modified error message and API doc for channel_last supported Op (#21002)

* modified error message for conv and conv_transpose, test=develop

* modified doc of conv and conv_transpose op, test=develop

* modified the expression for error message, test=develop

* modified error message for group_norm op, test=develop

* modified detail of Attr(data_format) or Attr(data_layout)

* add ValueError in API doc for maxout op, test=develop

paddle/fluid/operators/conv_op.cc

@@ -50,30 +50,28 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
   const std::string data_format = ctx->Attrs().Get<std::string>("data_format");
   const bool channel_last = (data_format == "NHWC" || data_format == "NDHWC");
 
-  PADDLE_ENFORCE_EQ(in_dims.size() == 4 || in_dims.size() == 5, true,
-                    "ShapeError: Conv input should be 4-D or 5-D tensor. But "
-                    "received: %u-D Tensor,"
-                    "the shape of Conv input is [%s]",
-                    in_dims.size(), in_dims);
+  PADDLE_ENFORCE_EQ(
+      in_dims.size() == 4 || in_dims.size() == 5, true,
+      "ShapeError: the input of Op(conv) should be 4-D or 5-D Tensor. But "
+      "received: %u-D Tensor, the shape of input is [%s].",
+      in_dims.size(), in_dims);
 
   PADDLE_ENFORCE_EQ(
       in_dims.size(), filter_dims.size(),
-      "ShapeError: Conv input dimension and filter dimension should be the "
-      "equal."
-      "But received: the shape of Conv input is [%s], input dimension of Conv "
-      "input is [%d],"
-      "the shape of filter is [%s],  the filter dimension of Conv is [%d]",
+      "ShapeError: the input's dimension size and filter's dimension size of "
+      "Op(conv) should be equal. But received: the shape of input is [%s], "
+      "the dimension size of input is [%d], the shape of filter is [%s],  "
+      "the dimension size of filter is [%d].",
       in_dims, in_dims.size(), filter_dims, filter_dims.size());
 
   int in_sub_stride_size = in_dims.size() - strides.size();
   PADDLE_ENFORCE_EQ(in_dims.size() - strides.size() == 2U, true,
-                    "ShapeError: the dimension of input minus the dimension of "
-                    "stride must be euqal to 2."
-                    "But received: the dimension of input minus the dimension "
-                    "of stride is [%d], the"
-                    "input dimension of Conv is [%d], the shape of Conv input "
-                    "is [%s], the stride"
-                    "dimension of Conv is [%d]",
+                    "ShapeError: the dimension size of input minus the size of "
+                    "Attr(stride) must be euqal to 2 for Op(conv)."
+                    "But received: the dimension size of input minus the size "
+                    "of Attr(stride) is [%d], the "
+                    "input's dimension size is [%d], the shape of input "
+                    "is [%s], the Attr(stride)'s size is [%d].",
                     in_sub_stride_size, in_dims.size(), in_dims,
                     strides.size());
 
@@ -83,16 +81,19 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
   PADDLE_ENFORCE_EQ(
       input_channels, filter_dims[1] * groups,
       "ShapeError: The number of input channels should be equal to filter "
-      "channels * groups. But received: the input channels is [%d], the shape"
-      "of input is [%s], the filter channel is [%d], the shape of filter is "
-      "[%s],"
-      "the groups is [%d]",
-      in_dims[1], in_dims, filter_dims[1], filter_dims, groups);
+      "channels * groups for Op(conv). But received: the input's channels is "
+      "[%d], the shape "
+      "of input is [%s], the filter's channel is [%d], the shape of filter is "
+      "[%s], the groups is [%d], the data_format is %s. The error may come "
+      "from wrong data_format setting.",
+      input_channels, in_dims, filter_dims[1], filter_dims, groups,
+      data_format);
   PADDLE_ENFORCE_EQ(
       filter_dims[0] % groups, 0,
-      "ShapeError: The number of output channels should be divided by groups."
-      "But received: the output channels is [%d], the shape of filter is [%s]"
-      "(the first dimension of filter is output channel), the groups is [%d]",
+      "ShapeError: The number of output channels of Op(conv) should be divided "
+      "by groups. "
+      "But received: the output channels is [%d], the shape of filter is [%s] "
+      "(the first dimension of filter is output channel), the groups is [%d].",
       filter_dims[0], filter_dims, groups);
 
   framework::DDim in_data_dims;

paddle/fluid/operators/conv_transpose_op.cc

@@ -46,30 +46,48 @@ void ConvTransposeOp::InferShape(framework::InferShapeContext* ctx) const {
   int groups = ctx->Attrs().Get<int>("groups");
   std::string padding_algorithm =
       ctx->Attrs().Get<std::string>("padding_algorithm");
-  const DataLayout data_layout = framework::StringToDataLayout(
-      ctx->Attrs().Get<std::string>("data_format"));
+  const std::string data_layout_str =
+      ctx->Attrs().Get<std::string>("data_format");
+  const framework::DataLayout data_layout =
+      framework::StringToDataLayout(data_layout_str);
 
   PADDLE_ENFORCE_EQ(in_dims.size() == 4 || in_dims.size() == 5, true,
-                    "ConvTransposeOp intput should be 4-D or 5-D tensor.");
-  PADDLE_ENFORCE_EQ(in_dims.size(), filter_dims.size(),
-                    "ConvTransposeOp input dimension and filter dimension "
-                    "should be the same.");
+                    "ShapeError: input of Op(conv_transpose) should be 4-D or "
+                    "5-D Tensor. But received: %u-D Tensor, "
+                    "the shape of input is [%s]",
+                    in_dims.size(), in_dims);
+  PADDLE_ENFORCE_EQ(
+      in_dims.size(), filter_dims.size(),
+      "ShapeError: the input's dimension size and filter's dimension size of "
+      "Op (conv_transpose) should be equal. But received: the shape of input "
+      "is [%s], the dimension size of input is [%d], the shape of filter is "
+      "[%s],  the dimension size of filter is [%d]. ",
+      in_dims, in_dims.size(), filter_dims, filter_dims.size());
+  int in_sub_stride_size = in_dims.size() - strides.size();
   PADDLE_ENFORCE_EQ(
       in_dims.size() - strides.size(), 2U,
-      "ConvTransposeOp input dimension and strides dimension should "
-      "be consistent.");
+      "ShapeError: the input's dimension size minus Attr(stride)'s size must "
+      "be euqal to 2 for Op(conv_transpose). But received: [%d], the "
+      "input's dimension size is [%d], the shape of input "
+      "is [%s], the Attr(stride)'s size is [%d].",
+      in_sub_stride_size, in_dims.size(), in_dims, strides.size());
   if (output_size.size())
-    PADDLE_ENFORCE_EQ(output_size.size(), strides.size(),
-                      "ConvTransposeOp output_size dimension and strides "
-                      "dimension should be the same.");
+    PADDLE_ENFORCE_EQ(
+        output_size.size(), strides.size(),
+        "The Attr(output_size) and Attr(stride) of Op(conv_transpose) "
+        "should be the same.");
 
   const int64_t C =
       (data_layout != DataLayout::kNHWC ? in_dims[1]
                                         : in_dims[in_dims.size() - 1]);
   PADDLE_ENFORCE_EQ(
       C, filter_dims[0],
-      "The number of input channels of Op(ConvTransposeOp) should "
-      "be equal to the number of filter's channels.");
+      "ShapeError: The number of input channels should be equal to filter "
+      "channels for Op(conv_transpose). But received: the input's channels is "
+      "[%d], the shape of input is [%s], the filter's channels is [%d], the "
+      "shape of filter is [%s]. The data_format is %s."
+      "The error may come from wrong data_format setting.",
+      C, in_dims, filter_dims[0], filter_dims, data_layout_str);
 
   framework::DDim in_data_dims;
   if (data_layout != DataLayout::kNHWC) {

paddle/fluid/operators/group_norm_op.cc

@@ -39,24 +39,57 @@ class GroupNormOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE(ctx->HasOutput("Variance"),
                    "Output(Variance) of GroupNormOp should not be null.");
     auto x_dim = ctx->GetInputDim("X");
-    const DataLayout data_layout = framework::StringToDataLayout(
-        ctx->Attrs().Get<std::string>("data_layout"));
+    const std::string data_layout_str =
+        ctx->Attrs().Get<std::string>("data_layout");
+    const framework::DataLayout data_layout =
+        framework::StringToDataLayout(data_layout_str);
     const int64_t channel_num =
         (data_layout == DataLayout::kNCHW ? x_dim[1] : x_dim[x_dim.size() - 1]);
     auto batch_size = x_dim[0];
     auto groups = ctx->Attrs().Get<int>("groups");
     PADDLE_ENFORCE_LE(
         groups, channel_num,
-        "'groups' must be less equal than the number of channels.");
-    PADDLE_ENFORCE_GE(groups, 1, "'groups' must be greater equal than 1.");
+        "ValueError: the Attr(groups) of Op(group_norm) must be less than or "
+        "equal to the number of channels. "
+        "But received: groups is [%s], channels is [%s], the Attr(data_layout) "
+        "is [%s]. The error may come from wrong data_layout setting.",
+        groups, channel_num, data_layout_str);
+    PADDLE_ENFORCE_GE(
+        groups, 1,
+        "ValueError: the Attr(groups) of Op(group_norm) must be "
+        "greater than or equal to 1. But received: groups is [%s].",
+        groups);
 
     if (ctx->HasInput("Scale")) {
-      PADDLE_ENFORCE_EQ(ctx->GetInputDim("Scale").size(), 1UL);
-      PADDLE_ENFORCE_EQ(ctx->GetInputDim("Scale")[0], channel_num);
+      PADDLE_ENFORCE_EQ(
+          ctx->GetInputDim("Scale").size(), 1UL,
+          "ShapeError: the Input(Scale) of Op(group_norm) should be 1-D "
+          "Tensor. "
+          "But received: %u-D Tensor, the shape of Input(Scale) is [%s].",
+          ctx->GetInputDim("Scale").size(), ctx->GetInputDim("Scale"));
+      PADDLE_ENFORCE_EQ(
+          ctx->GetInputDim("Scale")[0], channel_num,
+          "ShapeError: the Input(Scale)'s first dimension size of "
+          "Op(group_norm) must be equal to the number of channels. "
+          "But received: the Input(Scale)'s first dimension size is [%s], the "
+          "channels is [%s], the Attr(data_layout) is [%s]. The error may come "
+          "from wrong data_layout setting.",
+          ctx->GetInputDim("Scale")[0], channel_num, data_layout_str);
     }
     if (ctx->HasInput("Bias")) {
-      PADDLE_ENFORCE_EQ(ctx->GetInputDim("Bias").size(), 1UL);
-      PADDLE_ENFORCE_EQ(ctx->GetInputDim("Bias")[0], channel_num);
+      PADDLE_ENFORCE_EQ(
+          ctx->GetInputDim("Bias").size(), 1UL,
+          "ShapeError: the Input(Bias) of Op(group_norm) should be 1-D Tensor. "
+          "But received: %u-D Tensor, the shape of Input(Bias) is [%s].",
+          ctx->GetInputDim("Bias").size(), ctx->GetInputDim("Bias"));
+      PADDLE_ENFORCE_EQ(
+          ctx->GetInputDim("Bias")[0], channel_num,
+          "ShapeError: the Input(Bias)'s first dimension size of "
+          "Op(group_norm) must be equal to the number of channels. "
+          "But received: the Input(Bias)'s first dimension size is [%s], the "
+          "channels is [%s], the Attr(data_layout) is [%s]. The error may come "
+          "from wrong data_layout setting.",
+          ctx->GetInputDim("Bias")[0], channel_num, data_layout_str);
     }
 
     ctx->SetOutputDim("Y", ctx->GetInputDim("X"));