Fix PReluOp weight mapping bug in CodeGen.

1. The backend of PReluOp uses stride descriptions to represent data, so we should not align with the EU number. (loc: nodechip_prelu_local.c:36) Change-Id: I18e903acaebaf35e5762c76df973d7e1e978f8f9
sophgo · Jan 9, 2023 · 93d89e3 · 93d89e3
1 parent 2ae259b
commit 93d89e3
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Showing 3 changed files with 11 additions and 11 deletions.
diff --git a/lib/Dialect/Tpu/Transforms/LayerGroup/LayerGroupUtil.cpp b/lib/Dialect/Tpu/Transforms/LayerGroup/LayerGroupUtil.cpp
@@ -492,7 +492,8 @@ bool is_eu_align(Value opd) {
   // Eu align rule may be different in different platforms
   auto op = *opd.getUsers().begin();
   if (isWeightValue(opd)) {
-    if (isa<tpu::Conv1DOp, tpu::Conv2DOp, tpu::Conv3DOp, tpu::DeconvOp>(op) &&
+    if (isa<tpu::Conv1DOp, tpu::Conv2DOp, tpu::Conv3DOp, tpu::DeconvOp,
+            tpu::PReluOp>(op) &&
         (opd == op->getOperand(1) || opd == op->getOperand(2))) {
       return false;
     }

diff --git a/python/test/test_onnx.py b/python/test/test_onnx.py
@@ -2401,14 +2401,15 @@ def test_Reciprocal(self, case_name):
         self.onnx_and_test(graph_def, input_data={"input": input_data})
 
     def test_PRelu(self, case_name):
-        input_shape = [3, 5, 100, 100]
-        slope_shape = [1, 5, 1, 1]
-        output_shape = [3, 5, 100, 100]
-        slope = helper.make_tensor(name='slope',
-                                   data_type=onnx.TensorProto.FLOAT,
-                                   dims=slope_shape,
-                                   vals=[0.40, 0.37, 0.31, 0.19, 0.11])
-
+        input_shape = [3, 128, 100, 100]
+        slope_shape = [1, 128, 1, 1]
+        output_shape = [3, 128, 100, 100]
+        slope = helper.make_tensor(
+            name="slope",
+            data_type=onnx.TensorProto.FLOAT,
+            dims=slope_shape,
+            vals=np.random.rand(*slope_shape).astype(np.float32),
+        )
         inputs = [helper.make_tensor_value_info("input", TensorProto.FLOAT, input_shape)]
         outputs = [helper.make_tensor_value_info('output', TensorProto.FLOAT, output_shape)]
         prelu_def = helper.make_node("PRelu", ["input", "slope"], ["output"])

diff --git a/python/transform/CaffeConverter.py b/python/transform/CaffeConverter.py
@@ -336,8 +336,6 @@ def convert_scale_op(self, layer):
         output_shape = input_shape
         attrs = {'name': self.get_loc(layer.top[0])}
         assert (num_dims == 4 or num_dims == 2)
-        if num_dims == 2:
-            raise RuntimeError("Not support now, shape {}".format(input_shape))
         if len(layer.bottom) == 2:
             op1 = self.getOperand(layer.bottom[1])
             input_shape1 = self.getShape(layer.bottom[1])