未验证 提交 6885d156 编写于 作者: G gongweibao 提交者: GitHub

fix errorenhancement test=release/1.8 (#24471)

上级 fc43909e
......@@ -57,7 +57,13 @@ class PrefetchOp : public framework::OperatorBase {
}
}
for (size_t i = 0; i < rets.size(); i++) {
PADDLE_ENFORCE(rets[i]->Wait(), "internal error in RPCClient");
PADDLE_ENFORCE_EQ(
rets[i]->Wait(), true,
platform::errors::Fatal(
"It's a fatal error of RPCClient that RPCClient can't "
"get the wait result. It may happen when trainers or "
"parameter servers exit un normally or the network "
"issue!"));
}
}
};
......
......@@ -24,34 +24,42 @@ class ProximalAdagradOp : public framework::OperatorWithKernel {
protected:
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Param"),
"Input(Param) of ProximalAdagradOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Moment"),
"Input(Moment) of ProximalAdagradOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Grad"),
"Input(Grad) of ProximalAdagradOp should not be null.");
PADDLE_ENFORCE(
ctx->HasInput("LearningRate"),
"Input(LearningRate) of ProximalAdagradOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
"Output(ParamOut) of ProximalAdagradOp should not be null.");
PADDLE_ENFORCE(
ctx->HasOutput("MomentOut"),
"Output(MomentOut) of ProximalAdagradOp should not be null.");
OP_INOUT_CHECK(ctx->HasInput("Param"), "Input", "Param",
"ProximalAdagradOp");
OP_INOUT_CHECK(ctx->HasInput("Moment"), "Input", "Moment",
"ProximalAdagradOp");
OP_INOUT_CHECK(ctx->HasInput("Grad"), "Input", "Grad", "ProximalAdagradOp");
OP_INOUT_CHECK(ctx->HasInput("LearningRate"), "Input", "LearningRate",
"ProximalAdagradOp");
OP_INOUT_CHECK(ctx->HasOutput("ParamOut"), "Output", "ParamOut",
"ProximalAdagradOp");
OP_INOUT_CHECK(ctx->HasOutput("MomentOut"), "Output", "MomentOut",
"ProximalAdagradOp");
auto param_dim = ctx->GetInputDim("Param");
PADDLE_ENFORCE_EQ(
param_dim, ctx->GetInputDim("Grad"),
"Param and Grad of ProximalAdagrad Op must have same dimension.");
PADDLE_ENFORCE_EQ(
param_dim, ctx->GetInputDim("Moment"),
"Param and Moment of ProximalAdagrad Op must have same dimension.");
PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Grad"),
platform::errors::InvalidArgument(
"The shape of Intput(Param) should be equal to the "
"Input(Grad) of ProximalAdagrad Op. But received "
"Input(Param).dimensions=[%s], "
"Input(Grad).dimensions=[%s]",
param_dim, ctx->GetInputDim("Grad")));
PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Moment"),
platform::errors::InvalidArgument(
"The shape of Intput(Param) should be equal to the "
"Input(Moment) of ProximalAdagrad Op. But received "
"Input(Param).dimensions=[%s], "
"Input(Moment).dimensions=[%s]",
param_dim, ctx->GetInputDim("Moment")));
auto lr_dim = ctx->GetInputDim("LearningRate");
PADDLE_ENFORCE_EQ(framework::product(lr_dim), 1,
"Learning Rate should be a scalar.");
PADDLE_ENFORCE_EQ(
framework::product(lr_dim), 1,
platform::errors::InvalidArgument(
"Learning Rate should be a scalar. But received dimension[%s]",
lr_dim));
ctx->SetOutputDim("ParamOut", param_dim);
ctx->SetOutputDim("MomentOut", param_dim);
......
......@@ -24,23 +24,29 @@ class ProximalGDOp : public framework::OperatorWithKernel {
protected:
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Param"),
"Input(Param) of ProximalGDOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Grad"),
"Input(Grad) of ProximalGDOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("LearningRate"),
"Input(LearningRate) of ProximalGDOp should not be null.");
OP_INOUT_CHECK(ctx->HasInput("Param"), "Input", "Param", "ProximalGDOp");
OP_INOUT_CHECK(ctx->HasInput("Grad"), "Input", "Grad", "ProximalGDOp");
OP_INOUT_CHECK(ctx->HasInput("LearningRate"), "Input", "LearningRate",
"ProximalGDOp");
PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
"Output(ParamOut) of ProximalGDOp should not be null.");
OP_INOUT_CHECK(ctx->HasOutput("ParamOut"), "Output", "Paramout",
"ProximalGDOp");
auto param_dim = ctx->GetInputDim("Param");
PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Grad"),
"Two input of ProximalGD Op's dimension must be same.");
platform::errors::InvalidArgument(
"The shape of Intput(Param) should be equal to the "
"Input(Grad) of ProximalGD Op. But received "
"Input(Param).dimensions=[%s], "
"Input(Grad).dimensions=[%s]",
param_dim, ctx->GetInputDim("Grad")));
auto lr_dim = ctx->GetInputDim("LearningRate");
PADDLE_ENFORCE_EQ(framework::product(lr_dim), 1,
"Learning Rate should be a scalar.");
PADDLE_ENFORCE_EQ(
framework::product(lr_dim), 1,
platform::errors::InvalidArgument(
"Learning Rate should be a scalar. But received dimmensions:[%s]",
lr_dim));
ctx->SetOutputDim("ParamOut", param_dim);
}
......
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