fix(mgb): make error infomation of input channel mismatch more readable

GitOrigin-RevId: 6f95260070

dnn/src/common/convolution.cpp

@@ -573,8 +573,15 @@ void ConvolutionBase<Parameter>::check_or_deduce_dtype_fwd(
                 filter.param<dtype::QuantizedS8>().scale));
     } else {
         megdnn_throw(ssprintf(
-                "unsupported input / filter DType: %s x %s", src.name(),
-                filter.name()));
+                "runtime does not support input / filter DType: %s x %s"
+                "now support case list: FLOAT x FLOAT\n"
+                "                       Int8 x Int8\n"
+                "                       QuantizedS8 x QuantizedS8\n"
+                "                       Quantized8Asymm x Quantized8Asymm\n"
+                "                       QuantizedS4 x QuantizedS4\n"
+                "                       Quantized4Asymm x Quantized4Asymm\n"
+                "                       QuantizedS1 x QuantizedS1\n",
+                src.name(), filter.name()));
     }
     if (!dst.valid()) {
         dst = supported_dst_dtype.at(0);
@@ -588,8 +595,21 @@ void ConvolutionBase<Parameter>::check_or_deduce_dtype_fwd(
         }
         MEGDNN_MARK_USED_VAR(dst_supported);
         megdnn_assert(
-                dst_supported, "unsupported Conv(%s, %s) -> %s", src.name(),
-                filter.name(), dst.name());
+                dst_supported,
+                "runtime does not support Conv(%s, %s) -> %s"
+                "now support case list: Conv(FLOAT x FLOAT) -> FLOAT\n"
+                "                       Conv(Int8 x Int8) -> Int32\n"
+                "                       Conv(QuantizedS8 x QuantizedS8) -> "
+                "QuantizedS32\n"
+                "                       Conv(Quantized8Asymm x Quantized8Asymm) -> "
+                "Quantized32Asymm\n"
+                "                       Conv(QuantizedS4 x QuantizedS4) -> "
+                "QuantizedS32\n"
+                "                       Conv(Quantized4Asymm x Quantized4Asymm) -> "
+                "Quantized32Asymm\n"
+                "                       Conv(QuantizedS1 x QuantizedS1) -> "
+                "QuantizedS32\n",
+                src.name(), filter.name(), dst.name());
     }
     megdnn_assert(
             (param().compute_mode == Param::ComputeMode::FLOAT32 ||
@@ -1098,15 +1118,26 @@ void ConvolutionBackwardData::deduce_dtype(DType filter, DType diff, DType& grad
         }
     } else {
         megdnn_throw(ssprintf(
-                "unsupported input / diff DType: %s x %s", filter.name(), diff.name()));
+                "runtime does not support input / diff DType: %s x %s"
+                "now support case list: FLOAT x FLOAT\n"
+                "                       Int8 x Int8\n"
+                "                       QuantizedS8 x QuantizedS8\n"
+                "                       Quantized8Asymm x Quantized8Asymm\n",
+                filter.name(), diff.name()));
     }
     if (!grad.valid()) {
         grad = supported_dst_dtype.at(0);
     } else {
         megdnn_assert(
                 vec_contains(supported_dst_dtype, grad),
-                "unsupported ConvBwd(%s, %s) -> %s", filter.name(), diff.name(),
-                grad.name());
+                "runtime does not support ConvBwd(%s, %s) -> %s"
+                "now support case list: ConvBwd(FLOAT x FLOAT) -> FLOAT\n"
+                "                       ConvBwd(Int8 x Int8) -> Int32\n"
+                "                       ConvBwd(QuantizedS8 x QuantizedS8) -> "
+                "QuantizedS32\n"
+                "                       ConvBwd(Quantized8Asymm x Quantized8Asymm) -> "
+                "Quantized32Asymm\n",
+                filter.name(), diff.name(), grad.name());
     }
     megdnn_assert(
             param().compute_mode != Param::ComputeMode::FLOAT32

imperative/src/impl/ops/convolution.cpp

@@ -95,8 +95,11 @@ TensorLayout do_shape_infer(
         dilated_spatial[i] =
                 (filter[i + flt_start + flt_spatial_start] - 1) * dilation[i] + 1;
     }
-    mgb_assert(icpg * group == src[src_or_dst_c_pos], "group conv invalid");
-
+    mgb_assert(
+            icpg * group == src[src_or_dst_c_pos],
+            "group conv invalid: input channel of Conv expect %zu, but got %zu\n"
+            "hint: weight may be changed by mistake\n",
+            icpg * group, src[src_or_dst_c_pos]);
     TensorLayout dst{src.dtype};
     dst.ndim = src_ndim;
     dst[0] = src[0];
@@ -310,8 +313,11 @@ TensorLayout convbwd_do_shape_infer(
         dilated_spatial[i] =
                 (filter[i + flt_start + flt_spatial_start] - 1) * dilation[i] + 1;
     }
-    mgb_assert(ocpg * group == diff[src_or_dst_c_pos], "group conv invalid");
-
+    mgb_assert(
+            ocpg * group == diff[src_or_dst_c_pos],
+            "group conv invalid: input channel of Conv expect %zu, but got %zu\n"
+            "hint: weight may be changed by mistake\n",
+            ocpg * group, diff[src_or_dst_c_pos]);
     auto deduce = [](size_t out, size_t filter, size_t stride, size_t pad) {
         auto i = (out - 1) * stride + filter;
         mgb_assert(i > pad * 2);
@@ -479,8 +485,11 @@ TensorLayout do_shape_infer(
         dilated_spatial[i] =
                 (filter[i + flt_start + flt_spatial_start] - 1) * dilation[i] + 1;
     }
-    mgb_assert(icpg * group == src[src_or_dst_c_pos], "group conv invalid");
-
+    mgb_assert(
+            icpg * group == src[src_or_dst_c_pos],
+            "group conv invalid: input channel of Conv expect %zu, but got %zu\n"
+            "hint: weight may be changed by mistake\n",
+            icpg * group, src[src_or_dst_c_pos]);
     TensorLayout dst{src.dtype};
     dst.ndim = src_ndim;
     dst[0] = src[0];