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@ -264,31 +264,31 @@ class ReduceOp : public framework::OperatorWithKernel {
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of ReduceOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of ReduceOp should not be null.");
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "ReduceOp");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "ReduceOp");
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auto x_dims = ctx->GetInputDim("X");
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auto x_rank = x_dims.size();
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PADDLE_ENFORCE_LE(x_rank, 6,
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"ShapeError: The input tensor X's dimensions of Reduce "
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"should be less equal than 6. But received X's "
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"dimensions = %d, X's shape = [%s].",
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x_rank, x_dims);
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platform::errors::InvalidArgument(
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"The input tensor X's dimensions of ReduceOp "
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"should be less equal than 6. But received X's "
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"dimensions = %d, X's shape = [%s].",
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x_rank, x_dims));
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auto dims = ctx->Attrs().Get<std::vector<int>>("dim");
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PADDLE_ENFORCE_GT(
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dims.size(), 0,
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"ShapeError: The input dim dimensions of Reduce "
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"should be greater than 0. But received the dim dimesions of Reduce "
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" = %d",
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dims.size());
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PADDLE_ENFORCE_GT(dims.size(), 0,
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platform::errors::InvalidArgument(
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"The input dim dimensions of ReduceOp "
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"should be greater than 0. But received the dim "
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"dimesions of Reduce = %d.",
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dims.size()));
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for (size_t i = 0; i < dims.size(); ++i) {
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PADDLE_ENFORCE_LT(dims[i], x_rank,
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"ShapeError: The reduce dim index %d should be in the "
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"range [-dimension(X), dimension(X)]."
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"which dimesion = %d, But received dim index = %d",
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i, x_rank, dims[i]);
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platform::errors::InvalidArgument(
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"The reduce dim index %d should be in the "
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"range [-dimension(X), dimension(X)] "
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"which dimesion = %d. But received dim index = %d.",
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i, x_rank, dims[i]));
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if (dims[i] < 0) dims[i] = x_rank + dims[i];
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}
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sort(dims.begin(), dims.end());
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@ -346,19 +346,24 @@ class ReduceGradOp : public framework::OperatorWithKernel {
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null.");
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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"Input(Out@GRAD) should not be null.");
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "ReduceOp");
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OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
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"Out@GRAD", "ReduceOp");
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auto x_dims = ctx->GetInputDim("X");
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auto x_rank = x_dims.size();
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PADDLE_ENFORCE_LE(x_rank, 6, "Tensors with rank at most 6 are supported.");
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PADDLE_ENFORCE_LE(x_rank, 6,
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platform::errors::InvalidArgument(
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"Tensors with rank at most 6 are supported by "
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"ReduceOp. Received tensor with rank %d.",
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x_rank));
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auto dims = ctx->Attrs().Get<std::vector<int>>("dim");
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for (size_t i = 0; i < dims.size(); ++i) {
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PADDLE_ENFORCE_LT(dims[i], x_rank,
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"ShapeError: The reduce dim index %d should be in the "
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"range [-dimension(X), dimension(X)]."
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"which dimesion = %d, But received dim index = %d",
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i, x_rank, dims[i]);
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platform::errors::InvalidArgument(
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"The reduce dim index %d should be in the "
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"range [-dimension(X), dimension(X)], "
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"which dimesion = %d. But received dim index = %d.",
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i, x_rank, dims[i]));
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if (dims[i] < 0) dims[i] = x_rank + dims[i];
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}
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sort(dims.begin(), dims.end());
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Zhong Hui
5 years ago
committed by
GitHub