change var name padding_num to padding_value (#19498)

paddle/fluid/operators/ctc_align_op.cc

@@ -57,7 +57,7 @@ class CTCAlignOpMaker : public framework::OpProtoAndCheckerMaker {
                   "merge repeated elements between two blanks. ")
         .SetDefault(true);
     // add attr padding number for tensor input
-    AddAttr<int>("padding_num",
+    AddAttr<int>("padding_value",
                  "(int, default: 0), padding number "
                  "use to padding tensor. ")
         .SetDefault(0);
@@ -89,7 +89,7 @@ or Given:
 And:
     blank = 0
     merge_repeated = True
-    padding_num = 0
+    padding_value = 0
 
 Then:
     Output.data = [[1, 2, 4, 0, 0, 0],

paddle/fluid/operators/ctc_align_op.cu

@@ -46,7 +46,7 @@ template <typename T>
 __global__ void PaddingMergeAndDelCudaKernel(const int64_t num_token,
                                              const T* tokens, const int blank,
                                              const int merge_repeated,
-                                             const int padding_num,
+                                             const int padding_value,
                                              const int64_t batch_size,
                                              T* output) {
   int ind = blockIdx.x * blockDim.x + threadIdx.x;
@@ -62,7 +62,7 @@ __global__ void PaddingMergeAndDelCudaKernel(const int64_t num_token,
     prev_token = tokens[i];
   }
   for (int i = output_idx; i < ind * num_token + num_token; i++) {
-    output[i] = padding_num;
+    output[i] = padding_value;
   }
 }
 
@@ -82,13 +82,13 @@ class CTCAlignOpCUDAKernel : public framework::OpKernel<T> {
 
     // tensor input which has no lod
     if (input->lod().empty()) {
-      const int padding_num = ctx.Attr<int>("padding_num");
+      const int padding_value = ctx.Attr<int>("padding_value");
       auto input_dims = input->dims();
       T* output_data = output->mutable_data<T>({input_dims[0], input_dims[1]},
                                                ctx.GetPlace());
       PaddingMergeAndDelCudaKernel<
           T><<<32, (input_dims[0] + 32 - 1) / 32, 0, stream>>>(
-          input_dims[1], tokens, blank, merge_repeated, padding_num,
+          input_dims[1], tokens, blank, merge_repeated, padding_value,
           input_dims[0], output_data);
     } else {
       const size_t level = 0;

paddle/fluid/operators/ctc_align_op.h

@@ -39,7 +39,8 @@ class CTCAlignKernel : public framework::OpKernel<T> {
 
     // support tensor input, no lod information
     if (input->lod().empty()) {
-      size_t padding_num = static_cast<size_t>(ctx.Attr<int>("padding_num"));
+      size_t padding_value =
+          static_cast<size_t>(ctx.Attr<int>("padding_value"));
       for (size_t batch_id = 0; batch_id < (unsigned)input_dims[0];
            batch_id++) {
         T prev_token = -1;
@@ -55,7 +56,7 @@ class CTCAlignKernel : public framework::OpKernel<T> {
           prev_token = input_data[input_ind];
         }
         for (size_t j = output_idx; j < (unsigned)input_dims[1]; j++)
-          output_data[batch_id * input_dims[1] + j] = padding_num;
+          output_data[batch_id * input_dims[1] + j] = padding_value;
       }
     } else {
       const size_t level = 0;

python/paddle/fluid/tests/unittests/test_ctc_align.py

@@ -109,7 +109,7 @@ class TestCTCAlignPaddingOp(OpTest):
         self.op_type = "ctc_align"
         self.input_lod = []
         self.blank = 0
-        self.padding_num = 0
+        self.padding_value = 0
         self.merge_repeated = True
         self.input = np.array([[0, 2, 4, 4, 0, 6, 3, 6, 6, 0, 0],
                                [1, 1, 3, 0, 0, 4, 5, 6, 0, 0, 0]]).reshape(
@@ -118,13 +118,13 @@ class TestCTCAlignPaddingOp(OpTest):
     def setUp(self):
         self.config()
         output = CTCAlign(self.input, self.input_lod, self.blank,
-                          self.merge_repeated, self.padding_num)
+                          self.merge_repeated, self.padding_value)
         self.inputs = {"Input": (self.input, self.input_lod), }
         self.outputs = {"Output": output}
         self.attrs = {
             "blank": self.blank,
             "merge_repeated": self.merge_repeated,
-            "padding_num": self.padding_num
+            "padding_value": self.padding_value
         }
 
     def test_check_output(self):
@@ -138,7 +138,7 @@ class TestCTCAlignOpCase3(TestCTCAlignPaddingOp):
         self.blank = 0
         self.input_lod = []
         self.merge_repeated = True
-        self.padding_num = 0
+        self.padding_value = 0
         self.input = np.array([[0, 1, 2, 2, 0, 4], [0, 4, 5, 0, 6, 0],
                                [0, 7, 7, 7, 0, 0]]).reshape(
                                    [3, 6]).astype("int32")
@@ -146,7 +146,7 @@ class TestCTCAlignOpCase3(TestCTCAlignPaddingOp):
 
 class TestCTCAlignOpCase4(TestCTCAlignPaddingOp):
     '''
-    # test tensor input which has attr input padding_num
+    # test tensor input which has attr input padding_value
     '''
 
     def config(self):
@@ -154,7 +154,7 @@ class TestCTCAlignOpCase4(TestCTCAlignPaddingOp):
         self.blank = 0
         self.input_lod = []
         self.merge_repeated = False
-        self.padding_num = 0
+        self.padding_value = 0
         self.input = np.array([[0, 1, 2, 2, 0, 4], [0, 4, 5, 0, 6, 0],
                                [0, 7, 7, 7, 0, 0]]).reshape(
                                    [3, 6]).astype("int32")
@@ -166,7 +166,7 @@ class TestCTCAlignOpCase5(TestCTCAlignPaddingOp):
         self.blank = 0
         self.input_lod = []
         self.merge_repeated = False
-        self.padding_num = 1
+        self.padding_value = 1
         self.input = np.array([[0, 1, 2, 2, 0, 4], [0, 4, 5, 0, 6, 0],
                                [0, 7, 1, 7, 0, 0]]).reshape(
                                    [3, 6]).astype("int32")