Add TransformerParameters proto

PiperOrigin-RevId: 529213840

mediapipe/tasks/cc/components/processors/proto/BUILD

@@ -93,3 +93,8 @@ mediapipe_proto_library(
         "//mediapipe/framework:calculator_proto",
     ],
 )
+
+mediapipe_proto_library(
+    name = "transformer_params_proto",
+    srcs = ["transformer_params.proto"],
+)

mediapipe/tasks/cc/components/processors/proto/transformer_params.proto

@@ -0,0 +1,46 @@
+/* Copyright 2023 The MediaPipe Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto3";
+
+package mediapipe.tasks.components.processors.proto;
+
+option java_package = "com.google.mediapipe.tasks.components.processors.proto";
+option java_outer_classname = "TransformerParametersProto";
+
+// The parameters of transformer (https://arxiv.org/pdf/1706.03762.pdf)
+message TransformerParameters {
+  // Batch size of tensors.
+  int32 batch_size = 1;
+
+  // Maximum sequence length of the input/output tensor.
+  int32 max_seq_length = 2;
+
+  // Embedding dimension (or model dimension), `d_model` in the paper.
+  // `d_k` == `d_v` == `d_model`/`h`.
+  int32 embedding_dim = 3;
+
+  // Hidden dimension used in the feedforward layer, `d_ff` in the paper.
+  int32 hidden_dimension = 4;
+
+  // Head dimension, `d_k` or `d_v` in the paper.
+  int32 head_dimension = 5;
+
+  // Number of heads, `h` in the paper.
+  int32 num_heads = 6;
+
+  // Number of stacked transformers, `N` in the paper.
+  int32 num_stacks = 7;
+}