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Fix typos(RreplenishLayerAndOutput -> ReplenishLayerAndOutput) #62075

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Merged
luotao1 merged 1 commit into from
Feb 27, 2024
Merged

Fix typos(RreplenishLayerAndOutput -> ReplenishLayerAndOutput) #62075

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/activation_op.cc
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Expand Up @@ -112,7 +112,7 @@ class ActivationOpConverter : public OpConverter {

auto output_name = op_desc.Output("Out")[0];

RreplenishLayerAndOutput(layer, op_type_, {output_name}, test_mode);
ReplenishLayerAndOutput(layer, op_type_, {output_name}, test_mode);
}

protected:
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/affine_channel_op.cc
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Expand Up @@ -72,7 +72,7 @@ class AffineChannelOpConverter : public OpConverter {
power_weights.get(),
channel_axis);

RreplenishLayerAndOutput(layer, "affine_channel", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "affine_channel", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/anchor_generator_op.cc
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Expand Up @@ -80,7 +80,7 @@ class AnchorGeneratorOpConverter : public OpConverter {
anchor_generator_inputs.size(),
*anchor_generator_plugin);

RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
anchor_generator_layer, "anchor_generator", output_names, test_mode);
}
};
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10 changes: 5 additions & 5 deletions paddle/fluid/inference/tensorrt/convert/arg_max_op.cc
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Expand Up @@ -42,10 +42,10 @@ class ArgMaxOpConverter : public OpConverter {
auto output_name = op_desc.Output("Out")[0];
bool keepdims = PADDLE_GET_CONST(bool, op_desc.GetAttr("keepdims"));
if (keepdims) {
RreplenishLayerAndOutput(topk_layer,
"arg_max",
{output_name + "_value", output_name},
test_mode);
ReplenishLayerAndOutput(topk_layer,
"arg_max",
{output_name + "_value", output_name},
test_mode);
} else {
auto squeeze_layer =
TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *topk_layer->getOutput(1));
Expand All @@ -55,7 +55,7 @@ class ArgMaxOpConverter : public OpConverter {
dims.d[i] = dims.d[i + 1];
}
squeeze_layer->setReshapeDimensions(dims);
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
squeeze_layer, "arg_max", {output_name}, test_mode);
}
}
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10 changes: 5 additions & 5 deletions paddle/fluid/inference/tensorrt/convert/arg_min_op.cc
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Expand Up @@ -42,10 +42,10 @@ class ArgMinOpConverter : public OpConverter {
auto output_name = op_desc.Output("Out")[0];
bool keepdims = PADDLE_GET_CONST(bool, op_desc.GetAttr("keepdims"));
if (keepdims) {
RreplenishLayerAndOutput(topk_layer,
"arg_min",
{output_name + "_value", output_name},
test_mode);
ReplenishLayerAndOutput(topk_layer,
"arg_min",
{output_name + "_value", output_name},
test_mode);
} else {
auto squeeze_layer =
TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *topk_layer->getOutput(1));
Expand All @@ -55,7 +55,7 @@ class ArgMinOpConverter : public OpConverter {
dims.d[i] = dims.d[i + 1];
}
squeeze_layer->setReshapeDimensions(dims);
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
squeeze_layer, "arg_min", {output_name}, test_mode);
}
}
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/assign_op.cc
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Expand Up @@ -28,7 +28,7 @@ class AssignOpConverter : public OpConverter {
auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Identity, *input);
auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "assign", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "assign", {output_name}, test_mode);
}
};

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4 changes: 2 additions & 2 deletions paddle/fluid/inference/tensorrt/convert/batch_norm_op.cc
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Expand Up @@ -170,10 +170,10 @@ class BatchNormOpConverter : public OpConverter {
squeeze_layer =
TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *(layer->getOutput(0)));
squeeze_layer->setReshapeDimensions(squeeze_shape);
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
squeeze_layer, "batchnorm_add_scale", {output_name}, test_mode);
} else {
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
layer, "batchnorm_add_scale", {output_name}, test_mode);
}
}
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/bilinear_interp_v2_op.cc
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Expand Up @@ -148,7 +148,7 @@ class BilinearInterpolateV2OpConverter : public OpConverter {
layer->setScales(scales.data(), scales.size());
}

RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
layer, "bilinear_interp_v2", {output_name}, test_mode);
}
};
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/bitwise_and_op.cc
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Expand Up @@ -49,7 +49,7 @@ class BitwiseAndConverter : public OpConverter {
}

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "bitwise_and", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "bitwise_and", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/bitwise_not_op.cc
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Expand Up @@ -69,7 +69,7 @@ class BitwiseNotConverter : public OpConverter {
}

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "bitwise_not", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "bitwise_not", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/bitwise_or_op.cc
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Expand Up @@ -49,7 +49,7 @@ class BitwiseOrConverter : public OpConverter {
}

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "bitwise_or", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "bitwise_or", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/bmm_op.cc
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Expand Up @@ -38,7 +38,7 @@ class BMMOpConverter : public OpConverter {
*input2,
nvinfer1::MatrixOperation::kNONE);

RreplenishLayerAndOutput(layer, "bmm", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "bmm", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/c_allreduce_op.cc
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Expand Up @@ -84,7 +84,7 @@ class CAllReduceOpConverter : public OpConverter {
#endif
auto output_name = op_desc.Output("Out")[0];

RreplenishLayerAndOutput(layer, name, {output_name}, test_mode);
ReplenishLayerAndOutput(layer, name, {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/cast_op.cc
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Expand Up @@ -57,7 +57,7 @@ class CastOpConverter : public OpConverter {
}

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "cast", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "cast", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/celu_op.cc
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Expand Up @@ -78,7 +78,7 @@ class CeluOpConverter : public OpConverter {
nvinfer1::ElementWiseOperation::kSUM);

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "celu", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "celu", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/clip_op.cc
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Expand Up @@ -39,7 +39,7 @@ class ClipOpConverter : public OpConverter {
layer->setBeta(max);

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "clip", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "clip", {output_name}, test_mode);
#else
PADDLE_THROW(
platform::errors::Fatal("clip TRT converter is only supported on TRT "
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/concat_op.cc
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Expand Up @@ -49,7 +49,7 @@ class ConcatOpConverter : public OpConverter {
engine_, Concatenation, itensors.data(), itensors.size());
layer->setAxis(axis);
auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "concat", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "concat", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/cross_multihead_matmul_op.cc
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Expand Up @@ -265,7 +265,7 @@ class CrossMultiheadMatMulOpConverter : public OpConverter {
("shuffle_last_multihead_matmul(Output: " + output_name + ")").c_str());
// return
layer = reshape_after_mha_layer;
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
layer, "cross_multihead_matmul", {output_name}, test_mode);
}
};
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4 changes: 2 additions & 2 deletions paddle/fluid/inference/tensorrt/convert/cumsum_op.cc
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Expand Up @@ -45,7 +45,7 @@ class CumsumOpConverter : public OpConverter {
cumsum_dim.d[0] = 1;
}
layer->setReshapeDimensions(cumsum_dim);
RreplenishLayerAndOutput(layer, "cumsum", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "cumsum", {output_name}, test_mode);
} else {
int axis = 0;
if (op_desc.HasAttr("axis")) {
Expand Down Expand Up @@ -161,7 +161,7 @@ class CumsumOpConverter : public OpConverter {
nvinfer1::ILoopOutputLayer* loopOut =
loop->addLoopOutput(*curSum->getOutput(0), reverseFlag, axis);
loopOut->setInput(1, *tripLimit);
RreplenishLayerAndOutput(loopOut, "cumsum", {output_name}, test_mode);
ReplenishLayerAndOutput(loopOut, "cumsum", {output_name}, test_mode);
}
#else
VLOG(3) << "Cumsum is not supported when TensorRT < 7.2.2";
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4 changes: 2 additions & 2 deletions paddle/fluid/inference/tensorrt/convert/deformable_conv_op.cc
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Expand Up @@ -105,7 +105,7 @@ class DeformableConvOpConverter : public OpConverter {
std::vector<std::string> output_names;
output_names.push_back(op_desc.Output("Output").front());

RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
deformable_conv_layer, "deformable_conv", output_names, test_mode);
} else {
auto* deformable_conv_plugin = new plugin::DeformableConvPluginDynamic(
Expand Down Expand Up @@ -133,7 +133,7 @@ class DeformableConvOpConverter : public OpConverter {
std::vector<std::string> output_names;
output_names.push_back(op_desc.Output("Output").front());

RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
deformable_conv_layer, "deformable_conv", output_names, test_mode);
}
}
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/dequantize_linear_op.cc
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Expand Up @@ -49,7 +49,7 @@ class DequantizeLinearOpConverter : public OpConverter {
layer->setAxis(axis);
}
auto output_name = op_desc.Output("Y")[0];
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
layer, "dequantize_linear", {output_name}, test_model);
#else
PADDLE_THROW(
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4 changes: 2 additions & 2 deletions paddle/fluid/inference/tensorrt/convert/dropout_op.cc
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Expand Up @@ -43,7 +43,7 @@ class DropoutOpConverter : public OpConverter {
downgrade_in_infer == "upscale_in_train") {
auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input1);
auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "dropout", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "dropout", {output_name}, test_mode);
return;
}

Expand Down Expand Up @@ -75,7 +75,7 @@ class DropoutOpConverter : public OpConverter {
std::move(weight_tensor));
auto output_name = op_desc.Output("Out")[0];

RreplenishLayerAndOutput(layer, "dropout", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "dropout", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/einsum_op.cc
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Expand Up @@ -39,7 +39,7 @@ class EinsumOpConverter : public OpConverter {
engine_, Einsum, input_tensors.data(), input_num, equation.c_str());

auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer, "einsum", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "einsum", {output_name}, test_mode);
#else
VLOG(3) << "Einsum is not supported when TensorRT < 8.2.0";
#endif
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10 changes: 5 additions & 5 deletions paddle/fluid/inference/tensorrt/convert/elementwise_op.cc
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Expand Up @@ -162,7 +162,7 @@ class ElementwiseTensorOpConverter : public OpConverter {
*(less_layer->getOutput(0)),
*(equal_layer->getOutput(0)),
nvinfer1::ElementWiseOperation::kOR);
RreplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
} else if (op_type_ == "greater_equal") {
auto* greater_layer =
TRT_ENGINE_ADD_LAYER(engine_,
Expand All @@ -181,7 +181,7 @@ class ElementwiseTensorOpConverter : public OpConverter {
*(greater_layer->getOutput(0)),
*(equal_layer->getOutput(0)),
nvinfer1::ElementWiseOperation::kOR);
RreplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
} else if (op_type_ == "mod") {
auto* div_layer =
TRT_ENGINE_ADD_LAYER(engine_,
Expand All @@ -203,7 +203,7 @@ class ElementwiseTensorOpConverter : public OpConverter {
*(mul_layer->getOutput(0)),
nvinfer1::ElementWiseOperation::kSUB);
SupportFP32MixPrecision(output_name, op_desc.Type(), layer);
RreplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
} else {
auto op_pair = ops.find(op_type_);
PADDLE_ENFORCE_NE(
Expand All @@ -217,7 +217,7 @@ class ElementwiseTensorOpConverter : public OpConverter {
auto* layer = TRT_ENGINE_ADD_LAYER(
engine_, ElementWise, *X, *reshape_y_tensor, op_pair->second);
SupportFP32MixPrecision(output_name, op_desc.Type(), layer);
RreplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
}
}

Expand Down Expand Up @@ -350,7 +350,7 @@ class PowOpConverter : public OpConverter {
auto* layer = TRT_ENGINE_ADD_LAYER(
engine_, ElementWise, *X, *Y, nvinfer1::ElementWiseOperation::kPOW);
SupportFP32MixPrecision(output_name, op_desc.Type(), layer);
RreplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "elementwise", {output_name}, test_mode);
}
};

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8 changes: 4 additions & 4 deletions paddle/fluid/inference/tensorrt/convert/elementwiseadd_transpose_op.cc
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Expand Up @@ -40,10 +40,10 @@ class ElementwiseaddTransposeOpConverter : public OpConverter {
engine_->AddDynamicPlugin(inputs.data(), 2, plugin);
std::vector<std::string> output_names;
output_names.emplace_back(op_desc.Output("Out").front());
RreplenishLayerAndOutput(elementwise_layer,
"fuse_elementwiseadd_transpose",
output_names,
test_mode);
ReplenishLayerAndOutput(elementwise_layer,
"fuse_elementwiseadd_transpose",
output_names,
test_mode);
}
}
};
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14 changes: 7 additions & 7 deletions paddle/fluid/inference/tensorrt/convert/emb_eltwise_layernorm.cc
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Expand Up @@ -171,12 +171,12 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
} else {
layer = plugin_layer;
auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(layer,
"ManyEmbLayerNormVarlenPluginDynamicV1",
{output_name,
std::string("qkv_plugin_mask"),
std::string("max_seqlen_tensor")},
test_mode);
ReplenishLayerAndOutput(layer,
"ManyEmbLayerNormVarlenPluginDynamicV1",
{output_name,
std::string("qkv_plugin_mask"),
std::string("max_seqlen_tensor")},
test_mode);
}
} else {
for (int i = 0; i < input_num; i++) {
Expand Down Expand Up @@ -247,7 +247,7 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
}
layer = plugin_layer;
auto output_name = op_desc.Output("Out")[0];
RreplenishLayerAndOutput(
ReplenishLayerAndOutput(
layer, "ManyEmbLayerNormPluginDynamicV1", {output_name}, test_mode);
}
}
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4 changes: 2 additions & 2 deletions paddle/fluid/inference/tensorrt/convert/equal_op.cc
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Expand Up @@ -68,7 +68,7 @@ class EqualOpConverter : public OpConverter {

layer = TRT_ENGINE_ADD_LAYER(
engine_, ElementWise, *X, *Y, nvinfer1::ElementWiseOperation::kEQUAL);
RreplenishLayerAndOutput(layer, "equal", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "equal", {output_name}, test_mode);
}
};

Expand Down Expand Up @@ -125,7 +125,7 @@ class NotEqualOpConverter : public OpConverter {
layer = TRT_ENGINE_ADD_LAYER(
engine_, Unary, *layer->getOutput(0), nvinfer1::UnaryOperation::kNOT);

RreplenishLayerAndOutput(layer, "not_equal", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "not_equal", {output_name}, test_mode);
}
};

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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/expand_v2_op.cc
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Expand Up @@ -113,7 +113,7 @@ class ExpandOpConverter : public OpConverter {
layer->setInput(2, *sizes_tensor);
layer->setInput(3, *strides_tensor);

RreplenishLayerAndOutput(layer, op_type_, {output_name}, test_mode);
ReplenishLayerAndOutput(layer, op_type_, {output_name}, test_mode);
}

protected:
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/tensorrt/convert/fill_any_like_op.cc
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Expand Up @@ -77,7 +77,7 @@ class FillAnyLikeOpConverter : public OpConverter {
layer->setInput(2, *sizes_tensor);
layer->setInput(3, *strides_tensor);

RreplenishLayerAndOutput(layer, "fill_any_like", {output_name}, test_mode);
ReplenishLayerAndOutput(layer, "fill_any_like", {output_name}, test_mode);
}
};

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