data is available.\n\n!! WARNING !! This dataset is not deterministic!",
+      "inputs": [
+        {
+          "name": "input_dataset",
+          "type": 21
+        },
+        {
+          "name": "other_arguments",
+          "typeListAttr": "Targuments"
+        },
+        {
+          "name": "cycle_length",
+          "type": 9
+        },
+        {
+          "name": "block_length",
+          "type": 9
+        },
+        {
+          "name": "buffer_output_elements",
+          "type": 9
+        },
+        {
+          "name": "prefetch_input_elements",
+          "type": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "handle",
+          "type": 21
+        }
+      ],
+      "summary": "Creates a dataset that applies `f` to the outputs of `input_dataset`."
+    }
+  },
   {
     "name": "Less",
     "schema": {