Fix architecure architecture (#60998)

co63oc · web-flow · commit 45b9ac066abe · 2024-01-22T11:09:17.000+08:00
diff --git a/paddle/fluid/operators/fused/fused_gate_attention_op.cc b/paddle/fluid/operators/fused/fused_gate_attention_op.cc
@@ -166,7 +166,7 @@ class FusedGateAttentionOpMaker : public framework::OpProtoAndCheckerMaker {
         .AsDispensable();
     AddOutput("Out", "Result after attention.");
     AddAttr<bool>("has_gating",
-                  "if true, the attention op uses gate architecure, "
+                  "if true, the attention op uses gate architecture, "
                   "[default true].")
         .SetDefault(true);
     AddAttr<bool>("merge_qkv",
@@ -224,22 +224,22 @@ class FusedGateAttentionGradOp : public framework::OperatorWithKernel {
       OP_INOUT_CHECK(ctx->HasInput("QKVWeight"),
                      "Input",
                      "QKVWeight",
-                     "fused_gate_attention_arad");
+                     "fused_gate_attention_grad");
       ctx->SetOutputDim(framework::GradVarName("QKVWeight"),
                         ctx->GetInputDim("QKVWeight"));
     } else {
       OP_INOUT_CHECK(ctx->HasInput("QueryWeight"),
                      "Input",
                      "QueryWeight",
-                     "fused_gate_attention_arad");
+                     "fused_gate_attention_grad");
       OP_INOUT_CHECK(ctx->HasInput("KeyWeight"),
                      "Input",
                      "KeyWeight",
-                     "fused_gate_attention_arad");
+                     "fused_gate_attention_grad");
       OP_INOUT_CHECK(ctx->HasInput("ValueWeight"),
                      "Input",
                      "ValueWeight",
-                     "fused_gate_attention_arad");
+                     "fused_gate_attention_grad");
 
       for (auto& name : {"QueryWeight", "KeyWeight", "ValueWeight"}) {
         ctx->SetOutputDim(framework::GradVarName(name), ctx->GetInputDim(name));
@@ -249,7 +249,7 @@ class FusedGateAttentionGradOp : public framework::OperatorWithKernel {
     OP_INOUT_CHECK(ctx->HasInput("OutLinearWeight"),
                    "Input",
                    "OutLinearWeight",
-                   "fused_aate_attention_arad");
+                   "fused_gate_attention_grad");
 
     if (ctx->Attrs().Get<bool>("has_gating")) {
       for (auto& name : {"GateWeight", "GateBias"}) {
diff --git a/paddle/fluid/operators/fused/fused_gemm_epilogue_op.cc b/paddle/fluid/operators/fused/fused_gemm_epilogue_op.cc
@@ -54,15 +54,15 @@ class FusedGemmEpilogueOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<bool>(
         "trans_x",
         R"DOC((bool, default false), Whether to transpose input tensor X
-    or not. The input tensor X coulbe be more than two dimension. When
-    set trans_x=true, it would fully reverse X. For instant: X with shpae
+    or not. The input tensor X could be more than two dimension. When
+    set trans_x=true, it would fully reverse X. For instant: X with shape
     [d0, d1, d2, d3] -> [d3, d2, d1, d0].)DOC")
         .SetDefault(false);
     AddAttr<bool>(
         "trans_y",
         R"DOC((bool, default false), Whether to transpose input tensor Y
     or not. The input tensor Y should be two dimension. When
-    set trans_y=true, it would transpose Y. For instant: Y with shpae
+    set trans_y=true, it would transpose Y. For instant: Y with shape
     [d0, d1] -> [d1, d0].)DOC")
         .SetDefault(false);
 
@@ -75,7 +75,7 @@ class FusedGemmEpilogueOpMaker : public framework::OpProtoAndCheckerMaker {
 
     AddComment(R"DOC(
 FusedGemmEpilogue Operator
-This operator is used to perform Activeation(Elementwise_add(Matmul(X, Y), bias)).
+This operator is used to perform Activation(Elementwise_add(Matmul(X, Y), bias)).
 It is equal to paddle.nn.Linear + Activation (None, ReLU or GeLU).
 
 Note:
@@ -121,15 +121,15 @@ class FusedGemmEpilogueGradOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<bool>(
         "trans_x",
         R"DOC((bool, default false), Whether to transpose input tensor X
-    or not. The input tensor X coulbe be more than two dimension. When
-    set trans_x=true, it would fully reverse X. For instant: X with shpae
+    or not. The input tensor X could be more than two dimension. When
+    set trans_x=true, it would fully reverse X. For instant: X with shape
     [d0, d1, d2, d3] -> [d3, d2, d1, d0].)DOC")
         .SetDefault(false);
     AddAttr<bool>(
         "trans_y",
         R"DOC((bool, default false), Whether to transpose input tensor Y
     or not. The input tensor Y should be two dimension. When
-    set trans_y=true, it would transpose Y. For instant: Y with shpae
+    set trans_y=true, it would transpose Y. For instant: Y with shape
     [d0, d1] -> [d1, d0].)DOC")
         .SetDefault(false);
 
@@ -142,7 +142,7 @@ class FusedGemmEpilogueGradOpMaker : public framework::OpProtoAndCheckerMaker {
 
     AddComment(R"DOC(
 FusedGemmEpilogueGrad Operator
-This operator is used to perform backward of Elementwise_add(Matmul(Activeation(X), Y), bias).
+This operator is used to perform backward of Elementwise_add(Matmul(Activation(X), Y), bias).
 It is equal to Activation (None, ReLU or GeLU) + paddle.nn.Linear.
 
 Note:
diff --git a/paddle/fluid/operators/fused/fused_multi_transformer_int8_op.cc b/paddle/fluid/operators/fused/fused_multi_transformer_int8_op.cc
@@ -263,8 +263,8 @@ class FusedMultiTransformerINT8OpMaker
     AddOutput("Out", "Result after multi .");
 
     AddAttr<bool>("pre_layer_norm",
-                  "if true, the attention op uses pre_layer_norm architecure, "
-                  "else, uses post_layer_norm architecuture. "
+                  "if true, the attention op uses pre_layer_norm architecture, "
+                  "else, uses post_layer_norm architecture. "
                   "[default true].")
         .SetDefault(true);
     AddAttr<float>("epsilon",
diff --git a/paddle/fluid/operators/fused/fused_multi_transformer_op.cc b/paddle/fluid/operators/fused/fused_multi_transformer_op.cc
@@ -212,8 +212,8 @@ class FusedMultiTransformerOpOpMaker
     AddOutput("Out", "Result after multi .");
 
     AddAttr<bool>("pre_layer_norm",
-                  "if true, the attention op uses pre_layer_norm architecure, "
-                  "else, uses post_layer_norm architecuture. "
+                  "if true, the attention op uses pre_layer_norm architecture, "
+                  "else, uses post_layer_norm architecture. "
                   "[default true].")
         .SetDefault(true);
     AddAttr<int>("rotary_emb_dims",
diff --git a/paddle/fluid/operators/fused/fused_transformer_op.cc b/paddle/fluid/operators/fused/fused_transformer_op.cc
@@ -2,7 +2,7 @@
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
-Indicesou may obtain a copy of the License at
+You may obtain a copy of the License at
 
     https://www.apache.org/licenses/LICENSE-2.0
 
diff --git a/paddle/fluid/operators/fused/fused_transformer_op.cu b/paddle/fluid/operators/fused/fused_transformer_op.cu
@@ -2,7 +2,7 @@
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
-Indicesou may obtain a copy of the License at
+You may obtain a copy of the License at
 
     https://www.apache.org/licenses/LICENSE-2.0
 
diff --git a/paddle/fluid/operators/fused/fused_transformer_op.h b/paddle/fluid/operators/fused/fused_transformer_op.h
@@ -2,7 +2,7 @@
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
-Indicesou may obtain a copy of the License at
+You may obtain a copy of the License at
 
     https://www.apache.org/licenses/LICENSE-2.0
 
diff --git a/paddle/fluid/operators/fused/fusion_conv_inception_op.cc b/paddle/fluid/operators/fused/fusion_conv_inception_op.cc
@@ -41,14 +41,14 @@ class ConvInceptionFusionOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_EQ(w_dims[0][1],
                       in_dims[1],
                       platform::errors::InvalidArgument(
-                          "Invalid fileter channel number %d, which should be "
+                          "Invalid filter channel number %d, which should be "
                           "equal to input channel number %d.",
                           w_dims[0][1],
                           in_dims[1]));
     PADDLE_ENFORCE_EQ(w_dims[1][1],
                       in_dims[1],
                       platform::errors::InvalidArgument(
-                          "Invalid fileter channel number %d, which should be "
+                          "Invalid filter channel number %d, which should be "
                           "equal to input channel number %d.",
                           w_dims[1][1],
                           in_dims[1]));
diff --git a/paddle/fluid/operators/fused/fusion_lstm_op.cc b/paddle/fluid/operators/fused/fusion_lstm_op.cc
@@ -292,7 +292,7 @@ This operator fuse the X into LSTM, more details can refer to LSTM op.
 }
 
 template <typename T, typename DeviceContext>
-class FuisonLSTMKernel : public framework::OpKernel<T> {
+class FusionLSTMKernel : public framework::OpKernel<T> {
  public:
 #define INIT_BASE_DEFINES                                    \
   auto* x = ctx.Input<phi::DenseTensor>("X");                \
@@ -574,4 +574,4 @@ namespace ops = paddle::operators;
 REGISTER_OPERATOR(fusion_lstm, ops::FusionLSTMOp, ops::FusionLSTMOpMaker);
 
 PD_REGISTER_STRUCT_KERNEL(
-    fusion_lstm, CPU, ALL_LAYOUT, ops::FuisonLSTMKernel, float, double) {}
+    fusion_lstm, CPU, ALL_LAYOUT, ops::FusionLSTMKernel, float, double) {}
diff --git a/paddle/fluid/operators/fused/fusion_seqpool_concat_op.cc b/paddle/fluid/operators/fused/fusion_seqpool_concat_op.cc
@@ -27,7 +27,7 @@ void FusionSeqPoolConcatOp::InferShape(
   PADDLE_ENFORCE_GE(ctx->Inputs("X").size(),
                     1UL,
                     platform::errors::InvalidArgument(
-                        "Inputs(X) of FusionSeqPoolConcatOp should be greated "
+                        "Inputs(X) of FusionSeqPoolConcatOp should be greater "
                         "than 1, but received value is %d.",
                         ctx->Inputs("X").size()));
   OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "FusionSeqPoolConcat");
