Update tf-metadata.json

source/tf-metadata.json

@@ -60824,6 +60824,99 @@
       }
     ]
   },
+  {
+    "name": "XlaRecvTPUEmbeddingActivations",
+    "summary": "An op that receives embedding activations on the TPU.",
+    "description": "The TPU system performs the embedding lookups and aggregations. The results of\nthese aggregations are visible to the Tensorflow Graph as the outputs of a\nXlaRecvTPUEmbeddingActivations Op. This op returns a list containing one\nTensor of activations per table specified in the model.",
+    "attributes": [
+      {
+        "name": "num_tables",
+        "type": "int64",
+        "description": "The number of output activation tensors. If feature descriptor is\npresent in the tpu embedding config, it is equal to the number of features\notherwise equal to number of embedding tables in the model.",
+        "minimum": 1
+      },
+      {
+        "name": "config",
+        "type": "string",
+        "description": "Serialized TPUEmbeddingConfiguration proto."
+      }
+    ],
+    "inputs": [
+      {
+        "name": "deduplication_data",
+        "description": "A Tensor with type=DT_VARIANT containing the deduplication\ndata. The tensor is an XLA nested tuple containing N elements (where N is\nthe ratio of the number of embedding to tensor cores per TPU chip). Each\nelement of the nested tuple is a tuple of rank 1 tensors. Each tensor either\ncontains indices (DT_UINT32) for embedding lookup on the TensorCore or\nweights (DT_FLOAT) to apply to the output of the embedding lookup operation.",
+        "type": 21
+      }
+    ],
+    "outputs": [
+      {
+        "name": "outputs",
+        "description": "A TensorList of embedding activations containing one Tensor per\nembedding table in the model.",
+        "numberAttr": "num_tables",
+        "type": 1
+      }
+    ]
+  },
+  {
+    "name": "XlaRecvTPUEmbeddingDeduplicationData",
+    "summary": "Receives deduplication data (indices and weights) from the embedding core.",
+    "description": "The deduplication data is a Tensor with type=DT_VARIANT. The tensor itself is an\nXLA nested tuple containing N elements (where N is the ratio of the number of\nembedding to tensor cores per TPU chip). Each element of the nested tuple is a\ntuple of rank 1 tensors. Each tensor either contains indices (DT_UINT32) for\nembedding lookup on the TensorCore or weights (DT_FLOAT) to apply to the output\nof the embedding lookup operation.",
+    "attributes": [
+      {
+        "name": "config",
+        "type": "string",
+        "description": "Serialized TPUEmbeddingConfiguration proto."
+      }
+    ],
+    "outputs": [
+      {
+        "name": "output",
+        "type": 21
+      }
+    ]
+  },
+  {
+    "name": "XlaSendTPUEmbeddingGradients",
+    "summary": "An op that performs gradient updates of embedding tables.",
+    "description": "The gradients argument is a TensorList having the same length and shapes as the\nreturn value of XlaRecvTPUEmbeddingActivations, but contains gradients of the\nmodel's loss with respect to the embedding activations. The embedding tables are\nupdated from these gradients via the optimizer specified in the\nTPUEmbeddingConfiguration proto given to tpu.initialize_system.",
+    "attributes": [
+      {
+        "name": "NumTables",
+        "type": "int64",
+        "minimum": 1
+      },
+      {
+        "name": "NumLearningRateTags",
+        "type": "int64",
+        "minimum": 0,
+        "default": 0
+      },
+      {
+        "name": "config",
+        "type": "string",
+        "description": "Serialized TPUEmbeddingConfiguration proto."
+      }
+    ],
+    "inputs": [
+      {
+        "name": "gradients",
+        "description": "A TensorList of gradients with which to update embedding tables.",
+        "numberAttr": "NumTables",
+        "type": 1
+      },
+      {
+        "name": "learning_rates",
+        "description": "A TensorList of learning rates used for updating the embedding\ntables via the optimizer. The length of the TensorList must be equal to the\nnumber of dynamic learning rate tags specified in the\nTPUEmbeddingConfiguration proto.",
+        "numberAttr": "NumLearningRateTags",
+        "type": 1
+      },
+      {
+        "name": "deduplication_data",
+        "description": "A Tensor with type=DT_VARIANT containing the deduplication\ndata. The tensor is an XLA nested tuple containing N elements (where N is\nthe ratio of the number of embedding to tensor cores per TPU chip). Each\nelement of the nested tuple is a tuple of rank 1 tensors. Each tensor either\ncontains indices (DT_UINT32) for embedding lookup on the TensorCore or\nweights (DT_FLOAT) to apply to the output of the embedding lookup operation.",
+        "type": 21
+      }
+    ]
+  },
   {
     "name": "XlaSendToHost",
     "summary": "An op to send a tensor to the host.",